DBETH: a Database of Bacterial Exotoxins for Human

A comprehensive in silico analysis of putative outer membrane and secretory hydrolases from the pathogenic Leptospira: Possible implications in pathogenesis

Outer surface/membrane and virulent secretory proteins are primarily crucial for pathogenesis. Secreted and outer membrane hydrolases of many pathogens play an important role in attenuating the host immune system. Leptospira expresses many such proteins, and few have been characterized to display various roles, including host immune evasion. However, identification, classification, characterization, and elucidation of the possible role of Leptospira's outer membrane and secretory hydrolases have yet to be explored. In the present study, we used bioinformatics tools to predict exported proteins from the pathogenic Leptospira proteome. Moreover, we focused on secretory and outer membrane putative hydrolases from the exported proteins to generate a deeper understanding. Our analysis yielded four putative outer/secretory hydrolases, LIC_10995, LIC_11183, LIC_11463, and LIC_12988, containing α/β hydrolase fold and displayed similarity with lipase motif. Moreover, their conservation analysis of the predicted hydrolases across the spectrum of different Leptospira species showed high clustering with the pathogenic species. Outer membrane and secretory proteins with lipolytic activity may have a role in pathogenesis. This is the first bioinformatics analysis of secretory and outer membrane α/β hydrolases from leptospiral species. However, experimental studies are indeed required to unravel this possibility.

Toxinome-the bacterial protein toxin database

IMPORTANCE

Microbes use protein toxins as important tools to attack neighboring cells, microbial or eukaryotic, and for self-killing when attacked by viruses. These toxins work through different mechanisms to inhibit cell growth or kill cells. Microbes also use antitoxin proteins to neutralize the toxin activities. Here, we developed a comprehensive database called Toxinome of nearly two million toxins and antitoxins that are encoded in 59,475 bacterial genomes. We described the distribution of bacterial toxins and identified that they are depleted by bacteria that live in hot and cold temperatures. We found 5,161 cases in which toxins and antitoxins are densely clustered in bacterial genomes and termed these areas "Toxin Islands." The Toxinome database is a useful resource for anyone interested in toxin biology and evolution, and it can guide the discovery of new toxins.

Hypothetical Proteins of Mycoplasma synoviae Reannotation and Expression Changes Identified via RNA-Sequencing

Mycoplasma synoviae infection rates in chickens are increasing worldwide. Genomic studies have considerably improved our understanding of M. synoviae biology and virulence. However, approximately 20% of the predicted proteins have unknown functions. In particular, the M. synoviae ATCC 25204 genome has 663 encoding DNA sequences, among which 155 are considered encoding hypothetical proteins (HPs). Several of these genes may encode unknown virulence factors. This study aims to reannotate all 155 proteins in M. synoviae ATCC 25204 to predict new potential virulence factors using currently available databases and bioinformatics tools. Finally, 125 proteins were reannotated, including enzymes (39%), lipoproteins (10%), DNA-binding proteins (6%), phase-variable hemagglutinin (19%), and other protein types (26%). Among 155 proteins, 28 proteins associated with virulence were detected, five of which were reannotated. Furthermore, HP expression was compared before and after the M. synoviae infection of cells to identify potential virulence-related proteins. The expression of 14 HP genes was upregulated, including that of five virulence-related genes. Our study improved the functional annotation of M. synoviae ATCC 25204 from 76% to 95% and enabled the discovery of potential virulence factors in the genome. Moreover, 14 proteins that may be involved in M. synoviae infection were identified, providing candidate proteins and facilitating the exploration of the infection mechanism of M. synoviae.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

I am better than I look: genome based safety assessment of the probiotic Lactiplantibacillus plantarum IS-10506

BACKGROUND

Safety of probiotic strains that are used in human and animal trials is a prerequisite. Genome based safety assessment of probiotics has gained popularity due its cost efficiency and speed, and even became a part of national regulation on foods containing probiotics in Indonesia. However, reliability of the safety assessment based only on a full genome sequence is not clear. Here, for the first time, we sequenced, assembled, and analysed the genome of the probiotic strain Lactiplantibacillus plantarum IS-10506, that was isolated from dadih, a traditional fermented buffalo milk. The strain has already been used as a probiotic for more than a decade, and in several clinical trials proven to be completely safe.

METHODS

The genome of the probiotic strain L. plantarum IS-10506 was sequenced using Nanopore sequencing technology, assembled, annotated and screened for potential harmful (PH) and beneficial genomic features. The presence of the PH features was assessed from general annotation, as well as with the use of specialised tools. In addition, PH regions in the genome were compared to all other probiotic and non-probiotic L. plantarum strains available in the NCBI RefSeq database.

RESULTS

For the first time, a high-quality complete genome of L. plantarum IS-10506 was obtained, and an extensive search for PH and a beneficial signature was performed. We discovered a number of PH features within the genome of L. plantarum IS-10506 based on the general annotation, including various antibiotic resistant genes (AMR); however, with a few exceptions, bioinformatics tools specifically developed for AMR detection did not confirm their presence. We further demonstrated the presence of the detected PH genes across multiple L. plantarum strains, including probiotics, and overall high genetic similarities between strains.

CONCLUSION

The genome of L. plantarum IS-10506 is predicted to have several PH features. However, the strain has been utilized as a probiotic for over a decade in several clinical trials without any adverse effects, even in immunocompromised children with HIV infection and undernourished children. This implies the presence of PH feature signatures within the probiotic genome does not necessarily indicate their manifestation during administration. Importantly, specialized tools for the search of PH features were found more robust and should be preferred over manual searches in a general annotation.

