Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses both lean and obese phenotypes with variable progression to metabolic dysfunction-associated steatohepatitis (MASH), yet the metabolic determinants of this divergence under identical dietary exposure remain unclear. Here, genetically identical male C57BL/6J mice were fed a high-fat diet (HFD) enriched in fructose, palmitate, and cholesterol for 27 weeks, resulting in two distinct phenotypes: responders and mild responders. Responders exhibited increased liver and visceral adipose indices, hypertriglyceridemia, and right-lobe-predominant steatohepatitis with pronounced collagen deposition, accompanied by upregulation of pro-fibrotic (COL1A1, ACTA2) and proinflammatory (TNF-α, TGF-β) genes, whereas mild responders showed attenuated fibrosis and preserved IL-10 expression despite elevated hepatic triglycerides. Metabolomic profiling of serum and cecal samples identified "candidate circulatory" metabolites, and principal component analysis of these features revealed clear separation of all three cohorts, supporting metabolically distinct, nonprogressive trajectories. A cosine similarity-based angular criterion in PCA was applied to identify metabolites associated with each phenotype. Comprehensive metabolomics, coupled with pathway and functional network analyses, revealed different metabolic remodeling between phenotypes. Responders were enriched in cholesterol and bile acid metabolism, with metabolites linked to fibrogenesis and mitochondrial dysfunction, consistent with severe dietary lipotoxicity. In contrast, mild responders exhibited coordinated perturbations in glycerophospholipid, tyrosine, and gluconeogenic pathways, with corticosterone-centered network features suggestive of a compensatory metabolic adaptation rather than overt lipotoxicity. Collectively, these findings suggest that identical HFDs can lead to divergent lean and obese MASH phenotypes, highlighting candidate biomarkers that may support future stratification of MASLD and inform precision nutrition strategies.

Metabolic-dysfunction-associated steatotic liver disease (MASLD) is typically attributed to caloric overload, lipotoxicity, and static gut dysbiosis, but how chronic diet alters the temporal organization of gut-liver communication remains unclear. We combined a phase-stratified multiomics framework, cecal 16S rRNA profiling, dual-compartment (cecum and serum) metabolomics, and hepatic clock and lipogenic gene expression in C57BL/6J male mice fed a high-fat, palmitate, and cholesterol-enriched (FPC) diet containing high sucrose for 22 wk. FPC feeding was associated with severe MASLD and markedly attenuated homeostatic phase-dependent differences in hepatic clock and lipogenic transcripts, consistent with a persistently lipogenic transcriptional state across the light-dark cycle. This temporal disruption coincided with reduced phase-structured ecological organization in the cecal microbiome and the emergence of a constrained, dysbiotic community dominated by a few taxa. Dual-compartment metabolomics revealed that despite retaining overall phase structure, local (cecal) and systemic (serum) metabolite pools showed misalignment: proinflammatory and bile acid species showed exaggerated luminal variations but flattened, persistently elevated profiles in serum. High-stringency covariance network analysis identified diet-associated differences in microbiome-metabolome covariance patterns. These findings are consistent with a model in which diet-induced MASLD is associated with altered spatial and phase-dependent coordination across microbiome-host metabolic and transcriptional networks, suggesting disruption of integrated microbiome-host organization beyond static dysbiosis and lipotoxic stress.NEW & NOTEWORTHY Using a phase-stratified multiomics framework in a murine MASLD model, we show that chronic FPC feeding is associated with altered temporal coordination between the gut and liver, beyond compositional dysbiosis. FPC reduces phase-dependent differences in hepatic clock and lipogenic gene expression, attenuates microbiome phase organization, and is associated with misaligned cecal and systemic metabolite profiles. Covariance networks reveal alteration of microbiome-metabolome-transcriptional connectivity, implicating disruption of phase-dependent gut-liver integration as an underappreciated axis of MASLD pathogenesis.

