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Unbiased metagenomic sequencing complements specific routine diagnostic methods and increases chances to detect rare viral strains.

ABSTRACT: Multiplex PCR assays for respiratory viruses are widely used in routine diagnostics, as they are highly sensitive, rapid, and cost effective. However, depending on the assay system, cross-reactivity between viruses that share a high sequence homology as well as detection of rare virus isolates with sequence variations can be problematic. Virus sequence-independent metagenomic high-throughput sequencing allows for accurate detection of all virus species in a given sample, as we demonstrate here for human Enterovirus and Rhinovirus in a lung transplant patient. While early in infection a commercial PCR assay recorded Rhinovirus, high-throughput sequencing correctly identified human Enterovirus C104 as the source of infection, highlighting the potential of the technology and the benefit of applying open assay formats in complex diagnostic situations.

SUBMITTER: Lewandowska DW

PROVIDER: S-EPMC7172999 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Unbiased metagenomic sequencing complements specific routine diagnostic methods and increases chances to detect rare viral strains.

Lewandowska Dagmara W DW Zagordi Osvaldo O Zbinden Andrea A Schuurmans Macé M MM Schreiber Peter P Geissberger Fabienne-Desirée FD Huder Jon B JB Böni Jürg J Benden Christian C Mueller Nicolas J NJ Trkola Alexandra A Huber Michael M

Diagnostic microbiology and infectious disease 20150629 2

Multiplex PCR assays for respiratory viruses are widely used in routine diagnostics, as they are highly sensitive, rapid, and cost effective. However, depending on the assay system, cross-reactivity between viruses that share a high sequence homology as well as detection of rare virus isolates with sequence variations can be problematic. Virus sequence-independent metagenomic high-throughput sequencing allows for accurate detection of all virus species in a given sample, as we demonstrate here f ...[more]

PMID: 26231254

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Project description:ObjectiveTo determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population.DesignRetrospective, population based diagnostic evaluation.Participants49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project.Main outcome measuresGenotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data.ResultsOverall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03).ConclusionsSNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

Project description:IntroductionMetagenomic next-generation sequencing (mNGS) assay for detecting infectious agents is now in the stage of being translated into clinical practice. With no approved approaches or guidelines available, laboratories adopt customized mNGS assays to detect clinical samples. However, the accuracy, reliability, and problems of these routinely implemented assays are not clear.ObjectivesTo evaluate the performance of 90 mNGS laboratories under routine testing conditions through analyzing identical samples.MethodsEleven microbial communities were generated using 15 quantitative microbial suspensions. They were used as reference materials to evaluate the false negatives and false positives of participating mNGS protocols, as well as the ability to distinguish genetically similar organisms and to identify true pathogens from other microbes based on fictitious case reports.ResultsHigh interlaboratory variability was found in the identification and the quantitative reads per million reads (RPM) values of each microbe in the samples, especially when testing microbes present at low concentrations (1 × 103 cell/ml or less). 42.2% (38/90) of the laboratories reported unexpected microbes (i.e. false positive problem). Only 56.7% (51/90) to 83.3% (75/90) of the laboratories showed a sufficient ability to obtain clear etiological diagnoses for three simulated cases combined with patient information. The analysis of the performance of mNGS in distinguishing genetically similar organisms in three samples revealed that only 56.6% to 63.0% of the laboratories recovered RPM ratios (RPM S. aureus /RPM S. epidermidis ) within the range of a 2-fold change of the initial input ratios (indicating a relatively low level of bias).ConclusionThe high interlaboratory variability found in both identifying microbes and distinguishing true pathogens emphasizes the urgent need for improving the accuracy and comparability of the results generated across different mNGS laboratories, especially in the detection of low-microbial-biomass samples.

Dataset Information

Unbiased metagenomic sequencing complements specific routine diagnostic methods and increases chances to detect rare viral strains.

Publications

Unbiased metagenomic sequencing complements specific routine diagnostic methods and increases chances to detect rare viral strains.

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