Cellulase catalysis on cell surfaces using Caulobacter S-layer display
Bibliographic record
Abstract
Abstract Sustainable bioprocesses for energy and materials production and waste resource recovery are needed to support circular economic development. Enzyme surface display on cells or functionalized materials has emerged as a promising paradigm for sustainable bioprocess innovation. Surface (S)-layers are geometric, monomolecular, highly stable crystalline protein lattices encasing the outside of many bacteria and archaea. Several S-layer genes have been shown to tolerate heterologous insertions, thereby enabling high-density display of peptides of interest on cell surfaces without additional costly immobilisation or conjugation steps. Here, we employ an S-layer display platform in Caulobacter vibrioides CB2A JS4038 to express functional cellulases up to 445 amino acids in length. We explore critical design considerations needed for successful catalytic display and demonstrate synergistic activities between differentially expressed cellulases relevant to combinatorial lignocellulosic biomass conversion. Functionalised S-layers capable of transforming lignocellulosic biomass could have useful applications in engineering whole-cell biocatalysts and synthetic microbial consortia tuned for different bioprocess applications.
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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 | 0.001 | 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".