Characterization and comprehensive genome analysis of novel bacteriophage, vB_Kpn_ZCKp20p, with lytic and anti-biofilm potential against clinical multidrug-resistant Klebsiella pneumoniae

Introduction

The rise of infections by antibiotic-resistant bacterial pathogens is alarming. Among these, Klebsiella pneumoniae is a leading cause of death by hospital-acquired infections, and its multidrug-resistant strains are flagged as a global threat to human health, which necessitates finding novel antibiotics or alternative therapies. One promising therapeutic alternative is the use of virulent bacteriophages, which specifically target bacteria and coevolve with them to overcome potential resistance. Here, we aimed to discover specific bacteriophages with therapeutic potential against multiresistant K. pneumoniae clinical isolates.

Methods and Results

Out of six bacteriophages that we isolated from urban and medical sewage, phage vB_Kpn_ZCKp20p had the broadest host range and was thus characterized in detail. Transmission electron microscopy suggests vB_Kpn_ZCKp20p to be a tailed phage of the siphoviral morphotype. In vitro evaluation indicated a high lytic efficiency (30 min latent period and burst size of ∼100 PFU/cell), and extended stability at temperatures up to 70°C and a wide range of (2-12) pH. Additionally, phage vB_Kpn_ZCKp20p possesses antibiofilm activity that was evaluated by the crystal violet assay and was not cytotoxic to human skin fibroblasts. The whole genome was sequenced and annotated, uncovering one tRNA gene and 33 genes encoding proteins with assigned functions out of 85 predicted genes. Furthermore, comparative genomics and phylogenetic analysis suggest that vB_Kpn_ZCKp20p most likely represents a new species, but belongs to the same genus as Klebsiella phages ZCKP8 and 6691. Comprehensive genomic and bioinformatics analyses substantiate the safety of the phage and its strictly lytic lifestyle.

Conclusion

Phage vB_Kpn_ZCKp20p is a novel phage with potential to be used against biofilm-forming K. pneumoniae and could be a promising source for antibacterial and antibiofilm products, which will be individually studied experimentally in future studies.

Distinctive signatures of pathogenic and antibiotic resistant potentials in the hadal microbiome

BACKGROUND

Hadal zone of the deep-sea trenches accommodates microbial life under extreme energy limitations and environmental conditions, such as low temperature, high pressure, and low organic matter down to 11,000 m below sea level. However, microbial pathogenicity, resistance, and adaptation therein remain unknown. Here we used culture-independent metagenomic approaches to explore the virulence and antibiotic resistance in the hadal microbiota of the Mariana Trench.

RESULTS

The results indicate that the 10,898 m Challenger Deep bottom sediment harbored prosperous microbiota with contrasting signatures of virulence factors and antibiotic resistance, compared with the neighboring but shallower 6038 m steep wall site and the more nearshore 5856 m Pacific basin site. Virulence genes including several famous large translocating virulence genes (e.g., botulinum neurotoxins, tetanus neurotoxin, and Clostridium difficile toxins) were uniquely detected in the trench bottom. However, the shallower and more nearshore site sediment had a higher abundance and richer diversity of known antibiotic resistance genes (ARGs), especially for those clinically relevant ones (e.g., fosX, sul1, and TEM-family extended-spectrum beta-lactamases), revealing resistance selection under anthropogenic stresses. Further analysis of mobilome (i.e., the collection of mobile genetic elements, MGEs) suggests horizontal gene transfer mediated by phage and integrase as the major mechanism for the evolution of Mariana Trench sediment bacteria. Notably, contig-level co-occurring and taxonomic analysis shows emerging evidence for substantial co-selection of virulence genes and ARGs in taxonomically diverse bacteria in the hadal sediment, especially for the Challenger Deep bottom where mobilized ARGs and virulence genes are favorably enriched in largely unexplored bacteria.

CONCLUSIONS

This study reports the landscape of virulence factors, antibiotic resistome, and mobilome in the sediment and seawater microbiota residing hadal environment of the deepest ocean bottom on earth. Our work unravels the contrasting and unique features of virulence genes, ARGs, and MGEs in the Mariana Trench bottom, providing new insights into the eco-environmental and biological processes underlying microbial pathogenicity, resistance, and adaptative evolution in the hadal environment.

Identification and Characterization of vB_PreP_EPr2, a Lytic Bacteriophage of Pan-Drug Resistant Providencia rettgeri

Providencia rettgeri is an emerging opportunistic Gram-negative pathogen with reports of increasing antibiotic resistance. Pan-drug resistant (PDR) P. rettgeri infections are a growing concern, demonstrating a need for the development of alternative treatment options which is fueling a renewed interest in bacteriophage (phage) therapy. Here, we identify and characterize phage vB_PreP_EPr2 (EPr2) with lytic activity against PDR P. rettgeri MRSN 845308, a clinical isolate that carries multiple antibiotic resistance genes. EPr2 was isolated from an environmental water sample and belongs to the family Autographiviridae, subfamily Studiervirinae and genus Kayfunavirus, with a genome size of 41,261 base pairs. Additional phenotypic characterization showed an optimal MOI of 1 and a burst size of 12.3 ± 3.4 PFU per bacterium. EPr2 was determined to have a narrow host range against a panel of clinical P. rettgeri strains. Despite this fact, EPr2 is a promising lytic phage with potential for use as an alternative therapeutic for treatment of PDR P. rettgeri infections.

