Total protein extraction of Streptomyces luteogriseus in different fermentation times was analyzed in order to discover the enzymes associated with Maituolaimysin biosynthesis, make the biosynthesis pathway clear, and enhance its production. Two-dimensional gel electrophoresis analysis showed that 8 proteins were up-expressed, 5 were down-expressed, 6 were new-expressed and 6 disappeared in the protein extraction of 48 h compared with that of 36 h. Fifteen of the different expression proteins were analyzed by Matrix-Assisted Laser Desorption Ionization(MALDI)Time-of-Flight(TOF) mass spectrum and 4 of them were identified. Among the 4 identified proteins, one was involved in protein biosynthesis; one was associated with Streptomyces differentiation; one was a key enzyme in TCA circle and another one was a hypothetical protein whose function was unknown.Investigation of the function of these identified proteins suggested that they all had direct or indirect relations to Maituolaimysin biosynthesis, and especially, the protein Clp2 could accelerate the differentiation of Streptomyces, which would directly result in Maituolaimysin biosynthesis.
A novel OSC-KPCA based pattern analysis method was proposed to improve the clustering and predictive performance of the metabolomics.The strong nonlinear pattern recognition power and the predominance in dealing with small high-dimensional data of the Kernel Principal Component Analysis(KPCA)were used here to analyze four genotypes of the important model plant—Arabidopsis thaliana.In order to improve the performance of PR(Pattern Recognition),the Orthogonal Signal Correction(OSC)method was used to filter the original data firstly to eliminate the interference of noise.The PR results showed that the OSC-KPCA based PR method could reveal the underlying relationship between genotypes and metabolites successfully.The paternal genotypes(Co10 and C24)and the two F1 progeny C24×Co10 and Co10×C24 could be 100% correctly discriminated.More importantly the predictability was also as high as 100%.