Screening for antimicrobial resistance genes and virulence factors via genome sequencing.
Ontology highlight
ABSTRACT:
SUBMITTER: Bennedsen M
PROVIDER: S-EPMC3126367 | biostudies-literature | 2011 Apr
REPOSITORIES: biostudies-literature
Publications
Screening for antimicrobial resistance genes and virulence factors via genome sequencing.
Bennedsen Mads M Stuer-Lauridsen Birgitte B Danielsen Morten M Johansen Eric E
Applied and environmental microbiology 20110218 8
Second-generation genome sequencing and alignment of the resulting reads to in silico genomes containing antimicrobial resistance and virulence factor genes were used to screen for undesirable genes in 28 strains which could be used in human nutrition. No virulence factor genes were detected, while several isolates contained antimicrobial resistance genes. ...[more]
Similar Datasets
Project description:The surveillance of antimicrobial-resistant isolates has proven to be one of the most valuable tools to understand the global rise of multidrug-resistant bacterial pathogens. We report the first insights into the current situation in the Caribbean, where a pilot project to monitor antimicrobial resistance (AMR) through phenotypic resistance measurements combined with whole-genome sequencing was set up in collaboration with the Caribbean Public Health Agency (CARPHA). Our first study focused on Klebsiella pneumoniae, a highly relevant organism amongst the Gram-negative opportunistic pathogens worldwide causing hospital- and community-acquired infections. Our results show that not only carbapenem resistance, but also hypervirulent strains, are circulating in patients in the Caribbean. Our current data does not allow us to infer their prevalence in the population. We argue for the urgent need to further support AMR surveillance and stewardship in this almost uncharted territory, which can make a significant impact on the reduction of antimicrobial usage. This article contains data hosted by Microreact (https://microreact.org).
| S-EPMC6562249 | biostudies-literature
Project description:Actinobacillus equuli is mostly associated with disease in horses and is most widely known as the causative agent of sleepy foal disease. Even though existing phenotypic tools such as biochemical tests, 16S rRNA gene sequencing, and Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) can be used to identify members of the Actinobacillus genus, these methods struggle to differentiate between certain species and do not allow strain, virulence, and antimicrobial susceptibility typing. Hence, we performed in-depth analysis of 24 equine Actinobacillus isolates using phenotypic identification and susceptibility testing on the one hand, and long-read nanopore whole genome sequencing on the other hand. This allowed to address strain divergence down to the whole genome single nucleotide polymorphism (SNP) level. While lowest resolution was observed for 16S rRNA gene classification, a new multi-locus sequence typing (MLST) scheme allowed proper classification up to the species level. Nevertheless, a SNP-level analysis was required to distinguish A. equuli subspecies equuli and haemolyticus. Our data provided first WGS data on Actinobacillus genomospecies 1, Actinobacillus genomospecies 2, and A. arthritidis, which allowed the identification of a new Actinobacillus genomospecies 1 field isolate. Also, in-depth characterization of RTX virulence genes provided information on the distribution, completeness, and potential complementary nature of the RTX gene operons within the Actinobacillus genus. Even though overall low prevalence of acquired resistance was observed, two plasmids were identified conferring resistance to penicillin-ampicillin-amoxicillin and chloramphenicol in one A. equuli strain. In conclusion our data delivered new insights in the use of long-read WGS in high resolution identification, virulence gene typing, and antimicrobial resistance (AMR) of equine Actinobacillus species.
| S-EPMC10074821 | biostudies-literature
Project description:Introduction. Antimicrobial resistance (AMR) poses a critical threat to global health, underscoring the need for rapid and accurate diagnostic tools. Methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae (ESBL-Kp) are listed among the World Health Organization's priority pathogens.Hypothesis. A rapid nanopore-based protocol can accurately and efficiently detect AMR genes, virulence factors (VFs) and mobile genetic elements (MGEs) in MRSA and ESBL-Kp, offering performance comparable to or superior to traditional sequencing methods.Aim. Evaluate whole-genome sequencing (WGS) protocols for detecting AMR genes, VFs and MGEs in MRSA and ESBL-Kp, to identify the most accurate and efficient tool for pathogen profiling.Methodology. Five distinct WGS protocols, including a rapid nanopore-based protocol (ONT20h) and four slower sequencing methods, were evaluated for their effectiveness in detecting genetic markers. The protocols' performances were compared across AMR genes, VFs and MGEs. Additionally, phenotypic antimicrobial susceptibility testing was performed to assess concordance with the genomic findings.Results. Compared to four slower sequencing protocols, the rapid nanopore-based protocol (ONT20h) demonstrated comparable or superior performance in AMR gene detection and equivalent VF identification. Although MGE detection varied among protocols, ONT20h showed a high level of agreement with phenotypic antimicrobial susceptibility testing.Conclusion. The findings highlight the potential of rapid WGS as a valuable tool for clinical microbiology, enabling timely implementation of infection control measures and informed therapeutic decisions. However, further studies are required to optimize the clinical application of this technology, considering costs, availability of bioinformatics tools and quality of reference databases.
