scholarly journals Evaluating Metagenomic Analysis for Pathogen Transmission in Healthcare Settings

2020 ◽  
Vol 41 (S1) ◽  
pp. s224-s224
Author(s):  
Curt Hewitt ◽  
Katharina Weber ◽  
Danielle LeSassier ◽  
Anthony Kappell ◽  
Kathleen Schulte ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Dna Analysis ◽  
Pathogen Transmission ◽  
Species Level ◽  
Metagenomic Analysis ◽  
Skin Microbiome ◽  
Limited Information ◽  
Culture Methods ◽  
Data Set ◽  
Skin Contact

Background: The prevalence of healthcare-acquired infections (HAIs) and rising levels of antimicrobial resistance place a significant burden on modern healthcare systems. Cultures are typically used to track HAIs; however, culture methods provide limited information and are not applicable to all pathogens. Next-generation sequencing (NGS) can detect and characterize pathogens present within a sample, but few research studies have explored how NGS could be used to detect pathogen transmission events under HAI-relevant scenarios. The objective of this CDC-funded project was to evaluate and correlate sequencing approaches for pathogen transmission with standard culture-based analysis. Methods: We modeled pathogen transfer via hand contact using synthetic skin. These skin coupons were seeded with a community of commensal organisms to mimic the human skin microbiome. Pathogens were added at physiologically relevant high or low levels prior to skin-to-skin contact. The ESKAPE pathogens: E. faecium, S. aureus, K. pneumoniae, A. baumannii, P. aeruginosa, and Enterobacter spp plus C. difficile were employed because they are the most common antibiotic resistant HAIs. Pathogen transfer between skin coupons was measured following direct skin contact and fomite surface transmission. The effects of handwashing or fomite decontamination were also evaluated. Transferred pathogens were enumerated via culture to establish a robust data set against which DNA and RNA sequence analyses of the same samples could be compared. These data also provide a quantitative assessment of individual ESKAPE+C pathogen transfer rates in skin contact scenarios. Results: Metagenomic and metatranscriptomic analysis using custom analysis pipelines and reference databases successfully identified the commensal and pathogenic organisms present in each sample at the species level. This analysis also identified antibiotic resistance genes and plasmids. Metatranscriptomic analysis permitted not only gene identification but also confirmation of gene expression, a critical factor in the evaluation of antibiotic resistance. DNA analysis does not require cell viability, a key differentiator between sequencing and culturing reflected in simulated handwashing data. Sensitivity remains a key limitation of metagenomic analysis, as shown by the poor species identification and gene content characterization of pathogens present at low abundance within the simulated microbial community. Species level identification typically failed as ratios fell below 1:1,000 pathogen CFU:total community CFU. Conclusions: These findings demonstrate the strengths and weaknesses of NGS for molecular epidemiology. The data sets produced for this study are publicly available so they can be employed for future metagenomic benchmarking studies.Funding: NoneDisclosures: None

scholarly journals Next Generation Sequencing for the Prediction of the Antibiotic Resistance in Helicobacter pylori: A Literature Review

Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 437
Author(s):  
Ilaria Maria Saracino ◽  
Matteo Pavoni ◽  
Angelo Zullo ◽  
Giulia Fiorini ◽  
Tiziana Lazzarotto ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Next Generation Sequencing ◽  
Literature Review ◽  
Molecular Mechanisms ◽  
World Health ◽  
Next Generation ◽  
Culture Methods ◽  
Phenotypic Resistance ◽  
H Pylori ◽  
Generation Sequencing

Background and aims: Only a few antimicrobials are effective against H. pylori, and antibiotic resistance is an increasing problem for eradication therapies. In 2017, the World Health Organization categorized clarithromycin resistant H. pylori as a “high-priority” bacterium. Standard antimicrobial susceptibility testing can be used to prescribe appropriate therapies but is currently recommended only after the second therapeutic failure. H. pylori is, in fact, a “fastidious” microorganism; culture methods are time-consuming and technically challenging. The advent of molecular biology techniques has enabled the identification of molecular mechanisms underlying the observed phenotypic resistance to antibiotics in H. pylori. The aim of this literature review is to summarize the results of original articles published in the last ten years, regarding the use of Next Generation Sequencing, in particular of the whole genome, to predict the antibiotic resistance in H. pylori.Methods: a literature research was made on PubMed. The research was focused on II and III generation sequencing of the whole H. pylori genome. Results: Next Generation Sequencing enabled the detection of novel, rare and complex resistance mechanisms. The prediction of resistance to clarithromycin, levofloxacin and amoxicillin is accurate; for other antimicrobials, such as metronidazole, rifabutin and tetracycline, potential genetic determinants of the resistant status need further investigation.

