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Achreja A, Meurs N, Nagrath D. Quantifying Metabolic Transfer Mediated by Extracellular Vesicles Using Exo-MFA: An Integrated Empirical and Computational Platform. Methods Mol Biol 2020; 2088:205-221. [PMID: 31893376 PMCID: PMC7387122 DOI: 10.1007/978-1-0716-0159-4_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Extracellular vesicles (EVs) are ubiquitous nanoscale particles released from many different types of cells. They have been shown to contain proteins, DNA, RNA, miRNA, and, most recently, metabolites. These particles can travel through the intercellular space and bloodstream to have regulatory effects on distant recipients. When an EV reaches a target cell, it is taken up and degraded to release its contents for utilization within the cell. In addition to regulatory effects, EVs have been shown to supplement the high metabolic demands of recipient cells in a nutrient-deprived tumor microenvironment. We developed an integrated empirical and computational platform to quantify metabolic contribution of source cell-derived EVs to recipient cells. The versatile Exo-MFA software tool utilizes 13C stable-isotope tracing data to quantify the metabolic contributions of EVs from a source cell type on a recipient cell type. This is accomplished by creating EV-depleted culture medium, producing isotope-labeled EVs from the source cells, isolating the labeled EVs from the culture supernatant, culturing the recipient cells in the presence of the labeled EVs, and measuring the resulting metabolite levels across several time points.
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Affiliation(s)
- Abhinav Achreja
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Noah Meurs
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Deepak Nagrath
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
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Achreja A, Zhao H, Yang L, Yun TH, Marini J, Nagrath D. Exo-MFA - A 13C metabolic flux analysis framework to dissect tumor microenvironment-secreted exosome contributions towards cancer cell metabolism. Metab Eng 2017; 43:156-172. [PMID: 28087332 DOI: 10.1016/j.ymben.2017.01.001] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 12/05/2016] [Accepted: 01/05/2017] [Indexed: 02/04/2023]
Abstract
Dissecting the pleiotropic roles of tumor micro-environment (TME) on cancer progression has been brought to the foreground of research on cancer pathology. Extracellular vesicles such as exosomes, transport proteins, lipids, and nucleic acids, to mediate intercellular communication between TME components and have emerged as candidates for anti-cancer therapy. We previously reported that cancer-associated fibroblast (CAF) derived exosomes (CDEs) contain metabolites in their cargo that are utilized by cancer cells for central carbon metabolism and promote cancer growth. However, the metabolic fluxes involved in donor cells towards packaging of metabolites in extracellular vesicles and exosome-mediated metabolite flux upregulation in recipient cells are still not known. Here, we have developed a novel empirical and computational technique, exosome-mediated metabolic flux analysis (Exo-MFA) to quantify flow of cargo from source cells to recipient cells via vesicular transport. Our algorithm, which is based on 13C metabolic flux analysis, successfully predicts packaging fluxes to metabolite cargo in CAFs, dynamic changes in rate of exosome internalization by cancer cells, and flux of cargo release over time. We find that cancer cells internalize exosomes rapidly leading to depletion of extracellular exosomes within 24h. However, metabolite cargo significantly alters intracellular metabolism over the course of 24h by regulating glycolysis pathway fluxes via lactate supply. Furthermore, it can supply up to 35% of the TCA cycle fluxes by providing TCA intermediates and glutamine. Our algorithm will help gain insight into (i) metabolic interactions in multicellular systems (ii) biogenesis of extracellular vesicles and their differential packaging of cargo under changing environments, and (iii) regulation of cancer cell metabolism by its microenvironment.
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Affiliation(s)
- Abhinav Achreja
- Laboratory for Systems Biology of Human Diseases, Rice University, Houston, TX 77005, USA; Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hongyun Zhao
- Laboratory for Systems Biology of Human Diseases, Rice University, Houston, TX 77005, USA; Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lifeng Yang
- Laboratory for Systems Biology of Human Diseases, Rice University, Houston, TX 77005, USA; Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA
| | - Tae Hyun Yun
- Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA
| | | | - Deepak Nagrath
- Laboratory for Systems Biology of Human Diseases, Rice University, Houston, TX 77005, USA; Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA; Department of Bioengineering, Rice University, Houston, TX 77005, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA.
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