Insight into pathogenomics and phylogeography of hypervirulent and highly-lethal <i>Mycobacterium tuberculosis</i> strain cluster

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Abstract

Background

. The Mycobacterium tuberculosis Beijing genotype is globally spread lineage with important medical properties that however vary among its subtypes. M. tuberculosis Beijing 14717-15-cluster was recently discovered as both multidrug-resistant, hypervirulent, and highly-lethal strain circulating in the Far Eastern region of Russia. Here, we aimed to analyze its pathogenomic features and phylogeographic pattern.

Results

. The study collection included M. tuberculosis DNA collected between 1996 and 2020 in different world regions. The bacterial DNA was subjected to genotyping and whole genome sequencing followed by bioinformatics and phylogenetic analysis. The PCR-based assay to detect specific SNPs of the Beijing 14717-15-cluster was developed and used for its screening in the global collections. Phylogenomic and phylogeographic analysis confirmed endemic prevalence of the Beijing 14717-15-cluster in the Asian part of Russia, and distant common ancestor with isolates from Korea (> 115 SNPs). The Beijing 14717-15-cluster isolates had two common resistance mutations RpsL Lys88Arg and KatG Ser315Thr and belonged to spoligotype SIT269. The Russian isolates of this cluster were from the Asian Russia while 4 isolates were from the Netherlands and Spain. The cluster-specific SNPs that significantly affect the protein function were identified in silico in genes within different categories (lipid metabolism, regulatory proteins, intermediary metabolism and respiration, PE/PPE, cell wall and cell processes).

Conclusions

. We developed a simple method based on real-time PCR to detect clinically significant MDR and hypervirulent Beijing 14717-15-cluster. Most of the identified cluster-specific mutations were previously unreported and could potentially be associated with increased pathogenic properties of this hypervirulent M. tuberculosis strain. Further experimental study to assess the pathobiological role of these mutations is warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-023-08413-7.

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Most cited references 64

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

Subha Kalyaanamoorthy, Bui Minh, Thomas Wong … (2017)

Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.

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IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

Bui Minh, Heiko Schmidt, Olga Chernomor … (2020)

Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

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Author and article information

Contributors

Igor Mokrousov: igormokrousov@yahoo.com

Journal

Journal ID (nlm-ta): BMC Infect Dis

Journal ID (iso-abbrev): BMC Infect Dis

Title: BMC Infectious Diseases

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2334

Publication date (Electronic): 23 June 2023

Publication date PMC-release: 23 June 2023

Publication date Collection: 2023

Volume: 23

Electronic Location Identifier: 426

Affiliations

[1 ]GRID grid.419591.1, Laboratory of Molecular Epidemiology and Evolutionary Genetics, , St. Petersburg Pasteur Institute, ; St. Petersburg, Russia

[2 ]GRID grid.207374.5, ISNI 0000 0001 2189 3846, Henan International Joint Laboratory of Children’s Infectious Diseases, Henan Children’s Hospital, , Children’s Hospital, Zhengzhou University, Zhengzhou Children’s Hospital, ; Zhengzhou, China

[3 ]GRID grid.419144.d, ISNI 0000 0004 0637 9904, Department of Biomedicine and Genomics, , Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, ; Moscow, 119435 Russia

[4 ]GRID grid.446252.3, ISNI 0000 0000 9223 9449, Department of Infectious Diseases, , Dorji Banzarov Buryat State University, ; Ulan-Ude, Buryatia, Russia

[5 ]GRID grid.15447.33, ISNI 0000 0001 2289 6897, Resource Center Bio-bank Center, , Research Park of St. Petersburg State University, ; St. Petersburg, Russia

[6 ]GRID grid.433823.d, ISNI 0000 0004 0404 8765, Laboratory of Genogeography, , Vavilov Institute of General Genetics Russian Academy of Sciences Moscow, ; Moscow, Russia

[7 ]GRID grid.416145.3, ISNI 0000 0004 0489 8727, National Reference Laboratory for Mycobacteria, , Sotiria Chest Diseases Hospital, ; Athens, Greece

[8 ]GRID grid.411609.b, ISNI 0000 0004 1758 4735, National Clinical Research Center for Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Disease, Beijing Children’s Hospital, , Beijing Pediatric Research Institute, Capital Medical University, National Center for Children’s Health, ; Beijing, China

[9 ]GRID grid.467106.2, Department of Epidemiology and Microbiology, Scientific Centre of the Family Health and Human Reproduction Problems, ; Irkutsk, Russia

[10 ]Laboratory of Molecular Biology, Almaty Branch of National Center for Biotechnology in Central Reference Laboratory, Almaty, Kazakhstan

[11 ]GRID grid.77184.3d, ISNI 0000 0000 8887 5266, Department of Biotechnology, , Al-Farabi Kazakh National University, ; Almaty, Kazakhstan

[12 ]GRID grid.445426.5, ISNI 0000 0000 8650 7347, Department of Public Health, , Omsk State Medical University, ; Omsk, Russia

[13 ]GRID grid.9983.b, ISNI 0000 0001 2181 4263, iMed.ULisboa – Instituto de Investigação do Medicamento, Faculdade de Farmácia, , Universidade de Lisboa, ; Lisbon, Portugal

[14 ]GRID grid.428999.7, ISNI 0000 0001 2353 6535, WHO Supranational TB Reference Laboratory, Unité de la Tuberculose et des Mycobactéries, , Institut Pasteur de la Guadeloupe, ; Abymes, Guadeloupe, France

[15 ]GRID grid.490612.8, Henan Children’s Hospital, , Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou Children’s Hospital, ; Zhengzhou, China

[16 ]GRID grid.494800.1, St. Petersburg Research Institute of Phthisiopulmonology, ; St. Petersburg, Russia

[17 ]National Mycobacteria Reference Laboratory, University Hospital Shefqet Ndroqi, Tirana, Albania

[18 ]GRID grid.410344.6, ISNI 0000 0001 2097 3094, Laboratory of Molecular Genetics of Mycobacteria, The Stephan Angeloff Institute of Microbiology, , Bulgarian Academy of Sciences, ; Sofia, Bulgaria

[19 ]Bacteriology laboratory, Clinical Tuberculosis Dispensary, Omsk, Russia

Article

Publisher ID: 8413

DOI: 10.1186/s12879-023-08413-7

PMC ID: 10288800

SO-VID: ebedc061-f715-455d-9db3-3f2c801f76ea

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 11 March 2023

Date accepted : 21 June 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;

Award ID: 19-14-00013

Custom metadata

ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: mycobacterium tuberculosis,whole genome sequencing,virulence,drug resistance,beijing genotype

Data availability:

ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: mycobacterium tuberculosis, whole genome sequencing, virulence, drug resistance, beijing genotype

Insight into pathogenomics and phylogeography of hypervirulent and highly-lethal Mycobacterium tuberculosis strain cluster

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Abstract

Background

Results

Conclusions

Supplementary Information

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European Journal of Microbiology and Immunology

Most cited references 64

Fast and accurate short read alignment with Burrows–Wheeler transform

ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

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