Biology subjects

Fung, J. H.

Publications and source records attributed to Fung, J. H..

3 recordsLinked to original sources

bioRxiv2025

Quantitative molecular cartography of emergency myelopoiesis reveals conserved modules of hematopoietic activation

Hematopoietic stem and progenitor cells (HSPC) respond to infections, inflammation, and regenerative challenges using a collection of cellular and molecular mechanisms termed emergency myelopoiesis (EM) pathways. However, it remains unclear how various EM inducers regulate HSPCs using shared or distinct molecular mechanisms. Here, we generate a comprehensive and generalizable cell annotation method (HemaScribe) and a refined quantitative model of hematopoietic differentiation (HemaScape) using single cell RNA sequencing (scRNA-seq) of HSPCs, which we apply to a broad range of EM modalities. We uncover multiple strategies to enhance myelopoiesis acting at different levels of the HSPC hierarchy, which are associated with both unique and shared transcriptional response modules. In particular, we identify a myeloid progenitor-based module of EM engagement across diverse inflammatory challenges, which informs outcome in adult and pediatric human acute myeloid leukemia. Collectively, our work illuminates fundamental regulatory mechanisms in hematopoietic regeneration that have direct translational applications in disease contexts. HIGHLIGHTSO_LINew HemaScribe method for hematopoietic progenitor annotation in scRNA-seq datasets C_LIO_LIDifferent emergency myelopoiesis (EM) inducers act at distinct hematopoiesis levels C_LIO_LIUnique and shared transcriptional response modules enacted by different EM inducers C_LIO_LIA myeloid progenitor EM module informs outcome in acute myeloid leukemia C_LI eTOC BLURBSwann et al. conduct comparative analysis of single cell RNA sequencing data from multiple emergency myelopoiesis models, finding that different perturbations act at various levels of the hematopoietic hierarchy and recruit distinct sets of molecular mechanisms to enhance myelopoiesis. In particular, they identify a conserved myeloid progenitor-based activation module across multiple disease conditions, which informs outcome in human acute myeloid leukemia. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/656712v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@ffcd62org.highwire.dtl.DTLVardef@50eaeorg.highwire.dtl.DTLVardef@6df44org.highwire.dtl.DTLVardef@12bfacf_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Enhancer Dynamics and Spatial Organization Drive Anatomically Restricted Cellular States in the Human Spinal Cord

Here, we report the spatial organization of RNA transcription and associated enhancer dynamics in the human spinal cord at single-cell and single-molecule resolution. We expand traditional multiomic measurements to reveal epigenetically poised and bivalent active transcriptional enhancer states that define cell type specification. Simultaneous detection of chromatin accessibility and histone modifications in spinal cord nuclei reveals previously unobserved cell-type specific cryptic enhancer activity, in which transcriptional activation is uncoupled from chromatin accessibility. Such cryptic enhancers define both stable cell type identity and transitions between cells undergoing differentiation. We also define glial cell gene regulatory networks that reorganize along the rostrocaudal axis, revealing anatomical differences in gene regulation. Finally, we identify the spatial organization of cells into distinct cellular organizations and address the functional significance of this observation in the context of paracrine signaling. We conclude that cellular diversity is best captured through the lens of enhancer state and intercellular interactions that drive transitions in cellular state. This study provides fundamental insights into the cellular organization of the healthy human spinal cord.

neuroscience↗

bioRxiv2024

Statistical estimation of sparsity and efficiency for molecular codes

AO_SCPLOWBSTRACTC_SCPLOWA fundamental biological question is to understand how cell types and functions are determined by genomic and proteomic coding. A basic form of this question is to ask if small families of genes or proteins code for cell types. For example, it has been shown that the collection of homeodomain proteins can uniquely delineate all 118 neuron classes in the nematode C. elegans. However, unique characterization is neither robust nor rare. Our goal in this paper is to develop a rigorous methodology to characterize molecular codes. We show that in fact for information-theoretic reasons almost any sufficiently large collection of genes is able to disambiguate cell types, and that this property is not robust to noise. To quantify the discriminative properties of a molecular codebook in a more refined way, we develop new statistics - partition cardinality and partition entropy - borrowing ideas from coding theory. We prove these are robust to data perturbations, and then apply these in the C. elegans example and in cancer. In the worm, we show that the homeodomain transcription factor family is distinguished by coding for cell types sparsely and efficiently compared to a control of randomly selected family of genes. Furthermore, the resolution of cell type identities defined using molecular features increases as the worm embryo develops. In cancer, we perform a pan-cancer study where we use our statistics to quantify interpatient tumor heterogeneity and we identify the chromosome containing the HLA family as sparsely and efficiently coding for melanoma.

bioinformatics↗