Bacteriocin Sequences Research Articles

Deep learning neural network development for the classification of bacteriocin sequences produced by lactic acid bacteria

Background The rise of antibiotic-resistant bacteria presents a pressing need for exploring new natural compounds with innovative mechanisms to replace existing antibiotics. Bacteriocins offer promising alternatives for developing therapeutic and preventive strategies in livestock, aquaculture, and human health. Specifically, those produced by LAB are recognized as GRAS and QPS. Methods In this study was used a deep learning neural network for binary classification of bacteriocin amino acid sequences, distinguishing those produced by LAB. The features were extracted using the k-mer method and vector embedding. Ten different groups were tested, combining embedding vectors and k-mers: EV, ‘EV+3-mers’, ‘EV+5-mers’, ‘EV+7-mers’, ‘EV+15-mers’, ‘EV+20-mers’, ‘EV+3-mers+5-mers’, ‘EV+3-mers+7-mers’, ‘EV+5-mers+7-mers’, and ‘EV+15-mers+20-mers’. Results Five sets of 100 characteristic k-mers unique to bacteriocins produced by LAB were obtained for values of k = 3, 5, 7, 15, and 20. Significant difference was observed between using only and concatenation. Specially, ‘5-mers+7-mers+EV ’ group showed superior accuracy and loss results. Employing k-fold cross-validation with k=30, the average results for loss, accuracy, precision, recall, and F1 score were 9.90%, 90.14%, 90.30%, 90.10%, and 90.10% respectively. Folder 22 stood out with 8.50% loss, 91.47% accuracy, and 91.00% precision, recall, and F1 score. Conclusions The model developed in this study achieved consistent results with those seen in the reviewed literature. It outperformed some studies by 3-10%. The lists of characteristic k-mers pave the way to identify new bacteriocins that could be valuable for therapeutic and preventive strategies within the livestock, aquaculture industries, and potentially in human health.

BPAGS: a web application for bacteriocin prediction via feature evaluation using alternating decision tree, genetic algorithm, and linear support vector classifier.

The use of bacteriocins has emerged as a propitious strategy in the development of new drugs to combat antibiotic resistance, given their ability to kill bacteria with both broad and narrow natural spectra. Hence, a compelling requirement arises for a precise and efficient computational model that can accurately predict novel bacteriocins. Machine learning's ability to learn patterns and features from bacteriocin sequences that are difficult to capture using sequence matching-based methods makes it a potentially superior choice for accurate prediction. A web application for predicting bacteriocin was created in this study, utilizing a machine learning approach. The feature sets employed in the application were chosen using alternating decision tree (ADTree), genetic algorithm (GA), and linear support vector classifier (linear SVC)-based feature evaluation methods. Initially, potential features were extracted from the physicochemical, structural, and sequence-profile attributes of both bacteriocin and non-bacteriocin protein sequences. We assessed the candidate features first using the Pearson correlation coefficient, followed by separate evaluations with ADTree, GA, and linear SVC to eliminate unnecessary features. Finally, we constructed random forest (RF), support vector machine (SVM), decision tree (DT), logistic regression (LR), k-nearest neighbors (KNN), and Gaussian naïve Bayes (GNB) models using reduced feature sets. We obtained the overall top performing model using SVM with ADTree-reduced features, achieving an accuracy of 99.11% and an AUC value of 0.9984 on the testing dataset. We also assessed the predictive capabilities of our best-performing models for each reduced feature set relative to our previously developed software solution, a sequence alignment-based tool, and a deep-learning approach. A web application, titled BPAGS (Bacteriocin Prediction based on ADTree, GA, and linear SVC), was developed to incorporate the predictive models built using ADTree, GA, and linear SVC-based feature sets. Currently, the web-based tool provides classification results with associated probability values and has options to add new samples in the training data to improve the predictive efficacy. BPAGS is freely accessible at https://shiny.tricities.wsu.edu/bacteriocin-prediction/.

