Biology subjects

Humphreys, B. D.

Publications and source records attributed to Humphreys, B. D..

12 recordsLinked to original sources

bioRxiv2026

Cellular-Resolution Spatial Transcriptomics Reveals Laminar VSMC Phenotypic Remodeling and a Hypoxic Medial Core in Human Thoracic Aortic Dissection

Sporadic ascending aortic dissection (AAD) carries high short-term mortality and long-term morbidity. Hypertension is the predominant risk factor, yet no established tools identify patients at imminent risk. Although medial vulnerability likely contributes to dissection in heritable aortopathies, AAD predominantly understood as a luminal breach followed by false-lumen propagation, with comparatively less emphasis on the underlying medial substrate. We sought to define the vascular smooth muscle cell (VSMC) landscape in human AAD and identify spatial remodeling programs associated with interlamellar separation. Using Xenium in situ spatial transcriptomic profiling, we generated cellular-resolution maps of the dissected human ascending aorta. We identified extensive VSMC remodeling organized into distinct laminar domains across the aortic media, with distinct VSMC states supported by gene-expression module scoring and trajectory analysis. A reproducible mid-medial core of chronically hypoxia-adapted VSMCs was identified across patients and supported by carbonic anhydrase 9 immunohistochemistry. These hypoxia-adapted VSMCs lacked inflammatory and immediate-early activation programs and were spatially distinct from stress-responsive VSMC states enriched along the false lumen. Circumferential profiling in a complete aortic ring demonstrated greater adaptive remodeling in the outer curve compared with the inner curve. In contrast, donor control aortas contained fewer modulated VSMC states, less laminar striation, and no comparable hypoxia-adapted core. These findings define a spatially organized medial remodeling landscape in AAD and identify hypoxia-associated VSMC modulation as a potential feature of medial domains associated with heightened vulnerability to interlamellar separation. Defining these remodeling domains may inform improved risk stratification and experimental models that better recapitulate human AAD pathology.

genomics↗

bioRxiv2024

Multi-omics profiling of mouse polycystic kidney disease progression at a single cell resolution

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and causes significant morbidity, ultimately leading to end-stage kidney disease. PKD pathogenesis is characterized by complex and dynamic alterations in multiple cell types during disease progression, hampering a deeper understanding of disease mechanism and the development of therapeutic approaches. Here, we generate a single nucleus multimodal atlas of an orthologous mouse PKD model at early, mid and late timepoints, consisting of 125,434 single-nucleus transcriptomic and epigenetic multiomes. We catalogue differentially expressed genes and activated epigenetic regions in each cell type during PKD progression, characterizing cell-type-specific responses to Pkd1 deletion. We describe heterogeneous, atypical collecting duct cells as well as proximal tubular cells that constitute cyst epithelia in PKD. The transcriptional regulation of the cyst lining cell marker GPRC5A is conserved between mouse and human PKD cystic epithelia, suggesting shared gene regulatory pathways. Our single nucleus multiomic analysis of mouse PKD provides a foundation to understand the earliest changes molecular deregulation in a mouse model of PKD at a single-cell resolution.

genomics↗

bioRxiv2024

Epigenetic reprogramming driving successful and failed repair in acute kidney injury

Acute kidney injury (AKI) causes epithelial damage followed by subsequent repair. While successful repair restores kidney function, this process is often incomplete and can lead to chronic kidney disease (CKD) in a process called failed repair. To better understand the epigenetic reprogramming driving this AKI-to-CKD transition we generated a single nucleus multiomic atlas for the full mouse AKI time course, consisting of [~]280,000 single nucleus transcriptomes and epigenomes. We reveal cell-specific dynamic alterations in gene regulatory landscapes reflecting especially activation of proinflammatory pathways. We further generated single nucleus multiomic data from four human AKI samples including validation by genome-wide identification of NF-kB binding sites. A regularized regression analysis identifies key regulators involved in both successful and failed repair cell fate, identifying the transcription factor CREB5 as a regulator of both successful and failed tubular repair that also drives proximal tubule cell proliferation after injury. Our interspecies multiomic approach provides a foundation to comprehensively understand cell states in AKI.

genomics↗

bioRxiv2022

Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs

Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5,371 GLOM and 9,787 TUBE eQTLs by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an "integrative prior" for Bayesian statistical fine mapping. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.

