Human mesenchymal stromal cells (MSCs) are promising candidates for cell therapy due to their ease of isolation and expansion and their ability to secrete antiapoptotic, pro-angiogenic, and immunomodulatory factors. Three-dimensional (3D) aggregation “self-activates” MSCs to augment their pro-angiogenic and immunomodulatory potential, but the microenvironmental features and culture parameters that promote optimal MSC immunomodulatory function in 3D aggregates are poorly understood. Here, we generated MSC aggregates via three distinct methods and compared them with regard to their (a) aggregate structure and (b) immunomodulatory phenotype under resting conditions and in response to inflammatory stimulus. Methods associated with fast aggregation kinetics formed aggregates with higher cell packing density and reduced extracellular matrix (ECM) synthesis compared to those with slow aggregation kinetics. While all three methods of 3D aggregation enhanced MSC expression of immunomodulatory factors compared to two-dimensional culture, different aggregation methods modulated cells' temporal expression of these factors. A Design of Experiments approach, in which aggregate size and aggregation kinetics were systematically covaried, identified a significant effect of both parameters on MSCs' ability to regulate immune cells. Compared to small aggregates formed with fast kinetics, large aggregates with slow assembly kinetics were more effective at T-cell suppression and macrophage polarization toward anti-inflammatory phenotypes. Thus, culture parameters including aggregation method, kinetics, and aggregate size influence both the structural properties of aggregates and their paracrine immunomodulatory function. These findings underscore the utility of engineering strategies to control properties of 3D MSC aggregates, which may identify new avenues for optimizing the immunomodulatory function of MSC-based cell therapies.
Mesenchymal stromal cells (MSCs) have shown promise in regenerative medicine applications due in part to their ability to modulate immune cells. However, MSCs demonstrate significant functional heterogeneity in terms of their immunomodulatory function because of differences in MSC donor/tissue source, as well as non-standardized manufacturing approaches. As MSC metabolism plays a critical role in their ability to expand to therapeutic numbers ex vivo, we comprehensively profiled intracellular and extracellular metabolites throughout the expansion process to identify predictors of immunomodulatory function (T-cell modulation and indoleamine-2,3-dehydrogenase (IDO) activity). Here, we profiled media metabolites in a non-destructive manner through daily sampling and nuclear magnetic resonance (NMR), as well as MSC intracellular metabolites at the end of expansion using mass spectrometry (MS). Using a robust consensus machine learning approach, we were able to identify panels of metabolites predictive of MSC immunomodulatory function for 10 independent MSC lines. This approach consisted of identifying metabolites in 2 or more machine learning models and then building consensus models based on these consensus metabolite panels. Consensus intracellular metabolites with high predictive value included multiple lipid classes (such as phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins) while consensus media metabolites included proline, phenylalanine, and pyruvate. Pathway enrichment identified metabolic pathways significantly associated with MSC function such as sphingolipid signaling and metabolism, arginine and proline metabolism, and autophagy. Overall, this work establishes a generalizable framework for identifying consensus predictive metabolites that predict MSC function, as well as guiding future MSC manufacturing efforts through identification of high-potency MSC lines and metabolic engineering.more » « less
- NSF-PAR ID:
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Stem Cells
- Medium: X
- Sponsoring Org:
- National Science Foundation
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