Introduction Of Whole Genome Sequencing Research Articles

Clinical, microbiological, and molecular characterization of pediatric invasive infections by Streptococcus pyogenes in Spain in a context of global outbreak.

Group A Streptococcus (GAS) is a common bacterial pathogen in the pediatric population. In the last months of 2022, an unusual increase in GAS infections was detected in various countries. Certain strains were overrepresented, although the cause of this raise is not clear. In Spain, a significant increase in mild and severe cases was also observed; this study evaluates the clinical characteristics and the strains involved in both scenarios. Our study showed that the increase in incidence did not correlate with an increase in resistance or with an emm types shift. However, there seemed to be a rise in severity, partly related to a greater rate of pneumonia cases. These findings suggest a general increase in iGAS that highlights the need for surveillance. The introduction of whole genome sequencing in the diagnosis and surveillance of iGAS may improve the understanding of antibiotic resistance, virulence, and clones, facilitating its control and personalized treatment.

Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis.

Mixed infections of Mycobacterium tuberculosis, defined as the coexistence of multiple genetically distinct strains within a single host, have been associated with unfavorable treatment outcomes. Different methods have been used to detect mixed infections, but their performances have not been carefully evaluated. To compare the sensitivity of whole-genome sequencing (WGS) and variable-number tandem repeats (VNTR) typing to detect mixed infections, we prepared 10 artificial samples composed of DNA mixtures from two strains in different proportions and retrospectively collected 1,084 clinical isolates. The limit of detection (LOD) for the presence of a minor strain was 5% for both WGS and VNTR typing. The overall clinical detection rate of mixed infections was 3.7% (40/1,084) for the two methods combined, WGS identified 37/1,084 (3.4%), and VNTR typing identified 14/1,084 (1.3%), including 11 also identified by WGS. Multivariate analysis demonstrated that retreatment patients had a 2.7 times (95% confidence interval [CI], 1.2 to 6.0) higher risk of mixed infections than new cases. Collectively, WGS is a more reliable tool to identify mixed infections than VNTR typing, and mixed infections are more common in retreated patients. IMPORTANCE Mixed infections of M. tuberculosis have the potential to render treatment regimens ineffective and affect the transmission dynamics of the disease. VNTR typing, currently the most widely used method for the detection of mixed infections, detects mixed infections only by interrogating a small fraction of the M. tuberculosis genome, which necessarily limits sensitivity. With the introduction of WGS, it became possible to study the entire genome, but no quantitative comparison has yet been undertaken. Our systematic comparison of the ability of WGS and VNTR typing to detect mixed infections, using both artificial samples and clinical isolates, revealed the superior performance of WGS at a high sequencing depth (~100×) and found that mixed infections are more common in patients being retreated for tuberculosis (TB) in the populations studied. This provides valuable information for the application of WGS in the detection of mixed infections and the implications of mixed infections for tuberculosis control.

Challenging gold standard hematology diagnostics through the introduction of whole genome sequencing and artificial intelligence.

The diagnosis of hematological malignancies is rather complex and requires the application of a plethora of different assays, techniques and methodologies. Some of the methods, like cytomorphology, have been in use for decades, while other methods, such as next-generation sequencing or even whole genome sequencing (WGS), are relatively new. The application of the methods and the evaluation of the results require distinct skills and knowledge and place different demands on the practitioner. However, even with experienced hematologists, diagnostic ambiguity remains a regular occurrence and the comprehensive analysis of high-dimensional WGS data soon exceeds any human's capacity. Hence, in order to reduce inter-observer variability and to improve the timeliness and accuracy of diagnoses, machine learning based approaches have been developed to assist in the decision making process. Moreover, to achieve the goal of precision oncology, comprehensive genomic profiling is increasingly being incorporated into routine standard of care.

