Dataset Information

EGR1 dysregulation defines an inflammatory and leukemic program in cell trajectory of human-aged hematopoietic stem cells (HSC).

ABSTRACT:

Background

During aging, hematopoietic stem cells (HSC) lose progressively both their self-renewal and differentiation potential. The precise molecular mechanisms of this phenomenon are not well established. To uncover the molecular events underlying this event, we have performed a bioinformatics analysis of 650 single-cell transcriptomes.

Methods

Single-cell transcriptome analyses of expression heterogeneity, cell cycle, and cell trajectory in human cell compartment enriched in hematopoietic stem cell compartment were investigated in the bone marrow according to the age of the donors. Identification of aging-related nodules was identified by weighted correlation network analysis in this primitive compartment.

Results

The analysis of single-cell transcriptomes allowed to uncover a major upregulation of EGR1 in human-aged lineage-CD34+CD38- cells which present cell cycle dysregulation with reduction of G2/M phase according to less expression of CCND2 during S phase. EGR1 upregulation in aging hematopoietic stem cells was found to be independent of cell cycle phases and gender. EGR1 expression trajectory in aged HSC highlighted a signature enriched in hematopoietic and immune disorders with the best induction of AP-1 complex and quiescence regulators such as EGR1, BTG2, JUNB, and NR41A. Sonic Hedgehog-related TMEM107 transmembrane molecule followed also EGR1 cell trajectory. EGR1-dependent gene weighted network analysis in human HSC-associated IER2 target protein-specific regulators of PP2A activity, IL1B, TNFSF10 ligands, and CD69, SELP membrane molecules in old HSC module with immune and leukemogenic signature. In contrast, for young HSC which were found with different cell cycle phase progression, its specific module highlighted upregulation of HIF1A hypoxic factor, PDE4B immune marker, DRAK2 (STK17B) T cell apoptosis regulator, and MYADM myeloid-associated marker.

Conclusion

EGR1 was found to be connected to the aging of human HSC and highlighted a specific cell trajectory contributing to the dysregulation of an inflammatory and leukemia-related transcriptional program in aged human HSCs. EGR1 and its program were found to be connected to the aging of human HSC with dissociation of quiescence property and cell cycle phase progression in this primitive hematopoietic compartment.

SUBMITTER: Desterke C

PROVIDER: S-EPMC8296523 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:During adult bone marrow hematopoiesis, extremely rare and dormant hematopoietic stem cells (HSCs) harbor the highest self-renewal activity within all blood cells. They give rise to active HSCs, which generate multipotent progenitors (MPPs) which differentiate into lineage-committed progenitors and subsequently mature cells. While HSCs are characterized by long-term self-renewal capacity, quiescence and multipotency, MPPs show steadily decreasing self-renewal activity, are cycling but are thought to maintain multipotency. To establish a comprehensive genome-wide landscape of expressed transcripts, we performed a quantitative transcriptome analysis by next-generation sequencing (RNA-seq) of seven ex vivo FACS-sorted mouse HSC/progenitor populations. Eleven-fold coverage of the genome was achieved, revealing quantification of > 27,000 mRNA species of which 589 long non-coding RNAs (lncRNAs) were quantified. A profile of 79 differentially expressed lncRNAs in HSC-MPPs was identified suggesting a role for these RNA species in HSC/progenitor biology. Expression clusters of transcription factors and cell adhesion molecules are identified between the different cell populations. Dormant HSCs, as identified by label-retaining assays, showed a highly differential expression profile compared to active HSCs. In addition to >200 differentially expressed cell surface receptors and lncRNAs, processes including metabolism, development, immune response, signaling (TGFb, Kit, senescence/autophagy) are distinct between the two types of HSCs. In addition, using whole cell proteome analysis of FACS-sorted HSCs and MPP1, >6,000 proteins were identified by quantitative tandem mass spectrometry. Quantification of these proteins confirmed the close relationship between these cell types also seen in their transcript profile and revealed processes such as energy metabolism, immune response and cell cycle to be modulated along early lineage progression. While MPP1/2 still show multilineage potential in reconstitution experiments, a strong lineage bias and low self-renewal potential is observed in mice reconstituted with MPP3/4. These functional differences are accompanied by complex changes in their transcriptome and is also revealed by principal component analysis. In summary, the global mRNA, lncRNA and proteome signatures uncovered here and which are complemented by functional assays, provide a comprehensive and searchable resource of the molecular make-up of the entire HSC/progenitor population present in the bone marrow. These data will provide the basis for a global understanding of stem cell biology in the adult blood system. The uploaded dataset corresponds to the quantitative proteomic comparison of HSC and MPP1, which was done in three biological replicates. Data analysis: MS raw data files were processed with MaxQuant (version 1.3.0.5) (Cox and Mann 2008). Enzyme specificity was set to trypsin/P and a maximum of two missed cleavages were allowed. Cysteine carbamidomethylation and methionine oxidation were selected as fixed and variable modifications, respectively. The derived peak list was searched using the built-in Andromeda search engine (version 1.3.0.5) in MaxQuant against the Uniprot mouse database (2013.02.20) containing 75,721 proteins to which 247 frequently observed contaminants as well as reversed sequences of all entries had been added. Initial maximal allowed mass tolerance was set to 20 ppm for peptide masses, followed by 6 ppm in the main search, and 0.5 Dalton for fragment ion masses. The minimum peptide length was set to six amino acid residues and three labeled amino acid residues were allowed. A 1% false discovery rate (FDR) was required at both the protein level and the peptide level. In addition to the FDR threshold, proteins were considered identified if they had at least one unique peptide. The protein identification was reported as an indistinguishable “protein group” if no unique peptide sequence to a single database entry was identified. The ‘match between runs’ was enabled for consecutive peptide fractions with a 2 minutes time window. The iBAQ algorithm was used for estimation of the abundance of different proteins within a single sample (proteome) (Schwanhausser 2011). For evaluation of differential protein expression between HSC and MPP1, statistical analysis was performed for the proteins quantified in all three replicates using the Limma package in R/Bioconductor (Gentleman 2004, Smyth 2004). After fitting a linear model to the data, an empirical Bayes moderated t-test was used for the protein ratios, which were weighted on log10(summed peptide intensities) in order to capture the effect that the statistical spread of unregulated proteins is much more focused for highly abundant proteins than for low abundance ones (Cox 2008). P-values were then adjusted for multiple testing with Benjamini and Hochberg's method and proteins with an adjusted p-value lower than 0.1 were considered to be differentially expressed between HSC and MPP1. Associated transcriptomics data has been deposited at ArrayExpress with accession E-MTAB-2262.