Biology subjects

Nanduri, B.

Publications and source records attributed to Nanduri, B..

4 recordsLinked to original sources

bioRxiv2022

Genome-scale host-pathogen prediction for non-medical microbes.

BackgroundNetwork studies of host-pathogen interactions (HPI) are critical in understanding the mechanisms of pathogenesis. However, accessible HPI data for agriculturally important pathogens are limited. This lack of HPI data impedes network analysis to study agricultural pathogens, for preventing and reducing the severity of diseases of relevance to agriculture. ResultsTo rapidly provide HPIs for a broad range of pathogens, we use an interolog-based approach. This approach uses sequence similarity to transfer known HPIs from better studied host-pathogen pairs and predicts 389,878 HPIs for 23 host-pathogen systems of relevance to US agriculture. Each predicted HPI is qualitatively assessed using co-localization, infection related processes, and interacting domains and this information is provided as a confidence indicator for the prediction. Evaluation of predicted HPIs demonstrates that the host proteins predicted to be involved in pathogen interactions include hubs and bottlenecks in the network, as reported in curated host proteins. Moreover, we demonstrate that the use of the predicted HPIs adds value to network analysis and recapitulates known aspects of host-pathogen biology. Access to the predicted HPIs for these agricultural host-pathogen systems is available via the Host Pathogen Interaction Database (HPIDB, hpidb.igbb.msstate.edu), and can be downloaded in standard MITAB file format for subsequent network analysis. ConclusionsThis core set of interolog-based HPIs will enable animal health researchers to incorporate network analysis into their research and help identify host-pathogen interactions that may be tested and experimentally validated. Moreover, the development of a larger set of experimentally validated HPI will inform future predictions. Our approach of transferring biologically relevant HPIs based on interologs is broadly applicable to many host-microbe systems and can be extended to support network modeling of other pathogens, as well as interactions between non-pathogenic microbes.

bioinformatics↗

bioRxiv2022

Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain

Bovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development. Gene expression counts of previously published RNA-Seq data from 23 cattle (2017; n=11 Healthy, n=12 BRD) were used to construct gene co-expression modules and correlation patterns with complete blood count (CBC) and clinical datasets. Modules were further evaluated for cross-populational preservation of expression with RNA-Seq data from 24 cattle in an independent population (2019; n=12 Healthy, n=12 BRD). Genes within well-preserved modules were subject to functional enrichment analysis for significant Gene Ontology terms and pathways. Genes which possessed high module membership and association with BRD development, regardless of module preservation ("hub genes"), were utilized for protein-protein physical interaction network and clustering analyses. Five well-preserved modules of co-expressed genes were identified. One module ("steelblue"), involved in alpha-beta T-cell complexes and Th2-type immunity, possessed significant correlation with increased erythrocytes, platelets, and BRD development. One module ("purple"), involved in mitochondrial metabolism and rRNA maturation, possessed significant correlation with increased eosinophils, fecal egg count per gram, and weight gain over time. Fifty-two interacting hub genes, stratified into 11 clusters, may possess transient function involved in BRD development not previously described in literature. This study identifies co-expressed genes and coordinated mechanisms associated with BRD, which necessitates further investigation in BRD-prediction research. Author SummaryBovine respiratory disease (BRD), the leading disease in beef cattle, is a highly dynamic disease complex. Through simultaneous sequencing of thousands of genes active in the blood of cattle at arrival, we pursued the co-expression patterns of these genes to evaluate associations with BRD development and severity overtime. This approach allows for a better understanding of gene expression active in cattle at arrival, and the discovery of new molecules and biological complexes that may predict BRD before the onset of clinical signs. Our work provides evidence that genes related to T-cells, a type of immune cell, are strongly co-expressed when cattle arrive to beef production system, and correlate with increased red blood cell (RBC) factors and BRD development. Further analysis shows that genes involved in cellular energy production and the respiratory electron transport are strongly co-expressed when cattle arrive to beef production system, and correlate with increased eosinophils, a type of immune cell, and weight gain overtime. Additionally, using genes which strongly correlate with BRD development and severity overtime, we identify a novel protein interaction complex that may drive future research for discovering new ways to manage and treat BRD in beef cattle.

