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. 2022 Nov 14:13:1005755.
doi: 10.3389/fpls.2022.1005755. eCollection 2022.

Proteomic responses of two spring wheat cultivars to the combined water deficit and aphid (Metopolophium dirhodum) treatments

Affiliations

Proteomic responses of two spring wheat cultivars to the combined water deficit and aphid (Metopolophium dirhodum) treatments

Klára Kosová et al. Front Plant Sci. .

Abstract

In the field, plants usually have to face the combined effects of abiotic and biotic stresses. In our study, two spring wheat cultivars-Septima and Quintus-were subjected to three water regimes [70%, 50%, and 40% soil water capacity (SWC)], aphid (Metopolophium dirhodum) infestation, or the combination of both stresses, i.e., water deficit (50%, 40% SWC) and aphids. The study has a 2 × 3 × 2 factorial design with three biological replicates. In the present study, the results of proteomic analysis using 2D-DIGE followed by MALDI-TOF/TOF protein identification are presented. Water deficit but also aphid infestation led to alterations in 113 protein spots including proteins assigned to a variety of biological processes ranging from signaling via energy metabolism, redox regulation, and stress and defense responses to secondary metabolism indicating a long-term adaptation to adverse conditions. The absence of specific proteins involved in plant response to herbivorous insects indicates a loss of resistance to aphids in modern wheat cultivars during the breeding process and is in accordance with the "plant vigor hypothesis." Septima revealed enhanced tolerance with respect to Quintus as indicated by higher values of morphophysiological characteristics (fresh aboveground biomass, leaf length, osmotic potential per full water saturation) and relative abundance of proteins involved in mitochondrial respiration and ATP biosynthesis.

Keywords: 2D-DIGE; combined stress; herbivorous insects; proteome; spring wheat; water deficit.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
A representative 2D-DIGE gel (internal standard labeled by Cy2) with indicated positions of protein spots revealing differential relative abundance (at least 1.5-fold change at the 0.05 level) in at least one of 18 biologically relevant ratios: 70 (S/Q), 50 (S/Q), 40 (S/Q); S (50/70), S (40/70), S (40/50); Q (50/70), Q (40/70), Q (40/50); 70 (Qm/Q), 50 (Qm/Q), 40 (Qm/Q); 70 (Sm/S), 50 (Sm/S), 40 (Sm/S); and 70 (Sm/Qm), 50 (Sm/Qm), 40 (Sm/Qm). Detailed views on 2D-DIGE gel sections with protein spots revealing differential relative abundance patterns in the set of 12 experiment variants.
Figure 2
Figure 2
Principal component analysis of the 113 differentially abundant proteins (DAPs) with indicated positions of the 12 experiment variants showing the first two principal components PC1 versus PC2 (A) and PC1 versus PC3 (B). Q means Quintus, S means Septima, m means Metopolophium dirhodum treatment, 40 means 40% SWC, 50 means 50% SWC, and 70 means 70% SWC.
Figure 3
Figure 3
Venn diagrams showing the numbers of upregulated (↑) and downregulated (↓) protein spots in 24 biologically relevant ratios: in Septima (A) [S (50/70), S (40/70), S (40/50)]; in Quintus (B) [Q (50/70), Q (40/70), Q (40/50)]; in the aphid-infested Septima (C) [Sm (50/70), Sm (40/50), Sm (40/70)]; in the aphid-infested Quintus (D) [Qm (50/70), Qm (40/50), Qm (40/70)]; in the non-infested Septima versus Quintus (S/Q) (E) [70 (S/Q), 50 (S/Q), 40 (S/Q)]; in the aphid-infested versus non-infested Septima (Sm/S) (F) [70 (Sm/S), 50 (Sm/S), 40 (Sm/S)]; in the aphid-infested Septima versus Quintus (Sm/Qm) (G) [70 (Sm/Qm), 50 (Sm/Qm), 40 (Sm/Qm)]; and in the aphid-infested versus non-infested Quintus (Qm/Q) (H) [70 (Qm/Q), 50 (Qm/Q), 40 (Qm/Q)].
Figure 4
Figure 4
Cluster analysis of the 113 DAPs in the set of 12 experiment variants (S70, S50, S40, Sm70, Sm50, Sm40, Q70, Q50, Q40, Qm70, Qm50, Qm40). The data were normalized using Z-score transformation, and cluster analysis was performed in PermutMatrix software using Euclidean distances and Ward’s minimum criteria as algorithms for clusterogram construction. Details on the 2D-DIGE gel images of selected protein spots representing the individual clusters are given.
Figure 5
Figure 5
Pie chart of the identified protein spots showing protein classification according to GO biological processes (A) and cellular localization (B).
Figure 6
Figure 6
Representative 1-D SDS-PAGE gel stained by CBB R-250 (A), representative immunoblot with detected dehydrin proteins (B), and the results of densitometric analysis of dehydrin proteins detected in the immunoblot (C). In (B), the position of two detected dehydrin bands of 66 and 50 kDa corresponding to WCS66 and WCS120 proteins, respectively, is indicated by an arrow. In (C), the data columns represent mean values and the error bars represent standard deviation from three replicates (n = 3), and different letters above the data columns indicate significant differences in the density of dehydrin bands determined by ANOVA, LSD 0.05 test (STATISTICA version 14, Inc., TIBCO, UK). M means molecular marker (Bio-Rad), IS means internal standard as an equimolar mixture of all samples loaded on the gel, IS50 means internal standard at half dilution (50%), Q means Quintus, S means Septima, m means treatment with Metopolophium dirhodum, 70 means 70% SWC, 50 means 50% SWC, and 40 means 40% SWC.

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