Biology subjects

Sahoo, S.

Publications and source records attributed to Sahoo, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

KLF4 induces Mesenchymal-Epithelial Transition (MET) by suppressing multiple EMT-inducing transcription factors

Epithelial-Mesenchymal Plasticity (EMP) refers to reversible dynamic processes where cells can transition from epithelial to mesenchymal (EMT) or from mesenchymal to epithelial (MET) phenotypes. Both these processes are modulated by multiple transcription factors acting in concert. While EMT-inducing transcription factors (TFs) - TWIST1/2, ZEB1/2, SNAIL1/2/3, GSC, FOXC2 - are well-characterized, the MET-inducing TFs are relatively poorly understood (OVOL1/2, GRHL1/2). Here, using mechanism-based mathematical modeling, we show that the transcription factor KLF4 can delay the onset of EMT by suppressing multiple EMT-TFs. Our simulations suggest that KLF4 overexpression can promote phenotypic shift toward a more epithelial state, an observation suggested by negative correlation of KLF4 with EMT-TFs and with transcriptomic based EMT scoring metrics in cancer cell lines. We also show that the influence of KLF4 in modulating EMT dynamics can be strengthened by its ability to inhibit cell-state transitions at an epigenetic level. Thus, KLF4 can inhibit EMT through multiple parallel paths and can act as a putative MET-TF. KLF4 associates with patient survival metrics across multiple cancers in a context-specific manner, highlighting the complex association of EMP with patient survival.

cancer biology↗

bioRxiv2021

Immunosuppressive traits of the hybrid epithelial/mesenchymal phenotype

Recent preclinical and clinical data suggests enhanced metastatic fitness of hybrid epithelial/ mesenchymal (E/M) phenotypes, but mechanistic details regarding their survival strategies during metastasis remain unclear. Here, we investigate immune-evasive strategies of hybrid E/M states. We construct and simulate the dynamics of a minimalistic regulatory network encompassing the known associations among regulators of EMT (epithelial-mesenchymal transition) and PD-L1, an established immune-suppressor. Our model simulations, integrated with single-cell and bulk RNA-seq data analysis, elucidate that hybrid E/M cells can have high levels of PD-L1, similar to those seen in cells with a full EMT phenotype, thus obviating the need for cancer cells to undergo a full EMT to be immune-evasive. Specifically, in breast cancer, we show the co-existence of hybrid E/M phenotypes, enhanced resistance to anti-estrogen therapy and increased PD-L1 levels. Our results underscore how the emergent dynamics of interconnected regulatory networks can coordinate different axes of cellular fitness during metastasis.

cancer biology↗

bioRxiv2021

Zinc2+ ion inhibits SARS-CoV-2 main protease and viral replication in vitro.

Zinc deficiency is linked to poor prognosis in COVID-19 patients while clinical trials with Zinc demonstrate better clinical outcome. The molecular target and mechanistic details of anti-coronaviral activity of Zinc remain obscure. We show that ionic Zinc not only inhibits SARS-CoV-2 main protease (Mpro) with nanomolar affinity, but also viral replication. We present the first crystal structure of Mpro-Zn2+ complex at 1.9 [A] and provide the structural basis of viral replication inhibition. We show that Zn2+ coordinates with the catalytic dyad at the enzyme active site along with two previously unknown water molecules in a tetrahedral geometry to form a stable inhibited Mpro-Zn2+ complex. Further, natural ionophore quercetin increases the anti-viral potency of Zn2+. As the catalytic dyad is highly conserved across SARS-CoV, MERS-CoV and all variants of SARS-CoV-2, Zn2+ mediated inhibition of Mpro may have wider implications.

biochemistry↗

bioRxiv2021

Dynamics of a hepatocyte-cholangiocyte decision-making gene regulatory network during liver development and regeneration

Liver is one of the few organs with immense regenerative potential even at adulthood in mammals. It is composed of primarily two cell types: hepatocytes and cholangiocytes, that can trans-differentiate to one another either directly or through intermediate progenitor states, contributing to remarkable regenerative potential of the liver. However, the dynamical features of decision-making between these cell-fates during liver development and regeneration remains elusive. Here, we identify a core gene regulatory network comprising c/EBP, TGFBR2 and SOX9 that underlies liver development and injury-induced reprogramming. Dynamic simulations for this network reveal its multistable nature, enabling three distinct cell states - hepatocytes, cholangiocytes and liver progenitor cells (hepatoblasts/oval cells) - and stochastic switching among them. Predicted expression signature for these three states are validated through multiple bulk and single-cell transcriptomic datasets collected across developmental stages and injury-induced liver repair. This network can also explain the experimentally observed spatial organisation of phenotypes in liver parenchyma and predict strategies for efficient cellular reprogramming among these cell-fates. Our analysis elucidates how the emergent multistable dynamics of underlying gene regulatory networks drive diverse cell-state decisions in liver development and regeneration.

