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Record W2145145853 · doi:10.1186/1471-2229-13-167

iTRAQ-based protein profiling provides insights into the central metabolism changes driving grape berry development and ripening

2013· article· en· W2145145853 on OpenAlexfundno aff
María José Martínez‐Esteso, María Teresa Vilella-Antón, M. A. Pedreño, María Valero, Roque Bru‐Martínez

Bibliographic record

VenueBMC Plant Biology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
FundersGenome British ColumbiaUniversidad de AlicanteUniversity of VictoriaGenome Canada
KeywordsRipeningBerryBiologyProteomeMetabolic pathwayVitis viniferaBotanyFood scienceBiochemistryMetabolism

Abstract

fetched live from OpenAlex

BACKGROUND: Grapevine (Vitis vinifera L.) is an economically important fruit crop. Quality-determining grape components such as sugars, acids, flavors, anthocyanins, tannins, etc., accumulate in the different grape berry development stages. Thus, correlating the proteomic profiles with the biochemical and physiological changes occurring in grape is of paramount importance to advance in our understanding of berry development and ripening processes. RESULTS: We report the developmental analysis of Vitis vinifera cv. Muscat Hamburg berries at the protein level from fruit set to full ripening. An iTRAQ-based bottom-up proteomic approach followed by tandem mass spectrometry led to the identification and quantitation of 411 and 630 proteins in the green and ripening phases, respectively. Two key points in development relating to changes in protein level were detected: end of the first growth period (7 mm-to-15 mm) and onset of ripening (15 mm-to-V100, V100-to-110). A functional analysis was performed using the Blast2GO software based on the enrichment of GO terms during berry growth. CONCLUSIONS: The study of the proteome contributes to decipher the biological processes and metabolic pathways involved in the development and quality traits of fruit and its derived products. These findings lie mainly in metabolism and storage of sugars and malate, energy-related pathways such as respiration, photosynthesis and fermentation, and the synthesis of polyphenolics as major secondary metabolites in grape berry. In addition, some key steps in carbohydrate and malate metabolism have been identified in this study, i.e., PFP-PFK or SuSy-INV switches among others, which may influence the final sugar and acid balance in ripe fruit. In conclusion, some proteins not reported to date have been detected to be deregulated in specific tissues and developmental stages, leading to formulate new hypotheses on the metabolic processes underlying grape berry development. These results open up new lines to decipher the processes controlling grape berry development and ripening.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.238
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations66
Published2013
Admission routes1
Has abstractyes

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