Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity.

Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.

Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process.

BACKGROUND: Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters. RESULTS: This study quantified microbial immigration from an upstream full-scale anaerobic reactor to downstream activated sludge reactors. A mass balance was applied to 16S rRNA gene amplicon sequencing data to calculate the net growth rates of individual populations in the activated sludge reactors. Among the 1178 observed operational taxonomic units (OTUs), 582 had a positive growth rate, including all the populations with abundance > 0.1%. These active populations collectively accounted for 99% of the total sequences in activated sludge. The remaining 596 OTUs with a growth rate ≤ 0 were classified as inactive populations. All the abundant populations in the upstream anaerobic reactor were inactive in the activated sludge process, indicating a negligible immigration impact. We used a supervised learning regressor to predict environmental parameters based on community composition and compared the prediction accuracy based on either the entire community or the active populations. Temperature was the most predictable parameter, and the prediction accuracy was improved when only active populations were used to train the regressor. CONCLUSIONS: Calculating growth rate of individual microbial populations in the downstream system provides an effective approach to determine microbial activity and quantify immigration impact. For the studied biological process, a marginal immigration impact was observed, likely due to the significant differences in the growth environments between the upstream and downstream processes. Excluding inactive populations as a result of immigration further enhanced the prediction of key environmental parameters affecting process performance.

Integrated methodological approach reveals microbial diversity and functions in aerobic groundwater microcosms adapted to vinyl chloride.

Vinyl chloride (VC), a known human carcinogen, is often formed in groundwater (GW) by incomplete reductive dechlorination of chlorinated ethenes. An integrated microbial ecology approach involving bacterial enrichments and isolations, carbon stable-isotope probing (SIP) and metagenome and genome sequencing was applied to ethene-fed GW microcosms that rapidly transitioned to aerobic growth on VC. Actinobacteria, Proteobacteria and Bacteroidetes dominated the microbial communities in ethene- and VC-grown cultures. SIP with 13C2-VC demonstrated that Nocardioides spp. significantly participated in carbon uptake from VC (52.1%-75.7% enriched in heavy fractions). Sediminibacterium, Pedobacter and Pseudomonas spp. also incorporated 13C from VC into genomic DNA. Ethene- and VC-assimilating Nocardioides sp. strain XL1 was isolated. Sequencing revealed a large (∼300 kbp) plasmid harboring genes encoding alkene monooxygenase and epoxyalkane: coenzyme M transferase, enzymes known to participate in aerobic VC and ethene biodegradation. The plasmid was 100% identical to pNOCA01 found in VC-assimilating Nocardioides sp. strain JS614. Metagenomic analysis of enrichment cultures indicated other bacteria implicated in carbon uptake from VC possessed the genetic potential to detoxify epoxides via epoxide hydrolase or glutathione S-transferase (Pseudomonas) and/or metabolize VC epoxide breakdown products and downstream VC metabolites. This study provides new functional insights into aerobic VC metabolism within a GW microbial community.