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 originating from these practices such as Shiga Toxin-producing Escherichia coli (STEC) 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 nine-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and comparable to the functional and taxonomic diversity observed in soils. With our sequencing effort (~4Gbp 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. Further, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream, impacted sites compared to upstream, more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, a high number of metagenomic reads carrying antibiotic resistance genes (ARGs) was found in all samples that was significantly higher compared to 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 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 water-borne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health is assessed by culture-based tests for the intestinal bacterium, E. 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 remains unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the U.S. in order to assess how agricultural runoff affects the native microbial communities and if the presence of 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.

对于天然小溪沉积物相关的公共健康风险知之甚少，天然小溪沉积物受到农业和畜牧业的径流和粪便污染的影响。例如，源自这些做法的食源性病原体（例如产生志贺毒素的大肠杆菌（STEC））的持久性仍然很难量化。为了弥合这些知识鸿沟，我们使用宏基因组学和基于传统文化的STEC测试，在9个月的时间内对加利福尼亚州萨利纳斯河谷的两条小河的水-沉积物界面进行了采样。我们的研究结果表明，这些沉积物群落极为多样，可与土壤中观察到的功能和分类学多样性相媲美。通过我们的测序工作（每个文库〜4Gbp），我们无法检测到任何病原体大肠杆菌使用基于培养的方法测试为阳性的11个样本的基因组中的“基因组”显然是由于相对较低的丰度。此外，与上游，更多原始（对照）位点相比，下游受影响位点的人或牛特异性肠道微生物组序列的丰度没有显着差异，表明人为输入的自然稀释。值得注意的是，在所有样品中均发现大量带有抗生素抗性基因（ARG）的宏基因组读物，其显着高于其他可用淡水和土壤元基因组中的ARG读物，这表明这些群落可能是ARGs的天然储集层。此处介绍的工作应作为样本量，要应用的测序量，

重要信息当前的农业和畜牧业做法导致环境中的粪便污染以及食物和水传播疾病以及抗生素抗性基因（ARG）的传播。传统上，污染程度和对公共健康的风险是通过对肠道细菌大肠杆菌进行基于培养的测试来评估的。但是，这些传统方法的准确性（例如，定量准确性低，以及基于PCR的假阳性信号）及其对沉积物的适用性仍不清楚。我们从美国生产力最高的农业地区之一收集了沉积物，进行了时间序列宏基因组学研究，以评估农业径流如何影响原生微生物群落，以及是否可以通过测序直接检测出沉积物中的STEC是否存在。我们的研究提供了有关使用宏基因组学作为评估自然环境中公共健康风险的工具的潜力的重要信息。