Biology subjects

Zomorrodi, A. R.

Publications and source records attributed to Zomorrodi, A. R..

6 recordsLinked to original sources

bioRxiv2026

Long-Read Metagenomic Sequencing Reveals Persistent Gut Microbiome Alterations in Children with Celiac Disease in Remission

Background: Celiac Disease (CeD) is an immune-mediated enteropathy linked to gut microbiome dysbiosis driven by dietary gluten ingestion. Although most patients achieve clinical and histologic remission on a gluten-free diet (GFD), persistent symptoms and incomplete mucosal recovery are common. While gut microbiome alterations during active CeD are well documented, taxonomic and functional shifts during histologic remission remain considerably less characterized. Methods: We utilized PacBio's HiFi long-read metagenomic sequencing to profile the gut microbiome of 21 pediatric participants with histologically confirmed CeD remission on a GFD, active CeD, and non-CeD controls. Results: High-fidelity long reads enabled reconstruction of 857 high-quality metagenome-assembled genomes and high-resolution species- and pathway-level profiling. Microbial diversity analysis showed reduced alpha-diversity in remission patients compared with controls. Differential abundance analysis revealed persistent taxonomic and functional alterations in CeD remission, indicating incomplete restoration of microbiome homeostasis. Notably, remission patients showed depletion of commensals such as Alistipes finegoldii, Bifidobacterium longum, and Bacteroides uniformis, and persistence of some inflammation-associated taxa, alongside enrichment of beneficial species, including short-chain fatty acid producers, and suppression of other inflammation-associated taxa. At the functional level, pathways related to broader metabolic homeostasis were depleted in remission, while anti-inflammatory pathways such as propionate metabolism were enriched. Conclusions: Our findings suggest a distinct microbial ecosystem during histologic remission characterized by residual taxonomic dysbiosis and functional constraints, accompanied by adaptive remodeling that may promote mucosal healing. This work advances understanding of the gut microbiome in CeD after mucosal recovery and lays the groundwork for future studies of microbiome-based therapeutic interventions.

microbiology↗

bioRxiv2026

BiomeGPT: A foundation model for the human gut microbiome

The human gut microbiome encodes rich information about host health, yet current analysis pipelines remain narrowly optimized for individual tasks. This limits our ability to gain a thorough view of how the microbiome impacts health and disease. Here we introduce BiomeGPT, a transformer-based foundation model pretrained on over 13,300 human gut metagenomes spanning 32 phenotypes--including healthy and 31 diverse diseases--to learn context-aware, species-level gut microbiome representations. The model captures quantitative compositional structure and intricate cross-species dependencies embedded within community profiles. When fine-tuned for predicting host health status, BiomeGPT accurately distinguishes healthy from diseased microbiomes and resolves individual disease states across a broad clinical spectrum. Furthermore, its attention patterns reveal biologically plausible microbial signatures, highlighting both shared and disease-specific microbial species linked to host phenotypes. By providing a unified, scalable framework for species-level gut microbiome representation learning and prediction, BiomeGPT enables new avenues for biomarker discovery, disease stratification, and microbiome-driven precision medicine.

bioinformatics↗

bioRxiv2024

Unraveling the Link between Nutrition and Metabolic Syndrome Risk through In Silico Dietary Interventions

BackgroundMetabolic Syndrome (MetS) is a cluster of metabolic disorders that substantially increases the risk of chronic metabolic diseases. Diet is known to play a crucial role in the progression of MetS, yet a mechanistic understanding of its impact on MetS risk remains elusive. MethodsTo address this gap, we conducted a rigorous in silico diet intervention study by leveraging organ-resolved sex-specific whole-body models of metabolism. These models were utilized to computationally evaluate the effect of 12 diverse dietary regimens on key MetS biomarkers--glucose, triacylglycerol (TAG), LDL-C, and HDL-C--and fatty acid beta-oxidation in both males and females. ResultsOur analyses elucidated molecular mechanisms underlying the link between conventionally unhealthy diets and elevated MetS risk. Specifically, a typical Unhealthy diet indicated elevated TAG storage in the adipocytes and increased LDL-C to HDL-C ratios across both genders. Conversely, healthier dietary patterns like the Mediterranean and Vegan diets promoted favorable profiles for these biomarkers. Beyond substantiating these known dietary impacts, our analysis also revealed non-intuitive responses to diet. Notably, plant-based (Vegan and Vegetarian) diets induced elevated fatty acid oxidation compared to high-fat regimens like the Ketogenic diet, suggesting their potential in mitigating MetS risk. Pronounced gender differences in metabolic responses to diets were also observed, highlighting the need for gender-tailored dietary recommendations. Organ-specific dietary responses and their contributions to MetS biomarkers were also delineated, pinpointing the liver and lungs as major regulators of blood glucose homeostasis. ConclusionsThis study contributes to a deeper understanding of the intricate interactions between diet and MetS risk.

