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Suntsov VV. Host Aspect of Territorial Expansion of the Plague Microbe Yersinia pestis from the Populations of the Tarbagan Marmot (Marmota sibirica). BIOL BULL+ 2021. [DOI: 10.1134/s1062359021080288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Li J, Wang Y, Liu F, Shen X, Wang Y, Fan M, Peng Y, Wang S, Feng Y, Zhang W, Lv Y, Zhang H, Lu X, Zhang E, Wei J, Chen L, Kan B, Zhang Z, Xu J, Wang W, Li W. Genetic source tracking of human plague cases in Inner Mongolia-Beijing, 2019. PLoS Negl Trop Dis 2021; 15:e0009558. [PMID: 34343197 PMCID: PMC8362994 DOI: 10.1371/journal.pntd.0009558] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/13/2021] [Accepted: 06/11/2021] [Indexed: 11/19/2022] Open
Abstract
On 12 November 2019, one couple from the Sonid Left Qi (County) in the Inner Mongolia Autonomous Region was diagnosed with pneumonic plague in Beijing. The wife acquired the infection from her husband. Thereafter, two bubonic plague cases were identified in Inner Mongolia on November 16th and 24th. In this study, genome-wide single nucleotide polymorphism (SNP) analysis was used to identify the phylogenetic relationship of Yersinia pestis strains isolated in Inner Mongolia. Strains isolated from reservoirs in 2018 and 2019 in Inner Mongolia, together with the strain isolated from Patient C, were further clustered into 2.MED3m, and two novel lineages (2.MED3q, 2.MED3r) in the 2.MED3 population. According to the analysis of PCR-based molecular subtyping methods, such as the MLVA 14 scheme and seven SNP allele sequencing, Patients A/B and D were classified as 2.MED3m. In addition, strains from rodents living near the patients' residences were clustered into the same lineage as patients. Such observations indicated that human plague cases originated from local reservoirs. Corresponding phylogenetic analysis also indicated that rodent plague strains in different areas in Inner Mongolia belong to different epizootics rather than being caused by spreading from the same epizootic in Meriones unguiculatus in 2019.
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Affiliation(s)
- Jianyun Li
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Yumeng Wang
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Fang Liu
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Xiaona Shen
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Yiting Wang
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Mengguang Fan
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Yao Peng
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Shuyi Wang
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Yilan Feng
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Wen Zhang
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Yanning Lv
- Beijing Center for Disease Control and Prevention, Beijing, China
| | - Huijuan Zhang
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Xin Lu
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Enmin Zhang
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Jianchun Wei
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Lijuan Chen
- Beijing Center for Disease Control and Prevention, Beijing, China
| | - Biao Kan
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Zhongbing Zhang
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Jianguo Xu
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
| | - Wenrui Wang
- General Center for Disease Control and Prevention of Inner Mongolia Autonomous Region, Huhehot, China
| | - Wei Li
- National Institute for Communicable Disease Control and Prevention (ICDC), China CDC, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Changping, Beijing, China
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Cui Y, Schmid BV, Cao H, Dai X, Du Z, Ryan Easterday W, Fang H, Guo C, Huang S, Liu W, Qi Z, Song Y, Tian H, Wang M, Wu Y, Xu B, Yang C, Yang J, Yang X, Zhang Q, Jakobsen KS, Zhang Y, Stenseth NC, Yang R. Evolutionary selection of biofilm-mediated extended phenotypes in Yersinia pestis in response to a fluctuating environment. Nat Commun 2020; 11:281. [PMID: 31941912 PMCID: PMC6962365 DOI: 10.1038/s41467-019-14099-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Accepted: 12/04/2019] [Indexed: 12/16/2022] Open
Abstract
Yersinia pestis is transmitted from fleas to rodents when the bacterium develops an extensive biofilm in the foregut of a flea, starving it into a feeding frenzy, or, alternatively, during a brief period directly after feeding on a bacteremic host. These two transmission modes are in a trade-off regulated by the amount of biofilm produced by the bacterium. Here by investigating 446 global isolated Y. pestis genomes, including 78 newly sequenced isolates sampled over 40 years from a plague focus in China, we provide evidence for strong selection pressures on the RNA polymerase ω-subunit encoding gene rpoZ. We demonstrate that rpoZ variants have an increased rate of biofilm production in vitro, and that they evolve in the ecosystem during colder and drier periods. Our results support the notion that the bacterium is constantly adapting-through extended phenotype changes in the fleas-in response to climate-driven changes in the niche.
