Clin-mNGS: Automated Pipeline for Pathogen Detection from Clinical Metagenomic Data

High Performance ◽

Pathogen Detection ◽

Bacterial Species ◽

Workflow Management ◽

Metagenomic Data ◽

Culture Independent ◽

Automated Pipeline ◽

User Friendly

Background: Since bacteria are the earliest known organisms, there has been significant interest in their variety and biology, most certainly concerning human health. Recent advances in Metagenomics sequencing (mNGS), a culture-independent sequencing technology have facilitated an accelerated development in clinical microbiology and our understanding of pathogens. Objective: For the implementation of mNGS in routine clinical practice to become feasible, a practical and scalable strategy for the study of mNGS data is essential. This study presents a robust automated pipeline to analyze clinical metagenomic data for pathogen identification and classification. Method: The proposed Clin-mNGS pipeline is an integrated, open-source, scalable, reproducible, and user-friendly framework scripted using the Snakemake workflow management software. The implementation avoids the hassle of manual installation and configuration of the multiple command-line tools and dependencies. The approach directly screens pathogens from clinical raw reads and generates consolidated reports for each sample. Results: The pipeline is demonstrated using publicly available data and is tested on a desktop Linux system and a High-performance cluster. The study compares variability in results from different tools and versions. The versions of the tools are made user modifiable. The pipeline results in quality check, filtered reads, host subtraction, assembled contigs, assembly metrics, relative abundances of bacterial species, antimicrobial resistance genes, plasmid finding, and virulence factors identification. The results obtained from the pipeline are evaluated based on sensitivity and positive predictive value. Conclusion: Clin-mNGS is an automated Snakemake pipeline validated for the analysis of microbial clinical metagenomics reads to perform taxonomic classification and antimicrobial resistance prediction.

Culture-Independent Genotyping, Virulence and Antimicrobial Resistance Gene Identification of Staphylococcus aureus from Orthopaedic Implant-Associated Infections

Microorganisms ◽

10.3390/microorganisms9040707 ◽

2021 ◽

Vol 9 (4) ◽

pp. 707

Author(s):

J. Christopher Noone ◽

Fabienne Antunes Ferreira ◽

Hege Vangstein Aamot

Keyword(s):

Staphylococcus Aureus ◽

Resistance Genes ◽

Virulence Gene ◽

Orthopaedic Implant ◽

Metagenomic Sequencing ◽

Gene Detection ◽

Shotgun Metagenomic Sequencing ◽

Culture Independent

Our culture-independent nanopore shotgun metagenomic sequencing protocol on biopsies has the potential for same-day diagnostics of orthopaedic implant-associated infections (OIAI). As OIAI are frequently caused by Staphylococcus aureus, we included S. aureus genotyping and virulence gene detection to exploit the protocol to its fullest. The aim was to evaluate S. aureus genotyping, virulence and antimicrobial resistance genes detection using the shotgun metagenomic sequencing protocol. This proof of concept study included six patients with S. aureus-associated OIAI at Akershus University Hospital, Norway. Five tissue biopsies from each patient were divided in two: (1) conventional microbiological diagnostics and genotyping, and whole genome sequencing (WGS) of S. aureus isolates; (2) shotgun metagenomic sequencing of DNA from the biopsies. Consensus sequences were analysed using spaTyper, MLST, VirulenceFinder, and ResFinder from the Center for Genomic Epidemiology (CGE). MLST was also compared using krocus. All spa-types, one CGE and four krocus MLST results matched Sanger sequencing results. Virulence gene detection matched between WGS and shotgun metagenomic sequencing. ResFinder results corresponded to resistance phenotype. S. aureus spa-typing, and identification of virulence and antimicrobial resistance genes are possible using our shotgun metagenomics protocol. MLST requires further optimization. The protocol has potential application to other species and infection types.

Investigation of the Genes Involved in the Outbreaks of Escherichia coli and Salmonella spp. in the United States

Antibiotics ◽

10.3390/antibiotics10101274 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1274

Author(s):

Michelle Li ◽

Kyle Wang ◽

Ashley Tang ◽

Aaron Tang ◽

Andrew Chen ◽

...

