Biology subjects

Lau, K. S.

Publications and source records attributed to Lau, K. S..

16 recordsLinked to original sources

bioRxiv2026

Multimodal Imaging of the Cellular and Extracellular Microenvironment on the Same Formalin-Fixed Paraffin-Embedded Tissue Section

Same-tissue section multimodal imaging is a powerful strategy that spatially profiles tissue histology, cell populations and molecular composition while maximizing tissue economy, preserving spatial molecular relationships, and increasing co-registration capacity. However, performing multiple modalities on the same tissue section can destroy or chemically alter the tissue, compromising downstream data. Here, we systematically assess integration of picrosirius red staining, hematoxylin and eosin staining, and multiplexed immunofluorescence into N-glycan and extracellular matrix peptide matrix-assisted laser/desorption ionization imaging mass spectrometry (IMS) workflows. We evaluate alterations in tissue morphology, stain efficiency, IMS feature intensity as well as IMS feature localization after upstream modality integration. We propose an optimized multimodal sequence that maximizes data quality and follows a very specific order of: autofluorescence microscopy, multiplexed immunofluorescence, picrosirius red staining, N-glycan IMS, hematoxylin and eosin staining, and extracellular matrix peptide IMS. Overall, this work develops an optimized multimodal workflow that comprehensively images tissue morphology, collagen fibers, and cell populations at single-cell resolution as well as multiplexed N-glycan composition and multiplexed extracellular matrix peptides with post-translational modification status from a single tissue section.

biochemistry↗

bioRxiv2025

Microbiota promote enhanced CD39 expression in γδ intraepithelial lymphocytes through the activation of TCR and IL-15 signaling

Intraepithelial lymphocytes expressing the {gamma}{delta} T cell receptor ({gamma}{delta} IEL) provide continuous surveillance of the intestinal epithelium. We report that mice harboring a microbiota-specific hyperproliferative {gamma}{delta} IEL ({gamma}{delta}HYP) phenotype also upregulate the expression of the ectonucleotidase CD39, a marker of regulatory {gamma}{delta} T cells. Enhanced TCR and IL-15 signaling correlates with a progression from a naive-like CD39neg {gamma}{delta} IEL to a more mature, tissue-adapted CD39hi IEL population. We found that TCR{gamma}{delta} activation drives CD122-mediated CD39 upregulation on {gamma}{delta}HYP IELs and increased mucosal IL-15 further amplifies CD39 expression in these cells. Further investigation revealed that CD39 induction requires sustained exposure to the {gamma}{delta}HYP-associated microbiota. Moreover, CD39hi {gamma}{delta} IELs exhibit a reduced capacity to produce pro-inflammatory cytokine, which may explain the lack of histopathology in {gamma}{delta}HYP mice. Overall, our study identifies a previously unappreciated mechanism by which an altered microbiota amplifies CD39 expression on {gamma}{delta}HYP IELs, leading to the expansion of {gamma}{delta} IELs with regulatory potential.

immunology↗

bioRxiv2025

Coordinated changes in thymic stromal and hematopoietic cells that define the perinatal to juvenile transition

T cells in the perinatal thymus have distinct phenotypes and functions that may be instructed by age-specific features of the microenvironment. We evaluated molecular and cellular profiles of thymic stromal cells, including thymic epithelial cells (TECs), mesenchyme, endothelium, and hematopoietic antigen presenting cells (hAPCs), from birth through one-month of age in mice. Single-cell transcriptional profiling, flow cytometry, and immunohistochemistry revealed coordinated stromal changes accompanied by altered thymocyte differentiation at defined transitional ages during the shift from perinatal growth to juvenile homeostasis, which was mirrored in humans. These analyses link diminished IGF2 expression by mesenchymal cells with activation of the RB pathway in TECs at the transition. Moreover, a coordinated increase in type I interferon signaling in stroma across the transition is associated with altered antigen processing and presentation signatures in TECs and hAPCs. Collectively, these datasets provide a resource to interrogate thymic stroma across the perinatal to juvenile transition.

immunology↗

bioRxiv2025

Pathobiont-triggered induction of epithelial IDO1 drives regional susceptibility to Inflammatory Bowel Disease