| S-EPMC11923095 | biostudies-literature
Project description:Multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) is currently recognized not only as a significant nosocomial pathogen but also is an emerging bacterial infection in food-producing animals, posing a critical threat to global health. However, this is a hindrance to detailed bioinformatic studies of MDR A. baumannii of chicken origin due to the lack of its complete genome sequence. Here, we report whole-genome sequencing analysis of MDR A. baumannii Y03 isolated from chickens. The Y03 genome consists of 1 circular chromosome and 4 circular plasmids, The Y03 chromosome harbors 41 antimicrobial resistance genes conferring resistance to major classes of antibiotics, including β-lactams, phenicols, macrolides, lincosamides, aminoglycosides, and nitrofurans, as well as 135 virulence factors involved in effector delivery system, immune modulation, adherence, stress survival, biofilm, exotoxin, and nutritional/metabolic factor. The in vivo infection experiments certificated that Y03 was virulent to chickens. Meanwhile, we used PCR amplification method to detect 10 antimicrobial resistance genes including abeM, adeB, adeH, adeK, blaapmC, blaOXA-90, catB9, macB, folP, and parE, as well as 14 virulence genes including lpxC, pilO, fimT, ompA, basA, bauA, gspL, csu, pgaC, plc2, tssA, tviB, bap, and vgrG. Whole-genome sequencing analysis revealed that Y03 contained 46 horizontal gene transfer elements, including 11 genomic islands, 30 transposons, and 5 prophages, as well as 518 mutations associated with reduced virulence and 44 mutations resulting in loss of pathogenicity. Furthermore, there were 22 antibiotic targets and 28 lethal mutations on the Y03 chromosome that could be used as potential targets to prevent, control, and treat infections caused by MDR A. baumannii Y03. Therefore, this study contributes to the development of strategies for the prevention, control, and treatment of A. baumannii infections and their spread in chickens.
| S-EPMC11657679 | biostudies-literature
Project description:Salmonella Enteritidis causes a major public health problem in the world. Whole genome sequencing can give us a lot of information not only about the phylogenetic relatedness of these bacteria but also in antimicrobial resistance and virulence gene predictions. In this study, we analyzed the whole genome data of 45 S. Enteritidis isolates recovered in Tunisia from different origins, human, animal, and foodborne samples. Two major lineages (A and B) were detected based on 802 SNPs differences. Among these SNPs, 493 missense SNPs were identified. A total of 349 orthologue genes mutated by one or two missense SNPs were classified in 22 functional groups with the prevalence of carbohydrate transport and metabolism group. A good correlation between genotypic antibiotic resistance profiles and phenotypic analysis were observed. Only resistant isolates carried the respective molecular resistant determinants. The investigation of virulence markers showed the distribution of 11 Salmonella pathogenicity islands (SPI) out of 23 previously described. The SPI-1 and SPI-2 genes encoding type III secretion systems were highly conserved in all isolates except one. In addition, the virulence plasmid genes were present in all isolates except two. We showed the presence of two fimbrial operons sef and ste previously considered to be specific for typhoidal Salmonella. Our collection of S. Enteritidis reveal a diversity among prophage profiles. SNPs analysis showed that missense mutations identified in fimbriae and in SPI-1 and SPI-2 genes were mostly detected in lineage B. In conclusion, WGS is a powerful application to study functional genomic determinants of S. Enteritidis such as antimicrobial resistance genes, virulence markers and prophage sequences. Further studies are needed to predict the impact of the missenses SNPs that can affect the protein functions associated with pathogenicity.
| S-EPMC9325895 | biostudies-literature
Project description:Passengers are at a higher risk of respiratory infections and chronic diseases due to microbial exposure in airline cabins. However, the presence of virulence factors (VFs), antimicrobial resistance genes (ARGs), metabolites, and chemicals are yet to be studied. To address this gap, we collected dust samples from the cabins of two airlines, one with textile seats (TSC) and one with leather seats (LSC), and analyzed the exposure using shotgun metagenomics and LC/MS. Results showed that the abundances of 17 VFs and 11 risk chemicals were significantly higher in TSC than LSC (p < 0.01). The predominant VFs in TSC were related to adherence, biofilm formation, and immune modulation, mainly derived from facultative pathogens such as Haemophilus parainfluenzae and Streptococcus pneumoniae. The predominant risk chemicals in TSC included pesticides/herbicides (carbofuran, bromacil, and propazine) and detergents (triethanolamine, diethanolamine, and diethyl phthalate). The abundances of these VFs and detergents followed the trend of TSC > LSC > school classrooms (p < 0.01), potentially explaining the higher incidence of infectious and chronic inflammatory diseases in aircraft. The level of ARGs in aircraft was similar to that in school environments. This is the first multi-omic survey in commercial aircraft, highlighting that surface material choice is a potential intervention strategy for improving passenger health.
