Whole-Genome Sequencing to Determine Origin of Multinational Outbreak of Sarocladium kiliense Bloodstream Infections.
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ABSTRACT:
SUBMITTER: Etienne KA
PROVIDER: S-EPMC4766898 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:RationaleCurrent tools available to study the molecular epidemiology of tuberculosis do not provide information about the directionality and sequence of transmission for tuberculosis cases occurring over a short period of time, such as during an outbreak. Recently, whole genome sequencing has been used to study molecular epidemiology of Mycobacterium tuberculosis over short time periods.ObjectiveTo describe the microevolution of M. tuberculosis during an outbreak caused by one drug-susceptible strain. METHOD AND MEASUREMENTS: We included 9 patients with tuberculosis diagnosed during a period of 22 months, from a population-based study of the molecular epidemiology in San Francisco. Whole genome sequencing was performed using Illumina's sequencing by synthesis technology. A custom program written in Python was used to determine single nucleotide polymorphisms which were confirmed by PCR product Sanger sequencing.Main resultsWe obtained an average of 95.7% (94.1-96.9%) coverage for each isolate and an average fold read depth of 73 (1 to 250). We found 7 single nucleotide polymorphisms among the 9 isolates. The single nucleotide polymorphisms data confirmed all except one known epidemiological link. The outbreak strain resulted in 5 bacterial variants originating from the index case A1 with 0-2 mutations per transmission event that resulted in a secondary case.ConclusionsWhole genome sequencing analysis from a recent outbreak of tuberculosis enabled us to identify microevolutionary events observable during transmission, to determine 0-2 single nucleotide polymorphisms per transmission event that resulted in a secondary case, and to identify new epidemiologic links in the chain of transmission.
| S-EPMC3589338 | biostudies-literature
Project description:BackgroundThough detection of transmission clusters of methicillin-resistant Staphylococcus aureus (MRSA) infections is a priority for infection control personnel in hospitals, the transmission dynamics of MRSA among hospitalized patients with bloodstream infections (BSIs) has not been thoroughly studied. Whole genome sequencing (WGS) of MRSA isolates for surveillance is valuable for detecting outbreaks in hospitals, but the bioinformatic approaches used are diverse and difficult to compare.MethodsWe combined short-read WGS with genotypic, phenotypic, and epidemiological characteristics of 106 MRSA BSI isolates collected for routine microbiological diagnosis from inpatients in 2 hospitals over 12 months. Clinical data and hospitalization history were abstracted from electronic medical records. We compared 3 genome sequence alignment strategies to assess similarity in cluster ascertainment. We conducted logistic regression to measure the probability of predicting prior hospital overlap between clustered patient isolates by the genetic distance of their isolates.ResultsWhile the 3 alignment approaches detected similar results, they showed some variation. A gene family-based alignment pipeline was most consistent across MRSA clonal complexes. We identified 9 unique clusters of closely related BSI isolates. Most BSIs were healthcare associated and community onset. Our logistic model showed that with 13 single-nucleotide polymorphisms, the likelihood that any 2 patients in a cluster had overlapped in a hospital was 50%.ConclusionsMultiple clusters of closely related MRSA isolates can be identified using WGS among strains cultured from BSI in 2 hospitals. Genomic clustering of these infections suggests that transmission resulted from a mix of community spread and healthcare exposures long before BSI diagnosis.
| S-EPMC10200302 | biostudies-literature
Project description:BackgroundEscherichia coli is the most common cause of bloodstream infections (BSIs) and mortality is an important aspect of burden of disease. Using a multinational population-based cohort of E. coli BSIs, our objectives were to evaluate 30-day case fatality risk and mortality rate, and determine factors associated with each.MethodsDuring 2014-2018, we identified 30-day deaths from all incident E. coli BSIs from surveillance nationally in Finland, and regionally in Sweden (Skaraborg) and Canada (Calgary, Sherbrooke, western interior). We used a multivariable logistic regression model to estimate factors associated with 30-day case fatality risk. The explanatory variables considered for inclusion were year (2014-2018), region (five areas), age (< 70-years-old, ≥70-years-old), sex (female, male), third-generation cephalosporin (3GC) resistance (susceptible, resistant), and location of onset (community-onset, hospital-onset). The European Union 28-country 2018 population was used to directly age and sex standardize mortality rates. We used a multivariable Poisson model to estimate factors associated with mortality rate, and year, region, age and sex were considered for inclusion.ResultsFrom 38.7 million person-years of surveillance, we identified 2961 30-day deaths in 30,923 incident E. coli BSIs. The overall 30-day case fatality risk was 9.6% (2961/30923). Calgary, Skaraborg, and western interior had significantly increased odds of 30-day mortality compared to Finland. Hospital-onset and 3GC-resistant E. coli BSIs had significantly increased odds of mortality compared to community-onset and 3GC-susceptible. The significant association between age and odds of mortality varied with sex, and contrasts were used to interpret this interaction relationship. The overall standardized 30-day mortality rate was 8.5 deaths/100,000 person-years. Sherbrooke had a significantly lower 30-day mortality rate compared to Finland. Patients that were either ≥70-years-old or male both experienced significantly higher mortality rates than those < 70-years-old or female.ConclusionsIn our study populations, region, age, and sex were significantly associated with both 30-day case fatality risk and mortality rate. Additionally, 3GC resistance and location of onset were significantly associated with 30-day case fatality risk. Escherichia coli BSIs caused a considerable burden of disease from 30-day mortality. When analyzing population-based mortality data, it is important to explore mortality through two lenses, mortality rate and case fatality risk.
