Biology subjects

Chan, M. M.

Publications and source records attributed to Chan, M. M..

8 recordsLinked to original sources

bioRxiv2026

A single-nucleus multiomic and spatial atlas of gene regulation in human spermatogenesis

Gametogenesis, the production of oocytes and sperm, ensures the faithful transmission of genetic material to the next generation. In males, spermatogenesis occurs within the testis, where germ cells progress through a highly ordered developmental programme in close association with supporting somatic cells. Defects in this process cause infertility, yet the gene regulatory mechanisms coordinating normal and dysfunctional human spermatogenesis remain incompletely defined. Here we generate a single-nucleus multiomic and spatial atlas of human spermatogenesis by profiling chromatin accessibility and gene expression in the same nuclei and integrating these data with spatial transcriptomics of intact testicular tissue. We infer high-confidence gene regulatory networks that resolve stage-specific activity of known and novel candidate regulators across germline and somatic compartments, and map spatially restricted signalling interactions within the seminiferous tubule niche. Integration with infertility-associated genetic variation links non-coding risk loci to candidate enhancers and target genes in cell-type-specific regulatory contexts. Finally, profiling clinical cryptozoospermia samples as in vivo perturbations supports the ability of this network to capture downstream transcriptional consequences of disease-associated regulatory disruption. Together, these data provide a spatially resolved regulatory framework for human spermatogenesis and a foundation for interpreting the molecular basis of male infertility.

genomics↗

bioRxiv2025

Mapping embryonic mouse lung development using enhanced spatial transcriptomics

The mature mammalian lung contains [~]50 different cell types that are located in precise positions along and around the airway epithelial tree. Here, we investigated how these spatial patterns are progressively established during development. Specifically, we optimized a microfluidics-enabled, deterministic barcoding-based sequencing (DBiT-seq) workflow to achieve highly sensitive spatial mapping of tissue sections from early embryonic mouse lungs. Spatial mapping of epithelial populations revealed that Sox9+ epithelial progenitors are located throughout the epithelial tree at early stages before becoming confined to the distal ends. Spatial mapping of mesenchymal populations revealed a previously unrecognized mesenchymal cluster that expresses high levels of extracellular matrix proteins and appears to promote embryonic lung innervation. These findings provide new insights into the spatial organization and cellular dynamics underlying early lung development, and demonstrate the power of spatial transcriptomics to uncover hidden patterns and populations of cells.

developmental biology↗

bioRxiv2025

Induction of TFEB promotes Kupffer cell survival and reduces lipid accumulation and inflammation in MASLD

Kupffer cells (KCs) are the tissue-resident macrophage of the liver where they serve a critical role in maintaining liver tissue homeostasis and as a filter for circulation. The composition of liver macrophages changes during metabolic dysfunction-associated liver disease (MASLD), with the loss of resident KCs being a hallmark of disease progression. The mechanism(s) and consequences of KC death in metabolic liver disease have yet to be defined. Transcription factor EB (TFEB) is a master regulator of lysosome function and lipid metabolism which has been shown to protect macrophages from lipid stress in atherosclerosis. We hypothesized that TFEB would improve KC fitness in MASLD. To investigate this possibility, we created a transgenic mice in which TFEB was induced specifically in KCs. We found that TFEB induction protected KCs from cell death in two mouse models of MASLD. KC preservation through TFEB induction reduced liver steatosis via a mechanism that was dependent on macrophage lysosomal lipolysis and mitochondrial fatty acid oxidation. The protection from cell death in TFEB KCs was the result of reduced oxidative stress and ferroptosis through a mechanism that involved enhanced NADPH levels. Together, we provide evidence that TFEB promotes KC fitness during MASLD and orchestrates beneficial effects on liver pathology, thus providing potential targets to develop cell-specific therapeutics.

immunology↗

bioRxiv2025

Tracing LYVE1+ peritoneal fluid macrophages unveils two paths to resident macrophage repopulation with differing reliance on monocytes

Mouse resident peritoneal macrophages, called large cavity macrophages (LCM), arise from embryonic progenitors that proliferate as mature, CD73+Gata6+ tissue-specialized macrophages. After injury from irradiation or inflammation, monocytes are thought to replenish CD73+Gata6+ LCMs through a CD73-LYVE1+ LCM intermediate. Here, we show that CD73-LYVE1+ LCMs indeed yield Gata6+CD73+ LCMs through integrin-mediated interactions with mesothelial surfaces. CD73-LYVE1+ LCM repopulation of the peritoneum was reliant upon and quantitatively proportional to recruited monocytes. Unexpectedly, fate mapping indicated that only [~]10% of Gata6-dependent LCMs that repopulated the peritoneum after injury depended on the LYVE1+ LCM stage. Further supporting nonoverlapping lifecycles of CD73-LYVE1+ and CD73+Gata6+ LCMs, in mice bearing a paucity of monocytes, Gata6+CD73+ LCMs rebounded after ablative irradiation substantially more efficiently than their presumed LYVE1+ or CD73- LCM upstream precursors. Thus, after inflammatory insult, two temporally parallel pathways, each generating distinct differentiation intermediates with varying dependencies on monocytes, contribute to the replenish hment of Gata6+ resident peritoneal macrophages.

