A Comparative Proteomic Analysis of the Soluble Immune Factor Environment of Rectal and Oral Mucosa
Bibliographic record
Abstract
OBJECTIVE: Sexual transmission of HIV occurs across a mucosal surface, which contains many soluble immune factors important for HIV immunity. Although the composition of mucosal fluids in the vaginal and oral compartments has been studied extensively, the knowledge of the expression of these factors in the rectal mucosa has been understudied and is very limited. This has particular relevance given that the highest rates of HIV acquisition occur via the rectal tract. To further our understanding of rectal mucosa, this study uses a proteomics approach to characterize immune factor components of rectal fluid, using saliva as a comparison, and evaluates its antiviral activity against HIV. METHODS: Paired salivary fluid (n = 10) and rectal lavage fluid (n = 10) samples were collected from healthy, HIV seronegative individuals. Samples were analyzed by label-free tandem mass spectrometry to comprehensively identify and quantify mucosal immune protein abundance differences between saliva and rectal fluids. The HIV inhibitory capacity of these fluids was further assessed using a TZM-bl reporter cell line. RESULTS: Of the 315 proteins identified in rectal lavage fluid, 72 had known immune functions, many of which have described anti-HIV activity, including cathelicidin, serpins, cystatins and antileukoproteinase. The majority of immune factors were similarly expressed between fluids, with only 21 differentially abundant (p<0.05, multiple comparison corrected). Notably, rectal mucosa had a high abundance of mucosal immunoglobulins and antiproteases relative to saliva, Rectal lavage limited HIV infection by 40-50% in vitro (p<0.05), which is lower than the potent anti-HIV effect of oral mucosal fluid (70-80% inhibition, p<0.005). CONCLUSIONS: This study reveals that rectal mucosa contains many innate immune factors important for host immunity to HIV and can limit viral replication in vitro. This indicates an important role for this fluid as the first line of defense against HIV.
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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 | 0.001 | 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) | 0.001 | 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".