Molecular characterization of Indian pathotypes of Puccinia striiformis f. sp. tritici and multigene phylogenetic analysis to establish inter- and intraspecific relationships

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most devastating diseases of wheat (Triticum spp.) worldwide. Indian isolates were characterised based on their phenotypic reaction on differential hosts carrying different Yr genes. Based on virulence/avirulence structure, isolates were characterised into ten different pathotypes viz. 70S0-2, 67S64, 70S4, 66S0, 70S64, 66S64-1, 38S102, 47S102, 46S119, and 78S84. These Indian pathotypes of P. striiformis f. sp. tritici and 38 pathotypes of other rust species (P. graminis tritici and P. triticina) were used in this study to analyze their molecular phylogenetic relationship. The nucleotides of rDNA-ITS, partial β-tubulin and ketopantoate reductase genes of all the pathotypes were sequenced directly after PCR. Based on sequence data of rDNA-ITS and β-tubulin, three phylogenetic groups corresponding to three different species of Puccinia were obtained. Asian isolates formed a distinct evolutionary lineage than from those derived from USA. The sequence similarity of Indian pathotypes with other Asian (China and Iran) isolates indicated the same origin of pathotypes. The results will allow rapid identification of Indian P.striiformis f. sp. tritici pathotypes causing stripe rust in wheat, assist in making predictions regarding potential rust pathotypes, and identifying sources of resistance to the disease in advance.

Rapid detection of Puccinia triticina causing leaf rust of wheat by PCR and loop mediated isothermal amplification

Leaf rust of wheat caused by Puccinia triticina has significant impact on wheat production worldwide. Effective and quick detection methodologies are required to mitigate yield loss and time constraints associated with monitoring and management of leaf rust of wheat. In the present study, detection of P. triticina has been simplified by developing a rapid, reliable, efficient and visual colorimetric method i.e., loop mediated isothermal amplification of DNA (LAMP). Based on in silico analysis of P. triticina genome, PTS68, a simple sequence repeat was found highly specific to leaf rust fungus. A marker (PtRA68) was developed and its specificity was validated through PCR technique which gave a unique and sharp band of 919 bp in P. triticina pathotypes only. A novel gene amplification method LAMP which enables visual detection of pathogen by naked eye was developed for leaf rust pathogen. A set of six primers was designed from specific region of P. triticina and conditions were optimised to complete the observation process in 60 minutes at 65o C. The assay developed in the study could detect presence of P. triticina on wheat at 24 hpi (pre-symptomatic stage) which was much earlier than PCR without requiring thermal cycler. Sensitivity of LAMP assay developed in the study was 100 fg which was more sensitive than conventional PCR (50 pg) and equivalent to qPCR (100 fg). The protocol developed in the study was utilized for detection of leaf rust infected samples collected from different wheat fields. LAMP based colorimetric detection assay showed sky blue color in positive reaction and violet color in negative reaction after addition of 120 μM hydroxyl napthol blue (HNB) solution to reaction mixture. Similarly, 0.6 mg Ethidium bromide/ml was added to LAMP products, placed on transilluminator to witness full brightness in positive reaction and no such brightness could be seen in negative reaction mixture. Further, LAMP products spread in a ladder like banding pattern in gel electrophoresis. Our assay is significantly faster than the conventional methods used in the identification of P. triticina. The assay developed in the study shall be very much useful in the development of diagnostic kit for monitoring disease, creation of prediction model and efficient management of disease.

Whole Genome Sequencing of Fusarium fujikuroi Provides Insight into the Role of Secretory Proteins and Cell Wall Degrading Enzymes in Causing Bakanae Disease of Rice

