Biology subjects

Haberman, Y.

Publications and source records attributed to Haberman, Y..

3 recordsLinked to original sources

bioRxiv2024

Eicosatetraynoic Acid Regulates Pro-Fibrotic Pathways in an Induced Pluripotent Stem Cell Derived Macrophage:Human Intestinal Organoid Model of Crohns Disease

Background and AimsWe previously identified small molecules predicted to reverse an ileal gene signature for future Crohns Disease (CD) strictures. Here we used a new human intestinal organoid (HIO) model system containing macrophages to test a lead candidate, eicosatetraynoic acid (ETYA). MethodsInduced pluripotent stem cell lines (iPSC) were derived from CD patients and differentiated into macrophages and HIOs. Macrophages and macrophage:HIO co-cultures were exposed to lipopolysaccharide (LPS) with and without ETYA pre-treatment. Cytospin and flow cytometry characterized macrophage morphology and activation markers, and RNA sequencing defined the global pattern of macrophage gene expression. TaqMan Low Density Array, Luminex multiplex assay, immunohistologic staining, and sirius red polarized light microscopy were performed to measure macrophage cytokine production and HIO pro-fibrotic gene expression and collagen content. ResultsiPSC-derived macrophages exhibited morphology similar to primary macrophages and expressed inflammatory macrophage cell surface markers including CD64 and CD68. LPS-stimulated macrophages expressed a global pattern of gene expression enriched in CD ileal inflammatory macrophages and matrisome secreted products, and produced cytokines and chemokines including CCL2, IL1B, and OSM implicated in refractory disease. ETYA suppressed CD64 abundance and pro-fibrotic gene expression pathways in LPS stimulated macrophages. Co-culture of LPS-primed macrophages with HIO led to up-regulation of fibroblast activation genes including ACTA2 and COL1A1, and an increase in HIO collagen content. ETYA pre-treatment prevented pro-fibrotic effects of LPS-primed macrophages. ConclusionsETYA inhibits pro-fibrotic effects of LPS-primed macrophages upon co-cultured HIO. This model may be used in future untargeted screens for small molecules to treat refractory CD.

molecular biology↗

bioRxiv2022

Achieving pan-microbiome biological insights via the dbBact knowledge base

16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying the microbial world. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when analyzing their findings and interpret them in a broader context. To bridge this gap, we introduce dbBact, an open wiki-like bacterial knowledge base. dbBact combines information from hundreds of studies across diverse habitats, creating a collaborative central repository where 16S rRNA amplicon sequence variants (ASVs) are manually extracted from each study and assigned multiple ontology-based terms. Using the >900 studies of dbBact, covering more than 1,400,000 associations between 345,000 ASVs and 6,500 ontology terms, we show how the dbBact statistical and programmatic pipeline can augment standard microbiome analysis. We use multiple examples to demonstrate how dbBact leads to formulating novel hypotheses regarding inter-host similarities, intra-host sources of bacteria, and commonalities across different diseases, and helps detect environmental sources and identify contaminants.

microbiology↗

bioRxiv2021

Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of ulcerative colitis (UC) patients require colectomy within five years of diagnosis, but polygenic risk scores (PRS) utilizing findings from GWAS are unable to provide meaningful prediction of this adverse status. By contrast, in Crohns disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a Transcriptional Risk Score (TRS). Here we demonstrate that both measured (TRS) and polygenic predicted gene expression (PPTRS) identify UC patients at 5-fold elevated risk of colectomy with data from the PROTECT clinical trial and UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with transcriptome-wide association studies to stratify risk of disease complications.

genetics↗