For additional learning, sign up for a free online course or visit www.gfi.org. New series will be posted throughout 2019-2020.
Do you work for a company in this space or have relevant experience on a certain topic and disagree with any of the information presented? Shoot me an e-mail at email@example.com for comments.
Cell-Based Meat Science Series I: Cell Lines
Cell-based meat is a term for the technology currently being developed which allows for animal stem cells to be grown into consumable meat products without animal slaughter. It is also sometimes referred to as clean meat as a nod to clean energy and cleaner processing, which we will discuss later in Series V, as well as cultured or lab-grown meat. There are now over 40 companies spread across the globe that are working on making cell-based meat products that are as tasty and affordable as conventional animal meats. However, in order to achieve success, we need a dramatic influx of scientists from a variety of disciplines such as cell and molecular biology, tissue engineering, and chemical engineering to catalyze these industries. In this series, we will review the core scientific areas involved in cell-based meat production, aiming to provide an in-depth look at how the technology is being developed, the scientific hurdles to overcome to achieve success, and its potential to shape the future of food.
The series will be broken down as follows:
Series I: Cell Lines
Series V: Final products and regulatory considerations
Series VI: Impact (environment, human health, food security, animal welfare)
The cell lines used in cell-based meat production ultimately determine many of the downstream variables to consider. As starting material, cells that can self-renew and differentiate into the cell types that make up meat tissue (i.e. myofibers, adipocytes, fibroblasts, chondrocytes, endothelial cells, etc) are most attractive. In other words, we need to begin with a stem cell. There are several different possibilities for the starting stem cell population, delineated by their potency, or ability to differentiate into a diversity of cell types (Figure 1). For instance, embryonic stem cells have the ability to differentiate into cells of all three developmental germ layers (i.e. ectoderm, mesoderm, and endoderm), while adult stem cell populations found throughout our body are typically more specialized and limited to creating cells of the same germ layer or organ type. The most likely starting cell types for use in cell-based meat production are outlined in Table 1 and discussed below.
While not discussed throughout, it is also possible to use primary cell lines from specific organs or tissues for the generation of other consumable products such as foie gras derived from hepatocytes, or other organ tissues which are more commonly eaten outside of the Western world such as fish maw (swim bladder).
Pluripotent Stem Cells
In order to use embryonic stem cells as a source for cell-based meat production, one must first have access to an embryonic stem cell line. Embryonic stem cells are derived from the inner cell mass of an early embryonic structure called a blastocyst, which forms just a few days post-fertilization (Figure 2). The first embryonic stem cell lines were derived from mice in 1981 and were followed thereafter by a select few additional species including human, non-human primates, rat, chicken, and fish. However, derivation of stable embryonic stem cell lines is extremely challenging, as the embryonic material is difficult to obtain and work with, the cells are highly sensitive to their growth substrate, and they require different sets of growth factors or inhibitors from species to species to maintain proliferation without spontaneous differentiation. Indeed, the derivation of embryonic stem cell lines from agriculturally-relevant bovine species was only recently achieved in 2018 (Bogliotti et al. 2018). Therefore, if cell-based meat is to be available for every commonly-eaten animal species, there exists significant work in the establishment of bonafide embryonic stem cell lines from a diverse set of species.
As an alternative, scientists can utilize a technology called cellular reprogramming (Figure 3) to obtain induced pluripotent stem cells (iPSCs) that maintain the desirable properties of embryonic stem cells without being derived from an embryo. Cellular reprogramming enables the direct conversion of one cell type into any other cell type based on the expression of a defined set of important genes of the final cell type (Rackham et al. 2016) , typically a set of transcription factors. Reprogramming is classically performed via viral-mediated overexpression of transcription factors, either via permanent genome integration (e.g. via Lentivirus) or stochastic non-integrating expression (e.g. via Sendai Virus (Fujie et al. 2014)) based on the virus type. However, reprogramming can also be achieved by additional non-integrating methods such as episomal or mRNA gene delivery (Schlaeger et al. 2015) , proteins (Cho et al. 2010), or small molecules (Zhang et al. 2012). The generation of iPSCs can be performed from virtually any adult somatic cell, including easily obtained cells such as white blood cells or skin fibroblasts, by overexpressing the canonical set of transcription factor genes Oct4, Klf4, c-Myc, and Sox2, referred to as Yamanaka factors (Takahashi and Yamanaka 2006). Because these genes are highly conserved, iPSCs have been generated from virtually all agriculturally-relevant species, although examples of fish iPSC or other marine species derivation are sparse (Rosselló et al. 2013). Thus, iPSCs are easier to derive than embryonic stem cells while being generally equivalent in their functionality (Choi et al. 2015).
The use of reprogramming technically permits other starting cell types (e.g. fibroblasts) to be directly converted (i.e. transdifferentiated) into muscle (Ito et al. 2017), fat (Wu, Jin, and Gao 2017), or other cell types, bypassing the iPSC state altogether. Transdifferentiation strategies are somewhat limited in that their conversion efficiencies are variable and incomplete, and they result in a post-mitotic population that undergoes limited expansion (Prasad et al. 2017). Given that the production of cell-based meat will require excessively large numbers of cells (discussed in Series II), proliferation would have to occur prior to transdifferentiation and all non-converted cells would be wasted, impacting the overall efficiency of the bioprocess. Nevertheless, these reprogramming technologies may be pursued using non-integrating methods in order to avoid potential regulatory issues (discussed in Series IV) with transgenes.
Adult Stem Cells
Many tissues in the adult body contain a reservoir of stem cells needed to replenish cell populations due to injury, cell death, or normal cellular turnover. These are referred to as adult stem cells. One of the most studied adult stem cell types is the mesenchymal stem cell (MSC), sometimes also referred to as mesenchymal stromal cells (Figure 4). MSCs are most commonly obtained from purified cell populations originating from a bone marrow or adipose tissue biopsy, although other sources such as the placenta, dental pulp, or umbilical cord have also been cited. Indeed, the diverse set of tissue sources and resultant cell phenotypes has called into question how MSCs should be defined and whether they are stem cells at all (Sipp, Robey, and Turner 2018). While guidelines from the International Society for Cellular Therapy (Dominici et al. 2006) have aimed to better define MSCs, some criteria such as cell surface marker expression may not be applicable in species outside of humans and thus will need to be defined. Additionally, MSCs are typically defined in part by their ability to form osteoblasts, adipocytes, and chondrocytes, while MSC potency toward skeletal muscle cells is somewhat limited and can be dependent on tissue source. In general, the multipotent nature of MSCs can be harnessed by culturing cells in specific cell culture medium formulations in order to bias their differentiation pathways (discussed further in Series IV). Thus, MSCs can serve as a readily attainable source of starting cells capable of making the principal cellular components of meat.
The resident stem cell populations in adult skeletal muscle tissue are referred to as myosatellite or satellite cells (Figure 5). Satellite cells lie alongside myofibers under the basal lamina of the muscle tissue where they remain quiescent until activated upon injury or stress. In mouse, there are roughly 550 satellite cells per 1 mg of muscle tissue (Bentzinger, Wang, and Rudnicki 2012), making them one of the most abundant tissue-specific stem cell populations in the body. Satellite cells can be obtained from a small muscle biopsy, under local anesthesia or from animals recently slaughtered, and purified in the lab based on an array of well characterized cell surface markers (L. Liu et al. 2015). However, maintaining their proliferative capacity in vitro outside of the resident muscle niche has been challenging and is an area of active research. As a tissue-specific stem cell, activated satellite cells readily give rise to myoblasts, which eventually lead to the formation of myocytes, multinucleated myotubes, and myofibers, each delineated by the expression of key transcription factors (Chal and Pourquié 2017). There is some evidence that satellite cells can enter an alternative mesenchymal-like pathway, leading to the generation of other cell types such as adipocytes (Shefer, Wleklinski-Lee, and Yablonka-Reuveni 2004), however this has been refuted (Starkey et al. 2011). Therefore, satellite cells offer the most direct method for obtaining skeletal muscle tissue in vitro, but may not be ideal for the creation of other cellular components of meat.
A reproducible and consistent cell line is essential for any bioprocess. Due to the large number of cell population doublings needed to make cell-based meat at scale, there exists a sizable concern for genetic drift and cell line stability, which may lead to inconsistencies in downstream processing and final product. In essence, as cells continue to divide and replicate their DNA, the probability of an increased burden of genetic variation (single nucleotide polymorphisms, copy number variation, large insertions or deletions, epigenetic changes, or aneuploidy) also increases. In some cases, these variations can be harnessed for improved processing (e.g. adaptation to suspension culture or lower concentration of growth factors, discussed in Series II), however, in general, genetic stability is favorable for a reproducible process.
In order to mitigate the risk of genetic drift, cells will need to be initially expanded, validated via rigorous quality control, and cryopreserved as a master cell bank (Figure 6). Individual vials from the master bank can then be serially subcultured to produce working cell banks. Animal-origin free and chemically-defined cryopreservation techniques will need to be optimized for a diverse set of cell types from various species. This strategy can allow for batch processing of cell-based meat or continuous processing of progenitor stem cells, at least until sufficient differences are detected wherein the culture can then be restarted. Similar strategies are already employed in other biomedicine industries, such as vaccine production, and these may serve as a guide for the cell-based meat industry.
Currently, there exist few publicly available cell lines of the aforementioned cell types from agriculturally-relevant species for cell-based meat production. Thus, there is a great need for the creation of new cell lines that can be banked and distributed to researchers in academia and industry alike. These biorepositories can be set up similarly to those dedicated to housing tissues and cell lines for efforts related to endangered animal conservation or large scale distribution networks (e.g. American Type Culture Collection). Having many cell lines available from a diverse array of animal species will be one of the most important factors in bootstrapping the research required for the cell-based meat industry to thrive long-term. The Good Food Institute is funding a project, the “Frozen Farmyard,” to accomplish this goal.
Much of the knowledge for culturing stem cell lines has come from the fields of cell-based therapy and regenerative medicine. While there are many fundamental similarities in laboratory techniques, protocols, and reagents that can be used in cell-based meat production, an important difference lies in growing cells from different animal species. The vast majority of published literature using the cell types previously described comes from studies in human and mouse. While there exist examples of studies using the stem cells described from bovine, porcine, ovine, avian, and piscine animals, the field as a whole lacks well-established protocols and the degree of rich scientific literature from which to draw upon. Despite this, a vast amount of information, mostly held privately by corporations, does exist on the cellular biology and genetics of livestock species, which may be leveraged for adapting livestock species for cell culture. Additionally, resources such as sophisticated genome annotations, validated antibodies, and other -omics datasets will need to be generated. Lastly, while key developmental processes are generally conserved by evolution, it remains unclear the extent to which species differences will affect the success of applying human- or mouse-based cell culture strategies to evolutionarily distant species such as crustaceans or fish. Thus, the overall bioprocess will likely be replicated from species to species, but key differences, either advantageous or disadvantageous, are to be expected due to inherent biological differences across an evolutionarily diverse set of species.
Cell Line Considerations
Other cell line selection strategies may entail generation of multiple cell lines from an individual animal, different biopsy locations within an animal, different individuals within the same species, or clones of each derived cell line. For example, selective breeding has produced desirable traits in specific animal breeds and thus these same traits may be strategically recapitulated in vitro (e.g. using cattle from the Belgian Blue versus Holstein breed for skeletal muscle production). When possible, cell lines should also be obtained from animals that are raised in closed flocks, herds, or colonies, and free of known specific pathogens. Having multiple cell lines or clonal lines will also enable companies to choose lines which have the best downstream characteristics (e.g. proliferation rate, differentiation potential, etc), potentially avoiding labor-intensive strategies such as directed evolution to acquire the same characteristics.
The location of an initial cell biopsy may also have downstream effects. As previously discussed, this could influence the differentiation potential of a mesenchymal stem cell population. For myosatellite cells, a muscle biopsy from a region of fast-twitch muscle fiber will in turn bias production of fast-twitch muscle fibers, which may influence final taste, texture, and metabolic rates of the cells in culture (Y.-C. Huang, Dennis, and Baar 2006). Location variables are less likely to influence pluripotent stem cell-derived outcomes, however individual and clonal variation amongst pluripotent stem cell lines is a notoriously difficult problem to manage (Kyttälä et al. 2016). With these considerations in mind, it’s likely that many species, stem cell types, and cell line variables will be explored in order to determine the best cell lines for cell-based meat production. However, one of the inherent advantages of using cell culture to produce meat rather than an animal is the range of real-time testing, data analysis, and parameter iterations which can be made from biopsy to product packaging. These advantages can accelerate the rate of innovation to reach success and create new products (discussed in Series V) versus traditional animal agriculture.
Cell Proliferation and Immortalization
In general, the process of cell-based meat production following cell line selection can be broken up into two phases: proliferation and differentiation. In the proliferation phase, stem cells divide repeatedly to generate a large number of cells until they are transferred to a new environment and triggered to differentiate into a mature cell type via changes in scaffolding (discussed in Series III), medium composition (discussed in Series IV), or both.
One hurdle in obtaining a large number of cells is that the number of times a cell can divide is inherently limited based on the Hayflick Limit. The Hayflick Limit imposes a limitation on cell divisions due to degradation of end-capping chromosomal telomeres following each cell division. Once a certain number of cell divisions occurs (typically around 30-50 in vitro for human cells), the cells enter a state of senescence and stop dividing. Thus, the number of potential cells acquired from a single starting batch is biologically limited. Some cells, however, can bypass the Hayflick Limit and achieve cell immortality. Pluripotent stem cells achieve immortality in part by epigenetic changes (Hochedlinger and Jaenisch 2015) and upregulation of the enzyme telomerase (Y. Huang et al. 2014), which prevents telomere degradation. This property makes pluripotent stem cells especially useful in initial scaling, although genetic drift during proliferation may also lead to cell senescence or apoptosis.
While some adult stem cells can retain some telomerase expression (Hiyama and Hiyama 2007), it is insufficient to acquire immortality. One alternative method is to rely on the accumulation of a sufficient number of mutations in vitro to bypass normal cellular checkpoints and achieve spontaneous immortalization. Many cell lines used in research were derived from spontaneously immortalized lines, however the mutational burden can also alter the biology of the cells in unpredictable ways, potentially limiting their utility. Additionally, biological variation between species or cell type can contribute to the probability of spontaneous immortalization or cell transformation. For instance, the naked mole rat, which is highly resistant to cancerous cell transformation, is hypersensitive to contact inhibition (Seluanov et al. 2009) and resistant to iPSC reprogramming (Tan et al. 2017). Other species such as lobsters and fish, which retain high telomerase expression (Klapper et al. 1998; Gomes, Shay, and Wright 2010), or elephants, which have multiple copies of the p53 tumor suppressor (Sulak et al. 2016), may thus be easier and harder, respectively, to achieve transformation, although in vivo telomerase expression levels do not necessarily correlate to those observed in vitro (Venkatesan and Price 1998). These and other unique animal properties, known or currently unknown, may be strategically harnessed for cell-based meat production.
A targeted immortalization approach can be achieved by overexpression of exogenously added genes or viral proteins. In these cases, the overexpression of telomerase in combination with inhibition of cell cycle genes such as p16 or Rb (Tsutsui et al. 2002) or use of viral elements such as the SV40 Large T Antigen (Jha et al. 1998) or adenovirus type 5 E1 gene (Sieber and Dobner 2007) have been utilized for cell immortalization. Precision gene editing (e.g. CRISPR) methods can be used in combination to insert these genes into safe harbor loci (Sadelain, Papapetrou, and Bushman 2011), minimizing the risk of alterations in global gene expression. Additionally, tandem use of genetic engineering strategies can create ON-OFF switches for immortalization, through use of Cre-lox or Flp-FRT recombination (Robin et al. 2015; Westerman and Leboulch 1996) or piggyBac transposon (Xie et al. 2016) systems. Thus, immortalization can be readily targeted or reversed, however, it is currently unclear how spontaneously immortalized or intentionally immortalized lines will be regulated, as significant genetic alterations and use of genetic engineering may warrant rigorous regulatory standards (discussed in Series IV).
Additional methods to improve proliferation rates or maintain proliferative capacity of non-immortalized stem cells also exist. For example, in myoblasts, use of small molecule compounds can assist in maintaining proliferative capacity via targeting of proliferation pathways (Bar-Nur et al. 2018) or inhibition of specific proteins such as STAT3 (Tierney et al. 2014), p38 (Ding et al. 2018), and Setd7 (Judson et al. 2018). Other strategies include mimicking an injured or regenerative state via growth in the presence of cytokines (Fu et al. 2015), addition of small peptides normally released following exercise (Vinel et al. 2018), or growth of cells in a hypoxic environment which may more closely mimic fetal oxygen levels (W. Liu et al. 2012). Similar strategies can tune biochemical pathways in other cell types such as adipocytes or chondrocytes. Many genetic engineering methods can also be employed to achieve similar results. These include gene overexpression via inducible or constitutively active systems and gene inhibition or knockout. In general, mimicking the native stem cell niche to retain stemness in vitro is an area of active research, and there exists a broad amount of possibilities (more in Series III) for implementing these strategies for cell-based meat production.
Series II will focus on bioprocessing considerations for cell-based meat.
- Bar-Nur, Ori, Mattia F. M. Gerli, Bruno Di Stefano, Albert E. Almada, Amy Galvin, Amy Coffey, Aaron J. Huebner, et al. 2018. “Direct Reprogramming of Mouse Fibroblasts into Functional Skeletal Muscle Progenitors.” Stem Cell Reports 10 (5): 1505–21.
- Bentzinger, C. Florian, Yu Xin Wang, and Michael A. Rudnicki. 2012. “Building Muscle: Molecular Regulation of Myogenesis.” Cold Spring Harbor Perspectives in Biology 4 (2). https://doi.org/10.1101/cshperspect.a008342.
- Bogliotti, Yanina Soledad, Jun Wu, Marcela Vilarino, Daiji Okamura, Delia Alba Soto, Cuiqing Zhong, Masahiro Sakurai, et al. 2018. “Efficient Derivation of Stable Primed Pluripotent Embryonic Stem Cells from Bovine Blastocysts.” Proceedings of the National Academy of Sciences of the United States of America 115 (9): 2090–95.
- Chal, Jérome, and Olivier Pourquié. 2017. “Making Muscle: Skeletal Myogenesis in Vivo and in Vitro.” Development 144 (12): 2104–22.
- Cho, Hyun-Jai, Choon-Soo Lee, Yoo-Wook Kwon, Jae Seung Paek, Sun-Hee Lee, Jin Hur, Eun Ju Lee, et al. 2010. “Induction of Pluripotent Stem Cells from Adult Somatic Cells by Protein-Based Reprogramming without Genetic Manipulation.” Blood 116 (3): 386–95.
- Choi, Jiho, Soohyun Lee, William Mallard, Kendell Clement, Guidantonio Malagoli Tagliazucchi, Hotae Lim, In Young Choi, et al. 2015. “A Comparison of Genetically Matched Cell Lines Reveals the Equivalence of Human iPSCs and ESCs.” Nature Biotechnology 33 (11): 1173–81.
- Ding, Shijie, G. N. M. Swennen, Tobias Messmer, Mick Gagliardi, Daniël G. M. Molin, Chunbao Li, Guanghong Zhou, and Mark J. Post. 2018. “Maintaining Bovine Satellite Cells Stemness through p38 Pathway.” Scientific Reports 8 (1): 10808.
- Dominici, M., K. Le Blanc, I. Mueller, I. Slaper-Cortenbach, Fc Marini, Ds Krause, Rj Deans, A. Keating, Dj Prockop, and Em Horwitz. 2006. “Minimal Criteria for Defining Multipotent Mesenchymal Stromal Cells. The International Society for Cellular Therapy Position Statement.” Cytotherapy 8 (4): 315–17.
- Fujie, Yasumitsu, Noemi Fusaki, Tomohiko Katayama, Makoto Hamasaki, Yumi Soejima, Minami Soga, Hiroshi Ban, et al. 2014. “New Type of Sendai Virus Vector Provides Transgene-Free iPS Cells Derived from Chimpanzee Blood.” PloS One 9 (12): e113052.
- Fu, Xin, Jun Xiao, Yuning Wei, Sheng Li, Yan Liu, Jie Yin, Kun Sun, et al. 2015. “Combination of Inflammation-Related Cytokines Promotes Long-Term Muscle Stem Cell Expansion.” Cell Research 25 (6): 655–73.
- Gomes, Nuno M. V., Jerry W. Shay, and Woodring E. Wright. 2010. “Telomere Biology in Metazoa.” FEBS Letters 584 (17): 3741–51.
- Hiyama, E., and K. Hiyama. 2007. “Telomere and Telomerase in Stem Cells.” British Journal of Cancer 96 (7): 1020–24.
- Hochedlinger, Konrad, and Rudolf Jaenisch. 2015. “Induced Pluripotency and Epigenetic Reprogramming.” Cold Spring Harbor Perspectives in Biology 7 (12). https://doi.org/10.1101/cshperspect.a019448.
- Huang, Yan, Puping Liang, Dan Liu, Junjiu Huang, and Zhou Songyang. 2014. “Telomere Regulation in Pluripotent Stem Cells.” Protein & Cell 5 (3): 194–202.
- Huang, Yen-Chih, Robert G. Dennis, and Keith Baar. 2006. “Cultured Slow vs. Fast Skeletal Muscle Cells Differ in Physiology and Responsiveness to Stimulation.” American Journal of Physiology. Cell Physiology 291 (1): C11–17.
- Ito, Naoki, Isao Kii, Noriaki Shimizu, Hirotoshi Tanaka, and Shin ’ichi Takeda. 2017. “Direct Reprogramming of Fibroblasts into Skeletal Muscle Progenitor Cells by Transcription Factors Enriched in Undifferentiated Subpopulation of Satellite Cells.” Scientific Reports 7 (1): 8097.
- Jha, K. K., S. Banga, V. Palejwala, and H. L. Ozer. 1998. “SV40-Mediated Immortalization.” Experimental Cell Research 245 (1): 1–7.
- Judson, Robert N., Marco Quarta, Menno J. Oudhoff, Hesham Soliman, Lin Yi, Chih Kai Chang, Gloria Loi, et al. 2018. “Inhibition of Methyltransferase Setd7 Allows the In Vitro Expansion of Myogenic Stem Cells with Improved Therapeutic Potential.” Cell Stem Cell 22 (2): 177–90.e7.
- Klapper, W., K. Kühne, K. K. Singh, K. Heidorn, R. Parwaresch, and G. Krupp. 1998. “Longevity of Lobsters Is Linked to Ubiquitous Telomerase Expression.” FEBS Letters 439 (1-2): 143–46.
- Kyttälä, Aija, Roksana Moraghebi, Cristina Valensisi, Johannes Kettunen, Colin Andrus, Kalyan Kumar Pasumarthy, Mahito Nakanishi, et al. 2016. “Genetic Variability Overrides the Impact of Parental Cell Type and Determines iPSC Differentiation Potential.” Stem Cell Reports 6 (2): 200–212.
- Liu, Ling, Tom H. Cheung, Gregory W. Charville, and Thomas A. Rando. 2015. “Isolation of Skeletal Muscle Stem Cells by Fluorescence-Activated Cell Sorting.” Nature Protocols 10 (10): 1612–24.
- Liu, Weiyi, Yefei Wen, Pengpeng Bi, Xinsheng Lai, X. Shawn Liu, Xiaoqi Liu, and Shihuan Kuang. 2012. “Hypoxia Promotes Satellite Cell Self-Renewal and Enhances the Efficiency of Myoblast Transplantation.” Development 139 (16): 2857–65.
- Prasad, Ankshita, Daniel Boon Loong Teh, Fathima R. Shah Jahan, Janani Manivannan, Soo Min Chua, and Angelo H. All. 2017. “Direct Conversion Through Trans-Differentiation: Efficacy and Safety.” Stem Cells and Development 26 (3): 154–65.
- Rackham, Owen J. L., Jaber Firas, Hai Fang, Matt E. Oates, Melissa L. Holmes, Anja S. Knaupp, FANTOM Consortium, et al. 2016. “A Predictive Computational Framework for Direct Reprogramming between Human Cell Types.” Nature Genetics 48 (3): 331–35.
- Robin, Jerome D., Woody E. Wright, Yaqun Zou, Stacy C. Cossette, Michael W. Lawlor, and Emanuela Gussoni. 2015. “Isolation and Immortalization of Patient-Derived Cell Lines from Muscle Biopsy for Disease Modeling.” Journal of Visualized Experiments: JoVE, no. 95 (January): 52307.
- Rosselló, Ricardo Antonio, Chun-Chun Chen, Rui Dai, Jason T. Howard, Ute Hochgeschwender, and Erich D. Jarvis. 2013. “Mammalian Genes Induce Partially Reprogrammed Pluripotent Stem Cells in Non-Mammalian Vertebrate and Invertebrate Species.” eLife 2 (September): e00036.
- Sadelain, Michel, Eirini P. Papapetrou, and Frederic D. Bushman. 2011. “Safe Harbours for the Integration of New DNA in the Human Genome.” Nature Reviews. Cancer 12 (1): 51–58.
- Schlaeger, Thorsten M., Laurence Daheron, Thomas R. Brickler, Samuel Entwisle, Karrie Chan, Amelia Cianci, Alexander DeVine, et al. 2015. “A Comparison of Non-Integrating Reprogramming Methods.” Nature Biotechnology 33 (1): 58–63.
- Seluanov, Andrei, Christopher Hine, Jorge Azpurua, Marina Feigenson, Michael Bozzella, Zhiyong Mao, Kenneth C. Catania, and Vera Gorbunova. 2009. “Hypersensitivity to Contact Inhibition Provides a Clue to Cancer Resistance of Naked Mole-Rat.” Proceedings of the National Academy of Sciences of the United States of America 106 (46): 19352–57.
- Shefer, Gabi, Monika Wleklinski-Lee, and Zipora Yablonka-Reuveni. 2004. “Skeletal Muscle Satellite Cells Can Spontaneously Enter an Alternative Mesenchymal Pathway.” Journal of Cell Science 117 (Pt 22): 5393–5404.
- Sieber, Timo, and Thomas Dobner. 2007. “Adenovirus Type 5 Early Region 1B 156R Protein Promotes Cell Transformation Independently of Repression of p53-Stimulated Transcription.” Journal of Virology 81 (1): 95–105.
- Sipp, Douglas, Pamela G. Robey, and Leigh Turner. 2018. “Clear up This Stem-Cell Mess.” Nature 561 (7724): 455–57.
- Starkey, Jessica D., Masakazu Yamamoto, Shoko Yamamoto, and David J. Goldhamer. 2011. “Skeletal Muscle Satellite Cells Are Committed to Myogenesis and Do Not Spontaneously Adopt Nonmyogenic Fates.” The Journal of Histochemistry and Cytochemistry: Official Journal of the Histochemistry Society 59 (1): 33–46.
- Sulak, Michael, Lindsey Fong, Katelyn Mika, Sravanthi Chigurupati, Lisa Yon, Nigel P. Mongan, Richard D. Emes, and Vincent J. Lynch. 2016. “TP53 Copy Number Expansion Is Associated with the Evolution of Increased Body Size and an Enhanced DNA Damage Response in Elephants.” eLife 5 (September). https://doi.org/10.7554/eLife.11994.
- Takahashi, Kazutoshi, and Shinya Yamanaka. 2006. “Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures by Defined Factors.” Cell 126 (4): 663–76.
- Tan, Li, Zhonghe Ke, Gregory Tombline, Nicholas Macoretta, Kevin Hayes, Xiao Tian, Ruitu Lv, et al. 2017. “Naked Mole Rat Cells Have a Stable Epigenome That Resists iPSC Reprogramming.” Stem Cell Reports 9 (5): 1721–34.
- Tierney, Matthew Timothy, Tufan Aydogdu, David Sala, Barbora Malecova, Sole Gatto, Pier Lorenzo Puri, Lucia Latella, and Alessandra Sacco. 2014. “STAT3 Signaling Controls Satellite Cell Expansion and Skeletal Muscle Repair.” Nature Medicine 20 (10): 1182–86.
- Tsutsui, Takeki, Shin-Ichi Kumakura, Akito Yamamoto, Hideaki Kanai, Yukiko Tamura, Takashi Kato, Masanori Anpo, Hidetoshi Tahara, and J. Carl Barrett. 2002. “Association of p16(INK4a) and pRb Inactivation with Immortalization of Human Cells.” Carcinogenesis 23 (12): 2111–17.
- Venkatesan, R. N., and C. Price. 1998. “Telomerase Expression in Chickens: Constitutive Activity in Somatic Tissues and down-Regulation in Culture.” Proceedings of the National Academy of Sciences of the United States of America 95 (25): 14763–68.
