Comparative analysis of DNA extraction and PCR product purification methods for cervicovaginal microbiome analysis using cpn60 microbial profiling
Bibliographic record
Abstract
BACKGROUND: The microbiota of the lower female genital tract plays an important role in women's health. Microbial profiling using the chaperonin60 (cpn60) universal target (UT) improves resolution of vaginal species associated with negative health outcomes compared to the more commonly used 16S ribosomal DNA target. However, the choice of DNA extraction and PCR product purification methods may bias sequencing-based microbial studies and should be optimized for the sample type and molecular target used. In this study, we compared two commercial DNA extraction kits and two commercial PCR product purification kits for the microbial profiling of cervicovaginal samples using the cpn60 UT. METHODS: DNA from cervicovaginal secretions and vaginal lavage samples as well as mock community standards were extracted using either the specialized QIAamp DNA Microbiome Kit, or the standard DNeasy Blood & Tissue kit with enzymatic pre-treatment for enhanced lysis of gram-positive bacteria. Extracts were PCR amplified using well-established cpn60 primer sets and conditions. Products were then purified using a column-based method (QIAquick PCR Purification Kit) or a gel-based PCR clean-up method using the QIAEX II Gel Extraction Kit. Purified amplicons were sequenced with the MiSeq platform using standard procedures. The overall quality of each method was evaluated by measuring DNA yield, alpha diversity, and microbial composition. RESULTS: DNA extracted from cervicovaginal samples using the DNeasy Blood and Tissue kit, pre-treated with lysozyme and mutanolysin, resulted in increased DNA yield, bacterial diversity, and species representation compared to the QIAamp DNA Microbiome kit. The column-based PCR product purification approach also resulted in greater average DNA yield and wider species representation compared to a gel-based clean-up method. In conclusion, this study presents a fast, effective sample preparation method for high resolution cpn60 based microbial profiling of cervicovaginal samples.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".