The gut microbiome shapes systemic physiology through metabolites that enter circulation, yet most computational approaches focus on predicting metabolite profiles from microbial features rather than inferring microbial composition from host metabolomes. Here, we investigate whether host-derived metabolomic profiles can be leveraged to predict gut microbial community structure and to determine how disease-associated dysbiosis reshapes metabolite-microbe interactions and gut-to-systemic metabolic communication. We developed an integrative multi-omics framework combining serum and cecal metabolomics with 16S rRNA-based microbiome profiling. Supervised learning models demonstrated that cecal metabolites carry predictive signals for microbial abundances across conditions. Regularized canonical correlation analysis (rCCA) revealed cross-compartment metabolite-microbe networks. These analyses showed both conserved and condition-specific interaction patterns, indicating substantial network reorganization under disease-associated dysbiosis. Pathway-level integration further identified metabolic pathways linking the gut microbiome, the cecal environment, and the systemic circulation, representing coordinated gut-to-systemic communication axes. Together, our results establish a multi-omics strategy for predictive inference of gut microbial composition from host metabolomes and provide a framework for identifying pathway-level mechanisms underlying host-microbe metabolic crosstalk.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by dopaminergic neuronal loss, motor deficits, and systemic metabolic dysfunction. Using a chronic MPTP-induced C57BL/6 mouse model, we integrated behavioral, transcriptional, metabolomic, and microbiome analyses to investigate gut-metabolite-brain interactions in PD. MPTP-treated mice exhibited significant motor and non-motor impairments alongside increased α-synuclein and inflammatory markers in the midbrain. Untargeted LC-MS metabolomics revealed differential enrichment of host- and microbiome-derived metabolites, including altered arginine/proline, sphingolipid, tryptophan, and riboflavin metabolism. 16S rRNA sequencing demonstrated decreased Firmicutes/Bacteroidetes ratio and enrichment of lipopolysaccharide-producing taxa, functionally linked to amino-acid metabolism via correlation network analysis. These data define a coordinated gut-metabolite-brain axis underpinning PD pathology, highlighting microbiome-derived circulating metabolites as potential early biomarkers and therapeutic targets. While these findings are derived from a toxin-based, male-only PD model, they delineate robust gut-metabolite-brain signatures that provide a strong framework for future validation in α-synucleinopathy models and mixed-sex cohorts.

Type 2 diabetes (T2D), inflammatory bowel disease (IBD), and colorectal cancer (CRC) share overlapping metabolic alterations that hinder early, disease-specific diagnosis. Using publicly available serum metabolomics data sets (T2D: ST003390; IBD: ST003312; CRC: ST000284), a standardized workflow combining random forest-based imputation, log transformation, Pareto scaling, and ComBat batch correction was implemented prior to supervised machine learning. Eight algorithms (logistic regression, linear and RBF SVM, random forest, XGBoost, k-nearest neighbors, multilayer perceptron, and partial least-squares-discriminant analysis) were benchmarked for binary and multiclass classification using stratified 5-fold cross-validation, F1-scores, and bootstrapped ROC-AUC estimates. Binary models yielded near-perfect discrimination for T2D (AUC ≈ 1.0) and high accuracy for IBD and CRC (AUC 0.93-0.95), while multilayer perceptron and partial least-squares-discriminant analysis achieved multiclass accuracy >0.9 and macro-AUC 0.98. Mapping discriminative metabolites to KEGG pathways revealed disease-linked signatures, including glucose and lipid metabolism in T2D, amino acid and porphyrin metabolism in IBD, and nucleotide and sphingolipid metabolism in CRC, supporting proteome-metabolome network perturbations. The current comparative machine learning framework of serum metabolome demonstrates a robust, though variable, multidisease classification performance across conditions (T2D, IBD, and CRC) used in this study. This strategy has the potential to provide interpretable pathway-level markers that may inform future proteome- and metabolome-centered diagnostic strategies.

Purpose Antibiotics are frequently prescribed during active inflammatory bowel disease (IBD) flares, yet how simultaneous microbial depletion and epithelial injury interact in different immune backgrounds remains unclear. To determine how Th1- versus Th2-biased immunity shapes gut barrier integrity, cytokine architecture, microbiota composition, and metabolic circuits under direct, indirect, and combined gut perturbations. Methods Male C57BL/6 and BALB/c mice received a nine-antibiotic cocktail (9AB), dextran sulfate sodium (DSS), or single, sequential, and concurrent 9AB–DSS regimens. Colitis severity, barrier function, and inflammation were assessed. Cecal microbiota, untargeted metabolomics, and phase-plane analysis of pro- versus anti-inflammatory metabolites were integrated. Results 9AB alone spared the epithelium, whereas DSS induced severe mucosal injury in both strains. Sequential 9AB–DSS regimens attenuated histological damage compared with concurrent treatment, but full barrier restitution after drug withdrawal occurred predominantly in BALB/c mice. In C57BL/6 mice, IL-1β emerged as the dominant mucosal cytokine, coinciding with Proteobacteria expansion and loss of microbial evenness under antibiotic-containing regimens. Metabolomics revealed a Th1-specific arachidonic acid, histidine, and thiamine axis that enriched under combined perturbations. In contrast, BALB/c mice preferentially activated tryptophan, biotin, and glycerophospholipid pathways that supported anti-inflammatory metabolite dominance with phase-plane trajectories returning toward an anti-inflammatory steady state during recovery. Conclusions Host immune bias determines whether combined microbial depletion and epithelial injury drive IL 1β-centred metabolic amplification of inflammation or coordinated mucosal recovery. The arachidonic–histidine–thiamine circuit in Th1-biased hosts and the tryptophan–biotin–glycerophospholipid circuit in Th2-biased hosts represent candidate targets for immune endotype-tailored therapeutic strategies in IBD.

