Yadav, Pankaj

In the current study, gene network analysis revealed five novel disease-resistance proteins against bacterial leaf blight (BB) and rice blast (RB) diseases caused by Xanthomonas oryzae pv. oryzae (Xoo) and Magnaporthe oryzae (M. oryzae), respectively. In silico modeling, refinement, and model quality assessment were performed to predict the best structures of these five proteins and submitted to ModelArchive for future use. An in-silico annotation indicated that the five proteins functioned in signal transduction pathways as kinases, phospholipases, transcription factors, and DNA-modifying enzymes. The proteins were localized in the nucleus and plasma membrane. Phylogenetic analysis showed the evolutionary relation of the five proteins with disease-resistance proteins (XA21, OsTRX1, PLD, and HKD-motif-containing proteins). This indicates similar disease-resistant properties between five unknown proteins and their evolutionary-related proteins. Furthermore, gene expression profiling of these proteins using public microarray data showed their differential expression under Xoo and M. oryzae infection. This study provides an insight into developing disease-resistant rice varieties by predicting novel candidate resistance proteins, which will assist rice breeders in improving crop yield to address future food security through molecular breeding and biotechnology.

Aims: This study aimed to isolate plant growth and drought tolerance-promoting bacteria from the nutrient-poor rhizosphere soil of Thar desert plants and unravel their molecular mechanisms of plant growth promotion. Methods and results: Among our rhizobacterial isolates, Enterobacter cloacae C1P-IITJ, Kalamiella piersonii J4-IITJ, and Peribacillus frigoritolerans T7-IITJ, significantly enhanced root and shoot growth (4 - 5-fold) in Arabidopsis thaliana under PEG-induced drought stress. Whole genome sequencing and biochemical analyses of the non-pathogenic bacterium T7-IITJ revealed its plant growth-promoting traits, viz., solubilization of phosphate (40-73 μg/ml), iron (24 ± 0.58 mm halo on chrome azurol S media), and nitrate (1.58 ± 0.01 μg/ml nitrite), along with production of exopolysaccharides (125 ± 20 μg/ml) and auxin-like compounds (42.6 ± 0.05 μg/ml). Transcriptome analysis of A. thaliana inoculated with T7-IITJ and exposure to drought revealed the induction of 445 plant genes (log2fold-change > 1, FDR < 0.05) for photosynthesis, auxin and jasmonate signalling, nutrient uptake, redox homeostasis, and secondary metabolite biosynthesis pathways related to beneficial bacteria-plant interaction, but repression of 503 genes (log2fold-change < -1) including many stress-responsive genes. T7-IITJ enhanced proline 2.5-fold, chlorophyll 2.5 - 2.8-fold, iron 2-fold, phosphate 1.6-fold, and nitrogen 4-fold, and reduced reactive oxygen species 2 - 4.7-fold in plant tissues under drought. T7-IITJ also improved the germination and seedling growth of Tephrosia purpurea, Triticum aestivum, and Setaria italica under drought and inhibited the growth of two plant pathogenic fungi, Fusarium oxysporum, and Rhizoctonia solani. Conclusions: P. frigoritolerans T7-IITJ is a potent biofertilizer that regulates plant genes to promote growth and drought tolerance.

Mendelian randomization (MR) is an emerging tool for inferring causality in genetic epidemiology. MR studies suffer bias from weak genetic instrument variables (IVs) and horizontal pleiotropy. We introduce a robust integrative framework strictly adhering with STROBE-MR guidelines to improve causality inference through MR studies. We implemented novel t-statistics-based criteria to improve the reliability of selected IVs followed by various MR methods. Further, we include sensitivity analyses to remove horizontal-pleiotropy bias. For functional validation, we perform enrichment analysis of identified causal SNPs. We demonstrate effectiveness of our proposed approach on 5 different MR datasets selected from diverse populations. Our pipeline outperforms its counterpart MR analyses using default parameters on these datasets. Notably, we found a significant association between total cholesterol and coronary artery disease (P = 1.16 × 10−71) in a single-sample dataset using our pipeline. Contrarily, this same association was deemed ambiguous while using default parameters. Moreover, in a two-sample dataset, we uncover 13 new causal SNPs with enhanced statistical significance (P = 1.06 × 10−11) for liver-iron-content and liver-cell-carcinoma. Likewise, these SNPs remained undetected using the default parameters (P = 7.58 × 10−4). Furthermore, our analysis confirmed previously known pathways, such as hyperlipidemia in heart diseases and gene ME1 in liver cancer. In conclusion, we propose a robust and powerful framework to infer causality across diverse populations and easily adaptable to different diseases.

