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. 2023 Feb 9:14:1065465.
doi: 10.3389/fpls.2023.1065465. eCollection 2023.

Application of proteomics to determine the mechanism of ozone on sweet cherries (Prunus avium L.) by time-series analysis

Yuehan Zhao  1   2 , Zhaohua Hou  3 , Na Zhang  2 , Haipeng Ji  2   4 , Chenghu Dong  2 , Jinze Yu  2 , Xueling Chen  4 , Cunkun Chen  2 , Honglian Guo  1
Affiliations

Application of proteomics to determine the mechanism of ozone on sweet cherries (Prunus avium L.) by time-series analysis

Yuehan Zhao et al. Front Plant Sci. .

Abstract

This research investigated the mechanism of ozone treatment on sweet cherry (Prunus avium L.) by Lable-free quantification proteomics and physiological traits. The results showed that 4557 master proteins were identified in all the samples, and 3149 proteins were common to all groups. Mfuzz analyses revealed 3149 candidate proteins. KEGG annotation and enrichment analysis showed proteins related to carbohydrate and energy metabolism, protein, amino acids, and nucleotide sugar biosynthesis and degradation, and fruit parameters were characterized and quantified. The conclusions were supported by the fact that the qRT-PCR results agreed with the proteomics results. For the first time, this study reveals the mechanism of cherry in response to ozone treatment at a proteome level.

Keywords: label-free quantification proteomics; mfuzz; ozone; preservation; sweet cherry (Prunus avium L.).

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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
The visual appearance of different treatment cherry fruit stored for 28 days at 0°C.
Figure 2
Figure 2
The 12 physiological characteristics of sweet cherry.
Figure 3
Figure 3
Molecular weight distribution plot of all identified proteins (A). Distribution of proteins containing the different number of identified unique peptides (B). Principal component analysis of protein expression patterns (C). Heatmap of the 4457 identified proteins, different columns represent independent biological replicates (D).
Figure 4
Figure 4
Results of the Mfuzz clustering of 3149 differentially expressed proteins identified by Label-free proteomics based on their expression patterns.
Figure 5
Figure 5
Volcano plot of differential expression protein in 28 days at 0°C.
Figure 6
Figure 6
KEGG pathway plot and Emapplot of DEPs in group 3. According to the KEGG database: “GeneRatio” means the ratio of the number of differentially expressed genes under this pathway term to the number of annotated genes under the pathway term. The larger the value is, the greater the enrichment degree is in kegg and emapplot.
Figure 7
Figure 7
Verification of genes of protein using qRT-PCR.
See this image and copyright information in PMC

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