RESUMO
Botrytis cinerea is a foliar necrotrophic fungal-pathogen capable of infecting >580 genera of plants, is often used as model organism for studying fungal-host interactions. We used RNAseq to study transcriptome of B. cinerea infection on a major (worldwide) vegetable crop, tomato (Solanum lycopersicum). Most previous works explored only few infection stages, using RNA extracted from entire leaf-organ diluting the expression of studied infected region. Many studied B. cinerea infection, on detached organs assuming that similar defense/physiological reactions occurs in the intact plant. We analyzed transcriptome of the pathogen and host in 5 infection stages of whole-plant leaves at the infection site. We supply high quality, pathogen-enriched gene count that facilitates future research of the molecular processes regulating the infection process.
Assuntos
Botrytis/genética , Doenças das Plantas/microbiologia , Solanum lycopersicum/genética , Solanum lycopersicum/microbiologia , Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Interações Hospedeiro-Patógeno , HumanosRESUMO
BACKGROUND: Genomic studies demonstrate that components of virulence mechanisms in filamentous eukaryotic pathogens (FEPs, fungi and oomycetes) of plants are often highly conserved, or found in gene families that include secreted hydrolytic enzymes (e.g., cellulases and proteases) and secondary metabolites (e.g., toxins), central to the pathogenicity process. However, very few large-scale genomic comparisons have utilized complete proteomes from dozens of FEPs to reveal lifestyle-associated virulence mechanisms. Providing a powerful means for exploration, and the discovery of trends in large-scale datasets, network analysis has been used to identify core functions of the primordial cyanobacteria, and ancient evolutionary signatures in oxidoreductases. RESULTS: We used a sequence-similarity network to study components of virulence mechanisms of major pathogenic lifestyles (necrotroph (ic), N; biotroph (ic), B; hemibiotroph (ic), H) in complete pan-proteomes of 65 FEPs and 17 saprobes. Our comparative analysis highlights approximately 190 core functions found in 70% of the genomes of these pathogenic lifestyles. Core functions were found mainly in: transport (in H, N, B cores); carbohydrate metabolism, secondary metabolite synthesis, and protease (H and N cores); nucleic acid metabolism and signal transduction (B core); and amino acid metabolism (H core). Taken together, the necrotrophic core contains functions such as cell wall-associated degrading enzymes, toxin metabolism, and transport, which are likely to support their lifestyle of killing prior to feeding. The biotrophic stealth growth on living tissues is potentially controlled by a core of regulatory functions, such as: small G-protein family of GTPases, RNA modification, and cryptochrome-based light sensing. Regulatory mechanisms found in the hemibiotrophic core contain light- and CO2-sensing functions that could mediate important roles of this group, such as transition between lifestyles. CONCLUSIONS: The selected set of enriched core functions identified in our work can facilitate future studies aimed at controlling FEPs. One interesting example would be to facilitate the identification of the pathogenic potential of samples analyzed by metagenomics. Finally, our analysis offers potential evolutionary scenarios, suggesting that an early-branching saprobe (identified in previous studies) has probably evolved a necrotrophic lifestyle as illustrated by the highest number of shared gene families between saprobes and necrotrophs.
Assuntos
Fungos/genética , Fungos/fisiologia , Redes Reguladoras de Genes , Genômica , Oomicetos/genética , Oomicetos/fisiologia , Plantas/microbiologia , Evolução Molecular , Fungos/metabolismo , Oomicetos/metabolismoRESUMO
UNLABELLED: ProADD, a database for protein aggregation diseases, is developed to organize the data under a single platform to facilitate easy access for researchers. Diseases caused due to protein aggregation and the proteins involved in each of these diseases are integrated. The database helps in classification of proteins involved in the protein aggregation diseases based on sequence and structural analysis. Analysis of proteins can be done to mine patterns prevailing among the aggregating proteins. AVAILABILITY: http://bicmku.in/ProADD.