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      Frequent transmission of the Mycobacterium tuberculosis Beijing lineage and positive selection for EsxW Beijing variant in Vietnam

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          Abstract

          To examine transmission dynamics of Mtb isolated from TB patients in Ho Chi Minh City, Vietnam we sequenced whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data reveal an underlying burden of disease caused by endemic Mtb Lineage 1 associated with activation of long-term latent infection, and a three-fold higher burden associated with more recently introduced Beijing lineage and Lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than endemic Lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify a mutation in the ESX-5 type VII secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.

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          DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach

          Douglas Pires, David B. Ascher, Tom Blundell (2014)
          Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.
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            Evolutionary history and global spread of the Mycobacterium tuberculosis Beijing lineage.

            Matthias Merker, Camille Blin, Stefano Mona … (2015)
            Mycobacterium tuberculosis strains of the Beijing lineage are globally distributed and are associated with the massive spread of multidrug-resistant (MDR) tuberculosis in Eurasia. Here we reconstructed the biogeographical structure and evolutionary history of this lineage by genetic analysis of 4,987 isolates from 99 countries and whole-genome sequencing of 110 representative isolates. We show that this lineage initially originated in the Far East, from where it radiated worldwide in several waves. We detected successive increases in population size for this pathogen over the last 200 years, practically coinciding with the Industrial Revolution, the First World War and HIV epidemics. Two MDR clones of this lineage started to spread throughout central Asia and Russia concomitantly with the collapse of the public health system in the former Soviet Union. Mutations identified in genes putatively under positive selection and associated with virulence might have favored the expansion of the most successful branches of the lineage.
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              Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

              Phelim Bradley, N. Claire Gordon, Timothy Walker … (2015)
              The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 9216904
                Journal ID (pubmed-jr-id): 2419
                Journal ID (nlm-ta): Nat Genet
                Journal ID (iso-abbrev): Nat. Genet.
                Title: Nature genetics
                ISSN (Print): 1061-4036
                ISSN (Electronic): 1546-1718
                Publication date Nihms-submitted: 4 April 2018
                Publication date (Electronic): 21 May 2018
                Publication date (Print): June 2018
                Publication date PMC-release: 21 November 2018
                Volume: 50
                Issue: 6
                Pages: 849-856
                Affiliations
                [1 ]Department of Biochemistry and Molecular Biology, Bio 21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia
                [2 ]Pham Ngoc Thach Hospital for Tuberculosis and Lung Disease, Ho Chi Minh City, District 5, Viet Nam
                [3 ]Oxford University Clinical Research Unit, Ho Chi Minh City, District 5, Viet Nam
                [4 ]Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Oxford University, Oxford, UK
                [5 ]Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria 3010, Australia
                [6 ]Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne 3004, Victoria, Australia
                [7 ]Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
                [8 ]Genome Institute of Singapore, Singapore
                [9 ]Singapore Eye Research Institute, Singapore
                [10 ]Department of Statistics and Applied Probability, National University of Singapore, Singapore
                [11 ]Saw Swee Hock School of Public Health, National University of Singapore, Singapore
                [12 ]Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratories, Cambridge CB1 8RN, United Kingdom
                [13 ]Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, United Kingdom
                [14 ]Birat-Nepal Medical Trust, 257 Lazimpat, Kathmandu, Nepal
                [15 ]Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria 3010, Australia
                Author notes
                [* ] Corresponding authors: Correspondence should be addressed to KEH ( kholt@ 123456unimelb.edu.au ) and SJD ( sarah.dunstan@ 123456unimelb.edu.au )
                Article
                Manuscript ID: EMS76841
                DOI: 10.1038/s41588-018-0117-9
                PMC ID: 6143168
                PubMed ID: 29785015
                SO-VID: 9c068606-ab4b-4276-bf9f-a2e400398fd0
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                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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