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

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 developme...

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Published inData in brief Vol. 35; p. 106960
Main Authors Melfi, Maria Teresa, Kanawati, Basem, Schmitt-Kopplin, Philippe, Macchia, Luigi, Centonze, Diego, Nardiello, Donatella
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Inc 01.04.2021
Elsevier
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ISSN2352-3409
2352-3409
DOI10.1016/j.dib.2021.106960

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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.
AbstractList 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 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 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 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.
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.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.
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.
ArticleNumber 106960
Author Macchia, Luigi
Melfi, Maria Teresa
Centonze, Diego
Kanawati, Basem
Schmitt-Kopplin, Philippe
Nardiello, Donatella
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Keywords Fennel proteins
Peptide mass fingerprint
Custom-made protein database
Direct-infusion FT-ICR-MS
In-silico enzymatic digestion
Matlab data processing
Language English
License This is an open access article under the CC BY-NC-ND license.
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Snippet An untargeted shot-gun approach is described for the ultra-high-resolution analysis of fennel proteins by Fourier transform ion cyclotron resonance mass...
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StartPage 106960
SubjectTerms algorithms
allergenicity
Artemisia vulgaris
Betula
bioinformatics
carrots
celery
computer simulation
Custom-made protein database
Data
data collection
Direct-infusion FT-ICR-MS
fennel
Fennel proteins
Foeniculum vulgare
In-silico enzymatic digestion
mass spectrometry
Matlab data processing
parsley
Peptide mass fingerprint
peptides
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Title Data processing for fennel protein characterization by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS)
URI https://dx.doi.org/10.1016/j.dib.2021.106960
https://www.ncbi.nlm.nih.gov/pubmed/33855135
https://www.proquest.com/docview/2513247153
https://www.proquest.com/docview/2660976468
https://pubmed.ncbi.nlm.nih.gov/PMC8027264
https://doi.org/10.1016/j.dib.2021.106960
https://doaj.org/article/6461891641e7440a97c0ce8ac613a4c7
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