Abstract
Adductomics, an emerging field within the 'omics sciences, focuses on the formation and prevalence of DNA, RNA, and protein adducts induced by endogenous and exogenous agents in biological systems. These modifications often result from exposure to environmental pollutants, dietary components, and xenobiotics, impacting cellular functions and potentially leading to diseases such as cancer. This review highlights advances in mass spectrometry (MS) that enhance the detection of these critical modifications and discusses current and emerging trends in adductomics, including developments in MS instrument use, screening techniques, and the study of various biomolecular modifications from mono-adducts to complex hybrid crosslinks between different types of biomolecules. The review also considers challenges, including the need for specialized MS spectra databases and multi-omics integration, while emphasizing techniques to distinguish between exogenous and endogenous modifications. The future of adductomics possesses significant potential for enhancing our understanding of health in relation to environmental exposures and precision medicine.
Keywords: Adductomics, Adducts, Crosslinks, DNA, RNA, Protein, Exposome, High-resolution mass spectrometry, Post-data analysis
Graphical Abstract
1. Introduction
Adducts are covalent modifications to macromolecules (such as DNA, RNA, or proteins) resulting from environmental exposures and/or endogenous cellular processes, potentially altering the function and integrity of macromolecules. Such adducts predominantly result from interactions with diverse physicochemical agents. These agents, often of exogenous origin, include a spectrum of elements that range from ionizing and non-ionizing radiation to dietary components, lifestyle factors, environmental pollutants, and xenobiotics [1-4]. Molecules within cells can suffer direct or indirect damage; for instance, certain xenobiotics (e.g., aldehydes and ethylene oxide) [5, 6] can directly cause damage by binding with cellular components, whereas others (e.g., mycotoxins and nitrosamines) [7] must be metabolically converted into reactive metabolites that then covalently bind with cellular molecules, leading to alterations in cell structure and function [7]. Moreover, internal agents such as reactive oxygen species (ROS), which are byproducts of normal respiratory activities, can lead to the formation of oxidatively damaged DNA/RNA and other macromolecular alterations [8, 9]. In addition, some modifications may have a functional role, such as those arising from canonical cellular processes, such as epigenetic mechanisms (e.g., DNA methylation and RNA post-transcriptional modifications [10], and protein post-translational modification [11]), are not classified as damage. Conversely, “accidental” covalent alterations (i.e., those not arising from processes or exposures that are canonical, or escape cellular control) are often considered cellular damage and may be referred to as adducts [12]. Yet, distinguishing between these in situations where the distinction is unclear requires a deep understanding of the underlying circumstances. The dynamic interplay between functional and accidental modifications and their implications for health and disease is complex and still under thorough investigation [13].
Among the variety of macromolecular adducts, DNA adducts play a crucial role in the development of cancer [14]. During DNA replication, adducts can lead to incorrect base pairing, resulting in mutations that become permanent changes in the DNA sequence if not repaired [15]. These mutations can disrupt the normal function of genes involved in cell cycle regulation, DNA repair, and apoptosis. Consequently, the cumulative effect of these mutations over time can contribute to the progression and aggressiveness of cancer, highlighting the importance of studying and understanding DNA adducts in cancer research [16]. Moreover, their presence can serve as internal biomarkers for assessing exposure to carcinogens and the risk of cancer development, aiding in both prevention and early detection [5, 17]. Additionally, within the domain of epigenetic DNA modification, more than seven types of DNA methylation modifications have been identified to date, each reported to play a unique role in gene expression and cellular function [18].
Various biotypes of cellular RNA molecules exist, including transfer RNA (tRNA), messenger RNA (mRNA), ribosomal RNA (rRNA), long noncoding RNA (lncRNA), small nuclear RNA (snRNA) and more [19]. Currently, over 170 distinct post-transcriptional RNA modifications have been identified [20]. These modifications to RNA can influence its stability, translation, and even splicing, potentially leading to altered cellular functions and contributing to pathogenesis [21]. RNA resides in both the cytoplasm and the nucleus, with that in the cytoplasm being particularly susceptible to adduction by both external and internal electrophiles. In addition to post-transcriptional modifications, RNA nucleobases can be chemically altered at their nucleophilic sites through interactions with electrophilic reactive compounds or metabolites. When “accidental” adducts are formed, the affected RNA is linked to a range of diseases, including cancer, hepatitis, nephropathy, and neurodegenerative diseases [22, 23]. It has been shown that some RNA adducts form as the corresponding equivalents to DNA adducts in the same cell [24] and that RNA is more susceptible to damage than DNA [8]. Several factors contribute to the higher occurrence of RNA adducts compared to DNA adducts: [22, 25]: (i) the nuclear membrane acts as a selective barrier, potentially restricting the access of electrophiles to DNA, thus making RNA more susceptible; (ii) the cytosol, where RNA predominantly resides, often contains reactive metabolites; (iii) unlike DNA, which is densely packed within chromatin and enveloped by histones, RNA has a more open structure, rendering it more vulnerable to electrophilic attacks; furthermore, the double-helical and hydrogen-bonded nature of DNA decreases the availability of its nucleobases to react with electrophiles compared to RNA; and (iv) a more effective system of highly redundant DNA repair pathways plays a role in limiting the persistence of DNA adducts [26]. In contrast, pathways for the repair of RNA appear to be more limited, and is a topic much less well studied [27, 28].