In the era of Genome-Wide Association Studies (GWAS), biologists have unprecedented access to vast datasets, mirrored in the wealth of information from various omics studies, including genomics, transcriptomics, proteomics, metabolomics, and metagenomics. Integrating diverse data sources has emerged as crucial in unravelling the intricacies of biological processes. This chapter delves into our method for merging various omics methodologies, emphasizing metabolomics and metagenomics data. A powerful strategy addresses data processing challenges and opens new avenues for personalized microbiome-based interventions. The combined analysis of host and microbial metabolomics and metagenomics data has significantly advanced our understanding in diagnosing and treating conditions such as inflammatory bowel disease and irritable bowel syndrome. Metabolic signatures in biological fluids and their microbial counterparts serve as indicators, differentiating health from disease. The sheer volume of data demands sophisticated automated tools for processing and interpretation. Recognizing this need, integrating artificial intelligence (AI) and data science has become increasingly prominent. In this chapter, we combine microbiome and metabolome analyses through publicly available models to elucidate the correlations between microbial and metabolic profiles. By harnessing AI models across various omics data sources, this chapter bridges the gap between data acquisition and clinical applications, paving the way for personalized interventions and optimizing individual health.

Antibiotics have become an excellent tool for understanding the role of gut microbes. While the effect of antibiotic treatment on adults is studied, its impact during adolescence is unclear. In the current study, we treated C57BL/6 mice with an antibiotic cocktail composed of nine antibiotics from weaning (3 weeks old) until they became young adults (10 weeks old). We investigated the effect of antibiotic treatment (1) on gut microbiota composition, (2) on the brain by studying the behavior, Hypothalamic–Pituitary–Adrenal (HPA axis), neuroinflammation, neurotransmitters, neuronal health, and appetite regulators, and (3) on systemic circulation by recording changes in the stress hormones, insulin resistance, and metabolic profile. In the gut, we found that the antibiotic treatment significantly increased the Proteobacteria and Actinobacteria while decreasing the Bacteroidetes phylum. In the brain, we observed HPA axis activation, elevated proinflammatory response, decline in neurotrophins, neurotransmitter abundance, and appetite regulators expression, which could be linked with behavioral changes. We found increased insulin resistance and altered metabolite profiles in the peripheral system. Moreover, our association study highlights the role of Proteobacteria and Actinobacteria in altering the host behavior, brain function, and systemic circulation. Altogether this study demonstrates, how prolonged antibiotic exposure during adolescence disrupts gut microbiota and is associated with physiological and behavioral alterations through gut peripheral system and brain interactions.

Parkinson’s disease (PD), for long has been understood as a neurodegenerative disorder confined solely to the brain. It is now emerging as a systemic illness marked by early gastrointestinal, immune, and neuroendocrine perturbations. This review challenges the traditional neurocentric view of idiopathic PD (iPD), highlighting the gut- immune-brain axis as a central player in its pathogenesis. We have tried to explore how our dysbiosed gut, increased intestinal permeability, and immune hyperactivation orchestrate a cascade- from peripheral inflammation to microglial priming and α-synuclein aggregation thus leading to dopaminergic neurodegeneration. Intriguingly, the COVID-19 pandemic has amplified these mechanisms. SARS-CoV-2 not only perturbs gut ecology and immune signalling but may act as a hidden catalyst for parkinsonism. It can unmask or accelerate the diseased state through systemic inflammation, blood–brain barrier disruption, and HPA axis dysregulation. Strikingly, cases of post-COVID parkinsonism and symptom exacerbation in PD patients spotlight the virus as a potential environmental catalyst. By drawing parallels between post-COVID systemic disruption and the prodromal landscape of PD, we propose that the pandemic may be amplifying latent neurodegenerative pathways. Can pandemics act as silent accelerators of neurodegeneration, and are we equipped to detect their molecular footprints in time? This review synthesizes current evidence to reframe PD as a multisystem disorder, urging a shift toward integrative diagnostics and early peripheral interventions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multifactorial disorder with immunometabolic imprints that differ significantly by sex. Although sex differences in disease susceptibility and progression have been recognized in other systems, they remain understudied in MASLD. Here, we explore how sex-based immune responses, metabolic stressors (diet, drugs, and lifestyle), and the gut microbiome contribute to disease variability. Wherever applicable, we take into account sex as a biological variable. We also analyzed phylum-level microbiome data from Human Gut Microbiome Atlas using an interpretable machine learning framework to predict and explain the classification features associated with MASLD. Our integrative approach underscores the need for sex-specific diagnostics and interventions incorporating host–microbiome–immune interactions.