BaPreS: a software tool for predicting bacteriocins using an optimal set of features

BackgroundAntibiotic resistance is a major public health concern around the globe. As a result, researchers always look for new compounds to develop new antibiotic drugs for combating antibiotic-resistant bacteria. Bacteriocin becomes a promising antimicrobial agent to fight against antibiotic resistance, due to cases of both broad and narrow killing spectra. Sequence matching methods are widely used to identify bacteriocins by comparing them with the known bacteriocin sequences; however, these methods often fail to detect new bacteriocin sequences due to their high diversity. The ability to use a machine learning approach can help find new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. The aim of this work is to develop a machine learning-based software tool called BaPreS (Bacteriocin Prediction Software) using an optimal set of features for detecting bacteriocin protein sequences with high accuracy. We extracted potential features from known bacteriocin and non-bacteriocin sequences by considering the physicochemical and structural properties of the protein sequences. Then we reduced the feature set using statistical justifications and recursive feature elimination technique. Finally, we built support vector machine (SVM) and random forest (RF) models using the selected features and utilized the best machine learning model to implement the software tool.ResultsWe applied BaPreS to an established dataset and evaluated its prediction performance. Acquired results show that the software tool can achieve a prediction accuracy of 95.54% for testing protein sequences. This tool allows users to add new bacteriocin or non-bacteriocin sequences in the training dataset to further enhance the predictive power of the tool. We compared the prediction performance of the BaPreS with a popular sequence matching-based tool and a deep learning-based method, and our software tool outperformed both.ConclusionsBaPreS is a bacteriocin prediction tool that can be used to discover new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. This software tool can be used with Windows, Linux and macOS operating systems. The open-source software package and its user manual are available at https://github.com/suraiya14/BaPreS.

BADASS: BActeriocin-Diversity ASsessment Software

BackgroundBacteriocins are defined as thermolabile peptides produced by bacteria with biological activity against taxonomically related species. These antimicrobial peptides have a wide application including disease treatment, food conservation, and probiotics. However, even with a large industrial and biotechnological application potential, these peptides are still poorly studied and explored. BADASS is software with a user-friendly graphical interface applied to the search and analysis of bacteriocin diversity in whole-metagenome shotgun sequencing data.ResultsThe search for bacteriocin sequences is performed with tools such as BLAST or DIAMOND using the BAGEL4 database as a reference. The putative bacteriocin sequences identified are used to determine the abundance and richness of the three classes of bacteriocins. Abundance is calculated by comparing the reads identified as bacteriocins to the reads identified as 16S rRNA gene using SILVA database as a reference. BADASS has a complete pipeline that starts with the quality assessment of the raw data. At the end of the analysis, BADASS generates several plots of richness and abundance automatically as well as tabular files containing information about the main bacteriocins detected. The user is able to change the main parameters of the analysis in the graphical interface. To demonstrate how the software works, we used four datasets from WMS studies using default parameters. Lantibiotics were the most abundant bacteriocins in the four datasets. This class of bacteriocin is commonly produced by Streptomyces sp.ConclusionsWith a user-friendly graphical interface and a complete pipeline, BADASS proved to be a powerful tool for prospecting bacteriocin sequences in Whole-Metagenome Shotgun Sequencing (WMS) data. This tool is publicly available at https://sourceforge.net/projects/badass/.

Synthetic Peptide Libraries Designed From a Minimal Alpha-Helical Domain of AS-48-Bacteriocin Homologs Exhibit Potent Antibacterial Activity.

