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1.
Chem Res Toxicol ; 36(9): 1471-1482, 2023 09 18.
Article in English | MEDLINE | ID: mdl-37566384

ABSTRACT

Adductomics studies are used for the detection and characterization of various chemical modifications (adducts) of nucleic acids and proteins. The advancements in liquid chromatography coupled with high-resolution tandem mass spectrometry (HRMS/MS) have resulted in efficient methods for qualitative and quantitative adductomics. We developed an HRMS-based method for the simultaneous analysis of RNA and DNA adducts in a single run and demonstrated its application using Baltic amphipods, useful sentinels of environmental disturbances, as test organisms. The novelty of this method is screening for RNA and DNA adducts by a single injection on an Orbitrap HRMS instrument using full scan and data-independent acquisition. The MS raw files were processed with an open-source program, nLossFinder, to identify and distinguish RNA and DNA adducts based on the characteristic neutral loss of ribonucleosides and 2'-deoxyribonucleosides, respectively. In the amphipods, in addition to the nearly 150 putative DNA adducts characterized earlier, we detected 60 putative RNA adducts. For the structural identification of the detected RNA adducts, the MODOMICS database was used. The identified RNA adducts included simple mono- and dimethylation and other larger functional groups on different ribonucleosides and deaminated product inosine. However, 54 of these RNA adducts are not yet structurally identified, and further work on their characterization may uncover new layers of information related to the transcriptome and help understand their biological significance. Considering the susceptibility of nucleic acids to environmental factors, including pollutants, the developed multi-adductomics methodology with further advancement has the potential to provide biomarkers for diagnostics of pollution effects in biota.


Subject(s)
DNA Adducts , RNA , DNA , Tandem Mass Spectrometry/methods , Chromatography, Liquid
2.
Environ Sci Technol ; 57(29): 10591-10603, 2023 07 25.
Article in English | MEDLINE | ID: mdl-37341092

ABSTRACT

Exposure to chemical pollution can induce genetic and epigenetic alterations, developmental changes, and reproductive disorders, leading to population declines in polluted environments. These effects are triggered by chemical modifications of DNA nucleobases (DNA adducts) and epigenetic dysregulation. However, linking DNA adducts to the pollution load in situ remains challenging, and the lack of evidence-based DNA adductome response to pollution hampers the development and application of DNA adducts as biomarkers for environmental health assessment. Here, we provide the first evidence for pollution effects on the DNA modifications in wild populations of Baltic sentinel species, the amphipod Monoporeia affinis. A workflow based on high-resolution mass spectrometry to screen and characterize genomic DNA modifications was developed, and its applicability was demonstrated by profiling DNA modifications in the amphipods collected in areas with varying pollution loads. Then, the correlations between adducts and the contaminants level (polycyclic aromatic hydrocarbons (PAHs), trace metals, and pollution indices) in the sediments at the collection sites were evaluated. A total of 119 putative adducts were detected, and some (5-me-dC, N6-me-dA, 8-oxo-dG, and dI) were structurally characterized. The DNA adductome profiles, including epigenetic modifications, differed between the animals collected in areas with high and low contaminant levels. Furthermore, the correlations between the adducts and PAHs were similar across the congeners, indicating possible additive effects. Also, high-mass adducts had significantly more positive correlations with PAHs than low-mass adducts. By contrast, correlations between the DNA adducts and trace metals were stronger and more variable than for PAHs, indicating metal-specific effects. These associations between DNA adducts and environmental contaminants provide a new venue for characterizing genome-wide exposure effects in wild populations and apply DNA modifications in the effect-based assessment of chemical pollution.


Subject(s)
DNA Adducts , Polycyclic Aromatic Hydrocarbons , Animals , DNA , Environmental Pollution/analysis , Geologic Sediments/chemistry
3.
Toxics ; 9(4)2021 Apr 07.
Article in English | MEDLINE | ID: mdl-33916914

