BacARscan: A Comprehensive and Interactive Web-Resource to Discern Antibiotic Resistance Gene Diversity in –Omics Datasets

2021 ◽  
Author(s):  
Deeksha Pandey ◽  
Bandana Kumari ◽  
Neelja Singhal ◽  
Manish Kumar
Keyword(s):  
Antibiotic Resistance ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Resistance Mechanism ◽  
Antibiotic Resistance Genes ◽  
Metagenomic Data ◽  
Clinical Samples ◽  
Antibiotics Resistance ◽  
Web Resource ◽  
Proteomic Data

Abstract Regular surveillance of antibiotic resistance genes (ARGs) is important to understand the emergence and epidemiology of antibiotic resistance (AR) in clinical and environmental niches. With diminishing costs, NGS technologies are anticipated to replace classical microbiological and molecular methods for determination of AR. One major hindrance underlying identification and annotation of ARGs from WGS data is that a major part of genome databases contain fragmented genes/genomes (due to incomplete assembly). Herein, we propose a web resource of Bacterial ARGs, named as BacARscan (Bacterial Antibiotic Resistance scan), to detect, predict and characterize ARGs in metagenomic, genomic and proteomic data. The current version of BacARscan comprises 254 ARG models, each annotated with a resistant profile against different classes of antibiotics, resistance mechanism etc. Benchmarking on a combined dataset of AR and non-AR proteins found 92% precision & 95% F-measure. BacARscan can also discriminate between the protein families that are homologous but not all families are involved in the AR. BacARscan identified more ARGs in (a) gut microbiome and (b) datasets comprising short read genomic and proteomic sequences of ESKAPE pathogens. Analysis of clinical metagenomic data indicated its potential to complement and/or supplement WGS based identification of ARGs in clinical samples. BacARscan standalone software and web-server are freely available at http://proteininformatics.org/mkumar/bacarscan and github repository (https://github.com/University-of-Delhi-south-campus/BacARscan).

scholarly journals Metagenomics Analysis Reveals the Microbial Communities, Antimicrobial Resistance Gene Diversity and Potential Pathogen Transmission Risk of Two Different Landfills in China

Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 230
Author(s):  
Shan Wan ◽  
Min Xia ◽  
Jie Tao ◽  
Yanjun Pang ◽  
Fugen Yu ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Microbial Communities ◽  
Resistance Gene ◽  
Resistance Genes ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Pathogen Transmission ◽  
Transmission Risk ◽  
Antimicrobial Resistance Gene

In this study, we used a metagenomic approach to analyze microbial communities, antibiotic resistance gene diversity, and human pathogenic bacterium composition in two typical landfills in China. Results showed that the phyla Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in the two landfills, and archaea and fungi were also detected. The genera Methanoculleus, Lysobacter, and Pseudomonas were predominantly present in all samples. sul2, sul1, tetX, and adeF were the four most abundant antibiotic resistance genes. Sixty-nine bacterial pathogens were identified from the two landfills, with Klebsiella pneumoniae, Bordetella pertussis, Pseudomonas aeruginosa, and Bacillus cereus as the major pathogenic microorganisms, indicating the existence of potential environmental risk in landfills. In addition, KEGG pathway analysis indicated the presence of antibiotic resistance genes typically associated with human antibiotic resistance bacterial strains. These results provide insights into the risk of pathogens in landfills, which is important for controlling the potential secondary transmission of pathogens and reducing workers’ health risk during landfill excavation.

scholarly journals HflXr, a homolog of a ribosome-splitting factor, mediates antibiotic resistance

2018 ◽  
Vol 115 (52) ◽  
pp. 13359-13364 ◽  
Author(s):  
Mélodie Duval ◽  
Daniel Dar ◽  
Filipe Carvalho ◽  
Eduardo P. C. Rocha ◽  
Rotem Sorek ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Antibiotic Resistance Gene ◽  
Resistance Mechanism ◽  
Antibiotic Resistance Genes ◽  
Amino Acid Peptide ◽  
Splitting Factor ◽  
A Genome ◽  
Attenuation Mechanism ◽  
Drug Modification

