Biology subjects

Bararpour, N.

Publications and source records attributed to Bararpour, N..

5 recordsLinked to original sources

bioRxiv2026

Metabolomics identifies endocannabinoid system remodeling during obesity associated inflammation in adipose tissue

Visceral white adipose tissue (vAT) is more susceptible than subcutaneous white adipose tissue (scAT) to obesity-associated metaflammation, but the metabolic pathways accompanying this depot specific transition remain incompletely defined. We profiled vAT and scAT from mice fed a control diet or a 60% kcal high-fat diet (HFD) for 1 or 8 weeks. Untargeted metabolomics was integrated with targeted endocannabinoid quantification, gene expression and promoter associated chromatin analyses, adipocyte and stromal vascular fraction (SVF) measurements, cross-omics correlation analysis, and cell-culture perturbations. After 1 week, HFD induced relatively few metabolic changes, although vAT showed early alterations associated with sphingomyelin metabolism. By week 8, both depots exhibited extensive but distinct metabolic remodeling. The KEGG retrograde endocannabinoid-signaling pathway was the highest-ranked enriched pathway in vAT, with arachidonoylglycerol (2AG) among the most strongly altered metabolites. Targeted analysis confirmed selective 2AG accumulation in vAT, accompanied by coordinated changes in genes and promoter-associated chromatin marks related to endocannabinoid synthesis, degradation and receptor expression. Cellular fractionation localized excess 2AG predominantly to vAT adipocytes, whereas Cnr2 was enriched in the SVF and induced by HFD specifically in vAT. Cross omics integration further revealed a denser and predominantly inverse transcript metabolite association network in vAT than in scAT. Using macrophage adipocyte co-culture and secretome profiling, we demonstrated that cannabinoid stimulation shifts activated macrophage outputs away from pro-inflammatory cytokines (Il1b, Ccl2) toward extracellular matrix (ECM) proteoglycan remodeling and intercellular signaling.

molecular biology↗

bioRxiv2024

Gut microbiome shifts in chronic systolic heart failure are associated with disease severity and clinical improvement

Chronic systolic heart failure (HF) is a prevalent and morbid disease with marked variability in its progression and response to therapies. The gut microbiome may play a role in pathophysiology and progression of chronic HF, but clinical studies investigating relationships between the two are lacking. We analyzed the gut microbiome in a cohort of adults with chronic systolic HF caused by non-ischemic cardiomyopathy (n=59) using multi-omics profiling and, in some cases, longitudinal sampling. We identified microbiome differences compared to healthy subjects (n=50) and associated these differences with host metabolites, inflammatory markers and physiology. We found depletion of the anti-inflammatory probiotic Bifidobacterium and the associated short chain fatty acid producing and formaldehyde detoxifying pathways in the chronic HF cohort. We also discovered HF-specific microbiome-host immunome interactions. In addition to identifying several taxa and microbial pathways broadly associated with HF disease severity, we found significant links between Bifidobacterium and clinical HF improvement over time. Gut microbiome-host multi-omic data integration revealed a close association between Bifidobacterium and circulating metabolites previously implicated in cardiovascular physiology (e.g., malonic acid), thus pointing to potential mechanisms through which Bifidobacterium may affect chronic HF physiology. Our results suggest that Bifidobacterium may serve as a biomarker for chronic HF trajectory as well as suggest potential novel therapeutic interventions strategies.

microbiology↗

bioRxiv2022

Temporal dynamics of the multi-omic response to endurance exercise training across tissues