The structure and function of the mammalian gut vary by region, yet why inflammatory diseases manifest in specific regions and not others remains unclear. We use a TNF-overexpressing Crohns disease (CD) model (Tnf{Delta}ARE/+), which typically presents in the terminal ileum (TI), to investigate how environmental factors interact with the hosts immune susceptibility to drive region-specific disease. We identified Chlamydia muridarum, an intracellular bacterium and murine counterpart to the human sexually transmitted C. trachomatis, as necessary and sufficient to trigger disease manifestation in the ascending colon (AC), another common site of human CD. Disease manifestation in the AC depends on indoleamine 2,3-dioxygenase (IDO1) activity induced by hypersensitive surface secretory cells in genetically susceptible hosts. Single-cell and microbial analyses of human specimens also implicates this pathobiont-epithelial IDO1 pathway in patients with a history of CD in the AC. Our findings demonstrate that genetic and microbial factors can independently drive region-specific disease and provide a unique model to study CD specific to the AC.

cell biology↗

bioRxiv2024

Intestinal tuft cells assemble a cytoskeletal superstructure composed of co-aligned actin bundles and microtubules

Background & AimsAll tissues consist of a distinct set of cell types, which collectively support organ function and homeostasis. Tuft cells are a rare epithelial cell type found in diverse epithelia, where they play important roles in sensing antigens and stimulating downstream immune responses. Exhibiting a unique polarized morphology, tuft cells are defined by an array of giant actin filament bundles that support [~]2 m of apical membrane protrusion and extend over 7 m towards the cells perinuclear region. Despite their established roles in maintaining intestinal epithelial homeostasis, tuft cells remain understudied due to their rarity (e.g. [~] 1% in the small intestinal epithelium). Details regarding the ultrastructural organization of the tuft cell cytoskeleton, the molecular components involved in building the array of giant actin bundles, and how these cytoskeletal structures support tuft cell biology remain unclear. MethodsTo begin to answer these questions, we used advanced light and electron microscopy to perform quantitative morphometry of the small intestinal tuft cell cytoskeleton. ResultsWe found that tuft cell core bundles consist of actin filaments that are crosslinked in a parallel "barbed-end out" configuration. These polarized structures are also supported by a unique group of tuft cell enriched actin-binding proteins that are differentially localized along the giant core bundles. Furthermore, we found that tuft cell actin bundles are co-aligned with a highly ordered network of microtubules. ConclusionsTuft cells assemble a cytoskeletal superstructure that is well positioned to serve as a track for subcellular transport along the apical-basolateral axis and in turn, support the dynamic sensing functions that are critical for intestinal epithelial homeostasis. SYNOPSISThis research leveraged advanced light and electron microscopy to perform quantitative morphometry of the intestinal tuft cell cytoskeleton. Three-dimensional reconstructions of segmented image data revealed a co-aligned actin-microtubule superstructure that may play a fundamental role in tuft cell function.

cell biology↗

bioRxiv2023

A Specialized Epithelial Cell Type Regulating Mucosal Immunity and Driving Human Crohn's Disease

Crohns disease (CD) is a complex chronic inflammatory disorder that may affect any part of gastrointestinal tract with extra-intestinal manifestations and associated immune dysregulation. To characterize heterogeneity in CD, we profiled single-cell transcriptomics of 170 samples from 65 CD patients and 18 non-inflammatory bowel disease (IBD) controls in both the terminal ileum (TI) and ascending colon (AC). Analysis of 202,359 cells identified a novel epithelial cell type in both TI and AC, featuring high expression of LCN2, NOS2, and DUOX2, and thus is named LND. LND cells, confirmed by high-resolution in-situ RNA imaging, were rarely found in non-IBD controls, but expanded significantly in active CD. Compared to other epithelial cells, genes defining LND cells were enriched in antimicrobial response and immunoregulation. Moreover, multiplexed protein imaging demonstrated that LND cell abundance was associated with immune infiltration. Cross-talk between LND and immune cells was explored by ligand-receptor interactions and further evidenced by their spatial colocalization. LND cells showed significant enrichment of expression specificity of IBD/CD susceptibility genes, revealing its role in immunopathogenesis of CD. Investigating lineage relationships of epithelial cells detected two LND cell subpopulations with different origins and developmental potential, early and late LND. The ratio of the late to early LND cells was related to anti-TNF response. These findings emphasize the pathogenic role of the specialized LND cell type in both Crohns ileitis and Crohns colitis and identify novel biomarkers associated with disease activity and treatment response.