Fusarium fujikuroi causing bakanae disease has emerged as one of the major pathogen of rice across the world. The study aims to comparative genomic analysis of Fusarium fujikuroi isolates and identification of the secretary proteins of the fungus involved in rice pathogenesis. In the present study, F. fujikuroi isolate "F250" was sequenced with an assembly size of 42.47 Mb providing coverage of 96.89% on reference IMI58289 genome. A total of 13,603 protein-coding genes were predicted from genome assembly. The average gene density in the F. fujikuroi genome was 315.10 genes per Mb with an average gene length of 1.67 kb. Additionally, 134,374 single nucleotide polymorphisms (SNPs) are identified against IMI58289 isolate, with an average SNP density of 3.11 per kb of genome. Repetitive elements represent approximately 270,550 bp, which is 0.63% of the total genome. In total, 3,109 simple sequence repeats (SSRs), including 302 compound SSRs are identified in the 8,656 scaffolds. Comparative analysis of the isolates of F. fujikuroi revealed that they shared a total of 12,240 common clusters with F250 showing higher similarity with IMI58289. A total of 1,194 secretory proteins were identified in its genome among which there were 356 genes encoding carbohydrate active enzymes (CAZymes) capable for degradation of complex polysaccharides. Out of them glycoside hydrolase (GH) families were most prevalent (41%) followed by carbohydrate esterase (CE). Out of them CE8 (4 genes), PL1 (10 genes), PL3 (5 genes), and GH28 (8 genes) were prominent plant cell wall degrading enzymes families in F250 secretome. Besides this, 585 genes essential for the pathogen-host interactions were also identified. Selected genes were validated through quantitative real-time PCR analyses in resistant and susceptible genotypes of rice at different days of inoculation. The data offers a better understanding of F. fujikuroi genome and will help us enhance our knowledge on Fusarium fujikuroi-rice interactions.

Integrated gene co-expression network analysis in the growth phase of Mycobacterium tuberculosis reveals new potential drug targets

We have carried out weighted gene co-expression network analysis of Mycobacterium tuberculosis to gain insights into gene expression architecture during log phase growth. The differentially expressed genes between at least one pair of 11 different M. tuberculosis strains as source of biological variability were used for co-expression network analysis. This data included genes with highest coefficient of variation in expression. Five distinct modules were identified using topological overlap based clustering. All the modules together showed significant enrichment in biological processes: fatty acid biosynthesis, cell membrane, intracellular membrane bound organelle, DNA replication, Quinone biosynthesis, cell shape and peptidoglycan biosynthesis, ribosome and structural constituents of ribosome and transposition. We then extracted the co-expressed connections which were supported either by transcriptional regulatory network or STRING database or high edge weight of topological overlap. The genes trpC, nadC, pitA, Rv3404c, atpA, pknA, Rv0996, purB, Rv2106 and Rv0796 emerged as top hub genes. After overlaying this network on the iNJ661 metabolic network, the reactions catalyzed by 15 highly connected metabolic genes were knocked down in silico and evaluated by Flux Balance Analysis. The results showed that in 12 out of 15 cases, in 11 more than 50% of reactions catalyzed by genes connected through co-expressed connections also had altered fluxes. The modules 'Turquoise', 'Blue' and 'Red' also showed enrichment in essential genes. We could map 152 of the previously known or proposed drug targets in these modules and identified 15 new potential drug targets based on their high degree of co-expressed connections and strong correlation with module eigengenes.

Integrative immunoinformatics for Mycobacterial diseases in R platform

The sequencing of genomes of the pathogenic Mycobacterial species causing pulmonary and extrapulmonary tuberculosis, leprosy and other atypical mycobacterial infections, offer immense opportunities for discovering new therapeutics and identifying new vaccine candidates. Enhanced RV, which uses additional algorithms to Reverse Vaccinology (RV), has increased potential to reduce likelihood of undesirable features including allergenicity and immune cross reactivity to host. The starting point for MycobacRV database construction includes collection of known vaccine candidates and a set of predicted vaccine candidates identified from the whole genome sequences of 22 mycobacterium species and strains pathogenic to human and one non-pathogenic Mycobacterium tuberculosis H37Ra strain. These predicted vaccine candidates are the adhesins and adhesin-like proteins obtained using SPAAN at Pad > 0.6 and screening for putative extracellular or surface localization characteristics using PSORTb v.3.0 at very stringent cutoff. Subsequently, these protein sequences were analyzed through 21 publicly available algorithms to obtain Orthologs, Paralogs, BetaWrap Motifs, Transmembrane Domains, Signal Peptides, Conserved Domains, and similarity to human proteins, T cell epitopes, B cell epitopes, Discotopes and potential Allergens predictions. The Enhanced RV information was analysed in R platform through scripts following well structured decision trees to derive a set of nonredundant 233 most probable vaccine candidates. Additionally, the degree of conservation of potential epitopes across all orthologs has been obtained with reference to the M. tuberculosis H37Rv strain, the most commonly used strain in M. tuberculosis studies. Utilities for the vaccine candidate search and analysis of epitope conservation across the orthologs with reference to M. tuberculosis H37Rv strain are available in the mycobacrvR package in R platform accessible from the "Download" tab of MycobacRV webserver. MycobacRV an immunoinformatics database of known and predicted mycobacterial vaccine candidates has been developed and is freely available at http://mycobacteriarv.igib.res.in.