In Silico Investigations Of Virulent Gene Transfers In Xanthomonas Oryzae: A Study On Rice Bacterial Leaf Blight Disease.

Abstract

Rice (Oryza sativa L.) is a major global food crop, providing nutrition for nearly half the world's population. India ranks second in both rice production and acreage, with rice contributing nearly 70% of calories in the Indian diet. The rice is susceptible to various diseases caused by fungi, bacteria, nematodes, and viruses, leading to significant crop losses. Bacterial leaf blight (BLB), is a widespread disease caused by the plant pathogenic bacterium Xanthomonas oryzae pv. oryzae, with reports of frequently gaining genes from non-ancestral origins through methods like conjugation and transduction from other species and genera. These laterally transmitted genes (LTGs) enhance the bacterium's adaptability, pathogenicity, and ability to resist host defences. The present study integrates multiple computational methods to find and analyze genes with potential lateral transfer and abnormal properties, providing insights into the evolution and adaptability of Xanthomonas oryzae pv. oryzae. In the present study, a workflow of computational algorithms to identify horizontally transferred genes (HTGs) in bacterial chromosomes was employed. The SeqWord Gene Island Sniffer program predicted 12 genomic islands (GIs) containing genes with non-ancestral features, characterized by decreased GC content and potentially fast-evolving DNA regions. The DFAST server annotated 248 protein-coding sequences from the identified islands, and NCBI BLAST+ executables matched 225 of these proteins with those of Xanthomonas oryzae PXO99^A proteome. MP3 tool predicted 80 pathogenic proteins using the SVM method for analysis. A locally created database of putative horizontally transmitted proteins consisting of nearly 1.3 lakh sequences revealed 20 proteins potentially involved in lateral transfer. Dark Horse web server validated 13 genes of it, and CodonW software assessed anomalous gene nature by correspondence analysis, examining G+C, GC3, and ENc values for 13 anticipated genes compared to overall organism values.