developmental biology↗

bioRxiv2021

A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells

Resistance to anti-estrogen therapy is an unsolved clinical challenge in successfully treating ER+ breast cancer patients. Acquisition of mutations can confer heritable resistance to cancer cells, enabling their clonal selection to establish a drug-resistant population. Recent studies have demonstrated that cells can tolerate drug treatment without any genetic alterations too; however, the mechanisms and dynamics of such non-genetic adaptation remain elusive. Here, we investigate coupled dynamics of epithelial-mesenchymal transition (EMT) in breast cancer cells and emergence of reversible drug resistance. Our mechanism-based model for the underlying regulatory network reveals that these two axes can drive one another, thus conferring bidirectional plasticity. This network can also enable non-genetic heterogeneity in a population of cells by allowing for six co-existing phenotypes: epithelial-sensitive, mesenchymal-resistant, hybrid E/M-sensitive, hybrid E/M-resistant, mesenchymal-sensitive and epithelial-resistant, with the first two ones being most dominant. Next, in a population dynamics framework, we exemplify the implications of phenotypic plasticity (both drug-induced and intrinsic stochastic switching) and/or non-genetic heterogeneity in promoting population survival in a mixture of sensitive and resistant cells, even in the absence of any cell-cell cooperation. Finally, we propose the potential therapeutic use of MET (mesenchymal-epithelial transition) inducers besides canonical anti-estrogen therapy to limit the emergence of reversible drug resistance. Our results offer mechanistic insights into empirical observations on EMT and drug resistance and illustrate how such dynamical insights can be exploited for better therapeutic designs.

cancer biology↗

bioRxiv2021

MITOCHONDRIAL GENOME REVEALS CONTRASTING PATTERN OF ADAPTIVE SELECTION IN TURTLES AND TORTOISES

Testudinoidea represents an evolutionarily unique taxon comprising both turtles and tortoises. The contrasting habitats that turtles and tortoises inhabit are associated with unique physio-ecological challenges hence enable distinct adaptive evolutionary strategies. To comparatively understand the pattern and strength of Darwinian selection and physicochemical evolution in turtle and tortoise mitogenomes, we employed adaptive divergence and selection analyses. We evaluated changes in structural and biochemical properties, and codon models on the mitochondrial protein-coding genes (PCGs) among three turtles and a tortoise lineage. We used mitochondrial PCGs that constitute the crucial oxidative phosphorylation (OXPHOS) respiratory system, a critical metabolic regulator which assumes key significance in energy regulation of ectotherms. We detected strong evidence of positive selection along the turtle lineages: Geoemydidae, Emydidae, and Platysternidae, but relatively weak signals in tortoises. The Platysternidae turtles revealed the highest gene and site-wise positive selection. In turtles, positively selected sites were prevalent in NAD2 and NAD4 genes in OXPHOS Complex I, and COB gene of Complex III, indicating convergent adaptive evolution. Besides, NAD3 was the only subunit that showed adaptive selection in both turtles and tortoises, expressing its relevance for all Testudinoidea. Structural and functional analysis revealed many sites and physiochemical changes in important conserved as well as biomedically significant regions, suggesting the influence of adaptive pressure on mitogenome functions. Hence, our study furnished novel evidence of contrasting evolutionary selective pressure acting on closely related groups such as turtles and tortoises with unique habitat preferences and associated eco-physiological challenges.

evolutionary biology↗

bioRxiv2021

Prioritizing and characterizing functionally relevant genes across human tissues

Knowledge of genes that are critical to a tissues function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model - FUGUE - combining transcriptional and network features, to predict tissue-relevant genes across 30 human tissues. FUGUE achieves an average cross-validation auROC of 0.86 and auPRC of 0.50 (expected 0.09). In three independent datasets, FUGUE accurately distinguishes tissue or cell type-specific genes, significantly outperforming the conventional metric based on tissue-specific expression alone. Comparison of tissue-relevant transcription factors across tissue recapitulate their developmental relationships. Interestingly, the tissue-relevant genes cluster on the genome within topologically associated domains and furthermore, are highly enriched for differentially expressed genes in the corresponding cancer type. We provide the prioritized gene lists in 30 human tissues and an open-source software to prioritize genes in a novel context given multi-sample transcriptomic data.