We sequenced the drought-response transcriptome of the keystone tree species Prosopis cineraria from the Indian Thar desert to understand the key factors in its drought tolerance mechanism. We identified a network of genes activated in P. cineraria involved in the biosynthesis of osmolytes, antioxidants, phytohormones, and signal transduction. Of these, up-regulation of 54 APETALA2/Ethylene-Responsive Factor (AP2/ERF) transcription factor genes, validated by real-time PCR, suggests their key role in the drought tolerance of P. cineraria. We conducted a genome-wide study of the AP2/ERF superfamily in P. cineraria, classifying its 232 proteins into 15 clades and analyzing their protein structures, gene structure, and promoter organization. The P. cineraria genome contains more copies of AP2/ERF genes than drought-sensitive plants. Further, we identified sequence polymorphisms in AP2/ERF genes between Arabian and Indian cultivars of P. cineraria. We modeled the DNA–protein complex structures of AP2/ERFs from drought-tolerant and sensitive species using AlphaFold to compare their DNA-binding ability. Though the DNA-binding domain (DBD) is relatively conserved across species, the unstructured region of these proteins possesses different charge distributions, which might contribute differently to their DNA search and binding. Using all-atom molecular dynamics simulations, we teased out a higher number of specific DBD-DNA hydrogen bonds in P. cineraria, leading to a stronger DNA-binding affinity than drought-sensitive Arabidopsis thaliana. These results directly support copy number expansion of AP2/ERF transcription factors and the evolution of their structures for more efficient DNA search and binding as drought adaptation mechanisms in P. cineraria.

Neuropsychiatric disorders are mainly concerned with the behavioural, emotional and cognition symptoms that may be due to disturbed cerebral functions or extracerebral disease. Klotho protein is an antiaging protein that is mostly associated with cognitive changes in these disorders and thus this meta-analysis is conducted in order to find Klotho proteins association with these disorders. We searched related topics in pubmed, by using the key word i.e. Klotho and related disorder from neuropsychiatry e.g. Klotho levels and schizophrenia, Klotho levels and parkinsonism etc. Total 82 studies were found till 9th February 2021 after extensive search and 10 studies were selected for further analysis. The meta-analysis of studies was performed using the Random effect model. The forest plot represented each study in the meta-analysis, so as to make the comparison of SMD value across studies. The meta-analysis outcome demonstrated that overall schizophrenia had higher klotho levels as compared with bipolar disorder, psychosocial stress, parkinsonism, multiple sclerosis, depression, Alzheimer’s disease, and healthy controls, followed by MS. The meta-analysis also found that bipolar disorder and Alzheimer’s disease were associated with low klotho levels as compared to schizophrenia. The results indicate a significant association of the klotho levels and schizophrenia. Further studies are needed to characterize the potential biological roles of klotho levels in psychiatric disorders.

Lung cancer is the second most prevalent cancer worldwide and a leading cause of cancer-related deaths. Recent technological advancements have revealed that the lung microbiome, previously thought to be sterile, is host to various microorganisms. The association between the lung microbiome and lung cancer initiation, progression, and metastasis is complex and contradictory. However, disruption in the homeostasis of microbiome compositions correlated with the increased risk of lung cancer. This review summarizes current knowledge about the most recent developments and trends in lung cancer- related microbiota or microbial components. This article aims to provide information on this rapidly evolving field while giving context to the general role of the lung microbiome in lung cancer. In addition, this review briefly discussed the causative association of lung microbiome with lung cancer. We will review the mechanisms by which lung microbiota influence carcinogenesis, focusing on microbiota dysbiosis. Moreover, we will also discuss the host-microbiome interaction as it plays a crucial role in stimulating and regulating the immune response. Finally, we will provide information on the diagnostic role of the microbiome in lung cancer. This article aims to offer an overview of the lung microbiome as a predictive and diagnostic biomarker in lung cancer.

