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一种用于检测加拿大爱德华王子岛野生牡蛎中原生动物病原体的代谢条码方法。

A metabarcoding approach for detecting protozoan pathogens in wild oysters from Prince Edward Island, Canada.

机构信息

Department of Integrative Biology, University of Guelph, 50 Stone Rd E, Guelph, Ontario N1G 2W1, Canada; Department of Mathematics and Statistics, University of Guelph, 50 Stone Rd E, Guelph, Ontario N1G 2W1, Canada.

Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, 550 University Ave, Charlottetown, Prince Edward Island C1A 4P3, Canada.

出版信息

Int J Food Microbiol. 2021 Dec 16;360:109315. doi: 10.1016/j.ijfoodmicro.2021.109315. Epub 2021 Jun 21.

Abstract

Food and waterborne protozoan pathogens including Cryptosporidium parvum, Giardia enterica and Toxoplasma gondii are a global concern for human public health. While all three pathogens have been detected in commercial shellfish, there is currently no standard approach for detecting protozoan parasites in shellfish. Common molecular and microscopic methods are limited in the number of pathogens they can simultaneously detect and are often targeted at one or two of these pathogens. Previously, we developed and validated a novel 18S amplicon-based next-generation sequencing assay for simultaneous detection of Cryptosporidium spp., Giardia spp. and T. gondii in shellfish. In this study, we applied the assay for protozoan pathogen detection in wild oysters from Prince Edward Island (PEI). Oysters were harvested from restricted and prohibited areas, classified by the Canadian government according to fecal coliform counts in surrounding waters, and different fractions (whole tissue homogenate and hemolymph) were analyzed. Protozoan DNA was detected using metabarcoding in 28%, of oysters tested (N = 128), and the pathogen read counts in oyster homogenate were considerably higher than those in hemolymph. Protozoan read count thresholds were established for classifying probable oyster contamination with pathogens to account for low levels of background protozoan reads detected in negative controls. Assay results showed protozoan contamination was not associated with harvesting site classifications, suggesting that using fecal indicators for ensuring food safety may be insufficient. Due to the complex matrix, an oyster DNA reduction step may further improve the pathogen detection sensitivity of the assay. Results from this study affirm that novel metabarcoding is a promising screening tool for detection of protozoan pathogens in shellfish.

摘要

食品和水源性原生动物病原体,包括微小隐孢子虫、肠贾第鞭毛虫和刚地弓形虫,是全球人类公共卫生关注的问题。虽然这三种病原体都在商业贝类中被检测到,但目前还没有用于贝类中原生动物寄生虫检测的标准方法。常见的分子和显微镜方法在能够同时检测的病原体数量上存在限制,而且通常针对这些病原体中的一种或两种。此前,我们开发并验证了一种新的基于 18S 扩增子的下一代测序检测方法,用于同时检测贝类中的微小隐孢子虫、肠贾第鞭毛虫和刚地弓形虫。在这项研究中,我们应用该方法检测来自爱德华王子岛(PEI)的野生牡蛎中的原生动物病原体。牡蛎是根据周围水域粪便大肠菌群计数,由加拿大政府分类,从限制和禁止区域收获的,并对不同部分(组织匀浆和血淋巴)进行分析。使用代谢组学在 28%的测试牡蛎(N=128)中检测到原生动物 DNA,并且牡蛎匀浆中的病原体读数明显高于血淋巴中的读数。为了分类可能存在病原体污染的牡蛎,建立了原生动物读数阈值,以解释在阴性对照中检测到的低水平背景原生动物读数。检测结果表明,原生动物污染与收获地点分类无关,这表明使用粪便指标来确保食品安全可能是不够的。由于基质复杂,牡蛎 DNA 还原步骤可能会进一步提高该检测方法的病原体检测灵敏度。本研究结果证实,新型代谢组学是一种很有前途的贝类中原生动物病原体检测筛选工具。

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