Keyword(s):

Stress Response ◽

Pathogen Detection ◽

Dimensional Space ◽

Virulence Gene ◽

Principal Component ◽

The United States ◽

Salmonella Spp ◽

E Coli ◽

Salmonella spp. and Escherichiacoli (E. coli) are two of the deadliest foodborne pathogens in the US. Genes involved in antimicrobial resistance, virulence, and stress response, enable these pathogens to increase their pathogenicity. This study aims to examine the genes detected in both outbreak and non-outbreak Salmonella spp. and E. coli by analyzing the data from the National Centre for Biotechnology Information (NCBI) Pathogen Detection Isolates Browser database. A multivariate statistical analysis was conducted on the genes detected in isolates of outbreak Salmonella spp., non-outbreak Salmonella spp., outbreak E. coli, and non-outbreak E. coli. The genes from the data were projected onto a two-dimensional space through principal component analysis. Hierarchical clustering was then used to quantify the relationship between the genes in the dataset. Most of the outlier genes identified in E. coli isolates are virulence genes, while outlier genes identified in Salmonella spp. are mainly involved in stress response. Gene epeA, which encodes a high-molecular-weight serine protease autotransporter of Enterobacteriaceae (SPATE) protein, along with subA and subB that encode cytotoxic activity, may contribute to the pathogenesis of outbreak E. coli. The iro operon and ars operon may play a role in the ecological success of the epidemic clones of Salmonella spp. Concurrent relationships between esp and ter operons in E. coli and pco and sil operons in Salmonella spp. are found. Stress-response genes (asr, golT, golS), virulence gene (sinH), and antimicrobial resistance genes (mdsA and mdsB) in Salmonella spp. also show a concurrent relationship. All these findings provide helpful information for experiment design to combat outbreaks of E. coli and Salmonella spp.

Antimicrobial Susceptibility Testing and Tentative Epidemiological Cutoff Values for FiveBacillusSpecies Relevant for Use as Animal Feed Additives or for Plant Protection

Applied and Environmental Microbiology ◽

10.1128/aem.01108-18 ◽

2018 ◽

Vol 84 (19) ◽

Cited By ~ 7

Author(s):

Yvonne Agersø ◽

Birgitte Stuer-Lauridsen ◽

Karin Bjerre ◽

Michelle Geervliet Jensen ◽

Eric Johansen ◽

...

Keyword(s):

Resistance Genes ◽

Pathogenic Bacteria ◽

Animal Feed ◽

Bacterial Species ◽

Feed Additives ◽

Content Type ◽

Cutoff Values ◽

Species Specific

ABSTRACTBacillus megaterium(n= 29),Bacillus velezensis(n= 26),Bacillus amyloliquefaciens(n= 6),Bacillus paralicheniformis(n= 28), andBacillus licheniformis(n= 35) strains from different sources, origins, and time periods were tested for the MICs for nine antimicrobial agents by the CLSI-recommended method (Mueller-Hinton broth, 35°C, for 18 to 20 h), as well as with a modified CLSI method (Iso-Sensitest [IST] broth, 37°C [35°C forB. megaterium], 24 h). This allows a proposal of species-specific epidemiological cutoff values (ECOFFs) for the interpretation of antimicrobial resistance in these species. MICs determined by the modified CLSI method were 2- to 16-fold higher than with the CLSI-recommended method for several antimicrobials. The MIC distributions differed between species for five of the nine antimicrobials. Consequently, use of the modified CLSI method and interpretation of resistance by use of species-specific ECOFFs is recommended. The genome sequences of all strains were determined and used for screening for resistance genes against the ResFinder database and for multilocus sequence typing. A putative chloramphenicol acetyltransferase (cat) gene was found in oneB. megateriumstrain with an elevated chloramphenicol MIC compared to the otherB. megateriumstrains. InB. velezensisandB. amyloliquefaciens, a putative tetracycline efflux gene,tet(L), was found in all strains (n= 27) with reduced tetracycline susceptibility but was absent in susceptible strains. AllB. paralicheniformisand 23% ofB. licheniformisstrains had elevated MICs for erythromycin and harboredermD. The presence of these resistance genes follows taxonomy suggesting they may be intrinsic rather than horizontally acquired. Reduced susceptibility to chloramphenicol, streptomycin, and clindamycin could not be explained in all species.IMPORTANCEWhen commercializing bacterial strains, likeBacillusspp., for feed applications or plant bioprotection, it is required that the strains are free of acquired antimicrobial resistance genes that could potentially spread to pathogenic bacteria, thereby adding to the pool of resistance genes that may cause treatment failures in humans or animals. Conversely, if antimicrobial resistance is intrinsic to a bacterial species, the risk of spreading horizontally to other bacteria is considered very low. Reliable susceptibility test methods and interpretation criteria at the species level are needed to accurately assess antimicrobial resistance levels. In the present study, tentative ECOFFs for fiveBacillusspecies were determined, and the results showed that the variation in MICs followed the respective species. Moreover, putative resistance genes, which were detected by whole-genome sequencing and suggested to be intrinsic rather that acquired, could explain the resistance phenotypes in most cases.