To overcome the action of antibiotics, bacteria have evolved a variety of different strategies, such as drug modification, target mutation, and efflux pumps. Recently, we performed a genome-wide analysis ofListeria monocytogenesgene expression after growth in the presence of antibiotics, identifying genes that are up-regulated upon antibiotic treatment. One of them,lmo0762, is a homolog ofhflX, which encodes a heat shock protein that rescues stalled ribosomes by separating their two subunits. To our knowledge, ribosome splitting has never been described as an antibiotic resistance mechanism. We thus investigated the role oflmo0762in antibiotic resistance. First, we demonstrated thatlmo0762is an antibiotic resistance gene that confers protection against lincomycin and erythromycin, and that we renamedhflXr(hflXresistance). We show thathflXrexpression is regulated by a transcription attenuation mechanism relying on the presence of alternative RNA structures and a small ORF encoding a 14 amino acid peptide containing the RLR motif, characteristic of macrolide resistance genes. We also provide evidence that HflXr is involved in ribosome recycling in presence of antibiotics. Interestingly,L. monocytogenespossesses another copy ofhflX,lmo1296, that is not involved in antibiotic resistance. Phylogenetic analysis shows several events ofhflXrduplication in prokaryotes and widespread presence ofhflXrin Firmicutes. Overall, this study reveals theListeria hflXras the founding member of a family of antibiotic resistance genes. The resistance conferred by this gene is probably of importance in the environment and within microbial communities.

scholarly journals The Perfect Condition for the Rising of Superbugs: Person-to-Person Contact and Antibiotic Use Are the Key Factors Responsible for the Positive Correlation between Antibiotic Resistance Gene Diversity and Virulence Gene Diversity in Human Metagenomes

Antibiotics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 605
Author(s):  
Célia P. F. Domingues ◽  
João S. Rebelo ◽  
Joël Pothier ◽  
Francisca Monteiro ◽  
Teresa Nogueira ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Loss Rate ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Virulence Gene ◽  
Transmission Probability ◽  
Positive Correlation ◽  
High Diversity

Human metagenomes with a high diversity of virulence genes tend to have a high diversity of antibiotic-resistance genes and vice-versa. To understand this positive correlation, we simulated the transfer of these genes and bacterial pathogens in a community of interacting people that take antibiotics when infected by pathogens. Simulations show that people with higher diversity of virulence and resistance genes took antibiotics long ago, not recently. On the other extreme, we find people with low diversity of both gene types because they took antibiotics recently—while antibiotics select specific resistance genes, they also decrease gene diversity by eliminating bacteria. In general, the diversity of virulence and resistance genes becomes positively correlated whenever the transmission probability between people is higher than the probability of losing resistance genes. The positive correlation holds even under changes of several variables, such as the relative or total diversity of virulence and resistance genes, the contamination probability between individuals, the loss rate of resistance genes, or the social network type. Because the loss rate of resistance genes may be shallow, we conclude that the transmission between people and antibiotic usage are the leading causes for the positive correlation between virulence and antibiotic-resistance genes.

scholarly journals Molecular Identification and Quantification of Tetracycline and Erythromycin Resistance Genes in Spanish and Italian Retail Cheeses

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Ana Belén Flórez ◽  
Ángel Alegría ◽  
Franca Rossi ◽  
Susana Delgado ◽  
Giovanna E. Felis ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Resistant Bacteria ◽  
Gene Pools ◽  
Erythromycin Resistance ◽  
Identification And Quantification

Large antibiotic resistance gene pools in the microbiota of foods may ultimately pose a risk for human health. This study reports the identification and quantification of tetracycline- and erythromycin-resistant populations, resistance genes, and gene diversity in traditional Spanish and Italian cheeses, via culturing, conventional PCR, real-time quantitative PCR (qPCR), and denaturing gradient gel electrophoresis (DGGE). The numbers of resistant bacteria varied widely among the antibiotics and the different cheese varieties; in some cheeses, all the bacterial populations seemed to be resistant. Up to eight antibiotic resistance genes were sought by gene-specific PCR, six with respect to tetracycline, that is,tet(K),tet(L),tet(M),tet(O),tet(S), andtet(W), and two with respect to erythromycin, that is,erm(B) anderm(F). The most common resistance genes in the analysed cheeses weretet(S),tet(W),tet(M), anderm(B). The copy numbers of these genes, as quantified by qPCR, ranged widely between cheeses (from 4.94 to10.18log⁡10/g). DGGE analysis revealed distinct banding profiles and two polymorphic nucleotide positions fortet(W)-carrying cheeses, though the similarity of the sequences suggests thistet(W) to have a monophyletic origin. Traditional cheeses would therefore appear to act as reservoirs for large numbers of many types of antibiotic resistance determinants.

