Biology subjects

Chabra, S.

Publications and source records attributed to Chabra, S..

4 recordsLinked to original sources

bioRxiv2025

A subset of Haematopoietic Stem Cells resists Plasmodium infection-induced stress by uncoupling interferon sensing and metabolic activation

Hematopoietic stem cells (HSCs) sustain lifelong haematopoiesis as their progeny differentiate into all blood cell lineages. Homeostatic HSCs are mostly quiescent and only rarely divide, however their proliferation and differentiation rates can be modulated by external factors. Acute and chronic infections from a wide range of pathogens are known to challenge HSCs at the population level, being forced to respond to inflammation-mediated organismal demand to replenish the myeloid cell pool. However, less is known about the degree of heterogeneity in the HSCs response to inflammation at the single cell level. Here, using a natural murine malaria model and an NHS-ester biotin dilution assay we identify two subsets of HSCs, BiotinLo and BiotinHi, with distinct proliferation kinetics. Using combined functional, single-cell transcriptomics and phenotypic analyses, we uncover that BiotinHi HSCs remain highly functional despite expressing strong interferon response signatures. These infection-resistant HSCs express high levels of MHC II and are metabolically distinct from the remaining HSCs as they maintain less active mitochondria. These findings demonstrate that a likely reserve pool of HSCs remains highly functional during Plasmodium infection not because cells are shielded, but because they maintain a stemness associated metabolic profile despite effectively sensing inflammation.

cell biology↗

bioRxiv2024

diffGEK: Differential Gene Expression Kinetics

A defining characteristic of all metazoan organisms is the existence of different cell states or cell types, driven by changes in gene expression kinetics, principally transcription, splicing and degradation rates. The RNA velocity framework utilizes both spliced and unspliced reads in single cell mRNA preparations to predict future cellular states and estimate transcriptional kinetics. However, current models assume either constant kinetic rates, rates equal for all genes, or rates completely independent of progression through differentiation. Consequently, current models for rate estimation are either underparametrised or overparametrised. Here we developed a new method (diffGEK) which overcomes this issue, and allows comparison of transcriptional rates across different biological conditions. diffGEK assumes that rates can vary over a trajectory, but are smooth functions of the differentiation process. Analysing Jak2 V617F mutant versus wild type mice for erythropoiesis, and Ezh2 KO versus wild type mice in myelopoiesis, revealed which genes show altered transcription, splicing or degradation rates between different conditions. Moreover, we observed that, for some genes, compensatory changes between different rates can result in comparable overall mRNA levels, thereby masking highly dynamic changes in gene expression kinetics in conventional expression analysis. Collectively, we report a robust pipeline for comparative expression analysis based on altered transcriptional kinetics to discover mechanistic differences missed by conventional approaches, with broad applicability across any biomedical research question where single cell expression data are available for both wild type and treatment/mutant conditions.

bioinformatics↗

bioRxiv2024

Unveiling Clonal Cell Fate and Differentiation Dynamics: A Hybrid NeuralODE-Gillespie Approach

Recent lineage tracing single-cell techniques (LT-scSeq), e.g., the Lineage And RNA RecoverY (LARRY) barcoding system, have enabled clonally resolved interpretation of differentiation trajectories. However, the heterogeneity of clone-specific kinetics remains understudied, both quantitatively and in terms of interpretability, thus limiting the power of bar-coding systems to unravel how heterogeneous stem cell clones drive overall cell population dynamics. Here, we present CLADES, a NeuralODE-based framework to faithfully estimate clone-specific kinetics of cell states from newly generated and publicly available human cord blood LARRY LT-scSeq data. By incorporating a stochastic simulation algorithm (SSA) and differential expression gene (DEGs) analysis, CLADES yields cell division dynamics across differentiation timecourses and fate bias predictions for the early progenitor cells. Moreover, clone-level quantitative behaviours can be grouped into characteristic types by pooling individual clones into meta-clones. By benchmarking with CoSpar, we found that CLADES improves fate bias prediction accuracy at the meta-clone level. In conclusion, we report a broadly applicable approach to robustly quantify differentiation kinetics using meta-clones while providing valuable insights into the fate bias of cellular populations for any organ system maintained by a pool of heterogeneous stem and progenitor cells.

bioinformatics↗

bioRxiv2017

Morphogen dynamics control patterning in a stem cell model of the human embryo

During embryonic development, diffusible signaling molecules called morphogens are thought to determine cell fates in a concentration-dependent manner1-4, and protocols for directed stem cell differentiation are based on this picture5-8. However, in the mammalian embryo, morphogen concentrations change rapidly compared to the time for making cell fate decisions9-12. It is unknown how changing ligand levels are interpreted, and whether the precise timecourse of ligand exposure plays a role in cell fate decisions. Nodal and BMP4 are morphogens crucial for gastrulation in vertebrates13. Each pathway has distinct receptor complexes that phosphorylate specific signal transducers, known as receptor-Smads, which then complex with the shared cofactor Smad4 to activate target genes14. Here we show in human embryonic stem cells (hESCs) that the response to BMP4 signaling indeed is determined by the ligand concentration, but that unexpectedly, the expression of many mesodermal targets of Activin/Nodal depends on rate of concentration increase. In addition, we use live imaging of hESCs with GFP integrated at the endogenous SMAD4 locus to show that a stem cell model for the human embryo15 generates a wave of Nodal signaling. Cells experience rapidly increasing Nodal specifically in the region of mesendoderm differentiation. We also demonstrate that pulsatile stimulation with Activin induces repeated strong signaling and enhances mesoderm differentiation. Our results break with the paradigm of concentration-dependent differentiation and demonstrate an important role for morphogen dynamics in the cell fate decisions associated with mammalian gastrulation. They suggest a highly dynamic picture of embryonic patterning where some cell fates depend on rapid concentration increase rather than absolute levels, and point to ligand dynamics as a new dimension to optimize protocols for directed stem cell differentiation.

developmental biology↗