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Record W2340791212 · doi:10.1093/humrep/dew030

HT-COMET: a novel automated approach for high throughput assessment of human sperm chromatin quality

2016· article· en· W2340791212 on OpenAlexafffundabout
Océane Albert, Wolfgang Reintsch, Peter Chan, Bernard Robaire

Bibliographic record

VenueHuman Reproduction · 2016
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill University Health CentreCentre in Green Chemistry and CatalysisMcGill University
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMcGill University
KeywordsComet assayCometSpermDNA damageBiologyAndrologyMedicineGeneticsDNA

Abstract

fetched live from OpenAlex

STUDY QUESTION: Can we make the comet assay (single-cell gel electrophoresis) for human sperm a more accurate and informative high throughput assay? SUMMARY ANSWER: We developed a standardized automated high throughput comet (HT-COMET) assay for human sperm that improves its accuracy and efficiency, and could be of prognostic value to patients in the fertility clinic. WHAT IS KNOWN ALREADY: The comet assay involves the collection of data on sperm DNA damage at the level of the single cell, allowing the use of samples from severe oligozoospermic patients. However, this makes comet scoring a low throughput procedure that renders large cohort analyses tedious. Furthermore, the comet assay comes with an inherent vulnerability to variability. Our objective is to develop an automated high throughput comet assay for human sperm that will increase both its accuracy and efficiency. STUDY DESIGN, SIZE, DURATION: The study comprised two distinct components: a HT-COMET technical optimization section based on control versus DNAse treatment analyses ( ITALIC! n = 3-5), and a cross-sectional study on 123 men presenting to a reproductive center with sperm concentrations categorized as severe oligozoospermia, oligozoospermia or normozoospermia. PARTICIPANTS/MATERIALS, SETTING, METHODS: Sperm chromatin quality was measured using the comet assay: on classic 2-well slides for software comparison; on 96-well slides for HT-COMET optimization; after exposure to various concentrations of a damage-inducing agent, DNAse, using HT-COMET; on 123 subjects with different sperm concentrations using HT-COMET. Data from the 123 subjects were correlated to classic semen quality parameters and plotted as single-cell data in individual DNA damage profiles. MAIN RESULTS AND THE ROLE OF CHANCE: We have developed a standard automated HT-COMET procedure for human sperm. It includes automated scoring of comets by a fully integrated high content screening setup that compares well with the most commonly used semi-manual analysis software. Using this method, a cross-sectional study on 123 men showed no significant correlation between sperm concentration and sperm DNA damage, confirming the existence of hidden chromatin damage in men with apparently normal semen characteristics, and a significant correlation between percentage DNA in the tail and percentage of progressively motile spermatozoa. Finally, the use of DNA damage profiles helped to distinguish subjects between and within sperm concentration categories, and allowed a determination of the proportion of highly damaged cells. LIMITATIONS, REASONS FOR CAUTION: The main limitations of the HT-COMET are the high, yet indispensable, investment in an automated liquid handling system and heating block to ensure accuracy, and the availability of an automated plate reading microscope and analysis software. WIDER IMPLICATIONS OF THE FINDINGS: This standardized HT-COMET assay offers many advantages, including higher accuracy and evenness due to automation of sensitive steps, a 14.4-fold increase in sample analysis capacity, and an imaging and scoring time of 1 min/well. Overall, HT-COMET offers a decrease in total experimental time of more than 90%. Hence, this assay constitutes a more efficient option to assess sperm chromatin quality, paves the way to using this assay to screen large cohorts, and holds prognostic value for infertile patients. STUDY FUNDING/COMPETING INTERESTS: Funded by the CIHR Institute of Human Development, Child and Youth Health (IHDCYH; RHF 100625). O.A. is a fellow supported by the Fonds de la Recherche du Québec - Santé (FRQS) and the CIHR Training Program in Reproduction, Early Development, and the Impact on Health (REDIH). B.R. is a James McGill Professor. The authors declare no conflicts of interest.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.385
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2016
Admission routes3
Has abstractyes

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