- Vinel, Claire, Laura Lukjanenko, Aurelie Batut, Simon Deleruyelle, Jean-Philippe Pradère, Sophie Le Gonidec, Alizée Dortignac, et al. 2018. “The Exerkine Apelin Reverses Age-Associated Sarcopenia.” Nature Medicine 24 (9): 1360–71.
- Westerman, K. A., and P. Leboulch. 1996. “Reversible Immortalization of Mammalian Cells Mediated by Retroviral Transfer and Site-Specific Recombination.” Proceedings of the National Academy of Sciences of the United States of America 93 (17): 8971–76.
- Wu, Wei, Yu-Qing Jin, and Zhen Gao. 2017. “Directly Reprogramming Fibroblasts into Adipogenic, Neurogenic and Hepatogenic Differentiation Lineages by Defined Factors.” Experimental and Therapeutic Medicine 13 (6): 2685–90.
- Xie, Fei, Kerui Gong, Ke Li, Mingliang Zhang, Judy C. Chang, Shizhong Jiang, Lin Ye, Jiaming Wang, Yuting Tan, and Yuet Wai Kan. 2016. “Reversible Immortalization Enables Seamless Transdifferentiation of Primary Fibroblasts into Other Lineage Cells.” Stem Cells and Development 25 (16): 1243–48.
- Zhang, Yu, Wenlin Li, Timothy Laurent, and Sheng Ding. 2012. “Small Molecules, Big Roles -- the Chemical Manipulation of Stem Cell Fate and Somatic Cell Reprogramming.” Journal of Cell Science 125 (Pt 23): 5609–20.
Cell-based Meat Science Series II: Bioprocessing
If the goal of cell-based meat production is to significantly reduce the levels of meat consumption from industrial animal agriculture and in turn reduce the associated negative impacts (discussed in Series VI), then large quantities of meat will need to be produced affordably and efficiently. Currently, there are no cell-based meat products on the market, although several cell-based meat products have been taste-tested, including cell-based duck, pork sausage, foie gras, fat, beef meatballs, beef hamburgers, and beef steak strips. However, moving from bench-scale methods to an industrialized bioprocess requires an influx of talented scientists from a wide array of disciplines in order to solve significant technical hurdles in cell biology and engineering optimizations. These hurdles, potential strategies for solutions, and the roadmap to scaling cell-based meat are discussed below.
Although cell-based meat products for taste testing have been produced using standard cell culture dishes and stacked flasks, growing cell-based meat at scale will require the use of bioreactors in volumes up to or beyond several thousands of liters. This fundamental switch in how cells are grown brings in additional considerations such as gas exchange, heat transfer, shear stress, mixing, and foaming, which are not of common concern to the standard cell culture technician. While many of these techniques can be borrowed from industries such as cell therapies, recombinant protein production, or production of other biologics, considerable optimizations are required in order to move cell-based meat beyond taste-testing events and toward market readiness. This will require an interdisciplinary effort amongst cell biologists and chemical, mechanical, and bioprocessing engineers.
A variety of methods can be selected for scaling cell-based meat production past bench into pilot and full scales (Figure 1). Broadly speaking, these methods can be broken up categorically into batch, fed-batch, continuous, and perfusion (Meyer, Minas, and Schmidhalter 2017). In batch culture, a vessel is filled with a fixed volume of media and cells are grown to their maximum density before being harvested or transferred to a larger vessel. In fed-batch culture, cells grown in a vessel are fed fresh medium from an in-line, independent feed vessel at variable rates in order to maximize properties such as exponential cell growth or cell densities. In continuous culture, cells are grown in a vessel and fresh medium is added via an in-line feed vessel at an optimized flow rate, while product, cells, or medium are simultaneously collected in an independent collection vessel at the same or alternative rate. Lastly, perfusion culture is a subset of continuous culture wherein the cells are retained via a substrate or collection method, permitting medium recycling integration and high cell densities in a smaller space. Each method has potential benefits and caveats, and it is possible that multiple methods may be used throughout a cell-based meat bioprocess. Because optimizing a scale-up can require large capital expenses, use of high throughput miniature bioreactors can assist in modeling batch or fed-batch processes (Rameez et al. 2014). However, miniature perfusion bioreactors requiring microfluidics to match flow rates in small volumes has lagged behind and may be more difficult to accurately model at small scales (Fisher et al. 2019). Accordingly, products for high throughput modeling of perfusion methods still deal with volumes of up to 250 mL.
There are many different bioreactor designs to choose from which can be separated based on how the medium is mixed and whether the cells are grown in suspension or adhered to a solid surface. For mammalian cell culture, the most commonly used bioreactor is a continuous stirred tank reactor, as it offers greater long-term sterility and reduced bubbling versus air-lift reactors at scale (Figure 2; Meyer, Minas, and Schmidhalter 2017). In general, continuous stirred tank reactors permit growth of cells in suspension via mechanical stirring while maintaining high mass transfer of oxygen. Similar results can be obtained with rocking platform bioreactors and vertical wheel bioreactors, albeit at smaller maximum scales. Current cell therapy and biopharmaceutical industry trends show preference for stirred tank and rocking platform bioreactors in disposable, single-use systems up to 2000L. Single-use bioreactors have the advantage of not requiring heated sterilization (discussed later), saving on turnaround time, cross-contamination, water, energy, and sensor (discussed below) costs. Therefore, single-use bioreactors may be a favorable option when considering scale-out methods (discussed below) of production, however the comparably lower value of a batch of cell-based meat product versus a biologic drug or human cell therapy means that single-use technologies would likely not make economic sense for cell-based meat unless current models can be made more affordable. Notably, however, single-use bioreactor bags consist of various material layers which must meet strict regulatory standards at high cost in order to ensure that a high-value batch of product is not lost. Thus, at lower batch value and food-grade regulatory requirements, there may be room for engineering economically-feasible disposable bags tailored for cell-based meat production. The sustainability implications of single-use bioreactors if implemented, in terms of waste, will have to be considered against the potential savings of water and energy usage in sterilization procedures in lieu of their use.
There are many important variables which can affect a bioprocess when scaling. These include efficiency of mass transfer, avoidance of inhomogeneities, heat dissipation, impeller shape and speed, and reactor geometry, amongst others. Each can be affected differently depending on the cell type, scale, and intended downstream use. Adjustments for these variables are likely to be adapted from existing platforms from the cell therapy and biologics fields and custom-tailored to a specific bioprocess. Thus, the most generalizable optimizations are discussed below.
One important consideration when scaling is how to deal with shear stress. Shear stress is the mechanical force induced by the friction of liquid on a cell’s surface (Nerem 1991). In a bioreactor, this is caused by the liquid’s turbulence created by the impeller (or general motion) in order to keep the cells in suspension. Larger volumes generally imply stronger shear forces, although the force is inhomogenous throughout the bioreactor (Papoutsakis 1991). Shear stress can impact cell viability (Hu, Berdugo, and Chalmers 2011) and differentiation (Stolberg and McCloskey 2009) (discussed further in Series III), but can also be mitigated by installment of flow breakers, cell adaptations, or addition of poloxamers to the culture medium (D. Chang et al. 2017). The presence of bubbles or growth of cells in aggregates or on microcarriers (discussed below) can also lead to higher shear forces. Tolerable levels of shear stress should thus be calculated for each cell line and cell type (King and Miller 2007).
The vast majority of cell types, including those used in cell-based meat, are anchorage-dependent, meaning that they require some substrate to grow on in order to prevent programmed cell death, termed anoikis. While pluripotent stem cells can be grown as anchorage-independent aggregates in suspension, they must also be routinely dissociated to single cells in order to prevent spontaneous differentiation (Shafa et al. 2012; Zweigerdt et al. 2011), and are typically treated with an inhibitor of Rho Kinase (i.e. ROCK inhibitor) to prevent death as single cells. Pluripotent-derived cell types used in cell-based meat production are largely anchorage-dependent, although recent advances in organoid culture have led to the development of suspension-based differentiation protocols to create an array of iPSC-derived cell types, including myoblasts (Hosoyama et al. 2014). These protocols may also better recapitulate the physiology of in vivo cellular counterparts (discussed further in Series III), however, they have limited testing past bench scale (Kim and Kino-Oka 2018). Lastly, aggregate-based culture may be more susceptible to shear stress (Chapman et al. 2014), resulting in lower cell viability and lower cell densities relative to single cell suspension culture, although these limitations can likely be overcome (Lipsitz et al. 2018). Some scale-up strategies are described in Figure 3.
Adult stem cell types such as myosatellite cells and mesenchymal stem cells are also anchorage-dependent, and are generally grown in suspension on microcarriers (Figure 4, discussed further in Series III) in order to bypass this limitation, although spheroid cultures are a promising alternative (Alimperti et al. 2014; Jossen et al. 2018). However, there are no inherent biological limitations to suspension adaptation. For instance, the adherent epithelial Chinese Hamster Ovary cell type used in the production of biologics has been adapted to suspension growth and optimized for specific traits such as maximized protein production over time in vitro. Mesenchymal stem cells, on the other hand, are often used as cell therapies, and the development of off-the-shelf allogeneic products which necessitate large scale bioprocessing (e.g. 1 million doses) and cell line optimization is still in its infancy. As such, many routine mesenchymal stem cell therapies are autologous in nature, requiring minimal scaling and no cell line optimization prior to re-entry into the body (Galipeau and Sensébé 2018). Thus, sufficient selection, directed evolution strategies (Tizei et al. 2016), or genetic engineering (Lee et al. 2016) applied to adult stem cell types may be able to overcome anchorage-dependent limitations for cell-based meat cell line growth in bioreactors. Notably, species differences may also determine the likelihood of suspension growth, exemplified by suspension growth of insect myoblasts (Rubio et al. 2019). Some immortalized cell lines (discussed in Series I), depending on the method of immortalization, can acquire anchorage-independence, permitting growth in suspension (Kovalevich and Langford 2013; Qu et al. 2015). Lastly, in adipocytes, the accumulation of lipid droplets upon maturation and resultant increased buoyancy may pose additional problems for cell-based fat production in conventional stirred tank bioreactors (Zhang et al. 2000).
As cells grow, they release autocrine and paracrine factors that can serve as pro-growth or inhibitory signals to neighboring cells. Under high cell densities intended for cell-based meat production (i.e. > 1x10^7 cells/mL), these signals can greatly influence downstream proliferation, differentiation, and viability. Computational in silico modeling can assist in the selection of bioprocessing methods by modeling accumulation of paracrine signals and predicting methods to yield favorable outcomes (Figure 5; Csaszar et al. 2012). Identified undesirable signals may also be removed from the culture via filtration whereas desirable signals can be recycled (discussed in Series IV). Alternatively, growth of cells in high concentrations of paracrine factors such as lactic acid, ammonia (Schumpp and Schlaeger 1992), and low concentrations of growth factors can select for cells tolerant to high densities and lower growth factor requirements (e.g. serum-free conditions) (Sinacore, Drapeau, and Adamson 2000). High-density growth may also require nutrient alterations to the cell culture medium, as well as addition of oxygen carriers (Ozturk 1996) and anti-foaming agents (Velugula-Yellela et al. 2018) (discussed further in Series IV). It will therefore be important to generate optimized cell lines across a variety of species that are uniquely adapted to the biophysical environment within bioreactors and tolerant to relevant paracrine factors or secreted metabolites during the proliferation and differentiation stages, respectively.
For instance, a recent patent released by Memphis Meats describes cell lines containing a genetically encoded glutamine synthetase, which enables intracellular conversion of glutamate to glutamine while consuming ammonia in the process. Thus, ammonia can be reduced by ~20% while generating energy substrates for the cell in the form of glutamine (described further in Series IV, Genovese 2019). Some avian species have been shown to metabolize ammonia differently than mammals in their skeletal muscle due to differences in glutamine synthetase expression, yielding larger myotubes presumably from increased glutamine utilization (Stern and Mozdziak 2019). Thus, inherent species differences also come into play when considering optimizations around the biochemical and biophysical environments within bioreactors.
In order to produce large numbers of cells in large volumes, a progressive scaling process is started from a single vial of cells. This process is called a seed train. As cells grow, they proceed through a lag phase, where the cells adapt to their growing conditions, followed by a log phase where cells proliferate exponentially, and ending in a stationary phase. Thus, the starting density of cells compared to the volume in which they are thawed can influence their access to available nutrients and time to reach log phase (Frahm 2014). This can vary by cell type and species (Cheng et al. 2014). The seed train strategy relies on cells growing exponentially over time, tracked by population doublings, while transferring cells into progressively larger vessels. By the exponential nature of this process, the greatest efficiencies are achieved at high numbers of population doublings. However, a higher number of population doublings can negatively affect downstream proliferation rates and differentiation capacities (Park et al. 2008; Bonab et al. 2006). Thus, optimization strategies for seed train development are needed to achieve rapid, steady log phase growth without loss of downstream differentiation potential or viability.
Several strategies to reduce seed train times and save on costs have already been conceived of in other bioprocess applications and should be translatable to cell-based meat production. For instance, high density cryopreservation of cells (~10 x 10^7 cells/mL) can be thawed directly into multi-liter rocking platform bioreactors to dramatically reduce the number of days required to scale cell numbers (Figure 6; Tao et al. 2011). Alternatively, stem cells may be grown in a continuous or semi-continuous bioprocess early on, with subsets of cells from these bioreactors used to directly inoculate larger volume tanks. In these cases, coupled cell retention devices can enable continuous processing at high cell densities, saving on downtime between runs (Xiaoxia and Buser 2016; Fisher et al. 2019). Perfusion bioreactors, such as hollow fiber reactors, may serve as one example to generate high-density cultures, capable of continuous cell growth over many months with high automation potential (discussed later) (William G. Whitford John J.S. Cadwell 2011). Economic modeling of integrated continuous processing has shown savings of 55% on capital and operating expenses over a 10-year period [for production of monoclonal antibodies] compared to batch processing, suggesting that implementation of continuous processes would be attractive for cell-based meat companies (Walther et al. 2015). Additionally, new techniques utilizing co-extruded cells within 400 micron diameter alginate-based tubes (Lin et al. 2019; Li et al. 2018) offer tremendous potential for scaling cell-based meat production within closed microenvironments, bypassing seed train processing altogether and dramatically reducing the volume requirements of the bioreactor in order to obtain the same number of cells versus previously discussed methods.
Taken together, the bioprocessing scale-up strategy is one of the most substantial technical and engineering hurdles to overcome in order for cell-based meat production to reach mass markets. While it may take significant time to empirically validate or translate existing strategies in the biologics field to cell-based meat production in new species and cell types, the tremendous evolution of bioprocessing over the last few decades provides a roadmap for success. Sharing of ideas and technologies across the biologics, cell therapy, bioreactor, and cell-based meat industries promises to provide positive synergistic outcomes across these fields.
A general timeline for the production of cell-based meat is on the order of a handful of weeks, however, this can vary greatly based on the cell type, species, and downstream intended product. For instance, the developmental timelines of a species are generally recapitulated in vitro such that skeletal muscle derived from mouse pluripotent stem cells via directed differentiation can be produced in two weeks, whereas a human system will take three weeks or more (Chal and Pourquié 2017). Accordingly, the doubling times of the same cell types from different species can vary (Cheng et al. 2014), as well as doubling times from different cell types within the same species. For instance, mouse pluripotent stem cells will divide at higher rates (doubling time = 12-16 hours (Tamm, Pijuan Galitó, and Annerén 2013)) versus adult myoblast cells (doubling time = 24 hours (Shahini et al. 2018)). Thus, large timeline efficiency gains to produce a certain number of cells may be granted solely on the selection of species and starting cell type. However, other variables such as cell size in larger animals (Han et al. 2013) is also recapitulated in vitro, which may make up for slower doubling times in terms of gross tissue mass (Figure 7). Maturation time (discussed in Series III) may also influence timelines and end products with different texture requirements. Thus, economic modeling of the bioprocess should take into account the different variables presented for each species throughout the bioprocess, many of which will need to be empirically determined due to a dearth of rigorous literature for many species.
Scale Out vs. Scale Up
Given the challenges in scaling up cell production, a scaling out approach may yield a faster route to getting cell-based meat in the mouths of consumers. In this scenario, production takes place at smaller scales, satisfying meat production requirements which are more akin to a restaurant or butcher shop rather than a farm or a slaughterhouse. These scales have been estimated to require more manageable bioreactor sizes of 100 - 1000L volumes to reach local demand. Thus, it may be significantly easier to design a scale-out facility with higher automation potential, lower energy, land, and capital expenditure requirements, and saved time and money from avoiding large scale up challenges. Similar strategies have been conceived at even smaller scales, such as in-home kits. Thus, scaling out approaches may provide a more reasonable short-term path to market for cell-based meat products and exploration of this strategy should be encouraged. However, production volumes at these scales will likely fail to meet the large demands for global meat consumption as they would not be able to capitalize at later stage exponential growth. Co-existing systems of local scale-out and large scale-up approaches may therefore be required to meet these demands over time.
Non-Cellular Considerations and Sensor Systems
The interactions amongst cells (solid phase) suspended in a liquid phase and aerated by a gas phase within a bioreactor are complex and require sophisticated monitoring to ensure a bioprocess is operating optimally. In general, these interaction variables can be broken into physical (e.g. temperature), chemical (e.g. pH), and biological (e.g. cell concentration). The sensors which measure these variables can lie inside the bioreactor itself (in-line), outside of the bioreactor (at-line or off-line), or operate continually (on-line) (Biechele et al. 2015). In-line sensors require enduring the same temperature and sterilization processes as the bioreactor itself, having minimal leaching of components, and potentially operating for weeks at a time without requiring re-calibration. If there are inhomogeneities within the bioreactor, usage of multiple in-line sensors or sensor arrays may be required to achieve accuracy. On the other hand, off-line sampling can require manual human involvement and sample manipulations, which can affect more time-sensitive variables and introduce contaminants (discussed later). In general, current sensor development focuses on real-time, on-line monitoring systems, which are frequently becoming enabled by advanced spectroscopic systems and a push for continuous bioprocessing in other industries. These sensors are primarily being developed to adhere to the FDA’s Process Analytical Technology guidelines but can be adopted by the cell-based meat industry. The key variables affecting a cell-based meat bioprocess are temperature, oxygen, carbon dioxide, pH, glucose, biomass, and metabolites. These variables and their sensing systems are discussed independently below.
The temperature of a cell-based meat bioprocess will depend on the species of interest. For example, most mammalian cells are grown around 37ºC while insects, fish, and other marine creature cells may be grown at significantly lower temperatures (Rubio et al. 2019, Rubio et al. 2019). Nevertheless, recording and maintaining accurate temperatures during the process is crucial for many parameters. This is typically done through the use of platinum resistance thermometers which contain a stable, non-reactive piece of platinum wire. The electrical resistance of the wire increases linearly with temperature and thus temperature can be inferred by passing current through the wire (O’Mara et al. 2018).
Oxygen is often the rate-limiting substrate within a bioreactor, as approximately 45 times the amount of dissolved oxygen can be carried by blood versus cell culture media (Martin and Vermette 2005). Oxygen must be continually delivered in the form of dissolved oxygen in order to meet cellular metabolic demands, referred to as the oxygen utilization rate. Meeting a specific cell line’s oxygen utilization rate requires considerations influencing the oxygen mass transfer coefficient, kLa, such as mixing speed, bubble size, temperature, flow rate, and general properties of the cell culture medium. Thus, species’ cells grown at lower temperatures, such as fish, may require differing oxygen requirements, as oxygen solubility increases at lower temperatures. Without proper oxygenation (typically 30-40% of air saturation) or with over-oxygenation, cell growth and viability can be rapidly negatively affected. Several methods exist for monitoring liquid phase dissolved oxygen, however membrane-covered amperometric electrodes, optical sensors, and paramagnetic sensors are most practical for biological applications (Biechele et al. 2015; O’Mara et al. 2018).
Carbon dioxide and pH are intimately linked in a cell-based meat bioprocess. As a bioprocess scales, an increasing number and density of cells respire, leading to an increasing concentration of dissolved CO2 above the standard 5-10% operating range. The CO2 can readily diffuse across the cell membrane, lowering intracellular pH and affecting cellular metabolism, enzyme function, protein folding, and general cell health (Pattison et al. 2000). In order to decrease CO2 concentrations, surface aeration, sparging, or agitation can be used; however, each becomes more difficult with scale due to surface-to-volume limitations and shear stress considerations (Matsunaga et al. 2009). CO2 is typically measured using a Severinghaus electrode, which contains a CO2-permeable membrane and electrode that records the resulting pH change within a bicarbonate solution as CO2 is absorbed. pH indicators can also be used to adapt this methodology to optical sensing methods (Ali et al. 2010).
The pH of the cell culture medium must be tightly controlled for optimal cell health (for mammalian cells, generally 7.4 ± 0.4). Together with oxygen, the pH can yield information about cell growth rate and metabolism, as acidic byproducts of cellular metabolism such as lactic acid and carbonic acid (following CO2 reacting with water) accumulate in the medium, resulting in lower pH. pH is typically monitored via potentiometric and optical sensors. Indeed, the standard red-pink color associated with cell culture is caused by the dissolved pH indicator phenol-red, which adjusts color under certain pH thresholds (in this case, your eye is the optical sensor). Similar indicators can be used in immobilized substrates attached to optical fibers for more practical pH monitoring. The limitations of optical methods include a limited dynamic range, heat instability of some fluorophores, and sensitivity to mediums with high ionic strength (Biechele et al. 2015). Lastly, ion-sensitive field effect transistors can record pH by measuring current changes caused by ion (H+) concentration changes; however, these devices require parallel reference electrodes.
Glucose acts as the principal carbon energy source within a cell-based meat culture system and thus active monitoring of glucose and other metabolites can inform feeding strategy, optimal cell densities, and proliferative rates. As glucose and glutamine are consumed during exponential cell growth, lactate and ammonium, respectively, increase in the medium, which can have prohibitive effects on cell growth and viability. Several methods aimed at decreasing or controlling these byproducts have been developed (Freund and Croughan 2018), although ammonium toxicity is far more potent (2-4 mM) than lactate (20-40 mM) and thus can be a more important target to reduce (Schneider, Marison, and von Stockar 1996). Glucose and a range of metabolites are typically measured via spectroscopic analyses (Figure 8), although some enzymatic methods also exist. The methods primarily used in detecting biological molecules such as infrared, fluorescence, and Raman spectroscopy fundamentally rely on the interaction of electromagnetic waves with molecular bonds which reveal chemical fingerprints based on measured vibrational motion (infrared), scattering of vibrations (Raman), or emitted photons upon excitation (fluorescence). These sensor systems are advantageous as they can be used continually, there is no interaction between the sensor and analyte itself, and they can be multiplexed.
Infrared spectroscopy includes the near- (740-1300 nm) and mid- (1300-15000 nm) infrared wavelengths. Each can detect relevant organic molecules such as glucose and lactate, but certain wavelengths are more useful for molecules containing specific chemical bonding structures (Biechele et al. 2015). Using mid-infrared wavelengths can yield stronger signals and higher resolution for these purposes. Raman spectroscopy relies on electromagnetic waves typically in the visible or near infrared range and can complement infrared methods. In general, implementation of spectroscopic methods can be challenging due to relatively low concentrations of the molecules of interest, the diversity of molecules present, difficulty in calibration due to changing conditions within a live cell culture, and the large amount of data that is generated (Zhao et al. 2015). Therefore, large sets of training data from pilot or spike-in studies may be required in order to apply chemometric statistical techniques that permit identification of individual molecules of interest with high confidence. Data-driven models from chemometric analyses can then feed into a soft sensor (a sensor combined with a software-based algorithm) algorithm for a custom cell-based meat bioprocess.
Similar spectroscopic methods can also be used to detect biomass concentration, including bacterial contaminants, based on scattering or transmission of light through a turbid sample. Near-infrared wavelengths are typically used for larger mammalian cells, with specific wavelengths between 840 and 910 nm as typical culture mediums do not absorb much light in these wavelengths (Ahmed et al. 2014). However, these methods make no determination of cell viability and can be affected by air bubbles or other large particles within the cell culture. These issues can be partially alleviated through the use of impedance sensors where measurement of a sinusoidal electrical field between two electrodes is minimally affected by objects such as air bubbles with no plasma membrane. Impedance methods can be adapted for measurement of cell densities within a solid scaffold (discussed in Series III), where spectroscopy may otherwise fail. Lastly, in situ microscopy and flow cytometry can also be incorporated into a bioprocessing scheme if additional morphological, size, or viability data are needed (Biechele et al. 2015), although the practicality of implementing these methods for cell-based meat may be limited.
Recent advances in genetic engineering permit the design of genetically encoded biosensors that can sense extrinsic (e.g. shear stress) or intrinsic (e.g. oxidative damage) characteristics of cells (Polizzi and Kontoravdi 2015). Fundamentally, genetically encoded sensors rely on the transcription of specific genes tied to a specific characteristic. Using these gene promoters to drive expression of a detectable reporter protein such as green fluorescent protein (GFP) or product of an enzymatic reaction (e.g. light from luciferase) can provide critical insight into a cell population’s interaction with its environment. Some examples include genes involved in the unfolded protein response to sense glucose or amino acid starvation (Kaufman et al. 2002), hypoxia response genes (Liu et al. 2005), mechanical stress genes, and protein production (i.e. endoplasmic reticulum stress response) genes (Du et al. 2013). Building biosensors into an optimized cell line may offer several advantages over the aforementioned methods, including savings on cost, calibration, sterilization, time sensitivity, and flexibility. However, inhibitory metabolic burden from a constitutively active biosensor would need to be considered. Whether or not a product can be consumed with these transgenes in them is yet to be determined by regulation (discussed in Series V). However receiving Generally Recognized as Safe (GRAS) designation by the FDA may not be insurmountable, as many of these biosensors are derived from animal proteins (e.g. GFP from A. victoria and luciferase from P. pyralis) rather than being purely synthetic.
Incorporating automation into a bioprocess can unlock significant cost savings on manual labor time, reagent use, lab space, and general gains from limiting batch-to-batch variation and standardizing quality control. Automation can also facilitate the prevention of contamination and ease regulatory compliance when implemented in a closed system. Automation is just starting to gain traction in the cell therapy and regenerative medicine fields. Several products now exist that enable closed, end-to-end manufacturing of therapeutic doses of adipose-derived stem cells from adipose tissue biopsies (Fraser et al. 2014) or general stem cell expansion with high degree of customization and parallelization. Despite these advances, cell-based meat manufacturing fundamentally involves orders of magnitude higher numbers of cells and thus may require significant engineering customization, especially in regards to cell scaling, quality control, harvesting (discussed in Series IV), and product formulation (discussed in Series V). These customizations may require considerable capital expenditure and may therefore be better suited to be built out as hardware or software offerings from existing life science companies and technology stakeholders rather than internally within a startup. Applying learnings from the existing lower volume bioprocess industry and the larger volume food and agtech industries, where automation is abundant, may be favorable for implementation in cell-based meat production.
In general, automation should be designed to be implemented into the manufacturing process from the ground up, rather than retroactively replacing highly manual steps (Ball et al. 2018). While species or product specificity may dictate a custom implementation, the general bioprocess as described throughout this series is likely to be conserved. Thus, industry-wide collaboration toward identification of critical process parameters and the composition of their analytical frameworks to guide automation implementation would pay dividends for the entire industry. Similarly, these parameters may guide industry standardization across software (open-source), sensor systems, or other hardware components, although sacrificing the potential for intellectual property development would need to be considered. Collaborative efforts are also needed to establish cost of goods (COGS) models for cell-based meat from which high-cost areas or bottlenecks within the bioprocess can be identified and prioritized for automation or engineering optimization. The nascent nature of the industry may reveal that some critical process parameters need to be better defined, however eventual automation throughout the industry is likely to be necessary to achieve price parity with conventional animal meats.
While an academic cell culture lab may involve several individuals opening and closing an incubator door and walking freely through open air with containers of cells, an industrialized bioprocess is largely sealed off from the outside world. Notwithstanding previously discussed single-use bioreactor systems, a large effort has been dedicated to developing preventative controls and contamination monitoring methods so as to not incur losses in product, production time, or cost of decontamination, and to ensure adherence to regulatory and safety guidelines in other biological processing industries. These controls and practices should be translatable to the cell-based meat industry.
