Extension of Diagnostic Fragmentation Filtering for Automated Discovery in DNA Adductomics
Development of high-resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC–MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2′-deoxyr...
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| Published in | Analytical chemistry (Washington) Vol. 93; no. 14; pp. 5754 - 5762 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
13.04.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0003-2700 1520-6882 1520-6882 |
| DOI | 10.1021/acs.analchem.0c04895 |
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| Abstract | Development of high-resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC–MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2′-deoxyribose or the nucleobases using data-dependent acquisition represents a powerful approach for the unbiased detection of DNA modifications (adducts). The lack of available bioinformatics tools necessitates manual processing of acquired spectral data and hampers high throughput application of these techniques. To address this limitation, we present an automated workflow for the detection and curation of putative DNA adducts by using diagnostic fragmentation filtering of LC–MS/MS experiments within the open-source software MZmine. The workflow utilizes a new feature detection algorithm, DFBuilder, which employs diagnostic fragmentation filtering using a user-defined list of fragmentation patterns to reproducibly generate feature lists for precursor ions of interest. The DFBuilder feature detection approach readily fits into a complete small-molecule discovery workflow and drastically reduces the processing time associated with analyzing DNA adductomics results. We validate our workflow using a mixture of authentic DNA adduct standards and demonstrate the effectiveness of our approach by reproducing and expanding the results of a previously published study of colibactin-induced DNA adducts. The reported workflow serves as a technique to assess the diagnostic potential of novel fragmentation pattern combinations for the unbiased detection of chemical classes of interest. |
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| AbstractList | Development of high-resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2'-deoxyribose or the nucleobases using data-dependent acquisition represents a powerful approach for the unbiased detection of DNA modifications (adducts). The lack of available bioinformatics tools necessitates manual processing of acquired spectral data and hampers high throughput application of these techniques. To address this limitation, we present an automated workflow for the detection and curation of putative DNA adducts by using diagnostic fragmentation filtering of LC-MS/MS experiments within the open-source software MZmine. The workflow utilizes a new feature detection algorithm, DFBuilder, which employs diagnostic fragmentation filtering using a user-defined list of fragmentation patterns to reproducibly generate feature lists for precursor ions of interest. The DFBuilder feature detection approach readily fits into a complete small-molecule discovery workflow and drastically reduces the processing time associated with analyzing DNA adductomics results. We validate our workflow using a mixture of authentic DNA adduct standards and demonstrate the effectiveness of our approach by reproducing and expanding the results of a previously published study of colibactin-induced DNA adducts. The reported workflow serves as a technique to assess the diagnostic potential of novel fragmentation pattern combinations for the unbiased detection of chemical classes of interest.Development of high-resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2'-deoxyribose or the nucleobases using data-dependent acquisition represents a powerful approach for the unbiased detection of DNA modifications (adducts). The lack of available bioinformatics tools necessitates manual processing of acquired spectral data and hampers high throughput application of these techniques. To address this limitation, we present an automated workflow for the detection and curation of putative DNA adducts by using diagnostic fragmentation filtering of LC-MS/MS experiments within the open-source software MZmine. The workflow utilizes a new feature detection algorithm, DFBuilder, which employs diagnostic fragmentation filtering using a user-defined list of fragmentation patterns to reproducibly generate feature lists for precursor ions of interest. The DFBuilder feature detection approach readily fits into a complete small-molecule discovery workflow and drastically reduces the processing time associated with analyzing DNA adductomics results. We validate our workflow using a mixture of authentic DNA adduct standards and demonstrate the effectiveness of our approach by reproducing and expanding the results of a previously published study of colibactin-induced DNA adducts. The reported workflow serves as a technique to assess the diagnostic potential of novel fragmentation pattern combinations for the unbiased detection of chemical classes of interest. Development of high-resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC–MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2′-deoxyribose or the nucleobases using data-dependent acquisition represents a powerful approach for the unbiased detection of DNA modifications (adducts). The lack of available bioinformatics tools necessitates manual processing of acquired spectral data and hampers high throughput application of these techniques. To address this limitation, we present an automated workflow for the detection and curation of putative DNA adducts by using diagnostic fragmentation filtering of LC–MS/MS experiments within the open-source software MZmine. The workflow utilizes a new feature detection algorithm, DFBuilder, which employs diagnostic fragmentation filtering using a user-defined list of fragmentation patterns to reproducibly generate feature lists for precursor ions of interest. The DFBuilder feature detection approach readily fits into a complete small-molecule discovery workflow and drastically reduces the processing time associated with analyzing DNA adductomics results. We validate our workflow using a mixture of authentic DNA adduct standards and demonstrate the effectiveness of our approach by reproducing and expanding the results of a previously published study of colibactin-induced DNA adducts. The reported workflow serves as a technique to assess the diagnostic potential of novel fragmentation pattern combinations for the unbiased detection of chemical classes of interest. Development of high resolution/accurate mass liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) methodology enables the characterization of covalently modified DNA induced by interaction with genotoxic agents in complex biological samples. Constant neutral loss monitoring of 2´-deoxyribose or the nucleobases using data-dependent acquisition represents a powerful approach for the unbiased detection of DNA modifications (adducts). The lack of available bioinformatics tools necessitates manual processing of acquired spectral data and hampers high throughput application of these techniques. To address this limitation, we present an automated workflow for the detection and curation of putative DNA adducts by using diagnostic fragmentation filtering of LC-MS/MS experiments within the open-source software MZmine. The workflow utilizes a new feature detection algorithm, DFBuilder, which employs diagnostic fragmentation filtering using a user-defined list of fragmentation patterns to reproducibly generate feature lists for precursor ions of interest. The DFBuilder feature detection approach readily fits into a complete small molecule discovery workflow and drastically reduces the processing time associated with analyzing DNA adductomics results. We validate our workflow using a mixture of authentic DNA adduct standards and demonstrate the effectiveness of our approach by reproducing and expanding the results of a previously published study of colibactin-induced DNA adducts. The reported workflow serves as a technique to assess the diagnostic potential of novel fragmentation pattern combinations for the unbiased detection of chemical classes of interest. |
| Author | Stornetta, Alessia Balbo, Silvia Murray, Kevin J Villalta, Peter W Carlson, Erik S Balskus, Emily P |
| AuthorAffiliation | Division of Environmental Health Sciences, School of Public Health University of Minnesota Department of Medicinal Chemistry Masonic Cancer Center Department of Chemistry and Chemical Biology |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33797876$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Adducts Algorithms Analytical chemistry Automation Bases (nucleic acids) Bioinformatics Biological properties Biological samples chemical bonding Chemistry computer software Data acquisition Deoxyribonucleic acid DNA DNA adducts Filtration Fragmentation Genotoxic chemicals Genotoxicity Hand tools Liquid chromatography Mass spectrometry Mass spectroscopy mutagens nucleobases Source code spectral analysis tandem mass spectrometry Workflow |
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| Title | Extension of Diagnostic Fragmentation Filtering for Automated Discovery in DNA Adductomics |
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