ABSTRACT

DNA adductomics is a relatively new omics approach aiming to measure known and unknown DNA modifications, called DNA adducts. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the most common method for analyzing DNA adducts. Recent advances in the field of mass spectrometry have allowed the possibility to perform a comprehensive analysis of adducts, for instance, by using a nontargeted data-independent acquisition method, with multiple precursor m/z windows as an inclusion list. However, the generated data are large and complex, and there is a need to develop algorithms to simplify and automate the time-consuming manual analysis that has hitherto been used. Here, a graphical user interface (GUI) program was developed, with the purpose of tracking a characteristic neutral loss reaction from tandem mass spectrometry of the nucleoside adducts. This program, called nLossFinder, was developed in the MATLAB platform, available as open-source code. Calf thymus DNA was used as a model for method optimization, and the overall adductomics approach was applied to DNA from amphipods (Monoporeia affinis) collected within the Swedish National Marine Monitoring Program. In the amphipod DNA, over 150 putative adducts were found in comparison to 18 using a manual approach in a previous study. The developed program can improve the processing time for large MS data, as it processes each sample in a few seconds, and hence can be applicable for high-throughput screening of adducts.

4.
Anal Bioanal Chem ; 410(21): 5229-5235, 2018 Aug.
Article in English | MEDLINE | ID: mdl-29947907

ABSTRACT

Chromatographic retention time peak shifts between consecutive analyses is a well-known fact yet not fully understood. Algorithms have been developed to align peaks between runs, but with no specific studies considering the causes of peak shifts. Here, designed experiments reveal chromatographic shift patterns for a complex peptide mixture that are attributable to the temperature and pH of the mobile phase. These results demonstrate that peak shifts are highly structured and are to a high degree explained by underlying differences in physico-chemical parameters of the chromatographic system and also provide experimental support for the alignment algorithm called the generalized fuzzy Hough transform which exploits this fact. It can be expected that the development of alignment algorithms enters a new phase resulting in increasingly accurate alignment by considering the latent structure of the peak shifts.

5.
Chem Res Toxicol ; 30(5): 1157-1167, 2017 05 15.
Article in English | MEDLINE | ID: mdl-28398741

ABSTRACT

Electrophilic compounds/metabolites present in humans, originating from endogenous processes or exogenous exposure, pose a risk to health effects through their reactions with nucleophilic sites in proteins and DNA, forming adducts. Adductomic approaches are developed to screen for adducts to biomacromolecules in vivo by mass spectrometry (MS), with the aim to detect adducts corresponding to unknown exposures from electrophiles. In the present study, adductomic screening was performed using blood samples from healthy children about 12 years old (n = 51). The frequencies of micronuclei (MN) in erythrocytes in peripheral blood were monitored as a measure of genotoxic effect/genotoxic exposure. The applied adductomic approach has been reported earlier by us and is based on analysis of N-terminal valine adducts in hemoglobin (Hb) by liquid chromatography tandem mass spectrometry (LC-MS/MS). High resolution MS was introduced for refined screening of previously unknown N-terminal Hb adducts. Measured adduct levels were compared with MN frequencies using multivariate data analysis. In the 51 individuals, a total of 24 adducts (whereof 12 were previously identified) were observed and their levels quantified. Relatively large interindividual variations in adduct levels were observed. The data analysis (with partial least-squares regression) showed that as much as 60% of the MN variation could be explained by the adduct levels. This study, for the first time, applies the combination of these sensitive methods to measure the internal dose of potentially genotoxic chemicals and genotoxic effects, respectively. The results indicate that this is a valuable approach for the characterization of exposure to chemical risk factors for the genotoxic effects present in individuals of the general population.


Subject(s)
DNA Adducts/metabolism , Hemoglobins/metabolism , Micronucleus Tests , Child , Chromatography, Liquid , Environmental Exposure , Humans , Mutagens/toxicity , Tandem Mass Spectrometry
6.
Anal Bioanal Chem ; 406(7): 1985-98, 2014 Mar.
Article in English | MEDLINE | ID: mdl-24429977

ABSTRACT

Extraction of qualitative and quantitative information from large numbers of analytical signals is difficult with drifted baselines, particularly in multivariate analysis. Baseline drift obscures and "fuzzies" signals, and even deteriorates analytical results. In order to obtain accurate and clear results, some effective methods should be proposed and implemented to perform baseline correction before conducting further data analysis. However, most of the classic methods require user intervention or are prone to variability, especially with low signal-to-noise signals. In this study, a novel baseline correction algorithm based on quantile regression and iteratively reweighting strategy is proposed. This does not require user intervention and prior information, such as peak detection. The iteratively reweighting strategy iteratively changes weights of residuals between fitted baseline and original signals. After a series of tests and comparisons with several other popular methods, using various kinds of analytical signals, the proposed method is found to be fast, flexible, robust, and easy to use both in simulated and real datasets.

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