The most common forms of contamination are bacterial (e.g. mycoplasma), fungal, viral, or cell cross-contamination, with some concern for transmissible spongiform encephalopathies (Piccardo et al. 2011). As discussed previously, spectroscopic sensors to detect bacterial contamination may be utilized, as well as other methods such as polymerase chain reaction or immuno-based assays (e.g. ELISA) for detection of specific contaminants or foreign adventitious agents (discussed in Series IV). While sterility is ideal, it is possible that acceptable non-adverse contamination (e.g. tolerably low levels or non-pathogenic in nature) occurs, and there is always a risk for contamination events. Although antibiotics and antimycotics can be used for both treatment and prevention, they can lead to variations in gene expression (Ryu et al. 2017), proliferation (Cohen et al. 2006), and differentiation (Y. Chang, Goldberg, and Caplan 2006). Most importantly, proper practice of aseptic technique, implementation of preventative controls (discussed below), and sterilization strategies make antibiotic and antimycotic use in cell culture mediums unnecessary. As such, they will not be included in a cell-based meat bioprocess (discussed further in Series IV). It is possible that antimicrobials may be used in maintaining aseptic surfaces, however.
Different components of the bioreactor are susceptible to entry of various contaminants and thus require preventative barriers to entry, which maintain the sterile boundary (Figure 9). For gas or medium inlets and outlets, various membranes or filters can be used to capture potential contaminants via size exclusion. For instance, a 0.2 µm pore size filter permits steady flow of gases and fluids but will prevent passage of cells as small as bacteria. Smaller pore size filters (e.g. 20 nm) also exist for viral retention. Filters for medium are used primarily when steam sterilization (discussed below) may potentially damage heat-sensitive ingredients in the medium. Gas filters are commonly made of hydrophobic membranes such as PTFE to prevent passage of aqueous aerosols. These filters and other connective parts are commonly made of materials that can themselves be sterilized via gamma irradiation or autoclaving to ensure they are free of contaminants upon installation. Other forms of sterilization used in the food industry such as pulsed electric fields, which cause cellular permeabilization, may be adapted for prevention of bacteria and bacterial spore contamination of cell culture media (Reineke et al. 2015).
In addition to filtering and radiation-based sterilization strategies, thermal sterilization via steam is the most commonly used method. Thermal sterilization is often performed after cleaning of vessels or process components, adhering to clean-in-place guidelines where equipment is washed with high-pressure water jets, rinsed in alkaline and acidic solutions, and dried. Steam sterilization can be performed directly at inlets and outlets, in an empty vessel, on medium within a vessel, or on medium flowing through a continuous process line. When performed both upstream and downstream throughout an entire bioprocessing line, the act is referred to as steam-in-place. Steam sterilization parameters, estimated by measuring the death kinetics of the heat resistant bacteria B. stearothermophilus, are dependent on many variables including time, temperature, moisture (i.e. saturated steam), direct steam contact, air removal, and drying. Differences in the heating and cooling requirements and times can vary depending on the scale and other process variables. Due to the high temperatures required (usually ≥121ºC), these variables can influence the total energy demand of a clean meat facility at scale, affecting its carbon footprint (discussed in Series VI). Once sterilization has been achieved, the bioreactors operate under positive pressure, typically in the form of an inert nitrogen gas, in order to prevent entry of contaminants. If contamination is detected, investigation into the source is performed (e.g. faulty filters, micro-cracks, improper sealing) and components are cleaned and re-sterilized.
The next discussion series will focus on bioengineering considerations for clean meat.
- Ahmed, Asif, Jo V. Rushworth, Natalie A. Hirst, and Paul A. Millner. 2014. “Biosensors for Whole-Cell Bacterial Detection.” Clinical Microbiology Reviews 27 (3): 631–46.
- Alimperti, Stella, Pedro Lei, Yuan Wen, Jun Tian, Andrew M. Campbell, and Stelios T. Andreadis. 2014. “Serum-Free Spheroid Suspension Culture Maintains Mesenchymal Stem Cell Proliferation and Differentiation Potential.” Biotechnology Progress 30 (4): 974–83.
- Ali, Reham, Sayed M. Saleh, Robert J. Meier, Hassan A. Azab, Ibraheim I. Abdelgawad, and Otto S. Wolfbeis. 2010. “Upconverting Nanoparticle Based Optical Sensor for Carbon Dioxide.” Sensors and Actuators. B, Chemical 150 (1): 126–31.
- Ball, Oliver, Sarah Robinson, Kim Bure, David A. Brindley, and David Mccall. 2018. “Bioprocessing Automation in Cell Therapy Manufacturing: Outcomes of Special Interest Group Automation Workshop.” Cytotherapy 20 (4): 592–99.
- Biechele, Philipp, Christoph Busse, Dörte Solle, Thomas Scheper, and Kenneth Reardon. 2015. “Sensor Systems for Bioprocess Monitoring.” Engineering in Life Sciences 15 (5): 469–88.
- Bonab, Mandana Mohyeddin, Kamran Alimoghaddam, Fatemeh Talebian, Syed Hamid Ghaffari, Ardeshir Ghavamzadeh, and Behrouz Nikbin. 2006. “Aging of Mesenchymal Stem Cell in Vitro.” BMC Cell Biology 7 (March): 14.
- Chal, Jérome, and Olivier Pourquié. 2017. “Making Muscle: Skeletal Myogenesis in Vivo and in Vitro.” Development 144 (12): 2104–22.
- Chang, David, Ryan Fox, Ethan Hicks, Rachel Ferguson, Kevin Chang, Douglas Osborne, Weiwei Hu, and Orlin D. Velev. 2017. “Investigation of Interfacial Properties of Pure and Mixed Poloxamers for Surfactant-Mediated Shear Protection of Mammalian Cells.” Colloids and Surfaces. B, Biointerfaces 156 (August): 358–65.
- Chang, Yuhan, Victor M. Goldberg, and Arnold I. Caplan. 2006. “Toxic Effects of Gentamicin on Marrow-Derived Human Mesenchymal Stem Cells.” Clinical Orthopaedics and Related Research 452 (November): 242–49.
- Chapman, Lloyd A. C., Rebecca J. Shipley, Jonathan P. Whiteley, Marianne J. Ellis, Helen M. Byrne, and Sarah L. Waters. 2014. “Optimising Cell Aggregate Expansion in a Perfused Hollow Fibre Bioreactor via Mathematical Modelling.” PloS One 9 (8): e105813.
- Cheng, Cindy S., Yasser El-Abd, Khanh Bui, Young-Eun Hyun, Rebecca Harbuck Hughes, William E. Kraus, and George A. Truskey. 2014. “Conditions That Promote Primary Human Skeletal Myoblast Culture and Muscle Differentiation in Vitro.” American Journal of Physiology. Cell Physiology 306 (4): C385–95.
- Cohen, Shahar, Ali Samadikuchaksaraei, Julia M. Polak, and Anne E. Bishop. 2006. “Antibiotics Reduce the Growth Rate and Differentiation of Embryonic Stem Cell Cultures.” Tissue Engineering 12 (7): 2025–30.
- Csaszar, Elizabeth, Daniel C. Kirouac, Mei Yu, Weijia Wang, Wenlian Qiao, Michael P. Cooke, Anthony E. Boitano, Caryn Ito, and Peter W. Zandstra. 2012. “Rapid Expansion of Human Hematopoietic Stem Cells by Automated Control of Inhibitory Feedback Signaling.” Cell Stem Cell 10 (2): 218–29.
- Du, Zhimei, David Treiber, Rebecca E. McCoy, Amanda K. Miller, Mei Han, Feng He, Sarah Domnitz, Carole Heath, and Pranhitha Reddy. 2013. “Non-Invasive UPR Monitoring System and Its Applications in CHO Production Cultures.” Biotechnology and Bioengineering 110 (8): 2184–94.
- Fisher, Adam C., Mark-Henry Kamga, Cyrus Agarabi, Kurt Brorson, Sau L. Lee, and Seongkyu Yoon. 2019. “The Current Scientific and Regulatory Landscape in Advancing Integrated Continuous Biopharmaceutical Manufacturing.” Trends in Biotechnology 37 (3): 253–67.
- Frahm, Björn. 2014. “Seed Train Optimization for Cell Culture.” Methods in Molecular Biology 1104: 355–67.
- Fraser, John K., Kevin C. Hicok, Rob Shanahan, Min Zhu, Scott Miller, and Douglas M. Arm. 2014. “The Celution® System: Automated Processing of Adipose-Derived Regenerative Cells in a Functionally Closed System.” Advances in Wound Care: The Journal for Prevention and Healing 3 (1): 38–45.
- Freund, Nathaniel W., and Matthew S. Croughan. 2018. “A Simple Method to Reduce Both Lactic Acid and Ammonium Production in Industrial Animal Cell Culture.” International Journal of Molecular Sciences 19 (2). https://doi.org/10.3390/ijms19020385.
- Galipeau, Jacques, and Luc Sensébé. 2018. “Mesenchymal Stromal Cells: Clinical Challenges and Therapeutic Opportunities.” Cell Stem Cell 22 (6): 824–33.
- Genovese, N.J., Schulze, E.N., Desmet, D.N. (2019). "Compositions and methods for increasing the efficiency of cell cultures used for food production." Assigned to Memphis Meats, Inc. World Patent 2019014652:A1.
- Han, Xiaoning, Michael Chen, Fushun Wang, Martha Windrem, Su Wang, Steven Shanz, Qiwu Xu, et al. 2013. “Forebrain Engraftment by Human Glial Progenitor Cells Enhances Synaptic Plasticity and Learning in Adult Mice.” Cell Stem Cell 12 (3): 342–53.
- Hosoyama, Tohru, Jered V. McGivern, Jonathan M. Van Dyke, Allison D. Ebert, and Masatoshi Suzuki. 2014. “Derivation of Myogenic Progenitors Directly from Human Pluripotent Stem Cells Using a Sphere-Based Culture.” Stem Cells Translational Medicine 3 (5): 564–74.
- Hu, Weiwei, Claudia Berdugo, and Jeffrey J. Chalmers. 2011. “The Potential of Hydrodynamic Damage to Animal Cells of Industrial Relevance: Current Understanding.” Cytotechnology 63 (5): 445–60.
- Jossen, Valentin, Christian van den Bos, Regine Eibl, and Dieter Eibl. 2018. “Manufacturing Human Mesenchymal Stem Cells at Clinical Scale: Process and Regulatory Challenges.” Applied Microbiology and Biotechnology 102 (9): 3981–94.
- Kaufman, Randal J., Donalyn Scheuner, Martin Schröder, Xiaohua Shen, Kyungho Lee, Chuan Yin Liu, and Stacey M. Arnold. 2002. “The Unfolded Protein Response in Nutrient Sensing and Differentiation.” Nature Reviews. Molecular Cell Biology 3 (6): 411–21.
- Kim, Mee-Hae, and Masahiro Kino-Oka. 2018. “Bioprocessing Strategies for Pluripotent Stem Cells Based on Waddington’s Epigenetic Landscape.” Trends in Biotechnology 36 (1): 89–104.
- King, James A., and William M. Miller. 2007. “Bioreactor Development for Stem Cell Expansion and Controlled Differentiation.” Current Opinion in Chemical Biology 11 (4): 394–98.
- Kovalevich, Jane, and Dianne Langford. 2013. “Considerations for the Use of SH-SY5Y Neuroblastoma Cells in Neurobiology.” Methods in Molecular Biology 1078: 9–21.
- Lee, Namil, Jongoh Shin, Jin Hyoung Park, Gyun Min Lee, Suhyung Cho, and Byung-Kwan Cho. 2016. “Targeted Gene Deletion Using DNA-Free RNA-Guided Cas9 Nuclease Accelerates Adaptation of CHO Cells to Suspension Culture.” ACS Synthetic Biology 5 (11): 1211–19.
- Lin, Haishuang, Qiang Li, Qian Du, Ou Wang, Zhanqi Wang, Leonard Akert, Mark A. Carlson, et al. 2019. “Integrated Generation of Induced Pluripotent Stem Cells in a Low-Cost Device.” Biomaterials 189 (January): 23–36.
- Lipsitz, Yonatan Y., Curtis Woodford, Ting Yin, Jacob H. Hanna, and Peter W. Zandstra. 2018. “Modulating Cell State to Enhance Suspension Expansion of Human Pluripotent Stem Cells.” Proceedings of the National Academy of Sciences of the United States of America 115 (25): 6369–74.
- Li, Qiang, Haishuang Lin, Qian Du, Kan Liu, Ou Wang, Catelyn Evans, Hannah Christian, Chi Zhang, and Yuguo Lei. 2018. “Scalable and Physiologically Relevant Microenvironments for Human Pluripotent Stem Cell Expansion and Differentiation.” Biofabrication 10 (2): 025006.
- Liu, Junye, Runjiang Qu, Masakazu Ogura, Toru Shibata, Hiroshi Harada, and Masahiro Hiraoka. 2005. “Real-Time Imaging of Hypoxia-Inducible Factor-1 Activity in Tumor Xenografts.” Journal of Radiation Research 46 (1): 93–102.
- Martin, Yves, and Patrick Vermette. 2005. “Bioreactors for Tissue Mass Culture: Design, Characterization, and Recent Advances.” Biomaterials 26 (35): 7481–7503.
- Matsunaga, Naoki, Kenjiro Kano, Yasuyuki Maki, and Toshiaki Dobashi. 2009. “Estimation of Dissolved Carbon Dioxide Stripping in a Large Bioreactor Using Model Medium.” Journal of Bioscience and Bioengineering 107 (4): 419–24.
- Meyer, Hans-Peter, Wolfgang Minas, and Diego Schmidhalter. 2017. “Industrial-Scale Fermentation.” In Industrial Biotechnology, edited by Christoph Wittmann and James C. Liao, 349:1–53. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA.
- Nerem, R. M. 1991. “Shear Force and Its Effect on Cell Structure and Function.” ASGSB Bulletin: Publication of the American Society for Gravitational and Space Biology 4 (2): 87–94.
- O’Mara, P., A. Farrell, J. Bones, and K. Twomey. 2018. “Staying Alive! Sensors Used for Monitoring Cell Health in Bioreactors.” Talanta 176 (January): 130–39.
- Ozturk, S. S. 1996. “Engineering Challenges in High Density Cell Culture Systems.” Cytotechnology 22 (1-3): 3–16.
- Papoutsakis, E. T. 1991. “Fluid-Mechanical Damage of Animal Cells in Bioreactors.” Trends in Biotechnology 9 (12): 427–37.
- Park, Yong Bin, Yoon Young Kim, Sun Kyung Oh, Sun Gan Chung, Seung Yup Ku, Seok Hyun Kim, Young Min Choi, and Shin Yong Moon. 2008. “Alterations of Proliferative and Differentiation Potentials of Human Embryonic Stem Cells during Long-Term Culture.” Experimental & Molecular Medicine 40 (1): 98–108.
- Pattison, R. N., J. Swamy, B. Mendenhall, C. Hwang, and B. T. Frohlich. 2000. “Measurement and Control of Dissolved Carbon Dioxide in Mammalian Cell Culture Processes Using an in Situ Fiber Optic Chemical Sensor.” Biotechnology Progress 16 (5): 769–74.
- Piccardo, Pedro, Larisa Cervenakova, Irina Vasilyeva, Oksana Yakovleva, Igor Bacik, Juraj Cervenak, Carroll McKenzie, et al. 2011. “Candidate Cell Substrates, Vaccine Production, and Transmissible Spongiform Encephalopathies.” Emerging Infectious Diseases 17 (12): 2262–69.
- Polizzi, Karen M., and Cleo Kontoravdi. 2015. “Genetically-Encoded Biosensors for Monitoring Cellular Stress in Bioprocessing.” Current Opinion in Biotechnology 31 (February): 50–56.
- Qu, Ying, Bingchen Han, Yi Yu, Weiwu Yao, Shikha Bose, Beth Y. Karlan, Armando E. Giuliano, and Xiaojiang Cui. 2015. “Evaluation of MCF10A as a Reliable Model for Normal Human Mammary Epithelial Cells.” PloS One 10 (7): e0131285.
- Rameez, Shahid, Sigma S. Mostafa, Christopher Miller, and Abhinav A. Shukla. 2014. “High-Throughput Miniaturized Bioreactors for Cell Culture Process Development: Reproducibility, Scalability, and Control.” Biotechnology Progress 30 (3): 718–27.
- Reineke, Kai, Felix Schottroff, Nicolas Meneses, and Dietrich Knorr. 2015. “Sterilization of Liquid Foods by Pulsed Electric Fields-an Innovative Ultra-High Temperature Process.” Frontiers in Microbiology 6 (May): 400.
- Rubio, N., Datar, I., Stachura, D., and Krueger, K. 2019. “Cell-Based Fish: A Novel Approach to Seafood Production and an Opportunity for Cellular Agriculture.” Preprints, doi: 10.20944/preprints201811.0326.v1.
- Rubio, Natalie R., Kyle D. Fish, Barry A. Trimmer, and David L. Kaplan. 2019. “In Vitro Insect Muscle for Tissue Engineering Applications.” ACS Biomaterials Science & Engineering 5 (2): 1071–82.
- Rubio, Natalie R., Kyle D. Fish, Barry A. Trimmer, and David L. Kaplan. 2019. “Possibilities for Engineered Insect Tissue as a Food Source.” Frontiers in Sustainable Food Systems 3:24 doi: 10.3389/fsufs.2019.00024
- Ryu, Ann H., Walter L. Eckalbar, Anat Kreimer, Nir Yosef, and Nadav Ahituv. 2017. “Use Antibiotics in Cell Culture with Caution: Genome-Wide Identification of Antibiotic-Induced Changes in Gene Expression and Regulation.” Scientific Reports 7 (1): 7533.
- Schneider, M., I. W. Marison, and U. von Stockar. 1996. “The Importance of Ammonia in Mammalian Cell Culture.” Journal of Biotechnology 46 (3): 161–85.
- Schumpp, B., and E. J. Schlaeger. 1992. “Growth Study of Lactate and Ammonia Double-Resistant Clones of HL-60 Cells.” Cytotechnology 8 (1): 39–44.
- Shafa, Mehdi, Kirsten Sjonnesen, Akihiro Yamashita, Shiying Liu, Marek Michalak, Michael S. Kallos, and Derrick E. Rancourt. 2012. “Expansion and Long-Term Maintenance of Induced Pluripotent Stem Cells in Stirred Suspension Bioreactors.” Journal of Tissue Engineering and Regenerative Medicine 6 (6): 462–72.
- Shahini, Aref, Kalyan Vydiam, Debanik Choudhury, Nika Rajabian, Thy Nguyen, Pedro Lei, and Stelios T. Andreadis. 2018. “Efficient and High Yield Isolation of Myoblasts from Skeletal Muscle.” Stem Cell Research 30 (July): 122–29.
- Sinacore, M. S., D. Drapeau, and S. R. Adamson. 2000. “Adaptation of Mammalian Cells to Growth in Serum-Free Media.” Molecular Biotechnology 15 (3): 249–57.
- Stern, R.A., and Mozdziak, P.E. 2019. "Glutamine synthetase in avian muscle contributes to a positive myogenic response to ammonia compared with mammalian muscle." American Journal of Physiology 317 (1):214-221.
- Stolberg, Sarah, and Kara E. McCloskey. 2009. “Can Shear Stress Direct Stem Cell Fate?” Biotechnology Progress 25 (1): 10–19.
- Tamm, Christoffer, Sara Pijuan Galitó, and Cecilia Annerén. 2013. “A Comparative Study of Protocols for Mouse Embryonic Stem Cell Culturing.” PloS One 8 (12): e81156.
- Tao, Yiwen, Jennifer Shih, Marty Sinacore, Thomas Ryll, and Helena Yusuf-Makagiansar. 2011. “Development and Implementation of a Perfusion-Based High Cell Density Cell Banking Process.” Biotechnology Progress 27 (3): 824–29.
- Tizei, Pedro A. G., Eszter Csibra, Leticia Torres, and Vitor B. Pinheiro. 2016. “Selection Platforms for Directed Evolution in Synthetic Biology.” Biochemical Society Transactions 44 (4): 1165–75.
- Velugula-Yellela, Sai Rashmika, Abasha Williams, Nicholas Trunfio, Chih-Jung Hsu, Brittany Chavez, Seongkyu Yoon, and Cyrus Agarabi. 2018. “Impact of Media and Antifoam Selection on Monoclonal Antibody Production and Quality Using a High Throughput Micro-Bioreactor System.” Biotechnology Progress 34 (1): 262–70.
- Walther, Jason, Rahul Godawat, Chris Hwang, Yuki Abe, Andrew Sinclair, and Konstantin Konstantinov. 2015. “The Business Impact of an Integrated Continuous Biomanufacturing Platform for Recombinant Protein Production.” Journal of Biotechnology 213 (November): 3–12.
- William G. Whitford John J.S. Cadwell. 2011. “The Potential Application of Hollow Fiber Bioreactors to Large-Scale Production,” May. http://www.biopharminternational.com/potential-application-hollow-fiber-bioreactors-large-scale-production.
- Xiaoxia, J. I. N., and Claudia Buser. 2016. Ultra-high density cell banking methods. WIPO 2016044670:A1. World Patent, filed September 17, 2015, and issued March 24, 2016. https://patentimages.storage.googleapis.com/89/11/dc/6ec81015853e7d/WO2016044670A1.pdf.
- Zhang, H. H., S. Kumar, A. H. Barnett, and M. C. Eggo. 2000. “Ceiling Culture of Mature Human Adipocytes: Use in Studies of Adipocyte Functions.” The Journal of Endocrinology 164 (2): 119–28.
- Zhao, Liang, Hsu-Yuan Fu, Weichang Zhou, and Wei-Shou Hu. 2015. “Advances in Process Monitoring Tools for Cell Culture Bioprocesses.” Engineering in Life Sciences 15 (5): 459–68.
- Zweigerdt, Robert, Ruth Olmer, Harmeet Singh, Axel Haverich, and Ulrich Martin. 2011. “Scalable Expansion of Human Pluripotent Stem Cells in Suspension Culture.” Nature Protocols 6 (5): 689–700.
Cell-based Meat Science Discussion Series III: Bioengineering, part 1
The range of meat products on the market exists on a spectrum of structural sophistication. On one end of the spectrum, there are less sophisticated processed products such as chicken nuggets and sausages; in the middle, ground products; and on the other end, filets and steaks. In order to replicate the more sophisticated products, scientists will need to borrow and improve upon technologies from tissue engineering, regenerative medicine, and biomaterials science to recreate the complex multicellular architecture of meat. A review of the core bioengineering biology, scaffolding technologies, and methods to consider for the creation of complex structures are discussed below.
The Extracellular Matrix and Mechanotransduction
As discussed in Series I and II, the initial proliferation of stem cells is an essential part of the cell-based meat production process. How are trillions of stem cells then turned into structured meat via differentiation? In order to understand, background on the extracellular matrix and mechanotransduction is necessary.
In vivo, cells exist within a complex matrix of secreted proteins and proteoglycans called the extracellular matrix (ECM). The ECM has an inherent stiffness that in turn can influence cellular activity via specialized cell membrane proteins called integrins. Integrins act as mechanosensors to mediate downstream effector proteins, leading to the formation of focal adhesion complexes that connect the actomyosin cytoskeleton to the extracellular matrix. The integrin-mediated focal adhesion can be thought of as the midpoint of a tug-of-war between the ECM and a cell’s internal cytoskeleton. These connections collectively mediate a cell’s ability to sense the extracellular environment, leading to downstream signaling that can affect cell polarity, migration, and differentiation (Handorf et al., 2015; Sun et al., 2016). Altogether, this process is referred to as mechanotransduction (Figure 1).
During embryogenesis and development, cells multiply and become specialized (i.e. differentiate) in part via cues from their extracellular environment. During this time, ECM components and cells themselves are actively in motion as they pass through key developmental landmarks such as the formation of the primitive streak, gastrulation, and tissue specialization (Loganathan et al., 2016). Additional factors such as ECM density and gradients, composition, and 3D topography can have large effects on cell behaviors (Rozario and DeSimone, 2010). In essence, as cells become defined, their gene expression patterns dictate the creation and secretion of specified ECM components which in turn act as a feedback mechanism to further dictate cellular differentiation and migration, a process referred to as “dynamic reciprocity”(Bissell et al., 1982). Because components of the early embryo are all stem cells, this means that stem cells are exquisitely sensitive to ECM cues. Indeed, the regulation and maintenance of stem cells in the adult body is highly dependent on the ECM components that make up the stem cell niche, where each tissue’s niche typically contains a unique set of ECM components (Gattazzo et al., 2014).
Over the last two decades, a suite of studies have demonstrated the critical role of the ECM in the regulation of stemness and differentiation across all of the relevant cell types for cell-based meat production: pluripotent stem cells (Wang et al., 2015), mesenchymal stem cells (Engler et al., 2006), satellite cells (Calve et al., 2010), and adipogenic stem cells (Guneta et al., 2016). By mimicking in vitro the ECM stiffness and protein composition of a specified stem cell niche microenvironment, stem cells can be guided into predictable lineages. This biology, together with changes in the cell culture medium composition (discussed in Series IV), will assist in driving the future creation of structured, 3D cell-based meat products.
During the proliferation phase, anchorage-dependent stem cells are to be grown in bioreactors at large scales. As discussed in Series II, this non-native environment can lead to anoikis if cells are not adapted to suspension growth, grown as spheroids, or otherwise tricked into anchorage independence via small molecules such as Rho Kinase (ROCK) inhibitors. One commonly used method to bypass activation of anoikis is through the use of microcarriers. Microcarriers are small bead-like structures typically 100-400µm in diameter that permit attachment of cells via mimicry of ECM characteristics such as stiffness, topography, and porosity (discussed later, (McKee and Chaudhry, 2017; Rafiq et al., 2013). For instance, microcarrier topography can be designed with nooks to prevent shear stress and patterned topography to assist cell alignment and polarity (Figure 2, Wu et al., 2018). They are typically made from materials such as polysterene, polyacrylamide, glass, or dextran, but can also be made from other plant-derived biomaterials (discussed later) or materials which can be enzymatically dissolved or chemically-degraded (Rodrigues et al., 2019). The microcarriers are themselves often coated with ECM proteins or charged molecules to assist in cell attachment. Other materials exist which aim to accomplish the same goals as microcarriers, such as thermo-responsive nanobridges that are conjugated to ECM proteins (Harkness et al., 2019). These permit growth of cells in aggregates of a controlled size, which can later be dissociated and passaged in a cyclical nature following temperature-induced degradation and re-assembly.
Microcarriers are advantageous in bioreactor culture because they provide a large surface area to volume ratio, permitting high densities of cells relative to 2D culture and are able to be used in flexible (e.g. batch, fed-batch, perfusion) and controllable bioprocessing pipelines. Expansion of cells using microcarriers is relatively straightforward, either by the addition of more microcarriers where cells undergo bead-to-bead transfer (Verbruggen et al., 2018), or via enzymatic dissociation and passaging of cells to larger vessels via a seed train process (Oh et al., 2009; Rafiq et al., 2013). Furthermore, differentiation can occur on the microcarriers themselves (Park et al., 2014; Torgan et al., 2000), triggered by changes in media components, microcarrier characteristics, or shear forces via mechanotransduction (Jossen et al., 2014). Thus, microcarriers offer immense potential in scaling relevant stem cell populations and for providing differentiated cell types for cell-based meat production by leveraging the bioengineering principals discussed throughout. However, decisions on the use of microcarriers will need to be balanced against the intended product, which may influence the strategy surrounding cell proliferation and cell harvesting (discussed in Series V).
In order to produce structured and thick meat products, cells must be transferred to a scaffold. A scaffold ideally permits the attachment and differentiation of cells in a specified manner, mimicking the 3D cytoarchitecture of meat while allowing for continuous perfusion of media, analogous to the vascularization of real tissue. Therefore, considerations for the porosity of the scaffold, mechanical properties, and biocompatibility are paramount. In some cases, the production of differentiated cells on edible or biodegradable microcarriers (Marga et al., 2017, or other methods discussed later) may be chosen for inclusion as blended additives in a variety of unstructured products (discussed in Series V). However, fully replacing conventional animal meats will require replication of structured products such as steaks, requiring the skills of tissue engineers, materials science engineers, and other interdisciplinary scientists for building the methods for these applications.