An updated review on food-derived bioactive peptides: Focus on the regulatory requirements, safety, and bioavailability

Food-derived bioactive peptides (BAPs) are recently utilized as functional food raw materials owing to their potential health benefits. Although there is a huge amount of scientific research about BAPs' identification, purification, characterization, and physiological functions, and subsequently, many BAPs have been marketed, there is a paucity of review on the regulatory requirements, bioavailability, and safety of BAPs. Thus, this review focuses on the toxic peptides that could arise from their primary proteins throughout protein extraction, protein pretreatment, and BAPs' formulation. Also, the influences of BAPs' length and administration dosage on safety are summarized. Lastly, the challenges and possibilities in BAPs' bioavailability and regulatory requirements in different countries were also presented. Results revealed that the human studies of BAPs are essential for approvals as healthy food and to prevent the consumers from misinformation and false promises. The BAPs that escape the gastrointestinal tract epithelium and move to the stomach are considered good peptides and get circulated into the blood using different pathways. In addition, the hydrophobicity, net charge, molecular size, length, amino acids composition/sequences, and structural characteristics of BAPs are critical for bioavailability, and appropriate food-grade carriers can enhance it. The abovementioned features are also vital to optimize the solubility, water holding capacity, emulsifying ability, and foaming property of BAPs in food products. In the case of safety, the possible allergenic and toxic peptides often exhibit physiological functions and could be produced during the hydrolysis of food proteins. It was also noted that the production of iso-peptides bonds and undesirable Maillard reaction might occur during protein extraction, sample pretreatments, and peptide synthesis.

Reannotation of Mycoplasma hyopneumoniae hypothetical proteins revealed novel potential virulence factors

Mycoplasma hyopneumoniae is a bacterium that inhabits the swine respiratory tract, causing porcine enzootic pneumonia, which generates significant economic losses to the swine industry worldwide. The knowledge on M. hyopneumoniae biology and virulence have been significantly increased by genomics studies. However, around 30% of the predicted proteins remained of unknown function so far. According to the original annotation, the genome of M. hyopneumoniae 7448, a Brazilian pathogenic strain, had 693 coding DNA sequences, 244 of which were annotated as coding for hypothetical or uncharacterized proteins. Among them, there may be still several genes coding for unknown virulence factors. Therefore, this study aimed to functionally reannotate the whole set of 244 M. hyopneumoniae 7448 proteins of unknown function based on currently available database and bioinformatic tools, in order to predict novel potential virulence factors. Predictions of physicochemical properties, subcellular localization, function, overall association to virulence and antigenicity are provided. With that, 159 out of the set of 244 proteins of unknown function had a putative function associated to them, allowing identification of novel enzymes, membrane transporters, lipoproteins, DNA-binding proteins and adhesins. Furthermore, 139 proteins were generally associated to virulence, 14 of which had a function assigned and were differentially expressed between pathogenic and non-pathogenic strains of M. hyopneumoniae. Moreover, all extracellular or cytoplasmic membrane predicted proteins had putative epitopes identified. Overall, these analyses improved the functional annotation of M. hyopneumoniae 7448 genome from 65% to 87% and allowed the identification of new potential virulence factors.

Phage Annotation Guide: Guidelines for Assembly and High-Quality Annotation

All sequencing projects of bacteriophages (phages) should seek to report an accurate and comprehensive annotation of their genomes. This article defines 14 questions for those new to phage genomics that should be addressed before submitting a genome sequence to the International Nucleotide Sequence Database Collaboration or writing a publication.

Identical sequences found in distant genomes reveal frequent horizontal transfer across the bacterial domain

Horizontal gene transfer (HGT) is an essential force in microbial evolution. Despite detailed studies on a variety of systems, a global picture of HGT in the microbial world is still missing. Here, we exploit that HGT creates long identical DNA sequences in the genomes of distant species, which can be found efficiently using alignment-free methods. Our pairwise analysis of 93,481 bacterial genomes identified 138,273 HGT events. We developed a model to explain their statistical properties as well as estimate the transfer rate between pairs of taxa. This reveals that long-distance HGT is frequent: our results indicate that HGT between species from different phyla has occurred in at least 8% of the species. Finally, our results confirm that the function of sequences strongly impacts their transfer rate, which varies by more than three orders of magnitude between different functional categories. Overall, we provide a comprehensive view of HGT, illuminating a fundamental process driving bacterial evolution.

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides

Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop accurate machine learning models for ACP prediction. In this study, features were extracted from the three-dimensional (3D) structure of peptides to develop the model, compared to most of the previous computational models, which are based on sequence information. In order to develop ACPs with more potency, more selectivity and less toxicity, the model for predicting ACPs, hemolytic peptides and toxic peptides were established by peptides 3D structure separately. Multiple datasets were collected according to whether the peptide sequence was chemically modified. After feature extraction and screening, diverse algorithms were used to build the model. Twelve models with excellent performance (Acc > 90%) in the ACPs mixed datasets were used to form a hybrid model to predict the candidate ACPs, and then the optimal model of hemolytic peptides (Acc = 73.68%) and toxic peptides (Acc = 85.5%) was used for safety prediction. Novel ACPs were found by using those models, and five peptides were randomly selected to determine their anticancer activity and toxic side effects in vitro experiments.