bioinformatics↗

bioRxiv2023

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging

MotivationMultiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data. ResultsTo address the need for an evaluable semi-automated algorithm, we developed GammaGateR, an R package for interactive marker gating designed specifically for segmented cell-level data from mIF images. Based on a novel closed-form gamma mixture model, GammaGateR provides estimates of marker-positive cell proportions and soft clustering of marker-positive cells. The model incorporates user-specified constraints that provide a consistent but slide-specific model fit. We compared GammaGateR against the newest unsupervised approach for annotating mIF data, employing two colon datasets and one ovarian cancer dataset for the evaluation. We showed that GammaGateR produces highly similar results to a silver standard established through manual annotation. Furthermore, we demonstrated its effectiveness in identifying biological signals, achieved by mapping known spatial interactions between CD68 and MUC5AC cells in the colon and by accurately predicting survival in ovarian cancer patients using the phenotype probabilities as input for machine learning methods. GammaGateR is a highly efficient tool that can improve the replicability of marker gating results, while reducing the time of manual segmentation. Availability and ImplementationThe R package is available at https://github.com/JiangmeiRubyXiong/GammaGateR. ContactPlease address correspondence to jiangmei.xiong@vanderbilt.edu and simon.vandekar@vumc.org. Key PointsO_LIGammaGateR is the first semi-automated marker gating tool for mIF image, and it will help to diminish the inconsistency with manual marker gating. C_LIO_LIWith novel cfGMM, GammaGateR can fit flexibly across slides with different distributions and incorporate biology priors. C_LIO_LIGammaGateR is proven to reveal credible prognostic information, and it can quantify known findings in tumor cell populations. C_LI

bioinformatics↗

bioRxiv2023

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Leveraging spatial molecular information to construct a phylogeographic map of tumor evolution can reveal individualized growth trajectories with diagnostic and therapeutic potential. Integrative analysis of spatial multi-omic data from 31 colorectal specimens revealed simultaneous microenvironmental and clonal alterations as a function of progression. Copy number variation served to re-stratify microsatellite stable and unstable tumors into chromosomally unstable (CIN+) and hypermutated (HM) classes. Phylogeographical maps classified tumors by their evolutionary dynamics, and clonal regions were placed along a global pseudotemporal progression trajectory. Cell-state discovery from a single-cell cohort revealed recurring epithelial gene signatures and infiltrating immune states in spatial transcriptomics. Charting these states along progression pseudotime, we observed a transition to immune exclusion in CIN+ tumors as characterized by a novel gene expression signature comprised of DDR1, TGFBI, PAK4, and DPEP1. We demonstrated how these genes and their protein products are key regulators of extracellular matrix components, are associated with lower cytotoxic immune infiltration, and show prognostic value in external cohorts. Through high-dimensional data integration, this atlas provides insights into co-evolution of tumors and their microenvironments, serving as a resource for stratification and targeted treatment of CRC.

systems biology↗

bioRxiv2021

MTG16 (CBFA2T3) represses E protein-dependent transcription to regulate colonic secretory cell differentiation, epithelial regeneration, and tumorigenesis

Aberrant epithelial differentiation and regeneration contribute to colon pathologies including inflammatory bowel disease (IBD) and colitis-associated cancer (CAC). MTG16 (CBFA2T3) is a transcriptional corepressor expressed in the colonic epithelium. MTG16 deficiency in mice exacerbates colitis and increases tumor burden in CAC, though the underlying mechanisms remain unclear. Here, we identified MTG16 as a central mediator of epithelial differentiation, promoting goblet and restraining enteroendocrine cell development in homeostasis and enabling regeneration following dextran sulfate sodium (DSS)-induced colitis. Transcriptomic analyses implicated increased E box-binding transcription factor (E protein) activity in MTG16-deficient colon crypts. Using a novel mouse model with a point mutation that disrupts MTG16:E protein complex formation (Mtg16P209T), we established that MTG16 exerts control over colonic epithelial differentiation and regeneration by repressing E protein-mediated transcription. Mimicking murine colitis, MTG16 expression was increased in biopsies from patients with active IBD compared to unaffected controls. Finally, uncoupling MTG16:E protein interactions only partially phenocopied the enhanced tumorigenicity of Mtg16-/- colon in the azoxymethane(AOM)/DSS-induced model of CAC, indicating that MTG16 protects from tumorigenesis through additional mechanisms. Collectively, our results demonstrate that MTG16, via its repression of E protein targets, is a key regulator of cell fate decisions during colon homeostasis, colitis, and cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/467178v3_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@21948borg.highwire.dtl.DTLVardef@9f60eeorg.highwire.dtl.DTLVardef@194b9fdorg.highwire.dtl.DTLVardef@13eb1a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

Automated quality control and cell identification of droplet-based single-cell data using dropkick