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Affiliation(s)
- Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Boris V Schmid
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, N-0316, Oslo, Norway
| | - Hanli Cao
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, 830002, China
| | - Xiang Dai
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, 830002, China
| | - Zongmin Du
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - W Ryan Easterday
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, N-0316, Oslo, Norway
| | - Haihong Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Chenyi Guo
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Shanqian Huang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Wanbing Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Zhizhen Qi
- Key Laboratory for Plague Prevention and Control of Qinghai Province, Qinghai Institute for Endemic Diseases Prevention and Control, Xining, 811602, China
| | - Yajun Song
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Min Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yarong Wu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Bing Xu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Chao Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Jing Yang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Xianwei Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Qingwen Zhang
- Key Laboratory for Plague Prevention and Control of Qinghai Province, Qinghai Institute for Endemic Diseases Prevention and Control, Xining, 811602, China
| | - Kjetill S Jakobsen
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, N-0316, Oslo, Norway.
| | - Yujiang Zhang
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, 830002, China.
| | - Nils Chr Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, N-0316, Oslo, Norway. .,Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China.
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Natural Mega-Focus of Yersinia pestis Main Subspecies, Antique Biovar, Phylogenetic Line 4.ANT in Gorny Altai. PROBLEMS OF PARTICULARLY DANGEROUS INFECTIONS 2018. [DOI: 10.21055/0370-1069-2018-2-49-56] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Objective of this study was to investigate the areal of Yersinia pestis strains of antique biovar, main subspecies, phylogenetic line 4.ANT, as well as to establish the borders and spatial structure of mega-focus in the territory of Gorny Altai. Materials and methods. Complex comprehensive analysis of the properties in Yersinia pestis strains of the main subspecies, circulating in Gorny Altai has been conducted. 33 out of them, isolated predominantly in 2012–2017 have been sequenced. Whole genome SNP analysis and search of marker SNPs was performed using Wombac 2.0 software package. Tree diagram was built applying Maximum Likelihood algorithm, using PhyML 3.1 software on the basis of HKY85 model. Results and conclusions. Based on the results of whole genome SNPs analysis of 33 endemic strains and creation of the tree diagram of Y. pestis strains, the presence of natural mega-focus of Y. pestis belonging to the main subspecies, antique biovar, phylogenetic line 4.ANT has been substantiated. Epizootic manifestations on multiple local areas, characterized by persistent autonomous nature of plague manifestations, are registered on an annual basis. Within the boundaries of the areal of Yersinia pestis main subspecies, antique biovar, phylogenetic line 4.ANT, existence of joint natural foci of Yersinia pestis belonging to non-main subspecies ssp. altaica and ulegeica is established. Location of natural foci of the main and non-main subspecies of Yersinia pestis in different altitudinal belts of the Altai Mountains Range on the whole provides for observed multi-host and multi-vector feature of epizootic manifestations. For the first time ever, the data on the areal of the main subspecies of plague microbe are used for setting the boundaries of its natural focus.
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Genetic diversity and spatial-temporal distribution of Yersinia pestis in Qinghai Plateau, China. PLoS Negl Trop Dis 2018; 12:e0006579. [PMID: 29939993 PMCID: PMC6034908 DOI: 10.1371/journal.pntd.0006579] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 07/06/2018] [Accepted: 06/04/2018] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Plague, caused by the bacterium Yersinia pestis, is a highly infectious, zoonotic disease. Hundreds of human plague cases are reported across the world annually. Qinghai Plateau is one of the most severely affected plague regions in China, with more than 240 fatal cases of Y. pestis in the last 60 years. Conventional epidemiologic analysis has effectively guided the prevention and control of local plague transmission; however, molecular genetic analysis is more effective for investigating population diversity and transmission. In this report, we employed different genetic markers to analyze the population structure of Y. pestis in Qinghai Plateau. METHODOLOGY/PRINCIPAL FINDING We employed a two-step hierarchical strategy to analyze the phylogeny of 102 Qinghai Plateau isolates of Y. pestis, collected between 1954 and 2011. First, we defined the genealogy of Y. pestis by constructed minimum spanning tree based on 25 key SNPs. Seven groups were identified, with group 1.IN2 being identified as the dominant population. Second, two methods, MLVA and CRISPR, were applied to examine the phylogenetic detail of group 1.IN2, which was further divided into three subgroups. Subgroups of 1.IN2 revealed a clear geographic cluster, possibly associated with interaction between bacteriophage and Y. pestis. More recently, Y. pestis populations appear to have shifted from the east toward the center and west of Qinghai Plateau. This shift could be related to destruction of the local niche of the original plague focus through human activities. Additionally, we found that the abundance and relative proportion of 1.IN2 subgroups varied by decade and might be responsible for the fluctuations of plague epidemics in Qinghai Plateau. CONCLUSION/SIGNIFICANCE Molecular genotyping methods provided us with detailed information on population diversity and the spatial-temporal distribution of dominant populations of Y. pestis, which will facilitate future surveillance, prevention, and control of plague in Qinghai Plateau.