scholarly journals DeepARG: A deep learning approach for predicting antibiotic resistance genes from metagenomic data

2017 ◽  
Author(s):  
G. A. Arango-Argoty ◽  
E. Garner ◽  
A. Pruden ◽  
L. S. Heath ◽  
P. Vikesland ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Deep Learning ◽  
Resistance Genes ◽  
Agricultural Waste ◽  
Antibiotic Resistance Gene ◽  
False Negative ◽  
Antibiotic Resistance Genes ◽  
Direct Access ◽  
Metagenomic Data ◽  
Community Research

ABSTRACTGrowing concerns regarding increasing rates of antibiotic resistance call for global monitoring efforts. Monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is of particular interest as these media can serve as sources of potential novel antibiotic resistance genes (ARGs), as hot spots for ARG exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequence-based monitoring has recently enabled direct access and profiling of the total metagenomic DNA pool, where ARGs are identified or predicted based on the “best hits” of homology searches against existing databases. Unfortunately, this approach tends to produce high rates of false negatives. To address such limitations, we propose here a deep leaning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two models, deepARG-SS and deepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Performance evaluation of the deep learning models over 30 classes of antibiotics demonstrates that the deepARG models can predict ARGs with both high precision (>0.97) and recall (>0.90) for most of the antibiotic resistance categories. The models show advantage over the traditional best hit approach by having consistently much lower false negative rates and thus higher overall recall (>0.9). As more data become available for under-represented antibiotic resistance categories, the deepARG models’ performance can be expected to be further enhanced due to the nature of the underlying neural networks. The deepARG models are available both in command line version and via a Web server at http://bench.cs.vt.edu/deeparg. Our newly developed ARG database, deepARG-DB, containing predicted ARGs with high confidence and high degree of manual curation, greatly expands the current ARG repository. DeepARG-DB can be downloaded freely to benefit community research and future development of antibiotic resistance-related resources.AbbreviationsARGantibiotic resistance gene

scholarly journals The perfect condition for the rising of superbugs: person-to-person contagion and antibiotic use are the key factors responsible for the positive correlation between antibiotic resistance gene diversity and virulence gene diversity in human metagenomes

2020 ◽  
Author(s):  
Célia P. F. Domingues ◽  
João S. Rebelo ◽  
Teresa Nogueira ◽  
Joël Pothier ◽  
Francisca Monteiro ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Loss Rate ◽  
Gene Diversity ◽  
Recent Observation ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Antibiotic Use ◽  
Resistant Bacteria ◽  
Positive Correlation

1.AbstractThis study aims to understand the cause of the recent observation that humans with a higher diversity of virulence genes in their metagenomes tend to be precisely those with higher diversity of antibiotic-resistance genes. We simulated the transferring of virulence and antibiotic-resistance genes in a community of interacting people where some take antibiotics. The diversities of the two genes types became positively correlated whenever the contagion probability between two people was higher than the probability of losing resistant genes. However, no such positive correlations arise if no one takes antibiotics. This finding holds even under changes of several simulations’ parameters, such as the relative or total diversity of virulence and resistance genes, the contagion probability between individuals, the loss rate of resistance genes, or the social network type. Because the loss rate of resistance genes may be shallow, we conclude that the contagion between people and antibiotic usage is the leading cause of establishing the positive correlation mentioned above. Therefore, antibiotic use and something as prosaic as the contagion between people may facilitate the emergence of virulent and multi-resistant bacteria in people’s metagenomes with a high diversity of both gene types. These superbugs may then circulate in the community.

