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      MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates

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          Abstract

          Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.

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          The Bioperl toolkit: Perl modules for the life sciences.

          Jason E Stajich, David Block, Kris Boulez … (2002)
          The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.
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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

                Contributors
                Stefan Niemann
                Journal
                Journal ID (nlm-ta): PeerJ
                Journal ID (iso-abbrev): PeerJ
                Journal ID (pmc): PeerJ
                Journal ID (publisher-id): PeerJ
                Title: PeerJ
                Publisher: PeerJ Inc. (San Diego, USA )
                ISSN (Electronic): 2167-8359
                Publication date (Electronic): 13 November 2018
                Publication date Collection: 2018
                Volume: 6
                Electronic Location Identifier: e5895
                Affiliations
                [1 ] Molecular and Experimental Mycobacteriology, Research Center Borstel , Borstel, Germany
                [2 ] Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute , Milan, Italy
                [3 ] German Center for Infection Research (DZIF), partner site Hamburg—Lübeck—Borstel—Riems , Borstel, Germany
                Author information
                http://orcid.org/0000-0002-1126-6803
                Article
                Publisher ID: 5895
                DOI: 10.7717/peerj.5895
                PMC ID: 6238766
                PubMed ID: 30479891
                SO-VID: 02a9fb38-e2c5-4bc6-8c3c-923762bb2577
                Copyright © © 2018 Kohl et al.
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                Date received : 23 April 2018
                Date accepted : 9 October 2018
                Funding
                Funded by: European Community’s Seventh Framework Program
                Award ID: FP7/2007-2013
                Funded by: German Center for Infection Research
                Award ID: DZIF
                Parts of this work were funded by the European Community’s Seventh Framework Program (FP7/2007-2013) under grant agreement 278864 in the framework of the Patho-NGen-Trace project and the German Center for Infection Research (DZIF). The publication of this article was funded by the Open Access Fund of the Leibniz Association. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Molecular Biology
                Subject: Infectious Diseases
                Subject: Public Health
                Subject: Population Biology

                Keywords: next-generation sequencing,mycobacterium tuberculosis complex,phylogeny,whole-genome sequencing,automated analysis pipeline,bacterial genome analysis,bacterial epidemiology,antibiotic resistance profiling
                Data availability:
                Keywords: next-generation sequencing, mycobacterium tuberculosis complex, phylogeny, whole-genome sequencing, automated analysis pipeline, bacterial genome analysis, bacterial epidemiology, antibiotic resistance profiling

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