Regular exercise promotes whole-body health and prevents disease, yet the underlying molecular mechanisms throughout a whole organism are incompletely understood. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome, and immunome in whole blood, plasma, and 18 solid tissues in Rattus norvegicus over 8 weeks of endurance exercise training. The resulting data compendium encompasses 9466 assays across 19 tissues, 25 molecular platforms, and 4 training time points in young adult male and female rats. We identified thousands of shared and tissue- and sex-specific molecular alterations. Temporal multi-omic and multi-tissue analyses demonstrated distinct patterns of tissue remodeling, with widespread regulation of immune, metabolism, heat shock stress response, and mitochondrial pathways. These patterns provide biological insights into the adaptive responses to endurance training over time. For example, exercise training induced heart remodeling via altered activity of the Mef2 family of transcription factors and tyrosine kinases. Translational analyses revealed changes that are consistent with human endurance training data and negatively correlated with disease, including increased phospholipids and decreased triacylglycerols in the liver. Sex differences in training adaptation were widespread, including those in the brain, adrenal gland, lung, and adipose tissue. Integrative analyses generated novel hypotheses of disease relevance, including candidate mechanisms that link training adaptation to non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health, and tissue injury and recovery. The data and analysis results presented in this study will serve as valuable resources for the broader community and are provided in an easily accessible public repository (https://motrpac-data.org/). HighlightsO_LIMulti-tissue resource identifies 35,439 analytes regulated by endurance exercise training at 5% FDR across 211 combinations of tissues and molecular platforms. C_LIO_LIInterpretation of systemic and tissue-specific molecular adaptations produced hypotheses to help describe the health benefits induced by exercise. C_LIO_LIRobust sex-specific responses to endurance exercise training are observed across multiple organs at the molecular level. C_LIO_LIDeep multi-omic profiling of six tissues defines regulatory signals for tissue adaptation to endurance exercise training. C_LIO_LIAll data are available in a public repository, and processed data, analysis results, and code to reproduce major analyses are additionally available in convenient R packages. C_LI

molecular biology↗

bioRxiv2022

Ultra high-throughput whole-genome methylation sequencing reveals trajectories in precancerous polyps to early colorectal adenocarcinoma

Aberrant shifts in DNA methylation have long been regarded as an early marker for cancer onset and progression. To chart DNA methylation changes that occur during the transformation from normal healthy colon tissue to malignant colorectal cancer (CRC), we collected over 50 samples from 15 familial adenomatous polyposis (FAP) and non-FAP colorectal cancer patients, and generated 30-70x whole-genome methylation sequencing (WGMS) runs via the novel Ultima Genomics ultra high-throughput sequencing platform. We observed changes in DNA methylation that occur early in the malignant transformation process, in gene promoters and in distal regulatory elements. Among these changes are events of hyper-methylation which are associated with a bivalent "poised" chromatin state at promoters and are CRC-specific. Distal enhancers show nonlinear dynamics, lose methylation in the progression from normal mucosa to dysplastic polyps but regain methylation in the adenocarcinoma state. Enhancers that gain chromatin accessibility in the adenocarcinoma state and are enriched with HOX transcription factor binding sites, a marker of developmental genes. This work demonstrates the feasibility of generating large high quality WGMS data using the Ultima Genomics platform and provides the first detailed view of methylation dynamics during CRC formation and progression in a model case.

genomics↗

bioRxiv2020

Visualization and normalization of drift effect across batches in metabolome-wide association studies

As a powerful phenotyping technology, metabolomics provides new opportunities in biomarker discovery through metabolome-wide association studies (MWAS) and identification of metabolites having regulatory effect in various biological processes. While MS-based metabolomics assays are endowed with high-throughput and sensitivity, large-scale MWAS are doomed to long-term data acquisition generating an overtime-analytical signal drift that can hinder the uncovering of true biologically relevant changes. We developed "dbnorm", a package in R environment, which allows visualization and removal of signal heterogeneity from large metabolomics datasets. "dbnorm" integrates advanced statistical tools to inspect dataset structure, at both macroscopic (sample batch) and microscopic (metabolic features) scales. To compare model performance on data correction, "dbnorm" assigns a score, which allows the straightforward identification of the best fitting model for each dataset. Herein, we show how "dbnorm" efficiently removes signal drift among batches to capture the true biological heterogeneity of data in two large-scale metabolomics studies.

bioinformatics↗