Biology subjects

MacParland, S. A.

Publications and source records attributed to MacParland, S. A..

7 recordsLinked to original sources

bioRxiv2026

High-resolution spatial transcriptomics of adult and pediatric human liver with Visium HD

The liver is composed of diverse cell populations that coordinate essential metabolic and immune functions. Single-cell transcriptomics has advanced characterization of liver cellular composition, but dissociation of tissue to single-cells can introduce biases through the enrichment or depletion of cell types. Spatial transcriptomics is a complementary approach to avoid inherent bias for cell populations and to add important spatial context. The Visium HD spatial transcriptomics technology from 10X Genomics enables high-resolution spatial mapping of gene expression in tissue samples with a bin width of 2{micro}m enabling quantification of transcripts at a sub-cellular resolution. We applied Visium HD to three healthy human liver donor samples, from two adult and one pediatric donor. We identified cell types by clustering 8{micro}m bins and integration with single-cell reference maps. Differential expression analyses identified spatially distinct gene expression resulting in development of a high-resolution map of the liver. This resource provides cell-level and spatially-resolved insights into the cellular and anatomical heterogeneity of the liver to serve as a resource for researchers to identify disease-specific spatial signatures and novel therapeutic targets.

genomics↗

bioRxiv2025

A Single-Cell Atlas Of Human Pediatric Liver Reveals Age-Related Hepatic Gene Signatures

Background & AimsThe liver plays a critical role in metabolism and immune function, yet the contributions of its heterogeneous cell types to these processes remain unclear. While most liver studies focus on adults, pediatric liver diseases often present differently, underscoring the need for age-specific research. Approach & ResultsTo better understand cellular drivers of childhood liver diseases, we generated single-cell RNA-seq (scRNA-seq) maps of the normal pediatric liver and used this map to examine disease-related populations in biopsies from pediatric patients with Intestinal Failure-Associated Liver Disease (IFALD). The normal pediatric liver map consists of 42,660 cells from 9 donors aged 2-17 years. Compared to normal adult liver (26,372 cells; 7 donors, age 26-69) pediatric livers exhibited differences in myeloid populations. Specifically, pediatric Kupffer-like cells (MARCO+C1QA+VSIG4+) exhibited higher expression of immune activation genes, including CCL4, CCL3 and IL1B. In vitro stimulation confirmed more IL1-{beta} secreting myeloid cells in pediatric versus adult livers, supporting these findings. Using the pediatric atlas as a reference, we analyzed three IFALD biopsies (11,969 cells; 3 donors, ages 4 months-9 years) and identified increased expression of fibrosis-associated genes (e.g., LY96) in Kupffer-like cells. Additionally, mesenchymal cells in IFALD showed fibrotic gene modules resembling adult liver cells more than healthy pediatric cells. These signatures, undetectable when comparing IFALD to adult liver alone, highlighting the value of a pediatric map. ConclusionsTaken together, our healthy pediatric liver atlas reveals distinct age-related signatures and provides background against which to interpret pediatric liver disease data. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/649149v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@8d4131org.highwire.dtl.DTLVardef@1b336d2org.highwire.dtl.DTLVardef@d43ddeorg.highwire.dtl.DTLVardef@29fadf_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

A Single-Cell Woodchuck Liver Atlas Identifies Healthy and Disease-Related Cellular Programs Conserved in Human

BackgroundModel organisms allowing for longitudinal examinations of liver disease pathogenesis are pivotal for the development of new therapeutic modalities. The eastern North American woodchuck develops chronic hepatitis and liver cancer after woodchuck hepatitis virus (WHV) infection, mirroring aspects of the natural history of the human hepatitis B virus (HBV). However, the cellular landscape of the woodchuck liver and the cell-level relevance of WHV infection to HBV infection is currently uncharacterized. MethodsWe employed single-cell RNA sequencing (RNA-seq) to generate an atlas of healthy woodchuck liver (63,389 cells, n=8) and peripheral blood mononuclear cells (PBMCs) (26,972 cells, n=7). Cell-specific and hepatic zonation gene signatures were validated using spatial transcriptomics (n=1). We employed our atlas to examine immune activation in stimulated precision cut-liver slices (PCLS) and disease-related pathway activation in chronic WHV infection (11,797 cells, n=3). We further employed our atlas to examine shared disease pathways between WHV infection and human HBV infection. ResultsOur atlas revealed woodchuck hepatic cellular diversity comparable to human and murine livers. Applying single-nucleus RNA-seq to PMA/ionomycin-stimulated precision cut liver slices revealed inflammation-associated activation signatures in T cell, myeloid and endothelial cell compartment. Finally, we describe intrahepatic T cells in chronic WHV hepatitis with both exhaustion and activation-associated signatures that resemble intrahepatic T cell genes signatures described in human chronic HBV. ConclusionsWe present a multi-omic atlas of healthy, diseased and ex vivo stimulated woodchuck liver. By identifying shared pathological processes between WHV and HBV infections, our findings reinforce the value of this preclinical model in translational research. This resource aims to advance studies on HBV pathogenesis and oncogenesis to speed the development of novel therapeutic strategies. Impact and Implications/Lay summaryThe liver plays important roles in metabolism, detoxification, and immune processes; liver transplantation is often the only treatment option for severe chronic liver diseases. Therefore, developing animal models that reflect human liver disease and can be studied throughout the disease course is crucial for the discovery of new treatment options. The woodchuck is an animal that develops chronic hepatitis and liver cancer after infection with woodchuck hepatitis virus, which models the human hepatitis type B virus infection (HBV) and associated hepatic carcinoma. However, our understanding of the cells that compose the woodchuck liver is limited, making it challenging to design and test cell-based therapeutics. In this study, we atlased the healthy and chronically infected woodchuck liver, found that liver cell types in woodchuck resemble those in humans, and employed the atlas to show similarities between WHV and HBV at the cell level, reinforcing the potential of WHV-infected woodchuck as a model for human HBV disease. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/641192v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@18fdd40org.highwire.dtl.DTLVardef@6ccf2org.highwire.dtl.DTLVardef@7923e1org.highwire.dtl.DTLVardef@122a8d2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Single-cell and spatial transcriptomics reveals the human liver immunological landscape and myeloid dysfunction in PSC.

