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Antimicrobial peptides from Capsicum chinense fruits: agronomic alternatives against phytopathogenic fungi.

ABSTRACT: In recent years, the antimicrobial activity of peptides isolated from a wide variety of organs from plant species has been reported. However, a few studies have investigated the potential of antimicrobial peptides (AMPs) found in fruits, especially Capsicum chinense (pepper). The present study aimed to purify and characterize peptides from Capsicum chinense fruits and evaluate their inhibitory activities against different phytopathogenic fungi and also analyze the possible mechanisms of action involved in microbial inhibition. After fruit protein extraction and high-performance liquid chromatography (HPLC), different fractions were obtained, named F1 to F10. Peptides in the F4 and F5 fractions were sequenced and revealed similarity with the plant antimicrobial peptides like non-specific lipid transfer proteins and defensin-like peptide. The F4 and F5 fractions presented strong antimicrobial activity against the fungus Fusarium solani and Fusarium oxysporum, causing toxic effects on these fungi, leading to membrane permeabilization, endogenous reactive oxygen species increase, activation of metacaspase and loss of mitochondrial function.

SUBMITTER: de Azevedo Dos Santos L

PROVIDER: S-EPMC7442975 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Antimicrobial peptides from Capsicum chinense fruits: agronomic alternatives against phytopathogenic fungi.

de Azevedo Dos Santos Layrana L Taveira Gabriel Bonan GB da Silva Marciele Souza MS da Silva Gebara Rodrigo R da Silva Pereira Lídia L Perales Jonas J Teixeira-Ferreira André A de Oliveira Mello Érica É de Oliveira Carvalho André A Rodrigues Rosana R Gomes Valdirene Moreira VM

Bioscience reports 20200801 8

In recent years, the antimicrobial activity of peptides isolated from a wide variety of organs from plant species has been reported. However, a few studies have investigated the potential of antimicrobial peptides (AMPs) found in fruits, especially Capsicum chinense (pepper). The present study aimed to purify and characterize peptides from Capsicum chinense fruits and evaluate their inhibitory activities against different phytopathogenic fungi and also analyze the possible mechanisms of action i ...[more]

PMID: 32785580

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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.

Dataset Information

Antimicrobial peptides from Capsicum chinense fruits: agronomic alternatives against phytopathogenic fungi.

Publications

Antimicrobial peptides from Capsicum chinense fruits: agronomic alternatives against phytopathogenic fungi.

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