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Record W4294199477 · doi:10.21037/exrna-22-6

DodecaRNAs (doRNAs) are abundant in cow’s milk and differentially enriched in milk ultracentrifugation fractions

2022· article· en· W4294199477 on OpenAlexafffund
Abderrahim Benmoussa, Zeinab Husseini, Jeffrey D. Ho, Sara Guellal, Marine Lambert, Caroline Gilbert, Patrick Provost

Bibliographic record

VenueExRNA · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversité LavalMcGill University Health CentreUniversité de MontréalCentre hospitalier universitaire de QuébecCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health ResearchMassachusetts Department of Agricultural Resources
KeywordsFood scienceCow milkChemistryUltracentrifugeChromatographyAnimal scienceBiology

Abstract

fetched live from OpenAlex

Background: Extracellular RNAs (exRNAs) are found in numerous extracellular fluids, including milk. Until recently, microRNAs were the focus of research in this area, leaving aside other exRNAs. Recently, a modified small RNA-sequencing (sRNA-seq) approach led to the discovery of very short, 12 and 13 nucleotides (nt) ribosomal RNA (rRNA) fragments (rRFs), designated as dodecaRNAs (doRNAs), in reference to the number of core nucleotides (12 nt) they contain. Since milk is highly enriched in extracellular vesicles (EVs) and exRNAs, we inquired about the existence of doRNAs and other very short exRNAs in milk and milk EV (mEV)-enriched ultracentrifugation fractions. Methods: We used sRNA-seq to explore exRNAs shorter than 16 nt in cow’s milk and milk fractions obtained by ultracentrifugation. Results were validated with high-specificity splint-ligated reverse transcription quantitative polymerase chain reaction (RT-qPCR) using high sensitivity locked nucleic acid (LNA) oligonucleotides. Results: Cow’s milk was abundant in doRNAs and c-doRNAs, a doRNA derivative harboring an additional cytosine (C) at its 5' end. Together, these two sequences represented 66.5% of all 8- to 15-nt RNA species. The abundance of doRNAs in milk was 11 to 49 times higher than the most abundant microRNAs. These RNAs were differentially distributed in milk ultracentrifugation fractions; their concentration was highest in the lower speed fractions (12,000 and 35,000 g). We also observed an increased c-doRNA/doRNA ratio with centrifugation speed, suggesting a possible selective release of c-doRNA over doRNA in denser mEVs. RT-qPCR quantification confirmed the presence of doRNAs in milk and supported the differential enrichment of doRNAs in different mEV subsets compared to that of the most enriched milk bta-let-7b, bta-miR-30a-5p and bta-miR-148a, yet not without discrepancies with the sequencing data. Conclusions: These findings suggest that exRNAs might be more diverse in cow’s milk than previously thought. As doRNAs were found to be downregulated and to modulate cell proliferation/migration of prostate cancer cells, this could have health implications in adult and infant consumers which warrant further investigations.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.007
GPT teacher head0.235
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes2
Has abstractyes

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