TY - JOUR

T1 - Getting Ready for Large-Scale Proteomics in Crop Plants

AU - Brajkovic, Sarah

AU - Rugen, Nils

AU - Agius, Carlos

AU - Berner, Nicola

AU - Eckert, Stephan

AU - Sakhteman, Amirhossein

AU - Schwechheimer, Claus

AU - Kuster, Bernhard

N1 - Funding Information: This research was in part funded by Elitenetzwerk Bayern (grant number F-6-M5613.6.K-NW-2021-411/1/1) and the German Science Foundation (DFG) Coordinated Research Center SFB 924 (grant number 170483403).

PY - 2023/2/3

Y1 - 2023/2/3

N2 - Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant Arabidopsis thaliana, proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes.

AB - Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant Arabidopsis thaliana, proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes.

KW - liquid chromatography mass spectrometry

KW - nutritional crop proteomics

KW - plant proteomics

UR - http://www.scopus.com/inward/record.url?scp=85147827541&partnerID=8YFLogxK

U2 - 10.3390/nu15030783

DO - 10.3390/nu15030783

M3 - Article

VL - 15

JO - Nutrients

JF - Nutrients

SN - 2072-6643

IS - 3

M1 - 783

ER -