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@ARTICLE{Bouman:286281,
      author       = {B. J. Bouman and Y. Demerdash$^*$ and S. Sood$^*$ and F.
                      Grünschläger$^*$ and F. Pilz$^*$ and A. R. Itani$^*$ and
                      A. Kuck$^*$ and V. Marot-Lassauzaie and S. Haas$^*$ and L.
                      Haghverdi and M. Essers$^*$},
      title        = {{S}ingle-cell time series analysis reveals the dynamics of
                      {HSPC} response to inflammation.},
      journal      = {Life science alliance},
      volume       = {7},
      number       = {3},
      issn         = {2575-1077},
      address      = {Heidelberg},
      publisher    = {EMBO Press},
      reportid     = {DKFZ-2023-02768},
      pages        = {e202302309},
      year         = {2023},
      note         = {DKFZ–ZMBH Alliance / #EA:A011#LA:A011#},
      abstract     = {Hematopoietic stem and progenitor cells (HSPCs) are known
                      to respond to acute inflammation; however, little is
                      understood about the dynamics and heterogeneity of these
                      stress responses in HSPCs. Here, we performed single-cell
                      sequencing during the sensing, response, and recovery phases
                      of the inflammatory response of HSPCs to treatment (a total
                      of 10,046 cells from four time points spanning the first 72
                      h of response) with the pro-inflammatory cytokine IFNα to
                      investigate the HSPCs' dynamic changes during acute
                      inflammation. We developed the essential novel computational
                      approaches to process and analyze the resulting single-cell
                      time series dataset. This includes an unbiased cell type
                      annotation and abundance analysis post inflammation, tools
                      for identification of global and cell type-specific
                      responding genes, and a semi-supervised linear regression
                      approach for response pseudotime reconstruction. We
                      discovered a variety of different gene responses of the
                      HSPCs to the treatment. Interestingly, we were able to
                      associate a global reduced myeloid differentiation program
                      and a locally enhanced pyroptosis activity with reduced
                      myeloid progenitor and differentiated cells after IFNα
                      treatment. Altogether, the single-cell time series analyses
                      have allowed us to unbiasedly study the heterogeneous and
                      dynamic impact of IFNα on the HSPCs.},
      keywords     = {Humans / Time Factors / Hematopoietic Stem Cells / Cell
                      Differentiation: genetics / Hematopoiesis: genetics /
                      Inflammation: metabolism},
      cin          = {A011 / A010 / BE01},
      ddc          = {570},
      cid          = {I:(DE-He78)A011-20160331 / I:(DE-He78)A010-20160331 /
                      I:(DE-He78)BE01-20160331},
      pnm          = {311 - Zellbiologie und Tumorbiologie (POF4-311)},
      pid          = {G:(DE-HGF)POF4-311},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38110222},
      doi          = {10.26508/lsa.202302309},
      url          = {https://inrepo02.dkfz.de/record/286281},
}