Like RNA, proteins undergo post-translational modification. Currently, more than 500 distinct modifications have been identified across all 20 protein amino acids [29]. Like DNA and RNA, proteins can also be covalently altered by xenobiotics, including drugs, toxicants, and their metabolites, at their active amino acid sites, leading to protein adduction [30]. These protein adducts can alter the protein's structure and function, impacting crucial cellular functions such as enzyme activity (including DNA repair [31]), signal transduction, and immune responses [32]. The accumulation of certain protein adducts is associated with diseases like Alzheimer's [33] and Parkinson's [34] diseases, where protein misfolding and aggregation play a key role. Including the analysis of protein adducts enriches our understanding of DNA and RNA adducts through common mechanisms of binding with electrophilic substances and by providing a more comprehensive view of the cellular burden of reactive species and their consequences. It also helps elucidate differences in adduct half-lives, sensitivity to damaging agents, and potential roles in a variety of diseases. Such integration would enhance our ability to trace specific exposures and their associated disease risks. This emphasizes the importance of collaborative research efforts in these different, but complementary, adduct domains.
Mass spectrometry (MS) analysis is particularly notable for providing reliable qualitative and quantitative information about adducts, excelling in identifying their chemical structure and composition due to its high sensitivity and specificity [35]. Coupled with liquid chromatographic (LC) techniques, LC-MS effectively separates and identifies complex mixtures, enhancing accuracy in analyzing adducts within biological matrices [36]. When analyzing DNA, RNA, and protein adducts, MS delivers precise information about the varieties, positions, and quantities of the modifications. Despite this, the prevailing research often relies on targeted analysis that identifies only specific or a small number of adducts. Although valuable, such methods do not capture the complete spectrum of adducts present in the cell, and consequently, the full range of exposures. The ‘adductome’ refers to the totality of adducts (modifications) that are present in DNA, RNA, or proteins found within the cell/tissue/organ/organism (or a particular matrix, such as urine), thereby offering a crucial window into the molecular changes induced by various environmental and biological factors [37, 38]. To comprehensively analyze these modifications, researchers are progressively employing sophisticated MS profiling technologies, with a particular emphasis on the introduction of high-resolution mass spectrometry (HRMS) [39, 40]. These refined MS methods enable the detailed identification and quantification of a wide range of adducts simultaneously, thereby facilitating a deeper understanding of the complex interplay between an organism and its exposure to various agents [41].
The ‘exposome’ represents the complete range of external and internal exposures that an individual experiences over their lifetime, conceivably capturing the complex interaction between these exposures and their biological effects [42, 43]. Previous biomonitoring research primarily employed targeted analyses focusing on specific, known agents to characterize exposures. However, individuals encounter a wide variety of endogenous and exogenous compounds in daily life, often numbering in the thousands [44]. Consequently, once these agents enter the body, complexities in exposure arise. Targeted analytical methods fall short in adequately depicting the totality of exposures and hence prevent establishing connections to consequent health impacts [45]. The emerging field of untargeted analyses presents a substantial opportunity in this context. To accurately dissect the multiple, complex exposures that comprise the exposome, it is imperative to integrate a variety of ‘omics analytical techniques for a thorough surveillance of exposure hazards [46]. Key to this process is the development of multi-adductomics, which encompasses the modifications of DNA, RNA, and proteins (see Figure 1) [38]. The multi-adductome serves as a vital molecular mediator, linking the various exposures comprising the exposome to their distinct biochemical and pathophysiological effects within individuals [47].
Figure 1.
The influence of the exposome on cellular molecular modifications. The exposome, comprising external and internal factors, comprises a wide range of diverse exposures over an individual's lifetime. Agents derived from the exposome can potentially modify or damage key biomolecules such as DNA, RNA, and proteins. These modifications can negatively impact cellular function and may contribute to the onset of diseases within the organism. Reprinted and modified with permission from Ref. [38] with permission from Elsevier.
