A companion protease inhibitor for the protection of cytosol‐targeted recombinant proteins in plants
Bibliographic record
Abstract
We reported earlier the potential of tomato cathepsin D inhibitor (SlCDI) as an in-built stabilizing agent for the protection of recombinant proteins in transgenic plant leaf crude extracts (Plant Biotechnol J.4, 359-368). Here we document the potential of SlCDI for the in situ protection of proteins in potato leaves. Total protein assays with control and SlCDI-expressing potato lines indicated a positive impact of slcdi transgene expression on leaf protein content, with a mean relative increase of 35%-40% depending on the light regime. Out of approximately 700 proteins detected on 2-D gels, only 20 exhibited a significantly altered level on a protein-specific basis, whereas most proteins were up-regulated on a leaf fresh weight basis, albeit at variable rates. Quantitative reverse trancriptase-PCR assays for rubisco activase showed similar transcript levels in leaves of test and control lines despite protein levels increased by two- to threefold in SlCDI-expressing lines. These observations, along with the unrelated biological functions assigned to MS-identified proteins up-regulated in leaves and protease assays showing slightly increased proteasome activity in protein extracts of SlCDI-expressing lines, suggest a general, proteasome-independent protein stabilizing effect of SlCDI in planta. Transient expression assays with human alpha(1)-antichymotrypsin also showed a stabilizing effect for SlCDI on heterologous proteins, leading to net levels of the human protein increased by approximately 2.5-fold in SlCDI-expressing plants. These data illustrate, overall, the potential of SlCDI as an in vivo protein-stabilizing agent in transgenic plant systems, useful to improve protein levels and recombinant protein accumulation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".