Characterisation of Indian gut microbiome for B-vitamin production and its comparison with Chinese cohort.

The human gut microbiota can biosynthesize essential micronutrients such as B-vitamins and is also known for its metabolic cooperative behaviour. The present study characterises such B-vitamin biosynthesizers, their biosynthetic pathways, explores their prevalence and abundance, examines how lifestyle or diet affects them in multiple Indian cohorts and compares it with the Chinese cohort. To achieve this, publicly available faecal metagenome data of healthy individuals from multiple Indian (two urban and three tribal populations) and a Chinese cohort were analysed. The distribution of prevalence and abundance of B-vitamin biosynthesizers showed similar profiles to that of the entire gut community of the Indian cohort, and there were 28 B-vitamin biosynthesizers that had modest or higher prevalence and abundance. The omnivorous diet affected only the prevalence of a few B-vitamin biosynthesizers; however, lifestyle and/or location affected both prevalence and abundance. A comparison with the Chinese cohort showed that fourteen B-vitamin biosynthesizers were significantly more prevalent and abundant in Chinese as compared with Indian samples (False Discovery Rate (FDR) <= 0·05). The metabolic potential of the entire gut community for B-vitamin production showed that within India, the tribal cohort has a higher abundance of B-vitamin biosynthesis pathways as compared with two urban cohorts namely, Bhopal and Kasargod, and comparison with the Chinese cohort revealed a higher abundance in the latter group. Potential metabolic cooperative behaviour of the Indian gut microbiome for biosynthesis of the B-vitamins showed multiple pairs of species showed theoretical complementarity for complete biosynthetic pathways genes of thiamine, riboflavin, niacin and pantothenate.

Physiological significance of bistable circuit design in metabolic homeostasis: role of integrated insulin-glucagon signalling network.

BACKGROUND: Insulin and glucagon signalling pathways operate in a synchronised manner to regulate metabolic homeostasis in different physiological conditions (like postprandial, fasting & exercise). Non-linear positive feedback loops involving effector molecules such as AKT and PKA in anabolic and catabolic signalling modules have a key role in eliciting bistable response in these networks. METHODS: We have reviewed literature on insulin and glucagon signaling pathways in metabolic regulation along with the relevance of bistability in homeostasis. An ODE-based integrated signalling network model is used to simulate insulin and glucagon resistance conditions. Modifications in homeostatic to anabolic and catabolic switch activation thresholds are analyzed, indicating the effectiveness of insulin and glucagon signalling pathways in normal and diseased conditions. RESULTS: Perturbation analysis of the kinetic model provides valuable insights on bistability and its characterization with respect to endocrine inputs. Disturbance in bistability is linked with dysregulation of plasma macronutrient levels (glucose, fatty acids and amino acids) in abnormal conditions like insulin and glucagon resistance, which is associated with obesity, type 2 diabetes mellitus and non-alcoholic fatty liver disease. CONCLUSIONS: This article highlights the role of Systems biology approach in explaining plausible mechanisms underlying metabolic abnormalities. It captures essential crosstalk and feedback mechanisms that play a key role in inducing bistable response in a variety of physiological situations, as well as hints at how to reverse insulin and glucagon resistance.

Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.

Role of enhanced glucocorticoid receptor sensitivity in inflammation in PTSD: insights from computational model for circadian-neuroendocrine-immune interactions.

Although glucocorticoid resistance contributes to increased inflammation, individuals with posttraumatic stress disorder (PTSD) exhibit increased glucocorticoid receptor (GR) sensitivity along with increased inflammation. It is not clear how inflammation coexists with a hyperresponsive hypothalamic-pituitary-adrenal (HPA) axis. To understand this better, we developed and analyzed an integrated mathematical model for the HPA axis and the immune system. We performed mathematical simulations for a dexamethasone (DEX) suppression test and IC50-dexamethasone for cytokine suppression by varying model parameters. The model analysis suggests that increasing the steepness of the dose-response curve for GR activity may reduce anti-inflammatory effects of GRs at the ambient glucocorticoid levels, thereby increasing proinflammatory response. The adaptive response of proinflammatory cytokine-mediated stimulatory effects on the HPA axis is reduced due to dominance of the GR-mediated negative feedback on the HPA axis. To verify these hypotheses, we analyzed the clinical data on neuroendocrine variables and cytokines obtained from war-zone veterans with and without PTSD. We observed significant group differences for cortisol and ACTH suppression tests, proinflammatory cytokines TNFα and IL6, high-sensitivity C-reactive protein, promoter methylation of GR gene, and IC50-DEX for lysozyme suppression. Causal inference modeling revealed significant associations between cortisol suppression and post-DEX cortisol decline, promoter methylation of human GR gene exon 1F (NR3C1-1F), IC50-DEX, and proinflammatory cytokines. We noted significant mediation effects of NR3C1-1F promoter methylation on inflammatory cytokines through changes in GR sensitivity. Our findings suggest that increased GR sensitivity may contribute to increased inflammation; therefore, interventions to restore GR sensitivity may normalize inflammation in PTSD.

