Comparative Proteomic Analysis of saccharopolyspora spinosa SP06081 and PR2 strains reveals the differentially expressed proteins correlated with the increase of spinosad yield

Abstract

Background: Saccharopolyspora spinosa produces the environment-friendly biopesticide spinosad, a mixture of two polyketide-derived macrolide active ingredients called spinosyns A and D. Therefore considerable interest is in the improvement of spinosad production because of its low yield in wild-type S. spinosa. Recently, a spinosad-hyperproducing PR2 strain with stable heredity was obtained from protoplast regeneration of the wild-type S. spinosa SP06081 strain. A comparative proteomic analysis was performed on the two strains during the first rapid growth phase (RG1) in seed medium (SM) by using label-free quantitative proteomics to investigate the underlying mechanism leading to the enhancement of spinosad yield.

Results: In total, 224 proteins from the SP06081 strain and 204 proteins from the PR2 strain were unambiguously identified by liquid chromatography-tandem mass spectrometry analysis, sharing 140 proteins. A total of 12 proteins directly related to spinosad biosynthesis were identified from the two strains in RG1. Comparative analysis of the shared proteins revealed that approximately 31% of them changed their abundance significantly and fell in all of the functional groups, such as tricarboxylic acid cycles, glycolysis, biosynthetic processes, catabolic processes, transcription, translation, oxidation and reduction. Several key enzymes involved in the synthesis of primary metabolic intermediates used as precursors for spinosad production, energy supply, polyketide chain assembly, deoxysugar methylation, and antioxidative stress were differentially expressed in the same pattern of facilitating spinosad production by the PR2 strain. Real-time reverse transcriptase polymerase chain reaction analysis revealed that four of five selected genes showed a positive correlation between changes at the translational and transcriptional expression level, which further confirmed the proteomic analysis.

Conclusions: The present study is the first comprehensive and comparative proteome analysis of S. spinosa strains. Our results highlight the differentially expressed proteins between the two S. spinosa strains and provide some clues to understand the molecular and metabolic mechanisms that could lead to the increased spinosad production yield.

Figure 1

Growth-time curve of Saccharopolyspora spinosa SP06081 and PR2 strains in SM. RG, rapid growth phase; T, transition phase; S, stationary phase. Arrow indicates the time point chosen for biomass collection used for shotgun protein sample preparation and RNA isolation. Three replicates were performed for each strain. Error bars indicate standard error of the mean.

Figure 2

(a-c) Distribution of the identified proteins by LC-MS/MS. The distribution of total proteome showed (a) the overlap of proteins between SP06081 and PR2 strains, (b) the theoretical pI distribution of the total proteome, and (c) the Mw distribution of the total proteome.

Figure 3

Fold changes of functional categories of the total proteome between Saccharopolyspora spinosa SP06081 and PR2 strains. The total proteomes of (a) SP06081 and (b) PR2 strain protein set were classified into functional categories, and (c) the fold change of the different functional classes between these two sets was calculated as follows: the percentage of a specific category of the PR2 strain protein set divided by the percentage of that category in the SP06081 strain.

Figure 4

Fold changes of functional categories of the exclusive proteins between Saccharopolyspora spinosa SP06081 and PR2 strains. The proteins only expressed in (a) SP06081 and (b) PR2 strain were classified into functional categories, and (c) the fold change of the different functional classes between these two sets was calculated as follows: the percentage of a specific category of the PR2 strain protein set divided by the percentage of that category in the SP06081 strain.

Figure 5

Integrated proteome data onto a simplified metabolic network. I: TCA cycle; II: Glycolysis;III: SAM degradation pathway. Pathways and corresponding enzymes were identified from Swiss-Prot and TrEMBL databases, and only major reactions in each pathway are shown. Protein names are provided in Additional file 5: Table S6. Up or down arrows show the up- or down-regulation of proteins in PR2 strain, respectively. Abbreviations: PDGE1β, pyruvate dehydrogenase E1 component beta subunit; PEP, phosphoenolpyruvate; G6P, glucose-6-phosphate; RL5P, ribulose 5-phosphate; SAH, S-adenosyl-homocysteine; PFK, 6-phosphofructokinase; PK, pyruvate kinase; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; MMSAD, methylmalonate semialdehyde dehydrogenase (acylating); GS, glutamine synthetase; CS, citrate synthase; ACAT, acetyl-CoA acetyltransferase; MHM, 5-methyltetrahydropteroyltriglutamate-homocysteine methyltransferase; SCS, succinyl-CoA synthetase subunit alpha; UPS, uroporphyrinogen III synthetase; SAM, S-adenosylmethionine; PKS, polyketide synthase; L-Met, L-methionine; CoA, coenzyme A; NAD⁺, nicotinamide adenine dinucleotide; NADH, reduced form of nicotinamide adenine dinucleotide; NADP⁺, nicotinamide adenine dinucleotide phosphate; NADPH, reduced form of nicotinamide adenine dinucleotide phosphate.

Figure 6

Real-time RT-PCR analysis of selected genes. Quantitative real-time RT-PCR was used to substantiate differential expression patterns of five selected genes (CS, GS, MHM, SCS, and PK). mRNA levels after 48 h culture are expressed as relative values to sigA, arbitrarily setting the ratio values for the SP06081 sample to 1. Error bars are calculated from six independent determinations of mRNA abundance in each sample (see Methods section).