Ford Laura, Carter Glen P, Wang Qinning, Seemann Torsten, Sintchenko Vitali, Glass Kathryn, Williamson Deborah A, Howard Peter, Valcanis Mary, Castillo Cristina Fabiola Sotomayor, Sait Michelle, Howden Benjamin P, Kirk Martyn D
1 National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University , Canberra, Australia .
2 OzFoodNet, Health Protection Service, Population Health Protection and Prevention , ACT Health, Canberra, Australia .
Foodborne Pathog Dis. 2018 Mar;15(3):161-167. doi: 10.1089/fpd.2017.2352. Epub 2018 Jan 16.
In Australia, the incidence of Salmonella Typhimurium has increased dramatically over the past decade. Whole-genome sequencing (WGS) is transforming public health microbiology, but poses challenges for surveillance. To compare WGS-based approaches with conventional typing for Salmonella surveillance, we performed concurrent WGS and multilocus variable-number tandem-repeat analysis (MLVA) of Salmonella Typhimurium isolates from the Australian Capital Territory (ACT) for a period of 5 months. We exchanged data via a central shared virtual machine and performed comparative genomic analyses. Epidemiological evidence was integrated with WGS-derived data to identify related isolates and sources of infection, and we compared WGS data for surveillance with findings from MLVA typing. We found that WGS data combined with epidemiological data linked an additional 9% of isolates to at least one other isolate in the study in contrast to MLVA and epidemiological data, and 19% more isolates than epidemiological data alone. Analysis of risk factors showed that in one WGS-defined cluster, human cases had higher odds of purchasing a single egg brand. While WGS was more sensitive and specific than conventional typing methods, we identified barriers to uptake of genomic surveillance around complexity of reporting of WGS results, timeliness, acceptability, and stability. In conclusion, WGS offers higher resolution of Salmonella Typhimurium laboratory surveillance than existing methods and can provide further evidence on sources of infection in case and outbreak investigations for public health action. However, there are several challenges that need to be addressed for effective implementation of genomic surveillance in Australia.
在澳大利亚，过去十年间鼠伤寒沙门氏菌的发病率急剧上升。全基因组测序（WGS）正在改变公共卫生微生物学，但给监测工作带来了挑战。为了比较基于WGS的方法与传统分型方法在沙门氏菌监测中的效果，我们对来自澳大利亚首都地区（ACT）的鼠伤寒沙门氏菌分离株进行了为期5个月的同步WGS和多位点可变数目串联重复序列分析（MLVA）。我们通过中央共享虚拟机交换数据并进行比较基因组分析。将流行病学证据与WGS衍生数据相结合，以识别相关分离株和感染源，并将WGS监测数据与MLVA分型结果进行比较。我们发现，与MLVA和流行病学数据相比，WGS数据与流行病学数据相结合，在研究中可将另外9%的分离株与至少一个其他分离株联系起来，比仅使用流行病学数据多识别出19%的分离株。风险因素分析表明，在一个由WGS定义的集群中，人类病例购买单一品牌鸡蛋的几率更高。虽然WGS比传统分型方法更敏感、更具特异性，但我们发现，在WGS结果报告的复杂性、及时性、可接受性和稳定性方面，基因组监测的应用存在障碍。总之，与现有方法相比，WGS在鼠伤寒沙门氏菌实验室监测中具有更高的分辨率，并且可以为公共卫生行动的病例和疫情调查中的感染源提供进一步证据。然而，在澳大利亚有效实施基因组监测还需要应对若干挑战。
