دورية أكاديمية
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Deconvoluting the diversity of within-host pathogen strains in a multi-locus sequence typing framework.

التفاصيل البيبلوغرافية
العنوان: Deconvoluting the diversity of within-host pathogen strains in a multi-locus sequence typing framework.
المؤلفون: Gan GL; School of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby (BC), V5A 1S6, Canada., Willie E; School of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby (BC), V5A 1S6, Canada., Chauve C; Department of Mathematics, Simon Fraser University, 8888 University Drive, Burnaby (BC), V5A 1S6, Canada.; LaBRI, Université de Bordeaux, 351 Cours de la Libération, Talence, 33405, France., Chindelevitch L; School of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby (BC), V5A 1S6, Canada. leonid@sfu.ca.
المصدر: BMC bioinformatics [BMC Bioinformatics] 2019 Dec 17; Vol. 20 (Suppl 20), pp. 637. Date of Electronic Publication: 2019 Dec 17.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
أسماء مطبوعة: Original Publication: [London] : BioMed Central, 2000-
مواضيع طبية MeSH: Genetic Variation* , Multilocus Sequence Typing*, Host-Pathogen Interactions/*genetics, Alleles ; Borrelia burgdorferi/genetics ; Computer Simulation ; Databases, Genetic ; Genetic Loci ; Models, Biological
مستخلص: Background: Bacterial pathogens exhibit an impressive amount of genomic diversity. This diversity can be informative of evolutionary adaptations, host-pathogen interactions, and disease transmission patterns. However, capturing this diversity directly from biological samples is challenging.
Results: We introduce a framework for understanding the within-host diversity of a pathogen using multi-locus sequence types (MLST) from whole-genome sequencing (WGS) data. Our approach consists of two stages. First we process each sample individually by assigning it, for each locus in the MLST scheme, a set of alleles and a proportion for each allele. Next, we associate to each sample a set of strain types using the alleles and the strain proportions obtained in the first step. We achieve this by using the smallest possible number of previously unobserved strains across all samples, while using those unobserved strains which are as close to the observed ones as possible, at the same time respecting the allele proportions as closely as possible. We solve both problems using mixed integer linear programming (MILP). Our method performs accurately on simulated data and generates results on a real data set of Borrelia burgdorferi genomes suggesting a high level of diversity for this pathogen.
Conclusions: Our approach can apply to any bacterial pathogen with an MLST scheme, even though we developed it with Borrelia burgdorferi, the etiological agent of Lyme disease, in mind. Our work paves the way for robust strain typing in the presence of within-host heterogeneity, overcoming an essential challenge currently not addressed by any existing methodology for pathogen genomics.
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فهرسة مساهمة: Keywords: Bacterial diversity; Integer Linear Programming; Multi-Locus Sequence Typing
تواريخ الأحداث: Date Created: 20191218 Date Completed: 20200218 Latest Revision: 20200218
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC6915855
DOI: 10.1186/s12859-019-3204-8
PMID: 31842753
قاعدة البيانات: MEDLINE
الوصف
تدمد:1471-2105
DOI:10.1186/s12859-019-3204-8