Hemoglobin binding protein from «Actinobacillus pleuropneumoniae»: a novel method for extraction and isolation
Bibliographic record
Abstract
Membrane proteins (MPs) are the coveted, yet elusive, targets of structural genomics, structural proteomics, and the pharmaceutical industry. Characterized by amphiphilic surfaces, and lipid stabilized in vivo, MPs require unique combinations of detergent and additives for solubility and stability in vitro. We sought to bypass the exhaustive, and often unsuccessful exploration of detergents and additives for our target hemoglobin binding protein (HgbA): a 105 kDa, 22-stranded ß-barrel outer membrane protein (OMP) from Actinobacillus pleuropneumoniae. To address requirements of structural studies for milligram amounts of soluble target protein, a novel series of fractionating steps was developed to extract and isolate soluble HgbA. Two well established OMP properties were exploited in this pursuit: sarkosyl-insolubility and a robust structural architecture. Total membrane solubilization by sarkosyl detergent was modified for efficiency and fractionated insoluble OMPs from cytoplasmic membrane and soluble cytoplasmic proteins. Liberation of HgbA from the insoluble fraction required treatments more aggressive than variations of detergent and additives. Rigidified with extensive hydrogen bonding, the structural tolerance of ß-barrel proteins was exploited against elevated temperatures. Heat treatment of insoluble OMP fractions at 55 oC preferentially solubilized HgbA yielding 5mg HgbA per litre culture that retained its ability to bind hemoglobin. Protein profiles of these extraction products resolved one major band representing excess amounts of HgbA in the presence of limited quantities of minor species. This extraction protocol produces high quality HgbA that is markedly enriched from fractions that are otherwise inaccessible. Such preparations are advantageous for structural studies as well as promising for application to other ß-barrel proteins.
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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 | 0.001 |
| 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 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".