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Record W4402076747 · doi:10.1101/2024.08.29.610350

Optimizing Plant Biofactories: Enhancing Recombinant Protein Production in <i>Nicotiana benthamiana</i> through Phytoplasma Effectors

2024· preprint· en· W4402076747 on OpenAlexaff
Md. Saifur Rahman

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNicotiana benthamianaRecombinant DNAEffectorPhytoplasmaBiologyVirologyBotanyCell biologyComputational biologyBiochemistryPolymerase chain reactionGeneVirus

Abstract

fetched live from OpenAlex

Abstract Molecular farming, which utilizes plants as biofactories for recombinant protein production, offers an innovative and cost-effective alternative to traditional expression systems. Despite its advantages, plant-based production faces challenges such as low transgene expression and protein instability. Recent studies have highlighted the potential of Nicotiana benthamiana axillary stem leaves to enhance protein yield. This study explored the development of N. benthamiana lines expressing TENGU without signal peptide (T-SP), a phytoplasma effector known to induce plant dwarfism and increase shoot growth. TENGU and other effectors, such as SAP05 and SAP11, were introduced to create phenotypic variations that favor recombinant protein production. This study aimed to optimize these transgenic lines for increased biomass and protein yields by leveraging vertical farming conditions for scalable production. The results demonstrated significant improvements in leaf number, biomass, and five times more soluble protein content in T-SP lines compared to control lines, suggesting a promising approach for efficient molecular farming.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.217
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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