Biology subjects

Lipkin, S. M.

Publications and source records attributed to Lipkin, S. M..

8 recordsLinked to original sources

bioRxiv2025

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular- resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions and ligand-receptor pairs. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale.

systems biology↗

bioRxiv2024

Genomic characterization of Escherichia coli harbor a polyketide synthase (pks) island associated with colorectal cancer (CRC) development

The E. coli strain harboring the polyketide synthase (Pks) island encodes the genotoxin colibactin, a secondary metabolite reported to have severe implications for human health and for the progression of colorectal cancer. The present study involved whole-genome-wide comparison and phylogenetic analysis of pks harboring E. coli isolates to gain insight into the distribution and evolution of these organism. Fifteen E. coli strains isolated from patients with ulcerative colitis were sequenced, 13 of which harbored pks islands. In addition, 2,654 genomes from the public database were also screened for pks harboring E. coli genomes, 158 of which were pks-positive isolates. Whole-genome-wide comparison and phylogenetic analysis revealed that 171 (158+13) pks-positive isolates belonged to phylogroup B2, and most of the isolates associated to sequence types ST73 and ST95. One isolate from an ulcerative colitis (UC) patient was of the sequence type ST8303. The maximum likelihood tree based on the core genome of pks-positive isolates revealed horizontal gene transfer across sequence types and serotypes. Virulome and resistome analyses revealed the preponderance of virulence genes and a reduced number of antimicrobial genes in Pks-positive isolates. This study strongly contributes to understanding the evolution of pks islands in E. coli.

immunology↗

bioRxiv2021

Plakoglobin and HMGB1 mediate intestinal epithelial cell apoptosis induced by Clostridioides difficile TcdB

Clostridioides difficile infection (CDI) is the leading cause of antibiotic-associated intestinal disease, resulting in severe diarrhea and fatal pseudomembranous colitis. TcdB, one of the essential virulence factors secreted by this bacterium, induces host cell apoptosis through a poorly understood mechanism. Here, we performed an RNAi screen customized to Caco-2 cells, a cell line model of the intestinal epithelium, to discover host factors involved in TcdB-induced apoptosis. We identified plakoglobin, also known as junction plakoglobin (JUP) or {gamma}-catenin, a member of the catenin family, as a novel host factor, and a previously known cell death-related chromatin factor, high mobility group box 1 (HMGB1). Disruption of those host factors by RNAi and CRISPR resulted in resistance of cells to TcdB-mediated and mitochondria-dependent apoptosis. JUP was redistributed from adherens junctions to the mitochondria and colocalized with Bcl-XL after stimulation by TcdB, suggesting a role of JUP in cell death signaling through mitochondria. Treatment with glycyrrhizin, an HMGB1 inhibitor, resulted in significantly increased resistance to TcdB-induced epithelial damage in cultured cells and a mouse ligated colon loop model. These findings demonstrate the critical roles of JUP and HMGB1 in TcdB-induced epithelial cell apoptosis.

microbiology↗

bioRxiv2020

A 3D Structural Interactome to Explore the Impact of Evolutionary Divergence, Population Variation, and Small-molecule Drugs on SARS-CoV-2-Human Protein-Protein Interactions

The recent COVID-19 pandemic has sparked a global public health crisis. Vital to the development of informed treatments for this disease is a comprehensive understanding of the molecular interactions involved in disease pathology. One lens through which we can better understand this pathology is through the network of protein-protein interactions between its viral agent, SARS-CoV-2, and its human host. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV can be explained by rapid evolution along the interface between the Spike protein and its human receptor (ACE2) leading to increased binding affinity. Sequence divergences that modulate other protein-protein interactions may further explain differences in transmission and virulence in this novel coronavirus. To facilitate these comparisons, we combined homology-based structural modeling with the ECLAIR pipeline for interface prediction at residue resolution, and molecular docking with PyRosetta. This enabled us to compile a novel 3D structural interactome meta-analysis for the published interactome network between SARS-CoV-2 and human. This resource includes docked structures for all interactions with protein structures, enrichment analysis of variation along interfaces, predicted {Delta}{Delta}G between SARS-CoV and SARS-CoV-2 variants for each interaction, predicted impact of natural human population variation on binding affinity, and a further prioritized set of drug repurposing candidates predicted to overlap with protein interfaces{dagger}. All predictions are available online{dagger} for easy access and are continually updated when new interactions are published. {dagger}Some sections of this pre-print have been redacted to comply with current bioRxiv policy restricting the dissemination of purely in silico results predicting potential therapies for SARS-CoV-2 that have not undergone thorough peer-review. The results section titled "Prioritization of Candidate Inhibitors of SARS-CoV-2-Human Interactions Through Binding Site Comparison," Figure 4, Supplemental Table 9, and all links to our web resource have been removed. Blank headers left in place to preserve structure and item numbering. Our full manuscript will be published in an appropriate journal following peer-review.

systems biology↗

bioRxiv2019

A full-proteome, interaction-specific characterization of mutational hotspots across human cancers