PathoFact: a pipeline for the prediction of virulence factors and antimicrobial resistance genes in metagenomic data

BACKGROUND

Pathogenic microorganisms cause disease by invading, colonizing, and damaging their host. Virulence factors including bacterial toxins contribute to pathogenicity. Additionally, antimicrobial resistance genes allow pathogens to evade otherwise curative treatments. To understand causal relationships between microbiome compositions, functioning, and disease, it is essential to identify virulence factors and antimicrobial resistance genes in situ. At present, there is a clear lack of computational approaches to simultaneously identify these factors in metagenomic datasets.

RESULTS

Here, we present PathoFact, a tool for the contextualized prediction of virulence factors, bacterial toxins, and antimicrobial resistance genes with high accuracy (0.921, 0.832 and 0.979, respectively) and specificity (0.957, 0.989 and 0.994). We evaluate the performance of PathoFact on simulated metagenomic datasets and perform a comparison to two other general workflows for the analysis of metagenomic data. PathoFact outperforms all existing workflows in predicting virulence factors and toxin genes. It performs comparably to one pipeline regarding the prediction of antimicrobial resistance while outperforming the others. We further demonstrate the performance of PathoFact on three publicly available case-control metagenomic datasets representing an actual infection as well as chronic diseases in which either pathogenic potential or bacterial toxins are hypothesized to play a role. In each case, we identify virulence factors and AMR genes which differentiated between the case and control groups, thereby revealing novel gene associations with the studied diseases.

CONCLUSION

PathoFact is an easy-to-use, modular, and reproducible pipeline for the identification of virulence factors, bacterial toxins, and antimicrobial resistance genes in metagenomic data. Additionally, our tool combines the prediction of these pathogenicity factors with the identification of mobile genetic elements. This provides further depth to the analysis by considering the genomic context of the pertinent genes. Furthermore, PathoFact's modules for virulence factors, toxins, and antimicrobial resistance genes can be applied independently, thereby making it a flexible and versatile tool. PathoFact, its models, and databases are freely available at https://pathofact.lcsb.uni.lu . Video abstract.

Antibiotics create a shift from mutualism to competition in human gut communities with a longer-lasting impact on fungi than bacteria

BACKGROUND

Antibiotic treatment has a well-established detrimental effect on the gut bacterial composition, but effects on the fungal community are less clear. Bacteria in the lumen of the gastrointestinal tract may limit fungal colonization and invasion. Antibiotic drugs targeting bacteria are therefore seen as an important risk factor for fungal infections and induced allergies. However, antibiotic effects on gut bacterial-fungal interactions, including disruption and resilience of fungal community compositions, were not investigated in humans. We analysed stool samples collected from 14 healthy human participants over 3 months following a 6-day antibiotic administration. We integrated data from shotgun metagenomics, metatranscriptomics, metabolomics, and fungal ITS2 sequencing.

RESULTS

While the bacterial community recovered mostly over 3 months post treatment, the fungal community was shifted from mutualism at baseline to competition. Half of the bacterial-fungal interactions present before drug intervention had disappeared 3 months later. During treatment, fungal abundances were associated with the expression of bacterial genes with functions for cell growth and repair. By extending the metagenomic species approach, we revealed bacterial strains inhibiting the opportunistic fungal pathogen Candida albicans. We demonstrated in vitro how C. albicans pathogenicity and host cell damage might be controlled naturally in the human gut by bacterial metabolites such as propionate or 5-dodecenoate.

CONCLUSIONS

We demonstrated that antibacterial drugs have long-term influence on the human gut mycobiome. While bacterial communities recovered mostly 30-days post antibacterial treatment, the fungal community was shifted from mutualism towards competition. Video abstract.

Nano-Inspired Technologies for Peptide Delivery

Nano-inspired technologies offer unique opportunities to treat numerous diseases by using therapeutic peptides. Therapeutic peptides have attractive pharmacological profiles and can be manufactured at relatively low costs. The major advantages of using a nanodelivery approach comprises significantly lower required dosages compared to systemic delivery, and thus reduced toxicity and immunogenicity. The combination of therapeutic peptides with delivery peptides and nanoparticles or small molecule drugs offers systemic treatment approaches, instead of aiming for single biological targets or pathways. This review article discusses exemplary state-of-the-art nanosized delivery systems for therapeutic peptides and antibodies, as well as their biochemical and biophysical foundations and emphasizes still remaining challenges. The competition between using different nanoplatforms, such as liposome-, hydrogel-, polymer-, silica nanosphere-, or nanosponge-based delivery systems is still "on" and no clear frontrunner has emerged to date.

In Silico Identification of Probable Drug and Vaccine Candidates Against Antibiotic-Resistant Acinetobacter baumannii

Acinetobacter baumannii is known as a Gram-negative bacterium that has become one of the most important health problems due to antibiotic resistance. Today, numerous efforts are being made to find new antibiotics against this nosocomial pathogen. As an alternative solution, finding bacterial target(s), necessary for survival and spread of most resistant strains, can be a benefit exploited in drug and vaccine design. In this study, a list of extensive drug-resistant and carbapenem-resistant (multidrug resistant) A. bumannii strains with complete sequencing of genome were prepared and common hypothetical proteins (HPs) composed of more than 200 amino acids were selected. Then, a number of bioinformatics tools were combined for functional assignments of HPs using their sequence. Overall, among 18 in silico investigated proteins, the results showed that 7 proteins implicated in transcriptional regulation, pilus assembly, protein catabolism, fatty acid biosynthesis, adhesion, urea catalysis, and hydrolysis of phosphate monoesters have theoretical potential of involvement in successful survival and pathogenesis of A. baumannii. In addition, immunological analyses with prediction softwares indicated 4 HPs to be probable vaccine candidates. The outcome of this work will be helpful to find novel vaccine design candidates and therapeutic targets for A. baumannii through experimental investigations.

