An economic evaluation of the Whole Genome Sequencing source tracking program in the U.S.
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ABSTRACT:
SUBMITTER: Brown B
PROVIDER: S-EPMC8494326 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The spread of multidrug-resistant Staphylococcus aureus (MRSA) strains in the clinical environment has begun to pose serious limits to treatment options. Yet virtually nothing is known about how resistance traits are acquired in vivo. Here, we apply the power of whole-genome sequencing to identify steps in the evolution of multidrug resistance in isogenic S. aureus isolates recovered periodically from the bloodstream of a patient undergoing chemotherapy with vancomycin and other antibiotics. After extensive therapy, the bacterium developed resistance, and treatment failed. Sequencing the first vancomycin susceptible isolate and the last vancomycin nonsusceptible isolate identified genome wide only 35 point mutations in 31 loci. These mutations appeared in a sequential order in isolates that were recovered at intermittent times during chemotherapy in parallel with increasing levels of resistance. The vancomycin nonsusceptible isolates also showed a 100-fold decrease in susceptibility to daptomycin, although this antibiotic was not used in the therapy. One of the mutated loci associated with decreasing vancomycin susceptibility (the vraR operon) was found to also carry mutations in six additional vancomycin nonsusceptible S. aureus isolates belonging to different genetic backgrounds and recovered from different geographic sites. As costs drop, whole-genome sequencing will become a useful tool in elucidating complex pathways of in vivo evolution in bacterial pathogens.
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Project description:Brucellosis is a zoonotic disease caused by Brucella spp. and a major concern for livestock. Most human cases are caused by B. melitensis and clinical presentation is usually a mild febrile illness. However, treatment failure is frequent and more severe complications can occur. In Austria, every human brucellosis is investigated to determine whether it was imported from endemic areas or is the sign of an undetected autochthonous transmission. For this study, 21 B. melitensis strains isolated in Austria between 2005 and 2019 were collected, 17 strains from 15 different patients and four strains from cattle. Whole genome sequencing combined with core-genome MLST analysis was used to characterize these strains. A cluster of seven isolates from 2018 (three human and four cattle isolates) was identified, with fewer than two allelic differences. They corresponded to the only Austrian B. melitensis outbreak that happened over the past 15 years. The other 12 Austrian brucellosis cases were single cases, and geographical origins were available for 8/12. Genomic data was used to locate probable geographical origins and compared with the results of the epidemiological investigations. Austrian strains were compared with 67 published B. melitensis sequences available on NCBI. The result of genomic analysis matched for 7/8 cases with documented conclusion of the epidemiological investigation. Genome analysis also pointed to the geographical origin for three of the four cases with missing epidemiological data. Strains from six cases were grouped together (<40 allelic differences) with 4/6 cases imported from the Balkans. Additional B. melitensis isolates from Serbian animals were analyzed and grouped with this branch, suggesting frequent importation from Balkan countries to Austria. Overall, this study highlights the specificities of human brucellosis in Austria. It also underlines the value of whole genome sequencing as a tool to investigate brucellosis cases, allowing to identify and investigate outbreaks but also to support epidemiological investigation of imported cases. However, the reliability of such methods depends on the number of strains for comparison, which can be challenging in low incidence countries. Increasing the availability of published sequences with documented geographical origins would help establishing genomic-based methods for investigating brucellosis cases.
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Project description:Novel developments in genomic medicine may reduce the length of the diagnostic odyssey for patients with rare diseases. Health providers must thus decide whether to offer genome sequencing for the diagnosis of rare conditions in a routine clinical setting. We estimated the costs of singleton standard genetic testing and trio-based whole genome sequencing (WGS), in the context of the Scottish Genomes Partnership (SGP) study. We also explored what users value about genomic sequencing. Insights from the costing and value assessments will inform a subsequent economic evaluation of genomic medicine in Scotland. An average cost of £1,841 per singleton was estimated for the standard genetic testing pathway, with significant variability between phenotypes. WGS cost £6625 per family trio, but this estimate reflects the use of WGS during the SGP project and large cost savings may be realised if sequencing was scaled up. Patients and families valued (i) the chance of receiving a diagnosis (and the peace of mind and closure that brings); (ii) the information provided by WGS (including implications for family planning and secondary findings); and (iii) contributions to future research. Our costings will be updated to address limitations of the current study for incorporation in budget impact modelling and cost-effectiveness analysis (cost per diagnostic yield). Our insights into the benefits of WGS will guide the development of a discrete choice experiment valuation study. This will inform a user-perspective cost-benefit analysis of genome-wide sequencing, accounting for the broader non-health outcomes. Taken together, our research will inform the long-term strategic development of NHS Scotland clinical genetics testing services, and will be of benefit to others seeking to undertake similar evaluations in different contexts.
