Characterizing changes in transcriptome and kinome responses in testicular cells during infection by Ebola virus
Bibliographic record
Abstract
Abstract Ebola virus (EBOV) is able to persist and actively replicate in the reproductive tract of male disease survivors months or years after recovery from Ebola virus disease (EVD) 1 . Persistent EBOV infections are usually asymptomatic and can be transmitted sexually, but the host and viral factors that mediate these infections have not been characterized 2,3 . We investigated the interaction between host and viral factors during EBOV infection of the blood testis barrier (BTB), with a focus on Sertoli cells as a potential reservoir for viral persistence. We assessed viral replication kinetics and host responses of mouse testicular Leydig cells and Sertoli cells infected with EBOV Makona (i.e. infectious EBOV) and collected samples up to 28 days post-infection. Viral replication was apparent in both cell lines, but intracellular early viral loads were much higher in Leydig cells compared to Sertoli cells. We used RNAseq analysis to characterize transcriptomic responses of Leydig cells and Sertoli cells to EBOV infection over time. Further investigation of early interactions between host cells and EBOV was performed using virus-like particles (EBOV trVLP) and assays of phosphorylation-based cell signaling. Our findings indicate that virus-treated Sertoli cells responded more rapidly and robustly than Leydig cells, and with a particular emphasis on detection of, and response to, external stimuli. We discuss how the roles played by Sertoli cells in immune privilege and spermatogenesis may affect their initial and continued response to EBOV infection in a manner that could facilitate asymptomatic persistence.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".