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Record W2022546662 · doi:10.1073/pnas.0902578106

Protein targeting into secondary plastids of chlorarachniophytes

2009· article· en· W2022546662 on OpenAlexaff
Yoshihisa Hirakawa, Kisaburo Nagamune, Ken‐ichiro Ishida

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsDalhousie University
FundersJapan Society for the Promotion of Science
KeywordsPlastidEndoplasmic reticulumSignal peptideBiologyTransit PeptideFunction (biology)Cell biologyBiochemistryTransloconChloroplastPeptide sequenceMembrane proteinGeneMembrane

Abstract

fetched live from OpenAlex

Most plastid proteins are encoded by the nuclear genome, and consequently, need to be transported into plastids across multiple envelope membranes. In diverse organisms possessing secondary plastids, nuclear-encoded plastid precursor proteins (preproteins) commonly have an N-terminal extension that consists of an endoplasmic reticulum (ER)-targeting signal peptide and a transit peptide-like sequence (TPL). This bipartite targeting peptide is believed to be necessary for targeting the preproteins into the secondary plastids. Here, we newly demonstrate the function of the bipartite targeting peptides of an algal group, chlorarachniophytes, and characterize the functional domains of the TPL in the precursor of a plastid protein, ATP synthase delta subunit (AtpD), using a GFP as a reporter molecule. We show that the C-terminal portion of the TPL is important for targeting the AtpD preprotein from the ER into the chlorarachniophyte plastids, and several positively charged amino acids in the TPL are also necessary for transporting the preprotein across the 2 innermost plastid membranes. Compared with other groups with secondary plastids, the TPL functional domains of the chlorarachniophytes are unique, which might be caused by independent acquisition of their plastids.

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)0.001
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 score0.032
Threshold uncertainty score0.206

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 science0.0010.000
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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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

Citations33
Published2009
Admission routes1
Has abstractyes

Explore more

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