Metagenomic Next-Generation Sequencing in Clinical Microbiology

Identification of causative pathogens in infectious disease is a critical component of health care, as infectious diseases continue to be a leading cause of mortality and morbidity worldwide. In addition, the detection of drug resistance by traditional and novel antimicrobial susceptibility testing methods is becoming ever more important as antimicrobial resistance continues to emerge and spread. While culture-based methods are the current reference standard for identifying microbes, the time required to achieve results and the difficulty in culturing certain fastidious organisms have led to the development of multiple alternatives. Alternatives to culture, such as polymerase chain reaction (PCR) assays, serologic assays, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS), and 16S rRNA gene sequencing have been used in clinical laboratories, and positive impacts on patient care have been documented. Nonetheless, such methods require either presumption about the type of microbes present in the sample or growth of the organism(s) before analysis. Subsequently, there are some documented limitations in the routine detection methods for clinically relevant organisms.In contrast to the routine alternatives listed above, modern nucleic acid sequencing platforms support sequencing of random DNA strands, an approach known as “shotgun” sequencing of the DNA, also known as metagenomic next-generation sequencing (mNGS) present in the sample. The mNGS approach offers an unbiased and hypothesis-free approach to pathogen identification with the future potential to (i) achieve results in 12 to 24 hours; (ii) avoid the challenges associated with growth of fastidious organisms; (iii) avoid the biased growth that occurs when only routine culture medium is used; (iv) detect viral, fungal, and parasitic organisms in the same assay; and (v) detect the presence of drug resistance genes. Advances in mNGS technology and data analysis have reduced testing costs to the point where the potential advantages of mNGS over culture and other methods warrant its development for use in clinical settings. In this review, the mNGS approach is discussed, along with a comparison to other methods, limitations, and suggestions for further development and overcoming hurdles to adoption in the clinical setting.     

Targeted Next‐Generation Sequencing can Replace Sanger Sequencing in Clinical Diagnostics

Mutation detection through exome sequencing allows simultaneous analysis of all coding sequences of genes. However, it cannot yet replace Sanger sequencing (SS) in diagnostics because of incomplete representation and coverage of exons leading to missing clinically relevant mutations. Targeted next‐generation sequencing (NGS), in which a selected fraction of genes is sequenced, may circumvent these shortcomings. We aimed to determine whether the sensitivity and specificity of targeted NGS is equal to those of SS. We constructed a targeted enrichment kit that includes 48 genes associated with hereditary cardiomyopathies. In total, 84 individuals with cardiomyopathies were sequenced using 151 bp paired‐end reads on an Illumina MiSeq sequencer. The reproducibility was tested by repeating the entire procedure for five patients. The coverage of ≥30 reads per nucleotide, our major quality criterion, was 99% and in total ～21,000 variants were identified. Confirmation with SS was performed for 168 variants (155 substitutions, 13 indels). All were confirmed, including a deletion of 18 bp and an insertion of 6 bp. The reproducibility was nearly 100%. We demonstrate that targeted NGS of a disease‐specific subset of genes is equal to the quality of SS and it can therefore be reliably implemented as a stand‐alone diagnostic test.     

Clinical Application of Whole-Genome Sequencing To Inform Treatment for Multidrug-Resistant Tuberculosis Cases

The treatment of drug-resistant tuberculosis cases is challenging, as drug options are limited, and the existing diagnostics are inadequate. Whole-genome sequencing (WGS) has been used in a clinical setting to investigate six cases of suspected extensively drug-resistant Mycobacterium tuberculosis (XDR-TB) encountered at a London teaching hospital between 2008 and 2014. Sixteen isolates from six suspected XDR-TB cases were sequenced; five cases were analyzed in a clinically relevant time frame, with one case sequenced retrospectively. WGS identified mutations in the M. tuberculosis genes associated with antibiotic resistance that are likely to be responsible for the phenotypic resistance. Thus, an evidence base was developed to inform the clinical decisions made around antibiotic treatment over prolonged periods. All strains in this study belonged to the East Asian (Beijing) lineage, and the strain relatedness was consistent with the expectations from the case histories, confirming one contact transmission event. We demonstrate that WGS data can be produced in a clinically relevant time scale some weeks before drug sensitivity testing (DST) data are available, and they actively help clinical decision-making through the assessment of whether an isolate (i) has a particular resistance mutation where there are absent or contradictory DST results, (ii) has no further resistance markers and therefore is unlikely to be XDR, or (iii) is identical to an isolate of known resistance (i.e., a likely transmission event). A small number of discrepancies between the genotypic predictions and phenotypic DST results are discussed in the wider context of the interpretation and reporting of WGS results.     

