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Record W4367694062 · doi:10.1016/j.isci.2023.106787

Improving the extraction of ancient Yersinia pestis genomes from the dental pulp

2023· article· en· W4367694062 on OpenAlexaff
Pierre Clavel, Lexane Louis, Clio Der Sarkissian, Catherine Thèves, Claudia Gillet, Loreleï Chauvey, Gaétan Tressières, Stéphanie Schiavinato, Laure Calvière‐Tonasso, Norbert Telmon, Benoît Clavel, Richard Jonvel, Stéfan Tzortzis, Bouniol Laetitia, Jean-Marc Fémolant, Jennifer Klunk, Hendrik N. Poinar, Michel Signoli, Caroline Costedoat, Maria A. Spyrou, Andaine Seguin‐Orlando, Ludovic Orlando

Bibliographic record

VenueiScience · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsMcMaster UniversityCanadian Institute for Advanced Research
FundersAgence Nationale de la RechercheCentre National de la Recherche ScientifiqueEuropean CommissionFondation Simone et Cino Del Duca
KeywordsYersinia pestisAncient DNADNAGenomeDNA sequencingBiologyPulp (tooth)DNA extractionComputational biologyPolymerase chain reactionGeneGeneticsMedicineDentistryVirulence

Abstract

fetched live from OpenAlex

Ancient DNA preserved in the dental pulp offers the opportunity to characterize the genome of some of the deadliest pathogens in human history. However, while DNA capture technologies help, focus sequencing efforts, and therefore, reduce experimental costs, the recovery of ancient pathogen DNA remains challenging. Here, we tracked the kinetics of ancient Yersinia pestis DNA release in solution during a pre-digestion of the dental pulp. We found that most of the ancient Y. pestis DNA is released within 60 min at 37°C in our experimental conditions. We recommend a simple pre-digestion as an economical procedure to obtain extracts enriched in ancient pathogen DNA, as longer digestion times release other types of templates, including host DNA. Combining this procedure with DNA capture, we characterized the genome sequences of 12 ancient Y. pestis bacteria from France dating to the second pandemic outbreaks of the 17 th and 18 th centuries Common Era.

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 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)0.000
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 score0.519
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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