AIMS:The use of antibiotics affects health. The gut microbial dysbiosis by antibiotics is thought to be an essential pathway to influence health. It is important to have optimized energy utilization, in which adipose tissues (AT) play crucial roles in maintaining health. Adipocytes regulate the balance between energy expenditure and storage. While it is known that white adipose tissue (WAT) stores energy and brown adipose tissue (BAT) produces energy by thermogenesis, the role of an intermediate AT plays an important role in balancing host internal energy. In the current study, we tried to understand how treating an antibiotic cocktail transforms WAT into BAT or, more precisely, into beige adipose tissue (BeAT).METHODS:Since antibiotic treatment perturbs the host microbiota, we wanted to understand the role of gut microbial dysbiosis in transforming WAT into BeAT in C57BL/6 mice. We further correlated the metabolic profile at the systemic level with this BeAT transformation and gut microbiota profile.KEY FINDINGS:In the present study, we have reported that the antibiotic cocktail treatment increases the Proteobacteria and Actinobacteria while reducing the Bacteroidetes phylum. We observed that prolonged antibiotic treatment could induce the formation of BeAT in the inguinal and perigonadal AT. The correlation analysis showed an association between the gut microbiota phyla, beige adipose tissue markers, and serum metabolites.SIGNIFICANCE:Our study revealed that the gut microbiota has a significant role in regulating the metabolic health of the host via microbiota-adipose axis communication.

Aims Metabolic disease is a multifaceted condition characterized by the disruption of numerous metabolic parameters within the host. Its prevalence has surged significantly in recent years and it has become a prominent non-communicable disease worldwide. The effect of gut microbiota on various beige fat induction is well studied, while the mechanisms behind the link remain unclear. Given that gut microbiota-derived metabolites (meta-metabolites) secreted in the gut serve as a key mode of communication with their host through direct circulation or indirect host physiology modification, understanding the effect of meta-metabolites on adipose tissue is essential. Methodology In our previous in-vivo studies, we observed a correlation between gut microbiota and the formation of beige fat. In this study, we further aimed to validate this correlation by treating the adipocyte cell line (3T3-L1) with meta-metabolites collected from the cecum of mice exhibiting beige adipose tissue formation. Additionally, we treated the adipocyte cell line with known beige fat inducers (L-Rhamnose and Ginsenoside) to assess meta-metabolites' efficacy on beige fat formation. Key findings Upon treatment with the meta-metabolites from the antibiotic-treated mice, we observed a significant increase in lipid metabolism and beige-specific gene expression. Analyzing the metabolites in these cells revealed that a set of metabolites potentially govern adipocytes, contributing to a metabolically active state. These effects were at par or even better than those of cells treated with L-Rhamnose or Ginsenoside. Significance This research sheds light on the intricate interplay between microbial metabolites and adipose tissue, offering valuable clues for understanding and potentially manipulating these processes for therapeutic purposes.

