Illumina sequencing for the identification of filamentous bulking and foaming bacteria in industrial activated sludge plants

Abstract

In this study, Illumina sequencing was used for the identification of bulking and foaming bacteria in industrial wastewater treatment plants. The reliable identification of bulking and foaming bacteria represents the first step in developing effective and specific control strategies to avoid disturbances in activated sludge systems. Illumina sequencing revealed 432 16S rRNA operational taxonomic units, representing phylotypes and including 21 bulking and foaming bacteria in the two investigated industrial wastewater treatment plants. Foaming represents the most severe problem in the cascade biology system. Up to 22.5% of all sequencing reads are bulking and foaming bacteria, including Chryseobacterium, Candidatus Microthrix parvicella and Gordonia sp. as the dominant bulking and foaming bacteria which are known for foam formation. Moreover, Illumina sequencing revealed an increase in Candidatus Microthrix parvicella and Gordonia sp. reads from activated sludge to foam and scum samples, indicating a preferred flotation and/or growth advantages in the foam and scum layers. Analyses of the taxonomic assignment and distribution showed that the phylum Actinobacteria is the most dominant phylum, underlining the key role of Actinobacteria in bulking and foaming. Multivariate data analysis was applied, revealing that the dominant bulking and foaming bacteria are positively correlated with the sludge age and influent flow and negatively correlated with the dissolved oxygen level and the temperature. In terms of developing a specific control strategy, the positive linear relationships to the fatty acid and surfactant sludge loadings are highlighted and the removal of lipid compounds from the wastewater influent could avoid an overgrowth of bulking and foaming bacteria. Keywords CandidatusMicrothrix parvicella Á Filamentous bacteria Á Filamentous foaming Á Illumina sequencing Á Next-generation sequencing Á Industrial activated sludge plants Editorial responsibility: BV Thomas.

Bacteriophages in Natural and Artificial Environments

“…Clarification of what impacts phages in activated sludge might have raised the question of whether they might provide a specific environmental control method for the problematic bacteria found in activated sludge [112]. Proliferation of some bacterial members can lead to the severe global operational problems of bulking and foaming caused mainly by filamentous bacteria [113,114,115], for which few effective treatment options exist [116]. The idea is to reduce the population levels of these below the threshold needed to sustain a bulking or a foaming event.…”

The Phylogeny, Biodiversity, and Ecology of the Chloroflexi in Activated Sludge

“…Almost all have been carried out in China, and so similar data from plants in other countries are lacking. One exception is the report of Dunkel et al (2018), who used this approach to look at the 21 filamentous bacteria, including several Chloroflexi morphotypes, in two bulking and foaming German industrial treatment plants over a 3 month period. However, they did not take advantage of the MiDAS database for their filament identifications, instead using the less reliable filament database of Guo and Zhang (2012).…”

“…They and others e.g. (Yang et al, 2017) have applied their data to suggest the operating factors thought to support the increased abundances of many of these filament clades (Dunkel et al, 2018), but generally these add little to what is known already.…”

Recent advances in understanding the ecology of the filamentous bacteria responsible for activated sludge bulking

“…Amarolinea' was then confirmed as being filamentous after FISH analysis (Nierychlo et al 2020b). Filament Biogeography-global/national occurrence of bulking filaments 16S rRNA amplicon sequencing has been applied to analyse bulking full-scale activated sludge communities in Australia (Petrovski et al 2020), China including Hong Kong (Guo and Zhang 2012;Jiang et al 2016;Wang et al 2016;Yang et al 2017;Zhang et al 2019), Denmark (Nierychlo et al 2020b), Germany (Dunkel et al 2018), Japan , Singapore (Guo and Zhang 2012), and United States (Guo and Zhang 2012), usually where plant samples are collected regularly (each week) from the same plant at regular intervals, and populations identified using appropriate data bases. Of these, the MiDAS version 2/3 database (designed especially for wastewater plant communities (McIlroy et al 2017;Nierychlo et al 2020a) is now the preferred choice.…”