Metaproteome analysis to determine the metabolically active part of a thermophilic microbial community producing biogas from agricultural biomass
Bibliographic record
Abstract
Complex consortia of microorganisms are responsible for biogas production. A lot of information about the taxonomic structure and enzymatic potential of such communities has been collected by a variety of gene-based approaches, yet little is known about which of all the assumable metabolic pathways are active throughout the process of biogas formation. To tackle this problem, we established a protocol for the metaproteomic analysis of samples taken from biogas reactors fed with agricultural biomass. In contrast to previous studies where an anaerobic digester was fed with synthetic wastewater, the complex matrix in this study required the extraction of proteins with liquid phenol and the application of paper bridge loading for 2-dimensional gel electrophoresis. Proteins were subjected to nanoHPLC (high-performance liquid chromatography) coupled to tandem mass spectrometry for characterization. Several housekeeping proteins as well as methanogenesis-related enzymes were identified by a MASCOT search and de novo sequencing, which proved the feasibility of our approach. The establishment of such an approach is the basis for further metaproteomic studies of biogas-producing communities. In particular, the apparent status of metabolic activities within the communities can be monitored. The knowledge collected from such experiments could lead to further improvements of biogas production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".