Mechanistic inferences on metabolic dysfunction in posttraumatic stress disorder from an integrated model and multiomic analysis: role of glucocorticoid receptor sensitivity.

Posttraumatic stress disorder (PTSD) is associated with neuroendocrine alterations and metabolic abnormalities; however, how metabolism is affected by neuroendocrine disturbances is unclear. The data from combat-exposed veterans with PTSD show increased glycolysis to lactate flux, reduced TCA cycle flux, impaired amino acid and lipid metabolism, insulin resistance, inflammation, and hypersensitive hypothalamic-pituitary-adrenal (HPA) axis. To analyze whether the co-occurrence of multiple metabolic abnormalities is independent or arises from an underlying regulatory defect, we employed a systems biological approach using an integrated mathematical model and multiomic analysis. The models for hepatic metabolism, HPA axis, inflammation, and regulatory signaling were integrated to perform metabolic control analysis (MCA) with respect to the observations from our clinical data. We combined the metabolomics, neuroendocrine, clinical laboratory, and cytokine data from combat-exposed veterans with and without PTSD to characterize the differences in regulatory effects. MCA revealed mechanistic association of the HPA axis and inflammation with metabolic dysfunction consistent with PTSD. This was supported by the data using correlational and causal analysis that revealed significant associations between cortisol suppression, high-sensitivity C-reactive protein, homeostatic model assessment of insulin resistance, γ-glutamyltransferase, hypoxanthine, and several metabolites. Causal mediation analysis indicates that the effects of enhanced glucocorticoid receptor sensitivity (GRS) on glycolytic pathway, gluconeogenic and branched-chain amino acids, triglycerides, and hepatic function are jointly mediated by inflammation, insulin resistance, oxidative stress, and energy deficit. Our analysis suggests that the interventions to normalize GRS and inflammation may help to manage features of metabolic dysfunction in PTSD.

A methodological analysis of CTRI registered clinical trials on ayurveda interventions for COVID-19 management.

BACKGROUND: Clinical trial protocols provide important methodological information and are expected to be detailed. During COVID-19 pandemic several studies has been registered on CTRI regarding ayurveda for COVID-19. However, there is accumulating evidence that many protocols do not address important study elements. Therefore it is critical to analyze the clinical trial protocols and methodology of ayurveda clinical trials regarding COVID-19 registered on CTRI. OBJECTIVE: To assess the methodological aspects of CTRI registered ayurveda trial for COVID-19, based upon available trial protocols, during 2020 and 2021. MATERIALS AND METHODS: We searched the CTRI database for interventional trials protocols regarding ayurveda for COVID-19, during the year 2020 and 2021. We assessed the protocols for several methodological aspects such as study design, sample size, randomization, blinding, intervention (duration and type) and outcomes. RESULTS: Total 140 clinical trial protocols were analyzed. The highest numbers of studies were registered in May, June, and July 2020 with steady decline thereafter despite rising COVID-19 cases. Total 90 trials were randomized and only 29 are blinded, however majority of the trials did not mention methods of randomization and blinding. Sample size in hospital-based studies ranged from 30 -500 and in community-based studies from 500-80000, however, sample size calculation details were not mentioned in the protocol. Most common intervention used were guduchi, ashwagandha, yashtimadhu, AYUSH-64, curcumin and chyavanprash. CONCLUSION: Although there was a surge of clinical trials on CTRI regarding ayurveda for COVID -19, the methodological quality is not up to the mark with large scope for improvement.

Global Transcriptional Regulators Fine-Tune the Translational and Metabolic Efficiency for Optimal Growth of Escherichia coli.

