Assembled C. jejuni genomes for the publication: Machine learning to attribute the source of Campylobacter infections in the United States: a retrospective analysis of national surveillance data

Objectives Combined pathogen genomic surveillance with advanced bioinformatics analyses has the potential to inform public health risk and targeted interventions. In this study, we analyse the two most common pathogenic Campylobacter species in human gastrointestinal infection. These enteric bacteria are ubiquitous in the gut of birds and mammals and commonly infect humans via consumption of contaminated food. Rising incidence and antimicrobial resistance (AMR) are a major global concern and there is an urgent need to quantify the main routes to human infection. Methods As part of routine US national surveillance (2009 through 2019), 8,856 Campylobacter isolate genomes were sequenced from human infections and 16,703 from possible sources. Targeting genetic variation associated with host adaptation, we used machine learning and probabilistic models to attribute the source of human infections and estimate the relative importance of different disease reservoirs. Results Poultry was identified as the primary source of human infection, responsible for an estimated 68% of cases. Most of the remaining isolates were attributed to cattle (28%), with only a small contribution from wild bird (3%) and pork sources (1%). There was also evidence of an increase in multidrug resistance, particularly fluoroquinolone and aminoglycoside resistance among isolates attributed to chickens. Conclusions National-scale surveillance and quantification of the relative contribution of infection sources can guide policy. Our study suggests that the greatest reductions in human campylobacteriosis in the US will come from interventions that focus on poultry, which may also reduce the spread of AMR.研究背景与目标：将病原体基因组监测与先进的生物信息学分析相结合，可为公共卫生风险评估与精准干预提供关键依据。本研究聚焦于引发人类胃肠道感染的两种最常见致病弯曲杆菌（Campylobacter）物种。这类肠道细菌广泛定植于鸟类与哺乳动物的肠道内，通常经受污染食物传播而感染人类。近年来，其发病率上升与抗菌素耐药性（antimicrobial resistance, AMR）已成为全球重大公共卫生关切，亟需量化人类感染的主要传播途径。 研究方法：作为2009年至2019年美国常规国家监测项目的组成部分，研究团队从人类感染病例中获取了8856株弯曲杆菌分离株的基因组序列，同时从潜在污染源中获取了16703株分离株的基因组序列。针对与宿主适应性相关的遗传变异，本研究采用机器学习与概率模型对人类感染的传染源进行溯源，并评估不同宿主储存库的相对重要性。 研究结果：研究确认家禽是人类感染的主要传染源，据估算可导致68%的感染病例。剩余绝大多数分离株被溯源至牛（28%），仅少量分离株来自野生鸟类（3%）与猪肉源（1%）。此外，研究还观察到多重耐药性呈上升趋势，尤其是在被溯源至鸡只的分离株中，氟喹诺酮类与氨基糖苷类耐药性尤为显著。 研究结论：国家级规模的监测体系与感染来源相对贡献量化方法，可为公共卫生政策制定提供科学指导。本研究表明，若要降低美国人类弯曲杆菌病的发病率，最有效的干预措施应聚焦于家禽领域，此举同时也可减少抗菌素耐药性的传播扩散。