Advanced Proteomics as a Powerful Tool for Studying Toxins of Human Bacterial Pathogens

Exotoxins contribute to the infectious processes of many bacterial pathogens, mainly by causing host tissue damages. The production of exotoxins varies according to the bacterial species. Recent advances in proteomics revealed that pathogenic bacteria are capable of simultaneously producing more than a dozen exotoxins. Interestingly, these toxins may be subject to post-transcriptional modifications in response to environmental conditions. In this review, we give an outline of different bacterial exotoxins and their mechanism of action. We also report how proteomics contributed to immense progress in the study of toxinogenic potential of pathogenic bacteria over the last two decades.

Bioinformatic Exploration of Metal-Binding Proteome of Zoonotic Pathogen Orientia tsutsugamushi

Metal ions are involved in many essential biological processes and are crucial for the survival of all organisms. Identification of metal-binding proteins (MBPs) of human affecting pathogens may provide the blueprint for understanding biological metal usage and their putative roles in pathogenesis. This study is focused on the analysis of MBPs from Orientia tsutsugamushi (Ott), a causal agent of scrub typhus in humans. A total of 321 proteins were predicted as putative MBPs, based on sequence search and three-dimensional structure analysis. Majority of proteins could bind with magnesium, and the order of metal binding was Mg > Ca > Zn > Mn > Fe > Cd > Ni > Co > Cu, respectively. The predicted MBPs were functionally classified into nine broad classes. Among them, gene expression and regulation, metabolism, cell signaling, and transport classes were dominant. It was noted that the putative MBPs were localized in all subcellular compartments of Ott, but majorly found in the cytoplasm. Additionally, it was revealed that out of 321 predicted MBPs 245 proteins were putative bacterial toxins and among them, 98 proteins were nonhomologous to human proteome. Sixty putative MBPs showed the ability to interact with drug or drug-like molecules, which indicate that they may be used as broad-spectrum drug targets. These predicted MBPs from Ott could play vital role(s) in various cellular activities and virulence, hence may serve as plausible therapeutic targets to design metal-based drugs to curtail its infection.

Connecting environmental exposure and neurodegeneration using cheminformatics and high resolution mass spectrometry: potential and challenges

Connecting chemical exposures over a lifetime to complex chronic diseases with multifactorial causes such as neurodegenerative diseases is an immense challenge requiring a long-term, interdisciplinary approach. Rapid developments in analytical and data technologies, such as non-target high resolution mass spectrometry (NT-HR-MS), have opened up new possibilities to accomplish this, inconceivable 20 years ago. While NT-HR-MS is being applied to increasingly complex research questions, there are still many unidentified chemicals and uncertainties in linking exposures to human health outcomes and environmental impacts. In this perspective, we explore the possibilities and challenges involved in using cheminformatics and NT-HR-MS to answer complex questions that cross many scientific disciplines, taking the identification of potential (small molecule) neurotoxicants in environmental or biological matrices as a case study. We explore capturing literature knowledge and patient exposure information in a form amenable to high-throughput data mining, and the related cheminformatic challenges. We then briefly cover which sample matrices are available, which method(s) could potentially be used to detect these chemicals in various matrices and what remains beyond the reach of NT-HR-MS. We touch on the potential for biological validation systems to contribute to mechanistic understanding of observations and explore which sampling and data archiving strategies may be required to form an accurate, sustained picture of small molecule signatures on extensive cohorts of patients with chronic neurodegenerative disorders. Finally, we reflect on how NT-HR-MS can support unravelling the contribution of the environment to complex diseases.

ccPDB 2.0: an updated version of datasets created and compiled from Protein Data Bank

ccPDB 2.0 (http://webs.iiitd.edu.in/raghava/ccpdb) is an updated version of the manually curated database ccPDB that maintains datasets required for developing methods to predict the structure and function of proteins. The number of datasets compiled from literature increased from 45 to 141 in ccPDB 2.0. Similarly, the number of protein structures used for creating datasets also increased from ~74 000 to ~137 000 (PDB March 2018 release). ccPDB 2.0 provides the same web services and flexible tools which were present in the previous version of the database. In the updated version, links of the number of methods developed in the past few years have also been incorporated. This updated resource is built on responsive templates which is compatible with smartphones (mobile, iPhone, iPad, tablets etc.) and large screen gadgets. In summary, ccPDB 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about datasets.