The circularized bacteriocin enterocin AS-48 produced by Enterococcus sp. exhibits antibacterial activity through membrane disruption. The membrane-penetrating activity of enterocin AS-48 has been attributed to a specific alpha-helical region on the circular peptide. Truncated, linearized forms containing these domains have been shown to preserve limited bactericidal activity. We utilized the amino acid sequence of the active helical domain of enterocin AS-48 to perform a homology-based search of similar sequences in other bacterial genomes. We identified similar domains in three previously uncharacterized AS-48-like bacteriocin genes in Clostridium sordellii, Paenibacillus larvae, and Bacillus xiamenensis. Enterocin AS-48 and homologs from these bacterial species were used as scaffolds for the design of a minimal peptide library based on the active helical domain of each bacteriocin sequence. 95 synthetic peptide variants of each scaffold peptide, designated Syn-enterocin, Syn-sordellicin, Syn-larvacin, and Syn-xiamensin, were designed and synthesized from each scaffold sequence based on defined biophysical parameters. A total of 384 total peptides were assessed for antibacterial activity against Gram-negative and Gram-positive bacteria. Minimal Inhibitory Concentrations (MICs) as low as 15.6 nM could be observed for the most potent peptide candidate tested, with no significant cytotoxicity to eukaryotic cells. Our work demonstrates for the first time a general workflow of using minimal domains of natural bacteriocin sequences as scaffolds to design and rapidly synthesize a library of bacteriocin-based antimicrobial peptide variants for evaluation.

Discovery of Novel Type II Bacteriocins Using a New High-Dimensional Bioinformatic Algorithm.

Antimicrobial compounds first arose in prokaryotes by necessity for competitive self-defense. In this light, prokaryotes invented the first host defense peptides. Among the most well-characterized of these peptides are class II bacteriocins, ribosomally-synthesized polypeptides produced chiefly by Gram-positive bacteria. In the current study, a tensor search protocol—the BACIIα algorithm—was created to identify and classify bacteriocin sequences with high fidelity. The BACIIα algorithm integrates a consensus signature sequence, physicochemical and genomic pattern elements within a high-dimensional query tool to select for bacteriocin-like peptides. It accurately retrieved and distinguished virtually all families of known class II bacteriocins, with an 86% specificity. Further, the algorithm retrieved a large set of unforeseen, putative bacteriocin peptide sequences. A recently-developed machine-learning classifier predicted the vast majority of retrieved sequences to induce negative Gaussian curvature in target membranes, a hallmark of antimicrobial activity. Prototypic bacteriocin candidate sequences were synthesized and demonstrated potent antimicrobial efficacy in vitro against a broad spectrum of human pathogens. Therefore, the BACIIα algorithm expands the scope of prokaryotic host defense bacteriocins and enables an innovative bioinformatics discovery strategy. Understanding how prokaryotes have protected themselves against microbial threats over eons of time holds promise to discover novel anti-infective strategies to meet the challenge of modern antibiotic resistance.

LABiocin database: A new database designed specifically for Lactic Acid Bacteria bacteriocins

Bacteriocins from lactic acid bacteria (LAB) are successfully applied as natural alternatives to food preservation and to antibiotics; however, information on these antimicrobial peptides (AMPs) is scattered through the literature and databases. Therefore, we developed the LABiocin database, a specialized database on LAB bacteriocins. The database was stored and compiled using MySQL with NetBeans IDE as the platform. Important data are compiled, including bacteriocin name, class, amino acids and nucleic acid sequences, if available. Target microorganisms, origin, status of the producing strains and their culture conditions and extraction and purification methods are also included in this new database. A phylogenetic tree for the mature peptide bacteriocin sequences has also been created.LABiocin is an interactive database with a user-friendly interface that integrates several tools and services and comprises up to 517 LAB bacteriocins. Besides data searching tools, a BLAST tool was integrated into the database to enable the user to perform a homology search against mature peptide sequences. Users can be linked to other databases that contain additional information, particularly about predicted bacteriocin structure and mechanisms of action.The LABiocin database enables comprehensive functional analysis of this special group of AMPs. This would be useful in food preservation and food safety applications and would also have substantial implications for development of new drugs for medical use. LABiocin database is available at labiocin.net.

Common occurrence of antibacterial agents in human intestinal microbiota.

