A novel integrated automatic strategy for amino acid composition analysis of seeds from 67 species.

The composition and quantity of amino acids (AAs) in seeds are complicated due to the various origins and modifications of different species. In this study, a novel automatic neutral loss filtering (ANLF) strategy based on accurate mass searching by Python was developed to analyze the free and hydrolyzed AA-phenyl isothiocyanate (PITC) derivatives from seeds of Gymnosperm and Angiosperm phyla. Compared with traditional strategies, ANLF showed much higher accuracy in screening AA derivatives by filtering nitrogen-containing non-AA compounds and efficiency in processing large datasets. Meanwhile, the content phenotype of 20 proteinogenic AAs from seeds of these two families was characterized by a 35-min HPLC method combined with an automated peak-matching strategy. AA profiles of 232 batches of seeds from 67 species, consisting of 19 proteinogenic AAs, 21 modified AAs, and 77 unknown AAs, would be a good reference for their application in food and medicine.

Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics.

Animal-derived drugs are an indispensable part of folk medicine worldwide. However, their chemical constituents are poorly approached, which leads to the low level of the quality standard system of animal-derived drugs and further causes a chaotic market. Natural peptides are ubiquitous throughout the organism, especially in animal-derived drugs. Thus, in this study, we used multi-source leeches, including Hirudo nipponica (HN), Whitmania pigra (WP), Whitmania acranulata (WA), and Poecilobdella manillensis (PM), as a model. A strategy integrating proteogenomics and novel pseudotargeted peptidomics was developed to characterize the natural peptide phenotype and screen for signature peptides of four leech species. First, natural peptides were sequenced against an in-house annotated protein database of closely related species constructed from RNA-seq data from the Sequence Read Archive (SRA) website, which is an open-sourced public archive resource. Second, a novel pseudotargeted peptidomics integrating peptide ion pair extraction and retention time transfer was established to achieve high coverage and quantitative accuracy of the natural peptides and to screen for signature peptides for species authentication. In all, 2323 natural peptides were identified from four leech species whose databases were poorly annotated. The strategy was shown to significantly improve peptide identification. In addition, 36 of 167 differential peptides screened by pseudotargeted proteomics were identified, and about one-third of them came from the leucine-rich repeat domain (LRR) proteins, which are widely distributed in organisms. Furthermore, six signature peptides were screened with good specificity and stability, and four of them were validated by synthetic standards. Finally, a dynamic multiple reaction monitoring (dMRM) method based on these signature peptides was established and revealed that one-half of the commercial samples and all of the Tongxinluo capsules were derived from WP. All in all, the strategy developed in this study was effective for natural peptide characterization and signature peptide screening, which could also be applied to other animal-derived drugs, especially for modelless species that are less studied in protein database annotation.

Identification of Five Gelatins Based on Marker Peptides from Type I Collagen by Mass Spectrum in Multiple Reaction Monitoring Mode.

In this study, a novel pseudo-targeted peptidomics strategy, integrating the transition list generated by an in-house software (Pep-MRMer) and the retention time transfer by high-abundance ion-based retention time calibration (HAI-RT-cal), was developed to screen marker peptides of gelatins from five closely related animal species, including porcine, bovine, horse, mule, and donkey. Five marker peptides were screened from the molecular phenotypic differences of type I collagen. Furthermore, a simple and robust 10 min multiple reaction monitoring (MRM) method was established and performed well in distinguishing different gelatins, particularly in discerning horse-hide gelatin (HHG) and mule-hide gelatin (MHG) from donkey-hide gelatin (DHG). The market investigation revealed the serious adulteration of DHG. Meantime, the pseudo-targeted peptidomics could be used to screen marker peptides of other gelatin foods.