Effect of Whole-Genome Sequencing on the Clinical Management of Acutely Ill Infants With Suspected Genetic Disease

Whole-genome sequencing (WGS) shows promise as a first-line genetic test for acutely ill infants, but widespread adoption and implementation requires evidence of an effect on clinical management. To determine the effect of WGS on clinical management in a racially and ethnically diverse and geographically distributed population of acutely ill infants in the US. This randomized, time-delayed clinical trial enrolled participants from September 11, 2017, to April 30, 2019, with an observation period extending to July 2, 2019. The study was conducted at 5 US academic medical centers and affiliated children's hospitals. Participants included infants aged between 0 and 120 days who were admitted to an intensive care unit with a suspected genetic disease. Data were analyzed from January 14 to August 20, 2020. Patients were randomized to receive clinical WGS results 15 days (early) or 60 days (delayed) after enrollment, with the observation period extending to 90 days. Usual care was continued throughout the study. The main outcome was the difference in the proportion of infants in the early and delayed groups who received a change of management (COM) 60 days after enrollment. Additional outcome measures included WGS diagnostic efficacy, within-group COM at 90 days, length of hospital stay, and mortality. A total of 354 infants were randomized to the early (n = 176) or delayed (n = 178) arms. The mean participant age was 15 days (IQR, 7-32 days); 201 participants (56.8%) were boys; 19 (5.4%) were Asian; 47 (13.3%) were Black; 250 (70.6%) were White; and 38 (10.7%) were of other race. At 60 days, twice as many infants in the early group vs the delayed group received a COM (34 of 161 [21.1%; 95% CI, 15.1%-28.2%] vs 17 of 165 [10.3%; 95% CI, 6.1%-16.0%]; P = .009; odds ratio, 2.3; 95% CI, 1.22-4.32) and a molecular diagnosis (55 of 176 [31.0%; 95% CI, 24.5%-38.7%] vs 27 of 178 [15.0%; 95% CI, 10.2%-21.3%]; P < .001). At 90 days, the delayed group showed a doubling of COM (to 45 of 161 [28.0%; 95% CI, 21.2%-35.6%]) and diagnostic efficacy (to 56 of 178 [31.0%; 95% CI, 24.7%-38.8%]). The most frequent COMs across the observation window were subspecialty referrals (39 of 354; 11%), surgery or other invasive procedures (17 of 354; 4%), condition-specific medications (9 of 354; 2%), or other supportive alterations in medication (12 of 354; 3%). No differences in length of stay or survival were observed. In this randomized clinical trial, for acutely ill infants in an intensive care unit, introduction of WGS was associated with a significant increase in focused clinical management compared with usual care. Access to first-line WGS may reduce health care disparities by enabling diagnostic equity. These data support WGS adoption and implementation in this population. ClinicalTrials.gov Identifier: NCT03290469.

Transition From PCR-Ribotyping to Whole Genome Sequencing Based Typing of Clostridioides difficile.

Clostridioides difficile causes nosocomial outbreaks which can lead to severe and even life-threatening colitis. Rapid molecular diagnostic tests allow the identification of toxin-producing, potentially hypervirulent strains, which is critical for patient management and infection control. PCR-ribotyping has been used for decades as the reference standard to investigate transmission in suspected outbreaks. However, the introduction of whole genome sequencing (WGS) for molecular epidemiology provides a realistic alternative to PCR-ribotyping. In this transition phase it is crucial to understand the strengths and weaknesses of the two technologies, and to assess their correlation. We aimed to investigate ribotype prediction from WGS data, and options for analysis at different levels of analytical granularity. Ribotypes cannot be directly determined from short read Illumina sequence data as the rRNA operons including the ribotype-defining ISR fragments collapse in genome assemblies, and comparison with traditional PCR-ribotyping results becomes impossible. Ribotype extraction from long read Oxford nanopore data also requires optimization. We have compared WGS-based typing with PCR-ribotyping in nearly 300 clinical and environmental isolates from Switzerland, and in addition from the Enterobase database (n=1778). Our results show that while multi-locus sequence type (MLST) often correlates with a specific ribotype, the agreement is not complete, and for some ribotypes the resolution is insufficient. Using core genome MLST (cgMLST) analysis, there is an improved resolution and ribotypes can often be predicted within clusters, using cutoffs of 30-50 allele differences. The exceptions are ribotypes within known ribotype complexes such as RT078/RT106, where the genome differences in cgMLST do not reflect the ribotype segregation. We show that different ribotype clusters display different degrees of diversity, which could be important for the definition of ribotype cluster specific cutoffs. WGS-based analysis offers the ultimate resolution to the SNP level, enabling exploration of patient-to-patient transmission. PCR-ribotyping does not sufficiently discriminate to prove nosocomial transmission with certainty. We discuss the associated challenges and opportunities in a switch to WGS from conventional ribotyping for C. difficile.

Extensive Homoplasy but No Evidence of Convergent Evolution of Repeat Numbers at MIRU Loci in Modern Mycobacterium tuberculosis Lineages.

