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

2020 ◽  
Author(s):  
Laura de Nies ◽  
Sara Lopes ◽  
Anna Heintz-Buschart ◽  
Cedric Christian Laczny ◽  
Patrick May ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Virulence Factors ◽  
Resistance Genes ◽  
Bacterial Toxins ◽  
Metagenomic Data ◽  
Genomic Context ◽  
Pathogenic Potential ◽  
Signature Genes ◽  
Antimicrobial Resistance Genes ◽  
Versatile Tool

AbstractBackgroundPathogenic microorganisms cause disease by invading, colonizing and damaging their host. Virulence factors including bacterial toxins contribute to their pathogenicity. Additionally, antimicrobial resistance genes allow pathogens to evade otherwise curative treatments. To understand causal relationships between microbiome compositions, functioning, and disease, it is therefore essential to identify virulence factors and antimicrobial resistance genes in metagenomic datasets. At present, there is a clear lack of computational approaches to simultaneously identifying these factors. Here we present PathoFact, a tool for the contextualized prediction of virulence factors and antimicrobial resistance genes in metagenomic data.ResultsPathoFact predicts virulence factors, bacterial toxins and antimicrobial resistance genes with high accuracy (0.92, 0.83 and 0.99) and specificity (0.96, 0.99 and 0.98), respectively. The performance of PathoFact was furthermore demonstrated 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 were predicted to play a role. With PathoFact, we identified virulence factors (including toxins) and antimicrobial resistance genes, and identified signature genes which differentiated between the disease and control groups.ConclusionPathoFact is an easy-to-use, modular, and reproducible pipeline for the identification of virulence factors, toxins and antimicrobial resistance genes in metagenomic data. Additionally, PathoFact 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, each module (virulence factors, toxin and antimicrobial resistance genes) of PathoFact is also a standalone component, making it a flexible and versatile tool. PathoFact is freely available online at https://git-r3lab.uni.lu/laura.denies/PathoFact.

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

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Laura de Nies ◽  
Sara Lopes ◽  
Susheel Bhanu Busi ◽  
Valentina Galata ◽  
Anna Heintz-Buschart ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Virulence Factors ◽  
Resistance Genes ◽  
Bacterial Toxins ◽  
Metagenomic Data ◽  
Genomic Context ◽  
Pathogenic Potential ◽  
Antimicrobial Resistance Genes ◽  
Versatile Tool ◽  
And Control

Abstract 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.

scholarly journals An Evaluation of the Pathogenic Potential, and the Antimicrobial Resistance, of Salmonella Strains Isolated from Mussels

2022 ◽  
Vol 10 (1) ◽  
pp. 126
Author(s):  
Antonio Lozano-León ◽  
Carlos García-Omil ◽  
Rafael R. Rodríguez-Souto ◽  
Alexandre Lamas ◽  
Alejandro Garrido-Maestu
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Virulence Genes ◽  
Health Issues ◽  
Salmonella Spp ◽  
Pathogenic Potential ◽  
Antimicrobial Resistance Genes ◽  
Important Health ◽  
Main Production ◽  
Production Areas

Salmonella spp. and antimicrobial resistant microorganisms are two of the most important health issues worldwide. In the present study, strains naturally isolated from mussels harvested in Galicia (one of the main production areas in the world), were genetically characterized attending to the presence of virulence and antimicrobial resistance genes. Additionally, the antimicrobial profile was also determined phenotypically. Strains presenting several virulence genes were isolated but lacked all the antimicrobial resistance genes analyzed. The fact that some of these strains presented multidrug resistance, highlighted the possibility of bearing different genes than those analyzed, or resistance based on completely different mechanisms. The current study highlights the importance of constant surveillance in order to improve the safety of foods.

Formula-fed and Clostridium difficile infected neonatal piglets carry a highly diverse and abundant set of antimicrobial resistance genes

2020 ◽  
Author(s):  
Robert Pieper ◽  
Temesgen Dadi ◽  
Lukasz Grzeskowiak ◽  
Laura Pieper ◽  
Britta Siegmund ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Microbial Colonization ◽  
Metagenomic Data ◽  
Neonatal Piglets ◽  
Gut Colonization ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene ◽  
Genes Encoding

Abstract Background: Clostridium difficile infection (CDI) is an increasing zoonotic health threat and has also been documented as a cause of enteritis outbreaks in neonatal pigs. Furthermore, CDI in neonatal piglets cause changes in microbial gut colonization. We hypothesized that an imbalanced microbial colonization in piglets with CDI could be associated with an altered abundance of antimicrobial resistance genes. Results: We analyzed fecal metagenomic data of lactating sows (S), their piglets during suckling (SP), the same piglets two weeks after weaning (WP), 5-day old artificially reared and formula-fed siblings (FP) and FP infected with C. difficile (FP-CD) for microbiota composition and antimicrobial resistance gene abundance. FP and FP-CD piglets had an immature-type microbiota and increased abundance of antimicrobial resistance genes. A co-occurrence of genes encoding for resistance against aminoglycosides (e.g. aph(3”)-lb, aph(6)-ld, ant(2”)-la), β-lactams (blaCTX-M, blaTEM), fluoroquinolones (pat(A) macrolides (mph(A)), sulfonamides (sul1, sul2), polypeptides (e.g. pmrB, pmrC, arnA, bac(A)) and tetracyclines (e.g. tet(A-D),) was observed. Conclusion: Increased abundance of antimicrobial resistance genes in formula feeding and concomitant CDI may be associated with therapeutic resistance later in life and warrant further studies.

scholarly journals Unravelling native plant resistomes – The Sphagnum microbiome harbours versatile and novel antimicrobial resistance genes

