Cultivated meat (also cultured, cell-cultured, in vitro meat) uses tissue engineering to produce meat for food (Datar and Betti, 2010; Post, 2012; Post and Hocquette, 2017). Canonically, this research has focused on recreating the muscle component of meat (Post, 2012; Benjaminson et al., 2002; Simsa et al., 2019; Ben-Arye et al., 2020; Furuhashi et al., 2021; Verbruggen et al., 2018). However, fat is key to the taste and texture of meat (He et al., 2020; Moritz et al., 2015; Frank et al., 2016; Frank et al., 2017). For example, peak evaluation scores were achieved with beef samples containing ~36% crude fat (Iida et al., 2015). Hundreds of volatile compounds are released when meat is cooked, with a majority originating from lipids (Frank et al., 2017; Ba et al., 2012; Mottram et al., 1982). Fat is also responsible for the species-specific flavor of meat, making it important for reproducing the flavors of specific animals (Ramalingam et al., 2019). In addition to cultivated meat, in vitro-grown fat could also be used to enhance existing plant-based meats, as complex species-specific flavors of animals are difficult to recapitulate de novo (Fish et al., 2020; van Vliet et al., 2021; Bohrer, 2019).

While cultured fat stands to greatly improve the quality of alternative proteins, producing macroscale tissues remains a major challenge due to mass transport limitations. Even millimeter-scale in vitro tissues are challenging to generate, as oxygen and nutrients are only able to diffuse through several hundred microns of dense tissue (Coyle et al., 2019; Murphy et al., 2017; Helmlinger et al., 1997; Jain et al., 2005). Various approaches have been implemented in tissue engineering to overcome diffusion limitations, such as vascularization and the incorporation of perfusion channels (Kolesky et al., 2016; Sarig-Nadir et al., 2009; Li et al., 2018; Lovett et al., 2007; Lai et al., 2009; Muller et al., 2019; Kang et al., 2009; Louis et al., 2021; Volz et al., 2019; Wittmann et al., 2015; Yang et al., 2020). However, current strategies are often limited by scalability and complexity. A dense array is required when incorporating perfusion channels, as all tissues must remain within several hundred microns of a channel (Yamamoto et al., 2012). For adipose tissue, lipid accumulation decreases considerably once cells are ~1 mm away from a perfusion channel (Li et al., 2018). Vascularization of macroscale tissues is achieved via co-culture with endothelial cells, which spontaneously organize into capillary-sized vessels (Andrée et al., 2019). However, spontaneous vessel formation may not be feasible for centimeter- to meter-scale tissues, as cultivated cells may die during the time required for the vasculature to form (Unal et al., 2018). Capillaries may also be too small to deliver a sufficient volume of media when supporting larger tissues (Tetzlaff and Fischer, 2018; Moya et al., 2013). Thus, many challenges remain to scale fat (and other) tissues to bulk production levels.

In this study, our goal was to develop a relatively simple method of producing bulk cultured fat tissue that circumvents contemporary mass transport limitations. This was achieved by growing murine and porcine adipocytes in thin layers with easy access to the culture media, followed by post-growth aggregation into 3D adipose after sufficient adipocyte maturation (Figure 1). Aggregation at the end of cell culture removed the need for nutrient delivery via vascularization or elaborate 3D tissue perfusion, thus reducing costs and improving scalability. This approach is feasible when creating tissue solely for food purposes, as there is no requirement for continued cell survival once the final edible tissue is produced. This paradigm allows for simpler approaches and outcomes in comparison to regenerative medicine goals.

Figure 1

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We hypothesized that aggregating individual adipocytes would be sufficient to reproduce the taste, nutrition, and texture profile of fat, as adipose tissue in vivo is a dense aggregation of lipid-filled adipocytes with a sparse extracellular matrix (ECM) (Mescher, 2021). Lipid-filled adipocytes were grown in vitro and aggregated into bulk macroscale tissues within suitable matrices, then compared with native adipose tissue from various animals. Cultured fat and native adipose samples were characterized for lipid droplet morphology and mechanical properties to infer textural characteristics. The fatty acid compositions of cultured adipocytes were also analyzed to garner insight into flavor and nutrition.