More human deaths have been attributable to Mycobacterium tuberculosis than any other pathogen, and the epidemic is sustained by ongoing transmission. Various typing schemes have been developed to identify strain-specific differences and track transmission dynamics in affected communities, with recent introduction of whole genome sequencing providing the most accurate assessment. Mycobacterial interspersed repetitive unit (MIRU) typing is a family of variable number tandem repeat schemes that have been widely used to study the molecular epidemiology of M. tuberculosis. MIRU typing was used in most well-resourced settings to perform routine molecular epidemiology. Instances of MIRU homoplasy have been observed in comparison with sequence-based phylogenies, limiting its discriminatory value. A fundamental question is whether the observed homoplasy arises purely through stochastic processes, or whether there is evidence of natural selection. We compared repeat numbers at 24 MIRU loci with a whole genome sequence-based phylogeny of 245 isolates representing three modern M. tuberculosis lineages. This analysis demonstrated extensive homoplasy of repeat numbers, but did not detect any evidence of natural selection of repeat numbers, at least since the ancestral branching of the three modern lineages of M. tuberculosis. In addition, we observed good sensitivity but poor specificity and positive predictive values of MIRU-24 to detect clusters of recent transmission, as defined by whole-genome single nucleotide polymorphism analysis. These findings provide mechanistic insight, and support a transition away from VNTR-based typing toward sequence-based typing schemes for both research and public health purposes.

Computational Health Engineering Applied to Model Infectious Diseases and Antimicrobial Resistance Spread

Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host–pathogen–protein interactions, combined with a better understanding of a host’s immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination.

Whole-Genome Sequencing in Relation to Resistance of Mycobacterium Tuberculosis

Abstract Tuberculosis, a disease caused by Mycobacterium tuberculosis, represents one of the deadliest infections worldwide. The incidence of resistant forms is increasing year by year; therefore, it is necessary to involve new methods for rapid diagnostics and treatment. One of the possible solutions is the use of whole-genome sequencing (WGS). The WGS provides an identification of complete genome of the microorganism, including all genes responsible for resistance, in comparison with other genotypic methods (eg. Xpert MTB / RIF or Hain line-probes) that are capable to detect only basic genes. WGS data are available in 1-9 days and several online software tools (TBProfiler, CASTB, Mykrobe PredictorTB) are used for their interpretation and analysis, compared to 3-8 weeks in the case of classic phenotypic evaluation. Furthermore, WGS predicts resistance to the first-line antituberculotics with a sensitivity of 85-100% and a specificity of 85-100%. This review elucidates the importance and summarizes the current knowledge about the possible use of WGS in diagnosis and treatment of resistant forms of tuberculosis elucidates. WGS of M. tuberculosis brings new possibilities for rapid and accurate diagnostics of resistant forms of tuberculosis. Introducing WGS into routine practice can help to reduce the spread of resistant forms of tuberculosis as well as to increase the success rate of the treatment, especially through an appropriate combination of antituberculotics ATs. Introduction of WGS into routine diagnostics can, in spite of the financial difficulty, significantly improve patient care.

Genomic approaches used to investigate an atypical outbreak of Salmonella Adjame

In 2017, an outbreak of gastroenteritis in England attributed to Salmonella Adjame was detected and investigated. With the introduction of whole genome sequencing (WGS) for microbial typing, methods for comparing international outbreak data require evaluation. A case was defined as a person resident in England with a clinical sample from 1 June 2017 to 27 July 2017 from whom S. Adjame was isolated. Cases were interviewed and exposures analysed. Backward tracing of food provenance was undertaken. WGS was performed on isolates from cases and historical isolates and compared using Public Health England’s SnapperDB high-quality SNP pipeline and Enterobase’s Salmonella core genome multi-locus sequence typing (cgMLST) scheme. In total, 14 cases were identified. The majority were vegetarian, probably of South Asian descent, with a median age of 66.5 years with no recent international travel reported. Cases consumed a range of fresh food products including herbs and spices bought from South Asian grocers. Backward tracing did not identify a common source. WGS typing showed sub-clustering and considerable genetic variation across human samples. cgMLST allele-based analysis was comparable to SNP-derived phylogenetic analysis and clusters were defined using each method. Imported herbs or spices were suspected vehicles. The cases were linked in time and place but WGS showed marked heterogeneity, atypical of a point source Salmonella outbreak. The application of incorporating SNP or allelic differences into the case definition may not always be appropriate. With further validation, cgMLST could be used for international outbreak alerts when WGS analysis is being undertaken to facilitate comparison.

