Novel E2 Glycoprotein Tetramer Detects Hepatitis C Virus–Specific Memory B Cells
Bibliographic record
Abstract
Acute hepatitis C virus (HCV) infection culminates in viral persistence in the majority of cases. Abs that recognize the envelope glycoproteins E1 and E2 are generated during the late stages of acute infection, yet their contribution to spontaneous viral clearance remains controversial. Investigation of the humoral responses during acute HCV infection have been limited by the inability to directly identify and characterize HCV-specific B cells. In this study we describe the development of a novel tetramer of the E2 glycoprotein ectodomain (J6, genotype 2a strain), which allowed us to visualize E2-specific B cells longitudinally in the peripheral blood of HCV-infected individuals. HCV-specific class-switched memory B cells were detected in 3 out of 7 participants during late acute infection, with a mean frequency of 0.63% for positive samples (range 0.16-0.67%) and in 7 out of 7 participants with chronic infection with a mean frequency of 0.47% (range 0.20-0.78%). In a cross-sectional study, E2 tetramer positive population was detected in 28 out of 31 chronically infected individuals. Deep sequencing of the BCR from E2-specific class-switched memory B cells sorted from two independent participants revealed a focused repertoire suggestive of clonal selection. Tetramer-specific B cells exhibited skewed CDR3 length distribution and increased mutation frequency compared with naive B cells. This BCR profile is indicative of clonal expansion and affinity maturation. E2 tetramer allows for specific and sensitive ex vivo characterization of rare HCV-specific B cells in infected individuals, and will enable researchers to gain a better understanding of humoral immunity in HCV infection.
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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 | 0.001 | 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".