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      Asymptomatic infections with highly polymorphic Chlamydia suis are ubiquitous in pigs

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          Abstract

          Background

          Chlamydia suis is an important, globally distributed, highly prevalent and diverse obligate intracellular pathogen infecting pigs. To investigate the prevalence and genetic diversity of C. suis in China, 2,137 nasal, conjunctival, and rectal swabs as well as whole blood and lung samples of pigs were collected in 19 regions from ten provinces of China in this study.

          Results

          We report an overall positivity of 62.4% (1,334/2,137) of C. suis following screening by Chlamydia spp. 23S rRNA-based FRET-PCR and high-resolution melting curve analysis and confirmatory sequencing. For C. suis-positive samples, 33.3 % of whole blood and 62.5% of rectal swabs were found to be positive for the C. suis tetR(C) gene, while 13.3% of whole blood and 87.0% of rectal swabs were positive for the C. suis tet(C) gene. Phylogenetic comparison of partial C. suis ompA gene sequences revealed significant genetic diversity in the C. suis strains. This genetic diversity was confirmed by C. suis-specific multilocus sequence typing (MLST), which identified 26 novel sequence types among 27 examined strains. Tanglegrams based on MLST and ompA sequences provided evidence of C. suis recombination amongst the strains analyzed.

          Conclusions

          Genetically highly diverse C. suis strains are exceedingly prevalent in pigs. As it stands, the potential pathogenic effect of C. suis on pig health and production of C. suis remains unclear and will be the subject of further investigations. Further study is also required to address the transmission of C. suis between pigs and the risk of 'spill-over' and 'spill-back' of infections to wild animals and humans.

          Electronic supplementary material

          The online version of this article (10.1186/s12917-017-1295-x) contains supplementary material, which is available to authorized users.

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          Most cited references47

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          MRBAYES: Bayesian inference of phylogenetic trees.

          J P Huelsenbeck, F Ronquist (2001)
          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
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            Multilocus sequence typing of bacteria.

            Martin Maiden (2006)
            Multilocus sequence typing (MLST) was proposed in 1998 as a portable, universal, and definitive method for characterizing bacteria, using the human pathogen Neisseria meningitidis as an example. In addition to providing a standardized approach to data collection, by examining the nucleotide sequences of multiple loci encoding housekeeping genes, or fragments of them, MLST data are made freely available over the Internet to ensure that a uniform nomenclature is readily available to all those interested in categorizing bacteria. At the time of writing, over thirty MLST schemes have been published and made available on the Internet, mostly for pathogenic bacteria, although there are schemes for pathogenic fungi and some nonpathogenic bacteria. MLST data have been employed in epidemiological investigations of various scales and in studies of the population biology, pathogenicity, and evolution of bacteria. The increasing speed and reduced cost of nucleotide sequence determination, together with improved web-based databases and analysis tools, present the prospect of increasingly wide application of MLST.
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              Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach

              Alexandre Francisco, Miguel Bugalho, Mario Ramirez … (2009)
              Background Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier: the sequence type (ST). The relatedness between two strains can then be inferred by the differences between allelic profiles. For a more comprehensive analysis of the possible patterns of evolutionary descent, a set of rules were proposed and implemented in the eBURST algorithm. These rules allow the division of a data set into several clusters of related strains, dubbed clonal complexes, by implementing a simple model of clonal expansion and diversification. Within each clonal complex, the rules identify which links between STs correspond to the most probable pattern of descent. However, the eBURST algorithm is not globally optimized, which can result in links, within the clonal complexes, that violate the rules proposed. Results Here, we present a globally optimized implementation of the eBURST algorithm – goeBURST. The search for a global optimal solution led to the formalization of the problem as a graphic matroid, for which greedy algorithms that provide an optimal solution exist. Several public data sets of MLST data were tested and differences between the two implementations were found and are discussed for five bacterial species: Enterococcus faecium, Streptococcus pneumoniae, Burkholderia pseudomallei, Campylobacter jejuni and Neisseria spp.. A novel feature implemented in goeBURST is the representation of the level of tiebreak rule reached before deciding if a link should be drawn, which can used to visually evaluate the reliability of the represented hypothetical pattern of descent. Conclusion goeBURST is a globally optimized implementation of the eBURST algorithm, that identifies alternative patterns of descent for several bacterial species. Furthermore, the algorithm can be applied to any multilocus typing data based on the number of differences between numeric profiles. A software implementation is available at .
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                Author and article information