genomics↗

bioRxiv2022

Quality assessment and refinement of chromatin accessibility data using a sequence-based predictive model

Chromatin accessibility assays are central to the genome-wide identification of gene regulatory elements associated with transcriptional regulation. However, the data have highly variable quality arising from several biological and technical factors. To surmount this problem, we use the predictability of open-chromatin peaks from DNA sequence-based machine-learning models to evaluate and refine chromatin accessibility data. Our framework, gapped k-mer SVM quality check (gkmQC), provides the quality metrics for a sample based on the prediction accuracy of the trained models. We tested 886 samples with DNase-seq from the ENCODE/Roadmap projects to demonstrate that gkmQC can effectively identify high-quality samples underperforming owing to marginal read depths. Peaks identified in high-quality samples by gkmQC are more accurately aligned at functional regulatory elements, show greater enrichment of regulatory elements harboring functional variants from genome-wide association studies (GWAS), and explain greater heritability of phenotypes from their relevant tissues. Moreover, gkmQC can optimize the peak-calling threshold to identify additional peaks, especially for single-cell chromatin accessibility data as well as bulk data. Here we provide a standalone open-source toolkit (https://github.com/Dongwon-Lee/gkmQC) for such analyses and share improved regulatory maps using gkmQC. These resources will contribute to the functional interpretation of disease-associated regulatory genetic variation.

genomics↗

bioRxiv2021

Defining cellular complexity in human autosomal dominant polycystic kidney disease by multimodal single cell analysis

Autosomal dominant polycystic kidney disease (ADPKD) is the leading genetic cause of end stage renal disease and is characterized by the formation and progressive expansion of kidney cysts. Most ADPKD cases arise from mutations in either the PKD1 or PKD2 gene but the precise downstream signaling pathways driving cyst growth are not well understood, and relatively few studies investigate human cystic kidney due to sample scarcity. In order to better understand the cell types and states driving human ADPKD progression, we analyzed eight ADPKD and five healthy human kidney samples, generating a single cell multiomic atlas consisting of ~100,000 single nucleus transcriptomes and ~50,000 single nucleus epigenomes. The integrated datasets identified 11 primary cell clusters including most epithelial cell types as well as large endothelial and fibroblast cell clusters. Proximal tubular cells from ADPKD kidneys expressed a failed repair transcriptomic signature characterized by profibrotic and proinflammatory transcripts. We identified the G protein-coupled receptor GPRC5A as specifically upregulated in cyst lining cells derived from collecting duct. The principal cell subpopulation enriched for GPRC5A expression also exhibited increased transcription factor binding motif availability for NF-{kappa}B, TEAD, CREB and retinoic acid receptor families and we identified and validated a distal enhancer regulating GPRC5A expression containing these transcription factor binding motifs. This study establishes the single cell transcriptomic and epigenomic landscape of ADPKD, revealing previously unrecognized cellular heterogeneity.

genomics↗

bioRxiv2020

Harnessing Expressed Single Nucleotide Variation and Single Cell RNA Sequencing to Define Immune Cell Chimerism in the Rejecting Kidney Transplant

In solid organ transplantation, donor derived immune cells are assumed to decline with time after surgery. Whether donor leukocytes persist within kidney transplants or play any role in rejection is unknown, however, in part because of limited techniques for distinguishing recipient and donor cells. To address this question, we performed paired whole exome sequencing of donor and recipient DNA and single cell RNA sequencing (scRNA-seq) of 5 human kidney transplant biopsy cores. Exome sequences were used to define single nucleotide variations (SNV) across all samples. By analyzing expressed SNVs in the scRNA-seq dataset we could define recipient vs. donor cell origin for all 81,139 cells. The leukocyte donor to recipient ratio varied with rejection status for macrophages and with time post-transplant for lymphocytes. Recipient macrophages were characterized by inflammatory activation and donor macrophages by antigen presentation and complement signaling. Recipient origin T cells expressed cytotoxic and pro-inflammatory genes consistent with an effector cell phenotype whereas donor origin T cells are likely quiescent expressing oxidative phosphorylation genes relative to recipient T cells. Finally, both donor and recipient T cell clones were present within the rejecting kidney, suggesting lymphoid aggregation. Our results indicate that donor origin macrophages and T cells have distinct transcriptional profiles compared to their recipient counterparts and donor macrophages can persist for years post transplantation. This study demonstrates the power of this approach to accurately define leukocyte chimerism in a complex tissue such as the kidney transplant coupled with the ability to examine transcriptional profiles at single cell resolution.