Gut colonization by a novel Clostridium species is associated with the onset of epizootic rabbit enteropathy

Epizootic rabbit enteropathy (ERE) represents one of the most devastating diseases affecting rabbit farms. Previous studies showing transmissibility of disease symptoms through oral inoculation of intestinal contents from sick animals suggested a bacterial infectious origin for ERE. However, no etiological agent has been identified yet. On the other hand, ERE is associated with major changes in intestinal microbial communities, pinpointing dysbiosis as an alternative cause for the disease. To better understand the role of intestinal bacteria in ERE development, we have performed a prospective longitudinal study in which intestinal samples collected from the same animals before, during and after disease onset were analyzed using high-throughput sequencing. Changes in hundreds of bacterial groups were detected after the initiation of ERE. In contrast, before ERE onset, the microbiota from rabbits that developed ERE did not differ from those that remained healthy. Notably, an expansion of a single novel Clostridium species (Clostridium cuniculi) was detected the day of ERE onset. C. cuniculi encodes several putative toxins and it is phylogenetically related to the two well-characterized pathogens C. botulinum and C. perfringens. Our results are consistent with a bacterial infectious origin of ERE and discard dysbiosis as the initial trigger of the disease. Although experimental validation is required, results derived from sequencing analysis, propose a key role of C. cuniculi in ERE initiation.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

Role of Temperate Bacteriophage ϕ20617 on Streptococcus thermophilus DSM 20617T Autolysis and Biology

Streptococcus thermophilus DSM 20167^T showed autolytic behavior when cultured in lactose- and sucrose-limited conditions. The amount of cell lysis induced was inversely related to the energetic status of the cells, as demonstrated by exposing cells to membrane-uncoupling and glycolysis inhibitors. Genome sequence analysis of strain DSM 20617^T revealed the presence of a pac-type temperate bacteriophage, designated Φ20617, whose genomic organization and structure resemble those of temperate streptococcal bacteriophages. The prophage integrated at the 3'-end of the gene encoding the glycolytic enzyme enolase (eno), between eno and the lipoteichoic acid synthase-encoding gene ltaS, affecting their transcription. Comparative experiments conducted on the wild-type strain and a phage-cured derivative strain revealed that the cell-wall integrity of the lysogenic strain was compromised even in the absence of detectable cell lysis. More importantly, adhesion to solid surfaces and heat resistance were significantly higher in the lysogenic strain than in the phage-cured derivative. The characterization of the phenotype of a lysogenic S. thermophilus and its phage-cured derivative is relevant to understanding the ecological constraints that drive the stable association between a temperate phage and its bacterial host.

Discovery of novel bacterial toxins by genomics and computational biology

Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes.

In silico analysis of protein toxin and bacteriocins from Lactobacillus paracasei SD1 genome and available online databases

Lactobacillus paracasei SD1 is a potential probiotic strain due to its ability to survive several conditions in human dental cavities. To ascertain its safety for human use, we therefore performed a comprehensive bioinformatics analysis and characterization of the bacterial protein toxins produced by this strain. We report the complete genome of Lactobacillus paracasei SD1 and its comparison to other Lactobacillus genomes. Additionally, we identify and analyze its protein toxins and antimicrobial proteins using reliable online database resources and establish its phylogenetic relationship with other bacterial genomes. Our investigation suggests that this strain is safe for human use and contains several bacteriocins that confer health benefits to the host. An in silico analysis of protein-protein interactions between the target bacteriocins and the microbial proteins gtfB and luxS of Streptococcus mutans was performed and is discussed here.

Characterization of prophages of Lactococcus garvieae

This report describes the morphological characterization and genome analysis of an induced prophage (PLg-TB25) from a dairy strain of Lactococcus garvieae. The phage belongs to the Siphoviridae family and its morphology is typical of other lactococcal phages. A general analysis of its genome did not reveal similarities with other lactococcal phage genomes, confirming its novelty. However, similarities were found between genes of its morphogenesis cluster and genes of Gram-positive bacteria, suggesting that this phage genome resulted from recombination events that took place in a heterogeneous microbial environment. An in silico search for other prophages in 16 L. garvieae genomes available in public databases, uncovered eight seemingly complete prophages in strains isolated from dairy and fish niches. Genome analyses of these prophages revealed three novel L. garvieae phages. The remaining prophages had homology to phages of Lactococcus lactis (P335 group) suggesting a close relationship between these lactococcal species. The similarity in GC content of L. garvieae prophages to the genomes of L. lactis phages further supports the hypothesis that these phages likely originated from the same ancestor.

Exoproteomics of Pathogens: Analysis of Toxins and Other Virulence Factors by Proteomics

Pathogens are known to release in their environment a large range of toxins and other virulence factors. Their pathogenicity relies on this arsenal of exoproteins and their orchestrated release upon changing environmental conditions. Exoproteomics aims at describing and quantifying the proteins found outside of the cells, thus takes advantage of the most recent methodologies of next-generation proteomics. This approach has been applied with great success to a variety of pathogens increasing the fundamental knowledge on pathogenicity. In this chapter, we describe how the exoproteome should be prepared and handled for high-throughput identification of exoproteins and their quantitation by label-free shotgun proteomics. We also mentioned some bioinformatics tools for extracting information such as toxin similarity search.

Complete Genome Sequence of Brevibacterium linens SMQ-1335

Brevibacterium linens is one of the main bacteria found in the smear of surface-ripened cheeses. The genome of the industrial strain SMQ-1335 was sequenced using PacBio. It has 4,209,935 bp, a 62.6% G+C content, 3,848 open reading frames, and 61 structural RNAs. A new type I restriction-modification system was identified.

MOCAT2: a metagenomic assembly, annotation and profiling framework

MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assignments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes.

