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Assessment of genotypic identity of cyanobacterial strains in culture collections using HIP1-based primers

2004· article· en· W2037986878 on OpenAlexfundno aff
Katia Comte, Rosmarie Rippka, Thomas Friedl, John Day, Nicole Tandeau De Marsac, Michael Herdman

Bibliographic record

VenueNova Hedwigia · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueInstitut national de la recherche scientifique
KeywordsBiologyGenotypeIdentity (music)BotanyMicrobiologyEvolutionary biologyGeneticsGeneArt

Abstract

fetched live from OpenAlex

We examined 32 cyanobacterial strains, representative of 11 different genera, for the presence of the highly iterated genomic palindrome, called HIPI, using HIP I extended PCR primers. Cryolysates or cell suspensions, and even single colonies, of Microcystis aeruginosa, strain PCC 7806, yielded PCR products equivalent to those obtained with purified DNA, as judged from the banding patterns obtained by gel electrophoresis. Cryolysates were used for amplification and genotyping of all other strains. Representatives of different genera differed extensively in HIP1-based migration patterns, and the amplification products of axenic cyanobacteria were comparable to those obtained with duplicate, non-axenic strains. In addition, HIPI repeats were present in 11 strains of the species Microcystis aeruginosa and in isolates assignable to Planktothrix agardhii and P. rubescens. Based on available 16S rDNA sequence data and DNA/DNA hybridization results for members of these genera, the differences detected by HIP1-based profiling correlate with the interspecies distinctions between Planktothrix agardhii and P rubescens, and reflect intraspecific diversity for members of Microcystis aeruginosa. Thus, we have confirmed the value of this method for rapid genotyping and verification of presumably identical strains from different culture collections.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.302
Teacher spread0.278 · 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 designObservational
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

Citations3
Published2004
Admission routes1
Has abstractyes

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