Rapid accumulation of cancer genomic data has led to the identification of an increasing number of mutational hotspots with uncharacterized significance. Here we present a biologically-informed computational framework that characterizes the functional relevance of all 1,107 published mutational hotspots identified in [~]25,000 tumor samples across 41 cancer types in the context of a human 3D interactome network, in which the interface of each interaction is mapped at residue resolution. Hotspots reside in network hub proteins and are enriched on protein interaction interfaces, suggesting that alteration of specific protein-protein interactions is critical for the oncogenicity of many hotspot mutations. Our framework enables, for the first time, systematic identification of specific protein interactions affected by hotspot mutations at the full proteome scale. Furthermore, by constructing a hotspot-affected network that connects all hotspot-affected interactions throughout the whole human interactome, we uncover genome-wide relationships among hotspots and implicate novel cancer proteins that do not harbor hotspot mutations themselves. Moreover, applying our network-based framework to specific cancer types identifies clinically significant hotspots that can be used for prognosis and therapy targets. Overall, we demonstrate that our framework bridges the gap between the statistical significance of mutational hotspots and their biological and clinical significance in human cancers.

bioinformatics↗

bioRxiv2017

Intestinal crypts recover rapidly from focal damage with coordinated motion of stem cells that is impaired by aging

Despite the continuous renewal and turnover of the small intestinal epithelium, the intestinal stem cell niche maintains a soccer ball-like, alternating pattern of stem and Paneth cells in the crypt. To study the robustness of the niche pattern, we used intravital two-photon microscopy in mice with fluorescently-labeled Lgr5+ intestinal stem cells and precisely perturbed the mosaic pattern with femtosecond laser ablation. Ablation of one to three cells initiated rapid motion of niche cells that restored the alternation in the crypt pattern within about two hours without any cell proliferation. Crypt cells then performed a coordinated dilation of the crypt lumen, which resulted in peristalsis-like motion that forced damaged cells out of the niche. Crypt cell motion was reduced with inhibition of the ROCK pathway and attenuated with old age, and both resulted in incomplete pattern recovery. This suggests that in addition to proliferation and self-renewal, motility of stem cells is critical for maintaining homeostasis. Reduction of this novel behavior of stem cells could contribute to disease and age-related changes.

physiology↗

bioRxiv2017

Novel Pedigree Analysis Implicates DNA Repair And Chromatin Remodeling In Multiple Myeloma Risk

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance - a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691*, p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly, p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.\n\nAUTHOR SUMMARYAlthough family-based studies demonstrate inherited variants play a role in many common and complex diseases, finding the genes responsible remains a challenge. High-risk pedigrees, or families with more disease than expected by chance, have been helpful in the discovery of variants responsible for less complex diseases, but have not reached their potential in complex diseases. Here, we describe a method to utilize high-risk pedigrees to discover risk-genes in complex diseases. Our method is appropriate for complex diseases because it allows for genetic-heterogeneity, or multiple causes of disease, within a pedigree. This method allows us to identify shared segments that likely harbor disease-causing variants in a family. We apply our method in Multiple Myeloma, a heritable and complex cancer of plasma cells. We identified two genes USP45 and ARID1A that fall within shared segments with compelling statistical evidence. Exome sequencing of these genes revealed likely-damaging variants inherited in Myeloma high-risk families, suggesting these genes likely play a role in development of Myeloma. Our Myeloma findings demonstrate our high-risk pedigree method can identify genetic regions of interest in large high-risk pedigrees that are also relevant to smaller nuclear families and overall disease risk. In sum, we offer a strategy, applicable across phenotypes, to revitalize high-risk pedigrees in the discovery of the genetic basis of common and complex disease.

genetics↗

bioRxiv2017

Discovery and reporting of clinically-relevant germline variants in advanced cancer patients assessed using whole-exome sequencing

PurposeIn precision cancer care, WES-based analysis of tumor-normal samples helps reveal somatic alterations but can also identify cancer-associated germline variants important for disease surveillance, treatment choice and cancer prevention. WES can also identify germline secondary findings impacting risk of cardiac, neurodegenerative or metabolic diseases. In patients with advanced cancer, the frequency of reportable secondary findings encountered with WES is not well defined.\n\nMethodsTo address this question, we analyzed a cohort of 343 patients with advanced, metastatic cancer for whom we have performed tumor and germline WES interrogating more than 21,000 genes using a CLIA/CLEP approved assay.\n\nResults17% of patients in our cohort have one or more reportable germline variants, including patients with pathogenic variants in the BRCA1 and BRCA2 genes. The frequency of non-cancer clinically relevant germline variants (8.8%) was within the range of two control non-cancer cohorts (11.0% and 6.5%). The frequency of variants in cancer-associated genes was significantly higher (p<0.0005) in our advanced cancer cohort (8.2%) compared to control cohorts (2.7% and 3.8%). More than 50% of patients with reportable germline cancer variants had a family history of cancer.\n\nConclusionthese results stress the importance of returning germline results found during somatic genomic tumor testing.

genomics↗