microRNA-185 Inhibits SARS-CoV-2 Infection through the Modulation of the Host’s Lipid Microenvironment
Bibliographic record
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there has been an urgent need for the development of fast-acting antivirals, particularly in dealing with different variants of concern (VOC). SARS-CoV-2, like other RNA viruses, depends on host cell machinery to propagate and misregulate metabolic pathways to its advantage. Herein, we discovered that the immunometabolic microRNA-185 (miR-185) restricts SARS-CoV-2 propagation by affecting its entry and infectivity. The antiviral effects of miR-185 were studied in SARS-CoV-2 Spike protein pseudotyped virus, surrogate virus (HCoV-229E), as well as live SARS-CoV-2 virus in Huh7, A549, and Calu-3 cells. In each model, we consistently observed microRNA-induced reduction in lipid metabolism pathways-associated genes including SREBP2, SQLE, PPARG, AGPAT3, and SCARB1. Interestingly, we also observed changes in angiotensin-converting enzyme 2 (ACE2) levels, the entry receptor for SARS-CoV-2. Taken together, these data show that miR-185 significantly restricts host metabolic and other pathways that appear to be essential to SAR-CoV-2 replication and propagation. Overall, this study highlights an important link between non-coding RNAs, immunometabolic pathways, and viral infection. miR-185 mimics alone or in combination with other antiviral therapeutics represent possible future fast-acting antiviral strategies that are likely to be broadly antiviral against multiple variants as well as different virus types of potential pandemics.
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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 | 0.000 | 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) | 0.000 | 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".