Global View of the <i>Clostridium thermocellum</i> Cellulosome Revealed by Quantitative Proteomic Analysis
Bibliographic record
Abstract
A metabolic isotope-labeling strategy was used in conjunction with nano-liquid chromatography-electrospray ionization mass spectrometry peptide sequencing to assess quantitative alterations in the expression patterns of subunits within cellulosomes of the cellulolytic bacterium Clostridium thermocellum, grown on either cellulose or cellobiose. In total, 41 cellulosomal proteins were detected, including 36 type I dockerin-containing proteins, which count among them all but three of the known docking components and 16 new subunits. All differential expression data were normalized to the scaffoldin CipA such that protein per cellulosome was compared for growth between the two substrates. Proteins that exhibited higher expression in cellulosomes from cellulose-grown cells than in cellobiose-grown cells were the cell surface anchor protein OlpB, exoglucanases CelS and CelK, and the glycoside hydrolase family 9 (GH9) endoglucanase CelJ. Conversely, lower expression in cellulosomes from cells grown on cellulose than on cellobiose was observed for the GH8 endoglucanase CelA; GH5 endoglucanases CelB, CelE, CelG; and hemicellulases XynA, XynC, XynZ, and XghA. GH9 cellulases were the most abundant group of enzymes per CipA when cells were grown on cellulose, while hemicellulases were the most abundant group on cellobiose. The results support the existing theory that expression of scaffoldin-related proteins is coordinately regulated by a catabolite repression type of mechanism, as well as the prior observation that xylanase expression is subject to a growth rate-independent type of regulation. However, concerning transcriptional control of cellulases, which had also been previously shown to be subject to catabolite repression, a novel distinction was observed with respect to endoglucanases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".