Urban wastewater bacterial communities assemble into seasonal steady states

Abstract

Background Microorganisms in urban sanitary sewers exhibit community properties that suggest sewers are a novel ecosystem. Sewer microorganisms present both an opportunity as a control point for wastewater treatment and a risk to human health. If treatment processes are to be improved and health risks quantified, then it is necessary to understand microbial distributions and dynamics within this community. Here, we use 16S rRNA gene sequencing to characterize raw influent wastewater bacterial communities in a 5-year time series from two wastewater treatment plants in Milwaukee, WI; influent wastewater from 77 treatment plants across the USA; and wastewater in 12 Milwaukee residential sewers. Results In Milwaukee, we find that in transit from residences to treatment plants, the human bacterial component of wastewater decreases in proportion and exhibits stochastic temporal variation. In contrast, the resident sewer community increases in abundance during transit and cycles seasonally according to changes in wastewater temperature. The result is a bacterial community that assembles into two distinct community states each year according to the extremes in wastewater temperature. Wastewater bacterial communities from other northern US cities follow temporal trends that mirror those in Milwaukee, but southern US cities have distinct community compositions and differ in their seasonal patterns. Conclusions Our findings provide evidence that environmental conditions associated with seasonal change and climatic differences related to geography predictably structure the bacterial communities residing in below-ground sewer pipes.

Human Fecal Contamination Corresponds to Changes in the Freshwater Bacterial Communities of a Large River Basin

“…To generate additional taxonomic assignments for typical freshwater organisms, TaxAss was used to assign ASVs to the FreshTrain database ( 58 , 67 ). For human fecal and sewer organisms, a custom database was used based on a combination of DNA sequencing data from the Human Microbiome Project ( 68 ) and a large data set of raw sewage samples from Milwaukee (see the supplemental material) ( 69 ). Assignment to the human fecal and sewer ASV database was performed using a custom script to identify exact alignments (as in reference 69 ) (see the supplemental material), and any ASVs that were previously assigned to the freshwater database were excluded.…”

“…For human fecal and sewer organisms, a custom database was used based on a combination of DNA sequencing data from the Human Microbiome Project ( 68 ) and a large data set of raw sewage samples from Milwaukee (see the supplemental material) ( 69 ). Assignment to the human fecal and sewer ASV database was performed using a custom script to identify exact alignments (as in reference 69 ) (see the supplemental material), and any ASVs that were previously assigned to the freshwater database were excluded. River sequences that aligned exactly to human fecal or sewer sequences in the custom database were considered probable human fecal or sewer sequences if the 5th-percentile relative abundance in river samples was lower than the 95th-percentile relative abundance in raw sewage.…”

Environmental and Human Microbiome for Health

“…The abundance of microorganisms varies depending upon whether they belong to agricultural and forest soil, wetlands, grass, and desert soils [ 12 ]. Apart from that, sewage as an indicator of the human microbiome can be used broadly to obtain an idea of the microbiome of humans residing in a particular area [ 13 , 14 , 15 ]. In addition, the diversity of human-associated microbial community would let one know about the presence of pathogenic microbes that cause immediate infectious diseases or are associated with chronic condition, which allow us to take timely actions [ 16 , 17 ].…”

Full-Length 16S rRNA Gene Sequences from Raw Sewage Samples Spanning Geographic and Seasonal Gradients in Conveyance Systems across the United States

“…To aid the characterization of wastewater microorganisms, 46 raw wastewater treatment plant (WWTP) influent samples underwent near-full-length 16S rRNA gene sequencing. We selected samples that, according to previous work, encompass microbial community variability across geographic and seasonal gradients ( 3 , 4 ). Raw influent (25-mL) samples were filtered onto 0.2-μm mixed cellulose ester filters (product number WHA10401770; MilliporeSigma), from which DNA was extracted with the FastDNA Spin kit for soil (product number 116560200-CF; MP Biomedicals) as described previously ( 3 , 4 ).…”

“…We selected samples that, according to previous work, encompass microbial community variability across geographic and seasonal gradients ( 3 , 4 ). Raw influent (25-mL) samples were filtered onto 0.2-μm mixed cellulose ester filters (product number WHA10401770; MilliporeSigma), from which DNA was extracted with the FastDNA Spin kit for soil (product number 116560200-CF; MP Biomedicals) as described previously ( 3 , 4 ). Genes were amplified using KAPA HiFi HotStart ReadyMix (product number KK2602; Roche) with the primers 27F (5′- AGRGTTYGATYMTGGCTCAG -3′) and 1492R (5′- RGYTACCTTGTTACGACTT ) under the following thermocycler conditions: 95°C for 5 min; 20 cycles of 98°C for 20 s, 55°C for 45 s, and 72°C for 3 min; and 72°C for 5 min.…”