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机器学习归因美国弯曲杆菌感染源:国家监测数据的回顾性分析。

Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.

机构信息

Ineos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford, United Kingdom.

The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath, United Kingdom.

出版信息

J Infect. 2024 Nov;89(5):106265. doi: 10.1016/j.jinf.2024.106265. Epub 2024 Sep 7.

Abstract

OBJECTIVES

Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in the gut of birds and mammals and often infect humans via contaminated food. Rising incidence and antimicrobial resistance (AMR) are a global concern, and there is an urgent need to quantify the main routes to human infection.

METHODS

During routine US national surveillance (2009-2019), 8856 Campylobacter genomes from human infections and 16,703 from possible sources were sequenced. Using machine learning and probabilistic models, we target genetic variation associated with host adaptation to attribute the source of human infections and estimate the importance of different disease reservoirs.

RESULTS

Poultry was identified as the primary source of human infections, responsible for an estimated 68% of cases, followed by cattle (28%), and only a small contribution from wild birds (3%) and pork sources (1%). There was also evidence of an increase in multidrug resistance, particularly among isolates attributed to chickens.

CONCLUSIONS

National surveillance and source attribution can guide policy, and our study suggests that interventions targeting poultry will yield the greatest reductions in campylobacteriosis and spread of AMR in the US.

DATA AVAILABILITY

All sequence reads were uploaded and shared on NCBI's Sequence Read Archive (SRA) associated with BioProjects; PRJNA239251 (CDC / PulseNet surveillance), PRJNA287430 (FSIS surveillance), PRJNA292668 & PRJNA292664 (NARMS) and PRJNA258022 (FDA surveillance). Publicly available genomes, including reference genomes and isolates sampled worldwide from wild birds are associated with BioProject accessions: PRJNA176480, PRJNA177352, PRJNA342755, PRJNA345429, PRJNA312235, PRJNA415188, PRJNA524300, PRJNA528879, PRJNA529798, PRJNA575343, PRJNA524315 and PRJNA689604. Contiguous assemblies of all genome sequences compared are available at Mendeley data (assembled C. coli genomes doi: 10.17632/gxswjvxyh3.1; assembled C. jejuni genomes doi: 10.17632/6ngsz3dtbd.1) and individual project and accession numbers can be found in Supplementary tables S1 and S2, which also includes pubMLST identifiers for assembled genomes. Figshare (10.6084/m9.figshare.20279928). Interactive phylogenies are hosted on microreact separately for C. jejuni (https://microreact.org/project/pascoe-us-cjejuni) and C. coli (https://microreact.org/project/pascoe-us-ccoli).

摘要

目的

将病原体基因组监测与生物信息学相结合,可以通过识别风险和指导干预措施来增强公共卫生应对能力。本研究集中于两种主要的弯曲菌属,它们通常存在于鸟类和哺乳动物的肠道中,并且经常通过受污染的食物感染人类。发病率和抗生素耐药性(AMR)的上升是一个全球性的问题,迫切需要量化主要的人类感染途径。

方法

在美国国家监测期间(2009-2019 年),对 8856 例人类感染和 16703 例可能来源的弯曲菌基因组进行了测序。使用机器学习和概率模型,我们针对与宿主适应性相关的遗传变异,确定人类感染的来源,并估计不同疾病储主的重要性。

结果

家禽被确定为人类感染的主要来源,估计占病例的 68%,其次是牛(28%),只有一小部分来自野生鸟类(3%)和猪肉来源(1%)。也有证据表明多药耐药性增加,特别是在归因于鸡的分离株中。

结论

国家监测和来源归因可以指导政策,我们的研究表明,针对家禽的干预措施将在美国最大程度地减少弯曲菌病和 AMR 的传播。

数据可用性

所有序列读取均已上传并在 NCBI 的序列读取档案(SRA)上与 BioProjects 共享; PRJNA239251(CDC / PulseNet 监测),PRJNA287430(FSIS 监测),PRJNA292668 和 PRJNA292664(NARMS)和 PRJNA258022(FDA 监测)。可公开获得的基因组,包括参考基因组和从世界各地的野生鸟类中采样的分离株,与 BioProject 访问号相关联:PRJNA176480,PRJNA177352,PRJNA342755,PRJNA345429,PRJNA312235,PRJNA415188,PRJNA524300,PRJNA528879,PRJNA529798,PRJNA575343,PRJNA524315 和 PRJNA689604。比较的所有基因组序列的连续组装可在 Mendeley 数据中获得(组装的 C. coli 基因组 doi:10.17632/gxswjvxyh3.1; 组装的 C. jejuni 基因组 doi:10.17632/6ngsz3dtbd.1),并且可以在补充表 S1 和 S2 中找到各个项目和访问号,其中还包括组装基因组的 pubMLST 标识符。 Figshare(10.6084/m9.figshare.20279928)。交互式系统发育树分别在 microreact 上为 C. jejuni(https://microreact.org/project/pascoe-us-cjejuni)和 C. coli(https://microreact.org/project/pascoe-us-ccoli)托管。

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