Phosphate-regulated expression of the SARS-CoV-2 receptor-binding domain in the diatom Phaeodactylum tricornutum for pandemic diagnostics
Bibliographic record
Abstract
The worldwide COVID-19 pandemic caused by the SARS-CoV-2 betacoronavirus has highlighted the need for a synthetic biology approach to create reliable and scalable sources of viral antigen for uses in diagnostics, therapeutics and basic biomedical research. Here, we adapt plasmid-based systems in the eukaryotic microalgae Phaeodactylum tricornutum to develop an inducible overexpression system for SARS-CoV-2 proteins. Limiting phosphate and iron in growth media induced expression of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein from the P. tricornutum HASP1 promoter in the wild-type strain and in a histidine auxotrophic strain that alleviates the requirement for antibiotic selection of expression plasmids. The RBD was purified from whole cell extracts (algae-RBD) with yield compromised by the finding that 90-95% of expressed RBD lacked the genetically encoded C-terminal 6X-histidine tag. Constructs that lacked the TEV protease site between the RBD and C-terminal 6X-histidine tag retained the tag, increasing yield. Purified algae-RBD was found to be N-linked glycosylated by treatment with endoglycosidases, was cross-reactive with anti-RBD polyclonal antibodies, and inhibited binding of recombinant RBD purified from mammalian cell lines to the human ACE2 receptor. We also show that the algae-RBD can be used in a lateral flow assay device to detect SARS-CoV-2 specific IgG antibodies from donor serum at sensitivity equivalent to assays performed with RBD made in mammalian cell lines. Our study shows that P. tricornutum is a scalable system with minimal biocontainment requirements for the inducible production of SARS-CoV-2 or other coronavirus antigens for pandemic diagnostics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".