Comparison of MALDI-TOF MS,Housekeeping Gene Sequencing,and 16S rRNA Gene Sequencing for Identification of Aeromonas Clinical Isolates

PurposeThe genus Aeromonas is a pathogen that is well known to cause severe clinical illnesses, ranging from gastroenteritis to sepsis. Accurate identification of A. hydrophila, A. caviae, and A. veronii is important for the care of patients. However, species identification remains difficult using conventional methods. The aim of this study was to compare the accuracy of different methods of identifying Aeromonas at the species level: a biochemical method, matrix-assisted laser desorption ionization mass spectrometry-time of flight (MALDI-TOF MS), 16S rRNA sequencing, and housekeeping gene sequencing (gyrB, rpoB).ResultsThe conventional biochemical method and 16S rRNA sequencing identified Aeromonas at the genus level very accurately, although species level identification was unsatisfactory. MALDI-TOF MS system correctly identified 60 (92.3%) isolates at the species level and an additional four (6.2%) at the genus level. Overall, housekeeping gene sequencing with phylogenetic analysis was found to be the most accurate in identifying Aeromonas at the species level.ConclusionThe most accurate method of identification of Aeromonas to species level is by housekeeping gene sequencing, although high cost and technical difficulty hinder its usage in clinical settings. An easy-to-use identification method is needed for clinical laboratories, for which MALDI-TOF MS could be a strong candidate.     

Rapid Whole-Genome Sequencing for Detection and Characterization of Microorganisms Directly from Clinical Samples

Whole-genome sequencing (WGS) is becoming available as a routine tool for clinical microbiology. If applied directly on clinical samples, this could further reduce diagnostic times and thereby improve control and treatment. A major bottleneck is the availability of fast and reliable bioinformatic tools. This study was conducted to evaluate the applicability of WGS directly on clinical samples and to develop easy-to-use bioinformatic tools for the analysis of sequencing data. Thirty-five random urine samples from patients with suspected urinary tract infections were examined using conventional microbiology, WGS of isolated bacteria, and direct sequencing on pellets from the urine samples. A rapid method for analyzing the sequence data was developed. Bacteria were cultivated from 19 samples but in pure cultures from only 17 samples. WGS improved the identification of the cultivated bacteria, and almost complete agreement was observed between phenotypic and predicted antimicrobial susceptibilities. Complete agreement was observed between species identification, multilocus sequence typing, and phylogenetic relationships for Escherichia coli and Enterococcus faecalis isolates when the results of WGS of cultured isolates and urine samples were directly compared. Sequencing directly from the urine enabled bacterial identification in polymicrobial samples. Additional putative pathogenic strains were observed in some culture-negative samples. WGS directly on clinical samples can provide clinically relevant information and drastically reduce diagnostic times. This may prove very useful, but the need for data analysis is still a hurdle to clinical implementation. To overcome this problem, a publicly available bioinformatic tool was developed in this study.     

Evaluation of Five User-Friendly Whole Genome Sequencing Software for Mycobacterium tuberculosis in Clinical Application

BackgroundWhole genome sequencing (WGS) is an increasingly useful tool for tuberculosis (TB) diagnosis and disease management. In this study, we evaluated the utility of user-friendly WGS tools in reporting resistance profiles and identifying lineages of clinical TB isolates from South Korea.MethodsForty clinical samples from TB patients showing discrepancies between their rapid molecular and conventional drug susceptibility tests were used in this study. Among these clinical isolates, 37 strains were successfully evaluated via WGS software, using the GenTB, TB Profiler, PhyResSE, CASTB, and Mykrobe.ResultsMore accurate and faster susceptibility results could be obtained with isoniazid than with rifampin. Using the phenotypic test as the gold standard, the isoniazid concordance rate between phenotypic drug susceptibility test (DST) and WGS (GenTB: 45.9%, TB profiler: 40.5%, PhyResSE: 40.5%, CASTB: 48.6%, and Mykrobe: 43.2%) was much higher than between phenotypic DST and rapid molecular genotypic DST (18.9%) among the 37 strains. In contrast, the rifampin concordance rate between phenotypic DST and WGS and that between phenotypic DST and rapid molecular genotypic DST was similar (81.1–89.2%). We also found novel mutations associated with INH in katG and ahpC gene region, not covered by the line probe assay. In addition, lineage analysis identified 81.1% of these samples as L2 East Asian lineage strains, and 18.9% as L4 Euro-American lineage strains.ConclusionWGS may play a pivotal role in TB diagnosis and the detection of drug resistance, genetic diversity, and transmission dynamics in the near future because of its accuracy, speed, and extensibility.     

Efficient Depletion of Host DNA Contamination in Malaria Clinical Sequencing

The cost of whole-genome sequencing (WGS) is decreasing rapidly as next-generation sequencing technology continues to advance, and the prospect of making WGS available for public health applications is becoming a reality. So far, a number of studies have demonstrated the use of WGS as an epidemiological tool for typing and controlling outbreaks of microbial pathogens. Success of these applications is hugely dependent on efficient generation of clean genetic material that is free from host DNA contamination for rapid preparation of sequencing libraries. The presence of large amounts of host DNA severely affects the efficiency of characterizing pathogens using WGS and is therefore a serious impediment to clinical and epidemiological sequencing for health care and public health applications. We have developed a simple enzymatic treatment method that takes advantage of the methylation of human DNA to selectively deplete host contamination from clinical samples prior to sequencing. Using malaria clinical samples with over 80% human host DNA contamination, we show that the enzymatic treatment enriches Plasmodium falciparum DNA up to ∼9-fold and generates high-quality, nonbiased sequence reads covering >98% of 86,158 catalogued typeable single-nucleotide polymorphism loci.