systems biology↗

bioRxiv2020

Hybrid E/M phenotype(s) and stemness: a mechanistic connection embedded in network topology

Metastasis remains an unsolved clinical challenge. Two crucial features of metastasizing cancer cells are a) their ability to dynamically move along the epithelial-hybrid-mesenchymal spectrum and b) their tumor-initiation potential or stemness. With increasing functional characterization of hybrid epithelial/mesenchymal (E/M) phenotypes along the spectrum, recent in vitro and in vivo studies have suggested an increasing association of hybrid E/M phenotypes with stemness. However, the mechanistic underpinnings enabling this association remain unclear. Here, we develop a mechanism-based mathematical modeling framework that interrogates the emergent nonlinear dynamics of the coupled network modules regulating E/M plasticity (miR-200/ZEB) and stemness (LIN28/let-7). Simulating the dynamics of this coupled network across a large ensemble of parameter sets, we observe that hybrid E/M phenotype(s) are more likely to acquire stemness relative to pure epithelial or mesenchymal states. We also integrate multiple phenotypic stability factors (PSFs) that have been shown to stabilize hybrid E/M phenotypes both in silico and in vitro - such as OVOL1/2, GRHL2, and NRF2 - with this network, and demonstrate that the enrichment of hybrid E/M phenotype(s) with stemness is largely conserved in the presence of these PSFs. Thus, our results offer mechanistic insights into recent experimental observations of hybrid E/M phenotype(s) being essential for tumor-initiation and highlight how this feature is embedded in the underlying topology of interconnected EMT and stemness networks.

cancer biology↗

bioRxiv2020

A computational systems biology approach identifies SLUG as a mediator of partial Epithelial-Mesenchymal Transition (EMT)

Epithelial-mesenchymal plasticity comprises of reversible transitions among epithelial, hybrid epithelial/mesenchymal (E/M) and mesenchymal phenotypes, and underlies various aspects of aggressive tumor progression such as metastasis, therapy resistance and immune evasion. The process of cells attaining one or more hybrid E/M phenotypes is termed as partial EMT. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either fully epithelial or mesenchymal state. Thus, identifying regulators of hybrid E/M phenotypes is essential to decipher the rheostats of phenotypic plasticity and consequent accelerators of metastasis. Here, using a computational systems biology approach, we demonstrate that SLUG (SNAIL2) - an EMT-inducing transcription factor - can inhibit cells from undergoing a complete EMT and thus stabilizing them in hybrid E/M phenotype(s). It expands the parametric range enabling the existence of a hybrid E/M phenotype, thereby behaving as a phenotypic stability factor (PSF). Our simulations suggest that this specific property of SLUG emerges from the topology of the regulatory network it forms with other key regulators of epithelial-mesenchymal plasticity. Clinical data suggests that SLUG associates with worse patient prognosis across multiple carcinomas. Together, our results indicate that SLUG can stabilize hybrid E/M phenotype(s).

cancer biology↗

bioRxiv2020

Complete mitogenome of Kashmir musk deer (Moschus cupreus) and its comparative phylogenetic relationships

The endangered Kashmir musk deer (Moschus cupreus) is native to the high altitudinal region of the Himalayas. In this study, we sequenced, annotated and characterized the complete mitogenome of M. cupreus to gain insight into the molecular phylogeny and evolution of musk deer. The mitogenome of M. cupreus, which is 16,354 bp long comprised 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs) and non-coding control region. The M. cupreus mitogenome composition was highly A+T biased 68.42%, and exhibited a positive AT skew (0.082) and negative GC skew (0.307). The phylogenetic analysis suggested that KMD is the most primitive extant species in the genus Moschus whereas Alpine musk deer (M. chrysogaster) and Himalayan musk deer (M. leucogaster) are closely related. This result confirmed the placement of M. cupreus within the monotypic family Moschidae of musk deer. This study provides a better understanding of lineage identification and musk deer evolution for further research.

genetics↗

bioRxiv2020

Genetic evidence indicates new distribution record of endangered Kashmir musk deer (Moschus cupreus) with range expansion in Uttarakhand, India