By conducting detailed investigations that incorporate the concept of top-down analysis to map the full spectrum of modifications caused by reactive agents in the body, we can uncover both the type and extent of individual exposures [48]. Figure 2 illustrates the process of using top-down adductomics to trace and identify modifications in biomolecules, resulting from exposure to various endogenous/exogenous factors, by detecting unique adduct patterns through LC-MS analysis. The arising adductome maps are presented in a three-dimensional visualization format. On the left Y-axis, the mass-to-charge ratios (m/z) are indicated, while the retention times (RT) are positioned on the X-axis. The intensity of the peaks is represented by the varying color intensity of the dots. A detailed examination of the adductome maps offers insights into how both external and internal chemicals contribute to the onset of diseases, including various types of cancer. This analysis can explore the complex interactions between these chemicals and biological systems, uncovering their potential roles in initiating or exacerbating disease processes [38, 49].
Figure 2.
The concept of the top-down approach in MS-based adductomics. It aims to associate external and internal exposures with disease risks, which involves the analysis of modifications in crucial biomolecules within the body, enabling the tracing of these modifications back to their sources of exposure. This process reveals the pathways through which exposures contribute to specific diseases.
This review article summarizes the field of MS-based adductomics, focusing on the analysis of modifications in DNA, RNA, and proteins. As a consequence, we cover a wide range of modifications, including altered nucleosides in DNA and RNA, modified amino acids (AA), together with various crosslinks between DNA, RNA, and proteins, such as DNA-DNA and RNA-RNA crosslinks, and “hybrid” crosslinks i.e., those formed between two different macromolecules e.g., DNA-RNA, DNA-protein, and RNA-protein crosslinks), as shown in Figure 3. Furthermore, our review explores recent trends in MS-based adductomics methods and their significance towards dissecting the exposome. This review does not include protein-protein crosslinks (PPCL) studies as these studies mainly rely on proteomic techniques, which constitute another significant area, and have been reviewed extensively [47, 50, 51].
Figure 3.
Examples of various types of modifications in DNA, RNA, and proteins including modified (2'-deoxy)ribonucleosides (2'-dN/rN, respectively), modified amino acids (AA), and crosslinks between DNA-DNA (DDCL), RNA-RNA (RRCL), protein-protein (PPCL), and hybrid crosslinks between DNA-RNA (DRCL), DNA-protein (DPCL), and RNA-protein (RPCL).
2. Analytical trends in adductomics
Various LC-MS methods have been applied to adductome studies over the years. The pioneering research using MS for untargeted analysis emerged in 1992, utilizing triple-quadrupole MS (QqQ-MS) to investigate unknown DNA adducts through the neutral loss of 2-deoxyribose (dR) [52, 53]. The term ‘adductome’ was first introduced by Kanaly et al. in 2006 [54], with an initial focus on cellular DNA adductomics. Since then, fewer than a hundred research articles on MS-based DNA, RNA, and protein adductomics have been published, according to a search in the 'Web of Science' database. The search involved identifying journal articles using the following combination of keywords: (DNA OR RNA OR protein OR nucleoside OR amino acid) AND (adductom* OR crosslink*) AND (mass spectrometr*) NOT (protein-protein) after 2006. These articles were subsequently reviewed in detail manually to refine the results further. For articles published prior to 2006, collection entirely relied on the search and evaluation conducted by the authors' group. In the initial years up to 2009, publications on adductome analysis using MS were rare, but from 2010 onwards, there has been a significant increase (Figure 4A), reflecting the growing integration and advancement of MS in adductome studies. Figure 4B shows the different types of biomolecular modifications analyzed, with DNA (43.5%, 50/115) and proteins (32.2%, 37/115) being the most frequently studied.
Figure 4.
Representation of the number of publications describing MS-based adductome research with data compiled up to February 29, 2024. Publications in 2024 are included in the count for 2023. (A) the trend of MS-based adductome research with the number of published articles per year, (B) the types of macromolecular modifications studied, with DNA adducts representing the main type of adducts studied, (C) the trend of LRMS and HRMS employed with the number of published articles per year, (D) the types and scan modes of LRMS used, and (E) the types and scan modes of HRMS used.
