Disentangling the Drivers of Diversity and Distribution of Fungal Community Composition in Wastewater Treatment Plants Across Spatial Scales

Abstract

Activated sludge microbial community composition is a key bio-indicator of the sustainability of wastewater treatment systems. Therefore, a thorough understanding of the activated sludge microbial community dynamics is critical for environmental engineers to effectively manage the wastewater treatment plants (WWTPs). However, fungal communities associated with activated sludge have been poorly elucidated. Here, the activated sludge fungal community in 18 geographically distributed WWTPs was determined by using Illumina sequencing. The results showed that differences in activated sludge fungal community composition were observed among all WWTPs and also between oxidation ditch and anaerobic-anoxic-aerobic (A/A/O) systems. Ascomycota was the largest phyla, followed by Basidiomycota in all samples. Sporidiobolales and Pezizales were the most abundant order in oxidation ditch and A/A/O systems, respectively. The network analysis indicated cooperative and co-occurrence interactions between fungal taxa in order to accomplish the wastewater treatment process. Hygrocybe sp., Sporobolomyces sp., Rhodotorula sp., Stemphylium sp., Parascedosporium sp., and Cylindrocarpon sp., were found to have statistically significant interactions. Redundancy analysis revealed that temperature, total phosphorus, pH, and ammonia nitrogen were significantly affected the fungal community. This study sheds light on providing the ecological characteristics of activated sludge fungal communities and useful guidance for improving wastewater treatment performance efficiency.

Chromium (VI) bioremediation potential of filamentous fungi isolated from Peruvian tannery industry effluents

“…(P3-01), and Trichoderma viride (P1-01). Several studies [16][17][18] show that filamentous fungi from the phylum Ascomycota are common in mycoflora in industrial effluents. The growth capacity of fungal strains at different chromium (VI) concentrations was evaluated in solid medium ( Fig.…”

Mold and Yeast-Like Fungi in the Seaside Air of the Gulf of Gdańsk (Southern Baltic) after an Emergency Disposal of Raw Sewage

“…Therefore, the outcomes of 2018 were compared to the quality of air at the sewage treatment plant in order to indicate the likely origin of the species. Filamentous fungi of the genus Aspergillus , Cladosporium, and Mucor and yeast-like fungi, for example, Candida, were detected in domestic human and animal sewage [ 35 , 36 , 37 , 38 ]. Michałkiewicz et al found that the majority of yeast-like fungi isolated from the air of the four wastewater treatment plants was Candida [ 39 ].…”

Deciphering microbial diversity associated with Fusarium wilt-diseased and disease-free banana rhizosphere soil

“…Raw sequence files were demultiplexed, quality-filtered by Trimmomatic and merged by FLASH with the following criteria: (i) these reads were truncated at any site with an average quality score < 20 over a 50-bp sliding window; (ii) primers were exactly matched allowing a 2-nucleotide mismatch, and reads containing ambiguous bases were removed; (iii) sequences with an overlap longer than 10 bp were merged according to their overlapping sequences [60]. After quality filtering and chimera removal, rarefaction curves were plotted to determine the abundance of the communities and sequencing data for each sample [59, 61].…”

“…After quality filtering and chimera removal, rarefaction curves were plotted to determine the abundance of the communities and sequencing data for each sample [59, 61]. The abundance-based coverage estimator (ACE) index, Chao richness estimator (Chao1), Shannon diversity (H) and Simpson diversity (1/D) indices were calculated using the MOTHUR package (version 1.22.2 http://www.mothur.org) with Operational Taxonomic Units (OTUs) at 0.97 level [60, 61]. OTUs were clustered with a 97% similarity cutoff using UPARSE (version 7.1 http://drive5.com/uparse/), and chimeric sequences were identified and removed using the UCHIME software [61, 62].…”