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Cyclic Lipopeptide Biosynthetic Genes and Products, and Inhibitory Activity of Plant-Associated Bacillus against Phytopathogenic Bacteria.

ABSTRACT: The antibacterial activity against bacterial plant pathogens and its relationships with the presence of the cyclic lipopeptide (cLP) biosynthetic genes ituC (iturin), bmyB (bacillomycin), fenD (fengycin) and srfAA (surfactin), and their corresponding antimicrobial peptide products have been studied in a collection of 64 strains of Bacillus spp. isolated from plant environments. The most frequent antimicrobial peptide (AMP) genes were bmyB, srfAA and fenD (34-50% of isolates). Most isolates (98.4%) produced surfactin isoforms, 90.6% iturins and 79.7% fengycins. The antibacterial activity was very frequent and generally intense among the collection of strains because 75% of the isolates were active against at least 6 of the 8 bacterial plant pathogens tested. Hierarchical and correspondence analysis confirmed the presence of two clearly differentiated groups. One group consisted of Bacillus strains that showed a strong antibacterial activity, presented several cLPs genes and produced several isoforms of cLPs simultaneously, mainly composed of B. subtilis and B. amyloliquefaciens, although the last one was exclusive to this group. Another group was characterized by strains with very low or none antibacterial activity, that showed one or none of the cLP genes and produced a few or none of the corresponding cLPs, and was the most heterogenous group including B. subtilis, B. licheniformis, B. megaterium, B. pumilus, B. cereus and B. thuringiensis, although the last two were exclusive to this group. This work demonstrated that the antagonistic capacity of plant-associated Bacillus against plant pathogenic bacteria is related to the presence of cLP genes and to the production of the corresponding cLPs, and it is mainly associated to the species B. subtilis and B. amyloliquefaciens. Our findings would help to increase the yield and efficiency of screening methods to obtain candidate strains to biocontrol agents with a mechanism of action relaying on the production of antimicrobial cLPs.

SUBMITTER: Mora I

PROVIDER: S-EPMC4449161 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:The use of chemical fungicides against fungal pathogens adversely affects soil and plant health thereby resulting in overall environmental hazards. Therefore, biological source for obtaining antifungal agents is considered as an environment-friendly alternative for controlling fungal pathogens. RESULTS:In this study, seven endophytic bacteria were isolated from sugarcane leaves and screened for its antifungal activity against 10 fungal isolates belonging to the genera Alternaria, Cochliobolus, Curvularia, Fusarium, Neodeightonia, Phomopsis and Saccharicola isolated from diseased leaves of sugarcane. Among the seven bacterial isolates, SCB-1 showed potent antagonistic activity against the tested fungi. Based on the phenotypic data, Fatty Acid Methyl Esters (FAME) and 16S rRNA gene sequence analysis, the isolate SCB-1 was identified as Bacillus subtilis. The bacterial isolate was screened negative for chitinase production; however, chloroform and methanol extracts of the bacterial culture caused significant inhibition in the growth of the fungal isolates on semisolid media. Volatile component assay showed highest inhibitory activity against Saccharicola bicolor (SC1.4). A PCR based study detected the presence of the genes involved in biosynthesis of surfactin, bacillaene, difficidin, macrolactins and fengycin. Mass spectrometric analysis of the bacterial extract detected the presence of antifungal lipopeptide surfactin, but other metabolites were not detected. The biocontrol activity of the bacterial isolate was established when bacterial pretreated mung bean seeds were able to resist Fusarium infection, however, the untreated seeds failed to germinate. CONCLUSION:The antifungal potential of isolate Bacillus subtilis SCB-1 was established against taxonomically diverse fungal pathogens including the genera Saccharicola, Cochliobolus, Alternaria and Fusarium. The potent antifungal compound surfactin as well as volatiles produced by the bacterial isolate could be responsible for its bio-control activity against fungal infections.

Project description:IntroductionAntimicrobial peptides (AMPs) are promising alternatives to traditional antibiotics for combating plant pathogenic bacteria in agriculture and the environment. However, identifying potent AMPs through laborious experimental assays is resource-intensive and time-consuming. To address these limitations, this study presents a bioinformatics approach utilizing machine learning models for predicting and selecting AMPs active against plant pathogenic bacteria.MethodsN-gram representations of peptide sequences with 3-letter and 9-letter reduced amino acid alphabets were used to capture the sequence patterns and motifs that contribute to the antimicrobial activity of AMPs. A 5-fold cross-validation technique was used to train the machine learning models and to evaluate their predictive accuracy and robustness.ResultsThe models were applied to predict putative AMPs encoded by intergenic regions and small open reading frames (ORFs) of the citrus genome. Approximately 7% of the 10,000-peptide dataset from the intergenic region and 7% of the 685,924-peptide dataset from the whole genome were predicted as probable AMPs. The prediction accuracy of the reported models range from 0.72 to 0.91. A subset of the predicted AMPs was selected for experimental test against Spiroplasma citri, the causative agent of citrus stubborn disease. The experimental results confirm the antimicrobial activity of the selected AMPs against the target bacterium, demonstrating the predictive capability of the machine learning models.DiscussionHydrophobic amino acid residues and positively charged amino acid residues are among the key features in predicting AMPs by the Random Forest Algorithm. Aggregation propensity appears to be correlated with the effectiveness of the AMPs. The described models would contribute to the development of effective AMP-based strategies for plant disease management in agricultural and environmental settings. To facilitate broader accessibility, our model is publicly available on the AGRAMP (Agricultural Ngrams Antimicrobial Peptides) server.

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Cyclic Lipopeptide Biosynthetic Genes and Products, and Inhibitory Activity of Plant-Associated Bacillus against Phytopathogenic Bacteria.

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