                Contributors
                Min Li: limin6707@163.com
                Martina Jelocnik: Martina.Jelocnik@research.usc.edu.au
                Feng Yang: 674360059@qq.com
                Jianseng Gong: jjsensen@163.com
                Bernhard Kaltenboeck: kaltebe@auburn.edu
                Adam Polkinghorne: apolking@usc.edu.au
                Zhixin Feng: fzxjaas@163.com
                Yvonne Pannekoek: y.pannekoek@amc.uva.nl
                Nicole Borel: n.borel@access.uzh.ch
                Chunlian Song: 466569879@qq.com
                Ping Jiang: jiangp@njau.edu.cn
                Jing Li: lijing900401@163.com
                Jilei Zhang: zhangjilei0103@163.com
                Yaoyao Wang: 495930788@163.com
                Jiawei Wang: 912911025@qq.com
                Xin Zhou: zhouxin99@vip.126.com
                Chengming Wang:
                ORCID: http://orcid.org/0000-0001-7874-8340
                wangche@auburn.edu
                Journal
                Journal ID (nlm-ta): BMC Vet Res
                Journal ID (iso-abbrev): BMC Vet. Res
                Title: BMC Veterinary Research
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1746-6148
                Publication date (Electronic): 1 December 2017
                Publication date PMC-release: 1 December 2017
                Publication date Collection: 2017
                Volume: 13
                Electronic Location Identifier: 370
                Affiliations
                [1 ]GRID grid.268415.c, Yangzhou University College of Veterinary Medicine, ; Yangzhou, Jiangsu People’s Republic of China
                [2 ]ISNI 0000 0001 1555 3415, GRID grid.1034.6, Centre for Animal Health Innovation, Faculty of Science, Health, Education & Engineering, , University of the Sunshine Coast, ; QLD, Maroochydore, Australia
                [3 ]ISNI 0000 0001 0526 1937, GRID grid.410727.7, Poultry Institute, , Chinese Academy of Agricultural Sciences, ; Yangzhou, Jiangsu China
                [4 ]ISNI 0000 0001 2297 8753, GRID grid.252546.2, College of Veterinary Medicine, , Auburn University, ; Auburn, Alabama USA
                [5 ]Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences; Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, National Center for Engineering Research of Veterinary Bio-Products, Nanjing, China
                [6 ]ISNI 0000000084992262, GRID grid.7177.6, Academic Medical Center, , University of Amsterdam, ; Amsterdam, The Netherlands
                [7 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Institute for Veterinary Pathology, Vetsuisse Faculty, , University of Zurich, ; Zurich, Switzerland
                [8 ]GRID grid.410696.c, Yunnan Agricultural University College of Animal Science & Technology, ; Kunming, Yunnan China
                [9 ]ISNI 0000 0000 9750 7019, GRID grid.27871.3b, Key Laboratory of Animal Diseases Diagnostic and Immunology, Ministry of Agriculture, College of Veterinary Medicine, , Nanjing Agricultural University, ; Nanjing, China
                Author information
                http://orcid.org/0000-0001-7874-8340
                Article
                Publisher ID: 1295
                DOI: 10.1186/s12917-017-1295-x
                PMC ID: 5710075
                PubMed ID: 29191191
                SO-VID: f5de7bc6-c278-4fdb-a3b5-0d6d2d0de888
                Copyright © © The Author(s). 2017
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                Date received : 3 July 2017
                Date accepted : 22 November 2017
                Funding
                Funded by: National Key R & D Program of China
                Award ID: 2016YFD0500804
                Award Recipient :
                Categories
                Subject: Research Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2017

                ScienceOpen disciplines: Veterinary medicine
                Keywords: chlamydia suis,pig,fret-pcr,ompa,mlst,tanglegram
                Data availability:
                ScienceOpen disciplines: Veterinary medicine
                Keywords: chlamydia suis, pig, fret-pcr, ompa, mlst, tanglegram

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