Tetrabutylphosphonium Bromide Reduces Size and Polydispersity Index of Tat2:siRNA Nano-Complexes for Triticale RNAi
Bibliographic record
Abstract
Cell-penetrating peptides (CPPs) are short 8-30 amino-acid oligopeptides that act as effective transducers of macromolecular cargo, particularly nucleic acids. They have been implemented in delivering dsDNA, ssDNA and dsRNA into animal and plant cells. CPPs and nucleic acids form nano-complexes that are often 100-300 nm in size but still effectively transit the cell membrane of animal cells, but are less effective with plant cells due to the plant cell wall. To overcome this obstacle, nano-complexes of the CPP Tat2 and various lengths of nucleic acid (21-mer siRNA duplex (dsRNA) to ~5.5 kb circular plasmid) were evaluated for size using dynamic light scattering (DLS), under conditions of increasing ionic strength (Ic) and addition of phase transfer catalyst salts (tetrabutylammonium bromide-TBAB and tetrabutylphosphonium bromide-TBPB) and sugars (maltose-mannitol solution). It was found that the combination of 21-mer siRNA:Tat2 complexes with TBPB produced small 10-20 nm diameter nano-complexes with a polydispersity index (PDI) of ~0.1. Furthermore, it was found that for each length of nucleic acid that a linear mathematical relationship existed between the theoretical volume of the nano-complex and the nucleic acid length. Next, nano-complex formulation was tested for its ability to carry small interfering RNA molecules into plant cells and to trigger silencing of phytoene desaturase (PDS) in Triticale leaves. RT-qPCR showed 75% suppression of PDS, demonstrating that TBPB acts as an adjuvant in effecting the entry and efficacy of siRNA in young Triticale plants.
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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 | 0.000 | 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".