AVAILABILITY AND IMPLEMENTATION

MOCAT2 is implemented in Perl 5 and Python 2.7, designed for 64-bit UNIX systems and offers support for high-performance computer usage via LSF, PBS or SGE queuing systems; source code is freely available under the GPL3 license at http://mocat.embl.de

CONTACT

: bork@embl.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of virulence factors and antibiotic resistance markers using bacterial genomics

In recent years, the number of multidrug-resistant bacteria has increased rapidly and several epidemics were signaled in different regions of the world. Faced with this situation that presents a major global public health concern, the development and the use of new and rapid technologies is more than urgent. The use of the next-generation sequencing platforms by microbiologists and infectious disease specialists has allowed great progress in the medical field. Here, we review the usefulness of whole-genome sequencing for the detection of virulence and antibiotic resistance associated genes.

Draft Genome Sequence of Streptococcus sp. X13SY08, Isolated from Murray Cod (Maccullochella peelii peelii)

Streptococcus sp. X13SY08, isolated from freshwater Murray cod fish, likely presents a novel species of Streptococcus. Here, we present an annotated draft genome sequence of this species, which will improve our understanding of its physiology and pathogenesis.

A virulent phage infecting Lactococcus garvieae, with homology to Lactococcus lactis phages

A new virulent phage belonging to the Siphoviridae family and able to infect Lactococcus garvieae strains was isolated from compost soil. Phage GE1 has a prolate capsid (56 by 38 nm) and a long noncontractile tail (123 nm). It had a burst size of 139 and a latent period of 31 min. Its host range was limited to only two L. garvieae strains out of 73 tested. Phage GE1 has a double-stranded DNA genome of 24,847 bp containing 48 predicted open reading frames (ORFs). Putative functions could be assigned to only 14 ORFs, and significant matches in public databases were found for only 17 ORFs, indicating that GE1 is a novel phage and its genome contains several new viral genes and encodes several new viral proteins. Of these 17 ORFs, 16 were homologous to deduced proteins of virulent phages infecting the dairy bacterium Lactococcus lactis, including previously characterized prolate-headed phages. Comparative genome analysis confirmed the relatedness of L. garvieae phage GE1 to L. lactis phages c2 (22,172 bp) and Q54 (26,537 bp), although its genome organization was closer to that of phage c2. Phage GE1 did not infect any of the 58 L. lactis strains tested. This study suggests that phages infecting different lactococcal species may have a common ancestor.

Towards New Drug Targets? Function Prediction of Putative Proteins of Neisseria meningitidis MC58 and Their Virulence Characterization

Neisseria meningitidis is a Gram-negative aerobic diplococcus, responsible for a variety of meningococcal diseases. The genome of N. meningitidis MC58 is comprised of 2114 genes that are translated into 1953 proteins. The 698 genes (∼35%) encode hypothetical proteins (HPs), because no experimental evidence of their biological functions are available. Analyses of these proteins are important to understand their functions in the metabolic networks and may lead to the discovery of novel drug targets against the infections caused by N. meningitidis. This study aimed at the identification and categorization of each HP present in the genome of N. meningitidis MC58 using computational tools. Functions of 363 proteins were predicted with high accuracy among the annotated set of HPs investigated. The reliably predicted 363 HPs were further grouped into 41 different classes of proteins, based on their possible roles in cellular processes such as metabolism, transport, and replication. Our studies revealed that 22 HPs may be involved in the pathogenesis caused by this microorganism. The top two HPs with highest virulence scores were subjected to molecular dynamics (MD) simulations to better understand their conformational behavior in a water environment. We also compared the MD simulation results with other virulent proteins present in N. meningitidis. This study broadens our understanding of the mechanistic pathways of pathogenesis, drug resistance, tolerance, and adaptability for host immune responses to N. meningitidis.

Proteome-scale identification and characterization of mitochondria targeting proteins of Mycobacterium avium subspecies paratuberculosis: Potential virulence factors modulating host mitochondrial function

Mycobacterium avium subsp. paratuberculosis is the etiological agent of Johne's Disease among ruminants. During the course of infection, it expresses a number of proteins for its successful persistence inside the host that cause variety of physiological abnormalities in the host. Mitochondrion is one of the attractive targets for pathogenic bacteria. Employing a proteome-wide sequence and structural signature based approach we have identified 46 M. avium subsp. paratuberculosis proteins as potential targets for the host mitochondrial targeting. These may act as virulence factors modulating mitochondrial physiology for bacterial survival and immune evasion inside the host cells.

Complete Genome Sequence of Streptococcus thermophilus SMQ-301, a Model Strain for Phage-Host Interactions

Streptococcus thermophilus is used by the dairy industry to manufacture yogurt and several cheeses. Using PacBio and Illumina platforms, we sequenced the genome of S. thermophilus SMQ-301, the host of several virulent phages. The genome is composed of 1,861,792 bp and contains 2,037 genes, 67 tRNAs, and 18 rRNAs.

Peptide toxicity prediction

Last decade has witnessed the revival of interest in peptides as potential therapeutics candidates. However, one of the bottlenecks in the success of therapeutic peptides in clinics is their toxicity towards eukaryotic cells. Therefore, considerable efforts have been made over the years both in wet and dry lab to overcome this limitation. With the advances in peptide synthesis, now it is possible to fine-tune the physicochemical properties of peptides by incorporating several chemical modifications and thus to optimize the peptide functionality in order to minimize the toxicity without compromising their therapeutic activity. Also various in silico tools for peptide toxicity prediction and peptide designing have been developed, which facilitates designing of therapeutic peptides with desired toxicity. In this chapter, we have discussed both wet lab and dry lab approaches used to optimize peptide toxicity. More emphasis has been given to describe the in silico method, ToxinPred, to predict the toxicity of peptide and about how to design a peptide or protein with desired toxicity by mutating minimum number of amino acids.

