Proteomics Reveals the Mechanism Underlying the Inhibition of Phytophthora sojae by Propyl Gallate

Abstract

Phytophthora sojae is a serious soil-borne pathogen, and the major control measures undertaken include the induction of soybean-resistance genes, fungicides, and scientific and reasonable planting management. Owing to the safety and resistance of fungicides, it is of great importance to screen new control alternatives. In a preliminary study, we observed that propyl gallate (PG) exerts a considerable inhibitory effect on P. sojae and can effectively prevent and cure soybean diseases, although the underlying mechanism remains unclear. To explore the inhibitory mechanism of PG on P. sojae, we analyzed the differences in the protein profile of P. sojae before and after treatment with PG using tandem mass tag (TMT) proteomics. Proteomic analysis revealed that the number of differentially expressed proteins (DEPs) was 285, of which 75 were upregulated and 210 were downregulated, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways primarily comprised glycolysis, tricarboxylic acid cycle, fatty acid metabolism, secondary metabolite generation, and other pathways. Among the DEPs involved in PG inhibition of P. sojae are two closely related uncharacterized proteins encoded by PHYSODRAFT_522340 and PHYSODRAFT_344464, denoted PsFACL and PsCPT herein. The CRISPR/Cas9 knockout technique revealed that PsFACL and PsCPT were involved in the growth rate and pathogenicity. In addition, the results of gas chromatography-mass spectrometry (GC-MS) showed that there were differences in fatty acid levels between wild-type (WT) and CRISPR/Cas9 knockout transformants. Knocking out PsFACL and PsCPT resulted in the restriction of the synthesis and β-oxidation of long-chain fatty acids, respectively. These suggest that PsFACL and PsCPT were also involved in the regulation of the fatty acid metabolism. Our results aid in understanding the mechanism underlying the inhibition of P. sojae growth by PG.

Molecular Docking and Comparative Inhibitory Efficacy of Naturally Occurring Compounds on Vegetative Growth and Deoxynivalenol Biosynthesis in Fusarium culmorum

“…Propyl gallate 4, a food antioxidant, displayed a weak fungicidal effect against F. culmorum in vitro, despite its reported inhibitory activity against several fungi [60]. Differently from octyl gallate 5, propyl gallate 4 interacted in silico by activating H-bonds with the same set of amino acids identified in sites 1 and 2, albeit separately.…”

Allicin‐inspired disulfide derivatives containing quinazolin‐4(3H)‐one as a bacteriostat against Xanthomonas oryzae pv. oryzae

“…Finally, trypsin digestion, TMT mark, high‐performance liquid chromatography, liquid chromatography‐mass spectrometry analysis, and protein identification were performed (PTM Biolabs, China). To further evaluate the response of Xoo to compound 1 stress and speculate the potential antibacterial mechanism of compound 1 , enrichment analysis of the distribution of differential proteins in the GO (Gene Ontology) secondary annotation, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, and protein–protein interaction network analysis were performed 42,45,46 …”

“…[39][40][41] 2.6 Quantitative proteomics assay Tandem mass tags (TMT) labeled quantitative proteomics assay was carried out according to previously reported. [42][43][44] For the sample preparation, Xoo cells (OD 595 ≈ 0.1) and compound 1 (dosage: 10 μg mL −1 ) were co-incubated in NB medium in a shaker (250 rpm) at 28 °C until the negative control group grew to the logarithmic phase (OD 595 ≈ 0.6). After that, the resulted Xoo cells were collected to yield the total proteins.…”

“…Encyclopedia of Genes and Genomes) pathway, and proteinprotein interaction network analysis were performed. 42,45,46…”

Comparative Proteomic Analysis of Liver Tissues and Serum in db/db Mice

“…Recently, TMT (tandem mass tag)-labeling proteomic analysis has been recommended as a dependable method for accurately quantifying relative protein levels in complex samples due to its technical strengths such as good sensitivity, reproducibility, and signal-to-noise ratio [ 11 , 12 ]. Ample studies have employed this method to discover potential biomarkers that are closely correlated to the phenotypes of diseases including NAFLD [ 10 , 13 , 14 , 15 , 16 ].…”