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Shi L, Yang G, Zhang Z, Xia L, Liang Y, Tan H, He J, Xu J, Song Z, Li W, Wang P. Reemergence of human plague in Yunnan, China in 2016. PLoS One 2018; 13:e0198067. [PMID: 29897940 PMCID: PMC5999221 DOI: 10.1371/journal.pone.0198067] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Accepted: 04/11/2018] [Indexed: 01/15/2023] Open
Abstract
The third plague pandemic originated from Yunnan Province, China in the middle of the 19th century. The last human plague epidemic in Yunnan occurred from 1986-2005. On June 6, 2016, a case of human plague was reported in the Xishuangbanna Prefecture, Yunnan. The patient suffered from primary septicemic plague after exposure to a dead house rat (Rattus flavipectus), which has been identified as the main plague reservoir in the local epizootic area. Moreover, a retrospective investigation identified another bubonic plague case in this area. Based on these data, human plague reemerged after a silent period of ten years. In this study, three molecular typing methods, including a clustered regularly interspaced short palindromic repeats (CRISPR) analysis, different region analysis (DFR), and multiple-locus variable number of tandem repeats analysis (MLVA), were used to illustrate the molecular characteristics of Yersinia pestis (Y. pestis) strains isolated in Yunnan. The DFR profiles of the strains isolated in Yunnan in 2016 were the same as the strains that had previously been isolated in this Rattus flavipectus plague focus. The c3 spacer present in the previously isolated strains was absent in the spacer arrays of the Ypc CRISPR loci of the strains isolated in 2016. The MLVA analysis using MLVA (14+12) showed that the strains isolated from the human plague case and host animal plague infection in 2016 in Yunnan displayed different molecular patterns than the strains that had previously been isolated from Yunnan and adjacent provinces.
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Affiliation(s)
- Liyuan Shi
- Yunnan Institute for Endemic Disease Control and Prevention, Yunnan, China
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan, China
| | - Guirong Yang
- Yunnan Institute for Endemic Disease Control and Prevention, Yunnan, China
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan, China
| | - Zhikai Zhang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Lianxu Xia
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Ying Liang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Hongli Tan
- Yunnan Institute for Endemic Disease Control and Prevention, Yunnan, China
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan, China
| | - Jinrong He
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Jianguo Xu
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Zhizhong Song
- Yunnan Institute for Endemic Disease Control and Prevention, Yunnan, China
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan, China
| | - Wei Li
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease control and Prevention, Changping, Beijing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Zhejiang, China
| | - Peng Wang
- Yunnan Institute for Endemic Disease Control and Prevention, Yunnan, China
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan, China
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Furstenau TN, Cocking JH, Sahl JW, Fofanov VY. Variant site strain typer (VaST): efficient strain typing using a minimal number of variant genomic sites. BMC Bioinformatics 2018; 19:222. [PMID: 29890941 PMCID: PMC5996513 DOI: 10.1186/s12859-018-2225-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 05/30/2018] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Targeted PCR amplicon sequencing (TAS) techniques provide a sensitive, scalable, and cost-effective way to query and identify closely related bacterial species and strains. Typically, this is accomplished by targeting housekeeping genes that provide resolution down to the family, genera, and sometimes species level. Unfortunately, this level of resolution is not sufficient in many applications where strain-level identification of bacteria is required (biodefense, forensics, clinical diagnostics, and outbreak investigations). Adding more genomic targets will increase the resolution, but the challenge is identifying the appropriate targets. VaST was developed to address this challenge by finding the minimum number of targets that, in combination, achieve maximum strain-level resolution for any strain complex. The final combination of target regions identified by the algorithm produce a unique haplotype for each strain which can be used as a fingerprint for identifying unknown samples in a TAS assay. VaST ensures that the targets have conserved primer regions so that the targets can be amplified in all of the known strains and it also favors the inclusion of targets with basal variants which makes the set more robust when identifying previously unseen strains. RESULTS We analyzed VaST's performance using a number of different pathogenic species that are relevant to human disease outbreaks and biodefense. The number of targets required to achieve full resolution ranged from 20 to 88% fewer sites than what would be required in the worst case and most of the resolution is achieved within the first 20 targets. We computationally and experimentally validated one of the VaST panels and found that the targets led to accurate phylogenetic placement of strains, even when the strains were not a part of the original panel design. CONCLUSIONS VaST is an open source software that, when provided a set of variant sites, can find the minimum number of sites that will provide maximum resolution of a strain complex, and it has many different run-time options that can accommodate a wide range of applications. VaST can be an effective tool in the design of strain identification panels that, when combined with TAS technologies, offer an efficient and inexpensive strain typing protocol.