| S-EPMC8229717 | biostudies-literature
Project description:During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today's WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.
| S-EPMC4525730 | biostudies-literature
Project description:The clinical importance of Enterobacter spp. remains unclear because phenotype-based Enterobacter species identification is unreliable. We performed a genomic study on 48 cases of Enterobacter-caused bloodstream infection by using in silico DNA-DNA hybridization to identify precise species. Strains belonged to 12 species; Enterobacter xiangfangensis (n = 21) and an unnamed species (taxon 1, n = 8) were dominant. Most (63.5%) Enterobacter strains (n = 349) with genomes in GenBank from human blood are E. xiangfangensis; taxon 1 (19.8%) was next most common. E. xiangfangensis and taxon 1 were associated with increased deaths (20.7% vs. 15.8%), lengthier hospitalizations (median 31 d vs. 19.5 d), and higher resistance to aztreonam, cefepime, ceftriaxone, piperacillin-tazobactam, and tobramycin. Strains belonged to 37 sequence types (STs); ST171 (E. xiangfangensis) was most common (n = 6). Four ST171 strains belonged to a defined clone. Precise species identification has greater implications for epidemiology and infection control than treatment.
| S-EPMC7774573 | biostudies-literature
Project description:Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.
| S-EPMC4946012 | biostudies-other
Project description:BackgroundCampylobacter is one of the most frequent causes of bacterial gastroenteritis. Campylobacter outbreaks are rarely reported, which could be a reflection of a surveillance without routine molecular typing. We have previously shown that numerous small outbreak-like clusters can be detected when whole genome sequencing (WGS) data of clinical Campylobacter isolates was applied.AimTyping-based surveillance of Campylobacter infections was initiated in 2019 to enable detection of large clusters of clinical isolates and to match them to concurrent retail chicken isolates in order to react on ongoing outbreaks.MethodsWe performed WGS continuously on isolates from cases (n = 701) and chicken meat (n = 164) throughout 2019. Core genome multilocus sequence typing was used to detect clusters of clinical isolates and match them to isolates from chicken meat.ResultsSeventy-two clusters were detected, 58 small clusters (2-4 cases) and 14 large clusters (5-91 cases). One third of the clinical isolates matched isolates from chicken meat. One large cluster persisted throughout the whole year and represented 12% of all studied Campylobacter cases. This cluster type was detected in several chicken samples and was traced back to one slaughterhouse, where interventions were implemented to control the outbreak.ConclusionOur WGS-based surveillance has contributed to an improved understanding of the dynamics of the occurrence of Campylobacter strains in chicken meat and the correlation to clusters of human cases.
| S-EPMC8176674 | biostudies-literature
Project description:Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks.We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital.We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial "resistome" of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a "toxome" consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain.Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.).
| S-EPMC3715836 | biostudies-literature
Project description:Two Southeast Asian students attending the same school in the United Kingdom presented with pulmonary tuberculosis. An epidemiological investigation failed to link the two cases, and drug resistance profiles of the Mycobacterium tuberculosis isolates were discrepant. Whole-genome sequencing of the isolates found them to be genetically identical, suggesting a missed transmission event.
| S-EPMC3553910 | biostudies-literature
Project description:During June 2017-April 2018, active tuberculosis with Beijing SIT1 isolates was diagnosed in 14 persons living in 4 distant cities in France. Whole-genome sequencing indicated that these patients belonged to a single transmission chain. Whole-genome sequencing-based laboratory investigations enabled prompt tracing of linked cases to improve tuberculosis control.
| S-EPMC6390740 | biostudies-literature