genomics↗

bioRxiv2020

Single nucleus RNASeq profiling of mouse lung: reduced dissociation bias and improved detection of rare cell types compared with single cell RNASeq

RATIONALESingle cell RNA-sequencing (scRNASeq) has led to multiple recent advances in our understanding of lung biology and pathophysiology, but utility is limited by the need for fresh samples, loss of cell types due to death or inadequate dissociation, and the induction of transcriptional stress responses during tissue digestion. Single nucleus RNASeq (snRNASeq) has addressed these deficiencies in some other tissues, but no protocol exists for lung. We sought to develop such a protocol and compare its results with scRNA-seq. METHODSSingle nucleus suspensions were prepared rapidly (45 min) from two mouse lungs in lysis buffer on ice while a single cell suspension from an additional mouse lung was generated using a combination of enzymatic and mechanical dissociation (1.5 h). Cells and nuclei were processed using the 10x Genomics platform, and following sequencing of cDNA libraries single cell data was analyzed by Seurat. RESULTS16,656 single nucleus and 11,934 single cell transcriptomes were generated. Despite reduced mRNA levels in nuclei vs. cells, gene detection rates were equivalent in snRNASeq and scRNASeq ([~]1,750 genes and 3,000 UMI per cell) when mapping intronic and exonic reads. snRNASeq identified a much greater proportion of epithelial cells than scRNASeq (46% vs 2% of total), including basal and neuroendocrine cells, while reducing immune cells from 54% to 15%. snRNASeq transcripts are enriched for transcription factors and signaling proteins, with reduced detection of housekeeping genes, mitochondrial genes, and artifactual stress response genes. Both techniques improved mesenchymal cell detection over previous studies, and analysis of fibroblast diversity showed two transcriptionally distinct populations of Col13a1+ cells, termed Bmper+ and Brinp1+ fibroblasts. To define homeostatic signaling relationships among cell types, receptor-ligand mapping of was performed for alveolar compartment cells using snRNASeq data, revealing complex interplay among epithelial, mesenchymal, and capillary endothelial cells. CONCLUSIONSingle nucleus RNASeq can be readily applied to snap frozen, archival murine lung samples, improves dissociation bias, eliminates artifactual gene expression and provides similar gene detection compared to scRNASeq.

genomics↗

bioRxiv2020

Chemokine receptor 2-targeted molecular imaging in pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, inflammatory lung disease that is monitored clinically by measures of lung function, without effective molecular markers of disease activity or therapeutic efficacy. Lung immune cells active in the pro-fibrotic process include inflammatory monocyte and interstitial macrophages that express the C-C motif chemokine receptor 2 (CCR2). CCR2+ monocyte lung influx is essential for disease phenotypes in models of fibrosis and identified in lungs from subjects with IPF. Here, we show that our peptide-based radiotracer 64Cu-DOTA-ECL1i identifies CCR2+ inflammatory monocytes and interstitial macrophages in multiple preclinical mouse models of lung fibrosis, using positron emission tomography (PET) imaging. Mice with bleomycin-induced fibrosis treated with blocking antibodies to interleukin-1{beta}, a mediator of fibrosis associated with CCR2+ cell inflammation, or with pirfenidone, an approved anti-fibrotic agent, demonstrated decreased CCR2-dependent interstitial macrophage accumulation and reduced 64Cu-DOTA-ECL1i PET uptake, compared to controls. Lung tissues from patients with fibrotic lung disease demonstrated abundant CCR2+ cells surrounding regions of fibrosis, and an ex vivo tissue-binding assay showed correlation between radiotracer localization and CCR2+ cells. In a phase 0/1 clinical study of 64Cu-DOTA-ECL1i PET, healthy volunteers showed little lung uptake, while subjects with pulmonary fibrosis exhibited increased uptake, notably in zones of subpleural fibrosis, reflecting the distribution of CCR2+ cells in the profibrotic niche. These findings support a pathologic role of inflammatory lung monocytes/macrophages in fibrotic lung disease and the translational use of 64Cu-DOTA-ECL1i PET to track CCR2-specific inflammation for image-guided therapy. One Sentence SummaryPET imaging of CCR2+ cells in lung fibrosis identifies a therapeutic response in mouse models and displays a perifibrotic signal in subjects with IPF.