BackgroundPrimary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease characterized by bile retention, biliary tree destruction, and progressive fibrosis leading to end stage liver disease and transplantation. There is an unmet need to understand the cellular composition of the PSC liver and how it underlies disease pathogenesis. As such, we generated a comprehensive atlas of the PSC liver and a reference healthy liver dataset using multiple multi-omic modalities and functional validation. MethodsIn this work, we employed single-cell (12,000 cells), single-nuclei (23,000 nuclei), and spatial transcriptomics (1 sample by 10x Visium and 3 samples with multi-region profiling by Nanostring GeoMx DSP) to profile the cellular ecosystem in 5 patients with PSC. Transcriptomic profiles were compared to 100k single cell transcriptomes and spatial transcriptomics controls from 24 healthy neurologically deceased donor (NDD) livers. Flow cytometry and intracellular cytokine staining was performed to validate PSC-specific differences in immune phenotype and function. ResultsPSC explants with cirrhosis of the liver parenchyma and prominent periductal fibrosis were associated with a unique population of hepatocytes which transformed to a cholangiocyte-like phenotype. These hepatocytes were surrounded by diverse immune cell populations, including monocyte-like macrophages, liver-resident and circulating natural killer (NK) cells. Inflamed cholangiocytes, fibrosis-resident hepatic stellate cells, and endothelial cells released cytokines that recruited CD4+T-cells, dendritic cells, and neutrophils to the PSC liver. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional inflammatory response to LPS and IFN-{gamma} stimulation. ConclusionsWe present the first comprehensive atlas of the PSC liver and demonstrate hyper-activation and exhaustion-like phenotypes of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. Lay SummaryPrimary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts. Due to a limited understanding of the underlying pathogenesis of disease, there remains a paucity of treatment options. As such, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that outside PSC scar regions, hepatocytes are transitioning to bile duct cells, whereas within the scars, there is an accumulation of immune cells. Of these cells, macrophages that typically contribute to tissue repair were enriched in immunoregulatory genes and were less responsive to stimulation. These cells are likely involved in maintaining hepatic inflammation and could be targeted in novel therapeutic development.

cell biology↗

bioRxiv2021

Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity

Maintaining organ homeostasis requires complex functional synergy between distinct cell types, a snapshot of which is glimpsed through the simultaneously broad and granular analysis provided by single-cell atlases. Knowledge of the transcriptional programs underpinning the complex and specialized functions of human kidney cell populations at homeostasis is limited by difficulty accessing healthy, fresh tissue. Here, we present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 high-quality cells to map healthy kidney at high resolution. Our sex-balanced dataset revealed sex-based differences in gene expression within proximal tubular cells, specifically, increased anti-oxidant metallothionein genes in females and the predominance of aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed between male and female proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. Within the immune niche, we identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions and validated findings by flow cytometry. We observed significant heterogeneity in resident myeloid populations and identified an MRC1+ LYVE1+ FOLR2+ C1QC+ population as the predominant myeloid population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, revealing novel insights into the complexity of renal parenchymal cells and kidney-resident immune populations.

immunology↗

bioRxiv2021

Single Cell, Single Nucleus and Spatial RNA Sequencing of the Human Liver Identifies Hepatic Stellate Cell and Cholangiocyte Heterogeneity

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human livers parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

cell biology↗

bioRxiv2019

Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data

Identification of cell type subpopulations from complex cell mixtures using single-cell RNA-sequencing (scRNA-seq) data includes automated computational steps like data normalization, dimensionality reduction and cell clustering. However, assigning cell type labels to cell clusters is still conducted manually by most researchers, resulting in limited documentation, low reproducibility and uncontrolled vocabularies. Two bottlenecks to automating this task are the scarcity of reference cell type gene expression signatures and that some dedicated methods are available only as web servers with limited cell type gene expression signatures. In this study, we benchmarked four methods (CIBERSORT, GSEA, GSVA, and ORA) for the task of assigning cell type labels to cell clusters from scRNA-seq data. We used scRNA-seq datasets from liver, peripheral blood mononuclear cells and retinal neurons for which reference cell type gene expression signatures were available. Our results show that, in general, all four methods show a high performance in the task as evaluated by Receiver Operating Characteristic curve analysis (average AUC = 0.94, sd = 0.036), whereas Precision-Recall curve analyses show a wide variation depending on the method and dataset (average AUC = 0.53, sd = 0.24). CIBERSORT and GSVA were the top two performers. Additionally, GSVA was the fastest of the four methods and was more robust in cell type gene expression signature subsampling simulations. We provide an extensible framework to evaluate other methods and datasets at https://github.com/jdime/scRNAseq_cell_cluster_labeling.

bioinformatics↗