Multilocus sequence analysis for the taxonomic updating and identification of the genus Proteus and reclassification of Proteus genospecies 5 O'Hara et al. 2000, Proteus cibarius Hyun et al. 2016 as later heterotypic synonyms of Proteus terrae Behrendt et al. 2015.


Journal

BMC microbiology
ISSN: 1471-2180
Titre abrégé: BMC Microbiol
Pays: England
ID NLM: 100966981

Informations de publication

Date de publication:
10 06 2020
Historique:
received: 05 03 2020
accepted: 04 06 2020
entrez: 12 6 2020
pubmed: 12 6 2020
medline: 27 5 2021
Statut: epublish

Résumé

Members of the genus Proteus are mostly opportunistic pathogens that cause a variety of infections in humans. The molecular evolutionary characteristics and genetic relationships among Proteus species have not been elucidated to date. In this study, we developed a multilocus sequence analysis (MLSA) approach based on five housekeeping genes (HKGs) to delineate phylogenetic relationships of species within the genus Proteus. Of all 223 Proteus strains collected in the current study, the phylogenetic tree of five concatenated HKGs (dnaJ, mdh, pyrC, recA and rpoD) divided 223 strains into eleven clusters, which were representative of 11 species of Proteus. Meanwhile, the phylogenetic trees of the five individual HKGs also corresponded to that of the concatenated tree, except for recA, which clustered four strains at an independent cluster. The evaluation of inter- and intraspecies distances of HKG concatenation indicated that all interspecies distances were significantly different from intraspecies distances, which revealed that these HKG concatenations can be used as gene markers to distinguish different Proteus species. Further web-based DNA-DNA hybridization estimated by genome of type strains confirmed the validity of the MLSA, and each of eleven clusters was congruent with the most abundant Proteus species. In addition, we used the established MLSA method to identify the randomly collected Proteus and found that P. mirabilis is the most abundant species. However, the second most abundant species is P. terrae but not P. vulgaris. Combined with the genetic, genomic and phenotypic characteristics, these findings indicate that three species, P. terrae, P. cibarius and Proteus genospecies 5, should be regarded as heterotypic synonyms, and the species should be renamed P. terrae, while Proteus genospecies 5 has not been named to date. This study suggested that MLSA is a powerful method for the discrimination and classification of Proteus at the species level. The MLSA scheme provides a rapid and inexpensive means of identifying Proteus strains. The identification of Proteus species determined by the MLSA approach plays an important role in the clinical diagnosis and treatment of Proteus infection.

Sections du résumé

BACKGROUND
Members of the genus Proteus are mostly opportunistic pathogens that cause a variety of infections in humans. The molecular evolutionary characteristics and genetic relationships among Proteus species have not been elucidated to date. In this study, we developed a multilocus sequence analysis (MLSA) approach based on five housekeeping genes (HKGs) to delineate phylogenetic relationships of species within the genus Proteus.
RESULTS
Of all 223 Proteus strains collected in the current study, the phylogenetic tree of five concatenated HKGs (dnaJ, mdh, pyrC, recA and rpoD) divided 223 strains into eleven clusters, which were representative of 11 species of Proteus. Meanwhile, the phylogenetic trees of the five individual HKGs also corresponded to that of the concatenated tree, except for recA, which clustered four strains at an independent cluster. The evaluation of inter- and intraspecies distances of HKG concatenation indicated that all interspecies distances were significantly different from intraspecies distances, which revealed that these HKG concatenations can be used as gene markers to distinguish different Proteus species. Further web-based DNA-DNA hybridization estimated by genome of type strains confirmed the validity of the MLSA, and each of eleven clusters was congruent with the most abundant Proteus species. In addition, we used the established MLSA method to identify the randomly collected Proteus and found that P. mirabilis is the most abundant species. However, the second most abundant species is P. terrae but not P. vulgaris. Combined with the genetic, genomic and phenotypic characteristics, these findings indicate that three species, P. terrae, P. cibarius and Proteus genospecies 5, should be regarded as heterotypic synonyms, and the species should be renamed P. terrae, while Proteus genospecies 5 has not been named to date.
CONCLUSIONS
This study suggested that MLSA is a powerful method for the discrimination and classification of Proteus at the species level. The MLSA scheme provides a rapid and inexpensive means of identifying Proteus strains. The identification of Proteus species determined by the MLSA approach plays an important role in the clinical diagnosis and treatment of Proteus infection.

Identifiants

pubmed: 32522175
doi: 10.1186/s12866-020-01844-1
pii: 10.1186/s12866-020-01844-1
pmc: PMC7288399
doi:

Substances chimiques

Bacterial Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

152

Subventions

Organisme : the National Natural Science Foundation of China
ID : 31570134
Pays : International
Organisme : the National Sci-Tech Key Project from the Ministry of Health, China
ID : 2018ZX10734404, 2018ZX10102001
Pays : International

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Auteurs

Hang Dai (H)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China.
Center for Human Pathogen Collection, Chinese Center for Disease Control and Prevention, Changbai Road 155, Changping, Beijing, 102206, China.

Binghuai Lu (B)

Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, China.

Zhenpeng Li (Z)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China.

Zhenzhou Huang (Z)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China.
Center for Human Pathogen Collection, Chinese Center for Disease Control and Prevention, Changbai Road 155, Changping, Beijing, 102206, China.

Hongyan Cai (H)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China.
Center for Human Pathogen Collection, Chinese Center for Disease Control and Prevention, Changbai Road 155, Changping, Beijing, 102206, China.

Keyi Yu (K)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China.
Center for Human Pathogen Collection, Chinese Center for Disease Control and Prevention, Changbai Road 155, Changping, Beijing, 102206, China.

Duochun Wang (D)

National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), State Key Laboratory of Infectious Disease Prevention and Control, Changbai Road 155, Changping, Beijing, 102206, China. wangduochun@icdc.cn.
Center for Human Pathogen Collection, Chinese Center for Disease Control and Prevention, Changbai Road 155, Changping, Beijing, 102206, China. wangduochun@icdc.cn.

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Classifications MeSH