Microbiome, microbiota, and probiotics are a few popular buzzwords floating around with a lot of hopes in preventing and curing diseases be it infectious, metabolic, or cancer. A quick literature search over the last 2 decades suggests that the interest in understanding the relationship and potential of microbiome research in diagnosis and intervention is rapidly increasing. The potential, abundance, and diversity of residential gut microbiome are important parameters to be utilized for early diagnostics and effective intervention. Probiotics are a direct consequence of microbiome research. The area of probiotics is gradually becoming a potent alternate route of treatment and prophylaxis. The increasingly beneficial roles of probiotics are more rooted in the fact that we are more microbes than humans. We harbor a plethora of microbes on various internal and external body surfaces. The resident microbes and their metabolites help shaping our immunity and other physiological functions to maintain health. The current report explains the status and future use of probiotics and microbiome on health.Download : Download full-size image

The postnatal period is one of the critical windows for the structure-function development of the gastrointestinal tract and associated mucosal immunity. Along with other constituent members, recent studies suggest the contribution of gut microbiota in maintaining host health, immunity, and development. Although the gut microbiota's role in maintaining barrier integrity is known, its function in early life development still needs to be better understood. To understand the details of gut microbiota's effects on intestinal integrity, epithelium development, and immune profile, the route of antibiotic-mediated perturbation is taken. Mice on days 7(P7D), 14(P14D), 21(P21D) and 28(P28D) are sacrificed and 16S rRNA metagenomic analysis is performed. The barrier integrity, tight junction proteins (TJPs) expression, intestinal epithelial cell (IEC) markers, and inflammatory cytokines are analyzed. Results reveal a postnatal age-related impact of gut microbiota perturbation, with a gradual increase in the relative abundance of Proteobacteria and a reduction in Bacteroidetes and Firmicutes. Significant barrier integrity disruption, reduced TJPs and IECs marker expression, and increased systemic inflammation at P14D of AVNM-treated mice are found. Moreover, the microbiota transplantation shows recolonization of Verrucomicrobia, proving a causal role in barrier functions. The investigation reveals P14D as a critical period for neonatal intestinal development, regulated by specific microbiota composition.

Obesity is a complex health condition that increases the susceptibility to developing cardiovascular diseases, diabetes, and numerous other metabolic health issues. The effect of obesity is not just limited to the conditions mentioned above; it is also seen to have a profound impact on the patient's mental state, leading to the onset of various mental disorders, particularly mood disorders. Therefore, it is necessary to understand the mechanism underlying the crosstalk between obesity and mental disorders. The gut microbiota is vital in regulating and maintaining host physiology, including metabolism and neuronal circuits. Because of this newly developed understanding of gut microbiota role, here we evaluated the published diverse information to summarize the achievement in the field. In this review, we gave an overview of the association between obesity, mental disorders, and the role of gut microbiota there. Further new guidelines and experimental tools are necessary to understand the microbial contribution to regulate a balanced healthy life.

AIMS:Balanced gut microbial composition of the host plays a crucial role in maintaining harmony among various physiological processes to maintain physiological homeostasis. Immunity and metabolism are the two physiologies mainly controlled by the gut microbiota. Reports suggested that gut microbial composition and diversity alteration are the leading causes of the host's healthy homeostasis alteration or a diseased state. The extent of gut perturbation depends on the perturbing agents' strength, chemical nature, and mode of action. In the current report, we have studied the effects of different perturbing agents on gut microbial dysbiosis and its impact on host immunity and metabolism.MATERIALS AND METHODS:We studied the perturbation of gut microbial composition and diversity using next-generation sequencing and further investigated the changes in host immune and metabolic responses.KEY FINDINGS:Enrichment or abolition of a particular phylum or genus depended on the perturbing agents. In the current study, treatment with neomycin yielded an increase in the Bacteroidetes phylum. Vancomycin treatment caused a significant rise in Verrucomicrobia and Proteobacteria phyla. The treatment with AVNM and DSS caused a substantial increase in the Proteobacteria phylum. The gut microbial diversity was also lowest in AVNM treated group. The altered gut microbial composition ultimately altered the immune responses at localized and systemic levels of the host. Gut dysbiosis also changed the systemic level of SCFAs.SIGNIFICANCE:This study will help us understand how the enrichment of a particular phylum and genus maintains the host's immune responses and metabolism.

circadian clock can coordinate, regulate and predict physiology and behavior in response to the standard light-dark (LD: 12 h light and 12 h dark) cycle. If we alter the LD cycle by exposing mice to constant dark-ness (DD: 00 h light and 24 h dark), it can perturb behavior, the brain, and associated physiological parameters. The length of DD exposure and the sex of experimental animals are crucial variables that could alter the impact of DD on the brain, behavior, and physiology, which have not yet been explored. We exposed mice to DD for three and five weeks and studied their impact on (1) behavior, (2) hormones, (3) the prefrontal cortex, and (4) metabo-lites in male and female mice. We also studied the effect of three weeks of standard light-dark cycle restoration after five weeks of DD on the parameters mentioned above. We found that DD exposure was associated with anxiety-like behavior, increased corticosterone and pro-inflammatory cytokines (TNF-a, IL-6, and IL-1b), downreg-ulated neurotrophins (BDNF and NGF), and altered metabolites profile in a duration of DD exposure and sex -dependent manner. Females showed a more robust adaptation than males under DD exposure. Three weeks of restoration was adequate to establish homeostasis in both sexes. To the best of our knowledge, this study is the first of its kind to look at how DD exposure impacts physiology and behavior as a function of sex-and time. These findings would have translational value and may help in establishing sex-specific interventions for addressing DD-related psychological issues.(c) 2023 IBRO. Published by Elsevier Ltd. All rights reserved.