The biomaterial that makes up a scaffold dictates many of its downstream properties. Biomaterials can be categorized broadly as natural, synthetic, or composite materials consisting of both natural and synthetic materials. Natural biomaterials include those that make up the native vertebrate ECM, such as fibrin, laminin, hyaluronic acid, gelatin (i.e. hydrolyzed collagen), vitronectin, or ECM mixes such as Matrigel. Additional natural biomaterials include alginate (from algae), agarose (from seaweed), silk (from spiders, Johansson et al., 2018), chitosan (from crustaceans, yeast, or fungi), cellulose (many plants), decellularized plant or animal tissues (discussed later), and fungal mycelium (Brodwin, 2018). These natural biomaterials are generally advantageous in that they have high biocompatibility, high degradability, and low immunogenicity; however, only biomaterials derived from vertebrate ECM are functionalized via native cell adhesion motifs. While growing cells on biomaterials such as alginate or chitosan is possible, they lack recognition motifs that promote cell adhesion and migration, limiting their functionality. These cell recognition motifs include the Arg-Gly-Asp (RGD) and Ile-Lys-Val-Ala-Val (IKVAV, (Tashiro et al., 1989) motifs, amongst others less commonly used, derived from corresponding amino acid sequences in fibronectin and laminin, respectively (Bajaj et al., 2014). Integrins on the cell surface serve as the binding receptors for these motifs, mediating cell attachment and downstream signaling (Xiong et al., 2002). Many strategies exist that permit functionalization of non-RGD-containing biomaterials, either by mixing with other functional biomaterials such as gelatin (Enrione et al., 2017), chemical crosslinking with RGD peptides (Tsai et al., 2013), or genetically engineering the RGD motif directly into a biomaterial (Lee et al., 2016; Widhe et al., 2016). Surface functionalization methods such as ion beam deposition or plasma treatment can also be used to create favorable surface properties such as hydrophilicity (Rana et al., 2017). Alternatively, synthetic biomaterials can be used. Synthetic biomaterials permit high tunability for a variety of desired biophysical properties, making them attractive for tissue engineering purposes (Tibbitt and Anseth, 2009; Zhu and Marchant, 2011). Some common examples of synthetic biomaterials include Pluronic, poly(ethylene glycol) (PEG), poly(2-hydroxy ethyl methacrylate) (PHEMA), and poly(acrylamide) (Rosales and Anseth, 2016). However, because these materials do not support cell adhesion, they also need to be functionalized as previously described, and are commonly combined with other natural polymers to form a composite material.
Although purified ECM proteins can be used to coat substrates for 2D cell growth, the use of a single protein component in 3D culture often results in a lack of desirable attributes such as mechanical properties, mesh network size, and degradation (Caliari and Burdick, 2016). Thus, a large effort has been dedicated to controlling these characteristics, discussed below, by creating composite hydrogels composed of synthetic and natural biomaterials.
The vast majority of applied biomaterial use in tissue engineering comes in the form of a hydrogel (Figure 3). A hydrogel is a 3D network of polymer chains that can readily absorb water (up to 1000x their dry weight) due to their hydrophilic properties. They can be engineered to swell or de-swell in response to various external stimuli (e.g. temperature, light, pH, electric field), and tuned for incorporation of a variety of macromolecules (Ahmed, 2015; Bajaj et al., 2014). Because of their aqueous makeup, hydrogels naturally have high permeability for oxygen and permit the flow of water-soluble molecules, exquisitely mimicking soft tissues of the body.
A hydrogel’s mechanical properties are frequently measured with atomic force microscopy to reveal the Young’s modulus value, which defines the material stiffness in relation to stress and strain. In vivo, the Young’s modulus of different tissue types is variable and this helps to determine cell fate via mechanotransduction. For instance, adipose tissue and the brain are soft (~0.2 - 1.0 kPa), skeletal muscle is intermediate (~10 kPa), and bone is hard (~30-45 kPa) tissue. Thus, recapitulating these stiffnesses within a scaffold can direct the differentiation of stem cells. For instance, the growth of mesenchymal stem cells on soft or hard hydrogels can bias their fate into fat or bone, respectively (Engler et al., 2006; Guvendiren and Burdick, 2012). Similarly, muscle satellite cells can self-renew when grown in a substrate that matches the stiffness of their native stem cell niche (Gilbert et al., 2010; Safaee et al., 2017). Tuning of the stiffness can be achieved by increased crosslinking (Figure 4), addition of carbon nanotubes (Shin et al., 2012), graphene (Martín et al., 2017), DNA (Chen and Seelig, 2019), or modification of natural or synthetic polymer materials with photo-crosslinkable side groups. Importantly, these photo-crosslinkable groups permit fast polymerization, allowing encapsulation of cells during a process such as bioprinting (discussed later). Cell-based meat scaffolds may thus be constructed with various composite polymer materials that dictate stiffness in a pre-patterned spatial orientation to replicate the fat, muscle, and connective tissue architecture found in a desired meat product. Indeed, studies have demonstrated the biasing of stem cell fates to bone and fat via stiffness properties within a single hydrogel (Freeman and Kelly, 2017).
Although hydrogels can mimic soft tissues, they are limited in scale. The creation of thick tissues that permit diffusion of oxygen and transport of nutrients and waste in an analogous manner to vascularized tissue in vivo has been challenging and is an active area of research. In general, a scaffold used for transplantation contains pores that permit neovascularization of the tissue once in the body (Bramfeldt et al., 2010). However, a scaffold for cell-based meat may aim to support cell viability via perfusion within a bioreactor (discussed later) rather than in situ vascularization, as the current state of technology is just beginning to understand how to create vascular tissue from stem cells (Wimmer et al., 2019). This means that a scaffold’s mesh network of pores should ideally be interconnected and distributed such that cells can infiltrate the scaffold and lie within 200µm of nutrient access, as this is the upper limit for the mass transfer of oxygen (Martin and Vermette, 2005). Other parameters such as pore shape, volume, and roughness also need to be considered (El-Sherbiny and Yacoub, 2013). Ideally, the recapitulation of the ECM should happen on the scale of the structural ECM components themselves (i.e. 50 - 500nm diameter, (Barnes et al., 2007), while the porosity of the scaffold should be on the micrometer scale to permit cell invasion and migration. This general principle has been challenging to mimic; however, sophisticated techniques for fabricating large hydrogel scaffolds with these properties are coming of age (discussed later). Lastly, given that a tissue created for consumption does not need to be functional inside of a body, a scaffold designed to be less densely populated may be easier to achieve. Once populated, the structure could be compressed at harvesting or further structured into a final product (discussed in Series V).
Careful design considerations have been made in tissue engineering to utilize non-immunogenic, biodegradable materials with biologically inert by-products (as they are intended to be inserted into the body for regenerative medicine purposes, (Bajaj et al., 2014)). Likewise, a scaffold that biodegrades into inert by-products would be desirable for cell-based meat not only to avoid non-edible materials being incorporated into a final product but also by allowing the cells to replace the hydrogel scaffold with their own native ECM. Indeed, hydrogels are typically static substrates that alone fail to dynamically recapitulate the spatiotemporal interactions between a cell and the ECM. One method to overcome this is by incorporating proteolytically degradable crosslinks (Khetan et al., 2013; Patterson and Hubbell, 2010), which permit naturally secreted enzymes such as matrix metalloproteinases to degrade the hydrogel substrate, permitting cell migration and establishment of dynamic reciprocity previously mentioned. A suite of other methods such as photodegradable polymers (Kloxin et al., 2009) and unique chemistries permitting light-mediated crosslinking (Guvendiren and Burdick, 2012) have also been developed by bioengineers, enabling more accurate recapitulation of ECM-cell dynamics.
Bioengineers also attempt to mimic other characteristics of the ECM such as regulated diffusion of soluble secreted signals (Figure 5). In vivo, ECM molecules such as heparan sulfate proteoglycans can bind and sequester growth factors that regulate local cell migration and differentiation. Some hydrogels such as Matrigel, derived from mouse tumor cells, contain these embedded growth factors, albeit in variable quantities and unknown spatial distributions. Techniques such as incorporation of proteins containing photocleavable linkers or photocaged peptides permit precise and sometimes reversible spatiotemporal release of sequestered factors via light (So et al., 2018). However, it’s unclear how feasible these methods would be for cell-based meat production at scale. Rather, covalent tethering of specific growth factors within the hydrogel scaffold (McCall et al., 2012), spatially distributed to mimic the cytoarchitecture of meat, may be able to assist in attachment or guidance of precursor stem cells into their correct location within the scaffold or toward downstream terminally differentiated cell fates.
Many of the natural polymers that can be used as scaffolds are also edible to humans, with several already approved by the FDA for use in food (regulation may differ by region). Thus, edible polymer materials in microcarriers or scaffolds for cell-based meat development are likely to be pursued in order to avoid removing cells from the scaffold (discussed in Series V) or rigorous demonstration of safety for human consumption, as would be needed with some other material types. Research in this direction using edible scaffolds for cell-based meat has already begun. Examples of FDA-approved edible biomaterials include pectin (Munarin et al., 2012), gellan gum (Gong et al., 2009), chitosan, gelatin, cellulose, glucomannan, and alginate, amongst others (Del Valle et al., 2017). Some synthetic polymers such as PEGs are also FDA-approved. As previously mentioned, the majority of these polymers lack functional domains for cell adhesion; however, they can be functionalized with RGD peptides or combined with functional edible components such as gelatin (Enrione et al., 2017). Importantly, these scaffolds also tend to be affordable and scalable in terms of the raw material components, with scale limitations mainly determined by method of fabrication (discussed later). Some companies have independently demonstrated the large scale production of proteins such as collagen using recombinant yeast or bacteria, and this may serve as a future platform for the creation of biomaterial sidestreams used for the cell-based meat industry. Lastly, many of these biomaterials have also been used for tissue engineering of bone (Levengood and Zhang, 2014), which may be applicable for cell-based meat if bone-in products are ever pursued.
How are scaffolds made?
The quest to build human organs from scratch has led to the development of an array of technologies and methods for the reconstruction of complex tissues. In general, two approaches can be considered for biofabrication of a complex tissue: top-down and bottom-up. In top-down approaches, as generally described above, a scaffold is fabricated and cells are seeded onto the scaffold; however, these approaches generally struggle to recapitulate tissue microstructure (Nichol and Khademhosseini, 2009). Alternatively, bottom-up approaches aim to create modular biostructures on the microscale that can be assembled into larger, more complex tissue types. Advances in 3D printing now permit combinatorial approaches of both efforts (Daly and Kelly, 2019; Moroni et al., 2018). At the heart of each method is a concern for issues previously discussed: biomaterial selection, biocompatibility, porosity, etc. The emerging technologies that best handle these issues and those that are most likely to be explored for use in cell-based meat scaffold development such as 3D bioprinting, electrospinning, decellularization, and other considerations, will be discussed in the next section.
- Ahmed, E.M. (2015). Hydrogel: Preparation, characterization, and applications: A review. J. Advert. Res. 6, 105–121.
- Bajaj, P., Schweller, R.M., Khademhosseini, A., West, J.L., and Bashir, R. (2014). 3D biofabrication strategies for tissue engineering and regenerative medicine. Annu. Rev. Biomed. Eng. 16, 247–276.
- Barnes, C.P., Sell, S.A., Boland, E.D., Simpson, D.G., and Bowlin, G.L. (2007). Nanofiber technology: designing the next generation of tissue engineering scaffolds. Adv. Drug Deliv. Rev. 59, 1413–1433.
- Bissell, M.J., Hall, H.G., and Parry, G. (1982). How does the extracellular matrix direct gene expression? J. Theor. Biol. 99, 31–68.
- Bramfeldt, H., Sabra, G., Centis, V., and Vermette, P. (2010). Scaffold vascularization: a challenge for three-dimensional tissue engineering. Curr. Med. Chem. 17, 3944–3967.
- Brodwin, E. (2018). A startup that turns mushrooms into IKEA packaging has introduced a new platform that could change the way lab-grown meat is made. Business Insider.
- Caliari, S.R., and Burdick, J.A. (2016). A practical guide to hydrogels for cell culture. Nat. Methods 13, 405–414.
- Calve, S., Odelberg, S.J., and Simon, H.-G. (2010). A transitional extracellular matrix instructs cell behavior during muscle regeneration. Dev. Biol. 344, 259–271.
- Chen, S., and Seelig, G. (2019). Programmable patterns in a DNA-based reaction-diffusion system.
- Daly, A.C., and Kelly, D.J. (2019). Biofabrication of spatially organised tissues by directing the growth of cellular spheroids within 3D printed polymeric microchambers. Biomaterials 1–37.
- Del Valle, L.J., Díaz, A., and Puiggalí, J. (2017). Hydrogels for Biomedical Applications: Cellulose, Chitosan, and Protein/Peptide Derivatives. Gels 3.
- El-Sherbiny, I.M., and Yacoub, M.H. (2013). Hydrogel scaffolds for tissue engineering: Progress and challenges. Global Cardiology Science and Practice 2013, 38–27.
- Engler, A.J., Sen, S., Sweeney, H.L., and Discher, D.E. (2006). Matrix elasticity directs stem cell lineage specification. Cell 126, 677–689.
- Enrione, J., Blaker, J., Brown, D., Weinstein-Oppenheimer, C., Pepczynska, M., Olguín, Y., Sánchez, E., and Acevedo, C. (2017). Edible Scaffolds Based on Non-Mammalian Biopolymers for Myoblast Growth. Materials 10, 1404–1415.
- Freeman, F.E., and Kelly, D.J. (2017). Tuning Alginate Bioink Stiffness and Composition for Controlled Growth Factor Delivery and to Spatially Direct MSC Fate within Bioprinted Tissues. Sci. Rep. 1–12.
- Gattazzo, F., Urciuolo, A., and Bonaldo, P. (2014). Extracellular matrix: a dynamic microenvironment for stem cell niche. Biochim. Biophys. Acta 1840, 2506–2519.
- Gilbert, P.M., Havenstrite, K.L., Magnusson, K.E.G., Sacco, A., Leonardi, N.A., Kraft, P., Nguyen, N.K., Thrun, S., Lutolf, M.P., and Blau, H.M. (2010). Substrate elasticity regulates skeletal muscle stem cell self-renewal in culture. Science 329, 1078–1081.
- Gong, Y., Wang, C., Lai, R.C., Su, K., Zhang, F., and Wang, D.-A. (2009). An improved injectable polysaccharide hydrogel: modified gellan gum for long-term cartilage regenerationin vitro. J. Mater. Chem. 19, 1968–1977.
- Guneta, V., Loh, Q.L., and Choong, C. (2016). Cell-secreted extracellular matrix formation and differentiation of adipose-derived stem cells in 3D alginate scaffolds with tunable properties. J. Biomed. Mater. Res. A 104, 1090–1101.
- Guvendiren, M., and Burdick, J.A. (2012). Stiffening hydrogels to probe short- and long-term cellular responses to dynamic mechanics. Nat. Commun. 3, 792–799.
- Handorf, A.M., Zhou, Y., Halanski, M.A., and Li, W.-J. (2015). Tissue stiffness dictates development, homeostasis, and disease progression. Organogenesis 11, 1–15.
- Johansson, U., Widhe, M., Shalaly, N.D., Arregui, I.L., Nilebäck, L., Tasiopoulos, C.P., Åstrand, C., Berggren, P.-O., Gasser, C., and Hedhammar, M. (2018). Silk assembly integrates cells into a 3D fibrillar network that promotes cell spreading and proliferation.
- Jossen, V., Pörtner, R., Kaiser, S.C., Kraume, M., Eibl, D., and Eibl, R. (2014). Mass Production of Mesenchymal Stem Cells — Impact of Bioreactor Design and Flow Conditions on Proliferation and Differentiation. In Cells and Biomaterials in Regenerative Medicine, D. Eberli, ed. (InTech),.
- Khetan, S., Guvendiren, M., Legant, W.R., Cohen, D.M., Chen, C.S., and Burdick, J.A. (2013). Degradation-mediated cellular traction directs stem cell fate in covalently crosslinked three-dimensional hydrogels. Nat. Mater. 12, 458–465.
- Kloxin, A.M., Kasko, A.M., Salinas, C.N., and Anseth, K.S. (2009). Photodegradable hydrogels for dynamic tuning of physical and chemical properties. Science 324, 59–63.
- Lee, D.-Y., Lee, H., Kim, Y., Yoo, S.Y., Chung, W.-J., and Kim, G. (2016). Phage as versatile nanoink for printing 3-D cell-laden scaffolds. Acta Biomater. 29, 112–124.
- Levengood, S.L., and Zhang, M. (2014). Chitosan-based scaffolds for bone tissue engineering. J. Mater. Chem. B Mater. Biol. Med. 2, 3161–3184.
- Loganathan, R., Rongish, B.J., Smith, C.M., Filla, M.B., Czirok, A., Bénazéraf, B., and Little, C.D. (2016). Extracellular matrix motion and early morphogenesis. Development 143, 2056–2065.
- Marga, F.S., Purcell, B.P., Forgacs, G., and Forgacs, A. (2017). Edible and animal-product-free microcarriers for engineered meat. US Patent.
- Martin, Y., and Vermette, P. (2005). Bioreactors for tissue mass culture: Design, characterization, and recent advances. Biomaterials 26, 7481–7503.
- Martín, C., Merino, S., González-Domínguez, J.M., Rauti, R., Ballerini, L., Prato, M., and Vázquez, E. (2017). Graphene Improves the Biocompatibility of Polyacrylamide Hydrogels: 3D Polymeric Scaffolds for Neuronal Growth. Sci. Rep. 7, 10942.
- McCall, J.D., Luoma, J.E., and Anseth, K.S. (2012). Covalently tethered transforming growth factor beta in PEG hydrogels promotes chondrogenic differentiation of encapsulated human mesenchymal stem cells. Drug Deliv. Transl. Res. 2, 305–312.
- McKee, C., and Chaudhry, G.R. (2017). Advances and challenges in stem cell culture. Colloids Surf. B Biointerfaces 159, 62–77.
- Moroni, L., Burdick, J.A., Highley, C., Lee, S.J., Morimoto, Y., Takeuchi, S., and Yoo, J.J. (2018). Biofabrication strategies for 3D in vitro models and regenerative medicine. Nature Reviews Materials 1–17.
- Munarin, F., Tanzi, M.C., and Petrini, P. (2012). Advances in biomedical applications of pectin gels. Int. J. Biol. Macromol. 51, 681–689.
- Nichol, J.W., and Khademhosseini, A. (2009). Modular tissue engineering: engineering biological tissues from the bottom up. Soft Matter 5, 1312–1317.
- Oh, S.K.W., Chen, A.K., Mok, Y., Chen, X., Lim, U.-M., Chin, A., Choo, A.B.H., and Reuveny, S. (2009). Long-term microcarrier suspension cultures of human embryonic stem cells. Stem Cell Res. 2, 219–230.
- Park, Y., Chen, Y., Ordovas, L., and Verfaillie, C.M. (2014). Hepatic differentiation of human embryonic stem cells on microcarriers. J. Biotechnol. 174, 39–48.
- Patterson, J., and Hubbell, J.A. (2010). Enhanced proteolytic degradation of molecularly engineered PEG hydrogels in response to MMP-1 and MMP-2. Biomaterials 31, 7836–7845.
- Rafiq, Q.A., Coopman, K., and Hewitt, C.J. (2013). Scale-up of human mesenchymal stem cell culture: current technologies and future challenges. Curr. Opin. Chem. Eng. 2, 8–16.
- Rana, D., Ramasamy, K., Leena, M., Pasricha, R., Manivasagam, G., and Ramalingam, M. (2017). Chapter 21 - Surface Functionalization of Biomaterials (Elsevier Inc.).
- Rosales, A.M., and Anseth, K.S. (2016). The design of reversible hydrogels to capture extracellular matrix dynamics. Nature Reviews Materials 1, 10776–10715.
- Rozario, T., and DeSimone, D.W. (2010). The extracellular matrix in development and morphogenesis: a dynamic view. Dev. Biol. 341, 126–140.
- Safaee, H., Bakooshli, M.A., Davoudi, S., Cheng, R.Y., Martowirogo, A.J., Li, E.W., Simmons, C.A., and Gilbert, P.M. (2017). Tethered Jagged-1 Synergizes with Culture Substrate Stiffness to Modulate Notch-Induced Myogenic Progenitor Differentiation. Cell. Mol. Bioeng. 10, 501–513.
- Shin, S.R., Bae, H., Cha, J.M., Mun, J.Y., Chen, Y.-C., Tekin, H., Shin, H., Farshchi, S., Dokmeci, M.R., Tang, S., et al. (2012). Carbon nanotube reinforced hybrid microgels as scaffold materials for cell encapsulation. ACS Nano 6, 362–372.
- So, W.H., Wong, C.T.T., and Xia, J. (2018). Peptide photocaging: A brief account of the chemistry and biological applications. Chin. Chem. Lett. 29, 1058–1062.
- Sun, Z., Guo, S.S., and Fässler, R. (2016). Integrin-mediated mechanotransduction. J. Cell Biol. 215, 445–456.
- Tashiro, K., Sephel, G.C., Weeks, B., Sasaki, M., Martin, G.R., Kleinman, H.K., and Yamada, Y. (1989). A synthetic peptide containing the IKVAV sequence from the A chain of laminin mediates cell attachment, migration, and neurite outgrowth. J. Biol. Chem. 264, 16174–16182.
- Tibbitt, M.W., and Anseth, K.S. (2009). Hydrogels as extracellular matrix mimics for 3D cell culture. Biotechnol. Bioeng. 103, 655–663.
- Torgan, C.E., Burge, S.S., Collinsworth, A.M., Truskey, G.A., and Kraus, W.E. (2000). Differentiation of mammalian skeletal muscle cells cultured on microcarrier beads in a rotating cell culture system. Med. Biol. Eng. Comput. 38, 583–590.
- Tsai, W.-B., Chen, Y.-R., and Liu, H.-L. (2013). RGD-conjugated crosslinked chitosan scaffolds for culture and osteogenic differentiation of mesenchymal stem cells. J. Taiwan Inst. Chem. Eng. 44, 1–7.
- Verbruggen, S., Luining, D., van Essen, A., and Post, M.J. (2018). Bovine myoblast cell production in a microcarriers-based system. Cytotechnology 70, 503–512.
- Wang, H., Luo, X., and Leighton, J. (2015). Extracellular Matrix and Integrins in Embryonic Stem Cell Differentiation. Biochem. Insights 8, 15–21.
- Widhe, M., Shalaly, N.D., and Hedhammar, M. (2016). A fibronectin mimetic motif improves integrin mediated cell biding to recombinant spider silk matrices. Biomaterials 74, 256–266.
- Wimmer, R.A., Leopoldi, A., Aichinger, M., Wick, N., Hantusch, B., Novatchkova, M., Taubenschmid, J., Mmerle, M.H.X., Esk, C., Bagley, J.A., et al. (2019). Human blood vessel organoids as a model of diabetic vasculopathy. Nature 1–34.
- Wu, C.-Y., Stoecklein, D., Kommajosula, A., Lin, J., Owsley, K., Ganapathysubramanian, B., and Di Carlo, D. (2018). Shaped 3D microcarriers for adherent cell culture and analysis. Microsystems & Nanoengineering 4, 21.
- Xiong, J.-P., Stehle, T., Zhang, R., Joachimiak, A., Frech, M., Goodman, S.L., and Arnaout, M.A. (2002). Crystal structure of the extracellular segment of integrin alpha Vbeta3 in complex with an Arg-Gly-Asp ligand. Science 296, 151–155.
- Zhu, J., and Marchant, R.E. (2011). Design properties of hydrogel tissue-engineering scaffolds. Expert Rev. Med. Devices 8, 607–626.
Cell-based Meat Science Discussion Series III: Bioengineering, part 2
The range of meat products on the market exists on a spectrum of structural sophistication. On one end of the spectrum, there are less sophisticated processed products such as chicken nuggets and sausages; in the middle, ground products; and on the other end, filets and steaks. In order to replicate the more sophisticated products, scientists will need to borrow and improve upon technologies from tissue engineering, regenerative medicine, and biomaterials science to recreate the complex multicellular architecture of meat. Building off of bioengineering and biomaterials knowledge discussed previously, a review of the core methods to consider for the creation of complex multicellular meat products are discussed below.
3D bioprinting is an additive manufacturing technique where pre-polymer solutions or pre-polymer solutions containing cells (i.e. a bioink) are deposited onto a substrate layer-by-layer under the guidance of a computer-aided design (CAD) process. The CAD files typically result from real bioimaging data such as magnetic resonance imaging (MRI) and computer tomography (CT) scans of tissues, but can also be user-generated to form limitless geometry types. Similar imaging strategies can be performed to replicate specific cuts of meat (Ebrahimnejad et al. 2018). There are several types of bioprinting, summarized in Table 1 (Bajaj et al. 2014; Derakhshanfar et al. 2018) and described in detail below (Figure 1).
Bioink is the raw material for 3D bioprinting, composed of cells in combination with some other biological material. There are two major types of bioink materials: scaffold-based and scaffold-free. A scaffold-based bioink is, in essence, a hydrogel that is printed along with cells whereas a scaffold-free bioink contains only large cellular components such as tissue strands or spheroids (Hospodiuk et al. 2017). Cells within a bioink typically exist at a concentration of ~10 million cells per milliliter, constituting ~5% or less of the bioink volume (Moroni et al. 2018), although this can be optimized on a case by case basis to permit enough printed cells to replicate a specific tissue. Importantly, however, not all biomaterials previously discussed fit the parameters for use in a bioink. The main parameters to consider for a bioink include the “bioprintability” or rheological properties (e.g. viscosity, thixotropy), mechanical properties, insolubility in cell culture medium, cost, and manufacturing capability. Because natural biomaterials generally have weak mechanical properties, special considerations need to be made when including them in a bioink. Additionally, each bioprinting method affects these parameters differently, thus the intended application tends to dictate the chosen method. For cell-based meat, a food-grade (discussed in Series IV) bioink would be appropriate.
In extrusion-based bioprinting, an extruder continuously deposits a bioink while the stage or the extruder itself is moved. Bioink deposition can occur via pneumatic or mechanical systems and the 2D ink must be rapidly solidified either chemically (e.g. light) or physically (e.g. temperature) prior to adding a new layer in order to maintain shape without spreading. In general, extrusion-based systems are the most used and versatile of the methods, permitting a wide variety of natural and synthetic biomaterials to be used due to the range (30 mPa•s to 60 x 10^6 mPa•s; for reference, ketchup has a viscosity of 50,000 mPa•s) of printable ink viscosities. Extrusion-based methods fundamentally work by dispensing larger filaments (~150-300µm in diameter) rather than droplets. This permits both scaffold-based or scaffold-free printing, capable of incorporating high cell density bioinks, printed spheroids, or cell-laden microcarriers (Hölzl et al. 2016). However, this also results in poor printing resolution (as low as 100 µm) versus other methods, making intricate replication of complex tissues difficult. Bioinks with shear thinning properties are preferable as shear forces naturally align hydrogel polymers for extrusion; however, careful consideration must be given to the shear force effect on cell viability during extrusion (Hospodiuk et al. 2017). Additionally, bioinks with low adhesion and surface tension are necessary to prevent nozzle clogging. 3D food printers that use extrusion-based bioprinting methods and the technologies (e.g. texture analyzers) used to analyze the food products may also be adaptable for cell-based meat. Finally, the bioprinting of plant-based proteins may be informative for the creation of cell-based meat scaffolds or replication of other mechanical, textural, or organoleptic properties of meat.
Several recent advances show the potential for applying extrusion-based methods toward the creation of thick scaffolds or tissues applicable for cell-based meat production. For instance, researchers have developed hybrid bioprinting devices, where both vascular networks and cells are printed simultaneously under control of independent printing arms equipped with smart sensors to avoid collisions (Yu et al. 2014). This strategy permits continuous medium perfusion through the printed vascular networks while additional tissue is printed. Systems have also been developed where multiple bioinks can be extruded continuously with fast, dynamic switching between diverse bioinks, permitting printing of complex tissues composed of multiple cells and hydrogel materials (Liu et al. 2016). Another challenge in bioprinting thick scaffolds is the weak mechanical properties of natural polymers, resulting in their deformation under their own weight. To this end, the hydrogel can be printed within a second hydrogel that provides structural support (Video 1). The “sacrificial” support hydrogel acts as a Bingham plastic, where it is a solid up until the point of contact with the extrusion nozzle, permitting the printed hydrogel to displace the support hydrogel (Hinton et al. 2015). The support hydrogel can then be removed (i.e. dissolved) by increasing the temperature (e.g. when using gelatin), or applying calcium chelators (e.g. EDTA when using alginate) or enzymes, resulting in a standalone scaffold or cell-laden tissue. Sacrificial gels have also been adopted for the creation of artificial vasculature (Ji et al. 2019). Additionally, the benefits of these aforementioned methods can be combined, enabling bioprinting of human-scale tissues with fewer limitations (Kang et al. 2016). Lastly, as described previously, the spatiotemporal release of biomolecules within a scaffold can assist in biomimicry of the ECM. To this end, 3D printed light-sensitive nanocapsules containing growth factors can be dispersed within a scaffold during printing, permitting guided migration of cells in a spatiotemporally controlled fashion via light (Gupta et al. 2015; Meng et al. 2019). These and other advances in extrusion bioprinting hold great promise for their application to the cell-based meat industry, and at least one company has plans to utilize extrusion-based bioprinting for cell-based meat production.