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 Multidrug-Resistant Enterococci Lack CRISPR-cas

mBio ◽  
2010 ◽  
Vol 1 (4) ◽  
Author(s):  
Kelli L. Palmer ◽  
Michael S. Gilmore
Keyword(s):  
Antibiotic Resistance ◽  
Draft Genome ◽  
Inverse Correlation ◽  
Multidrug Resistant ◽  
Mobile Elements ◽  
Mobile Dna ◽  
Data Set ◽  
Content Type ◽  
Genome Defense ◽  
Acquired Antibiotic Resistance

ABSTRACT Clustered, regularly interspaced short palindromic repeats (CRISPR) provide bacteria and archaea with sequence-specific, acquired defense against plasmids and phage. Because mobile elements constitute up to 25% of the genome of multidrug-resistant (MDR) enterococci, it was of interest to examine the codistribution of CRISPR and acquired antibiotic resistance in enterococcal lineages. A database was built from 16 Enterococcus faecalis draft genome sequences to identify commonalities and polymorphisms in the location and content of CRISPR loci. With this data set, we were able to detect identities between CRISPR spacers and sequences from mobile elements, including pheromone-responsive plasmids and phage, suggesting that CRISPR regulates the flux of these elements through the E. faecalis species. Based on conserved locations of CRISPR and CRISPR-cas loci and the discovery of a new CRISPR locus with associated functional genes, CRISPR3-cas, we screened additional E. faecalis strains for CRISPR content, including isolates predating the use of antibiotics. We found a highly significant inverse correlation between the presence of a CRISPR-cas locus and acquired antibiotic resistance in E. faecalis, and examination of an additional eight E. faecium genomes yielded similar results for that species. A mechanism for CRISPR-cas loss in E. faecalis was identified. The inverse relationship between CRISPR-cas and antibiotic resistance suggests that antibiotic use inadvertently selects for enterococcal strains with compromised genome defense. IMPORTANCE For many bacteria, including the opportunistically pathogenic enterococci, antibiotic resistance is mediated by acquisition of new DNA and is frequently encoded on mobile DNA elements such as plasmids and transposons. Certain enterococcal lineages have recently emerged that are characterized by abundant mobile DNA, including numerous viruses (phage), and plasmids and transposons encoding multiple antibiotic resistances. These lineages cause hospital infection outbreaks around the world. The striking influx of mobile DNA into these lineages is in contrast to what would be expected if a self (genome)-defense system was present. Clustered, regularly interspaced short palindromic repeat (CRISPR) defense is a recently discovered mechanism of prokaryotic self-defense that provides a type of acquired immunity. Here, we find that antibiotic resistance and possession of complete CRISPR loci are inversely related and that members of recently emerged high-risk enterococcal lineages lack complete CRISPR loci. Our results suggest that antibiotic therapy inadvertently selects for enterococci with compromised genome defense.

scholarly journals Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes

2014 ◽  
Vol 171 (3-4) ◽  
pp. 441-447 ◽  
Author(s):  
G.C.A. Amos ◽  
L. Zhang ◽  
P.M. Hawkey ◽  
W.H. Gaze ◽  
E.M. Wellington
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Metagenomic Analysis

scholarly journals Increased mosquito abundance and species richness in Connecticut, United States 2001–2019

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tanya A. Petruff ◽  
Joseph R. McMillan ◽  
John J. Shepard ◽  
Theodore G. Andreadis ◽  
Philip M. Armstrong
Keyword(s):  
United States ◽  
Species Richness ◽  
Community Composition ◽  
Pathogen Transmission ◽  
Public Health Importance ◽  
Data Set ◽  
Mosquito Abundance ◽  
Total Species Richness ◽  
Multiple Species ◽  
Total Species

Abstract Historical declines in multiple insect taxa have been documented across the globe in relation to landscape-level changes in land use and climate. However, declines have either not been universally observed in all regions or examined for all species. Because mosquitoes are insects of public health importance, we analyzed a longitudinal mosquito surveillance data set from Connecticut (CT), United States (U.S.) from 2001 to 2019 to identify changes in mosquito community composition over time. We first analyzed annual site-level collections and metrics of mosquito community composition with generalized linear/additive mixed effects models; we also examined annual species-level collections using the same tools. We then examined correlations between statewide collections and weather variables as well as site-level collections and land cover classifications. We found evidence that the average trap night collection of mosquitoes has increased by ~ 60% and statewide species richness has increased by ~ 10% since 2001. Total species richness was highest in the southern portion of CT, likely due to the northward range expansion of multiple species within the Aedes, Anopheles, Culex, and Psorophora genera. How the expansion of mosquito populations in the northeast U.S. will alter mosquito-borne pathogen transmission in the region will require further investigation.

