New Insights into Chitosan−DNA Interactions Using Isothermal Titration Microcalorimetry
Bibliographic record
Abstract
The interaction of chitosan with plasmid DNA was investigated as a function of pH, buffer composition, degree of deacetylation (DDA), and molecular weight (M(n)) of chitosan, using isothermal titration microcalorimetry (ITC). The Single Set of Identical Sites model was used to obtain the enthalpy of interaction, the binding constant, and the stoichiometry of binding. The chitosan-DNA interaction was shown to be coupled with proton transfer from the buffer to chitosan, as revealed by the dependence of the measured heat release on the ionization enthalpy of the buffer. The measured enthalpy of binding was almost entirely due to proton transfer, because it was accounted for by the enthalpy of ionization of the buffer and of chitosan once the number of protons transferred was calculated. This proton transfer during binding resulted in the protonation of an additional 17, 37, and 58% of total glucosamine units at pH 5.5, 6.5, and 7.4, respectively. The strong polyanionic nature of DNA facilitates the ionization of glucosamines of chitosan upon complexation and is responsible for proton transfer. Interestingly, using the chitosan-DNA stoichiometry provided by ITC and the calculated degree of ionization of chitosan in the complex, the charge ratio of protonated amines to negative phosphate groups in the complex was nearly constant at 0.50-0.75 after saturation and was independent of the pH, buffer type and chitosan molecular characteristics. The chitosan-DNA binding constant was in the range of 10(9)-10(10) M(-1). The binding constant was pH-dependent and was greater at lower pH due to increased electrostatic attraction to DNA when chitosan is highly charged. Furthermore, the DDA and molecular weight of chitosan exerted a great influence on binding affinity which increased by almost an order of magnitude with an increase of the latter from 7 to 153 kDa. The binding affinity did not change significantly with DDA from 72 to 80% when the M(n) was kept constant near 80 kDa, but it increased substantially with DDA from 80 to 93% to reach a value similar to that obtained with chitosan of M(n) = 153 kDa and 80% DDA. These results provide insight into the previously reported dependence of the transfection efficiency of DNA/chitosan complexes on chitosan DDA and molecular weight, where complex stability and chitosan-DNA binding strength play a critical role.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".