Selection and engineering of anti-PaNie VHH single domain antibodies and their fusion to cellulose binding modules
Bibliographic record
Abstract
Plant pathogens from the genera 'Pythium, Phytophthora ' and 'Fusarium' are responsible for 80% of root disease epidemics in hydroponic greenhouses worldwide. Many of these pathogens secrete virulence factors belonging to the Nep1-Like-Protein (NLP) family of necrosis-inducing proteins. This thesis describes the development of a platform, consisting of antibody-cellulose binding modules bound to cellulose, for combating epidemics of plants through the capture of PaNie (NLPPya) secreted by ' Pythium aphanidermatum'. Four recombinant single domain antibodies (VHHs) with affinities to PaNie ranging from 800 nM to 20.2 M were developed by selection from a nai?ve ribosome display library and a hyperimmune phage display library. Three of these antibodies bind to a synthesized peptide containing the highly conserved NPP1 domain of the NLP family. All four antibodies have varied complementarity determining regions and framework regions representing three of the four VHH subfamilies. The genes of the three highest affinity VHHs were fused to a cellulose binding module (CBM) with an intervening thrombin cleavage site. All VHH-CBM fusions were functional and the highest affinity binder P10-CBM was analysed in more detail. P10-CBM could be purified directly from culture using cellulose beads and cleaved with thrombin to yield fully functional P10 VHH. P10-CBM was bound to paper to create a bioactive filter paper for the capture of PaNie. The data obtained suggest that the affinity of paper-bound P10-CBM is the same as for soluble P10-CBM. P10-CBM is also able to bind PaNie while attached to the cellulose surfaces of tobacco roots as shown by confocal laser scanning microscopy. Improvements of the affinity of the VHH-CBM-based platforms and the utility of the antibodies for the elucidation of NLP-associated disease are discussed. Features of PaNie and the VHH-PaNie interaction suggest that NLPs may be pore forming toxins. In the future, VHH-CBMs could be produced 'in situ' by non-pathogenic biocontrol agents and may be used to remove pathogenic toxins from hydroponic systems used in greenhouses and space-based advanced life support systems.
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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 | 0.000 | 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".