Stereolithography uses single or multiphoton light sources to rapidly polymerize a bath of light-sensitive pre-polymers. Structures derived from CAD models are recreated via light reflecting off of micromirror galvanometers, which provide feedback to the printing apparatus, enabling precise spatial and temporal control of the polymerization. Polymerization occurs either through direct laser light exposure or exposure through a mask in a bottom-up process of sequential 2D layers (Raman and Bashir 2015). Inclusion of photocrosslinkable biomaterials previously described now permits this technique to be used for scaffold generation or printing of structures from cell-laden pre-polymer baths. The advantages of stereolithography include avoidance of previously described considerations (e.g. viscosity, surface tension, and shear stress through a nozzle), automated control (in maskless methods), high resolution (< 100 µm), and fast printing speed. Disadvantages include potential cytotoxicity from light exposure and a limited but growing repertoire of suitable biomaterials to use. Further developments are also necessary to permit further scaling to more complex 3D constructs as well as derivation of non-cytotoxic photoinitiators that assist in the crosslinking reaction during polymerization (Raman and Bashir 2015).
Recent progress demonstrates the potential for using stereolithography in cell-based meat scaffold production. For instance, combining stereolithography with dielectrophoresis can enable precise spatial control of cells (Bajaj et al. 2013) and advances in microscale continuous projection printing enables sub-10µm resolution objects to be printed on the order of seconds (Soman et al. 2013). Computed axial lithography uses angled image projections that result in concurrent 3D printing of whole structures at high speeds (Kelly et al. 2019). As a non-layered approach, it does not require the use of supportive hydrogels (discussed previously) for mechanically weaker biomaterials and should be readily scalable. Stereolithographic techniques have also recently demonstrated the construction of intricate vasculature using common, photoabsorbable food dyes such as tartrazine and anthrocyanin (Grigoryan et al. 2019). Thus, further development of stereolithographic techniques may permit their use in the cell-based meat industry.
In droplet-based bioprinting, picoliter droplets (10-50µm diameter) are deposited on top of a substrate without direct contact being made between the nozzle and the substrate. Inkjet printing is the most common form of droplet-based bioprinting and can be further divided into whether droplets are created via electric, acoustic, or heat sources (Hospodiuk et al. 2017). Of these, piezoelectric and thermal methods are frequently used, where an electric charge or sharp increase in heat, produces pressure increases at the nozzle, forming droplets. Droplet-based methods have the advantage of precise control of cell numbers distributed in each droplet and high resolution printing (10-50 µm), however, the applications for droplet-based printing of complex structures is diminished due to a low range of bioink viscosities (3.5 - 12 mPa•s) and requirements of low surface tension and rare rheopectic traits (Hospodiuk et al. 2017). For these reasons, it’s unlikely that droplet-based bioprinting would be utilized for cell-based meat.
Laser-assisted bioprinting, also commonly referred to as laser-induced forward transfer (LIFT), uses laser-induced energy transfer to control deposition of bioinks. The LIFT system features an absorbing donor layer comprised of gold or titanium and a bioink layer beneath the donor layer. A focused laser beam vaporizes the donor layer, creating a high-pressure bubble that deposits the bioink to a substrate underneath, where it is subsequently crosslinked (Mandrycky et al. 2016; Moroni et al. 2018). Laser-assisted methods are able to avoid problems with mechanical stresses and are capable of bioprinting viscous bioinks (1 - 300 mPa•s) with high cell viability and high resolution (10 - 100µm, Hölzl et al. 2016). However, the apparatus cost is high and scalability is an issue. For these reasons, laser-assisted methods are less likely to translate to the cell-based meat industry.
Electrospinning is a versatile, low-cost technique where a solution of polymers is passed through a spinneret needle during application of a high electric field. The electric field causes stretching of the polymer via electrostatic forces (Video 2) until a critical point (i.e. Taylor cone) is reached, resulting in the formation of a fiber jet. As the fiber jet is formed, the solvent evaporates off, and the fiber hardens while it is harvested on an electrostatically-grounded collection device (Video 3, Wang et al. 2013). The fiber itself can be made from a variety of synthetic and natural polymers, resulting in porous fiber networks with tunable diameters and high surface area. Electrospinning is unique in that it provides the only way to achieve nanoscale biomimicry of the ECM (50 - 500 nm diameter fibers). Of note, cell-laden biomaterials can also be electrosprayed through a similar process that yields droplet deposition rather than fiber deposition (Weidenbacher et al. 2017), although this is less applicable toward scaffold creation. Lastly, similar fiber production methods are possible such as wet, dry, or melt spinning, which can be used to produce materials such as scaffolds (Farrugia et al. 2013) and hollow fiber membranes (Li et al. 1994) used in bioreactors (discussed in Series II).
Many of the same considerations and principles previously discussed for biomaterials in hydrogel formation, bioinks, and bioprinting also apply to the creation of electrospun scaffolds. For instance, mechanically weak but biocompatible natural polymers are often combined with synthetic polymers. Identifying rapidly evaporating solvents suitable for composite materials can be challenging, however, and the solvents themselves may be cytotoxic (Cheng et al. 2017) or damage the native structure of the polymers (Bürck et al. 2013). Similarly to a bioink, alterations in viscosity, solvent surface tension, and flow rate can affect the fiber characteristics, and alterations in the applied voltage and rotating speed, distance, or structure of the collection device can affect resultant scaffold geometries (Cheng et al. 2017; Khorshidi et al. 2016). Unless otherwise intended, electrospun scaffolds will result in a random arrangement of packed fibers, which can limit cell infiltration, migration, or uniform seeding (Khorshidi et al. 2016). Similar methods used for hydrogels, such as inclusion of protease-degradable polymers can assist in better mimicking native ECM for cell infiltration and migration (Wade et al. 2015). Additionally, a variety of methods have been developed in order to produce electrospun scaffolds with defined structure and purpose, including mixed, multilayer, coaxial, and emulsion electrospinning, and microfluidic spinning, discussed below.
While true biomimicry of the ECM requires nanoscale fibers, the porosity of the scaffold itself, which has a positive linear relationship with fiber diameter, should be on the microscale to permit cell infiltration and perfusion. A fiber network on both nano and microscales can be created via multilayer electrospinning (Figure 2), where different nanofiber and microfiber polymers are electrospun sequentially in layers. Alternatively, mixed electrospinning can be performed where nanofiber and microfiber polymer types are simultaneously electrospun on a collector that permits overlapping collection through lateral movement of the collector (Kidoaki et al. 2005). These techniques can permit or restrict certain cells from infiltrating a scaffold based on pore size (Ju et al. 2010), which may be leveraged for spatial distribution of cell seeding for cell-based meat. Sacrificial biomaterials such as gelatin can also be used as a polymer to create additional pores upon melting.
In coaxial electrospinning, an inner and outer solution is co-electrospun via independent feeding capillaries, forming a compound Taylor cone. One solution typically contains a hydrophobic polymer and the other contains a biological cargo of interest solubilized with hydrophilic polymers (e.g. dextran), resulting in a core-shell structure due to their immiscibility, or inability to mix (Rim et al. 2013). Coaxial electrospun fibers permit trapping of proteins, cells (discussed later), or other biomolecules such that their release kinetics can be varied based on the porosity or biodegradability of the outer shell polymer (Ji et al. 2010), which may serve well for embedding of growth factors for cell-based meat. The viscosity of the solutions, flow rate, and applied electric field strength can all influence the geometry and characteristics of the resultant core-shell fibers. Additionally, multi-layered fibers can be created by co-electrospinning more than 2 solutions (Labbaf et al. 2014). Similar core-shell fibers can be created via emulsion electrospinning where an emulsion of oil, water, surfactant, and biomaterial are co-electrospun. During electrospinning, the droplets in the emulsion coalesce due to increased viscosity of the evaporating oil and applied electric field. This process can produce core-shell fibers that can be embedded with growth factors or drugs, which may be leveraged for cell-based meat scaffolding (Nikmaram et al. 2017).
Microfluidic spinning (Figure 3) relies on differences in a fluid’s surface tension, energy dissipation, and fluidic resistance to produce a 3D coaxial flow between independent sample and sheath flows (Cheng et al. 2017). While similar in principle to coaxial electrospinning, the application of voltage is unnecessary, as the fluidic channel width controls fiber diameter. Thus, microfluidic spinning permits a more favorable environment for natural biomaterials due to the avoidance of harsh solvents. In contrast to electrospinning, microfluidic spinning can more easily achieve uniformity of fiber diameter, as well as tighter control over the shape, porosity, and diameter of the fiber. This allows for simple cell encapsulation, which can assist in cell alignment, proliferation, and growth in a 3D environment, all of which are favorable for cell-based meat production (discussed later). The resultant fibers must be solidified via photopolymerization, crosslinking, or solvent exchange, which somewhat limits the selection of polymers. Nevertheless, easily crosslinked materials such as alginate can be readily used in such a system.
Decellularization is a technique that aims to remove the cells and nucleic acids from a tissue while preserving the native ECM. Thus, the decellularized tissue acts as a scaffold with preserved ultrastructure and similar biophysical and biochemical properties of the original tissue, potentially avoiding previously discussed issues (e.g. porosity, material composition, stiffness, etc) associated with bottom-up approaches. Decellularization has been largely pioneered using animal tissues for the purposes of organ regeneration (Figure 4), however, the technique can also be applied to plant or fungal tissues. As such, it is likely that the knowledge and application of techniques originating from animal tissues could be useful for cell-based meat research and development purposes, while real-world implementation is more likely to utilize plant or fungal tissues.
Decellularization is performed by deploying chemical, physical, or enzymatic methods. Chemicals such as ionic (e.g. SDS), nonionic (e.g Triton X-100), or zwitterionic (e.g. CHAPS) detergents can be used as they assist in solubilizing membranes, disrupting DNA-protein and lipid-protein interactions, or protecting a protein’s native state, respectively (White et al. 2017). However, the harsh nature of these chemicals leads to their use in low amounts or not at all, if possible, as they inherently will also damage ECM proteins (Badylak et al. 2011). In some cases, the use of acids to catalyze hydrolytic degradation of macromolecules, or organic solvents and hypotonic solutions to cause cell lysis can assist in decellularization processes. Physical methods such as freezing and thawing, electroporation, agitation, and sonication can also be applied to assist in cell lysis. Lastly, various enzymes can assist in the decellularization process, including trypsin, dispase, phospholipases, exonucleases, endonucleases, and other proteases, although consideration has to again be paid to balancing the damage done to ECM proteins (Gupta et al. 2018). As different tissues consist of different cell compositions, sizes, and densities, each decellularization protocol needs to be optimized on a case-by-case basis, and may include one or combinations of the methods described above.
In general, the decellularization process is a balance between removing cells and nucleic acids and maintaining the integrity of the native ECM. Near complete removal of these components is critical in order to avoid immune responses from the host in the context of organ transplantation. However, this is less of a concern for cell-based meat as the tissue is dead and ingested rather than intended to survive in a host. Interestingly, some evidence suggests that residual antimicrobial peptides persist in some animal ECM scaffolds, which may instead be leveraged to prevent contamination in vitro (Brennan et al. 2006). In summary, the cell-based meat field can learn from and apply the knowledge gained from decellularization and recellularization processes, discussed below.
The most applicable decellularization techniques for cell-based meat are perfusion and immersion with agitation. Perfusion is typically used for whole organ decellularization, where native vasculature (typically the main organ artery) is co-opted and used as the plumbing for perfusion of decellularization reagents at physiological pressures. This is often performed in a perfusion bioreactor (discussed in Series II) where the physiological pressure ensures that the tissue is not damaged and that the decellularization reagents can effectively permeate all of the preserved vasculature, including capillaries. For tissues without accessible or large vasculature routes (e.g. skeletal muscle, skin), the tissue can be immersed in decellularization reagents and agitated, assisting in permeation of the tissue via diffusion (Garreta et al. 2017). While immersion methods do not require the need for a specialized bioreactor, they often can result in long exposures to the decellularization reagents and intracellular release of native proteases that can damage the ECM scaffold (Gupta et al. 2018).
Decellularization has come of age since the first demonstration of a decellularized rat heart in 2008 (Ott et al. 2008). Since then, decellularization of large, complex tissues such as human hearts (Guyette et al. 2016) and limbs (Gerli et al. 2018) has been achieved, as well as decellularization of cell-based meat-relevant tissue types such as whole muscles (Zhang et al. 2016). Information on the decellularized scaffold can be gleaned from microCT, scanning electron microscopy, atomic force microscopy, and immunohistochemistry, which yields information about the 3D architecture, biomechanical properties, and composition of the ECM, respectively (Garreta et al. 2017). This information can be leveraged for the recreation of scaffolds for cell-based meat, particularly through characterization of decellularized skeletal muscle (Wolf et al. 2012) and specific cuts of meat. Additionally, the information may be used in bottom-up scaffold approaches such as the creation of CAD models for 3D bioprinting or the solubilization of the native decellularized ECM itself for use in bioinks (Pati et al. 2014) or electrospinning (Young et al. 2017).
While decellularization has become relatively straightforward, a recellularization process may require additional optimizations in cell delivery and bioreactor engineering. For recellularization, cells are typically delivered via the vascular perfusion line at or below physiological flow rates over multiple infusions. Physiological flow rates assist in preventing structural damage to the ECM and protecting cells from shear stress, and these techniques have resulted in seeding efficiencies of organ parenchyma above 90% (Bijonowski et al. 2013). Pre-coating of the scaffold with biomaterials such as chitosan, collagen, gelatin, or RGD peptides can additionally assist in increasing reseeding efficiency (Gupta et al. 2018). As a tissue is recellularized, flow pressure may need to be dynamically adjusted as porosity becomes limited (due to cell attachment), and monitoring systems may need to be developed for this purpose (Lawrence et al. 2009). Additionally, the establishment of endothelial cells and vasculature may require pulsatile flow to more accurately mimic the experienced physiological environment of these cell types. However, it’s uncertain if scaffold endothelialization would be necessary for cell-based meat production (Badylak et al. 2011). At least one company in the field has cited creation of vasculature for their products.
One of the advantages of using a decellularized animal tissue as a scaffold is that it retains the “zip code” locations of the native cytoarchitecture encoded via residual embedded growth factors, mechanical properties, and other ECM characteristics previously discussed. Therefore, the process of recellularization is highly self-organized but still commands consideration for a cell population’s differentiation state prior to recellularization. All of the starting cell types desirable for cell-based meat production (discussed in Series I) have been utilized for recellularization, including myoblasts (Jank et al. 2015), mesenchymal stem cells (K et al. 2019), embryonic stem cells (Nakayama et al. 2013), and induced pluripotent stem cells (Jaramillo et al. 2018). Indeed, similarly to experiments on hydrogel scaffolds, evidence suggests that recellularization of a decellularized animal tissue scaffold with pluripotent stem cells is sufficient to direct the differentiation toward the native tissue type, increasing expression of relevant cell type markers and functionality versus 2D protocols (Jaramillo et al. 2018), as well as assemble native substructures due to local microenvironments (Nakayama et al. 2013). Likewise, recellularization with multipotent progenitors such as mesenchymal stem cells or induced pluripotent stem cell-derived progenitors can be directed into functional tissues made up of a variety of differentiated cell types (K et al. 2019; Kitano et al. 2017). Successful recellularization (and subsequent functional transplantation) has been performed on tissues as large as adult pig lungs in perfusion bioreactors up to dozens of liters in volume, suggesting that the process is scalable (Nichols et al. 2018). Thus, adoption of learned principles from recellularization or recreation of a decellularized scaffold via methods such as 3D printing with solubilized native ECM (Choi et al. 2016; Choi et al. 2019) should be highly applicable for cell-based meat research and development.
Use of decellularized scaffolds from animals has several limitations. For instance, the composition of a decellularized scaffold can vary between individuals and be affected by age and protocol irreproducibility (Gershlak et al. 2017). Most importantly, however, the supply is limited and thus expensive, and reconstructing an ECM containing up to hundreds of proteins is not feasible (Nakayama et al. 2013). For these reasons, plants have been an attractive alternative for decellularization strategies, as their cell walls are composed of abundant biocompatible polysaccharides such as cellulose, pectin, and hemicellulose, and native vasculature similar to animals that follows Murray’s Law, allowing perfusion (Figure 5). Indeed, in combination with functionalization methods previously discussed, attachment of mammalian cells onto decellularized plant scaffolds has been demonstrated using a variety of plant stems, leaves, or hypanthium tissues (Fontana et al. 2017; Modulevsky et al. 2014). Functionalized plant scaffolds have demonstrated long-term viability and cell proliferation, although differences in native stiffness, hydrophilicity, topography, and pore sizes can influence their success (Fontana et al. 2017). The vast variety of plants to choose from may ensure that different tissue architectures (e.g. celery for muscle fibers) can be recapitulated and future genetic engineering efforts could modify plants to express biocompatible protein domains (e.g. RGD), as done in silk (Widhe et al. 2016). Importantly, construction of plant scaffolds can be readily scaled simply by using larger or more abundant plant tissues, or processing of raw plant materials to create protein- or cellulose-based scaffolds using previously discussed methods (Krona et al. 2017). Plant-based materials will likely be significantly more cost-efficient at scale versus their animal ECM counterparts, as the processing and use of abundant raw plant materials such as cellulose or starches for tissue engineering are well characterized (Jovic et al. 2019). Similarly, the use of fungal mycelium may serve as a scalable and affordable scaffolding substrate, without the requirement for decellularization (Figure 6). The company Atlast Food Co was recently founded in 2019 to explore this possibility. Human control of the species strain in combination with temperature, carbon dioxide, humidity, airflow, or sugar source can enable the growth of predictable structures. Thus, by borrowing techniques pioneered for human organ generation and leveraging the plant and fungal kingdoms for practicality, use of prefabricated scaffolds by nature may be the most likely to take hold in the cell-based meat industry.
In general, deriving cells from stem cells in vitro results in a variety of immature phenotypes such as size, shape, gene expression, and function, which collectively are more akin to a fetal state versus that of an adult. This phenomenon is most apparent under 2D culture conditions where a cell is restricted in 3D space, resulting in alterations in ECM-mediated mechanotransduction, cell polarity, and cell-to-cell interactions (Tibbitt and Anseth 2009). Additionally, exposure to cell culture media containing homogeneously distributed growth factors as opposed to dynamic spatial gradients can influence a variety of cellular behaviors (Ashe and Briscoe 2006). For these reasons, the further maturation of cells in vitro has been an important area of research for stem cell biologists, with consequences for structured cell-based meat products. For instance, immature myotubes may not contain the adult sarcomeric protein content needed for matched nutrition or texture to muscle from an adult animal (Listrat et al. 2016). The methods previously discussed all aim to replicate the 3D in vivo environment in which cells grow, primarily through biomimicry of the ECM. Indeed, transplantation of stem cell-derived cells into an animal is the most well-characterized method to increase functional maturity (Incitti et al. 2019). However, additional methods can be utilized for the maturation of cells for cell-based meat production, discussed below.
In vivo, skeletal muscle fibers and their collagen-rich ECM are highly aligned and thus anisotropic. Therefore, in addition to mimicking porosity and other features of the ECM, growth of skeletal muscle on or within micro or nanopatterned topography can align, polarize, and increase the maturation state and functional output of myotubes (Figure 7, Kim et al. 2012). For electrically active cells such as skeletal myotubes, stimulation can lead to well-described downstream gene transcriptional changes that can influence fiber type composition (discussed in Series V), maturation, and hypertrophy (i.e. growth, Gundersen 2011). Electrical stimulation of skeletal muscle (Video 4) is mediated via the neuromuscular junction in vivo, however, in the absence of motor neuron input, similar effects can be accomplished via electrical pulse stimulation (Ito et al. 2014). Additionally, myotube growth on conductive polymers such as polyaniline (Jun et al. 2009), conductive coatings such as gold or titanium (Yang et al. 2016), or in the presence of a static magnetic field (Coletti et al. 2007), can assist in myotube maturation in part via myotube alignment and propagation of intracellular calcium signaling through conductive surfaces or gap junctions (Coletti et al. 2007). Lastly, many stem cell-derived populations of myotubes will spontaneously contract upon the development of sarcomeric structures that mediate contractility. In essence, the ability to “exercise” skeletal muscle in vitro is an important determinant in the overall size and maturation state of the cells, as demonstrated through its use in the production of the first cell-based meat burger.
However, many studies investigating muscle contraction in vitro are nascent and at small scales, (often intentionally in the biorobotics field (Ricotti et al. 2017)), and have used structured pillars to act like tendons to assist in force generation (Cvetkovic et al. 2014) rather than structured collagen and sparse fibroblasts as may be seen in vivo or used within a scaffold. Thus, the selection of a strategy for ‘exercising’ cell-based meat within a bioreactor at large scale or within a scaffold may be challenging and require new innovations. For instance, direct electric current application to the cell culture medium can lead to ionization of medium components, and the intensity, frequency, and periodicity of stimulation will need to be optimized (Pascoal-Faria et al. 2019). Lastly, there is some concern for the structural integrity of a scaffold to withstand forces generated upon contraction; however, the forces generated thus far from muscle constructs in vitro are orders of magnitude lower than skeletal muscle in vivo (Ricotti et al. 2017) and are unlikely to pose significant problems for applications in cell-based meat.
As discussed in Series II, one way to avoid anoikis in suspension growth within a bioreactor is to grow cells as aggregates, spheroids, or organoids. A major benefit of this methodology is the 3D growth environment which permits a high degree of self-organization and maturation in relation to 2D growth (Hu et al. 2018). However, reproducibility in the relatively new organoid field is a challenge and an area of active research (Huch et al. 2017). Additionally, transitioning cells from organoid growth onto a scaffold would be counterintuitive, as cells are already pre-patterned and self-organized. Thus, these methodologies may serve well for scaling cell numbers for direct use in unstructured products (discussed in Series V) but would not easily be incorporated into structured products utilizing scaffolds. A potential workaround to this could be the use of microfluidic spinning (Onoe et al. 2013) or coaxial microextrusion (Li et al. 2018) to produce cells encapsulated in a hydrogel core-shell tube structure. These techniques work by co-extruding cells within a hydrogel that can be readily crosslinked, such as alginate in the presence of calcium. By creating cell-laden tubes with a 400µm diameter, for instance, cells can readily proliferate within a 3D microenvironment without suffering from mass transport limitations, as oxygen, nutrients, and waste can pass through the porous hydrogel. Additionally, cells are shielded from shear forces within a bioreactor, remarkably high densities of up to 5x10^8 cells/mL of microspace can be achieved, and differentiation can be initiated via changes in culture mediums (discussed in Series IV) (Video 4, Figure 8, Lin et al. 2018). The process is scalable in both tube length and parallelization of extruders. The tubes are flexible and structurally sound, permitting handling via ejection or suction and can be woven into complex structures using tools and methods similar to the highly automated textile industry (Onoe et al. 2013). Furthermore, alginate can be dissolved in the presence of calcium chelators or enzymes, resulting in a purely cellular structure following handling. Thus, these strategies may provide non-obvious solutions for tackling various challenges associated with scale-up and creation of structured products.
Summary of Scaffolds for Cell-based Meat
Putting this information together, a scaffolding structure for cell-based meat will likely require leveraging multiple aspects of state-of-the-art tissue engineering. A scaffold will likely be composed of cheap, edible or biodegradable biomaterials with high biocompatibility and porosity suitable for cell migration (approximately 1 - 500µm), continuous perfusion, and recycling of cell culture medium (discussed in Series IV) to remove waste and refresh nutrient supply. This may leverage native tissue architecture (e.g. decellularization) or be constructed by design (e.g. 3D printing, electrospinning, core-shell tubes). The scaffold may consist of different composite biomaterials, pre-patterned to recreate the cytoarchitecture of meat, with differing stiffnesses and/or embedded growth factors to assist in the attachment, migration, and maturation of stem cells into their differentiated counterparts. This may be less challenging than it initially seems, as cell-based meat does not require the same microscale precision and organization required for functional tissues — it merely needs to represent tissue structure sufficiently to recapitulate the appropriate texture and mouthfeel of its conventional counterpart.
Important considerations should be taken into how a scaffold may integrate and behave in a bioreactor, which may require custom engineering, computational modeling of fluids, and integration of on-line sensors (discussed in Series II). For instance, oxygen and other nutrient mass transfer is likely to change when growing cells on a scaffold versus in suspension (Martin and Vermette 2005). Existing bioreactors for mammalian cell growth may provide some insight into best approaches (Wang et al. 2019), as well as learned principles from solid state fermentation used in production of fungi or plant hairy root culture used to produce metabolites or proteins. Additionally, sterilization procedures for scaffolds such as gamma and UV irradiation or ethylene oxide may denature or damage certain biomaterials, thus limiting certain raw material options (Caliari and Burdick 2016). Forward-thinking strategies to address these challenges should be pursued.
The level of cellular maturation required will likely be dictated by the final product’s nutritional and textural requirements, and a spectrum of options may be considered in practice. As will be discussed in Series V, it’s likely that many years will separate the release of unstructured versus structured products as described here due to the difficult nature of the process. Significant challenges will need to be met with new innovations, such as core-shell tubes, to address concerns of scaling, cost, and reproducibility, as current practices in tissue engineering are prohibitively expensive and technically challenging. Despite this, current technologies provide a foundational roadmap for the successful creation of future structured cell-based meat products. Scientists in tissue engineering and cell-based meat should be encouraged to share knowledge and collaborate around shared problems, resulting in mutual positive benefits for each respective field.
- Ashe, Hilary L., and James Briscoe. 2006. “The Interpretation of Morphogen Gradients.” Development 133 (3): 385–94.
- Badylak, Stephen F., Doris Taylor, and Korkut Uygun. 2011. “Whole-Organ Tissue Engineering: Decellularization and Recellularization of Three-Dimensional Matrix Scaffolds.” Annual Review of Biomedical Engineering 13 (August): 27–53.
- Bajaj, Piyush, Daniel Marchwiany, Carlos Duarte, and Rashid Bashir. 2013. “Patterned Three-Dimensional Encapsulation of Embryonic Stem Cells Using Dielectrophoresis and Stereolithography.” Advanced Healthcare Materials 2 (3): 450–58.
- Bajaj, Piyush, Ryan M. Schweller, Ali Khademhosseini, Jennifer L. West, and Rashid Bashir. 2014. “3D Biofabrication Strategies for Tissue Engineering and Regenerative Medicine.” Annual Review of Biomedical Engineering 16 (July): 247–76.
- Bijonowski, Brent M., William M. Miller, and Jason A. Wertheim. 2013. “Bioreactor Design for Perfusion-Based, Highly-Vascularized Organ Regeneration.” Current Opinion in Chemical Engineering 2 (1): 32–40.
- Brennan, Ellen P., Janet Reing, Douglas Chew, Julie M. Myers-Irvin, E. J. Young, and Stephen F. Badylak. 2006. “Antibacterial Activity within Degradation Products of Biological Scaffolds Composed of Extracellular Matrix.” Tissue Engineering 12 (10): 2949–55.
- Bürck, Jochen, Stefan Heissler, Udo Geckle, Mohammad Fotouhi Ardakani, Reinhard Schneider, Anne S. Ulrich, and Murat Kazanci. 2013. “Resemblance of Electrospun Collagen Nanofibers to Their Native Structure.” Langmuir: The ACS Journal of Surfaces and Colloids 29 (5): 1562–72.
- Caliari, Steven R., and Jason A. Burdick. 2016. “A Practical Guide to Hydrogels for Cell Culture.” Nature Methods 13 (5): 405–14.
- Cheng, Jie, Yesl Jun, Jianhua Qin, and Sang-Hoon Lee. 2017. “Electrospinning versus Microfluidic Spinning of Functional Fibers for Biomedical Applications.” Biomaterials 114 (January): 121–43.
- Choi, Yeong-Jin, Young-Joon Jun, Dong Yeon Kim, Hee-Gyeong Yi, Su-Hun Chae, Junsu Kang, Juyong Lee, et al. 2019. “A 3D Cell Printed Muscle Construct with Tissue-Derived Bioink for the Treatment of Volumetric Muscle Loss.” Biomaterials 206 (June): 160–69.
- Choi, Yeong-Jin, Taek Gyoung Kim, Jonghyeon Jeong, Hee-Gyeong Yi, Ji Won Park, Woonbong Hwang, and Dong-Woo Cho. 2016. “3D Cell Printing of Functional Skeletal Muscle Constructs Using Skeletal Muscle-Derived Bioink.” Advanced Healthcare Materials 5 (20): 2636–45.