An economic analysis of salmonella detection in fresh produce, poultry, and eggs using whole genome sequencing technology in Canada

The study estimates the annual costs of nontyphoidal Salmonellosis (referred to as Salmonellosis from hereon) from fresh produce, poultry and eggs in Canada. It also estimates the economic benefits from introduction of Whole Genome Sequencing (WGS) in detection of Salmonellosis clusters and outbreaks. Monetary and non-monetary costs from Salmonellosis are estimated. Monetary costs are divided into direct healthcare, indirect, federal and producer costs. Probability models are used to account for uncertainty in the cost-of-illness estimates. Two types of non-monetary costs have been estimated: Disability-adjusted Live Years and Quality-adjusted Life Years. These estimates are then used to calculate the economic impact of WGS on detection of Salmonellosis. The estimated incidence of illnesses is 47,082 annually, which represents a cost of $287.78 million (total cases) and $166.28 million (reported cases) from the traditional technology. The total net benefit from introduction of WGS is estimated to range from $5.21 million-$90.25 million. All monetary values are in CAD unless stated otherwise. WGS will help in reducing the economic burden from Salmonellosis. These estimates help will aid policy related decision making.

Molecular-based identification and detection of Salmonella in food production systems: current perspectives.

Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies have greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed.

OzFoodNet into the future: the rapid evolution of foodborne disease surveillance in Australia

OzFoodNet is Australia's national enhanced foodborne disease surveillance network. OzFoodNet is currently evolving in order to meet the most significant challenges faced since it commenced in 2000: the transition to culture independent diagnostic tests and the introduction of whole genome sequencing for typing of enteric pathogens. This has changed the nature of foodborne disease surveillance and outbreak investigation in Australia.

Next generation anatomy: integrating whole genome sequencing within the human anatomy curriculum (723.2)

Advances in genomics have vastly outpaced clinical education in this area. To help address this problem, the UW has piloted the introduction of whole genome sequencing within our first year human anatomy course.Last year, thirteen first‐year medical students performed whole genome sequencing and analysis of a cadaver during the anatomy course. The patient expired with a diagnosis of idiopathic pulmonary fibrosis. Students participated in a dissection of the cadaver, and a pathologist highlighted the anatomical changes resulting from the disease. Students then worked collaboratively to complete a ~45× whole genome sequence and then analyzed this patient’s genome using various bioinformatics tools. The analysis identified a variant in mucin‐encoding MUC5B that was recently associated with pulmonary fibrosis.A year later, these students presented their findings to small groups (&lt;20 students) of the new first year students and discussed the patient’s clinical history, the results of the dissection and genome sequencing.Our experience demonstrated the value of introducing whole genome sequencing within anatomy as an early entry point for establishing genotype‐phenotype associations in medical education.Grant Funding Source: Funding provided by University of Washington MSTP

Whole-Genome Sequencing in Newborn Screening Programs

The availability of whole-genome sequencing (WGS) is likely to change the practice of population screening programs such as newborn screening (NBS). This Commentary raises key ethical, legal, and social issues surrounding WGS in NBS and suggests a need for deliberation regarding the policy challenges of introducing sequencing in such programs. Any change in the goals of NBS programs should be discussed carefully and should represent the best interests of the child.

Managing incidental findings in population based biobank research

With the introduction of whole genome sequencing in medical research, the debate on how to handle incidental findings is becoming omnipresent. Much of the literature on the topic so far, seems to defend the researcher’s duty to inform, the participant’s right to know combined with a thorough informed consent in order to protect and secure high ethical standards in research. In this paper, we argue that this ethical response to incidental findings and whole genome sequencing is appropriate in a clinical context, in what we call therapeutic research. However, we further argue, that it is rather inappropriate in basic research, like the research going on in public health oriented population based biobanks. Our argument is based on two premises: First, in population based biobank research the duties and rights involved are radically different from a clinical based setting. Second, to introduce the ethical framework from the clinical setting into population based basic research, is not only wrong, but it may lead to unethical consequences. A Norwegian population based biobank and the research-ethical debate in Norway on the regulation of whole genome sequencing is used as an illustrative case to demonstrate the pitfalls when approaching the debate on incidental findings in population based biobank research.