Global transcriptional regulators coordinate complex genetic interactions that bestow better adaptability for an organism against external and internal perturbations. These transcriptional regulators are known to control an enormous array of genes with diverse functionalities. However, regulator-driven molecular mechanisms that underpin precisely tuned translational and metabolic processes conducive for rapid exponential growth remain obscure. Here, we comprehensively reveal the fundamental role of global transcriptional regulators FNR, ArcA, and IHF in sustaining translational and metabolic efficiency under glucose fermentative conditions in Escherichia coli By integrating high-throughput gene expression profiles and absolute intracellular metabolite concentrations, we illustrate that these regulators are crucial in maintaining nitrogen homeostasis, govern expression of otherwise unnecessary or hedging genes, and exert tight control on metabolic bottleneck steps. Furthermore, we characterize changes in expression and activity profiles of other coregulators associated with these dysregulated metabolic pathways, determining the regulatory interactions within the transcriptional regulatory network. Such systematic findings emphasize their importance in optimizing the proteome allocation toward metabolic enzymes as well as ribosomes, facilitating condition-specific phenotypic outcomes. Consequentially, we reveal that disruption of this inherent trade-off between ribosome and metabolic proteome economy due to the loss of regulators resulted in lowered growth rates. Moreover, our findings reinforce that the accumulations of intracellular metabolites in the event of proteome repartitions negatively affects the glucose uptake. Overall, by extending the three-partition proteome allocation theory concordant with multi-omics measurements, we elucidate the physiological consequences of loss of global regulators on central carbon metabolism restraining the organism to attain maximal biomass synthesis.IMPORTANCE Cellular proteome allocation in response to environmental or internal perturbations governs their eventual phenotypic outcome. This entails striking an effective balance between amino acid biosynthesis by metabolic proteins and its consumption by ribosomes. However, the global transcriptional regulator-driven molecular mechanisms that underpin their coordination remains unexplored. Here, we emphasize that global transcriptional regulators, known to control expression of a myriad of genes, are fundamental for precisely tuning the translational and metabolic efficiencies that define the growth optimality. Towards this, we systematically characterized the single deletion effect of FNR, ArcA, and IHF regulators of Escherichia coli on exponential growth under anaerobic glucose fermentative conditions. Their absence disrupts the stringency of proteome allocation, which manifests as impairment in key metabolic processes and an accumulation of intracellular metabolites. Furthermore, by incorporating an extension to the empirical growth laws, we quantitatively demonstrate the general design principles underlying the existence of these regulators in E. coli.

Computational Analysis of Insulin-Glucagon Signalling Network: Implications of Bistability to Metabolic Homeostasis and Disease states.

Insulin and glucagon control plasma macronutrient homeostasis through their signalling network composed of multiple feedback and crosstalk interactions. To understand how these interactions contribute to metabolic homeostasis and disease states, we analysed the steady state response of metabolic regulation (catabolic or anabolic) with respect to structural and input perturbations in the integrated signalling network, for varying levels of plasma glucose. Structural perturbations revealed: the positive feedback of AKT on IRS is responsible for the bistability in anabolic zone (glucose >5.5 mmol); the positive feedback of calcium on cAMP is responsible for ensuring ultrasensitive response in catabolic zone (glucose <4.5 mmol); the crosstalk between AKT and PDE3 is responsible for efficient catabolic response under low glucose condition; the crosstalk between DAG and PKC regulates the span of anabolic bistable region with respect to plasma glucose levels. The macronutrient perturbations revealed: varying plasma amino acids and fatty acids from normal to high levels gradually shifted the bistable response towards higher glucose range, eventually making the response catabolic or unresponsive to increasing glucose levels. The analysis reveals that certain macronutrient composition may be more conducive to homeostasis than others. The network perturbations that may contribute to disease states such as diabetes, obesity and cancer are discussed.

Implementation of integral feedback control in biological systems.

Integral control design ensures that a key variable in a system is tightly maintained within acceptable levels. This approach has been widely used in engineering systems to ensure offset free operation in the presence of perturbations. Several biological systems employ such an integral control design to regulate cellular processes. An integral control design motif requires a negative feedback and an integrating process in the network loop. This review describes several biological systems, ranging from bacteria to higher organisms in which the presence of integral control principle has been hypothesized. The review highlights that in addition to the negative feedback, occurrence of zero-order kinetics in the process is a key element to realize the integral control strategy. Although the integral control motif is common to these systems, the mechanisms involved in achieving it are highly specific and can be incorporated at the level of signaling, metabolism, or at the phenotypic levels.