- Coletti, Dario, Laura Teodori, Maria C. Albertini, Marco Rocchi, Alessandro Pristerà, Massimo Fini, Mario Molinaro, and Sergio Adamo. 2007. “Static Magnetic Fields Enhance Skeletal Muscle Differentiation in Vitro by Improving Myoblast Alignment.” Cytometry. Part A: The Journal of the International Society for Analytical Cytology 71 (10): 846–56.
- Cvetkovic, Caroline, Ritu Raman, Vincent Chan, Brian J. Williams, Madeline Tolish, Piyush Bajaj, Mahmut Selman Sakar, H. Harry Asada, M. Taher A. Saif, and Rashid Bashir. 2014. “Three-Dimensionally Printed Biological Machines Powered by Skeletal Muscle.” Proceedings of the National Academy of Sciences of the United States of America 111 (28): 10125–30.
- Derakhshanfar, Soroosh, Rene Mbeleck, Kaige Xu, Xingying Zhang, Wen Zhong, and Malcolm Xing. 2018. “3D Bioprinting for Biomedical Devices and Tissue Engineering: A Review of Recent Trends and Advances.” Bioactive Materials 3 (2): 144–56.
- Ebrahimnejad, Hamed, Hadi Ebrahimnejad, A. Salajegheh, and H. Barghi. 2018. “Use of Magnetic Resonance Imaging in Food Quality Control: A Review.” Journal of Biomedical Physics and Engineering 8 (1): 127–32.
- Farrugia, Brooke L., Toby D. Brown, Zee Upton, Dietmar W. Hutmacher, Paul D. Dalton, and Tim R. Dargaville. 2013. “Dermal Fibroblast Infiltration of Poly(ε-Caprolactone) Scaffolds Fabricated by Melt Electrospinning in a Direct Writing Mode.” Biofabrication 5 (2): 025001.
- Fontana, Gianluca, Joshua Gershlak, Michal Adamski, Jae-Sung Lee, Shion Matsumoto, Hau D. Le, Bernard Binder, John Wirth, Glenn Gaudette, and William L. Murphy. 2017. “Biofunctionalized Plants as Diverse Biomaterials for Human Cell Culture.” Advanced Healthcare Materials 6 (8). https://doi.org/10.1002/adhm.201601225.
- Garreta, Elena, Roger Oria, Carolina Tarantino, Mateu Pla-Roca, Patricia Prado, Francisco Fernández-Avilés, Josep Maria Campistol, Josep Samitier, and Nuria Montserrat. 2017. “Tissue Engineering by Decellularization and 3D Bioprinting.” Materials Today 20 (4): 166–78.
- Gerli, Mattia Francesco Maria, Jacques Paul Guyette, Daniele Evangelista-Leite, Brian Burns Ghoshhajra, and Harald Christian Ott. 2018. “Perfusion Decellularization of a Human Limb: A Novel Platform for Composite Tissue Engineering and Reconstructive Surgery.” PloS One 13 (1): e0191497.
- Gershlak, Joshua R., Sarah Hernandez, Gianluca Fontana, Luke R. Perreault, Katrina J. Hansen, Sara A. Larson, Bernard Y. K. Binder, et al. 2017. “Crossing Kingdoms: Using Decellularized Plants as Perfusable Tissue Engineering Scaffolds.” Biomaterials 125 (May): 13–22.
- Grigoryan, Bagrat, Samantha J. Paulsen, Daniel C. Corbett, Daniel W. Sazer, Chelsea L. Fortin, Alexander J. Zaita, Paul T. Greenfield, et al. 2019. “Multivascular Networks and Functional Intravascular Topologies within Biocompatible Hydrogels.” Science 364 (6439): 458–64.
- Gundersen, Kristian. 2011. “Excitation-Transcription Coupling in Skeletal Muscle: The Molecular Pathways of Exercise.” Biological Reviews of the Cambridge Philosophical Society 86 (3): 564–600.
- Gupta, Maneesh K., Fanben Meng, Blake N. Johnson, Yong Lin Kong, Limei Tian, Yao-Wen Yeh, Nina Masters, Srikanth Singamaneni, and Michael C. McAlpine. 2015. “3D Printed Programmable Release Capsules.” Nano Letters 15 (8): 5321–29.
- Gupta, Sweta K., Narayan C. Mishra, and Archna Dhasmana. 2018. “Decellularization Methods for Scaffold Fabrication.” Methods in Molecular Biology 1577: 1–10.
- Guyette, Jacques P., Jonathan M. Charest, Robert W. Mills, Bernhard J. Jank, Philipp T. Moser, Sarah E. Gilpin, Joshua R. Gershlak, et al. 2016. “Bioengineering Human Myocardium on Native Extracellular Matrix.” Circulation Research 118 (1): 56–72.
- Hinton, Thomas J., Quentin Jallerat, Rachelle N. Palchesko, Joon Hyung Park, Martin S. Grodzicki, Hao-Jan Shue, Mohamed H. Ramadan, Andrew R. Hudson, and Adam W. Feinberg. 2015. “Three-Dimensional Printing of Complex Biological Structures by Freeform Reversible Embedding of Suspended Hydrogels.” Science Advances 1 (9): e1500758–11.
- Hölzl, Katja, Shengmao Lin, Liesbeth Tytgat, Sandra Van Vlierberghe, Linxia Gu, and Aleksandr Ovsianikov. 2016. “Bioink Properties Before, during and after 3D Bioprinting.” Biofabrication 8 (3): 032002–20.
- Hospodiuk, Monika, Madhuri Dey, Donna Sosnoski, and Ibrahim T. Ozbolat. 2017. “The Bioink: A Comprehensive Review on Bioprintable Materials.” Biotechnology Advances, January, 1–89.
- Huch, Meritxell, Juergen A. Knoblich, Matthias P. Lutolf, and Alfonso Martinez-Arias. 2017. “The Hope and the Hype of Organoid Research.” Development 144 (6): 938–41.
- Hu, Jennifer L., Michael E. Todhunter, Mark A. LaBarge, and Zev J. Gartner. 2018. “Opportunities for Organoids as New Models of Aging.” The Journal of Cell Biology 217 (1): 39–50.
- Incitti, Tania, Alessandro Magli, Radbod Darabi, Ce Yuan, Karena Lin, Robert W. Arpke, Karim Azzag, et al. 2019. “Pluripotent Stem Cell-Derived Myogenic Progenitors Remodel Their Molecular Signature upon in Vivo Engraftment.” Proceedings of the National Academy of Sciences of the United States of America, February. https://doi.org/10.1073/pnas.1808303116.
- Ito, Akira, Yasunori Yamamoto, Masanori Sato, Kazushi Ikeda, Masahiro Yamamoto, Hideaki Fujita, Eiji Nagamori, Yoshinori Kawabe, and Masamichi Kamihira. 2014. “Induction of Functional Tissue-Engineered Skeletal Muscle Constructs by Defined Electrical Stimulation.” Scientific Reports 4 (1): 879.
- Jank, Bernhard J., Linjie Xiong, Philipp T. Moser, Jacques P. Guyette, Xi Ren, Curtis L. Cetrulo, David A. Leonard, Leopoldo Fernandez, Shawn P. Fagan, and Harald C. Ott. 2015. “Engineered Composite Tissue as a Bioartificial Limb Graft.” Biomaterials 61 (August): 246–56.
- Jaramillo, Maria, Heidi Yeh, Martin L. Yarmush, and Basak E. Uygun. 2018. “Decellularized Human Liver Extracellular Matrix (hDLM)-Mediated Hepatic Differentiation of Human Induced Pluripotent Stem Cells (hIPSCs).” Journal of Tissue Engineering and Regenerative Medicine 12 (4): e1962–73.
- Ji, Shen, Emily Almeida, and Murat Guvendiren. 2019. “3D Bioprinting of Complex Channels within Cell-Laden Hydrogels.” Acta Biomaterialia, March. https://doi.org/10.1016/j.actbio.2019.02.038.
- Ji, Wei, Fang Yang, Jeroen J. J. P. van den Beucken, Zhuan Bian, Mingwen Fan, Zhi Chen, and John A. Jansen. 2010. “Fibrous Scaffolds Loaded with Protein Prepared by Blend or Coaxial Electrospinning.” Acta Biomaterialia 6 (11): 4199–4207.
- Jovic, Thomas H., Garikai Kungwengwe, Adam C. Mills, and Iain S. Whitaker. 2019. “Plant-Derived Biomaterials: A Review of 3D Bioprinting and Biomedical Applications.” Frontiers of Mechanical Engineering in China 5: 19.
- Jun, Indong, Sungin Jeong, and Heungsoo Shin. 2009. “The Stimulation of Myoblast Differentiation by Electrically Conductive Sub-Micron Fibers.” Biomaterials 30 (11): 2038–47.
- Ju, Young Min, Jin San Choi, Anthony Atala, James J. Yoo, and Sang Jin Lee. 2010. “Bilayered Scaffold for Engineering Cellularized Blood Vessels.” Biomaterials 31 (15): 4313–21.
- Kang, Hyun-Wook, Sang Jin Lee, In Kap Ko, Carlos Kengla, James J. Yoo, and Anthony Atala. 2016. “A 3D Bioprinting System to Produce Human-Scale Tissue Constructs with Structural Integrity.” Nature Biotechnology 34 (3): 312–19.
- Kelly, Brett E., Indrasen Bhattacharya, Hossein Heidari, Maxim Shusteff, Christopher M. Spadaccini, and Hayden K. Taylor. 2019. “Volumetric Additive Manufacturing via Tomographic Reconstruction.” Science, January. https://doi.org/10.1126/science.aau7114.
- Khorshidi, Sajedeh, Atefeh Solouk, Hamid Mirzadeh, Saeedeh Mazinani, Jose M. Lagaron, Shahriar Sharifi, and Seeram Ramakrishna. 2016. “A Review of Key Challenges of Electrospun Scaffolds for Tissue-Engineering Applications.” Journal of Tissue Engineering and Regenerative Medicine 10 (9): 715–38.
- Kidoaki, Satoru, Il Kuen Kwon, and Takehisa Matsuda. 2005. “Mesoscopic Spatial Designs of Nano- and Microfiber Meshes for Tissue-Engineering Matrix and Scaffold Based on Newly Devised Multilayering and Mixing Electrospinning Techniques.” Biomaterials 26 (1): 37–46.
- Kim, Deok-Ho, Paolo P. Provenzano, Chris L. Smith, and Andre Levchenko. 2012. “Matrix Nanotopography as a Regulator of Cell Function.” The Journal of Cell Biology 197 (3): 351–60.
- Kitano, Kentaro, Dana M. Schwartz, Haiyang Zhou, Sarah E. Gilpin, Gregory R. Wojtkiewicz, Xi Ren, Cesar A. Sommer, et al. 2017. “Bioengineering of Functional Human Induced Pluripotent Stem Cell-Derived Intestinal Grafts.” Nature Communications 8 (1): 765.
- Krona, Annika, Felix Klose, Julie Gold, Roland Kádár, and Mats Stading. 2017. “Developing Cultured Meat Scaffolds of Extruded Vegetable-Based Proteins.” In ANNUAL TRANSACTIONS OF THE NORDIC RHEOLOGY SOCIETY. http://dx.doi.org/.
- K, Uday Chandrika, Rekha Tripathi, Avinash Raj T, N. Sairam, Vasundhara Kamineni Parlikar, V. B. Swami, Nandini Rangaraj, Mahesh Kumar Jerald, and Shashi Singh. 2019. “Preparation of Organ Scaffolds by Decellularization of Pancreas and Re-Functionalization.” bioRxiv. https://doi.org/10.1101/513465.
- Labbaf, Sheyda, Hanif Ghanbar, Eleanor Stride, and Mohan Edirisinghe. 2014. “Preparation of Multilayered Polymeric Structures Using a Novel Four-Needle Coaxial Electrohydrodynamic Device.” Macromolecular Rapid Communications 35 (6): 618–23.
- Lawrence, Benjamin J., Mamatha Devarapalli, and Sundararajan V. Madihally. 2009. “Flow Dynamics in Bioreactors Containing Tissue Engineering Scaffolds.” Biotechnology and Bioengineering 102 (3): 935–47.
- Lin, Haishuang, Qian Du, Qiang Li, Ou Wang, Zhanqi Wang, Kan Liu, Christian Elowsky, Chi Zhang, and Yuguo Lei. 2018. “Hydrogel-Based Bioprocess for Scalable Manufacturing of Human Pluripotent Stem Cell-Derived Neural Stem Cells.” ACS Applied Materials and Interfaces 10 (35): 29238–50.
- Li, Qiang, Haishuang Lin, Qian Du, Kan Liu, Ou Wang, Catelyn Evans, Hannah Christian, Chi Zhang, and Yuguo Lei. 2018. “Scalable and Physiologically Relevant Microenvironments for Human Pluripotent Stem Cell Expansion and Differentiation.” Biofabrication 10 (2): 025006.
- Li, S-G, G. H. Koops, M. H. V. Mulder, T. van den Boomgaard, and C. A. Smolders. 1994. “Wet Spinning of Integrally Skinned Hollow Fiber Membranes by a Modified Dual-Bath Coagulation Method Using a Triple Orifice Spinneret.” Journal of Membrane Science 94 (1): 329–40.
- Listrat, Anne, Bénédicte Lebret, Isabelle Louveau, Thierry Astruc, Muriel Bonnet, Louis Lefaucheur, Brigitte Picard, and Jérôme Bugeon. 2016. “How Muscle Structure and Composition Influence Meat and Flesh Quality.” TheScientificWorldJournal 2016 (February): 3182746.
- Liu, Wanjun, Yu Shrike Zhang, Marcel A. Heinrich, Fabio De Ferrari, Hae Lin Jang, Syeda Mahwish Bakht, Mario Moisés Alvarez, et al. 2016. “Rapid Continuous Multimaterial Extrusion Bioprinting.” Advanced Materials 29 (3): 1604630–38.
- Mandrycky, Christian, Zongjie Wang, Keekyoung Kim, and Deok-Ho Kim. 2016. “3D Bioprinting for Engineering Complex Tissues.” Biotechnology Advances 34 (4): 422–34.
- Martin, Yves, and Patrick Vermette. 2005. “Bioreactors for Tissue Mass Culture: Design, Characterization, and Recent Advances.” Biomaterials 26 (35): 7481–7503.
- Meng, Fanben, Carolyn M. Meyer, Daeha Joung, Daniel A. Vallera, Michael C. McAlpine, and Angela Panoskaltsis-Mortari. 2019. “3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments.” Advanced Materials 45 (January): 1806899–1806810.
- Modulevsky, Daniel J., Cory Lefebvre, Kristina Haase, Zeinab Al-Rekabi, and Andrew E. Pelling. 2014. “Apple Derived Cellulose Scaffolds for 3D Mammalian Cell Culture.” PloS One 9 (5): e97835.
- Moroni, Lorenzo, Thomas Boland, Jason A. Burdick, Carmelo De Maria, Brian Derby, Gabor Forgacs, Jürgen Groll, et al. 2018. “Biofabrication: A Guide to Technology and Terminology.” Trends in Biotechnology 36 (4): 384–402.
- Moroni, Lorenzo, Jason A. Burdick, Christopher Highley, Sang Jin Lee, Yuya Morimoto, Shoji Takeuchi, and James J. Yoo. 2018. “Biofabrication Strategies for 3D in Vitro Models and Regenerative Medicine.” Nature Reviews Materials 3 (5): 21–37.
- Nakayama, Karina H., C. Chang I. Lee, Cynthia A. Batchelder, and Alice F. Tarantal. 2013. “Tissue Specificity of Decellularized Rhesus Monkey Kidney and Lung Scaffolds.” PloS One 8 (5): e64134.
- Nichols, Joan E., Saverio La Francesca, Jean A. Niles, Stephanie P. Vega, Lissenya B. Argueta, Luba Frank, David C. Christiani, et al. 2018. “Production and Transplantation of Bioengineered Lung into a Large-Animal Model.” Science Translational Medicine 10 (452). https://doi.org/10.1126/scitranslmed.aao3926.
- Nikmaram, Nooshin, Shahin Roohinejad, Sara Hashemi, Mohamed Koubaa, Francisco J. Barba, Alireza Abbaspourrad, and Ralf Greiner. 2017. “Emulsion-Based Systems for Fabrication of Electrospun Nanofibers: Food, Pharmaceutical and Biomedical Applications.” RSC Advances 7 (46): 28951–64.
- Onoe, Hiroaki, Teru Okitsu, Akane Itou, Midori Kato-Negishi, Riho Gojo, Daisuke Kiriya, Koji Sato, et al. 2013. “Metre-Long Cell-Laden Microfibres Exhibit Tissue Morphologies and Functions.” Nature Materials 12 (6): 584–90.
- Ott, Harald C., Thomas S. Matthiesen, Saik-Kia Goh, Lauren D. Black, Stefan M. Kren, Theoden I. Netoff, and Doris A. Taylor. 2008. “Perfusion-Decellularized Matrix: Using Nature’s Platform to Engineer a Bioartificial Heart.” Nature Medicine 14 (2): 213–21.
- Pascoal-Faria, Paula, Pedro Castelo Ferreira, Abhishek Datta, Sandra Amado, Carla Moura, and Nuno Alves. 2019. “Electrical Stimulation Optimization in Bioreactors for Tissue Engineering Applications.” In Applied Mechanics and Materials, 890:314–23. Trans Tech Publ.
- Pati, Falguni, Jinah Jang, Dong-Heon Ha, Sung Won Kim, Jong-Won Rhie, Jin-Hyung Shim, Deok-Ho Kim, and Dong-Woo Cho. 2014. “Printing Three-Dimensional Tissue Analogues with Decellularized Extracellular Matrix Bioink.” Nature Communications 5 (June): 3935.
- Raman, Ritu, and Rashid Bashir. 2015. “Chapter 6 - Stereolithographic 3D Bioprinting for Biomedical Applications.” In Essentials of 3D Biofabrication and Translation, edited by Anthony Atala and James J. Yoo, 89–121. Boston: Academic Press.
- Ricotti, Leonardo, Barry Trimmer, Adam W. Feinberg, Ritu Raman, Kevin K. Parker, Rashid Bashir, Metin Sitti, Sylvain Martel, Paolo Dario, and Arianna Menciassi. 2017. “Biohybrid Actuators for Robotics: A Review of Devices Actuated by Living Cells.” Science Robotics 2 (12): eaaq0495.
- Rim, Nae Gyune, Choongsoo S. Shin, and Heungsoo Shin. 2013. “Current Approaches to Electrospun Nanofibers for Tissue Engineering.” Biomedical Materials 8 (1): 014102.
- Soman, Pranav, Peter H. Chung, A. Ping Zhang, and Shaochen Chen. 2013. “Digital Microfabrication of User-Defined 3D Microstructures in Cell-Laden Hydrogels.” Biotechnology and Bioengineering 110 (11): 3038–47.
- Tibbitt, Mark W., and Kristi S. Anseth. 2009. “Hydrogels as Extracellular Matrix Mimics for 3D Cell Culture.” Biotechnology and Bioengineering 103 (4): 655–63.
- Wade, Ryan J., Ethan J. Bassin, Christopher B. Rodell, and Jason A. Burdick. 2015. “Protease-Degradable Electrospun Fibrous Hydrogels.” Nature Communications 6 (March): 6639.
- Wang, Xianfeng, Bin Ding, and Bingyun Li. 2013. “Biomimetic Electrospun Nanofibrous Structures for Tissue Engineering.” Materials Today 16 (6): 229–41.
- Wang, Zongsen, Wing Lau, Faribourz Payvandi, and Peter Materna. 2019. Large-scale Bioreactor. USPTO 20190002815:A1. US Patent, filed September 11, 2018, and issued January 3, 2019. https://patentimages.storage.googleapis.com/f6/18/31/2c65eaeae74d8f/US20190002815A1.pdf.
- Weidenbacher, L., A. Abrishamkar, M. Rottmar, A. G. Guex, K. Maniura-Weber, A. J. deMello, S. J. Ferguson, R. M. Rossi, and G. Fortunato. 2017. “Electrospraying of Microfluidic Encapsulated Cells for the Fabrication of Cell-Laden Electrospun Hybrid Tissue Constructs.” Acta Biomaterialia 64 (December): 137–47.
- White, Lisa J., Adam J. Taylor, Denver M. Faulk, Timothy J. Keane, Lindsey T. Saldin, Janet E. Reing, Ilea T. Swinehart, Neill J. Turner, Buddy D. Ratner, and Stephen F. Badylak. 2017. “The Impact of Detergents on the Tissue Decellularization Process: A ToF-SIMS Study.” Acta Biomaterialia 50 (March): 207–19.
- Widhe, Mona, Nancy Dekki Shalaly, and My Hedhammar. 2016. “A Fibronectin Mimetic Motif Improves Integrin Mediated Cell Biding to Recombinant Spider Silk Matrices.” Biomaterials 74 (January): 256–66.
- Wolf, Matthew T., Kerry A. Daly, Janet E. Reing, and Stephen F. Badylak. 2012. “Biologic Scaffold Composed of Skeletal Muscle Extracellular Matrix.” Biomaterials 33 (10): 2916–25.
- Yang, Hee Seok, Bora Lee, Jonathan H. Tsui, Jesse Macadangdang, Seok-Young Jang, Sung Gap Im, and Deok-Ho Kim. 2016. “Electroconductive Nanopatterned Substrates for Enhanced Myogenic Differentiation and Maturation.” Advanced Healthcare Materials 5 (1): 137–45.
- Young, Bethany M., Keerthana Shankar, Brittany P. Allen, Robert A. Pouliot, Matthew B. Schneck, Nabil S. Mikhaiel, and Rebecca L. Heise. 2017. “Electrospun Decellularized Lung Matrix Scaffold for Airway Smooth Muscle Culture.” ACS Biomaterials Science and Engineering 3 (12): 3480–92.
- Yu, Yin, Yahui Zhang, and Ibrahim T. Ozbolat. 2014. “A Hybrid Bioprinting Approach for Scale-Up Tissue Fabrication.” Journal of Manufacturing Science and Engineering 136 (6): 061013.
- Zhang, Jian, Zhi Qian Hu, Neill J. Turner, Shi Feng Teng, Wen Yue Cheng, Hai Yang Zhou, Li Zhang, Hong Wei Hu, Qiang Wang, and Stephen F. Badylak. 2016. “Perfusion-Decellularized Skeletal Muscle as a Three-Dimensional Scaffold with a Vascular Network Template.” Biomaterials 89 (May): 114–26.
Ashe, Hilary L., and James Briscoe. 2006. “The Interpretation of Morphogen Gradients.” Development 133 (3): 385–94.
Badylak, Stephen F., Doris Taylor, and Korkut Uygun. 2011. “Whole-Organ Tissue Engineering: Decellularization and Recellularization of Three-Dimensional Matrix Scaffolds.” Annual Review of Biomedical Engineering 13 (August): 27–53.
Bajaj, Piyush, Daniel Marchwiany, Carlos Duarte, and Rashid Bashir. 2013. “Patterned Three-Dimensional Encapsulation of Embryonic Stem Cells Using Dielectrophoresis and Stereolithography.” Advanced Healthcare Materials 2 (3): 450–58.
Bajaj, Piyush, Ryan M. Schweller, Ali Khademhosseini, Jennifer L. West, and Rashid Bashir. 2014. “3D Biofabrication Strategies for Tissue Engineering and Regenerative Medicine.” Annual Review of Biomedical Engineering 16 (July): 247–76.
Bijonowski, Brent M., William M. Miller, and Jason A. Wertheim. 2013. “Bioreactor Design for Perfusion-Based, Highly-Vascularized Organ Regeneration.” Current Opinion in Chemical Engineering 2 (1): 32–40.
Brennan, Ellen P., Janet Reing, Douglas Chew, Julie M. Myers-Irvin, E. J. Young, and Stephen F. Badylak. 2006. “Antibacterial Activity within Degradation Products of Biological Scaffolds Composed of Extracellular Matrix.” Tissue Engineering 12 (10): 2949–55.
Bürck, Jochen, Stefan Heissler, Udo Geckle, Mohammad Fotouhi Ardakani, Reinhard Schneider, Anne S. Ulrich, and Murat Kazanci. 2013. “Resemblance of Electrospun Collagen Nanofibers to Their Native Structure.” Langmuir: The ACS Journal of Surfaces and Colloids 29 (5): 1562–72.
Caliari, Steven R., and Jason A. Burdick. 2016. “A Practical Guide to Hydrogels for Cell Culture.” Nature Methods 13 (5): 405–14.
Cheng, Jie, Yesl Jun, Jianhua Qin, and Sang-Hoon Lee. 2017. “Electrospinning versus Microfluidic Spinning of Functional Fibers for Biomedical Applications.” Biomaterials 114 (January): 121–43.
Choi, Yeong-Jin, Young-Joon Jun, Dong Yeon Kim, Hee-Gyeong Yi, Su-Hun Chae, Junsu Kang, Juyong Lee, et al. 2019. “A 3D Cell Printed Muscle Construct with Tissue-Derived Bioink for the Treatment of Volumetric Muscle Loss.” Biomaterials 206 (June): 160–69.
Choi, Yeong-Jin, Taek Gyoung Kim, Jonghyeon Jeong, Hee-Gyeong Yi, Ji Won Park, Woonbong Hwang, and Dong-Woo Cho. 2016. “3D Cell Printing of Functional Skeletal Muscle Constructs Using Skeletal Muscle-Derived Bioink.” Advanced Healthcare Materials 5 (20): 2636–45.
Coletti, Dario, Laura Teodori, Maria C. Albertini, Marco Rocchi, Alessandro Pristerà, Massimo Fini, Mario Molinaro, and Sergio Adamo. 2007. “Static Magnetic Fields Enhance Skeletal Muscle Differentiation in Vitro by Improving Myoblast Alignment.” Cytometry. Part A: The Journal of the International Society for Analytical Cytology 71 (10): 846–56.
Cvetkovic, Caroline, Ritu Raman, Vincent Chan, Brian J. Williams, Madeline Tolish, Piyush Bajaj, Mahmut Selman Sakar, H. Harry Asada, M. Taher A. Saif, and Rashid Bashir. 2014. “Three-Dimensionally Printed Biological Machines Powered by Skeletal Muscle.” Proceedings of the National Academy of Sciences of the United States of America 111 (28): 10125–30.
Derakhshanfar, Soroosh, Rene Mbeleck, Kaige Xu, Xingying Zhang, Wen Zhong, and Malcolm Xing. 2018. “3D Bioprinting for Biomedical Devices and Tissue Engineering: A Review of Recent Trends and Advances.” Bioactive Materials 3 (2): 144–56.
Ebrahimnejad, Hamed, Hadi Ebrahimnejad, A. Salajegheh, and H. Barghi. 2018. “Use of Magnetic Resonance Imaging in Food Quality Control: A Review.” Journal of Biomedical Physics & Engineering 8 (1): 127–32.
Farrugia, Brooke L., Toby D. Brown, Zee Upton, Dietmar W. Hutmacher, Paul D. Dalton, and Tim R. Dargaville. 2013. “Dermal Fibroblast Infiltration of Poly(ε-Caprolactone) Scaffolds Fabricated by Melt Electrospinning in a Direct Writing Mode.” Biofabrication 5 (2): 025001.
Fontana, Gianluca, Joshua Gershlak, Michal Adamski, Jae-Sung Lee, Shion Matsumoto, Hau D. Le, Bernard Binder, John Wirth, Glenn Gaudette, and William L. Murphy. 2017. “Biofunctionalized Plants as Diverse Biomaterials for Human Cell Culture.” Advanced Healthcare Materials 6 (8). https://doi.org/10.1002/adhm.201601225.
Garreta, Elena, Roger Oria, Carolina Tarantino, Mateu Pla-Roca, Patricia Prado, Francisco Fernández-Avilés, Josep Maria Campistol, Josep Samitier, and Nuria Montserrat. 2017. “Tissue Engineering by Decellularization and 3D Bioprinting.” Materials Today 20 (4): 166–78.
Gerli, Mattia Francesco Maria, Jacques Paul Guyette, Daniele Evangelista-Leite, Brian Burns Ghoshhajra, and Harald Christian Ott. 2018. “Perfusion Decellularization of a Human Limb: A Novel Platform for Composite Tissue Engineering and Reconstructive Surgery.” PloS One 13 (1): e0191497.
Gershlak, Joshua R., Sarah Hernandez, Gianluca Fontana, Luke R. Perreault, Katrina J. Hansen, Sara A. Larson, Bernard Y. K. Binder, et al. 2017. “Crossing Kingdoms: Using Decellularized Plants as Perfusable Tissue Engineering Scaffolds.” Biomaterials 125 (May): 13–22.
