amPEPpy 1.0: a portable and accurate antimicrobial peptide prediction tool

Lawrence, Travis J; Carper, Dana L.; Spangler, Margaret K.; Carrell, Alyssa A.; Rush, Tomás A.; Minter, Stephen J.; Weston, David J.; Labbé, Jessy

doi:10.1093/bioinformatics/btaa917

Cited by 75 publications

(36 citation statements)

References 20 publications

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“…For the antimicrobial assessment, we ran the predicted proteome of Nc2 through an antimicrobial prediction pipeline (https://github.com/danielzmbp/appred) consisting of several tools: Antimicrobial Peptide Scanner vr. 2, AmpGram and amPEPpy (Burdukiewicz et al, 2020; Lawrence et al, 2020; Veltri et al, 2018). These machine learning-based models attempt de novo prediction of antimicrobial activity not by similarity but by the compound features of the amino acid sequence.…”

Section: Methodsmentioning

confidence: 99%

Proteins released into the plant apoplast by the obligate parasitic protist Albugo selectively repress phyllosphere-associated bacteria

Gómez-Pérez

Schmid

Chaudhry

et al. 2022

Preprint

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Biotic and abiotic interactions shape natural microbial communities. The mechanisms behind microbe-microbe interactions, particularly those protein-based, are not well understood. We hypothesize that secreted proteins are a powerful and highly specific toolset to shape and defend plant niches. We have studied Albugo candida, an obligate plant parasite from the protist Oomycota phylum, for its potential to modulate the growth of bacteria through secretion of proteins into the apoplast. Amplicon sequencing and network analysis of Albugo-infected and uninfected samples revealed an abundance of negative correlations between Albugo and other phyllosphere microbes. Analysis of the apoplastic proteome of Albugo colonized leaves combined with machine-learning predictors enabled the selection of candidates for heterologous expression and study of their inhibitory activity. We found that three of the candidate proteins show selective antimicrobial activity on gram-positive bacteria isolated from Arabidopsis thaliana and that these inhibited bacteria are important for the stability of the community structure. We could ascribe the antibacterial activity of the candidates to intrinsically disordered regions and positively correlate it with net charge. This is the first report of protist proteins with antimicrobial activity under apoplastic conditions that therefore are potential biocontrol tools for targeted manipulations of the microbiome.

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Section: Methodsmentioning

confidence: 99%

Proteins released into the plant apoplast by the obligate parasitic protist Albugo selectively repress phyllosphere-associated bacteria

Gómez-Pérez

Schmid

Chaudhry

et al. 2022

Preprint

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“…Sequences with a length smaller than 100 amino acids were retrieved from the predicted M. complanata proteome using Linux (code repository: https://github.com/ vhelizarraga/Fire_coral_analysis.git, accessed on 2 September 2021). Potential AMPs were identified from these sequences with amPEPpy [64]. The antimicrobial activity was inferred by implementing a random forest classifier using the distribution descriptor set from the Global Protein Sequence Descriptors.…”

Section: Prediction Of Ampsmentioning

confidence: 99%

New Insights into the Toxin Diversity and Antimicrobial Activity of the “Fire Coral” Millepora complanata

