Using DNA-Binding Proteins as an Analytical Tool
Bibliographic record
Abstract
We propose that DNA-binding proteins can be used as highly efficient and versatile tools in analyses of DNA, RNA, and proteins. This work reports assays applying specific affinity probes: hybridization probes for analyses of DNA and RNA, and aptamer probes for analyses of proteins. Both types of probes are single-stranded DNA. In affinity analyses, in general, the probe (P) binds to a target molecule (T), and the amounts of the probe-target complex (P.T) and unbound P are determined. Distinguishing between P and P.T can be achieved by electrophoretic separation. If the electrophoretic mobilities of P and P.T are close in gel-free media, which is always the case for hybridization analyses, separation typically requires the use of a sieving matrix. Here we utilized a single-stranded DNA binding protein (SSB) to facilitate highly efficient gel-free separation of P and P.T in capillary electrophoresis (CE) for three types of targets: DNA, RNA, and proteins. When present in the CE run buffer, SSB binds differently to P and P.T. Due to this selective binding, SSB induces difference in electrophoretic mobilities of P and P.T in an SSB concentration-dependent fashion. The difference in the electrophoretic mobilities allows for affinity analyses of DNA, RNA, and proteins in gel-free CE. The large number of well-characterized DNA- and RNA-binding proteins and the diversity of their properties will allow researchers to design a comprehensive tool set for quantitative analyses of DNA, RNA, and proteins. Such analyses will facilitate identification of genomic DNA in ultra-small samples without error-prone and time-consuming PCR. They can also be used for monitoring gene expression at both mRNA and protein levels.
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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 | 0.001 |
| 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".