A major challenge for droplet-based single-cell sequencing technologies is distinguishing true cells from uninformative barcodes in datasets with disparate library sizes confounded by high technical noise (i.e. batch-specific ambient RNA). We present dropkick, a fully automated software tool for quality control and filtering of single-cell RNA sequencing (scRNA-seq) data with a focus on excluding ambient barcodes and recovering real cells bordering the quality threshold. By automatically determining dataset-specific training labels based on predictive global heuristics, dropkick learns a gene-based representation of real cells and ambient noise, calculating a cell probability score for each barcode. Using simulated and real-world scRNA-seq data, we benchmarked dropkick against a conventional thresholding approach and EmptyDrops, a popular computational method, demonstrating greater recovery of rare cell types and exclusion of empty droplets and noisy, uninformative barcodes. We show for both low and high-background datasets that dropkicks weakly supervised model reliably learns which genes are enriched in ambient barcodes and draws a multidimensional boundary that is more robust to dataset-specific variation than existing filtering approaches. dropkick provides a fast, automated tool for reproducible cell identification from scRNA-seq data that is critical to downstream analysis and compatible with popular single-cell analysis Python packages.

bioinformatics↗

bioRxiv2020

Combinatorial transcriptional profiling of mouse and human enteric neurons identifies shared and disparate subtypes in situ.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBACKGROUND & AIMSC_ST_ABSThe enteric nervous system (ENS) coordinates essential intestinal functions through the concerted action of diverse enteric neurons (EN). However, integrated molecular knowledge of EN subtypes is lacking. To compare human and mouse ENs, we transcriptionally profiled healthy ENS from adult humans and mice. We aimed to identify transcripts marking discrete neuron subtypes and visualize conserved EN subtypes for humans and mice in multiple bowel regions. METHODSHuman myenteric ganglia and adjacent smooth muscle were isolated by laser-capture microdissection for RNA-Seq. Ganglia-specific transcriptional profiles were identified by computationally subtracting muscle gene signatures. Nuclei from mouse myenteric neurons were isolated and subjected to single-nucleus RNA-Seq (snRNA-Seq), totaling over four billion reads and 25,208 neurons. Neuronal subtypes were defined using mouse snRNA-Seq data. Comparative informatics between human and mouse datasets identified shared EN subtype markers, which were visualized in situ using hybridization chain reaction (HCR). RESULTSSeveral EN subtypes in the duodenum, ileum, and colon are conserved between humans and mice based on orthologous gene expression. However, some EN subtype-specific genes from mice are expressed in completely distinct morphologically defined subtypes in humans. In mice, we identified several neuronal subtypes that stably express gene modules across all intestinal segments, with graded, regional expression of one or more marker genes. CONCLUSIONSOur combined transcriptional profiling of human myenteric ganglia and mouse EN provides a rich foundation for developing novel intestinal therapeutics. There is congruency among some EN subtypes, but we note multiple species differences that should be carefully considered when relating findings from mouse ENS research to human GI studies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/187211v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1b41277org.highwire.dtl.DTLVardef@12856feorg.highwire.dtl.DTLVardef@1674dadorg.highwire.dtl.DTLVardef@11ca1c8_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

neuroscience↗

bioRxiv2020

Clinically adaptable polymer enables simultaneous spatial analysis of colonic tissues and biofilms

Microbial influences on host cells depend upon the identities of the microbes, their spatial localization, and the responses they invoke on specific host cell populations. Multi-modal analyses of both microbes and host cells in a spatially-resolved fashion would enable studies into these complex interactions in native tissue environments, potentially in clinical specimens. While techniques to preserve each of the microbial and host cell compartments have been used to examine tissues and microbes separately, we endeavored to develop approaches to simultaneously analyze both compartments. Herein, we established an original method for mucus preservation using Poloxamer 407 (also known as Pluronic F-127), a thermoreversible polymer with mucus-adhesive characteristics. We demonstrate that this approach can preserve spatially-defined compartments of the mucus bi-layer in the colon and the bacterial communities within, compared with their marked absence when tissues were processed with traditional formalin-fixed paraffin-embedded (FFPE) pipelines. Additionally, antigens for antibody staining of host cells were preserved and signal intensity for 16S rRNA fluorescence in situ hybridization (FISH) was enhanced in Poloxamer-fixed samples. This in turn enabled us to integrate multi-modal analysis using a modified multiplex immunofluorescence (MxIF) protocol. Importantly, we have formulated Poloxamer 407 to polymerize and crosslink at room temperature for use in clinical workflows. These results suggest that the fixative formulation of Poloxamer 407 can be integrated into biospecimen collection pipelines for simultaneous analysis of microbes and host cells.

