Hetman Benjamin M, Mutschall Steven K, Carrillo Catherine D, Thomas James E, Gannon Victor P J, Inglis G Douglas, Taboada Eduardo N
Department of Biological Sciences, University of Lethbridge, Lethbridge, AB, Canada.
National Microbiology Laboratory at Lethbridge, Public Health Agency of Canada, Lethbridge, AB, Canada.
Front Microbiol. 2020 Apr 9;11:541. doi: 10.3389/fmicb.2020.00541. eCollection 2020.
Microbiological surveillance of the food chain plays a critical role in improving our understanding of the distribution and circulation of food-borne pathogens along the farm to fork continuum toward the development of interventions to reduce the burden of illness. The application of molecular subtyping to bacterial isolates collected through surveillance has led to the identification of strains posing the greatest risk to public health. Past evidence suggests that enrichment methods for , a leading bacterial foodborne pathogen worldwide, may lead to the differential recovery of subtypes, obscuring our ability to infer the composition of a mixed-strain sample and potentially biasing prevalence estimates in surveillance data. To assess the extent of potential selection bias resulting from enrichment-based isolation methods, we compared enrichment and non-enrichment isolation of mixed subtype cultures of , followed by subtype-specific enumeration using both colony plate-counts and digital droplet PCR. Results differed from the null hypothesis that similar proportions of subtypes are recovered from both methods. Our results also indicated a significant effect of subtype prevalence on isolation frequency post-recovery, with the recovery of more common subtypes being consistently favored. This bias was exacerbated when an enrichment step was included in the isolation procedure. Taken together, our results emphasize the importance of selecting multiple colonies per sample, and where possible, the use of both enrichment and non-enrichment isolation procedures to maximize the likelihood of recovering multiple subtypes present in a sample. Moreover, the effects of subtype-specific recovery bias should be considered in the interpretation of strain prevalence data toward improved risk assessment from microbiological surveillance data.
食物链的微生物监测在增进我们对食源性病原体在从农场到餐桌的连续过程中的分布和传播的理解方面发挥着关键作用，有助于制定干预措施以减轻疾病负担。将分子分型应用于通过监测收集的细菌分离株，已导致识别出对公众健康构成最大风险的菌株。过去的证据表明，对于一种全球主要的食源细菌性病原体，富集方法可能导致亚型的差异回收，模糊我们推断混合菌株样本组成的能力，并可能使监测数据中的流行率估计产生偏差。为了评估基于富集的分离方法导致的潜在选择偏差程度，我们比较了该菌混合亚型培养物的富集分离和非富集分离，随后使用菌落平板计数和数字液滴PCR进行亚型特异性计数。结果与两种方法回收相似比例的该菌亚型的零假设不同。我们的结果还表明亚型流行率对回收后的分离频率有显著影响，较常见亚型的回收一直受到青睐。当分离程序中包含富集步骤时，这种偏差会加剧。综上所述，我们的结果强调了每个样本选择多个菌落的重要性，并在可能的情况下，使用富集和非富集分离程序以最大限度地提高回收样本中存在的多种亚型的可能性。此外，在解释菌株流行率数据时应考虑亚型特异性回收偏差的影响，以便从微生物监测数据中改进风险评估。