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Affiliation(s)
- Tara N Furstenau
- The School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1295 S Knoles Dr., Flagstaff, Arizona, 86001, USA
| | - Jill H Cocking
- The School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1295 S Knoles Dr., Flagstaff, Arizona, 86001, USA
- Pathogen and Microbiome Institute, Northern Arizona University, 1395 S Knoles Dr., Flagstaff, Arizona, 86001, USA
| | - Jason W Sahl
- Pathogen and Microbiome Institute, Northern Arizona University, 1395 S Knoles Dr., Flagstaff, Arizona, 86001, USA
| | - Viacheslav Y Fofanov
- The School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1295 S Knoles Dr., Flagstaff, Arizona, 86001, USA.
- Pathogen and Microbiome Institute, Northern Arizona University, 1395 S Knoles Dr., Flagstaff, Arizona, 86001, USA.
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8
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Wang P, Shi L, Zhang F, Guo Y, Zhang Z, Tan H, Cui Z, Ding Y, Liang Y, Liang Y, Yu D, Xu J, Li W, Song Z. Ten years of surveillance of the Yulong plague focus in China and the molecular typing and source tracing of the isolates. PLoS Negl Trop Dis 2018; 12:e0006352. [PMID: 29601573 PMCID: PMC5895057 DOI: 10.1371/journal.pntd.0006352] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 04/11/2018] [Accepted: 02/27/2018] [Indexed: 01/27/2023] Open
Abstract
Plague, caused by Yersinia pestis, was classified as a reemerging infectious disease by the World Health Organization. The five human pneumonic plague cases in Yulong County in 2005 gave rise to the discovery of a Yulong plague focus in Yunnan province, China. Thereafter, continuous wild rodent plague (sylvatic plague) was identified as the main plague reservoir of this focus. In this study, the epizootics in Yulong focus were described, and three molecular typing methods, including the different region (DFR) analysis, clustered regularly interspaced short palindromic repeats (CRISPRs), and the multiple-locus variable number of tandem repeats (VNTR) analysis (MLVA) (14+12), were used for the molecular typing and source tracing of Y. pestis isolates in the Yulong plague focus. Simultaneously, several isolates from the vicinity of Yunnan were used as controls. The results showed that during the 10-year period from 2006 to 2016, an animal plague epidemic occurred in 6 of those years, and 5 villages underwent an animal plague epidemic within a 30-km2 area of the Yulong plague focus. Searching for dead mice was the most effective monitoring method in this plague focus. No positive sample has been found in 6937 captured live rodents thus far, suggesting that the virulence of strains in the Yulong plague focus is stronger and the survival time of mice is shorter after infection. Strains from Lijiang, Sichuan and Tibet were of the same complex based on a typing analysis of DFR and CRISPR. The genetic relationship of Y. pestis illustrated by MLVA “14+12” demonstrates that Tibet and Sichuan strains evolved from the strains 1.IN2 (Qinghai, 1970 and Tibet, 1976), and Lijiang strains are closer to Batang strains (Batang County in Sichuan province, 2011, Himalaya marmot plague foci) in terms of genetic or phylogenic relationships. In conclusion, we have a deeper understanding of this new plague focus throughout this study, which provides a basis for effective prevention and control. Plague is a type of zoonosis that is highly lethal to humans. The surveillance of animal hosts is critical for the prevention and control of plague. The Yulong plague focus is a newly discovered plague focus in China in recent years. The plague outbreak had attracted widespread attention because 5 people were infected in 2005, 2 of whom died. We have monitored the plague focus for a decade, and isolated strains and DNAs of Yersinia pestis were studied. The structure, origin and evolutionary trend of the Yulong plague focus were clarified, which provides a scientific basis for the effective prevention and control of human plague. This article also provides a set of paradigms for the systematic study of new plague foci, which is a perfect combination of traditional monitoring methods and modern research methods.
