Biology subjects

Bhatt, N. P.

Publications and source records attributed to Bhatt, N. P..

3 recordsLinked to original sources

bioRxiv2026

Modeling and dissecting bidirectional feedback in gene-metabolite systems using the CausalFlux method

Predicting cellular behaviors, a central task in systems biology and metabolic engineering, can be enhanced through integrative modeling of processes such as gene regulation and metabolism. Information flow from gene regulation (modeled via a gene regulatory network) to metabolism (modeled via a genome-scale metabolic model) is well-studied, but the reciprocal regulation of genes by metabolites is less explored. We introduce CausalFlux, a method that models bidirectional feedback between genes and metabolites, in order to predict steady-state reaction fluxes under wild-type (WT) or perturbed (e.g., gene knockout/KO) conditions. CausalFlux does so by iteratively performing causal surgery on a Bayesian gene regulatory network and constraint-based analysis of a coupled metabolic model. CausalFlux enabled us to assess the impact of two-way feedback in several testbed models and real-world biological systems by comparing its predictions to those of TRIMER, a state-of-the-art model of gene-to-metabolite one-way feedback. Incorporating bidirectional feedback, as in CausalFlux, improved the Spearman correlation between actual and predicted fluxes in 92% of the 39 distinct simulation conditions relative to TRIMER. For predicting growth/no-growth phenotype following single-gene KOs in E. coli, CausalFlux achieved a balanced accuracy of 0.79 in identifying essential genes, and TRIMER achieved 0.71 for the same task, again highlighting the importance of modeling two-way feedback. In ablation studies that further dissect the role of specific metabolite[->]gene feedback edges in E. coli, the F1 scores of gene essentiality predictions decreased by 7.5% and 13% upon ablation of feedback edges from any metabolite to the crp gene and the 10 metabolic feedback genes with the highest influence on the KO genes, respectively. Finally, we highlight the application of CausalFlux to predict the essentiality of several hundred genes under different media conditions. Overall, our findings show that CausalFlux can crucially utilize information on feedback metabolites to predict trends in reaction fluxes and qualitative (growth/no-growth) outcomes; thereby encouraging future systems modeling efforts to carefully incorporate not only gene-to-metabolite but also metabolite-to-gene interactions. AvailabilityCode pertaining to the CausalFlux method, and its benchmarking and application is publicly available at: https://github.com/BIRDSgroup/CausalFlux. Author summaryThe myriad processes within a living cell, such as gene regulation or metabolism, are tightly interconnected. Modeling these interconnected processes can offer a deeper mechanistic understanding of cellular behaviors, as well as guide efforts that engineer the metabolic output of a cell. In this work, we develop a novel integrated model of gene regulation and metabolism that incorporates bidirectional feedback between these two processes, via the concept of metabolite-induced causal surgery on a gene regulatory network and gene-induced constraints on the fluxes of metabolic reactions. Our model, which we call CausalFlux, represents an advance over most existing models that capture just the one-way gene-to-metabolism feedback (i.e., genes coding for enzymes that control metabolic reactions). Our CausalFlux methodology opens up an unique opportunity to quantify the impact of two-way feedback in gene-metabolite systems, via comparison of CausalFluxs predictions to those of TRIMER, a published model incorporating one-way feedback alone. For predicting reaction fluxes in testbed models and essential genes in E. coli, quantitative comparison of the performance of CausalFlux vs. TRIMER showed that accounting for two-way feedback leads to more accurate and biologically meaningful predictions. CausalFlux also enabled us to quantify the effect of two-way feedback by comparing prediction performance before and after ablation of certain feedback edges from metabolites to genes. Overall, our findings highlight the importance of modeling gene regulation and metabolism as two-way interconnected systems within a living cell, and encourage future works to incorporate gene{leftrightarrow}metabolite feedback into their analyses.

systems biology↗

bioRxiv2026

Generation of a novel Slc7a9G105R mutant mouse identifies new biomarkers for cystinuria

