Expression and Purification of Chemokine MIP-3α (CCL20) through a Calmodulin-Fusion Protein System
Bibliographic record
Abstract
Human macrophage inflammatory protein 3α (MIP-3α), also known as CCL20, is a 70 amino acid chemokine that selectively binds and activates chemokine receptor 6 (CCR6). This chemokine is responsible for inducing the migration of immature dendritic cells, effector, or memory T-cells, and B-cells. Moreover, the MIP-3α protein has been shown to display direct antimicrobial, antiviral and antiprotozoal activities. Because of the potential therapeutic uses of this protein, the efficient production of MIP-3α is of great interest. However, bacterial recombinant production of the MIP-3α protein has been limited by the toxicity of this extremely basic protein (pI 9.7) toward prokaryotic cells, and by solubility problems during expression and purification. In an attempt to overcome these issues, we have investigated the bacterial recombinant expression of MIP-3α by using several common expression and fusion tags, including 6× histidine (His), small ubiquitin modifier protein (SUMO), thioredoxin (TRX), ketosteroid isomerase (KSI), and maltose binding protein (MBP). We have also evaluated a recently introduced calmodulin (CaM)-tag that has been used for the effective expression of many basic antimicrobial peptides (AMPs). Here, we show that the CaM fusion tag system effectively expressed soluble MIP-3α in the cytoplasm of Escherichia coli with good yields. Rapid purification was facilitated by the His-tag that was integrated in the CaM-fusion protein system. Multidimensional nuclear magnetic resonance (NMR) studies demonstrated that the recombinant protein was properly folded, with the correct formation of disulfide bonds. In addition, the recombinant MIP-3α had antibacterial activity, and was shown to inhibit the formation of Pseudomonas aeruginosa biofilms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".