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Affiliation(s)
- Peng Wang
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Liyuan Shi
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Fuxin Zhang
- Lijiang Center for Disease Control and Prevention, Lijiang City of Yunnan province, China
| | - Ying Guo
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Zhikai Zhang
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Changping, Beijing, China
| | - Hongli Tan
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Zhigang Cui
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Changping, Beijing, China
| | - Yibo Ding
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Ying Liang
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Changping, Beijing, China
| | - Yun Liang
- Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Yunnan Institute for Endemic Disease Control and Prevention, Dali city of Yunnan province, China
| | - Dongzheng Yu
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Changping, Beijing, China
| | - Jianguo Xu
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, Changping, Beijing, China
| | - Wei Li
- Lijiang Center for Disease Control and Prevention, Lijiang City of Yunnan province, China
- * E-mail: (WL); (ZS)
| | - Zhizhong Song
- Yunnan Center for Disease Control and Prevention, Kunming City of Yunnan province, China
- * E-mail: (WL); (ZS)
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9
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Zhang Y, Luo T, Yang C, Yue X, Guo R, Wang X, Buren M, Song Y, Yang R, Cao H, Cui Y, Dai X. Phenotypic and Molecular Genetic Characteristics of Yersinia pestis at an Emerging Natural Plague Focus, Junggar Basin, China. Am J Trop Med Hyg 2018; 98:231-237. [PMID: 29141705 DOI: 10.4269/ajtmh.17-0195] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The 15th natural plague focus in China, the Junggar Basin plague focus, is located near an important communication route connecting China and Central Asia and was discovered after 2005. To characterize the phenotypic and genetic diversity of the Yersinia pestis population in this newly established focus, we collected 25 Y. pestis strains from six counties across Junggar Basin in 2005-2006, and determined their biochemical features and genotypes based on multiple-locus variable number of tandem repeats analysis and clustered regularly interspaced short palindromic repeats analysis. We inferred the phylogenetic positions and possible sources of the Junggar strains by comparing their genotypes with the genetic diversity for known representative Y. pestis strains. Our results indicate that the major genotype of Junggar strains belongs to 2.MED1, a lineage of biovar Medievalis with identical biochemical characters and high virulence in mice. Although share a similar ecology, the 2.MED1 in Junggar Basin are not descended from known strains in the neighboring Central Asian Desert plague foci. Therefore, the emergence of the Junggar Basin plague focus is not attributable to the recent clonal spread of Y. pestis from Central Asia. We also identified two distinct minor genotypes in Junggar Basin, one of which clusters genetically with the 0.ANT1 strains of the Tianshan Mountain natural plague focus and another belongs to a 1.IN lineage not previously reported. Our study clarifies the phenotypic and genetic characters of Junggar Y. pestis strains. These findings extend our knowledge of the population diversity of Y. pestis and will facilitate future plague surveillance and prevention in Junggar Basin and adjacent regions.
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Affiliation(s)
- Yujiang Zhang
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Tao Luo
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Chao Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Xihong Yue
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Rong Guo
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Xinhui Wang
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Mingde Buren
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Yuqin Song
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Hanli Cao
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
| | - Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Xiang Dai
- The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, P. R. China
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10
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Lian DS, Zhao SJ. Capillary electrophoresis based on nucleic acid detection for diagnosing human infectious disease. Clin Chem Lab Med 2017; 54:707-38. [PMID: 26352354 DOI: 10.1515/cclm-2015-0096] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 06/17/2015] [Indexed: 01/22/2023]
Abstract
Rapid transmission, high morbidity, and mortality are the features of human infectious diseases caused by microorganisms, such as bacteria, fungi, and viruses. These diseases may lead within a short period of time to great personal and property losses, especially in regions where sanitation is poor. Thus, rapid diagnoses are vital for the prevention and therapeutic intervention of human infectious diseases. Several conventional methods are often used to diagnose infectious diseases, e.g. methods based on cultures or morphology, or biochemical tests based on metabonomics. Although traditional methods are considered gold standards and are used most frequently, they are laborious, time consuming, and tedious and cannot meet the demand for rapid diagnoses. Disease diagnosis using capillary electrophoresis methods has the advantages of high efficiency, high throughput, and high speed, and coupled with the different nucleic acid detection strategies overcomes the drawbacks of traditional identification methods, precluding many types of false positive and negative results. Therefore, this review focuses on the application of capillary electrophoresis based on nucleic detection to the diagnosis of human infectious diseases, and offers an introduction to the limitations, advantages, and future developments of this approach.
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11
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Mao Y, Yang X, Liu Y, Yan Y, Du Z, Han Y, Song Y, Zhou L, Cui Y, Yang R. Reannotation of Yersinia pestis Strain 91001 Based on Omics Data. Am J Trop Med Hyg 2016; 95:562-70. [PMID: 27382076 DOI: 10.4269/ajtmh.16-0215] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 05/17/2016] [Indexed: 12/16/2022] Open
Abstract
Yersinia pestis is among the most dangerous human pathogens, and systematic research of this pathogen is important in bacterial pathogenomics research. To fully interpret the biological functions, physiological characteristics, and pathogenesis of Y. pestis, a comprehensive annotation of its entire genome is necessary. The emergence of omics-based research has brought new opportunities to better annotate the genome of this pathogen. Here, the complete genome of Y. pestis strain 91001 was reannotated using genomics and proteogenomics data. One hundred and thirty-seven unreliable coding sequences were removed, and 41 homologous genes were relocated with their translational initiation sites, while the functions of seven pseudogenes and 392 hypothetical genes were revised. Moreover, annotations of noncoding RNAs, repeat sequences, and transposable elements have also been incorporated. The reannotated results are freely available at http://tody.bmi.ac.cn.