Cystinuria is a rare inherited disease characterized by increased urinary cystine levels resulting in the formation of cystine stones in the urinary tract. Mutations in the genes encoding the cystine transporter complex, SLC3A1 and SLC7A9, are the primary drivers of the disease. Current mouse models used to study cystinuria rely on gene deficiency or spontaneous mutations in mice that do not accurately reflect the pathogenic mutations found in humans. To overcome this limitation, we generated novel Slc7a9G105R mice carrying the most common pathogenic single-point mutation in the SLC7A9 gene. Both male and female Slc7a9G105R mice developed a cystinuria phenotype by 9 weeks of age, characterized by substantial cystine stone formation and increased urinary cystine, lysine, arginine, and ornithine. Slc7a9G105R mice displayed distinct serum and urinary metabolite profiles mapped to dibasic amino acid pathways. Fecal metagenomics revealed that Slc7a9G105R mice had a heterogeneous microbiota with altered functional pathways, including increased L-cysteine biosynthesis. Depletion of the microbiota with antibiotics did not impact cystine stone burden but reduced urinary tract inflammation. Prophylactic or therapeutic dietary supplementation with alpha-lipoic acid reduced stone burden and inflammation, but it also caused damage to the urothelium. Untargeted metabolomics analysis following alpha-lipoic acid supplementation identified metabolites that can increase cystine solubility, reduce inflammation, and damage epithelial cells. Correlation analysis revealed novel serum biomarkers of stone burden, including blood urea nitrogen, 2-hydroxybutyric acid, 2-amino-2-thiazoline-4-carboxylic acid, and indole-3-acetylglycine. Collectively, the Slc7a9G105R mutant mouse model offers a precise, rapid-onset, and translational platform for investigating cystinuria pathogenesis and evaluating potential therapeutic strategies. Translational statementThe development of a novel knock-in mouse model carrying the most common pathogenic point mutation in the human SLC7A9 gene provides a clinically relevant and translationally valuable platform for investigating cystinuria pathogenesis and testing emerging therapies. This model represents the closest possible approximation of human SLC7A9-mediated cystinuria, enabling rigorous preclinical evaluation of small molecules and gene therapies. It has also facilitated the identification of candidate biomarkers for cystine stone burden and treatment response, which are urgently needed to improve disease monitoring and clinical decision-making. The next critical step is to validate these biomarkers in human cystinuria cohorts to support their clinical translation.

pathology↗

bioRxiv2020

Differences in pulmonary innate lymphoid cells are dependent on mouse age, sex and strain

Innate lymphoid cells (ILC) are resident in the lung and are involved in both the maintenance of homeostasis and the pathogenesis of respiratory diseases. In this study, murine lung ILC were characterised using flow cytometry and the impact of mouse age, sex and strain were assessed. Lung ILC were found as early as postnatal day 4 and numbers peaked at 2 weeks, and then decreased as the lung matured. During postnatal lung development, ILC expressed differential amounts of ILC2-associated cell surface antigens including ST2, CD90.2 and ICOS. Using Il5venusIl13td-tomato dual reporter mice, neonates were found to have increased constitutive IL-13 expression compared to adult mice. Neonates and adults had similar ratios of IL-5+CD45+ leukocytes, however, these cells were mostly composed of ILC in neonates and T cells in adults. Sex-specific differences in ILC numbers were also observed, with females having greater numbers of lung ILC than males in both neonatal and adult mice. Female lung ILC also expressed higher levels of ICOS and decreased KLRG1. Mouse strain also impacted on lung ILC with BALB/c mice having more ILC in the lung and increased expression of ST2 and ICOS compared with C57BL/6J mice. Collectively, these data show that lung ILC numbers, cell surface antigen expression, IL-5 and IL-13 levels differed between neonatal and adult lung ILC. Additionally, cell surface antigens commonly used for ILC2 quantification, such as ST2, CD90.2, and ICOS, differ depending on age, sex and strain and these are important considerations for consistent universal identification of lung ILC2.

immunology↗