Hérnandez-Elizárraga

Ocharán-Mercado

Olguín-López

et al. 2022

Toxins

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To date, few studies have been carried out aimed at characterizing the toxins synthesized by hydrocorals of the genus Millepora. The purpose of this study was to explore the toxin diversity and antibacterial activity of the “fire coral” M. complanata using a transcriptomic data mining approach. In addition, the cytolytic and antibacterial activities of the M. complanata nematocyst proteome were experimentally confirmed. Cytolysins were predicted from the transcriptome by comparing against the Animal Toxin Annotation Project database, resulting in 190 putative toxins, including metalloproteases, hemostasis-impairing toxins, phospholipases, among others. The M. complanata nematocyst proteome was analyzed by 1D and 2D electrophoresis and zymography. The zymograms showed different zones of cytolytic activity: two zones of hemolysis at ~25 and ~205 kDa, two regions corresponding to phospholipase A2 (PLA2) activity around 6 and 25 kDa, and a proteolytic zone was observed between 50 and 205 kDa. The hemolytic activity of the proteome was inhibited in the presence of PLA2 and proteases inhibitors, suggesting that PLA2s, trypsin, chymotrypsin, serine-proteases, and matrix metalloproteases are responsible for the hemolysis. On the other hand, antimicrobial peptide sequences were retrieved from their transcripts with the amPEPpy software. This analysis revealed the presence of homologs to SK84, cgUbiquitin, Ubiquicidin, TroTbeta4, SPINK9-v1, and Histone-related antimicrobials in the transcriptome of this cnidarian. Finally, by employing disk diffusion and microdilution assays, we found that the nematocyst peptidome of M. complanata showed inhibitory activity against both Gram-positive and Gram-negative bacteria including S. enteritidis, P. perfectomarina, E. coli, and C. xerosis, among others. This is the first transcriptomic data mining analysis to explore the diversity of the toxins synthesized by an organism of the genus Millepora. Undoubtedly, this work provides information that will broaden our general understanding of the structural richness of cnidarian toxins.

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“…Additionally, each genome was interrogated by the software tool amPEPpy, which uses a random forest classifier to predict putative antimicrobial peptides based on protein sequence characteristics often attributed to antimicrobials (e.g., small open reading frames, positively charged, etc.) (Lawrence et al, 2020).…”

Section: Genomic Prediction Tools Highlight Natural Product Diversity Across Trichoderma Speciesmentioning

confidence: 99%

“…To date, there were more than 30 computational methods for AMP prediction and identification as of 2021 (Xu et al, 2021). Of those computational methods, amPEPpy is a userfriendly, open-source, portable, multi-threaded command-line application for predicting AMPs through genome-based screening using a random forest classifier (Lawrence et al, 2020). amPEPpy was validated as predicting AMPs more The backbone enzyme type, the function of the predicted metabolite, whether it has been identified in Trichoderma species, and which fungi produce these metabolites are described.…”

Section: Antimicrobial Peptides Exploration Through Genomic Mining and Computational Analysismentioning

confidence: 99%

Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications

Rush

Shrestha

Meena

et al. 2021

Front. Fungal Biol.

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Natural products derived from microbes are crucial innovations that would help in reaching sustainability development goals worldwide while achieving bioeconomic growth. Trichoderma species are well-studied model fungal organisms used for their biocontrol properties with great potential to alleviate the use of agrochemicals in agriculture. However, identifying and characterizing effective natural products in novel species or strains as biological control products remains a meticulous process with many known challenges to be navigated. Integration of recent advancements in various “omics” technologies, next generation biodesign, machine learning, and artificial intelligence approaches could greatly advance bioprospecting goals. Herein, we propose a roadmap for assessing the potential impact of already known or newly discovered Trichoderma species for biocontrol applications. By screening publicly available Trichoderma genome sequences, we first highlight the prevalence of putative biosynthetic gene clusters and antimicrobial peptides among genomes as an initial step toward predicting which organisms could increase the diversity of natural products. Next, we discuss high-throughput methods for screening organisms to discover and characterize natural products and how these findings impact both fundamental and applied research fields.

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amPEPpy 1.0: a portable and accurate antimicrobial peptide prediction tool

Cited by 75 publications

References 20 publications

Proteins released into the plant apoplast by the obligate parasitic protist Albugo selectively repress phyllosphere-associated bacteria

Proteins released into the plant apoplast by the obligate parasitic protist Albugo selectively repress phyllosphere-associated bacteria

New Insights into the Toxin Diversity and Antimicrobial Activity of the “Fire Coral” Millepora complanata

Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications

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