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      Whole-genome and targeted sequencing of drug-resistant Mycobacterium tuberculosis on the iSeq100 and MiSeq: A performance, ease-of-use, and cost evaluation

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          Abstract

          Background

          Accurate, comprehensive, and timely detection of drug-resistant tuberculosis (TB) is essential to inform patient treatment and enable public health surveillance. This is crucial for effective control of TB globally. Whole-genome sequencing (WGS) and targeted next-generation sequencing (NGS) approaches have potential as rapid in vitro diagnostics (IVDs), but the complexity of workflows, interpretation of results, high costs, and vulnerability of instrumentation have been barriers to broad uptake outside of reference laboratories, especially in low- and middle-income countries. A new, solid-state, tabletop sequencing instrument, Illumina iSeq100, has the potential to decentralize NGS for individual patient care.

          Methods and findings

          In this study, we evaluated WGS and targeted NGS for TB on both the new iSeq100 and the widely used MiSeq (both manufactured by Illumina) and compared sequencing performance, costs, and usability. We utilized DNA libraries produced from Mycobacterium tuberculosis clinical isolates for the evaluation. We conducted WGS on three strains and observed equivalent uniform genome coverage with both platforms and found the depth of coverage obtained was consistent with the expected data output. Utilizing the standardized, cloud-based ReSeqTB bioinformatics pipeline for variant analysis, we found the two platforms to have 94.0% (CI 93.1%–94.8%) agreement, in comparison to 97.6% (CI 97%–98.1%) agreement for the same libraries on two MiSeq instruments. For the targeted NGS approach, 46 M. tuberculosis–specific amplicon libraries had 99.6% (CI 98.0%–99.9%) agreement between the iSeq100 and MiSeq data sets in drug resistance–associated SNPs. The upfront capital costs are almost 5-fold lower for the iSeq100 ($19,900 USD) platform in comparison to the MiSeq ($99,000 USD); however, because of difference in the batching capabilities, the price per sample for WGS was higher on the iSeq100. For WGS of M. tuberculosis at the minimum depth of coverage of 30x, the cost per sample on the iSeq100 was $69.44 USD versus $28.21 USD on the MiSeq, assuming a 2 × 150 bp run on a v3 kit. In terms of ease of use, the sequencing workflow of iSeq100 has been optimized to only require 27 minutes total of hands-on time pre- and post-run, and the maintenance is simplified by a single-use cartridge–based fluidic system. As these are the first sequencing attempts on the iSeq100 for M. tuberculosis, the sequencing pool loading concentration still needs optimization, which will affect sequencing error and depth of coverage. Additionally, the costs are based on current equipment and reagent costs, which are subject to change.

          Conclusions

          The iSeq100 instrument is capable of running existing TB WGS and targeted NGS library preparations with comparable accuracy to the MiSeq. The iSeq100 has reduced sequencing workflow hands-on time and is able to deliver sequencing results in <24 hours. Reduced capital and maintenance costs and lower-throughput capabilities also give the iSeq100 an advantage over MiSeq in settings of individualized care but not in high-throughput settings such as reference laboratories, where sample batching can be optimized to minimize cost at the expense of workflow complexity and time.

          Abstract

          Rebecca E. Colman and colleagues assess performance, cost, and throughput of a new sequencer designed for detecting drug-resistant tuberculosis strains.

          Author summary

          Why was this study done?
          • M. tuberculosis is the leading cause of death from a single infectious agent.

          • Diagnosis of drug-resistant M. tuberculosis is imperative for reducing tuberculosis (TB) mortality.

          • Next-generation sequencing (NGS) can provide comprehensive genetic information on drug resistance for supporting rapid clinical decision-making but currently can only be performed at the reference-laboratory level.

          • Illumina’s solid-state benchtop sequencer iSeq100 adds diversity to the intended use settings in which NGS can be practically utilized for drug-resistant TB detection, but it has not yet been demonstrated that existing TB NGS workflows will perform on the new instrument.

          What did the researchers do and find?
          • The study was focused on the performance of existing TB whole-genome sequencing (WGS) and targeted NGS approaches that work on the Illumina MiSeq to determine if they could be also utilized on the iSeq100 platforms.

          • WGS library preparations were performed on three strains, and the same libraries were run on two MiSeq instruments and one early-access iSeq100 instrument. The percentage of genome covered was similar across the instruments and the three isolates, ranging from 99.20% to 99.92% of the genome covered.

          • Targeted NGS preparations were performed on 46 strains and run on two MiSeq instruments and one iSeq100 instrument with 99.6% (CI. 98.0%–99.9%) agreement on drug resistance–associated SNPs between iSeq100 and MiSeq data sets.