Laboratory experiments have revealed many active mechanisms by which bacteria can inhibit the growth of other organisms. Bacteriocins are a diverse group of natural ribosomally synthesized antimicrobial peptides produced by a wide range of bacteria and which seem to play an important role in mediating competition within bacterial communities. In this study, we have identified and established the structural classification of putative bacteriocins encoded by 317 microbial genomes in the human intestine. On the basis of homologies to available bacteriocin sequences, mainly from lactic acid bacteria, we report the widespread occurrence of bacteriocins across the gut microbiota: 175 bacteriocins were found to be encoded in Firmicutes, 79 in Proteobacteria, 34 in Bacteroidetes, and 25 in Actinobacteria. Bacteriocins from gut bacteria displayed wide differences among phyla with regard to class distribution, net positive charge, hydrophobicity and secondary structure, but the α-helix was the most abundant structure. The peptide structures and physiochemical properties of bacteriocins produced by the most abundant bacteria in the gut, the Firmicutes and the Bacteroidetes, seem to ensure low antibiotic activity and participate in permanent intestinal host defense against the proliferation of harmful bacteria. Meanwhile, the potentially harmful bacteria, including the Proteobacteria, displayed highly effective bacteriocins, probably supporting the virulent character of diseases. These findings highlight the eventual role played by bacteriocins in gut microbial competition and their potential place in antibiotic therapy.

Diversity and dynamics of bacteriocins from human microbiome.

Human commensal microbiota are an important determinant of health and disease of the host. Different human body sites harbour different bacterial microbiota, bacterial communities that maintain a stable balance. However, many of the factors influencing the stabilities of bacterial communities associated with humans remain unknown. In this study, we identified putative bacteriocins produced by human commensal microbiota. Bacteriocins are peptides or proteins with antimicrobial activity that contribute to the stability and dynamics of microbial communities. We employed bioinformatic analyses to identify putative bacteriocin sequences in metagenomic sequences obtained from different human body sites. Prevailing bacterial taxa of the putative bacteriocins producers matched the most abundant organisms in each human body site. Remarkably, we found that samples from different body sites contain different density of putative bacteriocin genes, with the highest in samples from the vagina, the airway, and the oral cavity and the lowest in those from gut. Inherent differences of different body sites thus influence the density and types of bacteriocins produced by commensal bacteria. Our results suggest that bacteriocins play important roles to allow different bacteria to occupy several human body sites, and to establish a long-term commensal relationship with human hosts.

Purification and characterization of Plantaricin ZJ5, a new bacteriocin produced by Lactobacillus plantarum ZJ5.

The aim of this study is to investigate the antimicrobial potential of Lactobacillus plantarum ZJ5, a strain isolated from fermented mustard with a broad range of inhibitory activity against both Gram-positive and Gram-negative bacteria. Here we present the peptide plantaricin ZJ5 (PZJ5), which is an extreme pH and heat-stable. However, it can be digested by pepsin and proteinase K. This peptide has strong activity against Staphylococcus aureus. PZJ5 has been purified using a multi-step process, including ammonium sulfate precipitation, cation-exchange chromatography, hydrophobic interactions and reverse-phase chromatography. The molecular mass of the peptide was found to be 2572.9 Da using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The primary structure of this peptide was determined using amino acid sequencing and DNA sequencing, and these analyses revealed that the DNA sequence translated as a 44-residue precursor containing a 22-amino-acid N-terminal extension that was of the double-glycine type. The bacteriocin sequence exhibited no homology with known bacteriocins when compared with those available in the database, indicating that it was a new class IId bacteriocin. PZJ5 from a food-borne strain may be useful as a promising probiotic candidate.

