The human microbiome plays a key role in maintaining host homeostasis and is influenced by age, geography, diet, and other factors. traditionally, india has an established convention of extended family arrangements wherein three or more generations, bound by genetic relatedness, stay in the same household. in the present study, we have utilized this unique family arrangement to understand the association of age with the microbiome. We characterized stool, oral and skin microbiome of 54 healthy individuals from six joint families by 16S rRNA gene-based metagenomics. In total, 69 (1.03%), 293 (2.68%) and 190 (8.66%) differentially abundant OTUs were detected across three generations in the gut, skin and oral microbiome, respectively. Age-associated changes in the gut and oral microbiome of patrilineal families showed positive correlations in the abundance of phyla proteobacteria and fusobacteria, respectively. Genera Treponema and Fusobacterium showed a positive correlation with age while Granulicatella and Streptococcus showed a negative correlation with age in the oral microbiome. Members of genus Prevotella illustrated high abundance and prevalence as a core otUs in the gut and oral microbiome. in conclusion, this study highlights that precise and perceptible association of age with microbiome can be drawn when other causal factors are kept constant.

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A substantial majority of global population owns cellular phones independently to demographic factors like age, economic status, and educational attainment. In this study, we investigated the diversity of microorganisms associated with cellular phones of 27 individuals using cultivation-based methods. Cellular phones were sampled using cotton swabs and a total of 554 isolates representing different morphotypes were obtained on four growth media. Matrix-assisted laser desorption ionization time of flight (MALDI-TOF) mass spectrometry could generate protein profiles for 527 isolates and species-level identification was obtained for 415 isolates. A dendrogram was constructed based on the protein profiles of the remaining isolates, to group 112 isolates under 39 different proteotypes. The representative strains of each group were selected for 16S rRNA gene and ITS region sequencing based identification. Staphylococcus, Bacillus, Micrococcus, and Pseudomonas were the most frequently encountered bacteria, and Candida, Aspergillus, Aureobasidium, and Cryptococcus were in case of fungi. At species-level the prevalence of Micrococcus luteus, Staphylococcus hominis, Staphylococcus epidermidis, Staphylococcus arlettae, Bacillus subtilis, and Candida parapsilosis was observed, most of these species are commensal microorganisms of human skin. UPGMA dendrogram and PCoA biplot generated based on the microbial communities associated with all cellular phones exhibited build-up of specific communities on cellular phones and the prevalence of objectionable microorganisms in some of the cellular phones can be attributed to the poor hygiene and sanitary practices. The study also revealed the impact of MALDI-TOF MS spectral quality on the identification results. Overall MALDI-TOF appears a powerful tool for routine microbial identification and de-replication of microorganisms. Quality filtering of MALDI-TOF MS spectrum, development of better sample processing methods and enriching the spectral database will improve the role of MALDI-TOF MS in microbial identifications.

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Rhizosphere microbiome significantly influences plant growth and productivity. Legume crops such as pea have often been used as a rotation crop along with rice cultivation in long-term conservation agriculture experiments in the acidic soils of the northeast region of India. It is essential to understand how the pea plant influences the soil communities and shapes its rhizosphere microbiome. It is also expected that the longterm application of nutrients and tillage practices may also have a lasting effect on the rhizosphere and soil communities. In this study, we estimated the bacterial communities by 16S rRNA gene amplicon sequencing of pea rhizosphere and bulk soils from a longterm experiment with multiple nutrient management practices and different tillage history. We also used Tax4Fun to predict the functions of bacterial communities. Quantitative polymerase chain reaction (qPCR) was used to estimate the abundance of total bacterial and members of Firmicutes in the rhizosphere and bulk soils. The results showed that bacterial diversity was significantly higher in the rhizosphere in comparison to bulk soils. A higher abundance of Proteobacteria was recorded in the rhizosphere, whereas the bulk soils have higher proportions of Firmicutes. At the genus level, proportions of Rhizobium, Pseudomonas, Pantoea, Nitrobacter, Enterobacter, and Sphingomonas were significantly higher in the rhizosphere. At the same time, Massilia, Paenibacillus, and Planomicrobium were more abundant in the bulk soils. Higher abundance of genes reported for plant growth promotion and several other genes, including iron complex outer membrane receptor, cobalt-zinc-cadmium resistance, sigma-70 factor, and ribonuclease E, was predicted in the rhizosphere samples in comparison to bulk soils, indicating that the pea plants shape their rhizosphere microbiome, plausibly to meet its requirements for nutrient uptake and stress amelioration.