Unveiling the Wheat Microbiome under Varied Agricultural Field Conditions.

Wheat being the important staple food crop plays a significant role in nutritional security. A wide variety of microbial communities beneficial to plants and contributing to plant health and production are found in the rhizosphere. The wheat microbiome encompasses an extensive variety of microbial species playing a key role in sustaining the physiology of the crop, nutrient uptake, and biotic/abiotic stress resilience. This report presents wheat microbiome analysis under six different farm practices, namely, organic (Org), timely sown (TS), wheat after pulse crop (WAPC), temperature-controlled phenotyping facility (TCPF), maize-wheat cropping system (MW), and residue burnt field (Bur), using 16S rRNA sequencing methodology. The soil samples collected from either side of the wheat row were mixed to get a final sample set for DNA extraction under each condition. After the data preprocessing, microbial community analysis was performed, followed by functional analysis and annotation. An abundance of the phylum Proteobacteria was observed, followed by Acidobacteria, Actinobacteria, and Gemmatimonadetes in the majority of the samples, while relative abundance was found to vary at the genus level. Analysis against the Carbohydrate-Active Enzymes (CAZy) database showed a high number of glycoside hydrolase genes in the TS, TCPF, and WAPC samples, while the Org, MW, and Bur samples predominantly had glycosyltransferase genes and carbohydrate esterase genes were in the lowest numbers. Also, the Org and TCPF samples showed lower diversity, while rare and abundant species ranged from 12 to 25% and 20 to 32% of the total bacterial species in all the sets, respectively. These variations indicate that the different cropping sequence had a significant impact on soil microbial diversity and community composition, which characterizes its economic and environmental value as a sustainable agricultural approach to maintaining food security and ecosystem health. IMPORTANCE This investigation examined the wheat microbiome under six different agricultural field conditions to understand the role of cropping pattern on soil microbial diversity. This study also elaborated the community composition, which has importance in economic (role of beneficial community leading to higher production) and environmental (role of microbial diversity/community in safeguarding the soil health, etc.) arenas. This could lead to a sustainable farming approach for food security and improved ecosystem health. Also, the majority of the microbes are unculturable; hence, technology-based microcultivation will be a potential approach for harnessing other cultured microorganisms, leading to unique species for commercial production. The outcome of this research-accelerated work can provide an idea to the scientists/breeders/agronomists/pathologists under the mentioned field conditions regarding their influence over their crops.

Potential Use of Microbial Community Genomes in Various Dimensions of Agriculture Productivity and Its Management: A Review.

Agricultural productivity is highly influenced by its associated microbial community. With advancements in omics technology, metagenomics is known to play a vital role in microbial world studies by unlocking the uncultured microbial populations present in the environment. Metagenomics is a diagnostic tool to target unique signature loci of plant and animal pathogens as well as beneficial microorganisms from samples. Here, we reviewed various aspects of metagenomics from experimental methods to techniques used for sequencing, as well as diversified computational resources, including databases and software tools. Exhaustive focus and study are conducted on the application of metagenomics in agriculture, deciphering various areas, including pathogen and plant disease identification, disease resistance breeding, plant pest control, weed management, abiotic stress management, post-harvest management, discoveries in agriculture, source of novel molecules/compounds, biosurfactants and natural product, identification of biosynthetic molecules, use in genetically modified crops, and antibiotic-resistant genes. Metagenomics-wide association studies study in agriculture on crop productivity rates, intercropping analysis, and agronomic field is analyzed. This article is the first of its comprehensive study and prospects from an agriculture perspective, focusing on a wider range of applications of metagenomics and its association studies.

Microbiome of Pukzing Cave in India shows high antimicrobial activity against plant and animal pathogens.

Pukzing cave, the largest cave of Mizoram, India was explored for bacterial diversity. Culture dependent method revealed 235 bacterial isolates using three different treatments. Identity of the microbial species was confirmed by 16S rDNA sequencing. The highest bacterial population was recovered from heat treatment (n = 97;41.2%) followed by normal (n = 79;33.6%) and cold treatment (n = 59;25.1%) indicating dominance of moderate thermophiles. Antimicrobial potential of isolates showed 20.4% isolates having antimicrobial ability against tested pathogens. Amplicon sequencing of PKSI, PKSII and NRP specific genes revealed presence of AMP genes in the microbial population. Six microbial pathogens were selected for screening as they are well known for different disease cause organism in various fields such as agriculture and human health. Cave environment harbors unique microbial flora and hypervariable region V4 is more informative. Higher activity of AMP assay against these microbes indicates that cave microbial communities could be potential source of future genomic resources.

Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo.

Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.

Novel complex of HAT protein TIP60 and nuclear receptor PXR promotes cell migration and adhesion.

PXR is a member of nuclear receptor superfamily and a well-characterized mediator of xenobiotic metabolism. The classical mode of PXR activation involves its binding to appropriate ligand and subsequent heterodimerization with its partner RXR. However, various factors such as post-translational modifications and crosstalk with different cellular factors may also regulate the functional dynamics and behavior of PXR. In the present study, we have identified that TIP60, an essential lysine acetyltransferase protein interacts with unliganded PXR and together this complex promotes cell migration & adhesion. TIP60 utilizes its NR Box to interact with LBD region of PXR and acetylates PXR at lysine 170 to induce its intranuclear reorganization. Also, RXR is not required for TIP60-PXR complex formation and this complex does not induce ligand-dependent PXR target gene transactivation. Interestingly, we observed that PXR augments the catalytic activity of TIP60 for histones. This is the first report demonstrating the exclusive interaction of TIP60 with PXR and uncovers a potential role for the TIP60-PXR complex in cell migration and adhesion.

Comprehensive Map of Molecules Implicated in Obesity.

Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as type 2 diabetes mellitus and hypertension. We have constructed a comprehensive map of the molecules reported to be implicated in obesity. A deep curation strategy was complemented by a novel semi-automated text mining system in order to screen 1,000 full-length research articles and over 90,000 abstracts that are relevant to obesity. We obtain a scale free network of 804 nodes and 971 edges, composed of 510 proteins, 115 genes, 62 complexes, 23 RNA molecules, 83 simple molecules, 3 phenotype and 3 drugs in "bow-tie" architecture. We classify this network into 5 modules and identify new links between the recently discovered fat mass and obesity associated FTO gene with well studied examples such as insulin and leptin. We further built an automated docking pipeline to dock orlistat as well as other drugs against the 24,000 proteins in the human structural proteome to explain the therapeutics and side effects at a network level. Based upon our experiments, we propose that therapeutic effect comes through the binding of one drug with several molecules in target network, and the binding propensity is both statistically significant and different in comparison with any other part of human structural proteome.