Velocity Gradient Separation Reveals a New Extracellular Vesicle Population Enriched in miR-155 and Mitochondrial DNA
Bibliographic record
Abstract
Extracellular vesicles (EVs) and their contents (proteins, lipids, messenger RNA, microRNA, and DNA) are viewed as intercellular signals, cell-transforming agents, and shelters for viruses that allow both diagnostic and therapeutic interventions. EVs circulating in the blood of individuals infected with human immunodeficiency virus (HIV-1) may provide insights into pathogenesis, inflammation, and disease progression. However, distinguishing plasma membrane EVs from exosomes, exomeres, apoptotic bodies, virions, and contaminating proteins remains challenging. We aimed at comparing sucrose and iodixanol density and velocity gradients along with commercial kits as a means of separating EVs from HIV particles and contaminating protein like calprotectin; and thereby evaluating the suitability of current plasma EVs analysis techniques for identifying new biomarkers of HIV-1 immune activation. Multiple analysis have been performed on HIV-1 infected cell lines, plasma from HIV-1 patients, or plasma from HIV-negative individuals spiked with HIV-1. Commercial kits, the differential centrifugation and density or velocity gradients to precipitate and separate HIV, EVs, and proteins such as calprotectin, have been used. EVs, virions, and contaminating proteins were characterized using Western blot, ELISA, RT-PCR, hydrodynamic size measurement, and enzymatic assay. Conversely to iodixanol density or velocity gradient, protein and virions co-sedimented in the same fractions of the sucrose density gradient than AChE-positive EVs. Iodixanol velocity gradient provided the optimal separation of EVs from viruses and free proteins in culture supernatants and plasma samples from a person living with HIV (PLWH) or a control and revealed a new population of large EVs enriched in microRNA miR-155 and mitochondrial DNA. Although EVs and their contents provide helpful information about several key events in HIV-1 pathogenesis, their purification and extensive characterization by velocity gradient must be investigated thoroughly before further use as biomarkers. By revealing a new population of EVs enriched in miR-155 and mitochondrial DNA, this study paves a way to increase our understanding of HIV-1 pathogenesis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".