Our goal was to generate macroscale fat tissue for food applications. To achieve this, we circumvented the limitations of macroscale tissue engineering and 3D cell culture by first culturing murine and porcine adipocytes on 2D surfaces with ample access to the culture media, then aggregating the cells into macroscale 3D tissues after in vitro adipogenesis. This approach is feasible for food applications, as opposed to regenerative medicine needs, because cell viability does not need to be maintained once the final macroscale fat tissue is produced.

We were first able to generate considerable amounts of highly lipid-laden murine adipocytes bearing morphological resemblance to native adipose tissues. Most studies that investigate 3T3-L1 adipogenesis in 2D are of limited culture duration (≤15 days), with lipid accumulation manifesting as small lipid droplets (Sheng et al., 2014; Neal and Clipstone, 2002; Sharma et al., 2018; Wang et al., 2013; Pazienza et al., 2016; Bogan et al., 2001; Park et al., 2018). Here, we show that extended 2D culture (30 days) of in vitro adipocytes resulted in the emergence of larger lipid droplets, a key trait of white adipose tissue. Abundant lipids were also observed in porcine adipocytes, especially with 0–2% serum. Enhanced adipogenesis in low serum or serum-free media has been reported by numerous groups; the diminished lipid accumulation found in adipocytes differentiated in high serum conditions (e.g., 20% in this study) may be due to factors in FBS, such as transforming growth factor β, that have been found to be pro-proliferative and anti-adipogenic (Jurek et al., 2020; Mitić et al., 2023; Lee et al., 2012; Entenmann and Hauner, 1996; Sandhu et al., 2017; Sprenger et al., 2021; Boone et al., 2000; Suryawan and Hu, 1993). Indeed, our results with porcine adipocytes in 20% FBS show increased nuclei and decreased lipid accumulation during differentiation. Despite the abundant lipid accumulation observed in in vitro porcine adipocytes cultured with 0-2% FBS, intracellular lipid accumulation was multilocular. A multilocular phenotype can signify adipocyte browning, indicating the presence of beige or brown fat (Jung et al., 2019). However, the lipid morphology observed in the Yorkshire pig DFAT cells of this study likely represents an immature white adipocyte phenotype, as Yorkshire pigs reportedly have no brown adipose tissue (due to the lack of a functional UCP1 gene) (Zheng et al., 2017; Berg et al., 2006). Optimizations to the in vitro environment and culture regime may help enhance lipid accumulation and promote a unilocular phenotype (Hsiao et al., 2016; Sun et al., 2013). For example, in this study we found that Intralipid supplementation drastically increased porcine cell adipogenesis. In this study, porcine dedifferentiated fat (DFAT) cells were used as adipocytes as they been reported to proliferate and accumulate lipids for at least 50 passages while maintaining expression of adipocyte-specific genes such as PPARγ (Nobusue and Kano, 2010). Additionally, DFAT cells have been shown to accumulate more intracellular lipids than adipose-derived stromal vascular cells, making them a better choice for large-scale cultured fat production (Peng et al., 2015).

After in vitro adipocyte generation, mechanical aggregation of the cells during cell scraping immediately produced what looked like fat tissue. Murine adipocytes were then combined with food-relevant binders to maintain aggregation and tissue integrity. Uniaxial compression testing of alginate-based cultured fat tissues revealed similar stress-strain behaviors to native fat tissues, while mTG crosslinked adipocytes exhibited weaker resistance to compression closer to rendered fats. As mTG has been shown to greatly strengthen protein-rich materials, the weaker mTG fat tissues may be due to a lack of extracellular protein available for crosslinking among the aggregated in vitro adipocytes (Broderick et al., 2005). Thus, to strengthen mTG fat tissues it may be beneficial to mix in additional proteins such as soy (Dreher et al., 2020). It would also be interesting to investigate whether upregulating ECM deposition would improve mTG crosslinking, especially since ECM-promoting culture media components like ascorbic acid have also been shown to improve in vitro adipogenesis (Jurek et al., 2020; Cuaranta-Monroy et al., 2014; Liu et al., 2017; Kim et al., 2013; Thorrez et al., 2018). Ultimately, the mechanical properties of aggregated cultured fat tissues were tunable based on the binding technique used (alginate versus mTG), as well as via the concentration of binder (0.8 versus 1.6% alginate).