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Project description:The Gram-negative bacteria Klebsiella pneumoniae is a major cause of nosocomial infections, primarily among immunocompromised patients. The emergence of strains resistant to carbapenems has left few treatment options, making infection containment critical. In 2011, the U.S. National Institutes of Health Clinical Center experienced an outbreak of carbapenem-resistant K. pneumoniae that affected 18 patients, 11 of whom died. Whole-genome sequencing was performed on K. pneumoniae isolates to gain insight into why the outbreak progressed despite early implementation of infection control procedures. Integrated genomic and epidemiological analysis traced the outbreak to three independent transmissions from a single patient who was discharged 3 weeks before the next case became clinically apparent. Additional genomic comparisons provided evidence for unexpected transmission routes, with subsequent mining of epidemiological data pointing to possible explanations for these transmissions. Our analysis demonstrates that integration of genomic and epidemiological data can yield actionable insights and facilitate the control of nosocomial transmission.
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Project description:UnlabelledMethicillin-resistant Staphylococcus aureus (MRSA) USA300 is a successful S. aureus clone in the United States and a common cause of skin and soft tissue infections (SSTIs). We performed whole-genome sequencing (WGS) of 146 USA300 MRSA isolates from SSTIs and colonization cultures obtained from an investigation conducted from 2008 to 2010 in Chicago and Los Angeles households that included an index case with an S. aureus SSTI. Identifying unique single nucleotide polymorphisms (SNPs) and analyzing whole-genome phylogeny, we characterized isolates to understand transmission dynamics, genetic relatedness, and microevolution of USA300 MRSA within the households. We also compared the 146 USA300 MRSA isolates from our study with the previously published genome sequences of the USA300 MRSA isolates from San Diego (n = 35) and New York City (n = 277). We found little genetic variation within the USA300 MRSA household isolates from Los Angeles (mean number of SNPs ± standard deviation, 17.6 ± 35; π nucleotide diversity, 3.1 × 10(-5)) or from Chicago (mean number of SNPs ± standard deviation, 12 ± 19; π nucleotide diversity, 3.1 × 10(-5)). The isolates within a household clustered into closely related monophyletic groups, suggesting the introduction into and transmission within each household of a single common USA300 ancestral strain. From a Bayesian evolutionary reconstruction, we inferred that USA300 persisted within households for 2.33 to 8.35 years prior to sampling. We also noted that fluoroquinolone-resistant USA300 clones emerged around 1995 and were more widespread in Los Angeles and New York City than in Chicago. Our findings strongly suggest that unique USA300 MRSA isolates are transmitted within households that contain an individual with an SSTI. Decolonization of household members may be a critical component of prevention programs to control USA300 MRSA spread in the United States.ImportanceUSA300, a virulent and easily transmissible strain of methicillin-resistant Staphylococcus aureus (MRSA), is the predominant community-associated MRSA clone in the United States. It most commonly causes skin infections but also causes necrotizing pneumonia and endocarditis. Strategies to limit the spread of MRSA in the community can only be effective if we understand the most common sources of transmission and the microevolutionary processes that provide a fitness advantage to MRSA. We performed a whole-genome sequence comparison of 146 USA300 MRSA isolates from Chicago and Los Angeles. We show that households represent a frequent site of transmission and a long-term reservoir of USA300 strains; individuals within households transmit the same USA300 strain among themselves. Our study also reveals that a large proportion of the USA300 isolates sequenced are resistant to fluoroquinolone antibiotics. The significance of this study is that if households serve as long-term reservoirs of USA300, household MRSA eradication programs may result in a uniquely effective control method.