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

10.21203/rs.3.rs-17413/v1 ◽

2020 ◽

Author(s):

Robert Pieper ◽

Temesgen Dadi ◽

Lukasz Grzeskowiak ◽

Laura Pieper ◽

Britta Siegmund ◽

...

Keyword(s):

Clostridium Difficile ◽

Resistance Genes ◽

Microbial Colonization ◽

Metagenomic Data ◽

Neonatal Piglets ◽

Gut Colonization ◽

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.

Related Antimicrobial Resistance Genes Detected in Different Bacterial Species Co-isolated from Swine Fecal Samples

Foodborne Pathogens and Disease ◽

10.1089/fpd.2010.0695 ◽

2011 ◽

Vol 8 (6) ◽

pp. 663-679 ◽

Cited By ~ 19

Author(s):

Jonathan G. Frye ◽

Rebecca L. Lindsey ◽

Richard J. Meinersmann ◽

Mark E. Berrang ◽

Charlene R. Jackson ◽

...

Keyword(s):

Resistance Genes ◽

Bacterial Species ◽

Fecal Samples ◽

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

10.1101/2020.03.24.006148 ◽

2020 ◽

Author(s):

Laura de Nies ◽

Sara Lopes ◽

Anna Heintz-Buschart ◽

Cedric Christian Laczny ◽

Patrick May ◽

...

Keyword(s):

Virulence Factors ◽

Resistance Genes ◽

Bacterial Toxins ◽

Metagenomic Data ◽

Genomic Context ◽

Pathogenic Potential ◽

Signature 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.

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

10.1101/695973 ◽

2019 ◽

Cited By ~ 1

Author(s):

Melanie-Maria Obermeier ◽

Julian Taffner ◽

Alessandro Bergna ◽

Anja Poehlein ◽

Tomislav Cernava ◽

...

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Resistance Mechanisms ◽

Culture Collection ◽

Metagenomic Data ◽

Native Plant ◽

Resistance Determinants ◽

Target Spectrum ◽

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.

Preterm infants harbour diverse Klebsiella populations, including atypical species that encode and produce an array of antimicrobial resistance- and virulence-associated factors

Microbial Genomics ◽

10.1099/mgen.0.000377 ◽

2020 ◽

Vol 6 (6) ◽

Author(s):

Yuhao Chen ◽

Thomas C. Brook ◽

Cho Zin Soe ◽

Ian O'Neill ◽

Cristina Alcon-Giner ◽

...

Keyword(s):

