Screening for genetic heterogeneity in the interferon sensitivity determining region of the hepatitis C virus genome by polymerase chain reaction with melting curve analysis
Bibliographic record
Abstract
BACKGROUND: Although mutations in the interferon (IFN) sensitivity determining region (ISDR) of hepatitis C virus (HCV) have been reported to be useful as a predictive viral factor for IFN therapy in patients infected with HCV-1b, such laboratory research has not been favorably translated into the clinic. To promote such translation, we attempted the establishment of a rapid and simple polymerase chain reaction (PCR) combined with melting curve analysis (MCA) to screen for mutations in the ISDR and for the monitoring of HCV quasispecies. METHODS: A PCR-MCA protocol was established using in-house primers and hybridization probes designed according to the results of direct sequencing of 34 HCV-1b samples. Then, the performance of PCR-MCA was verified by comparing with mutation profiles obtained by direct sequencing and sequencing after cloning. RESULTS: The MCA assay revealed that melting temperature (Tm) was inversely correlated with the number of nucleotide (nt) and amino acid substitutions in the ISDR deduced on the basis of the results of direct sequencing. A boundary Tm of 58.0 degrees C allowed us to discriminate HCV genomes into two groups: one with a Tm >58.0 degrees C had no or a low number of nt substitutions, while the other genomes with a Tm <58.0 degrees C had a high number of nt substitutions, corresponding to wild-type in the former and mutant-type in the latter in respect of a clinical setting for IFN therapy. Moreover, this MCA assay provided precise discrimination of Tm between clones, reflecting the degree of the genetic complexity of HCV genomes. CONCLUSIONS: This study indicates that the MCA assay is useful to rapidly and simply screen the mutational status of the ISDR of HCV, as well as in using the ISDR as one of the targets for discriminating the genetic complexity of HCV genomes. The MCA assay could also be applicable as a convenient and useful screen of the genetic heterogeneity of clones relating to HCV quasispecies.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".