Kashmir musk deer, KMD (Moschus cupreus) is one the most threatened species reported from the Himalayan region of Kashmir, Pakistan and Afghanistan. A comprehensive and reliable distribution range of musk deer is still lacking. Recently, a molecular study confirmed the presence of KMD in Mustang in Nepal, west of Annapurna Himalayas. Here, we investigated the phylogenetic relationship of musk deer from Jammu and Kashmir (J&K), Kedarnath Wildlife Sanctuary (KWLS), and Nanda Devi Biosphere Reserve (NDBR), Uttarakhand region, India based on mitochondrial control region. The Bayesian phylogenetic analysis indicated a close genetic relationship between samples from J&K, KWLS and NDBR with identified lineages of KMD from Nepal with high posterior probabilities (PP[~]100). It confirmed that the musk deer lineage from the Uttarakhand region of KWLS (1025-3662 m) and NDBR (1800-7817 m) to be of KMD (M. cupreus) and hence a distinct Evolutionary Significant Unit (ESU). Besides, as per the IUCN database, the Western Himalayan region also holds the population of M. leucogaster and M. chrysogaster. Hence, we suggest extensive sampling for proper identification and validation of the geographic limits of musk deer species. We report for the first time the existence of KMD from the Uttarakhand region that we recommend to be updated in the IUCN database. It will assist in the effective conservation and management of this enigmatic endangered species.

genetics↗

bioRxiv2020

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

genomics↗

bioRxiv2020

Nanotrap(R) particles improve detection of SARS-CoV-2 for pooled sample methods, extraction-free saliva methods, and extraction-free medium methods

Here we present a rapid and versatile method for capturing and concentrating SARS-CoV-2 from transport medium and saliva using affinity-capture magnetic hydrogel particles. We demonstrate that the method concentrates virus prior to RNA extraction, thus significantly improving detection of the virus using a real-time RT-PCR assay across a range of viral titers, from 100 to 1,000,000 viral copies/mL; in particular, detection of virus in low viral load samples is enhanced when using the method coupled with the IDT 2019-nCoV CDC EUA Kit. This method is compatible with commercially available nucleic acid extraction kits, as well with a simple heat and detergent method. Using transport medium diagnostic remnant samples that previously had been tested for SARS-CoV-2 using either the Abbott RealTime SARS-CoV-2 EUA Test (n=14) or the Cepheid Xpert Xpress SARS-CoV-2 EUA Test (n=35), we demonstrate that our method not only correctly identifies all positive samples (n = 17) but also significantly improves detection of the virus in low viral load samples. The average improvement in cycle threshold (Ct) value as measured with the IDT 2019-nCoV CDC EUA Kit was 3.1; n = 10. Finally, to demonstrate that the method could potentially be used to enable pooled testing, we spiked infectious virus or a confirmed positive diagnostic remnant sample into 5 mL and 10 mL of negative transport medium and observed significant improvement in the detection of the virus from those larger sample volumes.

microbiology↗

bioRxiv2020

Mechanistic modeling of the SARS-CoV-2 and immune system interplay unravels design principles for diverse clinicopathological outcomes

The disease caused by SARS-CoV-2 is a global pandemic that threatens to bring long-term changes worldwide. Approximately 80% of infected patients are asymptomatic or have mild symptoms such as fever or cough, while rest of the patients have varying degrees of severity of symptoms, with 3-4% mortality rate. Severe symptoms such as pneumonia and Acute Respiratory Distress Syndrome can be caused by tissue damage mostly due to aggravated and unresolved innate and adaptive immune response, often resulting from a cytokine storm. However, the mechanistic underpinnings of such responses remain elusive, with an incomplete understanding of how an intricate interplay among infected cells and cells of innate and adaptive immune system can lead to such diverse clinicopathological outcomes. Here, we use a dynamical systems approach to dissect the emergent nonlinear intra-host dynamics among virally infected cells, the immune response to it and the consequent immunopathology. By mechanistic analysis of cell-cell interactions, we have identified key parameters affecting the diverse clinical phenotypes associated with COVID-19. This minimalistic yet rigorous model can explain the various phenotypes observed across the clinical spectrum of COVID-19, various co-morbidity risk factors such as age and obesity, and the effect of antiviral drugs on different phenotypes. It also reveals how a fine-tuned balance of infected cell killing and resolution of inflammation can lead to infection clearance, while disruptions can drive different severe phenotypes. These results will help further the case of rational selection of drug combinations that can effectively balance viral clearance and minimize tissue damage simultaneously. Significance StatementThe SARS-CoV-2 pandemic has already infected millions of people, and thousands of lives have been lost to it. The pandemic has already tested the limits of our public healthcare systems with a wide spectrum of clinicopathological symptoms and outcomes. The mechanistic underpinnings of the resultant immunopathology caused by the viral infection still remains to be elucidated. Here we propose a minimalistic but rigorous description of the interactions of the virus infected cells and the core components of the immune system that can potentially explain such diversity in the observed clinical outcomes. Our proposed framework could enable a platform to determine the efficacy of various treatment combinations and can contributes a conceptual understanding of dynamics of disease pathogenesis in SARS-CoV-2 infections.

