Macrel: antimicrobial peptide screening in genomes and metagenomes

Júnior, Célio Dias Santos; Pan, Shaojun; Zhao, Xing‐Ming; Coelho, Luís Pedro

doi:10.7717/peerj.10555

Cited by 50 publications

(41 citation statements)

References 63 publications

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“…Thus, the 95 potential virtual APPs (see SI8-1 and SI8-7 ) were evaluated by 24 in silico tools (see Table 9 ) to select the best drug-like peptides. We jointly analyze several antiparasitic activity predictions according to AMPDiscover , 37 AMPFun , 38 AMAP , 102 and AxPEP ( 103 ) web servers, toxic/hemolytic effects by all ML models in ToxinPred2 89 and by HemoPI , 90 HemoPred , 104 Happenn, 105 and Macrel , 106 respectively. Other relevant end points such as cell permeability and half-life were screened by ( CellPPD , 107 C2Pred 108 and MLCPP ( 109 )) and ( pLifePred 110 and HLP ( 111 )), respectively, while the most popular immune-toxicity end points (see Table 9 ), like allergenic reactions and aggregation/amylogenicity, were predicted by AlgPred2 , 112 MILAMP , 113 MetAmyl , 114 and others, see Table 9 .…”

Section: Resultsmentioning

confidence: 99%

Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides

et al. 2022

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Antimicrobial peptides (AMPs) have appeared as promising compounds to treat a wide range of diseases. Their clinical potentialities reside in the wide range of mechanisms they can use for both killing microbes and modulating immune responses. However, the hugeness of the AMPs' chemical space (AMPCS), represented by more than 10 65 unique sequences, has represented a big challenge for the discovery of new promising therapeutic peptides and for the identification of common structural motifs. Here, we introduce network science and a similarity searching approach to discover new promising AMPs, specifically antiparasitic peptides (APPs). We exploited the network-based representation of APPs' chemical space (APPCS) to retrieve valuable information by using three network types: chemical space (CSN), half-space proximal (HSPN), and metadata (METN). Some centrality measures were applied to identify in each network the most important and nonredundant peptides. Then, these central peptides were considered as queries (Qs) in group fusion similarity-based searches against a comprehensive collection of known AMPs, stored in the graph database StarPepDB, to propose new potential APPs. The performance of the resulting multiquery similarity-based search models (mQSSMs) was evaluated in five benchmarking data sets of APP/non-APPs. The predictions performed by the best mQSSM showed a strong-tovery-strong performance since their external Matthews correlation coefficient (MCC) values ranged from 0.834 to 0.965. Outstanding MCC values (>0.85) were attained by the mQSSM with 219 Qs from both networks CSN and HSPN with 0.5 as similarity threshold in external data sets. Then, the performance of our best mQSSM was compared with the APPs prediction servers AMPDiscover and AMPFun. The proposed model showed its relevance by outperforming state-of-the-art machine learning models to predict APPs. After applying the best mQSSM and additional filters on the non-APP space from StarPepDB, 95 AMPs were repurposed as potential APP hits. Due to the high sequence diversity of these peptides, different computational approaches were applied to identify relevant motifs for searching and designing new APPs. Lastly, we identified 11 promising APP lead candidates by using our best mQSSMs together with diversity-based network analyses, and 24 web servers for activity/toxicity and drug-like properties. These results support that network-based similarity searches can be an effective and reliable strategy to identify APPs. The proposed models and pipeline are freely available through the StarPep toolbox software at http://mobiosd-hub.com/starpep.

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Section: Resultsmentioning

confidence: 99%

Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides

et al. 2022

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“…AMPs were predicted from the genome contigs using the programme macrel (Meta[genomic] AMPs Classification and REtrievaL) (v0.4.0) [ 45 ], locally installed. The predicted AMPs sequences were converted to an amino acid FASTA file and uploaded to the efi-est programme [ 46 ], which generates an SSN that was uploaded to Cytoscape for the visualization of the relationships among the peptide sequences.…”

Section: Methodsmentioning

confidence: 99%

Unveiling the genomic potential of Pseudomonas type strains for discovering new natural products