scholarly journals Estimating relatedness between malaria parasites

2019 ◽  
Author(s):  
Aimee R. Taylor ◽  
Pierre E. Jacob ◽  
Daniel E. Neafsey ◽  
Caroline O. Buckee
Keyword(s):  
Genetic Epidemiology ◽  
Ad Hoc ◽  
Pathogen Transmission ◽  
Identity By Descent ◽  
Malaria Parasites ◽  
Data Set ◽  
Epidemiology Studies ◽  
Diverse Data ◽  
Prospective Study Design ◽  
Identity By State

1.AbstractUnderstanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites,Plasmodium falciparumandPlasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

scholarly journals A computationally tractable birth-death model that combines phylogenetic and epidemiological data

2020 ◽  
Author(s):  
Alexander E. Zarebski ◽  
Louis du Plessis ◽  
Kris V. Parag ◽  
Oliver G. Pybus
Keyword(s):  
Transmission Rate ◽  
Epidemiological Data ◽  
Heterogeneous Data ◽  
Pathogen Transmission ◽  
Data Sources ◽  
Primary Data ◽  
Analytic Approximation ◽  
Data Set ◽  
Combining Data ◽  
Birth Death

Inferring the dynamics of pathogen transmission during an outbreak is an important problem in both infectious disease epidemiology and phylodynamics. In mathematical epidemiology, estimates are often informed by time-series of infected cases while in phylodynamics genetic sequences sampled through time are the primary data source. Each data type provides different, and potentially complementary, insights into transmission. However inference methods are typically highly specialised and field-specific. Recent studies have recognised the benefits of combining data sources, which include improved estimates of the transmission rate and number of infected individuals. However, the methods they employ are either computationally prohibitive or require intensive simulation, limiting their real-time utility. We present a novel birth-death phylogenetic model, called TimTam which can be informed by both phylogenetic and epidemiological data. Moreover, we derive a tractable analytic approximation of the TimTam likelihood, the computational complexity of which is linear in the size of the data set. Using the TimTam we show how key parameters of transmission dynamics and the number of unreported infections can be estimated accurately using these heterogeneous data sources. The approximate likelihood facilitates inference on large data sets, an important consideration as such data become increasingly common due to improving sequencing capability.

scholarly journals Detection of ESKAPE pathogens and Clostridioides difficile in Simulated Skin Transmission Events with Metagenomic and Metatranscriptomic Sequencing

2021 ◽  
Author(s):  
Krista L. Ternus ◽  
Nicolette C. Keplinger ◽  
Anthony D. Kappell ◽  
Gene D. Godbold ◽  
Veena Palsikar ◽  
...  
Keyword(s):  
Microbial Community ◽  
Antimicrobial Resistance ◽  
Epidemiological Studies ◽  
Pathogen Transmission ◽  
Metagenomic Analysis ◽  
Indirect Transmission ◽  
Healthcare Settings ◽  
Clostridioides Difficile ◽  
Analysis Methods ◽  
Global Threat

1AbstractBackgroundAntimicrobial resistance is a significant global threat, posing major public health risks and economic costs to healthcare systems. Bacterial cultures are typically used to diagnose healthcare-acquired infections (HAI); however, culture-dependent methods provide limited presence/absence information and are not applicable to all pathogens. Next generation sequencing (NGS) has the capacity to detect a wide variety of pathogens, virulence elements, and antimicrobial resistance (AMR) signatures in healthcare settings without the need for culturing, but few research studies have explored how NGS could be used to detect viable human pathogen transmission events under different HAI-relevant scenarios.MethodsThe objective of this project was to assess the capability of NGS-based methods to detect the direct and indirect transmission of high priority healthcare-related pathogens. DNA was extracted and sequenced from a previously published study exploring pathogen transfer with simulated skin containing background microorganisms, which allowed for complementary culture and metagenomic analysis comparisons. RNA was also isolated from an additional set of samples to evaluate metatranscriptomic analysis methods at different concentrations.ResultsUsing various analysis methods and custom reference databases, both pathogenic and non-pathogenic members of the microbial community were taxonomically identified. Virulence and AMR genes known to reside within the community were also routinely detected. Ultimately, pathogen abundance within the overall microbial community played the largest role in successful taxonomic classification and gene identification.ConclusionsThese results illustrate the utility of metagenomic analysis in clinical settings or for epidemiological studies, but also highlight the limits associated with the detection and characterization of pathogens at low abundance in a microbial community.

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