Project description:Two parallel anaerobic digestion lines were designed to match a "bovid-like" digestive structure. Each of the lines consisted of two Continuous Stirred Tank Reactors placed in series and separated by an acidic treatment step. The first line was inoculated with industrial inocula whereas the second was seeded with cow digestive tract contents. After three month of continuous sewage sludge feeding, samples were recovered for shotgun metaproteomic and DNA-based analysis. Strikingly, protein inferred and 16S rDNA tags based taxonomic community profiles were not fully consistent. Principal Component analysis however revealed a similar clustering pattern of the samples, suggesting that reproducible methodological and/or biological factors underlie this observation. The performances of the two digestion lines did not differ significantly and the cow derived inocula did not establish in the reactors. A low throughput metagenomic dataset (3.4x106 reads, 1.1 Gb) was also generated for one of the samples. It allowed a substantial increase of the analysis depth (increase of the spectral identification rate). For the first time, a high level of proteins expressed by members of the "Candidatus Competibacter" group is reported in an anaerobic digester, a key microbial player in environmental bioprocess communities.
Project description:<p>The impact of ammonia on anaerobic digestion performance and microbial dynamics has been extensively studied, but the concurrent effect of anions brought by ammonium salt should not be neglected. This paper studied this effect using metabolomics and a time-course statistical framework. Metabolomics provides novel perspectives to study microbial processes and facilitates a more profound understanding at the metabolic level. The advanced statistical framework enables deciphering the complexity of large metabolomics data sets. More specifically, a series of lab-scale batch reactors were set up with different ammonia sources added. Samples of 9 time points over the degradation were analyzed with liquid chromatography-mass spectrometry. A filtering procedure was applied to select the promising metabolomic peaks from 1262 peaks, followed by modeling their intensities across time. The metabolomic peaks with similar time profiles were clustered, evidencing the correlation of different biological processes. Differential analysis was performed to seek the differences in metabolite dynamics caused by different anions. Finally, tandem mass spectrometry and metabolite annotation provided further information on the molecular structure and possible metabolic pathways. For example, the consumption of 5-aminovaleric acid, a short-chain fatty acid obtained from l-lysine degradation, was slowed down by phosphates. Overall, by investigating the effect of anions on anaerobic digestion, our study demonstrated the effectiveness of metabolomics in providing detailed information in a set of samples from different experimental conditions. With the statistical framework, the approach enables capturing subtle differences in metabolite dynamics between samples while accounting for the differences caused by time variations.</p>