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Affiliation(s)
- Yiqing Mao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China. Center of Information Technology, Beijing Institute of Health and Medical Information, Beijing, People's Republic of China
| | - Xianwei Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Yang Liu
- Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China
| | - Yanfeng Yan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Zongmin Du
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Yanping Han
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Yajun Song
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Lei Zhou
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China
| | - Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China.
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People's Republic of China.
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12
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Two Distinct Yersinia pestis Populations Causing Plague among Humans in the West Nile Region of Uganda. PLoS Negl Trop Dis 2016; 10:e0004360. [PMID: 26866815 PMCID: PMC4750964 DOI: 10.1371/journal.pntd.0004360] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Accepted: 12/14/2015] [Indexed: 01/14/2023] Open
Abstract
Background Plague is a life-threatening disease caused by the bacterium, Yersinia pestis. Since the 1990s, Africa has accounted for the majority of reported human cases. In Uganda, plague cases occur in the West Nile region, near the border with Democratic Republic of Congo. Despite the ongoing risk of contracting plague in this region, little is known about Y. pestis genotypes causing human disease. Methodology/Principal Findings During January 2004–December 2012, 1,092 suspect human plague cases were recorded in the West Nile region of Uganda. Sixty-one cases were culture-confirmed. Recovered Y. pestis isolates were analyzed using three typing methods, single nucleotide polymorphisms (SNPs), pulsed field gel electrophoresis (PFGE), and multiple variable number of tandem repeat analysis (MLVA) and subpopulations analyzed in the context of associated geographic, temporal, and clinical data for source patients. All three methods separated the 61 isolates into two distinct 1.ANT lineages, which persisted throughout the 9 year period and were associated with differences in elevation and geographic distribution. Conclusions/Significance We demonstrate that human cases of plague in the West Nile region of Uganda are caused by two distinct 1.ANT genetic subpopulations. Notably, all three typing methods used, SNPs, PFGE, and MLVA, identified the two genetic subpopulations, despite recognizing different mutation types in the Y. pestis genome. The geographic and elevation differences between the two subpopulations is suggestive of their maintenance in highly localized enzootic cycles, potentially with differing vector-host community composition. This improved understanding of Y. pestis subpopulations in the West Nile region will be useful for identifying ecologic and environmental factors associated with elevated plague risk. Plague, a severe and often fatal zoonotic disease, is caused by the bacterium Yersinia pestis. Currently, the majority of human cases have been reported from resource limited areas of Africa, where the proximity to commensal rats and other small mammals increases the likelihood for human contact with infected animals or their fleas. Over a 9 year time period, >1000 suspect cases were recorded in the West Nile region of Uganda within the districts of Arua and Zombo. Culture-confirmed cases were shown by three independent typing methods to be due to two distinct 1.ANT genetic subpopulations of Y. pestis. The two genetic subpopulations persisted throughout the 9 year time period, consistent with their ongoing maintenance in local enzootic cycles. Additionally, the two subpopulations were found to differ with respect to geographic location and elevation, with SNP Group 1 strains being found further north and at lower elevations as compared to SNP Group 2. The relative independence of the two Y. pestis subpopulations is suggestive of their maintenance in distinct foci involving enzootic cycles with differing vector-host community composition.
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13
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Qi Z, Cui Y, Zhang Q, Yang R. Taxonomy of Yersinia pestis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 918:35-78. [PMID: 27722860 DOI: 10.1007/978-94-024-0890-4_3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This chapter summarized the taxonomy and typing works of Yersinia pestis since it's firstly identified in Hong Kong in 1894. Phenotyping methods that based on phenotypic characteristics, including biotyping, serotyping, antibiogram analysis, bacteriocin typing, phage typing, and plasmid typing, were firstly applied in classification of Y. pestis in subspecies level. And then, with the advancement of molecular biological technology, the methods based on outer membrane protein profiles, fatty acid composition, and bacterial mass fingerprinting were also used to identify the populations within Y. pestis. However, Y. pestis is a highly homogenous species; therefore, the above typing methods could only provide low resolution, e.g., only one serotype and one phage type were observed for the whole species. Since the 1990s, molecular typing based on DNA variations, including single-nucleotide polymorphism, gene gain/loss, variable-number tandem repeats, clustered regularly interspaced short palindromic repeat, etc., was introduced and improved the resolution and robust of typing result. Especially in recent years, genotyping-based whole-genome-wide variations were successfully employed in Y. pestis, which built the "gold standard" of typing scheme of the species and could distinguish the samples under the strain level. The taxonomy and typing works leaved us enormous polymorphism data; therefore, a comprehensive fingerprint database of Y. pestis was needed to collect and standardize these data, for facilitating future works on evolution, plague surveillance and control, anti-bioterrorism, and microbial forensic researches.
