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Record W1987532371 · doi:10.1099/ijs.0.054213-0

Conserved signature indels and signature proteins as novel tools for understanding microbial phylogeny and systematics: identification of molecular signatures that are specific for the phytopathogenic genera Dickeya, Pectobacterium and Brenneria

2014· article· en· W1987532371 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueINTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyPectobacteriumPhylogenetic treePhylogeneticsIndelGenomeConserved sequenceMolecular phylogeneticsEvolutionary biologySubgenusGeneticsSystematicsBacterial genome sizeGenusTaxonomy (biology)BotanyBacteriaGenePeptide sequence

Abstract

fetched live from OpenAlex

Genome sequences are enabling applications of different approaches to more clearly understand microbial phylogeny and systematics. Two of these approaches involve identification of conserved signature indels (CSIs) and conserved signature proteins (CSPs) that are specific for different lineages. These molecular markers provide novel and more definitive means for demarcation of prokaryotic taxa and for identification of species from these groups. Genome sequences are also enabling determination of phylogenetic relationships among species based upon sequences for multiple proteins. In this work, we have used all of these approaches for studying the phytopathogenic bacteria belonging to the genera Dickeya, Pectobacterium and Brenneria. Members of these genera, which cause numerous diseases in important food crops and ornamental plants, are presently distinguished mainly on the basis of their branching in phylogenetic trees. No biochemical or molecular characteristic is known that is uniquely shared by species from these genera. Hence, detailed studies using the above approaches were carried out on proteins from the genomes of these bacteria to identify molecular markers that are specific for them. In phylogenetic trees based upon concatenated sequences for 23 conserved proteins, members of the genera Dickeya, Pectobacterium and Brenneria formed a strongly supported clade within the other Enterobacteriales. Comparative analysis of protein sequences from the Dickeya, Pectobacterium and Brenneria genomes has identified 10 CSIs and five CSPs that are either uniquely or largely found in all genome-sequenced species from these genera, but not present in any other bacteria in the database. In addition, our analyses have identified 10 CSIs and 17 CSPs that are specifically present in either all or most sequenced Dickeya species/strains, and six CSIs and 19 CSPs that are uniquely found in the sequenced Pectobacterium genomes. Finally, our analysis also identified three CSIs and one CSP that are specifically shared by members of the genera Pectobacterium and Brenneria, but absent in species of the genus Dickeya, indicating that the former two genera shared a common ancestor exclusive of Dickeya. The identified CSIs and CSPs provide novel tools for identification of members of the genera Dickeya and Pectobacterium and for delimiting these taxa in molecular terms. Descriptions of the genera Dickeya and Pectobacterium have been revised to provide information for these molecular markers. Biochemical studies on these CSIs and CSPs, which are specific for these genera, may lead to discovery of novel properties that are unique to these bacteria and which could be targeted to develop antibacterial agents that are specific for these plant-pathogenic bacteria.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.223
Teacher spread0.184 · 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