| S-EPMC10058785 | biostudies-literature
Project description:Whole genome sequencing (WGS) is a key tool in identifying and characterising disease-associated bacteria across clinical, agricultural, and environmental contexts. One increasingly common use of genomic and metagenomic sequencing is in identifying the type and range of antimicrobial resistance (AMR) genes present in bacterial isolates in order to make predictions regarding their AMR phenotype. However, there are a large number of alternative bioinformatics software and pipelines available, which can lead to dissimilar results. It is, therefore, vital that researchers carefully evaluate their genomic and metagenomic AMR analysis methods using a common dataset. To this end, as part of the Microbial Bioinformatics Hackathon and Workshop 2021, a 'gold standard' reference genomic and simulated metagenomic dataset was generated containing raw sequence reads mapped against their corresponding reference genome from a range of 174 potentially pathogenic bacteria. These datasets and their accompanying metadata are freely available for use in benchmarking studies of bacteria and their antimicrobial resistance genes and will help improve tool development for the identification of AMR genes in complex samples.
| S-EPMC9200708 | biostudies-literature
Project description:Proteus mirabilis is a common opportunistic pathogen causing severe illness in humans and animals. To determine the prevalence, antibiogram, biofilm-formation, screening of virulence, and antimicrobial resistance genes in P. mirabilis isolates from ducks; 240 samples were obtained from apparently healthy and diseased ducks from private farms in Port-Said Province, Egypt. The collected samples were examined bacteriologically, and then the recovered isolates were tested for atpD gene sequencing, antimicrobial susceptibility, biofilm-formation, PCR detection of virulence, and antimicrobial resistance genes. The prevalence of P. mirabilis in the examined samples was 14.6% (35/240). The identification of the recovered isolates was confirmed by the atpD gene sequencing, where the tested isolates shared a common ancestor. Besides, 94.3% of P. mirabilis isolates were biofilm producers. The recovered isolates were resistant to penicillins, sulfonamides, β-Lactam-β-lactamase-inhibitor-combinations, tetracyclines, cephalosporins, macrolides, and quinolones. Using PCR, the retrieved strains harbored atpD, ureC, rsbA, and zapA virulence genes with a prevalence of 100%, 100%, 94.3%, and 91.4%, respectively. Moreover, 31.4% (11/35) of the recovered strains were XDR to 8 antimicrobial classes that harbored blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Besides, 22.8% (8/35) of the tested strains were MDR to 3 antimicrobial classes and possessed blaTEM, tetA, and sul1genes. Furthermore, 17.1% (6/35) of the tested strains were MDR to 7 antimicrobial classes and harbored blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Alarmingly, three strains were carbapenem-resistant that exhibited PDR to all the tested 10 antimicrobial classes and shared blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Of them, two strains harbored the blaNDM-1 gene, and one strain carried the blaKPC gene. In brief, to the best of our knowledge, this is the first study demonstrating the emergence of XDR and MDR-P.mirabilis in ducks. Norfloxacin exhibited promising antibacterial activity against the recovered XDR and MDR-P. mirabilis. The emergence of PDR, XDR, and MDR-strains constitutes a threat alarm that indicates the complicated treatment of the infections caused by these superbugs.
| S-EPMC8096940 | biostudies-literature
Project description:Streptococcus uberis is one of the primary causative agents of mastitis, a clinically and economically significant disease that affects dairy cattle worldwide. In this study, we analyzed 140 S. uberis strains isolated from mastitis milk samples collected from 74 cow herds in the Czech Republic. We employed whole-genome sequencing to screen for the presence of antimicrobial resistance (AMR) genes and genes encoding virulence factors, and to assess their genetic relationships. Our analysis revealed the presence of 88 different sequence types (STs), with 41% of the isolates assigned to global clonal complexes (GCCs), the majority of which were affiliated with GCC5. The STs identified were distributed across the major phylogenetic branches of all currently known STs. We identified fifty-one putative virulence factor genes, and the majority of isolates carried between 27 and 29 of these genes. A tendency of virulence factors and AMR genes to cluster with specific STs was observed, although such clustering was not evident within GCCs. Principal component analysis did not reveal significant diversity among isolates when grouped by GCC or ST prevalence. The substantial genomic diversity and the wide array of virulence factors found in S. uberis strains present a challenge for the implementation of effective anti-mastitis measures.
| S-EPMC10745719 | biostudies-literature
Project description:BackgroundPathogenic 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.ResultsHere, 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.ConclusionPathoFact 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.
| S-EPMC7890817 | biostudies-literature