| S-EPMC4453535 | biostudies-literature
Project description:Numerous viral sequences have been reported in the whole-genome sequencing (WGS) data of human blood. However, it is not clear to what degree the virus-mappable reads represent true viral sequences rather than random-mapping or noise originating from sample preparation, sequencing processes, or other sources. Identification of patterns of virus-mappable reads may generate novel indicators for evaluating the origins of these viral sequences. We characterized paired-end unmapped reads and reads aligned to viral references in human WGS datasets, then compared patterns of the virus-mappable reads among DNA sources and sequencing facilities which produced these datasets. We then examined potential origins of the source- and facility-associated viral reads. The proportions of clean unmapped reads among the seven sequencing facilities were significantly different (P < 2 × 10-16). We identified 260,339 reads that were mappable to a total of 99 viral references in 2535 samples. The majority (86.7%) of these virus-mappable reads (corresponding to 47 viral references), which can be classified into four groups based on their distinct patterns, were strongly associated with sequencing facility or DNA source (adjusted P value <0.01). Possible origins of these reads include artificial sequences in library preparation, recombinant vectors in cell culture, and phages co-contaminated with their host bacteria. The sequencing facility-associated virus-mappable reads and patterns were repeatedly observed in other datasets produced in the same facilities. We have constructed an analytic framework and profiled the unmapped reads mappable to viral references. The results provide a new understanding of sequencing facility- and DNA source-associated batch effects in deep sequencing data and may facilitate improved bioinformatics filtering of reads.
| S-EPMC7856238 | biostudies-literature
Project description:Campylobacter spp. are a leading and increasing cause of gastrointestinal infections worldwide. Source attribution, which apportions human infection cases to different animal species and food reservoirs, has been instrumental in control- and evidence-based intervention efforts. The rapid increase in whole-genome sequencing data provides an opportunity for higher-resolution source attribution models. Important challenges, including the high dimension and complex structure of WGS data, have inspired concerted research efforts to develop new models. We propose network analysis models as an accurate, high-resolution source attribution approach for the sources of human campylobacteriosis. A weighted network analysis approach was used in this study for source attribution comparing different WGS data inputs. The compared model inputs consisted of cgMLST and wgMLST distance matrices from 717 human and 717 animal isolates from cattle, chickens, dogs, ducks, pigs and turkeys. SNP distance matrices from 720 human and 720 animal isolates were also used. The data were collected from 2015 to 2017 in Denmark, with the animal sources consisting of domestic and imports from 7 European countries. Clusters consisted of network nodes representing respective genomes and links representing distances between genomes. Based on the results, animal sources were the main driving factor for cluster formation, followed by type of species and sampling year. The coherence source clustering (CSC) values based on animal sources were 78%, 81% and 78% for cgMLST, wgMLST and SNP, respectively. The CSC values based on Campylobacter species were 78%, 79% and 69% for cgMLST, wgMLST and SNP, respectively. Including human isolates in the network resulted in 88%, 77% and 88% of the total human isolates being clustered with the different animal sources for cgMLST, wgMLST and SNP, respectively. Between 12% and 23% of human isolates were not attributed to any animal source. Most of the human genomes were attributed to chickens from Denmark, with an average attribution percentage of 52.8%, 52.2% and 51.2% for cgMLST, wgMLST and SNP distance matrices respectively, while ducks from Denmark showed the least attribution of 0% for all three distance matrices. The best-performing model was the one using wgMLST distance matrix as input data, which had a CSC value of 81%. Results from our study show that the weighted network-based approach for source attribution is reliable and can be used as an alternative method for source attribution considering the high performance of the model. The model is also robust across the different Campylobacter species, animal sources and WGS data types used as input.