Preterm Infants ◽

Type Species ◽

Metagenomic Data ◽

Preterm Neonates ◽

Content Type ◽

Link Type ◽

Faecal Samples ◽

Klebsiella spp. are frequently enriched in the gut microbiota of preterm neonates, and overgrowth is associated with necrotizing enterocolitis (NEC), nosocomial infections and late-onset sepsis. Little is known about the genomic and phenotypic characteristics of preterm-associated Klebsiella , as previous studies have focused on the recovery of antimicrobial-resistant isolates or culture-independent molecular analyses. The aim of this study was to better characterize preterm-associated Klebsiella populations using phenotypic and genotypic approaches. Faecal samples from a UK cohort of healthy and sick preterm neonates (n=109) were screened on MacConkey agar to isolate lactose-positive Enterobacteriaceae . Whole-genome sequences were generated for Klebsiella spp., and virulence and antimicrobial resistance genes identified. Antibiotic susceptibility profiling and in vitro macrophage and iron assays were undertaken for the Klebsiella strains. Metapangenome analyses with a manually curated genome dataset were undertaken to examine the diversity of Klebsiella oxytoca and related bacteria in a publicly available shotgun metagenome dataset. Approximately one-tenth of faecal samples harboured Klebsiella spp. ( Klebsiella pneumoniae , 7.3 %; Klebsiella quasipneumoniae , 0.9 %; Klebsiella grimontii , 2.8 %; Klebsiella michiganensis , 1.8 %). Isolates recovered from NEC- and sepsis-affected infants and those showing no signs of clinical infection (i.e. ‘healthy’) encoded multiple β-lactamases. No difference was observed between isolates recovered from healthy and sick infants with respect to in vitro siderophore production (all encoded enterobactin in their genomes). All K. pneumoniae , K. quasipneumoniae , K. grimontii and K. michiganensis faecal isolates tested were able to reside and persist in macrophages, indicating their immune evasion abilities. Metapangenome analyses of published metagenomic data confirmed our findings regarding the presence of K. michiganensis in the preterm gut. There is little difference in the phenotypic and genomic characteristics of Klebsiella isolates recovered from healthy and sick infants. Identification of β-lactamases in all isolates may prove problematic when defining treatment regimens for NEC or sepsis, and suggests that healthy preterm infants contribute to the resistome. Refined analyses with curated sequence databases are required when studying closely related species present in metagenomic data.

Benefits of Adding a Rapid PCR-Based Blood Culture Identification Panel to an Established Antimicrobial Stewardship Program

Journal of Clinical Microbiology ◽

10.1128/jcm.00996-16 ◽

2016 ◽

Vol 54 (10) ◽

pp. 2455-2463 ◽

Cited By ~ 55

Author(s):

Shawn H. MacVane ◽

Frederick S. Nolte

Keyword(s):

Blood Culture ◽

Antimicrobial Stewardship ◽

Bacterial Species ◽

Effective Therapy ◽

Control Group ◽

Stewardship Program ◽

Culture Identification ◽

Organism Identification

Studies have demonstrated that the combination of antimicrobial stewardship programs (ASP) and rapid organism identification improves outcomes in bloodstream infections (BSI) but have not controlled for the incremental contribution of the individual components. Hospitalized adult patients with blood culture pathogens on a rapid, multiplex PCR-based blood culture identification panel (BCID) that included 19 bacterial species, 5Candidaspp., and 4 antimicrobial resistance genes were studied over sequential time periods in a pre-post quasiexperimental study in 3 groups in the following categories: conventional organism identification (controls), conventional organism identification with ASP (AS), and BCID with ASP (BCID). Clinical and economic outcomes were compared between groups. There were 783 patients with positive blood cultures; of those patients, 364 (115 control, 104 AS, and 145 BCID) met inclusion criteria. The time from blood culture collection to organism identification was shorter in the BCID group (17 h;P< 0.001) than in the control group (57 h) or the AS group (54 h). The BCID group had a shorter time to effective therapy (5 h;P< 0.001) than the control group (15 h) or AS group (13 h). The AS (57%) and BCID (52%) groups had higher rates of antimicrobial de-escalation than the control group (34%), with de-escalation occurring sooner in the BCID group (48 h;P= 0.034) than in the AS group (61 h) or the control group (63 h). No difference between the control group, AS group, and BCID group was seen with respect to mortality, 30-day readmission, intensive care unit length of stay (LOS), postculture LOS, or costs. In patients with BSI, ASP alone improved antimicrobial utilization. Addition of BCID to an established ASP shortened the time to effective therapy and further improved antimicrobial use compared to ASP alone, even in a setting of low antimicrobial resistance rates.

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

Scientific Data ◽

10.1038/s41597-020-00638-4 ◽

2020 ◽

Vol 7 (1) ◽

Cited By ~ 8

Author(s):

Sebastiaan P. Huber ◽

Spyros Zoupanos ◽

Martin Uhrin ◽

Leopold Talirz ◽

Leonid Kahle ◽

...

Keyword(s):

High Performance ◽

Workflow Management ◽

Scientific Progress ◽

Simulation Software ◽

Data Provenance ◽

Full Data ◽

Computing Power ◽

Sustained Development ◽

Sustained Performance ◽

User Friendly

Abstract The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA’s workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.