scholarly journals ARGminer: A web platform for crowdsourcing-based curation of antibiotic resistance genes

2018 ◽  
Author(s):  
G. A. Arango-Argoty ◽  
G. K. P. Guron ◽  
E. Garner ◽  
M.V. Riquelme ◽  
L. S. Heath ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Language Processing ◽  
Expert Knowledge ◽  
Antibiotic Resistance Gene ◽  
Resistance Mechanism ◽  
Antibiotic Resistance Genes ◽  
Bacterial Strains ◽  
Expert Annotation ◽  
Novel Strategy ◽  
High Level

ABSTRACTCuration of antibiotic resistance gene (ARG) databases is labor intensive and requires expert knowledge to manually collect, correct, and/or annotate individual genes. Consequently, most existing ARG databases contain only a small number of ARGs (~5k genes) and updates to these databases tend to be infrequent, commonly requiring years for completion and often containing inconsistencies. Thus a new approach is needed to achieve a truly comprehensive ARG database while also maintaining a high level of accuracy. Here we propose a new web-based curation system, ARGminer, that supports the annotation and inspection of several key attributes of potential ARGs, including gene name, antibiotic category, resistance mechanism, evidence for mobility and occurrence in clinically-important bacterial strains. Here we employ crowdsourcing as a novel strategy to overcome limitations of manual curation and expand curation capacity towards achieving a truly comprehensive and perpetually up-to-date database. Further, machine learning is employed as a powerful means to validate database curation, drawing from natural language processing to infer correct and consistent nomenclature for each potential ARG. We develop and validate the crowdsourcing approach by comparing performances of multiple cohorts of curators with varying levels of expertise, demonstrating that ARGminer is a time and cost efficient means of achieving accurate ARG curation. We further demonstrate the reliability of a trust validation filter for rejecting input generated by spammers. Crowdsourcing was found to be as accurate as expert annotation, with an accuracy >90% for the annotation of a diverse test set of ARGs. The ARGminer public search platform and database is available at http://bench.cs.vt.edu/argminer.

scholarly journals Mutation-Based Antibiotic Resistance Mechanism in Methicillin-Resistant Staphylococcus aureus Clinical Isolates

2021 ◽  
Vol 14 (5) ◽  
pp. 420
Author(s):  
Tanveer Ali ◽  
Abdul Basit ◽  
Asad Mustafa Karim ◽  
Jung-Hun Lee ◽  
Jeong-Ho Jeon ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Antibiotic Resistance ◽  
Active Site ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Meca Gene ◽  
Resistance Mechanism ◽  
Ligand Docking ◽  
Clinical Samples ◽  
Allosteric Site ◽  
Methicillin Resistant

β-Lactam antibiotics target penicillin-binding proteins and inhibit the synthesis of peptidoglycan, a crucial step in cell wall biosynthesis. Staphylococcus aureus acquires resistance against β-lactam antibiotics by producing a penicillin-binding protein 2a (PBP2a), encoded by the mecA gene. PBP2a participates in peptidoglycan biosynthesis and exhibits a poor affinity towards β-lactam antibiotics. The current study was performed to determine the diversity and the role of missense mutations of PBP2a in the antibiotic resistance mechanism. The methicillin-resistant Staphylococcus aureus (MRSA) isolates from clinical samples were identified using phenotypic and genotypic techniques. The highest frequency (60%, 18 out of 30) of MRSA was observed in wound specimens. Sequence variation analysis of the mecA gene showed four amino acid substitutions (i.e., E239K, E239R, G246E, and E447K). The E239R mutation was found to be novel. The protein-ligand docking results showed that the E239R mutation in the allosteric site of PBP2a induces conformational changes in the active site and, thus, hinders its interaction with cefoxitin. Therefore, the present report indicates that mutation in the allosteric site of PBP2a provides a more closed active site conformation than wide-type PBP2a and then causes the high-level resistance to cefoxitin.

scholarly journals Nitric oxide (NO) elicits aminoglycoside tolerance in Escherichia coli but antibiotic resistance gene carriage and NO sensitivity have not co-evolved

