Sara Romano-Bertrand, Maxine Virieux-Petit, Florian Mauffrey, Laurence Senn, Dominique S Blanc
{"title":"定义研究铜绿假单胞菌医院暴发的基因组阈值。","authors":"Sara Romano-Bertrand, Maxine Virieux-Petit, Florian Mauffrey, Laurence Senn, Dominique S Blanc","doi":"10.1016/j.jhin.2025.04.028","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>When investigating Pseudomonas aeruginosa (PA) outbreak, the clonality of isolates should be demonstrated using molecular typing method. Whole-genome sequencing (WGS) is the new Gold Standard for bacterial genotyping, but results interpretation must be careful about considering isolates as part of the same chain of transmission.</p><p><strong>Aim: </strong>To determine genomic threshold to identify recent transmission events considering the spatiotemporal scale of the outbreak.</p><p><strong>Methods: </strong>PA outbreaks occurring in our hospital during the past 15 years were retrospectively analysed by both core-genome MLST and single-nucleotide polymorphism (SNP) in regards of epidemiological data. Our results were discussed in the light of previous published literature employing WGS to investigate hospital outbreaks of PA.</p><p><strong>Findings: </strong>14 investigations of PA outbreaks in our hospital were included, lasting a few days to 9 years. Isolates belonging to a same chain of transmission presented up to 13 loci differences and 25 SNPs. These results were in accordance with the 19 published outbreaks that mostly reported a similarity among epidemiologically related isolates below 15-25 SNPs. The impact of time and space on the threshold of eligible SNPs or loci differences was possibly masked by other factors including the genotype, the number of isolates included in the WGS analysis, the path of transmission and the presence of environmental reservoir.</p><p><strong>Conclusions: </strong>Our study emphasizes the need to integrate genomic thresholds with epidemiological data, especially when environmental reservoirs or hypermutators are involved, to accurately assess transmission dynamics and outbreak origins.</p>","PeriodicalId":54806,"journal":{"name":"Journal of Hospital Infection","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Defining a genomic threshold for investigating Pseudomonas aeruginosa hospital outbreak.\",\"authors\":\"Sara Romano-Bertrand, Maxine Virieux-Petit, Florian Mauffrey, Laurence Senn, Dominique S Blanc\",\"doi\":\"10.1016/j.jhin.2025.04.028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>When investigating Pseudomonas aeruginosa (PA) outbreak, the clonality of isolates should be demonstrated using molecular typing method. Whole-genome sequencing (WGS) is the new Gold Standard for bacterial genotyping, but results interpretation must be careful about considering isolates as part of the same chain of transmission.</p><p><strong>Aim: </strong>To determine genomic threshold to identify recent transmission events considering the spatiotemporal scale of the outbreak.</p><p><strong>Methods: </strong>PA outbreaks occurring in our hospital during the past 15 years were retrospectively analysed by both core-genome MLST and single-nucleotide polymorphism (SNP) in regards of epidemiological data. Our results were discussed in the light of previous published literature employing WGS to investigate hospital outbreaks of PA.</p><p><strong>Findings: </strong>14 investigations of PA outbreaks in our hospital were included, lasting a few days to 9 years. Isolates belonging to a same chain of transmission presented up to 13 loci differences and 25 SNPs. These results were in accordance with the 19 published outbreaks that mostly reported a similarity among epidemiologically related isolates below 15-25 SNPs. The impact of time and space on the threshold of eligible SNPs or loci differences was possibly masked by other factors including the genotype, the number of isolates included in the WGS analysis, the path of transmission and the presence of environmental reservoir.</p><p><strong>Conclusions: </strong>Our study emphasizes the need to integrate genomic thresholds with epidemiological data, especially when environmental reservoirs or hypermutators are involved, to accurately assess transmission dynamics and outbreak origins.</p>\",\"PeriodicalId\":54806,\"journal\":{\"name\":\"Journal of Hospital Infection\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hospital Infection\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jhin.2025.04.028\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hospital Infection","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jhin.2025.04.028","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Defining a genomic threshold for investigating Pseudomonas aeruginosa hospital outbreak.
Background: When investigating Pseudomonas aeruginosa (PA) outbreak, the clonality of isolates should be demonstrated using molecular typing method. Whole-genome sequencing (WGS) is the new Gold Standard for bacterial genotyping, but results interpretation must be careful about considering isolates as part of the same chain of transmission.
Aim: To determine genomic threshold to identify recent transmission events considering the spatiotemporal scale of the outbreak.
Methods: PA outbreaks occurring in our hospital during the past 15 years were retrospectively analysed by both core-genome MLST and single-nucleotide polymorphism (SNP) in regards of epidemiological data. Our results were discussed in the light of previous published literature employing WGS to investigate hospital outbreaks of PA.
Findings: 14 investigations of PA outbreaks in our hospital were included, lasting a few days to 9 years. Isolates belonging to a same chain of transmission presented up to 13 loci differences and 25 SNPs. These results were in accordance with the 19 published outbreaks that mostly reported a similarity among epidemiologically related isolates below 15-25 SNPs. The impact of time and space on the threshold of eligible SNPs or loci differences was possibly masked by other factors including the genotype, the number of isolates included in the WGS analysis, the path of transmission and the presence of environmental reservoir.
Conclusions: Our study emphasizes the need to integrate genomic thresholds with epidemiological data, especially when environmental reservoirs or hypermutators are involved, to accurately assess transmission dynamics and outbreak origins.
期刊介绍:
The Journal of Hospital Infection is the editorially independent scientific publication of the Healthcare Infection Society. The aim of the Journal is to publish high quality research and information relating to infection prevention and control that is relevant to an international audience.
The Journal welcomes submissions that relate to all aspects of infection prevention and control in healthcare settings. This includes submissions that:
provide new insight into the epidemiology, surveillance, or prevention and control of healthcare-associated infections and antimicrobial resistance in healthcare settings;
provide new insight into cleaning, disinfection and decontamination;
provide new insight into the design of healthcare premises;
describe novel aspects of outbreaks of infection;
throw light on techniques for effective antimicrobial stewardship;
describe novel techniques (laboratory-based or point of care) for the detection of infection or antimicrobial resistance in the healthcare setting, particularly if these can be used to facilitate infection prevention and control;
improve understanding of the motivations of safe healthcare behaviour, or describe techniques for achieving behavioural and cultural change;
improve understanding of the use of IT systems in infection surveillance and prevention and control.