cell biology↗

bioRxiv2019

The Single Cell Transcriptomic Landscape of Early Human Diabetic Nephropathy

Diabetic nephropathy is characterized by damage to both the glomerulus and tubulointerstitium, but relatively little is known about accompanying cell-specific changes in gene expression. We performed unbiased single nucleus RNA sequencing (snRNAseq) on cryopreserved human diabetic kidney samples to generate 23,980 single nucleus transcriptomes from three control and three early diabetic nephropathy samples. All major cell types of the kidney were represented in the final dataset. Side by side comparison demonstrated cell-type-specific changes in gene expression that are important for ion transport, angiogenesis, and immune cell activation. In particular, we show that the diabetic loop of Henle, late distal convoluted tubule, and principal cells all adopt a gene expression signature consistent with increased potassium secretion, including alterations in Na-K+-ATPase, WNK1, mineralocorticoid receptor and NEDD4L expression, as well as decreased paracellular calcium and magnesium reabsorption. We also identify strong angiogenic signatures in glomerular cell types, proximal convoluted tubule, distal convoluted tubule and principal cells. Taken together, these results suggest that increased potassium secretion and angiogenic signaling represent early kidney responses in human diabetic nephropathy.\n\nSignificance StatementSingle nucleus RNA sequencing revealed gene expression changes in early diabetic nephropathy that promote urinary potassium secretion and decreased calcium and magnesium reabsorption. Multiple cell types exhibited angiogenic signatures, which may represent early signs of aberrant angiogenesis. These alterations may help to identify biomarkers for disease progression or signaling pathways amenable to early intervention.\n\nO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

genomics↗

bioRxiv2018

FoxM1 drives proximal tubule proliferation during repair from acute kidney injury

The proximal tubule has a remarkable capacity for repair after acute injury but the cellular lineage and molecular mechanisms underlying this repair response have been poorly characterized. Here, we developed a Kim-1-GFPCreERt2 knockin mouse line (Kim-1-GCE), performed genetic lineage analysis after injury and measured the cellular transcriptome of proximal tubule during repair. Acutely injured genetically labeled clones co-expressed Kim-1, Vimentin, Sox9 and Ki67, indicating a dedifferentiated and proliferative state. Clonal analysis revealed clonal expansion of Kim-1+ cells, indicating that acutely injured, dedifferentiated proximal tubule cells account for repair rather than a fixed tubular progenitor. Translational profiling during injury and repair revealed signatures of both successful and unsuccessful maladaptive repair. The transcription factor FoxM1 was induced early in injury, was required for epithelial proliferation, and was dependent on epidermal growth factor receptor (EGFR) stimulation. In conclusion, dedifferentiated proximal tubule cells effect proximal tubule repair and we reveal a novel EGFR-FoxM1-dependent signaling pathway that drives proliferative repair after injury.

cell biology↗

bioRxiv2017

Comparative analysis of kidney organoid and adult human kidney single cell and single nucleus transcriptomes

Kidney organoids differentiated from human pluripotent stem cells hold great promise for understanding organogenesis, modeling disease and ultimately as a source of replacement tissue. Realizing the full potential of this technology will require better differentiation strategies based upon knowledge of the cellular diversity and differentiation state of all cells within these organoids. Here we analyze single cell gene expression in 45,227 cells isolated from 23 organoids differentiated using two different protocols. Both generate kidney organoids that contain a diverse range of kidney cells at differing ratios as well as non-renal cell types. We quantified the differentiation state of major organoid kidney cell types by comparing them against a 4,259 single nucleus RNA-seq dataset generated from adult human kidney, revealing immaturity of all kidney organoid cell types. We reconstructed lineage relationships during organoid differentiation through pseudotemporal ordering, and identified transcription factor networks associated with fate decisions. These results define impressive kidney organoid cell diversity, identify incomplete differentiation as a major roadblock for current directed differentiation protocols and provide a human adult kidney snRNA-seq dataset against which to benchmark future progress.

developmental biology↗