Dynamic interactions between gut microbiota and a host’s innate and adaptive immune systems are essential in maintaining intestinal homeostasis and inhibiting inflammation. Gut microbiota metabolizes proteins and complex carbohydrates, synthesizes vitamins, and produces an enormous number of metabolic products that can mediate cross-talk between gut epithelium and immune cells. As a defense mechanism, gut epithelial cells produce a mucosal barrier to segregate microbiota from host immune cells and reduce intestinal permeability. An impaired interaction between gut bacteria and the mucosal immune system can lead to an increased abundance of potentially pathogenic gram-negative bacteria and their associated metabolic changes, disrupting the epithelial barrier and increasing susceptibility to infections. Gut dysbiosis, or negative alterations in gut microbial composition, can also dysregulate immune responses, causing inflammation, oxidative stress, and insulin resistance. Over time, chronic dysbiosis and the leakage of microbiota and their metabolic products across the mucosal barrier may increase prevalence of type 2 diabetes, cardiovascular disease, autoimmune disease, inflammatory bowel disease, and a variety of cancers. In this paper, we highlight the pivotal role gut bacteria and their metabolic products (short-chain fatty acids (SCFAs)) which play in mucosal immunity.

Early life gut microbiota have been increasingly recognized as major contributors to short and/or long-term human health and diseases. Numerous studies have demonstrated that human gut microbial colonization begins at birth, but continues to develop a succession of taxonomic abundances for two to three years until the gut microbiota reaches adult-like diversity and proportions. Several factors, including gestational age (GA), delivery mode, birth weight, feeding types, antibiotic exposure, maternal microbiome, and diet, influence the diversity, abundance, and function of early life gut microbiota. Gut microbial life is essential for assisting with the digestion of food substances to release nutrients, exerting control over pathogens, stimulating or modulating the immune system, and influencing many systems such as the liver, brain, and endocrine system. Microbial metabolites play multiple roles in these interactions. Furthermore, studies provide evidence supporting that imbalances of the gut microbiota in early life, referred to as dysbiosis, are associated with specific childhood or adult disease outcomes, such as asthma, atopic dermatitis, diabetes, allergic diseases, obesity, cardiovascular diseases (CVD), and neurological disorders. These findings support that the human gut microbiota may play a fundamental role in the risk of acquiring diseases that may be programmed during early life. In fact, it is critical to explore the role of the human gut microbiota in early life.

Corrections have been made to “Gut Microbiota and Immune System Interactions”

India, known for its rich cultural, linguistic and ethnic diversity, has attracted the attention of population geneticists to understand its genetic diversity employing autosomal, Y-chromosomal and mitochondrial DNA markers. Y-chromosomal short tandem repeats (Y-STRs) are useful in understanding population substructures and reveal the patrilineal affinities among populations. Previous studies on Indian populations based on Y-STR markers were either limited to restricted number of markers or focused on few selected populations. In this study we genotyped 407 unrelated male individuals from 12 states in India employing the suite of Y-STRs present in PowerPlex Y23 (Promega, Madison, WI, USA). These populations clustered genetically close to each other irrespective of their geographic co-ordinates and were characterized primarily by R1a, H and L haplogroups. Interestingly, comparison with 129 worldwide populations showed genetic affinity of the Indian populations with few populations from Europe and Levantine. This study presents the first pan-Indian landscape of 23 Y-STRs and serves as a useful resource for construction of an Indian Y-STR database.

The importance of studying the salivary microbiome has been highlighted for its connection to health and disease and as a potential tool for supplementing human genetic diversity studies. While the salivary microbiome has been studied in various world populations, Indian populations have not been examined. We therefore analyzed microbiome diversity in saliva samples from 92 volunteers from eight different sampling locations in India by amplifying and sequencing variable regions (V1 and V2) of the bacterial 16S rRNA gene. The results showed immense bacterial richness in Indian populations; we identified 165 bacterial genera and 785 unique Operational Taxonomic Units (OTUs), with substantial sharing among the populations. There were small, but significant correlations in the abundance of bacterial genera in sampling locations from the same geographic region. Most of the core OTUs detected were also observed previously in other populations, but Solobacterium spp., Lachnoanaerobaculum spp. and Alloprevotella spp. were observed to be a component of the saliva microbiome unique to Indian populations. Importantly, nine bacterial genera were observed that were not listed in the Human Oral Microbiome Database (HOMD). These results highlight the importance of analyzing underrepresented populations like those of India.

To examine a) whether there are significant differences in the severity of symptoms of fatigue, sleep disturbance, or depression between patients with rectal cancer who develop co-occurring symptoms and those with no symptoms before and at the end of chemotherapy and radiation therapy (CRT); b) differences in gut microbial diversity between those with co-occurring symptoms and those with no symptoms; and c) whether before-treatment diversity measurements and taxa abundances can predict co-occurrence of symptoms. Stool samples and symptom ratings were collected from 31 patients with rectal cancer prior to and at the end of (24–28 treatments) CRT. Descriptive statistics were computed and the Mann-Whitney U test was performed for symptoms. Gut microbiome data were analyzed using R’s vegan package software. Participants with co-occurring symptoms reported greater severity of fatigue at the end of CRT than those with no symptoms. Bacteroides and Blautia2 abundances differed between participants with co-occurring symptoms and those with no symptoms. Our random forest classification (unsupervised learning algorithm) predicted participants who developed co-occurring symptoms with 74% accuracy, using specific phylum, family, and genera abundances as predictors. Our preliminary results point to an association between the gut microbiota and co-occurring symptoms in rectal cancer patients and serves as a first step in potential identification of a microbiota-based classifier.