摘要

       由于农业和畜牧业活动造成的径流和粪便污染，天然河流沉积物对公众健康的危害鲜为人知。例如，食源性病原体如志贺毒素产生性大肠杆菌（STEC）的持续存在，这些来源于这些做法仍然缺乏量化。为了弥补这些知识空白，在加州萨利纳斯河谷的两条小溪的水-沉积物界面进行了为期9个月的STEC亚基因组学和传统培养基试验取样。我们的研究结果表明，这些沉积物群落是极其多样的，其功能和分类多样性与在土壤中观察到的相当。通过我们的测序工作（每个文库4 Gbp），我们无法在11个使用基于培养的方法检测呈阳性的样本的基因组中检测到任何致病性大肠杆菌，显然是由于相对较低的丰度。此外，与上游较原始（对照）点相比，下游受影响点的人类或奶牛特定肠道微生物组序列的丰度没有显著差异，表明人为输入的自然稀释。值得注意的是，在所有样本中发现的携带抗生素抗性基因（ARGs）的高数量的亚基因组读数明显高于其他可用的淡水和土壤亚基因组中的ARG读数，这表明这些群落可能是ARGs的自然宿主。这里的工作应该作为取样量、应用的排序数量的指南，以及在使用宏基因组学对环境样本（如沉积物）进行公共健康风险研究时，生物信息学分析要执行的操作。重要的是，当前的农业和畜牧业做法会导致环境中的粪便污染以及食物和水传播疾病和抗生素抗性基因（ARG）的传播。传统上，对肠出血性大肠杆菌的污染水平和对公众健康的风险是通过基于培养的试验来评估的，然而，这些传统方法的准确性（例如，定量的准确性低，以及基于PCR的假阳性信号）及其对沉积物的适用性仍然不清楚。我们收集了美国最高产农业区的沉积物进行时间序列的亚基因组学研究，以评估农业径流对本地微生物群落的影响，以及沉积物样品中是否可以直接检测到产志贺毒素的大肠杆菌（STEC）排序。我们的研究提供了重要的信息，说明了在自然环境中利用亚基因组学作为评估公共健康风险的工具的潜力。

        Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (∼4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was significantly higher than ARG reads in other available freshwater and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments.IMPORTANCE Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli However, the accuracy of these traditional methods (e.g., low accuracy in quantification, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.

        https://aem.asm.org/content/86/6/e02525-19.long