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Data processing for fennel protein characterization by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS).

ABSTRACT: An untargeted shot-gun approach is described for the ultra-high-resolution analysis of fennel proteins by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) combined with a home-made Matlab search algorithm. The first step of the proposed bioinformatic strategy was the development of a custom-made fennel protein database, starting from the well-known, on-line available, protein NCBI database, under Foeniculum Vulgare organism, consisting of 231 total proteins. Partial and redundant forms of proteins, repeatedly included in the official NCBI database under different codes, were removed. In the final custom-made database, in addition to the 92 fennel specific non-redundant proteins, 10 proteins belonging to recognized allergenic sources associated with spice-mugwort-allergy syndrome (celery, carrot, parsley, birch, and mugwort) were also included. The second step was the in-silico enzymatic digestion, performed on all the 102 proteins, to obtain a theoretical list of m/z dataset of tryptic peptides. The Matlab processing data was the third and crucial step, necessary to search for in-silico mass calculated peptide sequences in the high resolution ICR mass spectra of the digested fennel extract. The final step was based on database searching in Peptide Mass Fingerprint (PMF) mode by using the matched m/z values as input data. The PMF search results confirmed the presence of 70 proteins (61 fennel specific and 9 allergenic proteins) inside the fennel extract.

SUBMITTER: Melfi MT

PROVIDER: S-EPMC8027264 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Dataset Information

Data processing for fennel protein characterization by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS).

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