When investigating the TAG compositions of in vitro-grown fats, we found murine 3T3-L1 cells to differ from native fats, notably being deficient in 18:1 and 18:2 while being enriched in 16:1 and shorter chained SFAs. It has been shown that rodents lacking dietary oleic acid (18:1 ω-9) compensated with higher levels of 16:1, as endogenous production of oleic acid is insufficient to achieve the amounts typically found in normal tissue (Bourre et al., 1997). Primary porcine adipocytes on the other hand achieved a closer FA profile their native equivalents, though slightly lacking in certain FAs such as 18:2. The scarce presence of 18:2 for both murine and porcine cells is likely due an inability for mammals to synthesize linoleic acid (18:2 ω-6), which may highlight the importance of its supplementation during in vitro culture (Hansen, 1986; Malcicka et al., 2018). Indeed, Intralipid treatment (44–62% linoleic acid) enriched 18:2 and raised overall PUFA levels for all in vitro adipocytes, with murine cells additionally achieving more similarity to native mouse fats in terms of 16:1 and 18:1 levels (Abdelghany et al., 2020). The increase in 18:3 from Intralipid across murine and porcine adipocytes represents a potential enrichment in omega 3 PUFAs, as 18:3 in soybean oil is alpha-linoleic acid. These changes suggest that lipid supplementation may be useful for tuning in vitro adipocyte TAGs to address deficiencies in particular FAs, enhance specific FAs, or more closely match the composition of native fats.

As phospholipids have been reported to contribute significantly to meat flavor, we additionally looked at IVF phospholipid FAs (Mottram and Edwards, 1983; Huang et al., 2010). In vitro porcine adipocytes were found to contain similar ratios of phospholipid FAs with their in vivo counterparts, although they notably contained fewer 20:4 and 18:2 FAs than the native fat samples tested. As linoleic acid (18:2) is a precursor to arachidonic acid (20:4 ω-6), it was possible that low 20:4 was due to a lack of 18:2. However, Intralipid-treated porcine IVFs did not show increased 20:4 despite having increases in 18:2. 20:4 levels in porcine IVFs were not uncommonly low though, achieving the same value as reported elsewhere for pig fat (1.4% of all FAs) (Dinh et al., 2021). High 20:4 in our native pig samples could be related to how native pork fat FAs are very pliable based on the animal’s diet (Wood et al., 2008). Ultimately, optimal intracellular 20:4 levels are unclear, as arachidonic acid has been linked with both inflammation and enhanced meat flavor (Calder, 2006; Adam et al., 2003; Takahashi, 2018). If desired, raising 20:4 may be possible through supplementation during cell culture, or via genetic interventions (Takahashi, 2018; Rouzer et al., 2006; Gol et al., 2018). For murine IVF phospholipids, Intralipid did not raise 18:2 despite its high linoleic acid content (Abdelghany et al., 2020). This could be due to genetic influence over phospholipid FAs and our use of the 3T3-L1 cell line (less representative of native adipocytes). It has been reported that different strains of mice can have varying phospholipid compositions when fed the same diet (Hulbert et al., 2006). While useful as a preliminary assessment on the potential flavor or aroma profiles of cultured fat, phospholipid FA profiles are not considered a definitive analysis on fat flavor and aroma. There is thus a need in the field for further research comparing the flavor profiles of cultured fats with native fats and plant-based alternatives, such as via sensory evaluation panels where human participants taste or smell food samples with cultured fat (Iida et al., 2015). Gas chromatography/mass spectrometry approaches may also be explored for a quantitative analysis of the various volatile compounds present in the aromas of cultured and in vivo fats (Watanabe et al., 2008).

As a result of the comparable fatty acid compositions between in vitro and native fats (especially for primary porcine cells), similar caloric values may be expected for in vitro and native fats on a ‘per gram of lipid’ basis. However, structured cultured fat tissues in this study may have lowered caloric values due to adipocyte dilution (e.g., the 1:1 mixing of alginate and adipocytes in this study). Here, alternate adipocyte binding protocols and materials may be pursued to create cultured fat tissues with larger proportions of cultured adipocytes. For example, mixing cell-cultured adipocytes with more concentrated alginate would allow a smaller volume to be added for the same final alginate percentage. Other binder materials such as locust bean gum may also be used, which can be dispersed into cultured adipocytes as a powder and then formed into a gel after heating (thus minimally diluting the in vitro-grown adipocytes) (Dionísio and Grenha, 2012). With future efforts, characterizations such as calorimetry may be useful for quantifying any differences in caloric value between cultured and in vivo fat tissues. In this realm, thermogravimetric analyses may also be useful for assessing the cooking behavior of cultured fat tissues.