Bio/chemoinformatics in India: an outlook

With the advent of significant establishment and development of Internet facilities and computational infrastructure, an overview on bio/chemoinformatics is presented along with its multidisciplinary facts, promises and challenges. The Government of India has paved the way for more profound research in biological field with the use of computational facilities and schemes/projects to collaborate with scientists from different disciplines. Simultaneously, the growth of available biomedical data has provided fresh insight into the nature of redundant and compensatory data. Today, bioinformatics research in India is characterized by a powerful grid computing systems, great variety of biological questions addressed and the close collaborations between scientists and clinicians, with a full spectrum of focuses ranging from database building and methods development to biological discoveries. In fact, this outlook provides a resourceful platform highlighting the funding agencies, institutes and industries working in this direction, which would certainly be of great help to students seeking their career in bioinformatics. Thus, in short, this review highlights the current bio/chemoinformatics trend, educations, status, diverse applicability and demands for further development.

First Complete Genome Sequence of Staphylococcus xylosus, a Meat Starter Culture and a Host to Propagate Staphylococcus aureus Phages

Staphylococcus xylosus is a bacterial species used in meat fermentation and a commensal microorganism found on animals. We present the first complete circular genome from this species. The genome is composed of 2,757,557 bp, with a G+C content of 32.9%, and contains 2,514 genes and 79 structural RNAs.

A multi-omic analysis of an Enterococcus faecium mutant reveals specific genetic mutations and dramatic changes in mRNA and protein expression

BACKGROUND

For a long time, Enterococcus faecium was considered a harmless commensal of the mammalian gastrointestinal (GI) tract and was used as a probiotic in fermented foods. In recent decades, E. faecium has been recognised as an opportunistic pathogen that causes diseases such as neonatal meningitis, urinary tract infections, bacteremia, bacterial endocarditis and diverticulitis. E. faecium could be taken into space with astronauts and exposed to the space environment. Thus, it is necessary to observe the phenotypic and molecular changes of E. faecium after spaceflight.

RESULTS

An E. faecium mutant with biochemical features that are different from those of the wild-type strain was obtained from subculture after flight on the SHENZHOU-8 spacecraft. To understand the underlying mechanism causing these changes, the whole genomes of both the mutant and the WT strains were sequenced using Illumina technology. The genomic comparison revealed that dprA, a recombination-mediator gene, and arpU, a gene associated with cell wall growth, were mutated. Comparative transcriptomic and proteomic analyses showed that differentially expressed genes or proteins were involved with replication, recombination, repair, cell wall biogenesis, glycometabolism, lipid metabolism, amino acid metabolism, predicted general function and energy production/conversion.

CONCLUSION

This study analysed the comprehensive genomic, transcriptomic and proteomic changes of an E. faecium mutant from subcultures that were loaded on the SHENZHOU-8 spacecraft. The implications of these gene mutations and expression changes and their underlying mechanisms should be investigated in the future. We hope that the current exploration of multiple "-omics" analyses of this E. faecium mutant will provide clues for future studies on this opportunistic pathogen.

In silico approach for predicting toxicity of peptides and proteins

Background

Over the past few decades, scientific research has been focused on developing peptide/protein-based therapies to treat various diseases. With the several advantages over small molecules, including high specificity, high penetration, ease of manufacturing, peptides have emerged as promising therapeutic molecules against many diseases. However, one of the bottlenecks in peptide/protein-based therapy is their toxicity. Therefore, in the present study, we developed in silico models for predicting toxicity of peptides and proteins.

Description

We obtained toxic peptides having 35 or fewer residues from various databases for developing prediction models. Non-toxic or random peptides were obtained from SwissProt and TrEMBL. It was observed that certain residues like Cys, His, Asn, and Pro are abundant as well as preferred at various positions in toxic peptides. We developed models based on machine learning technique and quantitative matrix using various properties of peptides for predicting toxicity of peptides. The performance of dipeptide-based model in terms of accuracy was 94.50% with MCC 0.88. In addition, various motifs were extracted from the toxic peptides and this information was combined with dipeptide-based model for developing a hybrid model. In order to evaluate the over-optimization of the best model based on dipeptide composition, we evaluated its performance on independent datasets and achieved accuracy around 90%. Based on above study, a web server, ToxinPred has been developed, which would be helpful in predicting (i) toxicity or non-toxicity of peptides, (ii) minimum mutations in peptides for increasing or decreasing their toxicity, and (iii) toxic regions in proteins.

Conclusion

ToxinPred is a unique in silico method of its kind, which will be useful in predicting toxicity of peptides/proteins. In addition, it will be useful in designing least toxic peptides and discovering toxic regions in proteins. We hope that the development of ToxinPred will provide momentum to peptide/protein-based drug discovery (http://crdd.osdd.net/raghava/toxinpred/).

Draft genome sequence of Bacillus cereus strain LCT-BC244

Bacillus cereus is a prevalent, soil-dwelling, Gram-positive bacterium. Some strains are harmful to humans and cause food-borne illness, while other strains can be beneficial as probiotics for animals. To gain insight into the bacterial genetic determinants, we report the genome sequence of a strain, LCT-BC244, which was isolated from CGMCC 1.230.