2021 ◽  
Author(s):  
Cláudia A. Ribeiro ◽  
Luke A. Rahman ◽  
Louis G. Holmes ◽  
Ayrianna M. Woody ◽  
Calum M. Webster ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Antibiotic Resistance ◽  
Antibiotic Susceptibility ◽  
Bacterial Pathogens ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Resistance Mechanisms ◽  
Current Work ◽  
E Coli ◽  
Respiratory Inhibitor

AbstractThe spread of multidrug-resistance in Gram-negative bacterial pathogens presents a major clinical challenge, and new approaches are required to combat these organisms. Nitric oxide (NO) is a well-known antimicrobial that is produced by the immune system in response to infection, and numerous studies have demonstrated that NO is a respiratory inhibitor with both bacteriostatic and bactericidal properties. However, given that loss of aerobic respiratory complexes is known to diminish antibiotic efficacy, it was hypothesised that the potent respiratory inhibitor NO would elicit similar effects. Indeed, the current work demonstrates that pre-exposure to NO-releasers elicits a > tenfold increase in IC50 for gentamicin against pathogenic E. coli (i.e. a huge decrease in lethality). It was therefore hypothesised that hyper-sensitivity to NO may have arisen in bacterial pathogens and that this trait could promote the acquisition of antibiotic-resistance mechanisms through enabling cells to persist in the presence of toxic levels of antibiotic. To test this hypothesis, genomics and microbiological approaches were used to screen a collection of E. coli clinical isolates for antibiotic susceptibility and NO tolerance, although the data did not support a correlation between increased carriage of antibiotic resistance genes and NO tolerance. However, the current work has important implications for how antibiotic susceptibility might be measured in future (i.e. ± NO) and underlines the evolutionary advantage for bacterial pathogens to maintain tolerance to toxic levels of NO.

scholarly journals Black Queen Evolution and Trophic Interactions Determine Plasmid Survival after the Disruption of the Conjugation Network

mSystems ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Johannes Cairns ◽  
Katariina Koskinen ◽  
Reetta Penttinen ◽  
Tommi Patinen ◽  
Anna Hartikainen ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Bacterial Communities ◽  
Resistance Mechanism ◽  
Real Life ◽  
Ecological Factors ◽  
Mobile Genetic Elements ◽  
Resistance Mechanisms ◽  
Antibiotics Resistance ◽  
Bacterial Populations ◽  
Genetic Elements

ABSTRACTMobile genetic elements such as conjugative plasmids are responsible for antibiotic resistance phenotypes in many bacterial pathogens. The ability to conjugate, the presence of antibiotics, and ecological interactions all have a notable role in the persistence of plasmids in bacterial populations. Here, we set out to investigate the contribution of these factors when the conjugation network was disturbed by a plasmid-dependent bacteriophage. Phage alone effectively caused the population to lose plasmids, thus rendering them susceptible to antibiotics. Leakiness of the antibiotic resistance mechanism allowing Black Queen evolution (i.e. a “race to the bottom”) was a more significant factor than the antibiotic concentration (lethal vs sublethal) in determining plasmid prevalence. Interestingly, plasmid loss was also prevented by protozoan predation. These results show that outcomes of attempts to resensitize bacterial communities by disrupting the conjugation network are highly dependent on ecological factors and resistance mechanisms.IMPORTANCEBacterial antibiotic resistance is often a part of mobile genetic elements that move from one bacterium to another. By interfering with the horizontal movement and the maintenance of these elements, it is possible to remove the resistance from the population. Here, we show that a so-called plasmid-dependent bacteriophage causes the initially resistant bacterial population to become susceptible to antibiotics. However, this effect is efficiently countered when the system also contains a predator that feeds on bacteria. Moreover, when the environment contains antibiotics, the survival of resistance is dependent on the resistance mechanism. When bacteria can help their contemporaries to degrade antibiotics, resistance is maintained by only a fraction of the community. On the other hand, when bacteria cannot help others, then all bacteria remain resistant. The concentration of the antibiotic played a less notable role than the antibiotic used. This report shows that the survival of antibiotic resistance in bacterial communities represents a complex process where many factors present in real-life systems define whether or not resistance is actually lost.

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