Grigoryan, Bagrat, Samantha J. Paulsen, Daniel C. Corbett, Daniel W. Sazer, Chelsea L. Fortin, Alexander J. Zaita, Paul T. Greenfield, et al. 2019. “Multivascular Networks and Functional Intravascular Topologies within Biocompatible Hydrogels.” Science 364 (6439): 458–64.
Gundersen, Kristian. 2011. “Excitation-Transcription Coupling in Skeletal Muscle: The Molecular Pathways of Exercise.” Biological Reviews of the Cambridge Philosophical Society 86 (3): 564–600.
Gupta, Maneesh K., Fanben Meng, Blake N. Johnson, Yong Lin Kong, Limei Tian, Yao-Wen Yeh, Nina Masters, Srikanth Singamaneni, and Michael C. McAlpine. 2015. “3D Printed Programmable Release Capsules.” Nano Letters 15 (8): 5321–29.
Gupta, Sweta K., Narayan C. Mishra, and Archna Dhasmana. 2018. “Decellularization Methods for Scaffold Fabrication.” Methods in Molecular Biology 1577: 1–10.
Guyette, Jacques P., Jonathan M. Charest, Robert W. Mills, Bernhard J. Jank, Philipp T. Moser, Sarah E. Gilpin, Joshua R. Gershlak, et al. 2016. “Bioengineering Human Myocardium on Native Extracellular Matrix.” Circulation Research 118 (1): 56–72.
Hinton, Thomas J., Quentin Jallerat, Rachelle N. Palchesko, Joon Hyung Park, Martin S. Grodzicki, Hao-Jan Shue, Mohamed H. Ramadan, Andrew R. Hudson, and Adam W. Feinberg. 2015. “Three-Dimensional Printing of Complex Biological Structures by Freeform Reversible Embedding of Suspended Hydrogels.” Science Advances 1 (9): e1500758–11.
Hölzl, Katja, Shengmao Lin, Liesbeth Tytgat, Sandra Van Vlierberghe, Linxia Gu, and Aleksandr Ovsianikov. 2016. “Bioink Properties Before, during and after 3D Bioprinting.” Biofabrication 8 (3): 032002–20.
Hospodiuk, Monika, Madhuri Dey, Donna Sosnoski, and Ibrahim T. Ozbolat. 2017. “The Bioink: A Comprehensive Review on Bioprintable Materials.” Biotechnology Advances, January, 1–89.
Huch, Meritxell, Juergen A. Knoblich, Matthias P. Lutolf, and Alfonso Martinez-Arias. 2017. “The Hope and the Hype of Organoid Research.” Development 144 (6): 938–41.
Hu, Jennifer L., Michael E. Todhunter, Mark A. LaBarge, and Zev J. Gartner. 2018. “Opportunities for Organoids as New Models of Aging.” The Journal of Cell Biology 217 (1): 39–50.
Incitti, Tania, Alessandro Magli, Radbod Darabi, Ce Yuan, Karena Lin, Robert W. Arpke, Karim Azzag, et al. 2019. “Pluripotent Stem Cell-Derived Myogenic Progenitors Remodel Their Molecular Signature upon in Vivo Engraftment.” Proceedings of the National Academy of Sciences of the United States of America, February. https://doi.org/10.1073/pnas.1808303116.
Ito, Akira, Yasunori Yamamoto, Masanori Sato, Kazushi Ikeda, Masahiro Yamamoto, Hideaki Fujita, Eiji Nagamori, Yoshinori Kawabe, and Masamichi Kamihira. 2014. “Induction of Functional Tissue-Engineered Skeletal Muscle Constructs by Defined Electrical Stimulation.” Scientific Reports 4 (1): 879.
Jank, Bernhard J., Linjie Xiong, Philipp T. Moser, Jacques P. Guyette, Xi Ren, Curtis L. Cetrulo, David A. Leonard, Leopoldo Fernandez, Shawn P. Fagan, and Harald C. Ott. 2015. “Engineered Composite Tissue as a Bioartificial Limb Graft.” Biomaterials 61 (August): 246–56.
Jaramillo, Maria, Heidi Yeh, Martin L. Yarmush, and Basak E. Uygun. 2018. “Decellularized Human Liver Extracellular Matrix (hDLM)-Mediated Hepatic Differentiation of Human Induced Pluripotent Stem Cells (hIPSCs).” Journal of Tissue Engineering and Regenerative Medicine 12 (4): e1962–73.
Ji, Shen, Emily Almeida, and Murat Guvendiren. 2019. “3D Bioprinting of Complex Channels within Cell-Laden Hydrogels.” Acta Biomaterialia, March. https://doi.org/10.1016/j.actbio.2019.02.038.
Ji, Wei, Fang Yang, Jeroen J. J. P. van den Beucken, Zhuan Bian, Mingwen Fan, Zhi Chen, and John A. Jansen. 2010. “Fibrous Scaffolds Loaded with Protein Prepared by Blend or Coaxial Electrospinning.” Acta Biomaterialia 6 (11): 4199–4207.
Jovic, Thomas H., Garikai Kungwengwe, Adam C. Mills, and Iain S. Whitaker. 2019. “Plant-Derived Biomaterials: A Review of 3D Bioprinting and Biomedical Applications.” Frontiers of Mechanical Engineering in China 5: 19.
Jun, Indong, Sungin Jeong, and Heungsoo Shin. 2009. “The Stimulation of Myoblast Differentiation by Electrically Conductive Sub-Micron Fibers.” Biomaterials 30 (11): 2038–47.
Ju, Young Min, Jin San Choi, Anthony Atala, James J. Yoo, and Sang Jin Lee. 2010. “Bilayered Scaffold for Engineering Cellularized Blood Vessels.” Biomaterials 31 (15): 4313–21.
Kang, Hyun-Wook, Sang Jin Lee, In Kap Ko, Carlos Kengla, James J. Yoo, and Anthony Atala. 2016. “A 3D Bioprinting System to Produce Human-Scale Tissue Constructs with Structural Integrity.” Nature Biotechnology 34 (3): 312–19.
Kelly, Brett E., Indrasen Bhattacharya, Hossein Heidari, Maxim Shusteff, Christopher M. Spadaccini, and Hayden K. Taylor. 2019. “Volumetric Additive Manufacturing via Tomographic Reconstruction.” Science, January. https://doi.org/10.1126/science.aau7114.
Khorshidi, Sajedeh, Atefeh Solouk, Hamid Mirzadeh, Saeedeh Mazinani, Jose M. Lagaron, Shahriar Sharifi, and Seeram Ramakrishna. 2016. “A Review of Key Challenges of Electrospun Scaffolds for Tissue-Engineering Applications.” Journal of Tissue Engineering and Regenerative Medicine 10 (9): 715–38.
Kidoaki, Satoru, Il Kuen Kwon, and Takehisa Matsuda. 2005. “Mesoscopic Spatial Designs of Nano- and Microfiber Meshes for Tissue-Engineering Matrix and Scaffold Based on Newly Devised Multilayering and Mixing Electrospinning Techniques.” Biomaterials 26 (1): 37–46.
Kim, Deok-Ho, Paolo P. Provenzano, Chris L. Smith, and Andre Levchenko. 2012. “Matrix Nanotopography as a Regulator of Cell Function.” The Journal of Cell Biology 197 (3): 351–60.
Kitano, Kentaro, Dana M. Schwartz, Haiyang Zhou, Sarah E. Gilpin, Gregory R. Wojtkiewicz, Xi Ren, Cesar A. Sommer, et al. 2017. “Bioengineering of Functional Human Induced Pluripotent Stem Cell-Derived Intestinal Grafts.” Nature Communications 8 (1): 765.
Krona, Annika, Felix Klose, Julie Gold, Roland Kádár, and Mats Stading. 2017. “Developing Cultured Meat Scaffolds of Extruded Vegetable-Based Proteins.” In ANNUAL TRANSACTIONS OF THE NORDIC RHEOLOGY SOCIETY. http://dx.doi.org/.
K, Uday Chandrika, Rekha Tripathi, Avinash Raj T, N. Sairam, Vasundhara Kamineni Parlikar, V. B. Swami, Nandini Rangaraj, Mahesh Kumar Jerald, and Shashi Singh. 2019. “Preparation of Organ Scaffolds by Decellularization of Pancreas and Re-Functionalization.” bioRxiv. https://doi.org/10.1101/513465.
Labbaf, Sheyda, Hanif Ghanbar, Eleanor Stride, and Mohan Edirisinghe. 2014. “Preparation of Multilayered Polymeric Structures Using a Novel Four-Needle Coaxial Electrohydrodynamic Device.” Macromolecular Rapid Communications 35 (6): 618–23.
Lawrence, Benjamin J., Mamatha Devarapalli, and Sundararajan V. Madihally. 2009. “Flow Dynamics in Bioreactors Containing Tissue Engineering Scaffolds.” Biotechnology and Bioengineering 102 (3): 935–47.
Lin, Haishuang, Qian Du, Qiang Li, Ou Wang, Zhanqi Wang, Kan Liu, Christian Elowsky, Chi Zhang, and Yuguo Lei. 2018. “Hydrogel-Based Bioprocess for Scalable Manufacturing of Human Pluripotent Stem Cell-Derived Neural Stem Cells.” ACS Applied Materials & Interfaces 10 (35): 29238–50.
Li, Qiang, Haishuang Lin, Qian Du, Kan Liu, Ou Wang, Catelyn Evans, Hannah Christian, Chi Zhang, and Yuguo Lei. 2018. “Scalable and Physiologically Relevant Microenvironments for Human Pluripotent Stem Cell Expansion and Differentiation.” Biofabrication 10 (2): 025006.
Li, S-G, G. H. Koops, M. H. V. Mulder, T. van den Boomgaard, and C. A. Smolders. 1994. “Wet Spinning of Integrally Skinned Hollow Fiber Membranes by a Modified Dual-Bath Coagulation Method Using a Triple Orifice Spinneret.” Journal of Membrane Science 94 (1): 329–40.
Listrat, Anne, Bénédicte Lebret, Isabelle Louveau, Thierry Astruc, Muriel Bonnet, Louis Lefaucheur, Brigitte Picard, and Jérôme Bugeon. 2016. “How Muscle Structure and Composition Influence Meat and Flesh Quality.” TheScientificWorldJournal 2016 (February): 3182746.
Liu, Wanjun, Yu Shrike Zhang, Marcel A. Heinrich, Fabio De Ferrari, Hae Lin Jang, Syeda Mahwish Bakht, Mario Moisés Alvarez, et al. 2016. “Rapid Continuous Multimaterial Extrusion Bioprinting.” Advanced Materials 29 (3): 1604630–38.
Mandrycky, Christian, Zongjie Wang, Keekyoung Kim, and Deok-Ho Kim. 2016. “3D Bioprinting for Engineering Complex Tissues.” Biotechnology Advances 34 (4): 422–34.
Martin, Yves, and Patrick Vermette. 2005. “Bioreactors for Tissue Mass Culture: Design, Characterization, and Recent Advances.” Biomaterials 26 (35): 7481–7503.
Meng, Fanben, Carolyn M. Meyer, Daeha Joung, Daniel A. Vallera, Michael C. McAlpine, and Angela Panoskaltsis-Mortari. 2019. “3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments.” Advanced Materials 45 (January): 1806899–1806810.
Modulevsky, Daniel J., Cory Lefebvre, Kristina Haase, Zeinab Al-Rekabi, and Andrew E. Pelling. 2014. “Apple Derived Cellulose Scaffolds for 3D Mammalian Cell Culture.” PloS One 9 (5): e97835.
Moroni, Lorenzo, Thomas Boland, Jason A. Burdick, Carmelo De Maria, Brian Derby, Gabor Forgacs, Jürgen Groll, et al. 2018. “Biofabrication: A Guide to Technology and Terminology.” Trends in Biotechnology 36 (4): 384–402.
Moroni, Lorenzo, Jason A. Burdick, Christopher Highley, Sang Jin Lee, Yuya Morimoto, Shoji Takeuchi, and James J. Yoo. 2018. “Biofabrication Strategies for 3D in Vitro Models and Regenerative Medicine.” Nature Reviews Materials 3 (5): 21–37.
Nakayama, Karina H., C. Chang I. Lee, Cynthia A. Batchelder, and Alice F. Tarantal. 2013. “Tissue Specificity of Decellularized Rhesus Monkey Kidney and Lung Scaffolds.” PloS One 8 (5): e64134.
Nichols, Joan E., Saverio La Francesca, Jean A. Niles, Stephanie P. Vega, Lissenya B. Argueta, Luba Frank, David C. Christiani, et al. 2018. “Production and Transplantation of Bioengineered Lung into a Large-Animal Model.” Science Translational Medicine 10 (452). https://doi.org/10.1126/scitranslmed.aao3926.
Nikmaram, Nooshin, Shahin Roohinejad, Sara Hashemi, Mohamed Koubaa, Francisco J. Barba, Alireza Abbaspourrad, and Ralf Greiner. 2017. “Emulsion-Based Systems for Fabrication of Electrospun Nanofibers: Food, Pharmaceutical and Biomedical Applications.” RSC Advances 7 (46): 28951–64.
Onoe, Hiroaki, Teru Okitsu, Akane Itou, Midori Kato-Negishi, Riho Gojo, Daisuke Kiriya, Koji Sato, et al. 2013. “Metre-Long Cell-Laden Microfibres Exhibit Tissue Morphologies and Functions.” Nature Materials 12 (6): 584–90.
Ott, Harald C., Thomas S. Matthiesen, Saik-Kia Goh, Lauren D. Black, Stefan M. Kren, Theoden I. Netoff, and Doris A. Taylor. 2008. “Perfusion-Decellularized Matrix: Using Nature’s Platform to Engineer a Bioartificial Heart.” Nature Medicine 14 (2): 213–21.
Pascoal-Faria, Paula, Pedro Castelo Ferreira, Abhishek Datta, Sandra Amado, Carla Moura, and Nuno Alves. 2019. “Electrical Stimulation Optimization in Bioreactors for Tissue Engineering Applications.” In Applied Mechanics and Materials, 890:314–23. Trans Tech Publ.
Pati, Falguni, Jinah Jang, Dong-Heon Ha, Sung Won Kim, Jong-Won Rhie, Jin-Hyung Shim, Deok-Ho Kim, and Dong-Woo Cho. 2014. “Printing Three-Dimensional Tissue Analogues with Decellularized Extracellular Matrix Bioink.” Nature Communications 5 (June): 3935.
Raman, Ritu, and Rashid Bashir. 2015. “Chapter 6 - Stereolithographic 3D Bioprinting for Biomedical Applications.” In Essentials of 3D Biofabrication and Translation, edited by Anthony Atala and James J. Yoo, 89–121. Boston: Academic Press.
Ricotti, Leonardo, Barry Trimmer, Adam W. Feinberg, Ritu Raman, Kevin K. Parker, Rashid Bashir, Metin Sitti, Sylvain Martel, Paolo Dario, and Arianna Menciassi. 2017. “Biohybrid Actuators for Robotics: A Review of Devices Actuated by Living Cells.” Science Robotics 2 (12): eaaq0495.
Rim, Nae Gyune, Choongsoo S. Shin, and Heungsoo Shin. 2013. “Current Approaches to Electrospun Nanofibers for Tissue Engineering.” Biomedical Materials 8 (1): 014102.
Soman, Pranav, Peter H. Chung, A. Ping Zhang, and Shaochen Chen. 2013. “Digital Microfabrication of User-Defined 3D Microstructures in Cell-Laden Hydrogels.” Biotechnology and Bioengineering 110 (11): 3038–47.
Tibbitt, Mark W., and Kristi S. Anseth. 2009. “Hydrogels as Extracellular Matrix Mimics for 3D Cell Culture.” Biotechnology and Bioengineering 103 (4): 655–63.
Wade, Ryan J., Ethan J. Bassin, Christopher B. Rodell, and Jason A. Burdick. 2015. “Protease-Degradable Electrospun Fibrous Hydrogels.” Nature Communications 6 (March): 6639.
Wang, Xianfeng, Bin Ding, and Bingyun Li. 2013. “Biomimetic Electrospun Nanofibrous Structures for Tissue Engineering.” Materials Today 16 (6): 229–41.
Wang, Zongsen, Wing Lau, Faribourz Payvandi, and Peter Materna. 2019. Large-scale Bioreactor. USPTO 20190002815:A1. US Patent, filed September 11, 2018, and issued January 3, 2019. https://patentimages.storage.googleapis.com/f6/18/31/2c65eaeae74d8f/US20190002815A1.pdf.
Weidenbacher, L., A. Abrishamkar, M. Rottmar, A. G. Guex, K. Maniura-Weber, A. J. deMello, S. J. Ferguson, R. M. Rossi, and G. Fortunato. 2017. “Electrospraying of Microfluidic Encapsulated Cells for the Fabrication of Cell-Laden Electrospun Hybrid Tissue Constructs.” Acta Biomaterialia 64 (December): 137–47.
White, Lisa J., Adam J. Taylor, Denver M. Faulk, Timothy J. Keane, Lindsey T. Saldin, Janet E. Reing, Ilea T. Swinehart, Neill J. Turner, Buddy D. Ratner, and Stephen F. Badylak. 2017. “The Impact of Detergents on the Tissue Decellularization Process: A ToF-SIMS Study.” Acta Biomaterialia 50 (March): 207–19.
Widhe, Mona, Nancy Dekki Shalaly, and My Hedhammar. 2016. “A Fibronectin Mimetic Motif Improves Integrin Mediated Cell Biding to Recombinant Spider Silk Matrices.” Biomaterials 74 (January): 256–66.
Wolf, Matthew T., Kerry A. Daly, Janet E. Reing, and Stephen F. Badylak. 2012. “Biologic Scaffold Composed of Skeletal Muscle Extracellular Matrix.” Biomaterials 33 (10): 2916–25.
Yang, Hee Seok, Bora Lee, Jonathan H. Tsui, Jesse Macadangdang, Seok-Young Jang, Sung Gap Im, and Deok-Ho Kim. 2016. “Electroconductive Nanopatterned Substrates for Enhanced Myogenic Differentiation and Maturation.” Advanced Healthcare Materials 5 (1): 137–45.
Young, Bethany M., Keerthana Shankar, Brittany P. Allen, Robert A. Pouliot, Matthew B. Schneck, Nabil S. Mikhaiel, and Rebecca L. Heise. 2017. “Electrospun Decellularized Lung Matrix Scaffold for Airway Smooth Muscle Culture.” ACS Biomaterials Science & Engineering 3 (12): 3480–92.
Yu, Yin, Yahui Zhang, and Ibrahim T. Ozbolat. 2014. “A Hybrid Bioprinting Approach for Scale-Up Tissue Fabrication.” Journal of Manufacturing Science and Engineering 136 (6): 061013.
Zhang, Jian, Zhi Qian Hu, Neill J. Turner, Shi Feng Teng, Wen Yue Cheng, Hai Yang Zhou, Li Zhang, Hong Wei Hu, Qiang Wang, and Stephen F. Badylak. 2016. “Perfusion-Decellularized Skeletal Muscle as a Three-Dimensional Scaffold with a Vascular Network Template.” Biomaterials 89 (May): 114–26.
Cell-based Meat Science Discussion Series IV: The Cell Culture Medium, part 1
Growing cells ex vivo requires the same fundamental inputs as required in vivo: a mixture of a carbon-based energy source, amino acids, salts, vitamins, water, and other components to support cell viability and vitality. This mixture, known as the cell culture medium, is the most important factor in cell culture technology. Although cell culture is routinely performed in academic labs and industrial bioprocesses, creating the biomass required for cell-based meat to achieve mass-market penetration at competitive prices will demand significant reductions in costs, innovations for serum removal, and optimization across a diverse set of species and cell types. An overview of cell culture medium composition and the factors at play to achieve price parity with conventional meat are discussed below.
Common Components of Cell Culture Medium
The first instance of culturing tissues outside of the body came from Sydney Ringer in 1882. By creating a balanced salt solution with similar pH, osmolarity, and salt concentration to that of an animal’s body, Ringer was able to keep various animal tissues alive outside of the body for several days. Subsequent work in the following decades first demonstrated that culturing cells in the presence of blood plasma (i.e. serum) or embryonic extracts assisted in cellular proliferation and viability, allowing tissues to survive for longer periods of time. Over time, researchers identified the importance of glucose, amino acids, glutathione, insulin, and vitamins in the sera being used (Yao and Asayama 2017). Once this was known, scientists aimed at uncovering the additional unknown essential components of serum and other extracts that permitted cell proliferation and viability.
In the 1940s and 50s, working with the first immortalized cell lines such as L cells (Earle et al. 1943) and HeLa (discussed in Series I), scientists used iterative approaches to discover that low molecular weight dialyzed fractions of serum containing amino acids were necessary for cell survival. In 1955, Harry Eagle developed a Minimum Essential Medium by testing the amino acid requirements on several different cell lines, discovering that thirteen were indispensable (Figure 1). Eagle’s minimum essential medium additionally consists of glucose, six inorganic salts, eight water-soluble vitamins, and dialyzed serum. Variations on this medium were then derived using a variety of different cell lines as well as trial and error approaches that aimed at replacing serum with chemically defined components. These variations, including Dulbecco’s Minimum Essential Medium (DMEM), Iscove’s Modified DMEM, Ham’s F12, Medium 199, RPMI 1640, Leibovitz’s L-15, and others, still make up the majority of what are referred to as basal cell culture media in use for culturing the variety of cell types used today (Yao and Asayama 2017; Arora 2019).
What makes these formulations essential? Although formulations have been varied and optimized over time, the principal components of basal cell culture media have remained largely unchanged. Importantly, these variations may be cell-type specific, including for the cell types used in cell-based meat (described in Series I). Therefore, rather than discussing optimal conditions for a specific cell line or species, only the general roles of each component of common basal media including glucose, amino acids, inorganic salts, vitamins, and buffers are briefly discussed below.
Glucose (specifically D-glucose) is the most common energy input used in cell culture, although some media formulations use galactose or a combination of glucose and its metabolite, pyruvate. Industrially, it is produced enzymatically using amylase enzymes to breakdown starches from maize, potato, wheat, and other crops into constituent sugars used in various downstream products such as industrialized food, fermentation processes, or in this case, culturing of cells. Glucose enters the cell via transporter proteins on the cell surface, using either passive transport down its concentration gradient (more common) or ATP-dependent active transport. Once inside the cell, it serves as a reducing agent against oxidative stress in the form of NADPH generation via the pentose phosphate pathway, as well as a primary source of energy in the form of ATP generation via glycolysis.
In cell culture, glucose is used at concentrations between 5.5 and 55 mM, where the lower end is more common and similar to fasting blood glucose levels in humans. Different cell types will require different amounts of glucose. During periods of rapid cell proliferation and growth, as typically maintained during bioprocessing, glucose metabolism is high and can yield lactic acid even in the presence of sufficient oxygen, leading to pH changes (Zagari et al. 2013). Thus, glucose and lactic acid levels are commonly measured and tightly controlled throughout a bioprocess (discussed in Series II).
Amino acids are necessary to create proteins and other low molecular weight compounds such as nucleotides and small peptides. Amino acids can be split into two groups: essential and non-essential. Non-essential amino acids (NEAAs) can be synthesized de novo by an animal, whereas essential amino acids (EAAs) must be obtained through the diet. Generally speaking, pathways for the de novo synthesis of NEAAs are conserved in vertebrate species (Hou, Yin, and Wu 2015). In humans and many other animals, the EAAs include histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. NEAAs include alanine, arginine, asparagine, aspartate, cysteine, glutamate, glutamine, glycine, proline, serine, taurine, and tyrosine. However, EAA requirements can vary between species. For instance, dogs, cows, and pigs have the same EAA requirements as humans plus arginine, whereas cats and chickens require the same EAA as the former plus taurine and glycine, respectively.
Importantly, what is considered to be “essential” in cell culture is different than what is considered “essential” to a whole organism, as the diversity of cell types that may synthesize certain amino acids in vivo are not present in vitro (Figure 2). For instance, Eagle’s Minimum Essential Medium formulation lists 13 (L-enantiomer) amino acids as being essential across multiple cell lines in vitro: arginine, cysteine, glutamine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, tyrosine, and valine. As an example, arginine is essential in vitro as its biosynthesis in vivo primarily occurs between epithelial cells in the gut and proximal tubule cells of the kidney. Thus, arginine must be supplied in the absence of these cell types. Media that are particularly nutrient-rich (eg. DMEM/F12 or Medium 199) may contain all amino acids. Alternatively, NEAAs can be supplemented independently.
Industrialized production of amino acids can be obtained through bulk extraction from protein hydrolysates (discussed later), chemical synthesis, or microbial fermentation and purification, with the latter being the most common (D’Este, Alvarado-Morales, and Angelidaki 2018). Amino acids enter the cell through a variety of transporter proteins on the cell surface, at rates influenced by the cell’s state and consumption rates due to protein production levels, cell cycle state, and other parameters. Once inside the cell, amino acids serve as substrates for many biosynthetic pathways and optimal concentrations are important for maintaining metabolic equilibrium. The majority of carbon mass in proliferative cells is derived from bulk amino acids rather than glucose or L-glutamine, despite these being the most rapidly metabolized (Figure 3, Hosios et al. 2016).
Ultimately, the levels of amino acids required for cell culture are determined not only by their utilization by the growing cells, but also by individual amino acid solubility, stability, and interaction with other medium components such as metal cations, all of which can change once in a complex mixture (Salazar, Keusgen, and von Hagen 2016). Consideration for all of these variables is highly complex and a full understanding of amino acid behavior, utilization, and optimization in a bioprocess has yet to be accomplished. Given the variety of biosynthetic pathways that involve amino acids, it is likely that amino acid content, concentration, and perfusion rate (when applicable) will need to be optimized for a particular bioprocess across species and cell types for parameters such as growth rates or protein content in the final product. Computational approaches to model specific utilization rates of amino acids and other basal media components are an active area of research (Quiroga-Campano, Panoskaltsis, and Mantalaris 2018) (discussed later).
L-glutamine deserves special consideration as one of the most important amino acids included in cell culture media, as it is readily transported into cells and becomes a major contributor to protein biomass. It is a notable precursor of carbon and nitrogen-containing biomolecules such as the intermediate molecules used in the synthesis of other amino acids and nucleotides (DeBerardinis and Cheng 2010) and it can be added at concentrations 3-40x higher than other amino acids in the medium (Yao and Asayama 2017). During times of high cellular growth and proliferation, the demand for glutamine outpaces its supply, making it de facto an essential amino acid that can be readily metabolized as a replenishing alternative energy source (i.e. anaplerosis). At physiological pH in a cell culture medium solution, L-glutamine is unstable, resulting in its decomposition into pyroglutamate and ammonia, the latter of which is toxic to cells. Ammonia, therefore, is a tightly monitored and regulated metabolite in large scale bioprocesses that involve high densities of cells undergoing rapid growth (discussed in Series II).
In order to avoid some of these disadvantages of L-glutamine, glutamate — which is more stable in solution — can be substituted in when working with cells expressing high levels of glutamine synthetase, an enzyme which enables intracellular conversion of glutamate to glutamine while consuming ammonia in the process. A more common practice involves supplementation with L-glutamine as a stable dipeptide in the form of alanyl-glutamine (i.e. GlutaMAX) or glycyl-glutamine, which enable cells to endogenously cleave the dipeptide for more controlled usage of the amino acids in the dipeptide. There is still much to learn about amino acid metabolism in cell culture. For instance, recent discoveries suggest L-glutamine is entirely dispensable for the culture of pluripotent stem cells (Vardhana et al. 2019).
The inclusion of inorganic salts is important in establishing and maintaining the osmolarity of the cell with its surrounding cell culture medium solution as well as serving as enzymatic cofactors and important components of receptor and extracellular matrix proteins. These inorganic salts are composed of cations and anions that fully dissociate in solution. The original minimal essential medium solution contained six inorganic salts (calcium chloride, potassium chloride, magnesium sulfate, sodium chloride, sodium phosphate, and sodium bicarbonate), which are based on Earle’s salt solution. Other formulations include additional inorganic salts containing zinc, copper, and iron, which have particular importance for a variety of cellular functions (discussed later).