systems biology↗

bioRxiv2024

Investigating intestinal epithelium metabolic dysfunction in Celiac Disease using personalized genome scale models

Celiac Disease (CeD) is an autoimmune condition characterized by an aberrant immune response triggered by the ingestion of gluten, which damages epithelial cells lining the small intestine. Small intestinal epithelial cells (sIECs) play a key role in various metabolic processes, including the enzymatic digestion and absorption of nutrients. Although nutritional malabsorption is widely recognized in CeD, the underlying disrupted metabolic processes remain largely undefined. To address this knowledge gap, we constructed personalized gender-specific genome-scale models of sIEC metabolism using transcriptional data from 42 subjects with active CeD, remission CeD, and healthy controls. We computationally simulated these models under a relevant diet for each group of subjects to assess the activity of 59 metabolic tasks essential for sIEC function and to profile metabolite secretion into the bloodstream and intestinal lumen. These investigations revealed significant variations in the activity of 25 metabolic tasks in active and remission CeD models. These tasks impact critical processes integral to sIEC function such as amino acid metabolism, nucleotide synthesis and DNA repair, ATP generation, and oxidative stress regulation. Additionally, we identified 54 metabolites with altered secretion profiles in CeD, encompassing amino acids, vitamins, antioxidants, and fatty acids. Furthermore, we pinpointed 22 FDA-approved drugs that target the genes associated with differentially active metabolic functions whose altered activities adversely affect sIECs in CeD, potentially helping to restore their normal activity. Our study unveils new insights into the metabolic reprogramming of sIECs in CeD, paving the way for therapeutic interventions targeting dysregulated metabolic processes.

systems biology↗

bioRxiv2022

Computational design and construction of an Escherichia coli strain engineered to produce a non-standard amino acid

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para-aminophenylalanine (pAF) in Escherichia coli. First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism, and computationally identified metabolic interventions in the hosts native metabolism to improve pAF production. Next, we explored different ways of imposing these flux interventions experimentally and found that the upregulation of flux in chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers ([~]20 fold) while maintaining a reasonable pAF yield-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

systems biology↗

bioRxiv2017

Intracellular metabolic circuits shape inter-species microbial interactions

Metabolite exchanges in microbial communities give rise to ecological interaction networks that influence ecosystem diversity and stability1-6. These exchanges depend on complex intracellular pathways thus raising the question of whether ecological interactions are inferable from genomes. We address these questions by integrating genome-scale models of metabolism7, to compute the fitness of interacting microbes, with evolutionary game theory, which uses these fitness values to infer evolutionarily stable interactions in multi-species microbial \"games\". After validating our approach using data on sucrose hydrolysis by S. cerevisiae, we performed over 80,000 in silico experiments to evaluate the rise of unidirectional and cross-feeding metabolic dependencies in populations of Escherichia coli secreting 189 amino acid pairs. We found that, despite the diversity of exchanged amino acids, most pairs conform to general patterns of inter-species interactions. However, several amino acid pairs deviate from these patterns due to pleiotropy and epistasis in metabolic pathways. To better understand the emergence of cross-feeding, we performed in silico invasion experiments and found possible evolutionary paths that could lead to such association. Overall, our study provides mechanistic insights into the rise of evolutionarily stable interdependencies, with important implications for biomedicine and microbiome engineering 8-10.

systems biology↗