The rich ethnolinguistic and sociocultural differences that exist in India offers a unique opportunity to study human diversity. With the whole genomes of 10,000 healthy and unrelated Indians from 83 populations, the GenomeIndia project captures the genetic diversity of one of the highly underrepresented populations in the global genomics landscape. © Springer Nature America, Inc. 2025.

The combination of nanotechnology and hydroponics paves the way toward sustainable agriculture with less environmental footprints. We investigated the effects of a liquid nano urea formulation (NUF) marketed by Indian Farmers Fertilizer Cooperative (IFFCO) on the model plant Arabidopsis thaliana in hydroponics, comparing it to an equimolar bulk urea. Dynamic light scattering and transmission electron microscopy confirmed NUF’s negative surface charge and sub-100-nm size, suitable for its uptake and distribution in the plant. A two-week growth in a nitrogen-free hydroponic medium with 70 μM NUF led to a 20% higher biomass and 16% higher chlorophyll content than a medium with 70 μM urea. Higher doses of NUF inhibited growth, whereas higher equivalent urea doses did not. Transcriptome analysis revealed that NUF led to the differential expression of more genes than urea at 12 h to seven days of treatment. Nitrogen assimilation, growth, photosynthesis, and stress tolerance genes showed higher transcript levels in NUF than in urea. On the other hand, NUF led to greater suppression of many negative growth-regulating genes. After seven days of treatment, chlorophyll biosynthesis genes were up-regulated, while chlorophyll catabolism genes down-regulated at higher levels by NUF than by urea, correlating with the higher chlorophyll content of NUF-treated seedlings. In conclusion, NUF outperformed equimolar urea for the growth promotion of A. thaliana at a low concentration in hydroponics, leading to a greater regulation of genes for nitrogen metabolism and chlorophyll biosynthesis. Our results suggest a potential use of NUF as a nitrogen fertilizer for hydroponic agriculture.

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.

Intratumoral bacteria flexibly contribute to cellular and molecular tumor heterogeneity for supporting cancer recurrence through poorly understood mechanisms. Using spatial metabolomic profiling technologies and 16SrRNA sequencing, we herein report that right-sided colorectal tumors are predominantly populated with Colibactin-producing Escherichia coli (CoPEC) that are locally establishing a high-glycerophospholipid microenvironment with lowered immunogenicity. It coincided with a reduced infiltration of CD8+ T lymphocytes that produce the cytotoxic cytokines IFN-γ where invading bacteria have been geolocated. Mechanistically, the accumulation of lipid droplets in infected cancer cells relied on the production of colibactin as a measure to limit genotoxic stress to some extent. Such heightened phosphatidylcholine remodeling by the enzyme of the Land’s cycle supplied CoPEC-infected cancer cells with sufficient energy for sustaining cell survival in response to chemotherapies. This accords with the lowered overall survival of colorectal patients at stage III-IV who were colonized by CoPEC when compared to patients at stage I-II. Accordingly, the sensitivity of CoPEC-infected cancer cells to chemotherapies was restored upon treatment with an acyl-CoA synthetase inhibitor. By contrast, such metabolic dysregulation leading to chemoresistance was not observed in human colon cancer cells that were infected with the mutant strain that did not produce colibactin (11G5∆ClbQ). This work revealed that CoPEC locally supports an energy trade-off lipid overload within tumors for lowering tumor immunogenicity. This may pave the way for improving chemoresistance and subsequently outcome of CRC patients who are colonized by CoPEC.