Saati‐Santamaría

Sélem-Mójica²,

Peral-Aranega

et al. 2022

Microbial Genomics

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Microbes host a huge variety of biosynthetic gene clusters that produce an immeasurable array of secondary metabolites with many different biological activities such as antimicrobial, anticarcinogenic and antiviral. Despite the complex task of isolating and characterizing novel natural products, microbial genomic strategies can be useful for carrying out these types of studies. However, although genomic-based research on secondary metabolism is on the increase, there is still a lack of reports focusing specifically on the genus Pseudomonas . In this work, we aimed (i) to unveil the main biosynthetic systems related to secondary metabolism in Pseudomonas type strains, (ii) to study the evolutionary processes that drive the diversification of their coding regions and (iii) to select Pseudomonas strains showing promising results in the search for useful natural products. We performed a comparative genomic study on 194 Pseudomonas species, paying special attention to the evolution and distribution of different classes of biosynthetic gene clusters and the coding features of antimicrobial peptides. Using EvoMining, a bioinformatic approach for studying evolutionary processes related to secondary metabolism, we sought to decipher the protein expansion of enzymes related to the lipid metabolism, which may have evolved toward the biosynthesis of novel secondary metabolites in Pseudomonas . The types of metabolites encoded in Pseudomonas type strains were predominantly non-ribosomal peptide synthetases, bacteriocins, N-acetylglutaminylglutamine amides and ß-lactones. Also, the evolution of genes related to secondary metabolites was found to coincide with Pseudomonas species diversification. Interestingly, only a few Pseudomonas species encode polyketide synthases, which are related to the lipid metabolism broadly distributed among bacteria. Thus, our EvoMining-based search may help to discover new types of secondary metabolite gene clusters in which lipid-related enzymes are involved. This work provides information about uncharacterized metabolites produced by Pseudomonas type strains, whose gene clusters have evolved in a species-specific way. Our results provide novel insight into the secondary metabolism of Pseudomonas and will serve as a basis for the prioritization of the isolated strains. This article contains data hosted by Microreact.

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“…Taxonomic annotation of MAGs was performed with gtdbtk version 1.5.1 (Chaumeil et al 2020) and at the read level using Kaiju 1.8.2 (Menzel et al 2016). Identification of AMP sequences was performed using marcel v. 0.3.1 on default parameters (Santos-Júnior et al 2020). AMP sequences with haemolytic properties were verified and classified into functional types by using iAMP-2L platform (Xiao et al 2013).…”

Section: Discussionmentioning

confidence: 99%

A first insight into the Polish Bochnia Salt Mine metagenome

Lach

Królikowska

Baranowska

et al. 2023

Environ Sci Pollut Res

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The Bochnia Salt Mine is one of the oldest mines in Europe. It was established in the thirteenth century, and actively operated until 1990. The mine has been placed on the UNESCO World Heritage List. Previous research describing Polish salt mines has been focused on bioaerosol characteristics and the identification of microorganisms potentially important for human health. The use of Polish salt mines as inhalation chambers for patients of health resorts has also been investigated. Nevertheless, the biodiversity of salt mines associated with biotechnological potential has not been well characterized. The present study paper examines the biodiversity of microorganisms in the Bochnia Salt Mine based on 16S rRNA gene and shotgun sequencing. Biodiversity studies revealed a significantly higher relative abundance of Chlamydiae at the first level of the mine (3.5%) compared to the other levels (< 0.1%). Patescibacteria microorganisms constituted a high percentage (21.6%) in the sample from site RA6. Shotgun sequencing identified 16 unique metagenome-assembled genomes (MAGs). Although one was identified as Halobacterium bonnevillei, the others have not yet been assigned to any species; it is possible that these species may be undescribed. Preliminary analyses of the biotechnological and pharmaceutical potential of microorganisms inhabiting the mine were also performed, and the biosynthetic gene cluster (BGC) profiles and antimicrobial peptide (AMP) coding genes in individual samples were characterized. Hundreds of BGCs and dozens of AMP coding genes were identified in metagenomes. Our findings indicate that Polish salt mines are promising sites for further research aimed at identifying microorganisms that are producers of potentially important substances with biotechnological and pharmaceutical applications.

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Macrel: antimicrobial peptide screening in genomes and metagenomes

Cited by 50 publications

References 63 publications

Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides

Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides

Unveiling the genomic potential of Pseudomonas type strains for discovering new natural products

A first insight into the Polish Bochnia Salt Mine metagenome

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