Aggregating in vitro adipocytes to generate cell-cultured animal fat using various binders unlocks a simplified approach of producing bulk cultured fat tissue with lower costs and direct scalability, addressing a key obstacle in cultivated meat production and contributing to the paradigm of food production using cell culture techniques. The adipocyte aggregation approach is cell type and species agnostic, as demonstrated via the 3T3-L1s (adipogenic fibroblasts) and primary porcine DFAT cells (mesenchymal stem cell-like cells) in this study. While laboratory techniques (2D culture in tissue culture flasks) were used to produce the adipocytes for aggregation in this study, the concept of generating adipose tissues for food via the aggregation of individual fat cells should be applicable to cells generated in larger-scale bioreactor systems (Figure 7). For example, adherent preadipocytes could be proliferated and differentiated en masse in various fixed bed bioreactors, after which they are harvested (e.g., by spraying fluid onto the cells to detach them) (Leinonen et al., 2020; Pörtner and Platas Barradas, 2007; Hanley et al., 2014; Leung et al., 2022; Yuen et al., 2022). The large-scale generation of adipocytes might also be achieved in suspension bioreactors using microcarrier, spheroid/aggregate approaches, or through cell adaptation to single cell suspension (Yuen et al., 2022; Frye and Patrick, 2006; Lohr et al., 2010; Nahmias and Cohen, 2020; Bellani et al., 2020). Once produced, adipocytes can then be formed into structured cultured fat tissues by mixing with binder or crosslinking ingredients. Cultured adipocytes can also be directly added to food products (e.g., soups and sauces) as an unstructured fat biomass. Incorporating cultured fats or fat tissues into plant-based meats permits the creation of hybrid products, where sustainable and low-cost plant ingredients are enhanced by the complex species-specific flavors that arise from added animal fat cells. Taken together, these approaches offer a potential path to producing meat (or realistic meat alternatives) without animal slaughter, while potentially being more sustainable than conventional meat production (Tuomisto et al., 2014; Tuomisto and de Mattos, 2011; Sun et al., 2015; Mattick et al., 2015; Odegard and Sinke, 2021).

Figure 7

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Datasets for our mouse lipidomics data (Figure 3) are included in Supplementary Files 4 and 5. For our porcine lipidomics, datasets are included in Supplementary Files 6 and 7. For lipidomics, this includes tables depicting the top 50 FAs present in our lipidomics analyses for triacylglyceridesTAGs and phospholipids, as well as separate files containing full lists of FAs detected. Our full LC-MS/MS peak aligned and lipid species identified dataset has been uploaded publicly at https://doi.org/10.7910/DVN/DXGQNH.

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Author details

1. John Se Kit Yuen Jr

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9854-1654

2. Michael K Saad

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Data curation, Software, Formal analysis, Validation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Ning Xiang

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Investigation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

4. Brigid M Barrick

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Formal analysis, Investigation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

5. Hailey DiCindio

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Formal analysis, Investigation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

6. Chunmei Li

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Supervision, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

7. Sabrina W Zhang

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Formal analysis, Investigation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

8. Miriam Rittenberg

   Biological Engineering Department, MIT, Cambridge, United States

   Contribution

   Software, Writing – review and editing

   Competing interests

   No competing interests declared

9. Emily T Lew

   Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

   Contribution

   Investigation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

10. Kevin Lin Zhang

    Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

    Contribution

    Data curation, Formal analysis, Investigation, Visualization, Writing – review and editing

    Competing interests

    No competing interests declared

11. Glenn Leung

    Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

    Contribution

    Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

12. Jaymie A Pietropinto

    Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

13. David L Kaplan

    Biomedical Engineering Department, Tissue Engineering Resource Center, Tufts University, Medford, United States

    Contribution

    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Project administration, Writing – review and editing

    For correspondence

    David.Kaplan@tufts.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9245-7774

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