          • Because of batching-based pricing constraints for TB sequencing, the sequencing cost per sample is higher on the iSeq100 platform than for the same coverage on the MiSeq when batched optimally. However, the iSeq100 allows for a more open-access workflow due to a lower number of samples being in one sequencing batch. This relationship is the same for WGS and targeted NGS, although the scale is different depending on the sequencing approach chosen.

          What do these findings mean?
          • In settings of individualized TB care, lower throughput will drive a different need for batching, and the iSeq100, with its lower-throughput capabilities, has an advantage over MiSeq. However, in high-throughput settings such as reference laboratories, where sample batching can be optimized to minimize cost at the expense of workflow complexity and time, the MiSeq will make the most sense.

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          Most cited references9

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          DNA Sequencing Predicts 1st-Line Tuberculosis Drug Susceptibility Profiles

          Background The World Health Organization recommends universal drug susceptibility testing for Mycobacterium tuberculosis complex to guide treatment decisions and improve outcomes. We assessed whether DNA sequencing can accurately predict antibiotic susceptibility profiles for first-line anti-tuberculosis drugs. Methods Whole-genome sequences and associated phenotypes to isoniazid, rifampicin, ethambutol and pyrazinamide were obtained for isolates from 16 countries across six continents. For each isolate, mutations associated with drug-resistance and drug-susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These were predicted to be pan-susceptible if predicted susceptible to isoniazid and to other drugs, or contained mutations of unknown association in genes affecting these other drugs. We simulated how negative predictive value changed with drug-resistance prevalence. Results 10,209 isolates were analysed. The greatest proportion of phenotypes were predicted for rifampicin (9,660/10,130; (95.4%)) and the lowest for ethambutol (8,794/9,794; (89.8%)). Isoniazid, rifampicin, ethambutol and pyrazinamide resistance was correctly predicted with 97.1%, 97.5% 94.6% and 91.3% sensitivity, and susceptibility with 99.0%, 98.8%, 93.6% and 96.8% specificity, respectively. 5,250 (89.5%) drug profiles were correctly predicted for 5,865/7,516 (78.0%) isolates with complete phenotypic profiles. Among these, 3,952/4,037 (97.9%) predictions of pan-susceptibility were correct. The negative predictive value for 97.5% of simulated drug profiles exceeded 95% where the prevalence of drug-resistance was below 47.0%. Conclusions Phenotypic testing for first-line drugs can be phased down in favour of DNA sequencing to guide anti- tuberculosis drug therapy.
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            Rapid Drug Susceptibility Testing of Drug-Resistant Mycobacterium tuberculosis Isolates Directly from Clinical Samples by Use of Amplicon Sequencing: a Proof-of-Concept Study

            Increasingly complex drug-resistant tuberculosis (DR-TB) is a major global health concern and one of the primary reasons why TB is now the leading infectious cause of death worldwide. Rapid characterization of a DR-TB patient's complete drug resistance profile would facilitate individualized treatment in place of empirical treatment, improve treatment outcomes, prevent amplification of resistance, and reduce the transmission of DR-TB. The use of targeted next-generation sequencing (NGS) to obtain drug resistance profiles directly from patient sputum samples has the potential to enable comprehensive evidence-based treatment plans to be implemented quickly, rather than in weeks to months, which is currently needed for phenotypic drug susceptibility testing (DST) results. In this pilot study, we evaluated the performance of amplicon sequencing of Mycobacterium tuberculosis DNA from patient sputum samples using a tabletop NGS technology and automated data analysis to provide a rapid DST solution (the Next Gen-RDST assay). One hundred sixty-six out of 176 (94.3%) sputum samples from the Republic of Moldova yielded complete Next Gen-RDST assay profiles for 7 drugs of interest. We found a high level of concordance of our Next Gen-RDST assay results with phenotypic DST (97.0%) and pyrosequencing (97.8%) results from the same clinical samples. Our Next Gen-RDST assay was also able to estimate the proportion of resistant-to-wild-type alleles down to mixtures of ≤1%, which demonstrates the ability to detect very low levels of resistant variants not detected by pyrosequencing and possibly below the threshold for phenotypic growth methods. The assay as described here could be used as a clinical or surveillance tool.
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              Predicting extensively drug-resistant Mycobacterium tuberculosis phenotypes with genetic mutations.