immunology↗

bioRxiv2023

Recording morphogen signals reveals origins of gastruloid symmetry breaking

When cultured in three dimensional spheroids, mammalian stem cells can reproducibly self-organize a single anterior-posterior axis and sequentially differentiate into structures resembling the primitive streak and tailbud. Whereas the embryos body axes are instructed by spatially patterned extra-embryonic cues, it is unknown how these stem cell gastruloids break symmetry to reproducibly define a single anterior-posterior (A-P) axis. Here, we use synthetic gene circuits to trace how early intracellular signals predict cells future anterior-posterior position in the gastruloid. We show that Wnt signaling evolves from a homogeneous state to a polarized state, and identify a critical 6-hour time period when single-cell Wnt activity predicts future cellular position, prior to the appearance of polarized signaling patterns or morphology. Single-cell RNA sequencing and live-imaging reveal that early Wnt-high and Wnt-low cells contribute to distinct cell types and suggest that axial symmetry breaking is driven by sorting rearrangements involving differential cell adhesion. We further extend our approach to other canonical embryonic signaling pathways, revealing that even earlier heterogeneity in TGF{beta} signaling predicts A-P position and modulates Wnt signaling during the critical time period. Our study reveals a sequence of dynamic cellular processes that transform a uniform cell aggregate into a polarized structure and demonstrates that a morphological axis can emerge out of signaling heterogeneity and cell movements even in the absence of exogenous patterning cues. HighlightsO_LISymmetry-breaking gastruloid protocol where Wnt signaling evolves from a uniform high state to a single posterior domain. C_LIO_LISynthetic gene circuits record Wnt, Nodal and BMP signaling with high time resolution. C_LIO_LIHeterogeneity in Wnt signaling at 96 h predicts cells future positions and types. C_LIO_LIWnt activity differences are influenced by earlier heterogeneity in Nodal/BMP activity. C_LI

developmental biology↗

bioRxiv2022

Startle: a star homoplasy approach for CRISPR-Cas9 lineage tracing

CRISPR-Cas9 based genome editing combined with single-cell sequencing enables the tracing of the history of cell divisions, or cellular lineage, in tissues and whole organisms. While standard phylogenetic approaches may be applied to reconstruct cellular lineage trees from this data, the unique features of the CRISPR-Cas9 editing process motivate the development of specialized models that describe the evolution of CRISPR-Cas9 induced mutations. Here, we introduce the star homoplasy model, a novel evolutionary model that constrains a phylogenetic character to mutate at most once along a lineage, capturing the non-modifiability property of CRISPR-Cas9 mutations. We derive a combinatorial characterization of star homoplasy phylogenies by identifying a relationship between the star homoplasy model and the binary perfect phylogeny model. We use this characterization to develop an algorithm, Startle (Star tree lineage estimator), that computes a maximum parsimony star homoplasy phylogeny. We demonstrate that Startle infers more accurate phylogenies on simulated CRISPR-based lineage tracing data compared to existing methods; particularly on data with high amounts of dropout and homoplasy. Startle also infers more parsimonious phylogenies with fewer metastatic migrations on a lineage tracing dataset from mouse metastatic lung adenocarcinoma. Code availabilitySoftware is available at https://github.com/raphael-group/startle

bioinformatics↗

bioRxiv2021

Lineage Recording Reveals the Phylodynamics, Plasticity and Paths of Tumor Evolution

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth, expansion to neighboring and distal tissues, and therapeutic resistance. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma which enabled us to track tumor evolution from single transformed cells to metastatic tumors at unprecedented resolution. We found that loss of the initial, stable alveolar-type2-like state was accompanied by transient increase in plasticity. This was followed by adoption of distinct fitness-associated transcriptional programs which enable rapid expansion and ultimately clonal sweep of rare, stable subclones capable of metastasizing to distant sites. Finally, we showed that tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates tumor progression by creating novel evolutionary paths. Overall, our study elucidates the hierarchical nature of tumor evolution, and more broadly enables the in-depth study of tumor progression.

cancer biology↗

bioRxiv2019

Inference of Single-Cell Phylogenies from Lineage Tracing Data

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. To address this, we provide three resources. First, we introduce Cassiopeia - a suite of scalable and theoretically grounded maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date - consisting of 34,557 human cells continuously traced over 15 generations, 71% of which are uniquely marked - and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia.

bioinformatics↗