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  • Togninalli, MatteoStanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA. (author)

Machine learning-based classification of dual fluorescence signals reveals muscle stem cell fate transitions in response to regenerative niche factors

  • Article/chapterEnglish2023

Publisher, publication year, extent ...

  • 2023-01-14
  • Springer Nature,2023
  • printrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:kth-324751
  • https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324751URI
  • https://doi.org/10.1038/s41536-023-00277-4DOI

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  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • QC 20230316
  • The proper regulation of muscle stem cell (MuSC) fate by cues from the niche is essential for regeneration of skeletal muscle. How pro-regenerative niche factors control the dynamics of MuSC fate decisions remains unknown due to limitations of population-level endpoint assays. To address this knowledge gap, we developed a dual fluorescence imaging time lapse (Dual-FLIT) microscopy approach that leverages machine learning classification strategies to track single cell fate decisions with high temporal resolution. Using two fluorescent reporters that read out maintenance of stemness and myogenic commitment, we constructed detailed lineage trees for individual MuSCs and their progeny, classifying each division event as symmetric self-renewing, asymmetric, or symmetric committed. Our analysis reveals that treatment with the lipid metabolite, prostaglandin E2 (PGE2), accelerates the rate of MuSC proliferation over time, while biasing division events toward symmetric self-renewal. In contrast, the IL6 family member, Oncostatin M (OSM), decreases the proliferation rate after the first generation, while blocking myogenic commitment. These insights into the dynamics of MuSC regulation by niche cues were uniquely enabled by our Dual-FLIT approach. We anticipate that similar binary live cell readouts derived from Dual-FLIT will markedly expand our understanding of how niche factors control tissue regeneration in real time.

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  • Ho, Andrew T. V.Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.;Univ Paris Cite, Dept Funct, Adapt Biol, UMR CNRS 8251, F-75013 Paris, France. (author)
  • Madl, Christopher M. M.Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.;Univ Penn, Dept Mat Sci & Engn, Philadelphia, PA 19104 USA. (author)
  • Holbrook, Colin A. A.Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA. (author)
  • Wang, Yu XinStanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.;Sanford Burnham Prebys Med Discovery Inst, Ctr Genet Disorders & Aging, La Jolla, CA 92037 USA. (author)
  • Magnusson, Klas E. G.,1985-KTH,ACCESS Linnaeus Centre,Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.(Swepub:kth)u12ybtjw (author)
  • Kirillova, AnnaStanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA. (author)
  • Chang, AndrewStanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA. (author)
  • Blau, Helen M. M.Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA. (author)
  • Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.Stanford Sch Med, Inst Stem Cell Biol & Regenerat Med, Dept Microbiol & Immunol, Baxter Lab Stem Cell Biol, Stanford, CA 94305 USA.;Univ Paris Cite, Dept Funct, Adapt Biol, UMR CNRS 8251, F-75013 Paris, France. (creator_code:org_t)

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  • In:NPJ REGENERATIVE MEDICINE: Springer Nature8:12057-3995

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