Comprehensive Proteomic Study Identifies Serpin and Cystatin Antiproteases as Novel Correlates of HIV-1 Resistance in the Cervicovaginal Mucosa of Female Sex Workers
Bibliographic record
Abstract
Not all individuals exposed to HIV-1 become infected, and evidence from HIV-1 highly exposed seronegative women (HIV-1-resistant) suggests that mucosal factors in the female genital tract, the first site of contact for the virus, are playing a role. To better understand factors mediating protection from HIV-1, we performed a large clinical study using the tools of systems biology to fully characterize the cervicovaginal mucosa proteome in HIV-1-resistant women. Cervicovaginal lavage fluid was collected from 293 HIV-1-resistant, uninfected, and infected sex workers and analyzed by 2D-LC LTQ-FT-MS. Of the more than 360 unique proteins identified, 41 were differentially abundant (>3-fold cutoff) in HIV-1-resistant women. The majority of over-abundant proteins were antiproteases (>40%), some with described anti-inflammatory and anti-HIV-1 activity. Quantification of specific anti-HIV-1 antiproteases Serpin A1, Serpin A3, and Cystatin B and an epithelial antiprotease A2ML1 found them to be significantly over-abundant in HIV-1-resistant women (p = 0.004; p = 0.046; p = 0.0003; and p = 0.04, respectively). Expression levels were not correlated to sexual practices or other epidemiological factors. Mucosal antiprotease levels correlated with pro-inflammatory cytokine concentration (p = <0.0001), but independently of pro-inflammatory cytokine levels in HIV-1-resistant women including TNF-alpha, IL-1 alpha, IL-1 beta, IL-6, and IL-8. This comprehensive systems biology approach identifies mucosal serpins and cystatins as novel correlates of HIV-1-resistance. This represents the first study characterizing these factors in the female genital tract.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".