The transcriptome analysis on urea response mechanism in the process of ergosterol synthesis by Cordyceps cicadae

Nitrogen source is required for the growth of Cordyceps cicadae and involved in the regulation of metabolite synthesis. In order to further investigate the regulatory effects of nitrogen sources on the ergosterol synthesis by C. cicadae. We first confirmed that urea could significantly increase the ergosterol synthesis. The transcriptome analysis showed that compared with biomass cultured in the control fermentation medium (CFM), 1340 differentially expressed genes (DEGs) were obtained by Gene Ontology (GO) annotation, and 312 DEGs were obtained by Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation from the biomass cultured in CFM + CO(NH₂)₂. Urea up-regulated D-3-phosphoglycerate dehydrogenase gene transcription level and down-regulated enolase and L-serine/L-threonine ammonialyase gene transcription level, increased serine synthesis, allosterically activate pyruvate kinase, to promote the synthesis of pyruvate and CH₃CO ~ SCOA, the primer of ergosterol; Urea increase the genes transcription related with ergosterol synthesis by up-regulating the steroid regulatory element binding protein gene transcription levels. The transcriptome results were provided by those of qRT-PCR. Collectively, our finding provided valuable insights into the regulatory effect of nitrogen source on the ergosterol synthesis by C. cicadae.

Rapid determination of crocins in saffron by near-infrared spectroscopy combined with chemometric techniques

Saffron is an expensive spice. Its primary effective constituents are crocin I and II, and the contents of these compounds directly affect the quality and commercial value of saffron. In this study, near-infrared spectroscopy was combined with chemometric techniques for the determination of crocin I and II in saffron. Partial least squares regression models were built for the quantification of crocin I and II. By comparing different spectral ranges and spectral pretreatment methods (no pretreatment, vector normalization, subtract a straight line, multiplicative scatter correction, minimum-maximum normalization, eliminate the constant offset, first derivative, and second derivative), optimum models were developed. The root mean square error of cross-validation values of the best partial least squares models for crocin I and II were 1.40 and 0.30, respectively. The coefficients of determination for crocin I and II were 93.40 and 96.30, respectively. These results show that near-infrared spectroscopy can be combined with chemometric techniques to determine the contents of crocin I and II in saffron quickly and efficiently.

An image analysis of TLC patterns for quality control of saffron based on soil salinity effect: A strategy for data (pre)-processing

Quality of saffron, a valuable food additive, could considerably affect the consumers' health. In this work, a novel preprocessing strategy for image analysis of saffron thin layer chromatographic (TLC) patterns was introduced. This includes performing a series of image pre-processing techniques on TLC images such as compression, inversion, elimination of general baseline (using asymmetric least squares (AsLS)), removing spots shift and concavity (by correlation optimization warping (COW)), and finally conversion to RGB chromatograms. Subsequently, an unsupervised multivariate data analysis including principal component analysis (PCA) and k-means clustering was utilized to investigate the soil salinity effect, as a cultivation parameter, on saffron TLC patterns. This method was used as a rapid and simple technique to obtain the chemical fingerprints of saffron TLC images. Finally, the separated TLC spots were chemically identified using high-performance liquid chromatography-diode array detection (HPLC-DAD). Accordingly, the saffron quality from different areas of Iran was evaluated and classified.