Expression and Purification of Heat Shock Protein 65(HSP65) of Mycobacterium leprae and Preparation of Anti-HSP65 Polyclonal Antiserum
Bibliographic record
Abstract
Objective To express the heat shock protein 65(HSP65) of Mycobacterium leprae in prokaryotic cells,purify the expressed product and prepare anti-HSP65 polyclonal antiserum.Methods The hsp65 gene was amplified by PCR using plasmid pCMV4.65 carrying the target gene as a template,and cloned into vector pET-28a(+).The constructed recombinant plasmid pET-28a-hsp65 was transformed to E.coli BL21(DE3) for expression under induction of IPTG.The expressed product was purified by nickel ion affinity chromatography and used for immunization of BALB/c mice to prepare antiserum.The reactogenicity of recombinant HSP65 was analyzed by Western blot.Results Both restriction analysis and sequencing proved that recombinant plasmid pET-28a-hsp65 was constructed correctly.The expressed recombinant HSP65,with a relative molecular mass of about 65 000,contained about 30% of total somatic protein and mainly existed in a form of inclusion body.The purity and concentration of purified recombinant HSP65 were 95% and about 1.0 mg/ml respectively.The prepared anti-HSP65 antiserum reached a titer of 1 ∶ 12 800,and showed high reactogenicity.Conclusion The recombinant HSP65 of M.leprae was successfully expressed and purified,and anti-HSP65 polyclonal antiserum was prepared,which laid a foundation of further study on HSP65-based subunit vaccine and DNA vaccine.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".