Shotgun Metagenomic Profiles Have a High Capacity To Discriminate Samples of Activated Sludge According to Wastewater Type

Abstract

This study was conducted to investigate whether functions encoded in the metagenome could improve our ability to understand the link between microbial community structures and functions in activated sludge. By analyzing data sets from six industrial and six municipal wastewater treatment plants (WWTPs), covering different configurations, operational conditions, and geographic regions, we found that wastewater influent composition was an overriding factor shaping the metagenomic composition of the activated sludge samples. Community GC content profiles were conserved within treatment plants on a time scale of years and between treatment plants with similar influent wastewater types. Interestingly, GC contents of the represented phyla covaried with the average GC contents of the corresponding WWTP metagenome. This suggests that the factors influencing nucleotide composition act similarly across taxa and thus the variation in nucleotide contents is driven by environmental differences between WWTPs. While taxonomic richness and functional richness were correlated, shotgun metagenomics complemented taxon-based analyses in the task of classifying microbial communities involved in wastewater treatment systems. The observed taxonomic dissimilarity between full-scale WWTPs receiving influent types with varied compositions, as well as the inferred taxonomic and functional assignment of recovered genomes from each metagenome, were consistent with underlying differences in the abundance of distinctive sets of functional categories. These conclusions were robust with respect to plant configuration, operational and environmental conditions, and even differences in laboratory protocols. IMPORTANCEThis work contributes to the elucidation of drivers of microbial community assembly in wastewater treatment systems. Our results are significant because they provide clear evidence that bacterial communities in WWTPs assemble mainly according to influent wastewater characteristics. Differences in bacterial community structures between WWTPs were consistent with differences in the abundance of distinctive sets of functional categories, which were related to the metabolic potential that would be expected according to the source of the wastewater.

A novel culture-independent method to search unknown dominant bacterial groups and its application to microbial analysis of membrane bioreactors

“…2). Our other results, that the composition of overall classes was not changed between sampling periods, was also consistent with those by the other conventional techniques (29, 30) (Fig. 2).…”

“…Until now, most of the microbial research of CAS (18-22, 24-29, 31, 32), and MBR (23, 24, 30) has been focused on the exploration of microbial diversity using the conventional culture-independent molecular techniques with aim to cover almost all the low-abundance microorganisms. These approaches seemed to have targeted such bacterial groups as those that appeared as smeared bands in lower dilutions of DGGE profiles (Fig.…”

“…Most reports have focused mainly on the comparative study of overall microbial composition (23, 26-28, 32), and their changes in the reactor (29, 30). With respect to the well-known specific gene, or bacteria, their numbers were estimated by using real-time PCR (33-35), or by FISH (24, 25).…”

Improving Metagenomic Assemblies Through Data Partitioning: a GC content approach

“…The sludge sample was collected in a municipal sewage treatment plant located in Argentina [23]. This sample was split in two technical replicates and sequenced with the platform Illumina HiSeq 1500 in 150 bp short reads.…”

Tools for Metagenomic Analysis at Wastewater Treatment Plants: Application to a Foaming Episode

“…In either case, the nucleotide sequences of millions of DNA fragments are determined, and then computational analyses are used to identify and quantify all of the organisms (or genes) as long as they are found within already extensive and growing databases (Gilbert and DuPont, 2011;Vanwonterghem et al, 2014). MGA is developing in the academic realm as a powerful approach to gain insight into processes that are of fundamental interest to the WWTP community (Ibarbalz et al, 2016;Jiang, et al, 2016;Sharma et al, 2012;Shchegolkova, 2016;Yang, et al, 2014). Research has shown, for example, that reactor populations can vary over time, at least in part due to changes in climatic and operational conditions (Ju et al, 2014;Wang, 2016).…”