Although all cells maintain a resting membrane potential, excitable cells such as neurons and skeletal muscle cells are particularly sensitive to changes in ionic concentrations that can readily affect their functionality and viability. Several basal medium formulations have thus been optimized for salt concentrations for neuronal (Bardy et al. 2015) and skeletal muscle cell culture that more accurately recapitulate the interstitial fluids surrounding these cell types. The osmolality or measurement of osmotic pressure within the medium is typically between 260 to 320 mOSM/kg (milliosmoles per kg of solute), although this can vary with cell lines that are particularly robust in varying solute concentrations such as insect cells (Rubio et al. 2019). Changes in the salt concentration, either abruptly due to medium changing or slowly due to water evaporation, can lead to osmotic shock. Thus, maintenance of osmolarity is an important component of cell culture.
Vitamins are classes of organic compounds that serve as a critical component for the maintenance and growth of cells. Most vitamins are essential in that they need to be obtained directly from the diet or cell culture medium with few exceptions (e.g. vitamin D synthesized by fibroblasts and keratinocytes of the skin or some B vitamins produced in low levels by intestinal microbiota). Vitamins are classified as either fat-soluble or water-soluble and can serve broadly as enzymatic cofactors, antioxidants, and hormones. Vitamins are processed in a variety of ways in vivo following ingestion, often in a complex sequence that ends in absorption into intestinal cells via membrane surface transporters. This complex sequence involved in absorption can be largely avoided in vitro, as hostile environments (e.g. stomach acid) or barriers (e.g. the blood-brain-barrier) are absent (Said 2011). Thus, vitamins are typically included in a medium formulation as a single chemical compound that can be processed and absorbed directly by cells in vitro.
Vitamins can also effectively function as a group of compounds (i.e. vitamers) where each compound can serve the vitamin’s functional role, albeit with varying properties. The natural production of vitamins in microbes and plants has made industrial production of vitamins via microbial fermentation possible, however, improvements in metabolic engineering strategies are needed to increase yields and sustainability in the industry. For these reasons, some vitamins are produced more efficiently via chemical synthesis (Acevedo-Rocha et al. 2019).
Water-soluble vitamins including riboflavin (vitamin B2), nicotinamide (vitamin B3), pantothenic acid (vitamin B5), pyrodoxine and pyridoxal (vitamin B6), biotin (vitamin B7), i-inositol (vitamin B8), folic acid (vitamin B9), cyanocobalamin (vitamin B12), and choline are typically added to and “essential” in cell culture media, sometimes in various modified forms in order to provide stability. Fat-soluble vitamins A, D, E, and K are excluded in basal medium formulations but can be added if necessary when dissolved in an organic solvent. Similar to the different in vivo versus in vitro requirements of amino acids, fat-soluble vitamins play specific roles for certain cell types or bodily functions and are thus only “essential” when culturing a relevant cell type. For instance, a metabolite of vitamin A, retinoic acid, is an important developmental morphogen (discussed in detail later) and may be included as an additive in media to derive spinal motor neuron cells from pluripotent stem cells (Patani 2016). Special consideration for vitamin stability must be taken when using serum-free medium formulations (discussed later) as the lack of stabilizing serum proteins can lead to rapid degradation via light, heat, oxidation, or pH fluctuations (Schnellbaecher et al. 2019). These properties make it advisable to reconstitute powdered B vitamins immediately before use (discussed later).
Buffers are essential to cell culture systems as they serve to maintain pH at a constant level (for mammalian cells, generally 7.4 ± 0.4) despite changes in the composition of acids or bases that would otherwise alter the pH of the cell culture medium. Buffers are mixtures of a weak acid and its conjugate base or a weak base and its conjugate acid, where each mixture serves as a sponge to soak up free protons or hydroxide ions in solution, minimizing their effect on overall pH. Buffer systems in cell culture typically consist of either CO2-bicarbonate systems (Figure 4) or buffering agents such as HEPES. As discussed in Series II, a CO2-bicarbonate system can be achieved by exogenous addition of 5-10% gaseous CO2 (often delivered in bioreactor systems via sparging), which reaches equilibrium in solution with bicarbonate ions, forming a natural buffer system.
pH slowly changes over time due to the respiration of cells and the release of additional CO2, which forms carbonic acid in solution, in addition to the metabolism of glucose and the formation of lactic acid. The resultant decreasing pH changes are counteracted by the inclusion of sodium bicarbonate in the basal medium itself. Importantly, added sodium bicarbonate should be proportional to the atmospheric CO2 being used to maintain equilibrium. For instance, for media containing 1.5 to 2.2 g/L sodium bicarbonate, 5% CO2 is recommended, whereas 10% CO2 is recommended for media containing 3.7 g/L sodium bicarbonate.
HEPES is a zwitterionic buffer that can be used in cell culture systems as a supplemental buffer, especially in the absence of CO2 exposure. As one of Good’s buffers, its high solubility, low toxicity, and membrane impermeability have made it attractive for use in cell culture applications. In the scale-up of highly proliferative stem cell populations, dissolved CO2 due to high metabolism can reach levels that are deleterious for cell growth and nutrient utilization (Kimura and Miller 1996). Attempts have thus been made to limit dissolved CO2 by culturing cells in the presence of atmospheric CO2 levels with added buffering capacity from HEPES or other Good’s buffers (Brodsky et al. 2013). This strategy may be useful for future scale-up efforts in cell-based meat. Consideration for the cost of the buffer must also be weighed, as it may constitute the most expensive component of a basal media formulation at scale (Specht 2018).
Out of convenience, most academic and lab-scale cell culture is performed using commercially available premade liquid media. However, large volumes necessitate on-site preparation of liquid cell culture media from reconstituted powdered medium ingredients. Powdered medium is more efficiently transported and stored, resulting in cost savings and reduced degradation of fragile ingredients (e.g. B vitamins). Ideally, a powdered medium contains all of the components to be utilized and is created through a process known as micronization, where the average size of crystallized particles in the mix is reduced in order to increase solubility and homogeneity. When ready to use, the powder is typically reconstituted in a dedicated tank using high-quality water prepared by reverse osmosis, deionization, and filtration. The reconstituted medium is then itself sterilized by filtration (e.g. through a 0.22 µm filter), irradiation, or other methods discussed in Series II (e.g. pulsed electric fields). The use of sterilization involving high heat is precluded by some heat-labile ingredients that may be part of the formulation. Other preparation methods for additional ingredients are discussed throughout.
As previously mentioned, a basal medium formulation is often sufficient to keep cells alive for short periods of time, but in order for them to proliferate efficiently over extended periods of time, a variety of animal sera (e.g. fetal bovine serum, horse serum, and others) and extracts (e.g. chick embryo extract) have historically been used (notably, on a volumetric basis, serum-free formulations are now more dominant in their usage although FBS is still often included in routine cell culture in many academic settings and in some industrial settings). Serum is a high protein-containing mixture that contains growth and attachment factors, hormones, antioxidants, lipids, and other components (all described later) that mimic a proliferative, fetal-like state. Indeed, most sera used in cell culture are derived from fetal animals, which are rich in the necessary components and contain low immunoglobulin and complement content due to developmentally immature immune systems. As fetal bovine serum (FBS) is the most common sera used in cell culture, it will be used as a reference example throughout this section.
Originally employed in the late 1950s (Puck, Cieciura, and Robinson 1958), FBS has become a mainstay in biomedical research because it can supplement the growth of virtually all common human, animal, and even insect cell lines. As an added supplement for many cell culture applications in amounts typically 5-20% of total medium volume, FBS — when used — is often the most expensive part of performing cell culture.
FBS is harvested from a fetal calf any time during the last two-thirds of gestation following the discovery of pregnant cows due for slaughter. It has been estimated that up to 8% of cows in the slaughter line may be pregnant, making FBS a byproduct of the meat processing industry (van der Valk et al. 2018). It is prepared by the sterile collection of fetal blood followed by coagulation at low temperatures and centrifugation to remove clotting factors and blood cells. The serum supernatant is then filtered and assessed for a variety of quality controls including residual microbial or viral contamination, endotoxin, immunoglobulin content, and total protein, before being bottled and sold commercially, at prices exceeding $1000 USD per liter (at time of writing, July 2019) depending on quality control parameters (some described later), which vary by industry and use-case.
Despite its long history of use, FBS has several well-described issues that have made its replacement a priority in recent years. First, FBS contains hundreds or even thousands of different components and the true composition and amounts of these components are unknown, making it a chemically undefined product. The composition also varies by geographic region where a cow’s diet can vary, by batch within the same geographic region, by seasonality of collection, by the quantity and identity of antibiotics or hormones received by the mother, and by the gestational age of the fetus. Variability can also stem from a single bottled product originating from fetuses of different sexes (Elhofy, n.d.). This variability has led to a growing concern over serum’s contribution to irreproducibility of in vitro experiments within and between labs around the world (Baker 2016). Rigorous quality control involving testing of serum batches across multiple cell lines or experiments prior to purchasing a specific, well-performing large batch is often performed in industry but can remain burdensome from a labor and economic perspective for smaller academic labs. Thus, the inherent variability (Figure 5) and undefined nature of FBS use leads to compounding external costs in quality control testing, experimental irreproducibility or conflicting results, and follow-up research to dissect irreproducible signals.
Second, FBS is a potential source of contamination from multiple organisms, including Mycoplasma, viruses, and bovine spongiform encephalopathy. Mycoplasma are a class of parasitic bacteria that lead to metabolic and gene expression variations for infected cell lines. Mycoplasma are likely the most common cell line contaminant, with recent estimates showing 11% of cell lines being infected, and rates as high as 70% in geographical regions where testing is not routine (Olarerin-George and Hogenesch 2015). Although presently FBS is routinely filtered using 0.1 micron systems that should theoretically capture Mycoplasma, suppliers cannot make this guarantee. The common cell line contaminants M. arginini and A. laidlawii, in particular, have been linked in origin to FBS, and ongoing cross-contamination of cell lines has likely propagated this contamination in laboratories since the 1960s and 1970s when FBS batches were routinely positive for these bacteria (Drexler and Uphoff 2002). Additional methods to decontaminate serum from Mycoplasma include gamma irradiation, however, this can also damage growth factors and other proteins in the serum (Baker 2016). Thus, the use of FBS is responsible for a non-trivial amount of bacterial contamination in cell lines today, leading to compounding problems concerning reproducibility and potential unknown variability stemming from some decontamination practices.
In addition to bacterial contamination, the threat of adventitious viral agents in FBS also persists. Regulations under USDA and the EU mandate the testing and/or treatment (via heat or irradiation) of eight viruses known to be present in FBS from all geographical regions of origin (Hawkes 2015). Although modern production methods make the risk of contamination in a validated batch low, viral contamination is often still detectable in batches that manufacturer screens claim to be negative (Gagnieur et al. 2014). Similarly, the threat of FBS containing the causative prion proteins involved in bovine spongiform encephalopathy (i.e. Mad Cow Disease, which manifests in humans as variant Creutzfeldt-Jakob Disease) is persistent and requires additional testing as well as documented traceability for the FBS origin. For instance, countries such as the USA, New Zealand, and Australia have no documented cases of bovine spongiform encephalopathy; thus FBS originating from these countries may be considered ‘safer,’ often commanding significantly higher prices and collectively comprises up to 90% of the serum supply for commercial therapeutics (Schnitzler et al. 2015). This fact has also incentivized fraudulent activity in the field, where manufacturers may opt for fake labels from New Zealand in order to solicit higher prices (van der Valk et al. 2018). Industry associations have formed in an attempt to mitigate these concerns. Nevertheless, the inherent risk of contamination from FBS poses threats to experimental and bioprocess reproducibility, drives price fluctuations, and can even incentivize bad actors that value profit over safety. Contamination will be discussed further from a food safety perspective in Series V.
Third, there is a limited global supply of FBS and there exists competition for it from profitable, mature industries. For instance, while the vaccine and biologics industries have begun to move to serum-free formulations (discussed later), the rise of cell therapies and stem cell research more generally has ushered in an impending demand that exceeds current availability. Because FBS is a byproduct of a more lucrative product per animal (i.e. meat and dairy) and profits are retained by slaughterhouses rather than farmers, farmers have little incentive to increase cattle herds to meet a future FBS demand (Brindley et al. 2012). It has thus been hypothesized that “peak serum” has been met, with serum availability relatively stagnant and serum demand increasing dramatically as cell therapies begin to be approved (Figure 6, Brindley et al. 2012). The replacement of serum thus may be driven first by limited total availability followed by cost concerns that will spur replacement innovation in the field as non-pharmaceutical players are priced out. In the case of cell-based meat, this cost concern is already prohibitive, making FBS an economic nonstarter as meat products cannot be justified at prices that rival a cell-based therapeutic (currently at a cost of goods of approximately $50,000 and selling price of hundreds of thousands of dollars).
Lastly, the use of FBS carries ethical concerns, making its use inherently misaligned with one of the fundamental benefits of cell-based meat: animal welfare (discussed in Series VI). A single liter of serum requires 1-3 fetuses, with roughly 2 million fetal calves used in serum collection annually, totaling approximately 800,000 liters of FBS produced per year. The collection process involves removal of the fetus from the mother’s womb and aseptic collection of blood by a syringe placed directly into the beating heart as this contains unclotted blood, raising concerns that the fetus could consciously experience the event as painful (van der Valk et al. 2018). Thus, the search for serum-free formulations (discussed later) is in alignment with the cell-based meat industry and general animal welfare concerns, manifested by replacement, reduction, or refinement of animal experiments or animal-based products in science.
The next series on cell culture medium will explore the components of serum that have made it a near-universal cell culture supplement and approaches for replacing serum in a cost-effective manner.
- Acevedo-Rocha, Carlos G., Luisa S. Gronenberg, Matthias Mack, Fabian M. Commichau, and Hans J. Genee. 2019. “Microbial Cell Factories for the Sustainable Manufacturing of B Vitamins.” Current Opinion in Biotechnology 56 (April): 18–29.
- Arora, Meenakshi. 2019. “Cell Culture Media: A Review.” Materials and Methods , August. https://doi.org///dx.doi.org/10.13070/mm.en.3.175.
- Baker, Monya. 2016. “Reproducibility: Respect Your Cells!” Nature 537 (7620): 433–35.
- Bardy, Cedric, Mark van den Hurk, Tameji Eames, Cynthia Marchand, Ruben V. Hernandez, Mariko Kellogg, Mark Gorris, et al. 2015. “Neuronal Medium That Supports Basic Synaptic Functions and Activity of Human Neurons in Vitro.” Proceedings of the National Academy of Sciences of the United States of America 112 (20): E2725–34.
- Brindley, David A., Natasha L. Davie, Emily J. Culme-Seymour, Chris Mason, David W. Smith, and Jon A. Rowley. 2012. “Peak Serum: Implications of Serum Supply for Cell Therapy Manufacturing.” Regenerative Medicine 7 (1): 7–13.
- Brodsky, Arthur Nathan, Jing Zhang, Richard P. Visconti, and Sarah W. Harcum. 2013. “Expansion of Mesenchymal Stem Cells under Atmospheric Carbon Dioxide.” Biotechnology Progress 29 (5): 1298–1306.
- DeBerardinis, R. J., and T. Cheng. 2010. “Q’s next: The Diverse Functions of Glutamine in Metabolism, Cell Biology and Cancer.” Oncogene 29 (3): 313–24.
- D’Este, Martina, Merlin Alvarado-Morales, and Irini Angelidaki. 2018. “Amino Acids Production Focusing on Fermentation Technologies - A Review.” Biotechnology Advances 36 (1): 14–25.
- Drexler, Hans G., and Cord C. Uphoff. 2002. “Mycoplasma Contamination of Cell Cultures: Incidence, Sources, Effects, Detection, Elimination, Prevention.” Cytotechnology 39 (2): 75–90.
- Earle, Wilton R., Edward L. Schilling, Thomas H. Stark, Nancy P. Straus, Mary F. Brown, and Emma Shelton. 1943. “Production of Malignancy in Vitro. IV. The Mouse Fibroblast Cultures and Changes Seen in the Living Cells.” Journal of the National Cancer Institute 4 (2): 165–212.
- Elhofy, Adam. n.d. “Serum and Its Applicability and Use in Cell Culture.” https://pdfs.semanticscholar.org/8388/48042dabfe7221887dc8484c4833c694b9ad.pdf.
- Gagnieur, Léa, Justine Cheval, Marlène Gratigny, Charles Hébert, Erika Muth, Marine Dumarest, and Marc Eloit. 2014. “Unbiased Analysis by High Throughput Sequencing of the Viral Diversity in Fetal Bovine Serum and Trypsin Used in Cell Culture.” Biologicals: Journal of the International Association of Biological Standardization 42 (3): 145–52.
- Hawkes, Percy William. 2015. “Fetal Bovine Serum: Geographic Origin and Regulatory Relevance of Viral Contamination.” Bioresources and Bioprocessing 2 (1): 34.
- Hosios, Aaron M., Vivian C. Hecht, Laura V. Danai, Marc O. Johnson, Jeffrey C. Rathmell, Matthew L. Steinhauser, Scott R. Manalis, and Matthew G. Vander Heiden. 2016. “Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells.” Developmental Cell 36 (5): 540–49.
- Hou, Yongqing, Yulong Yin, and Guoyao Wu. 2015. “Dietary Essentiality of ‘Nutritionally Non-Essential Amino Acids’ for Animals and Humans.” Experimental Biology and Medicine 240 (8): 997–1007. Kimura, R., and W. M. Miller. 1996. “Effects of Elevated pCO(2) And/or Osmolality on the Growth and Recombinant tPA Production of CHO Cells.” Biotechnology and Bioengineering 52 (1): 152–60.
- Olarerin-George, Anthony O., and John B. Hogenesch. 2015. “Assessing the Prevalence of Mycoplasma Contamination in Cell Culture via a Survey of NCBI’s RNA-Seq Archive.” Nucleic Acids Research 43 (5): 2535–42.
- Patani, Rickie. 2016. “Generating Diverse Spinal Motor Neuron Subtypes from Human Pluripotent Stem Cells.” Stem Cells International 2016: 1036974.
- Puck, T. T., S. J. Cieciura, and A. Robinson. 1958. “Genetics of Somatic Mammalian Cells. III. Long-Term Cultivation of Euploid Cells from Human and Animal Subjects.” The Journal of Experimental Medicine 108 (6): 945–56.
- Quiroga-Campano, Ana L., Nicki Panoskaltsis, and Athanasios Mantalaris. 2018. “Energy-Based Culture Medium Design for Biomanufacturing Optimization: A Case Study in Monoclonal Antibody Production by GS-NS0 Cells.” Metabolic Engineering 47 (May): 21–30.
- Rubio, Natalie R., Kyle D. Fish, Barry A. Trimmer, and David L. Kaplan. 2019. “Possibilities for Engineered Insect Tissue as a Food Source.” Frontiers in Sustainable Food Systems 3: 24.
- Said, Hamid M. 2011. “Intestinal Absorption of Water-Soluble Vitamins in Health and Disease.” Biochemical Journal 437 (3): 357–72. Salazar, Andrew, Michael Keusgen, and Jörg von Hagen. 2016. “Amino Acids in the Cultivation of Mammalian Cells.” Amino Acids 48 (5): 1161–71.
- Schnellbaecher, Alisa, Dennis Binder, Stephanie Bellmaine, and Aline Zimmer. 2019. “Vitamins in Cell Culture Media: Stability and Stabilization Strategies.” Biotechnology and Bioengineering 116 (6): 1537–55.
- Schnitzler, Aletta C., Anjali Verma, Daniel E. Kehoe, Donghui Jing, Julie R. Murrell, Kara A. Der, Manjula Aysola, Peter J. Rapiejko, Sandhya Punreddy, and Martha S. Rook. 2015. “Bioprocessing of Human Mesenchymal Stem/stromal Cells for Therapeutic Use: Current Technologies and Challenges.” Biochemical Engineering Journal, September, 1–11.
- Specht, Liz. 2018. “An Analysis of Culture Medium Costs and Production Volumes for Cell-Based Meat.” The Good Food Institute. https://www.gfi.org/files/sci-tech/clean-meat-production-volume-and-medium-cost.pdf.
- Valk, Jan van der, Karen Bieback, Christiane Buta, Brett Cochrane, Wilhelm G. Dirks, Jianan Fu, James J. Hickman, et al. 2018. “Fetal Bovine Serum (FBS): Past - Present - Future.” ALTEX 35 (1): 99–118. Vardhana, Santosha A., Paige K. Arnold, Bess P. Rosen, Yanyang Chen, Bryce W. Carey, Danwei Huangfu, Carlos Carmona-Fontaine, Craig B. Thompson, and Lydia W. S. Finley. 2019. “Glutamine Independence Is a Selectable Feature of Pluripotent Stem Cells.” Nature Metabolism, July. https://doi.org/10.1038/s42255-019-0082-3.
- Yao, Tatsuma, and Yuta Asayama. 2017. “Animal-Cell Culture Media: History, Characteristics, and Current Issues.” Reproductive Medicine and Biology 16 (2): 99–117.
- Zagari, Francesca, Martin Jordan, Matthieu Stettler, Hervé Broly, and Florian M. Wurm. 2013. “Lactate Metabolism Shift in CHO Cell Culture: The Role of Mitochondrial Oxidative Activity.” New Biotechnology 30 (2): 238–45.
Acevedo-Rocha, Carlos G., Luisa S. Gronenberg, Matthias Mack, Fabian M. Commichau, and Hans J. Genee. 2019. “Microbial Cell Factories for the Sustainable Manufacturing of B Vitamins.” Current Opinion in Biotechnology 56 (April): 18–29.
Arora, Meenakshi. 2019. “Cell Culture Media: A Review.” Materials and Methods , August. https://doi.org///dx.doi.org/10.13070/mm.en.3.175.
Baker, Monya. 2016. “Reproducibility: Respect Your Cells!” Nature 537 (7620): 433–35.
Bardy, Cedric, Mark van den Hurk, Tameji Eames, Cynthia Marchand, Ruben V. Hernandez, Mariko Kellogg, Mark Gorris, et al. 2015. “Neuronal Medium That Supports Basic Synaptic Functions and Activity of Human Neurons in Vitro.” Proceedings of the National Academy of Sciences of the United States of America 112 (20): E2725–34.
Brindley, David A., Natasha L. Davie, Emily J. Culme-Seymour, Chris Mason, David W. Smith, and Jon A. Rowley. 2012. “Peak Serum: Implications of Serum Supply for Cell Therapy Manufacturing.” Regenerative Medicine 7 (1): 7–13.
Brodsky, Arthur Nathan, Jing Zhang, Richard P. Visconti, and Sarah W. Harcum. 2013. “Expansion of Mesenchymal Stem Cells under Atmospheric Carbon Dioxide.” Biotechnology Progress 29 (5): 1298–1306.
DeBerardinis, R. J., and T. Cheng. 2010. “Q’s next: The Diverse Functions of Glutamine in Metabolism, Cell Biology and Cancer.” Oncogene 29 (3): 313–24.
D’Este, Martina, Merlin Alvarado-Morales, and Irini Angelidaki. 2018. “Amino Acids Production Focusing on Fermentation Technologies - A Review.” Biotechnology Advances 36 (1): 14–25.
Drexler, Hans G., and Cord C. Uphoff. 2002. “Mycoplasma Contamination of Cell Cultures: Incidence, Sources, Effects, Detection, Elimination, Prevention.” Cytotechnology 39 (2): 75–90.
Earle, Wilton R., Edward L. Schilling, Thomas H. Stark, Nancy P. Straus, Mary F. Brown, and Emma Shelton. 1943. “Production of Malignancy in Vitro. IV. The Mouse Fibroblast Cultures and Changes Seen in the Living Cells.” Journal of the National Cancer Institute 4 (2): 165–212.
Elhofy, Adam. n.d. “Serum and Its Applicability and Use in Cell Culture.” https://pdfs.semanticscholar.org/8388/48042dabfe7221887dc8484c4833c694b9ad.pdf.
Gagnieur, Léa, Justine Cheval, Marlène Gratigny, Charles Hébert, Erika Muth, Marine Dumarest, and Marc Eloit. 2014. “Unbiased Analysis by High Throughput Sequencing of the Viral Diversity in Fetal Bovine Serum and Trypsin Used in Cell Culture.” Biologicals: Journal of the International Association of Biological Standardization 42 (3): 145–52.
Hawkes, Percy William. 2015. “Fetal Bovine Serum: Geographic Origin and Regulatory Relevance of Viral Contamination.” Bioresources and Bioprocessing 2 (1): 34.
Hosios, Aaron M., Vivian C. Hecht, Laura V. Danai, Marc O. Johnson, Jeffrey C. Rathmell, Matthew L. Steinhauser, Scott R. Manalis, and Matthew G. Vander Heiden. 2016. “Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells.” Developmental Cell 36 (5): 540–49.
Hou, Yongqing, Yulong Yin, and Guoyao Wu. 2015. “Dietary Essentiality of ‘Nutritionally Non-Essential Amino Acids’ for Animals and Humans.” Experimental Biology and Medicine 240 (8): 997–1007.
Kimura, R., and W. M. Miller. 1996. “Effects of Elevated pCO(2) And/or Osmolality on the Growth and Recombinant tPA Production of CHO Cells.” Biotechnology and Bioengineering 52 (1): 152–60.
Olarerin-George, Anthony O., and John B. Hogenesch. 2015. “Assessing the Prevalence of Mycoplasma Contamination in Cell Culture via a Survey of NCBI’s RNA-Seq Archive.” Nucleic Acids Research 43 (5): 2535–42.
Patani, Rickie. 2016. “Generating Diverse Spinal Motor Neuron Subtypes from Human Pluripotent Stem Cells.” Stem Cells International 2016: 1036974.
Puck, T. T., S. J. Cieciura, and A. Robinson. 1958. “Genetics of Somatic Mammalian Cells. III. Long-Term Cultivation of Euploid Cells from Human and Animal Subjects.” The Journal of Experimental Medicine 108 (6): 945–56.
Quiroga-Campano, Ana L., Nicki Panoskaltsis, and Athanasios Mantalaris. 2018. “Energy-Based Culture Medium Design for Biomanufacturing Optimization: A Case Study in Monoclonal Antibody Production by GS-NS0 Cells.” Metabolic Engineering 47 (May): 21–30.
Rubio, Natalie R., Kyle D. Fish, Barry A. Trimmer, and David L. Kaplan. 2019. “Possibilities for Engineered Insect Tissue as a Food Source.” Frontiers in Sustainable Food Systems 3: 24.
Said, Hamid M. 2011. “Intestinal Absorption of Water-Soluble Vitamins in Health and Disease.” Biochemical Journal 437 (3): 357–72.
Salazar, Andrew, Michael Keusgen, and Jörg von Hagen. 2016. “Amino Acids in the Cultivation of Mammalian Cells.” Amino Acids 48 (5): 1161–71.
Schnellbaecher, Alisa, Dennis Binder, Stephanie Bellmaine, and Aline Zimmer. 2019. “Vitamins in Cell Culture Media: Stability and Stabilization Strategies.” Biotechnology and Bioengineering 116 (6): 1537–55.
Schnitzler, Aletta C., Anjali Verma, Daniel E. Kehoe, Donghui Jing, Julie R. Murrell, Kara A. Der, Manjula Aysola, Peter J. Rapiejko, Sandhya Punreddy, and Martha S. Rook. 2015. “Bioprocessing of Human Mesenchymal Stem/stromal Cells for Therapeutic Use: Current Technologies and Challenges.” Biochemical Engineering Journal, September, 1–11.
Specht, Liz. 2018. “An Analysis of Culture Medium Costs and Production Volumes for Cell-Based Meat.” The Good Food Institute. https://www.gfi.org/files/sci-tech/clean-meat-production-volume-and-medium-cost.pdf.
Valk, Jan van der, Karen Bieback, Christiane Buta, Brett Cochrane, Wilhelm G. Dirks, Jianan Fu, James J. Hickman, et al. 2018. “Fetal Bovine Serum (FBS): Past - Present - Future.” ALTEX 35 (1): 99–118.
Vardhana, Santosha A., Paige K. Arnold, Bess P. Rosen, Yanyang Chen, Bryce W. Carey, Danwei Huangfu, Carlos Carmona-Fontaine, Craig B. Thompson, and Lydia W. S. Finley. 2019. “Glutamine Independence Is a Selectable Feature of Pluripotent Stem Cells.” Nature Metabolism, July. https://doi.org/10.1038/s42255-019-0082-3.
Yao, Tatsuma, and Yuta Asayama. 2017. “Animal-Cell Culture Media: History, Characteristics, and Current Issues.” Reproductive Medicine and Biology 16 (2): 99–117.
Zagari, Francesca, Martin Jordan, Matthieu Stettler, Hervé Broly, and Florian M. Wurm. 2013. “Lactate Metabolism Shift in CHO Cell Culture: The Role of Mitochondrial Oxidative Activity.” New Biotechnology 30 (2): 238–45.