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Affiliation(s)
- Zhizhen Qi
- Qinghai Provincial Key Laboratory for Plague Control and Research, Qinghai Institute for Endemic Disease Prevention and Control, Xining, Qinghai Province, 811602, China
| | - Yujun Cui
- Beijing Institute of Microbiology and Epidemiology, No. Dongdajie, Fengtai, Beijing, 100071, China
| | - Qingwen Zhang
- Qinghai Provincial Key Laboratory for Plague Control and Research, Qinghai Institute for Endemic Disease Prevention and Control, Xining, Qinghai Province, 811602, China
| | - Ruifu Yang
- Beijing Institute of Microbiology and Epidemiology, No. Dongdajie, Fengtai, Beijing, 100071, China.
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14
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Vogler AJ, Keim P, Wagner DM. A review of methods for subtyping Yersinia pestis: From phenotypes to whole genome sequencing. INFECTION GENETICS AND EVOLUTION 2015; 37:21-36. [PMID: 26518910 DOI: 10.1016/j.meegid.2015.10.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 10/23/2015] [Accepted: 10/24/2015] [Indexed: 12/28/2022]
Abstract
Numerous subtyping methods have been applied to Yersinia pestis with varying success. Here, we review the various subtyping methods that have been applied to Y. pestis and their capacity for answering questions regarding the population genetics, phylogeography, and molecular epidemiology of this important human pathogen. Methods are evaluated in terms of expense, difficulty, transferability among laboratories, discriminatory power, usefulness for different study questions, and current applicability in light of the advent of whole genome sequencing.
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Affiliation(s)
- Amy J Vogler
- Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ 86011-4073, USA.
| | - Paul Keim
- Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ 86011-4073, USA; Translational Genomics Research Institute North, Flagstaff, AZ 86001, USA.
| | - David M Wagner
- Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ 86011-4073, USA.
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15
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Papadopoulou E, Gale N, Goodchild SA, Cleary DW, Weller SA, Brown T, Bartlett PN. Strain discrimination of Yersinia pestis using a SERS-based electrochemically driven melting curve analysis of variable number tandem repeat sequences. Chem Sci 2015; 6:1846-1852. [PMID: 29449917 PMCID: PMC5701729 DOI: 10.1039/c4sc03084b] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 12/23/2014] [Indexed: 12/05/2022] Open
Abstract
Strain discrimination within genetically highly similar bacteria is critical for epidemiological studies and forensic applications. An electrochemically driven melting curve analysis monitored by SERS has been utilised to reliably discriminate strains of the bacterial pathogen Yersinia pestis, the causative agent of plague. DNA amplicons containing Variable Number Tandem Repeats (VNTRs) were generated from three strains of Y. pestis: CO92, Harbin 35 and Kim. These amplicons contained a 10 base pair VNTR repeated 6, 5, and 4 times in CO92, Harbin 35 and Kim respectively. The assay also included a blocker oligonucleotide comprising 3 repeats of the 10-mer VNTR sequence. The use of the blocker reduced the effective length of the target sequence available to bind to the surface bound probe and significantly improved the sensitivity of the discrimination. The results were consistent during three replicates that were carried out on different days, using different batches of PCR product and different SERS sphere segment void (SSV) substrate. This methodology which combines low cost, speed and sensitivity is a promising alternative to the time consuming current electrophoretic methods.
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Affiliation(s)
- E Papadopoulou
- Chemistry , University of Southampton , Highfield , Southampton SO17 1BJ , UK .
| | - N Gale
- ATDBio Ltd , Chemistry , University of Southampton , Highfield , Southampton SO17 1BJ , UK
| | - S A Goodchild
- DSTL , Wiltshire SP4 0JQ , Salisbury , Porton Down , UK
| | - D W Cleary
- DSTL , Wiltshire SP4 0JQ , Salisbury , Porton Down , UK
| | - S A Weller
- DSTL , Wiltshire SP4 0JQ , Salisbury , Porton Down , UK
| | - T Brown
- Department of Chemistry , University of Oxford , Chemistry Research Laboratory , Oxford OX1 3TA , UK
| | - P N Bartlett
- Chemistry , University of Southampton , Highfield , Southampton SO17 1BJ , UK .
