Comparative analysis of different transformed Saccharomyces cerevisiae strains based on high-throughput Fourier transform infrared spectroscopy

•FT-MIR spectroscopy associated to high-throughput tool, allowed to distinguish different transformed yeast strains.•PCA allowed the analysis of the cellular metabolism related to heterologous cyprosin production based on clusters formed.•PC loadings vectors revealed the biochemical compounds differences in both expression systems.•The ratio bands can be useful to compare expression systems.•FT-MIR spectroscopy and the chemometric techniques can be used to screen and select the optimum expression system. This study shows the application of the Fourier transform mid-infrared spectroscopy (FT-MIR) associated with high-throughput technology to study the biochemical fingerprints of different Saccharomyces cerevisiae strains transformed with the same expression system along the similar cultivation in bioreactor. The phenotype, as well as the cellular metabolism and recombinant cyprosin biosynthesis, were determined. The differences observed were confirmed by conventional cyprosin activity protocol, and the metabolic evolution was analyzed using high-performance liquid chromatography technique. The spectral analysis based on chemometrics tools, such as the principal component analysis, is a useful methodology for the phenotypes characterization as well as the specific metabolic states along the cultivations according to the clusters created. The ratio bands of spectra also represented a useful tool to evaluate the metabolic and biochemical differences between both expression systems, allowing to have an additional parameter to the biomolecular comparison. Therefore, high-throughput FT-MIR spectroscopy associated with multivariate data analysis represent a valuable strategy for extracting significant specific biomolecular information along the cultivation, providing a complete bioprocess analysis, once it detects slight molecular changes which it will be useful for screening and optimization process in the biotechnological or pharmaceutical industry.