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      Intra-continental spread of human invasive Salmonella Typhimurium pathovariants in sub-Saharan Africa

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          Abstract

          A highly invasive form of non-typhoidal Salmonella (iNTS) disease has been recently documented in many countries in sub-Saharan Africa. The most common Salmonella enterica serovar causing this disease is Typhimurium. We applied whole-genome sequence-based phylogenetic methods to define the population structure of sub-Saharan African invasive Salmonella Typhimurium and compared these to global Salmonella Typhimurium isolates. Notably, the vast majority of sub-Saharan invasive Salmonella Typhimurium fell within two closely-related, highly-clustered phylogenetic lineages that we estimate emerged independently ~52 and ~35 years ago, in close temporal association with the current HIV pandemic. Clonal replacement of isolates of lineage I by lineage II was potentially influenced by the use of chloramphenicol for the treatment of iNTS disease. Our analysis suggests that iNTS disease is in part an epidemic in sub-Saharan Africa caused by highly related Salmonella Typhimurium lineages that may have occupied new niches associated with a compromised human population and antibiotic treatment.

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          Most cited references43

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          A Flexible Growth Function for Empirical Use

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            Aromatic-dependent Salmonella typhimurium are non-virulent and effective as live vaccines.

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              SSAHA: a fast search method for large DNA databases.

              We describe an algorithm, SSAHA (Sequence Search and Alignment by Hashing Algorithm), for performing fast searches on databases containing multiple gigabases of DNA. Sequences in the database are preprocessed by breaking them into consecutive k-tuples of k contiguous bases and then using a hash table to store the position of each occurrence of each k-tuple. Searching for a query sequence in the database is done by obtaining from the hash table the "hits" for each k-tuple in the query sequence and then performing a sort on the results. We discuss the effect of the tuple length k on the search speed, memory usage, and sensitivity of the algorithm and present the results of computational experiments which show that SSAHA can be three to four orders of magnitude faster than BLAST or FASTA, while requiring less memory than suffix tree methods. The SSAHA algorithm is used for high-throughput single nucleotide polymorphism (SNP) detection and very large scale sequence assembly. Also, it provides Web-based sequence search facilities for Ensembl projects.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                24 September 2012
                30 September 2012
                November 2012
                01 May 2013
                : 44
                : 11
                : 1215-1221
                Affiliations
                [1 ]Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton Cambridge, UK. CB10 1SA
                [2 ]Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
                [3 ]Department of Clinical Infection, Microbiology and Immunology, Institute for Infection and Global Health, University of Liverpool, Liverpool, UK
                [4 ]Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
                [5 ]Malawi-Liverpool-Wellcome Trust Clinical Research Program, University of Malawi College of Medicine, Blantyre, Malawi
                [6 ]Department of Microbiology, College of Medicine, University of Malawi, Blantyre, Malawi
                [7 ]Department of Gastroenterology, Institute of Translational Medicine, Liverpool University, Liverpool, UK. L69 3GE
                [8 ]Health Protection Agency, Laboratory for Gastrointestinal Infections, Centre for Infections, London, United Kingdom
                [9 ]Norwich Medical School, University of East Anglia, Norwich, United Kingdom
                [10 ]Cellular and Molecular Medicine, School of Medical Sciences, University of Bristol, Bristol, United Kingdom
                [11 ]Division of Paediatric Infectious Diseases, Department of Paediatrics and Human Development, Michigan State University, East Lansing, MI 48824, USA
                [12 ]National Hospital Abuja, Plot 132 Central District (Phase II), Garki Abuja, Nigeria
                [13 ]Barcelona Centre for International Health Research (CRESIB, Hospital Clínic-Universitat de Barcelona), Barcelona, Spain
                [14 ]Centro de Investigação em Saúde de Manhiça (CISM), Manhiça, Mozambique
                [15 ]Instituto Nacional de Saúde, Ministerio de Saúde, Maputo, Mozambique
                [16 ]Novartis Vaccines Institute for Global Health S.r.l. (NVGH), Via Fiorentina 1, 53100 Siena, Italy
                [17 ]MRC Centre for Immune Regulation, School of Immunity and Infection, College of Medicine and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
                [18 ]Center for Vaccine Development, University of Maryland, Baltimore, HSFI 480, 685 West Baltimore St., Baltimore, MD 21201, USA
                [19 ]Department of Medicine, University of Maryland, Baltimore, HSFI 480, 685 West Baltimore St., Baltimore, MD 21201, USA
                Author notes
                [20]

                These authors contributed equally to this work

                [§ ]Corresponding author
                Article
                EMS49913
                10.1038/ng.2423
                3491877
                23023330
                928e10b8-3e76-4a75-8276-cf11114ab078

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                History
                Funding
                Funded by: Wellcome Trust :
                Award ID: 098051 || WT
                Categories
                Article

                Genetics
                Genetics

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