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Strategies for Measuring Induction of Fatty Acid Oxidation in Intestinal Stem and Progenitor Cells

Protocol
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Part of the Methods in Molecular Biology book series (MIMB, volume 2171)

Abstract

This protocol describes a multipronged approach that we have created to determine the transcriptional induction of fatty acid oxidation (FAO) genes in Lgr5high intestinal stem cells and a subsequent metabolomics-based approach for assessing fatty acid utilization in the mammalian intestinal crypt. More specifically, we describe methods for crypt isolation followed by a FACS-based purification of stem and progenitor populations and RNA-sequencing analysis. Using this workflow, we can determine both basal gene expression profiles of key metabolic genes as well as corresponding changes in response to altered metabolic states, such as fasting. Subsequently, we describe a complementary metabolomics-based approach that we have developed to assess fatty acid uptake and utilization in the crypt using 13C stable isotope tracing. Combining these approaches, one can gain a better understanding of substrate utilization and the preceding transcriptional changes that accommodate these reactions in physiologic states of low carbohydrate utilization or during overabundance of dietary lipids.

Key words

Fatty acid oxidation RNA-sequencing Stem cell metabolism Metabolomics Stable isotope tracing 

Notes

Acknowledgments

We would like to thank Dr. David M. Sabatini for guidance and discussions. We would also like to thank Dr. Elizaveta Freinkman, Dr. Michael Pacold and Dr. Caroline A. Lewis for isotope tracing and metabolomics protocol assistance and discussions, as well as the Whitehead Institute Metabolite Profiling Core Facility. We thank Dr. Sue Jean Hong of the Bartel lab at the Whitehead Institute for suggestions on the RNA purification protocol, Glenn Paradis of the Koch Institute Flow Cytometry Core for suggestions on building multicolor panels, as well as the Whitehead Institute Flow Cytometry Core and the Koch Institute Flow Cytometry Core. We thank Dr. Stuart Levine of the MIT BioMicro Center for population RNA-sequencing. We would like to also thank the members of the Mihaylova lab for critical reading and comments. C.W.C. is supported by a Helen Hay Whitney postdoctoral fellowship and a NIH/NIDDK K99 fellowship. O¨.H.Y. is supported by NIH R00 AG045144, R01CA211184, R01CA034992, and U54CA224068; a V Foundation V scholar award; a Sidney Kimmel scholar award; a Pew-Stewart Trust scholar award; the Kathy and Curt Marble Cancer Research Fund; a Bridge grant; the American Federation of Aging Research (AFAR); and the MIT Stem Cell Initiative. M.M.M. is supported by NIH R00 AG054760 and the Glenn Foundation for Medical Research and AFAR Grants for Junior Faculty.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.The David H. Koch Institute for Integrative Cancer Research at MITCambridgeUSA
  2. 2.Department of BiologyMITCambridgeUSA
  3. 3.Broad Institute of Harvard and MITCambridgeUSA
  4. 4.Department of PathologyMassachusetts General Hospital and Harvard Medical SchoolBostonUSA
  5. 5.Department of Biological Chemistry and PharmacologyThe Ohio State UniversityColumbusUSA
  6. 6.The Ohio State University Comprehensive Cancer CenterColumbusUSA

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