Nonalcoholic fatty liver disease or NAFLD is a complex and multifactorial liver disease that is affecting a majority of the world’s population now more than ever. The review focuses on two major contributing factors in the etiology of the disease – oxidative stress and the gut microbiota. There is a complex interplay between oxidative stress and the gut microbiota in the pathogenesis of NAFLD. Oxidative stress in NAFLD can result from both the accumulation of lipids in the liver and the interactions between gut-derived metabolites and the liver. Dysbiosis in the gut microbiota can contribute to oxidative stress by promoting the production of reactive oxygen species and altering the balance of antioxidant systems. This interplay between oxidative stress and the gut microbiota can create a vicious cycle, where dysbiosis contributes to oxidative stress, and oxidative stress further promotes dysbiosis, exacerbating liver damage in NAFLD. Understanding the intricate relationship between oxidative stress, the gut microbiota, and NAFLD is essential for developing targeted therapeutic strategies. In this context, more scientific research is required to unravel the complex and interconnecting pathways underlying NAFLD pathogenesis and progression. Modulating the gut microbiota through dietary interventions, prebiotics, probiotics, and change in lifestyle may help restore microbial balance and reduce oxidative stress in NAFLD.

A healthy state of life suggests not only a disease-free condition but also normal psychological functioning and behaviour. To maintain a healthy life, the duration of light exposure is a crucial factor. Perturbation of the standard light-dark cycle (LD: 12 h light-12 h dark in mice) may result in brain, behavioural and physiological abnormalities. The current study determined the effects of 3 and 5 weeks of constant darkness (DD: 00 h light-24 h dark) on the behaviour, hormones, prefrontal cortex (PFC) and metabolome of male and female C57BL/6 J mice. We also studied 3 weeks of restoration in LD following 5 weeks of DD exposure. The results revealed that 3 weeks of DD affected male mice more than females, and 5 weeks of DD had a comparable impact on behaviour, hormones and the PFC of male and female mice. After restoration in LD, the DD-induced changes reverted to time-matched LD conditions in male and female mice. Furthermore, metabolome analysis corroborated male and female mice's behavioural and molecular kinetics. The present study laid the foundation for understanding how DD affects behaviour and the PFC as a function of (a) time and (b) sex and described the roles of stress and sex hormones, cytokines, neurotrophins and metabolic pathways.

Background: During the early postnatal life, gut microbiota development experiences dynamic changes in their structural and functional composition. The postnatal period is the critical window to develop a host defense mechanism. The maturation of intestinal mucosal barrier integrity is one of the essential defense mechanisms to prevent the entry of pathogens. However, the co-development of intestinal microbial colonization, formation of barrier integrity, and intestinal epithelial cell layer is not entirely understood. Methods: We studied the gut microbial composition and diversity using 16S rRNA marker gene-based sequencing in mice to understand postnatal age-dependent association ki-netics between gut microbial and intestinal development. Next, we assessed the intestinal development by in vivo gut permeability assay, mRNA gene expression of different tight junction proteins and intestinal epithelial cell markers, goblet cells population, villus length, and cecal IgA quantification. Results: Our results showed a significant shift in gut microbial structural and functional composition from postnatal day 14 onwards with early life Proteobacteria abundance. Relative abundance of Verrucomicrobia was maximum at postnatal day 14 and showed a gradual decrease over time. We also observed an age-dependent biphasic pattern in barrier integrity improvement and differentiation of intestinal epithelial cells (IECs). A significant improvement in barrier integrity between days 1 and 7 showed the host factor contribu-tion, while that beyond day 14 revealed an association with changes in microbiota composition. Our temporal correlation analysis associated Bacteroidetes phylum with the mucosal barrier formation during postnatal development. Conclusions: The present study revealed the importance and interplay of host factors and the microbiome in gut development and intestinal mucosal homeostasis.