Analysis of the Differential Host Cell Nuclear Proteome Induced by Attenuated and Virulent Hemorrhagic Arenavirus Infection
Bibliographic record
Abstract
Arenaviruses are important emerging pathogens and include a number of hemorrhagic fever viruses classified as NIAID category A priority pathogens and CDC potential biothreat agents. Infection of guinea pigs with the New World arenavirus Pichindé virus (PICV) has been used as a biosafety level 2 model for the Lassa virus. Despite continuing research, little is known about the molecular basis of pathogenesis, and this has hindered the design of novel antiviral therapeutics. Modulation of the host response is a potential strategy for the treatment of infectious diseases. We have previously investigated the global host response to attenuated and lethal arenavirus infections by using high-throughput immunoblotting and kinomics approaches. In this report, we describe the differential nuclear proteomes of a murine cell line induced by mock infection and infection with attenuated and lethal variants of PICV, investigated by using two-dimensional gel electrophoresis. Spot identification using tandem mass spectrometry revealed the involvement of a number of proteins that regulate inflammation via potential modulation of NF-kappaB activity and of several heterogeneous nuclear ribonuclear proteins. Pathway analysis revealed a potential role for transcription factor XBP-1, a transcription factor involved in major histocompatibility complex II (MHC-II) expression; differential DNA-binding activity was revealed by electrophoretic mobility shift assay, and differences in surface MHC-II expression were seen following PICV infection. These data are consistent with the results of several previous studies and highlight potential differences between transcriptional and translational regulation. This study provides a number of differentially expressed targets for further research and suggests that key events in pathogenesis may be established early in infection.
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 | 0.000 |
| 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".