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Record W2504908266 · doi:10.1021/acs.jproteome.6b00224

Carnivorous Nutrition in Pitcher Plants (<i>Nepenthes</i> spp.) via an Unusual Complement of Endogenous Enzymes

2016· article· en· W2504908266 on OpenAlexafffund
Linda Lee, Ye Zhang, Brittany Ozar, Christoph W. Sensen, David C. Schriemer

Bibliographic record

VenueJournal of Proteome Research · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationAlberta Innovates - Health Solutions
KeywordsComplement (music)Carnivorous plantBiologyEnzymeEndogenyBotanyBiochemistryEcologyGenePhenotype

Abstract

fetched live from OpenAlex

Plants belonging to the genus Nepenthes are carnivorous, using specialized pitfall traps called "pitchers" that attract, capture, and digest insects as a primary source of nutrients. We have used RNA sequencing to generate a cDNA library from the Nepenthes pitchers and applied it to mass spectrometry-based identification of the enzymes secreted into the pitcher fluid using a nonspecific digestion strategy superior to trypsin in this application. This first complete catalog of the pitcher fluid subproteome includes enzymes across a variety of functional classes. The most abundant proteins present in the secreted fluid are proteases, nucleases, peroxidases, chitinases, a phosphatase, and a glucanase. Nitrogen recovery involves a particularly rich complement of proteases. In addition to the two expected aspartic proteases, we discovered three novel nepenthensins, two prolyl endopeptidases that we name neprosins, and a putative serine carboxypeptidase. Additional proteins identified are relevant to pathogen-defense and secretion mechanisms. The full complement of acid-stable enzymes discovered in this study suggests that carnivory in the genus Nepenthes can be sustained by plant-based mechanisms alone and does not absolutely require bacterial symbiosis.

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 score0.089
Threshold uncertainty score0.157

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 science0.0000.000
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 head0.154
GPT teacher head0.327
Teacher spread0.173 · 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

Citations69
Published2016
Admission routes2
Has abstractyes

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