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Project description:Although a standard genome-wide significance level has been accepted for the testing of association between common genetic variants and disease, the era of whole-genome sequencing (WGS) requires a new threshold. The allele frequency spectrum of sequence-identified variants is very different from common variants, and the identified rare genetic variation is usually jointly analyzed in a series of genomic windows or regions. In nearby or overlapping windows, these test statistics will be correlated, and the degree of correlation is likely to depend on the choice of window size, overlap, and the test statistic. Furthermore, multiple analyses may be performed using different windows or test statistics. Here we propose an empirical approach for estimating genome-wide significance thresholds for data arising from WGS studies, and we demonstrate that the empirical threshold can be efficiently estimated by extrapolating from calculations performed on a small genomic region. Because analysis of WGS may need to be repeated with different choices of test statistics or windows, this prediction approach makes it computationally feasible to estimate genome-wide significance thresholds for different analysis choices. Based on UK10K whole-genome sequence data, we derive genome-wide significance thresholds ranging between 2.5 × 10(-8) and 8 × 10(-8) for our analytic choices in window-based testing, and thresholds of 0.6 × 10(-8) -1.5 × 10(-8) for a combined analytic strategy of testing common variants using single-SNP tests together with rare variants analyzed with our sliding-window test strategy.
| S-EPMC4489336 | biostudies-other
Project description:Whole genome sequencing (WGS), using high throughput sequencing technology, reveals the complete sequence of the bacterial genome in a few days. WGS is increasingly being used for source tracking, pathogen surveillance and outbreak investigation due to its high discriminatory power. In the food industry, WGS used for source tracking is beneficial to support contamination investigations. Despite its increased use, no standards or guidelines are available today for the use of WGS in outbreak and/or trace-back investigations. Here we present a validation of our complete (end-to-end) WGS workflow for Listeria monocytogenes and Salmonella enterica including: subculture of isolates, DNA extraction, sequencing and bioinformatics analysis. This end-to-end WGS workflow was evaluated according to the following performance criteria: stability, repeatability, reproducibility, discriminatory power, and epidemiological concordance. The current study showed that few single nucleotide polymorphism (SNPs) were observed for L. monocytogenes and S. enterica when comparing genome sequences from five independent colonies from the first subculture and five independent colonies after the tenth subculture. Consequently, the stability of the WGS workflow for L. monocytogenes and S. enterica was demonstrated despite the few genomic variations that can occur during subculturing steps. Repeatability and reproducibility were also demonstrated. The WGS workflow was shown to have a high discriminatory power and has the ability to show genetic relatedness. Additionally, the WGS workflow was able to reproduce published outbreak investigation results, illustrating its capability of showing epidemiological concordance. The current study proposes a validation approach comprising all steps of a WGS workflow and demonstrates that the workflow can be applied to L. monocytogenes or S. enterica.
| S-EPMC5861296 | biostudies-literature
Project description:BackgroundWith rapidly dropping sequencing cost, the popularity of whole-genome DNA methylation sequencing has been on the rise. Multiple library preparation protocols currently exist. We have performed 22 whole-genome DNA methylation sequencing experiments on snap frozen human samples, and extensively benchmarked common library preparation protocols for whole-genome DNA methylation sequencing, including three traditional bisulfite-based protocols and a new enzyme-based protocol. In addition, different input DNA quantities were compared for two kits compatible with a reduced starting quantity. In addition, we also present bioinformatic analysis pipelines for sequencing data from each of these library types.ResultsAn assortment of metrics were collected for each kit, including raw read statistics, library quality and uniformity metrics, cytosine retention, and CpG beta value consistency between technical replicates. Overall, the NEBNext Enzymatic Methyl-seq and Swift Accel-NGS Methyl-Seq kits performed quantitatively better than the other two protocols. In addition, the NEB and Swift kits performed well at low-input amounts, validating their utility in applications where DNA is the limiting factor.ResultsThe NEBNext Enzymatic Methyl-seq kit appeared to be the best option for whole-genome DNA methylation sequencing of high-quality DNA, closely followed by the Swift kit, which potentially works better for degraded samples. Further, a general bioinformatic pipeline is applicable across the four protocols, with the exception of extra trimming needed for the Swift Biosciences's Accel-NGS Methyl-Seq protocol to remove the Adaptase sequence.
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