A ‘bacteriocin PCR array’ for identification of bacteriocin-related structural genes in lactic acid bacteria

Bacteriocins have been identified in many strains of lactic acid bacteria (LAB) which are a source of natural food preservatives and microbial inhibitors. Our objectives were to use a PCR array of primers to identify bacteriocin structural genes in Bac+ LAB. DNA sequence homology at the 5′- and 3′-ends of the various structural genes indicated that non-specific priming may allow PCR amplification of heterologous bacteriocin genes. Successful amplification was obtained by real-time PCR and confirmed by melting curve and agarose gel analysis. Sequence information specific to targeted bacteriocin structural genes from the intra-primer regions of amplimers was compared to sequences residing in GenBank. The bacteriocin PCR array allowed the successful amplification of bacteriocin structural genes from strains of Lactobacillus, Lactococcus, and Pediococcus including one whose amino acid sequence was unable to be determined by Edman degradation analysis. DNA sequence analysis identified as many as 3 bacteriocin structural genes within a given strain, identifying ten unique bacteriocin sequences that were previously uncharacterized (partial homology) and one that was 100% identical to sequences in GenBank. This study provides a rapid approach to sequence and identify bacteriocin structural genes among Bac+ LAB using a microplate bacteriocin PCR array.

BACTIBASE second release: a database and tool platform for bacteriocin characterization

BackgroundBACTIBASE is an integrated open-access database designed for the characterization of bacterial antimicrobial peptides, commonly known as bacteriocins.DescriptionFor its second release, BACTIBASE has been expanded and equipped with additional functions aimed at both casual and power users. The number of entries has been increased by 44% and includes data collected from published literature as well as high-throughput datasets. The database provides a manually curated annotation of bacteriocin sequences. Improvements brought to BACTIBASE include incorporation of various tools for bacteriocin analysis, such as homology search, multiple sequence alignments, Hidden Markov Models, molecular modelling and retrieval through our taxonomy Browser.ConclusionThe provided features should make BACTIBASE a useful tool in food preservation or food safety applications and could have implications for the development of new drugs for medical use. BACTIBASE is available at http://bactibase.pfba-lab-tun.org.

The identification of a low molecular mass bacteriocin, rhamnosin A, produced byLactobacillus rhamnosusstrain 68

This study focuses on the isolation and characterization of a peptide with bacteriocin-like properties isolated from Lactobacillus rhamnosus strain 68, previously identified by 16S rRNA gene sequencing and originating from human gastrointestinal flora. The peptide was isolated from a supernatant of bacteria maintained under restrictive conditions by a combination of ethanol precipitation and reversed-phase chromatography. The molecular mass of the peptide as assessed by mass spectrometry was 6433.8 Da. An isoelectric point of 9.8 was determined by 2D-PAGE. The peptide designated rhamnosin A inhibited Micrococcus lysodeikticus ATCC 4698 but did not inhibit Lactobacillus plantarum 8014 or Lact. plantarum 39268. Inhibitory activity against M. lysodeikticus at concentrations used in this study was shown to be bacteriostatic rather than bacteriolytic or bactericidal. Rhamnosin A retained biological activity after heat treatment (95 degrees C, 30 min) but was sensitive to proteolytic activity of pepsin and trypsin. The N-terminal sequence of rhamnosin A, as determined by Edman degradation and in more detail by blast analysis, did not show identity with any currently available Lact. rhamnosus HN001-translated protein sequences, nor any significant similarity with other sequences in the nonredundant protein sequence database. Being a small, heat-stable, nonlanthionine-containing peptide, rhamnosin A should be categorized as a class II bacteriocin. This study describes a partial bacteriocin sequence isolated from Lact. rhamnosus 68 and broadens our understanding of bacteriocins.

Enhancement of the enterocin CRL35 activity by a synthetic peptide derived from the NH2-terminal sequence.

The enterocin CRL35 biosynthetic gene cluster was cloned and sequenced. The sequence was revealed to be highly identical to that of the mundticin KS gene cluster (S. Kawamoto, J. Shima, R. Sato, T. Eguchi, S. Ohmomo, J. Shibato, N. Horikoshi, K. Takeshita, and T. Sameshima, Appl. Environ. Microbiol. 68:3830-3840, 2002). Short synthetic peptides were designed based on the bacteriocin sequence and were evaluated in antimicrobial competitive assays. The peptide KYYGNGVSCNKKGCS produced an enhancement of enterocin CRL35 antimicrobial activity in a buffer system.