2019 ◽  
Author(s):  
Melanie-Maria Obermeier ◽  
Julian Taffner ◽  
Alessandro Bergna ◽  
Anja Poehlein ◽  
Tomislav Cernava ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Resistance Mechanisms ◽  
Culture Collection ◽  
Metagenomic Data ◽  
Native Plant ◽  
Resistance Determinants ◽  
Target Spectrum ◽  
Antimicrobial Resistance Genes

The expanding antibiotic resistance crisis calls for a more in depth understanding of the importance of antimicrobial resistance genes (ARGs) in pristine environments. We, therefore, studied the microbiota associated with Sphagnum forming the main vegetation in undomesticated, evolutionary old bog ecosystems. In our complementary analysis of a culture collection, metagenomic data and a fosmid library, we identified a low abundant but highly diverse pool of resistance determinants, which targets an unexpected broad range of antibiotics including natural and synthetic compounds. This derives both, from the extraordinarily high abundance of efflux pumps (80%), and the unexpectedly versatile set of ARGs underlying all major resistance mechanisms. The overall target spectrum of detected resistance determinants spans 21 antibiotic classes, whereby β-lactamases and vancomycin resistance appeared as the predominant resistances in all screenings. Multi-resistance was frequently observed among bacterial isolates, e.g. in Serratia, Pandorea, Paraburkhotderia and Rouxiella. In a search for novel ARGs we identified the new class A β-lactamase Mm3. The native Sphagnum resistome comprising a highly diversified and partially novel set of ARGs contributes to the bog ecosystem’s plasticity. Our results shed light onto the antibiotic resistance background of non-agricultural plants and highlight the ecological link between natural and clinically relevant resistomes.

scholarly journals Genomic Investigation of Antimicrobial-Resistant Salmonella enterica Isolates From Dead Chick Embryos in China

2021 ◽  
Vol 12 ◽  
Author(s):  
Mohammed Elbediwi ◽  
Yanting Tang ◽  
Dawei Shi ◽  
Hazem Ramadan ◽  
Yaohui Xu ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Chick Embryo ◽  
Virulence Factors ◽  
Resistance Genes ◽  
Salmonella Enterica ◽  
Multidrug Resistant ◽  
Henan Province ◽  
Health Concern ◽  
Antimicrobial Resistance Genes ◽  
Genomic Characterization

Salmonella spp. is recognized as an important zoonotic pathogen. The emergence of antimicrobial resistance in Salmonella enterica poses a great public health concern worldwide. While the knowledge on the incidence and the characterization of different S. enterica serovars causing chick embryo death remains obscure in China. In this study, we obtained 45 S. enterica isolates from 2,139 dead chick embryo samples collected from 28 breeding chicken hatcheries in Henan province. The antimicrobial susceptibility assay was performed by the broth microdilution method and the results showed that 31/45 (68.8%) isolates were multidrug-resistant (≥3 antimicrobial classes). Besides the highest resistance rate was observed in the aminoglycoside class, all the isolates were susceptible to chloramphenicol, azithromycin, and imipenem. Furthermore, genomic characterization revealed that S. Enteritidis (33.33%; 15/45) was a frequent serovar that harbored a higher number of virulence factors compared to other serovars. Importantly, genes encoding β-lactamases were identified in three serovars (Thompson, Enteritidis, and Kottbus), whereas plasmid-mediated quinolone resistance genes (qnrB4) were detected in certain isolates of S. Thompson and the two S. Kottbus isolates. All the examined isolates harbored the typical virulence factors from Salmonella pathogenicity islands 1 and 2 (SPI-1 and SPI-2). Additionally, a correlation analysis between the antimicrobial resistance genes, phenotype, and plasmids was conducted among Salmonella isolates. It showed strong positive correlations (r < 0.6) between the different antimicrobial-resistant genes belonging to certain antimicrobial classes. Besides, IncF plasmid showed a strong negative correlation (r > −0.6) with IncHI2 and IncHI2A plasmids. Together, our study demonstrated antimicrobial-resistant S. enterica circulating in breeding chicken hatcheries in Henan province, highlighting the advanced approach, by using genomic characterization and statistical analysis, in conducting the routine monitoring of the emerging antimicrobial-resistant pathogens. Our findings also proposed that the day-old breeder chicks trading could be one of the potential pathways for the dissemination of multidrug-resistant S. enterica serovars.

scholarly journals * Virulence factors, antimicrobial resistance genes and protein structure of crohn's disease-derived

Gut ◽  
2011 ◽  
Vol 60 (Suppl 1) ◽  
pp. A202-A203
Author(s):  
T. Elliott ◽  
B. Hudspith ◽  
N. Rayment ◽  
L. Randall ◽  
G. Wu ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Protein Structure ◽  
Antimicrobial Resistance ◽  
Crohn's Disease ◽  
Virulence Factors ◽  
Resistance Genes ◽  
Antimicrobial Resistance Genes

scholarly journals Screening for Antimicrobial Resistance Genes and Virulence Factors via Genome Sequencing

2011 ◽  
Vol 77 (8) ◽  
pp. 2785-2787 ◽  
Author(s):  
Mads Bennedsen ◽  
Birgitte Stuer-Lauridsen ◽  
Morten Danielsen ◽  
Eric Johansen
Keyword(s):  
Antimicrobial Resistance ◽  
Genome Sequencing ◽  
Virulence Factors ◽  
Virulence Factor ◽  
Resistance Genes ◽  
In Silico ◽  
Human Nutrition ◽  
Content Type ◽  
Antimicrobial Resistance Genes ◽  
Virulence Factor Genes

ABSTRACTSecond-generation genome sequencing and alignment of the resulting reads toin silicogenomes 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.

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