title: Improving the identification rate of data independent label-free quantitative proteomics experiments on non-model crops: a case study on apple fruit.
abstract: Complex peptide extracts from non-model crops are troublesome for proper identification and quantification. To increase the identification rate of label free DIA experiments of Braeburn apple a new workflow was developed where a DDA database was constructed and linked to the DIA data. At a first level, parent masses found in DIA were searched in the DDA database based on their mass to charge ratio and retention time; at a second level, masses of fragmentation ions were compared for each of the linked spectrum. Following this workflow, a tenfold increase of peptides was identified from a single DIA run. As proof of principle, the designed workflow was applied to determine the changes during a storage experiment, achieving a two-fold identification increase in the number of significant peptides. The corresponding protein families were divided into nine clusters, representing different time profiles of changes in abundances during storage. Up-regulated protein families already show a glimpse of important pathways affecting aging during long-term storage, such as ethylene synthesis, and responses to abiotic stresses and their influence on the central metabolism.
  
  
  CONCLUSIONS
  Proteomics research on non-model crops causes additional difficulties in identifying the peptides present in, often complex, samples. This work proposes a new workflow to retrieve more identifications from a set of quantitative data, based on linking DIA and DDA data at two consecutive levels. As proof of principle, a storage experiment on Braeburn apple resulted in twice as much identified storage related peptides. Important proteins involved in central metabolism and stress are significantly up-regulated after long term storage. This article is part of a Special Issue entitled: Proteomics of non-model organisms.
authors.affiliation: BIOSYST-MeBioS, KU Leuven, Belgium. Electronic address: kim.buts@kuleuven.be.
authors.forename: Kim
authors.initials: K
authors.lastname: Buts
authors.affiliation: Quantum Chemistry and Physical Chemistry Section, KU Leuven, Belgium; Computational Biomolecular Dynamics Group, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.
authors.forename: Servaas
authors.initials: S
authors.lastname: Michielssens
authors.affiliation: BIOSYST-MeBioS, KU Leuven, Belgium.
authors.forename: Maarten L A T M
authors.initials: ML
authors.lastname: Hertog
authors.affiliation: Research Group of Functional Genomics and Proteomics, KU Leuven, Belgium.
authors.forename: Eisuke
authors.initials: E
authors.lastname: Hayakawa
authors.affiliation: Plant Research International, Wageningen, Netherlands.
authors.forename: Jan
authors.initials: J
authors.lastname: Cordewener
authors.affiliation: Plant Research International, Wageningen, Netherlands.
authors.forename: Antoine H P
authors.initials: AH
authors.lastname: America
authors.affiliation: BIOSYST-MeBioS, KU Leuven, Belgium; Flanders Centre of Postharvest Technology, Leuven, Belgium.
authors.forename: Bart M
authors.initials: BM
authors.lastname: Nicolai
authors.affiliation: SYBIOMA, KU Leuven, Belgium; BIOSYST - Crop Biotechnics, KU Leuven, Belgium. Electronic address: sebastien.carpentier@biw.kuleuven.be.
authors.forename: Sebastien C
authors.initials: SC
authors.lastname: Carpentier
mesh_terms: D030541:Databases, Genetic; D005030:Ethylenes / Q000096:biosynthesis; D005519:Food Preservation; D005638:Fruit / Q000235:genetics / Q000378:metabolism; D027845:Malus / Q000235:genetics / Q000378:metabolism; D010940:Plant Proteins / Q000096:biosynthesis / Q000235:genetics; D040901:Proteomics / Q000379:methods*
chemical_list: D005030:Ethylenes; D010940:Plant Proteins; C036216:ethylene
keywords: Data independent acquisition; Label free quantification; Non-model crop; Plant proteomics