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16
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Cui Y, Yang X, Xiao X, Anisimov AP, Li D, Yan Y, Zhou D, Rajerison M, Carniel E, Achtman M, Yang R, Song Y. Genetic variations of live attenuated plague vaccine strains (Yersinia pestis EV76 lineage) during laboratory passages in different countries. INFECTION GENETICS AND EVOLUTION 2014; 26:172-9. [PMID: 24905600 DOI: 10.1016/j.meegid.2014.05.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2014] [Revised: 05/13/2014] [Accepted: 05/21/2014] [Indexed: 12/20/2022]
Abstract
Plague, one of the most devastating infectious diseases in human history, is caused by the bacterial species Yersinia pestis. A live attenuated Y. pestis strain (EV76) has been widely used as a plague vaccine in various countries around the world. Here we compared the whole genome sequence of an EV76 strain used in China (EV76-CN) with the genomes of Y. pestis wild isolates to identify genetic variations specific to the EV76 lineage. We identified 6 SNPs and 6 Indels (insertions and deletions) differentiating EV76-CN from its counterparts. Then, we screened these polymorphic sites in 28 other strains of EV76 lineage that were stored in different countries. Based on the profiles of SNPs and Indels, we reconstructed the parsimonious dissemination history of EV76 lineage. This analysis revealed that there have been at least three independent imports of EV76 strains into China. Additionally, we observed that the pyrE gene is a mutation hotspot in EV76 lineages. The fine comparison results based on whole genome sequence in this study provide better understanding of the effects of laboratory passages on the accumulation of genetic polymorphisms in plague vaccine strains. These variations identified here will also be helpful in discriminating different EV76 derivatives.
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Affiliation(s)
- Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Xianwei Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Xiao Xiao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Andrey P Anisimov
- State Research Center for Applied Microbiology and Biotechnology, Obolensk, Moscow Region, Russia
| | | | - Yanfeng Yan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Dongsheng Zhou
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | | | - Elisabeth Carniel
- Yersinia Research Unit, National Reference Laboratory, Institut Pasteur, Paris, France
| | - Mark Achtman
- Environmental Research Institute, University College Cork, Cork, Ireland, United Kingdom; Warwick Medical School, University of Warwick, Coventry, United Kingdom
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
| | - Yajun Song
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China; Environmental Research Institute, University College Cork, Cork, Ireland, United Kingdom.
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17
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Yan Y, Wang H, Li D, Yang X, Wang Z, Qi Z, Zhang Q, Cui B, Guo Z, Yu C, Wang J, Wang J, Liu G, Song Y, Li Y, Cui Y, Yang R. Two-step source tracing strategy of Yersinia pestis and its historical epidemiology in a specific region. PLoS One 2014; 9:e85374. [PMID: 24416399 PMCID: PMC3887043 DOI: 10.1371/journal.pone.0085374] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2013] [Accepted: 11/26/2013] [Indexed: 11/24/2022] Open
Abstract
Source tracing of pathogens is critical for the control and prevention of infectious diseases. Genome sequencing by high throughput technologies is currently feasible and popular, leading to the burst of deciphered bacterial genome sequences. Utilizing the flooding genomic data for source tracing of pathogens in outbreaks is promising, and challenging as well. Here, we employed Yersinia pestis genomes from a plague outbreak at Xinghai county of China in 2009 as an example, to develop a simple two-step strategy for rapid source tracing of the outbreak. The first step was to define the phylogenetic position of the outbreak strains in a whole species tree, and the next step was to provide a detailed relationship across the outbreak strains and their suspected relatives. Through this strategy, we observed that the Xinghai plague outbreak was caused by Y. pestis that circulated in the local plague focus, where the majority of historical plague epidemics in the Qinghai-Tibet Plateau may originate from. The analytical strategy developed here will be of great help in fighting against the outbreaks of emerging infectious diseases, by pinpointing the source of pathogens rapidly with genomic epidemiological data and microbial forensics information.
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Affiliation(s)
- Yanfeng Yan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- BGI-Shenzhen, Shenzhen, China
| | - Hu Wang
- Qinghai Institute for Endemic Diseases Prevention and Control, Xining, China
| | | | - Xianwei Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Zuyun Wang
- Qinghai Institute for Endemic Diseases Prevention and Control, Xining, China
| | - Zhizhen Qi
- Qinghai Institute for Endemic Diseases Prevention and Control, Xining, China
| | - Qingwen Zhang
- Qinghai Institute for Endemic Diseases Prevention and Control, Xining, China
| | - Baizhong Cui
- Qinghai Institute for Endemic Diseases Prevention and Control, Xining, China
| | - Zhaobiao Guo
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | | | | | | | - Guangming Liu
- School of Computer Science, National University of Defense Technology, Changsha, China
| | - Yajun Song
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | | | - Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- BGI-Shenzhen, Shenzhen, China
- * E-mail: (RY); (YC)
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- BGI-Shenzhen, Shenzhen, China
- * E-mail: (RY); (YC)
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