Lactococcin 972: a homodimeric lactococcal bacteriocin whose primary target is not the plasma membrane

Lactococcus lactis subsp. lactis IPLA 972 was shown to produce a bacteriocin which had a bactericidal effect on sensitive lactococci. Production of lactococcin 972 reached a maximum during the late-exponential phase of growth. The bacteriocinogenic activity was heat-sensitive, active in the pH range 40-9.0 and showed low susceptibility to proteases. Purification of the bacteriocin rendered a single polypeptide of 7.5 kDa (monomer) as shown by SDS-PACE. Gels overlaid with a lawn of sensitive bacteria showed inhibitory activity at a point corresponding t o 15 kDa. Changes in the electrophoretic conditions allowed the detection of a band at a position corresponding to that expected for a hypothetical dimer. Sequencing of the NH,-terminal end of lactococcin 972 revealed the sequence NH,-EGTWQHGYGV, which is not related to any other bacteriocin sequence present in the databases. Finally, lactococcin 972 did not induce the efflux of compounds previously incorporated into the cytoplasm of sensitive cultures nor did it inhibit macromolecular synthesis,suggesting that, in contrast to other bacteriocins, its primary target is not the plasma membrane.

Simple method of purification and sequencing of a bacteriocin produced by Pediococcus acidilactici UL5.

A bacteriocin produced by a strain of Pediococcus acidilactici was successfully purified sequentially by acid extraction (at pH 2) and reverse-phase high-performance liquid chromatography (HPLC). Cell extracts of derivative strains deficient in bacteriocin production exhibited a similar HPLC elution profile to the active extracts except for the two peaks containing bacteriocin activity. The sequence of the antibacterial peptide consisted of 44 amino acid residues of which 42 were identified, and its molecular weight was 4624 Da, as determined by mass spectrometry. Moreover, according to the molecular weight of the peptide, the unidentified residues in the bacteriocin sequence must correspond to two tryptophan residues, confirming that the peptide isolated from Ped. acidilactici UL5 is pediocin PA-1. However, oxidized forms of the bacteriocin produced during storage also showed bacteriocin activity and resulted in a second peak with activity in the chromatograms. HPLC chromatograms of cell surface preparations from the active and from the deficient strains were confirmed by capillary electrophoresis. The purification method used is simple and effective in comparison with traditional methods, permitting a selective recovery of cell-associated bacteriocin at low pH, and its isolation in pure form for sequencing.

Purification and Partial Characterization of Lacticin 481, a Lanthionine-Containing Bacteriocin Produced by Lactococcus lactis subsp. lactis CNRZ 481

Lacticin 481, a bacteriocin produced during the growth of Lactococcus lactis subsp. lactis CNRZ 481, was purified sequentially by ammonium sulfate precipitation, gel filtration, and preparative and analytical reversed-phase high-pressure liquid chromatography. Ammonium sulfate precipitations resulted in a 455-fold increase in total lacticin 481 activity. The entire purification protocol led to a 107, 506-fold increase in the specific activity of lacticin 481. On the basis of its electrophoretic pattern in sodium dodecyl sulfate-polyacrylamide gels, lacticin 481 appeared as a single peptide band of 1.7 kDa. However, dimers of 3.4 kDa also exhibiting lacticin activity were detected. Derivatives of the lacticin-producing strain which did not produce lacticin 481 (Bac) were sensitive to this bacteriocin (Bac) and failed to produce the 1.7-kDa band. Amino acid composition analysis of purified lacticin 481 revealed the presence of lanthionine residues, suggesting that lacticin 481 is a member of the lantibiotic family of antimicrobial peptides. Seven residues (K G G S G V I) were sequenced from the N-terminal portion of lacticin 481, and these did not shown any homology with nisin or other known bacteriocin sequences.