cell biology↗

bioRxiv2019

An Inter-Species Translation Model Implicates Integrin Signaling in Infliximab-Resistant Colonic Crohn’s Disease

Anti-TNF therapy resistance is a major clinical challenge in Crohns Disease (CD), partly due to insufficient understanding of disease-site, protein-level mechanisms of CD and anti-TNF treatment resistance. Although some proteomics data from CD mouse models exists, data type and phenotype discrepancies contribute to confounding attempts to translate between preclinical animal models of disease and human clinical cohorts. To meet this important challenge, we develop and demonstrate here an approach called Translatable Components Regression (TransComp-R) to overcome inter-species and trans-omic discrepancies between CD mouse models and human subjects. TransComp-R combines CD mouse model proteomic data with patient pre-treatment transcriptomic data to identify molecular features discernable in the mouse data predictive of patient response to anti-TNF therapy. Interrogating the TransComp-R models predominantly revealed upregulated integrin pathway signaling via collagen-binding integrin ITGA1 in anti-TNF resistant colonic CD (cCD) patients. Toward validation, we performed single-cell RNA sequencing on biopsies from a cCD patient and analyzed publicly available immune cell proteomics data to characterize the immune and intestinal cell types contributing to anti-TNF resistance. We found that ITGA1 is indeed expressed in colonic T-cell populations and that interactions between collagen-binding integrins on T-cells and colonic cell types expressing secreted collagens are associated with anti-TNF therapy resistance. Biologically, TransComp-R linked previously disparate observations about collagen and ITGA1 signaling to a potential therapeutic avenue for overcoming anti-TNF therapy resistance in cCD. Methodologically, TransComp-R provides a flexible, generalizable framework for addressing inter-species, inter-omic, and inter-phenotypic discrepancies between animal models and patients to deliver translationally relevant biological insights.\n\nOne Sentence SummaryBrubaker et al. implicate dysregulated collagen-binding integrin signaling in resistance to anti-TNF therapy in Crohns Disease by developing a mouse-proteomic to human-transcriptomic translation model and confirm the associated inter-cellular signaling network using single-cell RNA sequencing.

systems biology↗

bioRxiv2019

Commensal-derived succinate enhances tuft cell specification and suppresses ileal inflammation

Longitudinal analysis of Crohn's disease (CD) incidence has identified an inverse correlation with helminth infestation and recent studies have revealed that intestinal tuft cell hyperplasia is critical for helminth response. Tuft cell frequency was decreased in the inflamed ilea of CD patients and a mouse model of TNF-induced Crohn's-like ileitis (TNF{Delta}ARE). Single-cell RNA sequencing paired with unbiased differential trajectory analysis of the tuft cell lineage in a genetic model of tuft cell hyperplasia (AtohKO) demonstrated that the tuft cell lineage had increased tricarboxylic acid (TCA) cycle gene signatures. Commensal microbiome-derived succinate was detected in the ileal lumen of these animals while microbiome depletion suppressed tuft cell hyperplasia. Therapeutic succinate treatment in TNF{Delta}ARE animals reduced pathology in correlation with induced tuft cell specification. We provide evidence implicating the modulatory role of intestinal tuft cells in chronic intestinal inflammation, which could facilitate leveraging this rare and elusive cell type for CD treatment.

cell biology↗

bioRxiv2019

A quantitative framework for evaluating single-cell data structure preservation by dimensionality reduction techniques

High-dimensional data, such as those generated using single-cell RNA sequencing, present challenges in interpretation and visualization. Numerical and computational methods for dimensionality reduction allow for low-dimensional representation of genome-scale expression data for downstream clustering, trajectory reconstruction, and biological interpretation. However, a comprehensive and quantitative evaluation of the performance of these techniques has not been established. We present an unbiased framework that defines metrics of global and local structure preservation in dimensionality reduction transformations. Using discrete and continuous scRNA-seq datasets, we find that input cell distribution and method parameters are largely determinant of global, local, and organizational data structure preservation by eleven published dimensionality reduction methods. Code available at github.com/KenLauLab/DR-structure-preservation allows for rapid evaluation of further datasets and methods.

bioinformatics↗

bioRxiv2018

Quantitative assessment of cell population diversity in single-cell landscapes

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such expansion or shrinkage, or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes, identification and definition of altered cell populations, and benchmarking batch correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions, and has broad utility for gaining insight on how cell populations respond to perturbations.

bioinformatics↗