              Molecular diagnostic methods based on the detection of mutations conferring drug resistance are promising technologies for rapidly detecting multidrug-/extensively drug-resistant tuberculosis (M/XDR TB), but large studies of mutations as markers of resistance are rare. The Global Consortium for Drug-Resistant TB Diagnostics analyzed 417 Mycobacterium tuberculosis isolates from multinational sites with a high prevalence of drug resistance to determine the sensitivities and specificities of mutations associated with M/XDR TB to inform the development of rapid diagnostic methods. We collected M/XDR TB isolates from regions of high TB burden in India, Moldova, the Philippines, and South Africa. The isolates underwent standardized phenotypic drug susceptibility testing (DST) to isoniazid (INH), rifampin (RIF), moxifloxacin (MOX), ofloxacin (OFX), amikacin (AMK), kanamycin (KAN), and capreomycin (CAP) using MGIT 960 and WHO-recommended critical concentrations. Eight genes (katG, inhA, rpoB, gyrA, gyrB, rrs, eis, and tlyA) were sequenced using Sanger sequencing. Three hundred seventy isolates were INHr, 356 were RIFr, 292 were MOXr/OFXr, 230 were AMKr, 219 were CAPr, and 286 were KANr. Four single nucleotide polymorphisms (SNPs) in katG/inhA had a combined sensitivity of 96% and specificities of 97 to 100% for the detection of INHr. Eleven SNPs in rpoB had a combined sensitivity of 98% for RIFr. Eight SNPs in gyrA codons 88 to 94 had sensitivities of 90% for MOXr/OFXr. The rrs 1401/1484 SNPs had 89 to 90% sensitivity for detecting AMKr/CAPr but 71% sensitivity for KANr. Adding eis promoter SNPs increased the sensitivity to 93% for detecting AMKr and to 91% for detecting KANr. Approximately 30 SNPs in six genes predicted clinically relevant XDR-TB phenotypes with 90 to 98% sensitivity and almost 100% specificity.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: SoftwareRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                30 April 2019
                April 2019
                : 16
                : 4
                : e1002794
                Affiliations
                [1 ] Foundation for Innovative New Diagnostics, Campus Biotech, Geneva, Switzerland
                [2 ] Department of Medicine, University of California, San Diego, San Diego, California, United States of America
                [3 ] Illumina Inc., San Diego, California, United States of America
                [4 ] Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
                [5 ] Department of Biological Sciences, University of Arkansas, Fayetteville, Arkansas, United States of America
                John Hopkins University, UNITED STATES
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: DL and DME work for the nonprofit Translational Genomics Research Institute (TGen), which holds the patent on the Next Gen RDST assay that was employed in this study. As of this submission, TGen has not licensed the assay to any commercial party. JH is currently a paid employee of Illumina, where he works as a scientist. AGY is currently an employee of Illumina and a shareholder. CMD served as a Guest Editor on PLOS Medicine’s Special Issue on Tuberculosis.

                Author information
                http://orcid.org/0000-0002-6854-2100
                http://orcid.org/0000-0002-3282-1650
                http://orcid.org/0000-0002-7554-6396
                http://orcid.org/0000-0003-2785-6928
                http://orcid.org/0000-0001-5945-059X
                http://orcid.org/0000-0003-1760-0574
                http://orcid.org/0000-0002-7216-7067
                http://orcid.org/0000-0003-2779-3197
                Article
                PMEDICINE-D-18-04020
                10.1371/journal.pmed.1002794
                6490892
                31039166
                d6771a3c-0ad9-490c-a0e9-bd26be419549
                © 2019 Colman et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 November 2018
                : 28 March 2019
                Page count
                Figures: 3, Tables: 3, Pages: 13
                Funding
                Funded by: Department for International Development (GB)
                Award ID: 204074-101
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000996, Department of Foreign Affairs and Trade, Australian Government;
                Award ID: 70957
                Award Recipient :
                Funded by: National Hearth Lung and Blood Institute at the National Institutes of Health
                Award ID: T32HL134632
                Award Recipient :
                Funded by: National institute of Allergy and Infecitous Diseases
                Award ID: R21AI135756
                Award Recipient :
                REC, CMD, TCR, and AM had funding from the Department for International Development from the United Kingdom award (204074-101) and Department of Foreign Affairs and Trade Australian Government award (70957). TCR had funding from National Institute of Allergy and Infectious Diseases (grant number: R21AI135756). MS was supported from the National Heart, Lung, and Blood Institute at the National Institutes of Health (grant number: T32HL134632). Illumina supplied early-access iSeq100 sequencing reagents. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All sequencing read files were deposited in the NIH Sequence Read Archive ( http://www.ncbi.nlm.nih.gov/bioproject/505787) under BioProject no. PRJNA505787.

                Medicine
                Medicine

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