Metagenomic and metatranscriptomic analysis of microbial community structure and gene expression of activated sludge

Abstract

The present study applied both metagenomic and metatranscriptomic approaches to characterize microbial structure and gene expression of an activated sludge community from a municipal wastewater treatment plant in Hong Kong. DNA and cDNA were sequenced by Illumina Hi-seq2000 at a depth of 2.4 Gbp. Taxonomic analysis by MG-RAST showed bacteria were dominant in both DNA and cDNA datasets. The taxonomic profile obtained by BLAST against SILVA SSUref database and annotation by MEGAN showed that activated sludge was dominated by Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Verrucomicrobia phyla in both DNA and cDNA datasets. Global gene expression annotation based on KEGG metabolism pathway displayed slight disagreement between the DNA and cDNA datasets. Further gene expression annotation focusing on nitrogen removal revealed that denitrification-related genes sequences dominated in both DNA and cDNA datasets, while nitrifying genes were also expressed in relative high levels. Specially, ammonia monooxygenase and hydroxylamine oxidase demonstrated the high cDNA/DNA ratios in the present study, indicating strong nitrification activity. Enzyme subunits gene sequences annotation discovered that subunits of ammonia monooxygenase (amoA, amoB, amoC) and hydroxylamine oxygenase had higher expression levels compared with subunits of the other enzymes genes. Taxonomic profiles of selected enzymes (ammonia monooxygenase and hydroxylamine oxygenase) showed that ammonia-oxidizing bacteria present mainly belonged to Nitrosomonas and Nitrosospira species and no ammonia-oxidizing Archaea sequences were detected in both DNA and cDNA datasets.

Figure 1. Combined taxonomic domain information of DNA and cDNA datasets.

Total DNA sequences and cDNA sequences were assigned to Bacteria, Eukaryota, Archaea, viruses, and other sequences.

Figure 2. Microbial community composition assessed by taxonomic classification of metagenomic and metatranscriptomic datasets.

SSU and LSU rDNA reads, and protein coding DNA reads from metagenomic dataset as well as those reads from metatranscriptomic datasets identified as SSU rRNA, LSU rRNA, and mRNA. Only taxonomic groups that represented >1% of total reads in at least one dataset were included.

Figure 3. Gene expression classification based on automated SEED subsystem in MG-RAST.

Total six datasets were annotated by Level 1 subsystems.

Figure 4. Nitrogen metabolism classification analysis based on level 2 SEED subsystems.

Six datasets have been analyzed.

Figure 5. Functional genes and their expression levels in nitrification, denitrification, ammonification, and nitrogen fixation processes.

Figure 6. Community abundance of enzymes sequences in ammonification, denitrification, nitrification, and nitrogen fixation (ammonia monooxygenase, hydroxylamine reductase, hydroxylamine oxidase, nitrate reductase, nitric oxide reductase, nitrite reductase, nitrous oxide reductase, and nitrogenase).

Figure 7. Community abundance of enzymes subunits associated with ammonification, denitrification, nitrification, and nitrogen fixation.

Figure 8. Functional microorganisms in denitrification, nitrogen fixation, as well as nitrification processes.

37 genera of bacteria, containing sequences at least one of the coding sequences of ammonia monooxygenase, hydroxylamine reductase, hydroxylamine oxidase, nitric oxide reductase, and nitrous oxide reductase, were displayed with genus information.