Biology subjects

Sahoo, S.

Publications and source records attributed to Sahoo, S..

4 recordsLinked to original sources

bioRxiv2018

Computational framework for exploring the interplay of diet and gut microbiota in autism

Autism spectrum disorder (ASD)1 refers to the set of complex neurological disorders characterized by repetitive behaviour. The reported occurrence of abnormal gut bacteria, along with prevalence of gastrointestinal disorders in ASD indicate its strong correlation with the gut microflora. Our study aims to understand the role of diet and gut bacteria in ASD via an integrated constraint-based and PBPK model. Genome scale models of five major gut bacteria, which were reported to be associated with ASD, were integrated with the human host, i.e., the combined small intestinal enterocyte and neuronal brain model. Simultaneously, a permeability-limited two sub compartment PBPK model was developed to determine the distribution of bacteria-derived toxins in the body. The important results include, (i) inclusion of probiotics into the diet of autistic case restores gut balance, majorly seen as a result of reduced oxidative stress in the brain and the gut, (ii) microbiome and diet together mediate host metabolism in autism, majorly via the nucleotide, central carbon, amino acid, and reactive oxygen species metabolisms, and (iii) gut bacterial-specific secretions contribute to autistic metabotype. Thus, the presented integrated model is the first ever quantitative model, providing a mechanistic basis for autism pathogenesis, capturing known biomarkers, as well as, highlighting the potential of novel dietary modifications in alleviating the symptoms of autism.

systems biology↗

bioRxiv2018

The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

A multitude of factors contribute to complex diseases and can be measured with \"omics\" methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, http://vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources \"Human metabolism\", \"Gut microbiome\", \"Disease\", \"Nutrition\", and \"ReconMaps\". The VMH captures 5,180 unique metabolites, 17,730 unique reactions, 3,288 human genes, 255 Mendelian diseases, 818 microbes, 632,685 microbial genes, and 8,790 food items. The VMHs unique features are i) the hosting the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; ii) seven human metabolic maps for data visualization; iii) a nutrition designer; iv) a user-friendly webpage and application-programming interface to access its content; and v) user feedback option for community engagement. We demonstrate with four examples the VMHs utility. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

systems biology↗

bioRxiv2018

When metabolism meets physiology: Harvey and Harvetta

Precision medicine is an emerging paradigm that requires realistic, mechanistic models capturing the complexity of the human body. We present two comprehensive molecular to physiological-level, gender-specific whole-body metabolism (WBM) reconstructions, named Harvey, in recognition of William Harvey, and Harvetta. These validated, knowledge-based WBM reconstructions capture the metabolism of 20 organs, six sex organs, six blood cells, the gastrointestinal lumen, systemic blood circulation, and the blood-brain barrier. They represent 99% of the human body weight, when excluding the weight of the skeleton. Harvey and Harvetta can be parameterized based on physiological, dietary, and omics data. They correctly predict inter-organ metabolic cycles, basal metabolic rates, and energy use. We demonstrate the integration of microbiome data thereby allowing the assessment of individual-specific, organ-level modulation of host metabolism by the gut microbiota. The WBM reconstructions and the individual organ reconstructions are available under http://vmh.life. Harvey and Harvetta represent a pivotal step towards virtual physiological humans.

systems biology↗

bioRxiv2018

Signaling pathway screening platforms are an efficient approach toidentify therapeutic targets in precision-medicine oriented early phaseclinical trials

Precision medicine aims to tailor cancer therapies to target specific tumorpromoting aberrations. For tumors that lack actionable drivers, extensive molecular characterization and pre-clinical drug efficacy studies will be required to match patients with the appropriate targeted therapy. A cell line maintained at low passage and a patient-derived xenograft model (PDX) were generated using a fresh biopsy from a patient with a poorly-differentiated neuroendocrine tumor of unknown primary origin. Next-generation sequencing, high throughput signaling network analysis, and drug efficacy trials were then conducted to identify actionable targets for therapeutic intervention. No actionable mutations were identified after whole exome sequencing of the patients DNA; however, whole genome sequencing revealed amplification of the 3q and 5p chromosomal arms, that include the PIK3CA and RICTOR genes, respectively. Consistent with amplification of these genes, pathway analysis revealed activation of the AKT pathway. Based on this analysis, efficacy of PIK3CA and AKT inhibitors were evaluated in the tumor biopsy-derived cell culture and PDX, and response to the AKT inhibitor AZD5363 was observed both in vitro and in vivo indicating the patient would benefit from targeted therapies directed against the serine/threonine kinase AKT. In conclusion, our study demonstrates that high throughput signaling pathway analysis complements next-generation sequencing approaches for detection of actionable alterations and will aid in patient stratification into early-phase clinical trials.

clinical trials↗