systems biology↗

bioRxiv2020

Emergent properties of the HNF4α-PPARγ may drive consequent phenotypic plasticity in NAFLD

Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common form of chronic liver disease in adults and children. It is characterized by excessive accumulation of lipids in the hepatocytes of patients without any excess alcohol intake. With a global presence of 24% and limited therapeutic options, the disease burden of NAFLD is increasing. Thus, it becomes imperative to attempt to understand the dynamics of disease progression at a systems-level. Here, we decode the emergent dynamics of underlying gene regulatory networks that have been identified to drive the initiation and progression of NAFLD. We have developed a mathematical model to elucidate the dynamics of the HNF4-PPAR{gamma} gene regulatory network. Our simulations reveal that this network can enable multiple co-existing phenotypes under certain biological conditions: an adipocyte, a hepatocyte, and a "hybrid" adipocyte-like state of the hepatocyte. These phenotypes may also switch among each other, thus enabling phenotypic plasticity and consequently leading to simultaneous deregulation of the levels of molecules that maintain a hepatic identity and/or facilitate a partial or complete acquisition of adipocytic traits. These predicted trends are supported by the analysis of clinical data, further substantiating the putative role of phenotypic plasticity in driving NAFLD. Our results unravel how the emergent dynamics of underlying regulatory networks can promote phenotypic plasticity, thereby propelling the clinically observed changes in gene expression often associated with NAFLD.

systems biology↗

bioRxiv2019

Silver nanoparticle induced oxidative stress augments anticancer gut bacterial metabolites production

Colorectal cancer (CRC) is the fourth leading cause of mortality, world-wide. Gut bacterial dysbiosis being one of the major causes of CRC onset. Gut microbiota produced metabolites, e.g. folate and butyrate play crucial roles in cancer progression and treatment, and thus, need to be considered for effective CRC management. A potential cancer therapy, i.e., use of silver nanoparticles (AgNPs), imparts cytotoxic effects by inducing high intracellular reactive oxygen species (ROS) levels. However, the simultaneous interactions of AgNPs with gut microbiota to aid CRC treatment has not been reported thus far. Therefore, in this study, variation of intracellular ROS concentrations, in Enterococcus durans (E. durans), a representative gut microbe, was studied in the presence of low AgNP concentrations (25 ppm). Increases were observed in intracellular hydroxyl radical and extracellular folic acid concentrations by 48% and 52%, respectively, at the 9thhour of microbial growth. To gain a systems level understanding of ROS metabolism in E. durans, genome scale metabolic network reconstruction and modeling was adopted. In silico modeling reconfirmed the critical association between ROS and folate metabolism. Further, amino acids, energy metabolites, nucleotides, and butyrate were found to be important key players. Consequently, the anticancer effect of folic acid was experimentally studied on HCT116 (i.e., colon cancer cell line), wherein, its viability was reduced to 79% via folate present in the supernatants from AgNP treated E. durans cultures. Thus, we suggest that the inter-relationship between gut bacteria and AgNP-based cancer treatment can be used to design robust and effective cancer therapies.

systems biology↗

bioRxiv2019

Exosome-mediated MIR211 modulates tumor microenvironment via the DUSP6-ERK5 axis and contributes to BRAFV600E inhibitor resistance in melanoma.

The microRNA MIR211 is an important regulator of melanoma tumor cell behavior. Previous studies suggested that in certain tumors, MIR211 acted as a tumor suppressor while in others it behaved as an oncogenic regulator. When MIR211 is expressed in BRAFV600E-mutant A375 melanoma cells in mouse xenografts, it promotes aggressive tumor growth accompanied by increased cellular proliferation and angiogenesis. We demonstrate that MIR211 is transferred to adjacent cells in the tumor micro-environment via exosomes. Cross-species genome-wide transcriptomic analysis showed that human tumor-derived MIR211 interacts with the mouse transcriptome in the tumor microenvironment, and activates ERK5 signaling in human tumor cells via the modulation of a feedback loop. Human miR211 directly inhibits human DUSP6 protein phosphatase at the post-transcriptional level. We provide support for the hypothesis that DUSP6 inhibition conferred resistance of the human tumor cells to the BRAF inhibitor vemurafenib and to the MEK inhibitor cobimetinib, with associated increases in ERK5 phosphorylation. These findings are consistent with a model in which MIR211 regulates melanoma tumor proliferation and BRAF inhibitor resistance by inducing ERK5 signaling within the complex tumor microenvironment. We propose that the MIR211-ERK5 axis represents an important and sensitive regulatory arm in melanoma with potential theranostic applications.

cancer biology↗

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↗