systems biology↗

bioRxiv2019

An atlas of the catalytically active liver and spleen kinases in chicken identified by chemoproteomics

Chicken is the first agricultural animal to have a sequenced genome, but current kinase annotations of Gallus gallus are overwhelmingly limited to the predictions generated based on homology or isolated studies focused on specific kinases. Our approach used chemical probes consisting of ATP and ADP derivatives binding to specific lysine residues within the ATP-binding pocket of kinases. Collectively, we identified 188 chicken kinases and corresponding 267 peptides labeled with the ATP and ADP acyl derivatives in chicken spleen and liver. The kinases identified here are publicly available through the database, Chickspress genome browser (http://geneatlas.arl.arizona.edu/cgi-bin/GeneAtlas/chickspress_genes.cgii). Analysis of putative functions of these chicken kinases indicates that kinases identified in this study might regulate hematological system development, necrosis, apoptosis, epithelial neoplasm, and other processes. The identified tissue-specific expression atlas of active chicken kinases along with the ATP binding sites of kinases provide the basis for the development of specific drug targets for multiple chicken diseases as well as starting point for inhibitor selectivity studies in this agriculturally important species. Moreover, this study will support future studies focused on identifying the role of these kinases in chicken growth, metabolism, and disease.

zoology↗

bioRxiv2018

SP1433-1438 operon of Streptococcuspneumoniae regulates metal homeostasis and cellular metabolism during zinc-stress

Streptococcus pneumoniae colonizes the mucosa of the human nasopharynx and is a leading cause of community-acquired pneumonia, acute otitis media, and bacterial meningitis. Metal ion homeostasis is vital to the survival of this pathogen and contributes significantly to both colonization and invasive disease. Microarray and qRT-PCR analysis revealed an upregulation of an uncharacterized operon (SP1433-1438) in pneumococci subjected to metal-chelation by N,N,N,N-tetrakis-(2-Pyridylmethyl)ethylenediamine (TPEN). Supplementation of either zinc or cobalt following TPEN treatment drastically abrogated induction. BLAST analysis predicted this operon to encode two ABC-transporters, sharing homology to a multidrug resistance system (SP1434-1435) and an energy-coupling factor (ECF) transport system (SP1436-1438). Inductively coupled plasma mass spectrometry (ICP-MS) analysis indicated changes in intracellular concentrations of iron, zinc, and manganese ions in a {Delta}1434-8 strain compared to parental T4R. Analysis of the secreted metabolomic profile of the T4R and {Delta}1434-8 strains identified significant changes in pneumococcal glycolytic pathways, indicating a shift towards increased production of acetate. Additionally, proteomic analysis revealed 41 differentially expressed proteins in the {Delta}1434-8 strain, with roughly 20% of them regulated by the global catabolite repressor, CcpA. Based on these findings, we propose that the SP1433-1438 operon is largely involved in the central metabolism of S. pneumoniae during zinc-limitation.\n\nImportanceMetal sequestration is a common strategy utilized by the host immune response as well as antibiotics such as vancomycin to kill invading bacterial pathogens (1). However, pneumococcus is still able to thrive under zinc-limiting conditions. This study describes a previously uncharacterized operon encoding two ABC transport systems that are strongly induced during zinc-limiting conditions. This operon was found to be regulated by a zinc-dependent regulator (SP1433) that functions independently of the overarching AdcR regulon. We have additionally utilized a 2D-NMR approach to analyze the secreted metabolome and have employed proteomic analysis to identify a role for these systems in the maintenance of cellular metabolism. This study provides new information on how Streptococcus pneumoniae responds and adapts to zinc-limiting conditions.

microbiology↗