As shown in Figure 4C, since 2014, there has been a marked trend towards the adoption of HRMS from low-resolution mass spectrometry (LRMS) in MS-based adductomics research. HRMS stands out for its mass analyzer, which possesses a resolving power exceeding 10,000 at m/z 400, defined as m/Δm50%, where Δm50% denotes the peak width at half its maximum height. This contrasts with LRMS, where the resolving power is generally below 10,000, potentially hindering its ability to distinguish between closely spaced m/z peaks [55]. For the LRMS-based adductomics (Figure 4D), the QqQ-MS is the dominant choice, with constant neutral loss (CNL) and pseudo CNL being the preferred scanning techniques. For HRMS (Figure 4E), hybrid configurations have significantly enhanced the analytical capabilities of these instruments for complex screening tasks. The Orbitrap, frequently combined with either a quadrupole (Q) or linear ion trap (LIT) as the initial mass analyzer (i.e., Q-Orbitrap or LIT-Orbitrap), or more recently, in tribrid configurations (i.e., Q-LIT-Orbitrap), is highly favored in adductomics. These advanced HRMS systems, whether in hybrid or tribrid form, play a crucial role in uncovering essential structural details by producing high-resolution accurate-mass product ion spectra in multistage fragmentation (MSn) experiments, making them extremely valuable for identifying and characterizing unknown adducts [35, 56].
3. MS-based DNA/RNA adductomics
Following the isolation of DNA or RNA from cells, enzymatic hydrolysis is used to break them down into nucleosides. Each nucleoside consists of three distinct components: the modifying group, the nucleobase (nB), and the sugar moiety, which is 2-deoxyribose (dR) in the case of DNA and ribose (R) for RNA. Positive ion mode is commonly favored for nucleoside detection by LC-MS due to the absence of phosphates on nucleosides following complete DNA/RNA hydrolysis to the nucleoside building block. The ionization of nucleosides capitalizes on the basic character of the nucleobases, which are easily ionized through protonation [24, 57]. In DNA adductomics, a fundamental feature common to 2'-deoxyribonucleosides (2'-dN) is a deoxyribose moiety connected to a nucleobase through a glycosidic bond. During collision-induced fragmentation in positive ionization mode, the mass spectra of structurally modified DNA nucleosides primarily exhibit the breaking of this glycosidic bond and the subsequent neutral loss (NL) of the dR, resulting in protonated nucleobases. LC-MS2 facilitates the characterization of the DNA adductome by tracking the NL of dR, which is 116 Da for LRMS or 116.0473 Da for HRMS from positively charged 2'-dN adducts (see Figure 5A). Additionally, the production of the [dR + H]+ ion during the collision-induced fragmentation of nucleosides has been recently utilized for screening DNA adducts [58, 59]. In RNA adductomics, the approach builds on the understanding that modified ribonucleosides (rN) undergo breakdown in MS through their N-glycosidic bonds in a manner similar to 2'-dN, leading to the formation of protonated nucleobase adducts through the neutral loss of R (132 Da for LRMS or 132.0422 Da for HRMS, see Figure 5B) [24, 60].
Figure 5.
Overview of the fragmentation patterns of DNA/RNA adducts utilized in DNA/RNA adductomics via MS techniques. After enzymatic hydrolysis of DNA and RNA, the resulting nucleosides (2'-dN and rN, respectively) are composed of three components: the nucleobase (depicted as 'B' within a square in the figure), a modifying component (M), and the sugar ring, which is either dR for DNA, or R (or MeR) for RNA. (A) The dominant fragmentation pathway of 2'-dN adducts. (B) The dominant fragmentation pathway of rN adducts. (C) Two major fragmentation pathways exist for modified nB fragments: (i) further fragmentation, leading to the loss of the nucleobases themselves with the fragment ion of the modification itself ([M + H]+), and/or (ii) generation of the characteristic product ions of the nucleobases with a neutral loss of the modification itself (M Da). This original figure was created for this review, incorporating concepts from Refs. [58, 60, 71].
The addition of a methyl group to the 2'-OH position on the ribose sugar, known as ribose 2'-O-methylation (MeR), is a common modification observed in various forms of RNA, including rRNA, tRNA, snRNA, and more recently, mRNA [61]. This methylated modification can occur in all four standard nucleosides and various non-canonical nucleosides, making their presence and patterns in RNA molecules potentially significant for both health and disease scenarios. These modifications can impact RNA stability, translation efficiency, and the overall gene expression profile, which, in turn, can influence cellular function and organismal health [62]. In most cases, the preferred protonation sites or tautomeric forms of the 2′-O-methylated nucleosides parallel their canonical and modified RNA nucleoside analogues. While 2'-O-methylated nucleosides exhibit greater glycosidic bond stability compared to their RNA analogues, the predominant fragmentation pattern upon collision remains the loss of MeR [63, 64]. The unique loss of MeR, characterized by a mass of 146.0579 Da, presents special opportunities in RNA adductomics, as illustrated in Figure 5B. However, to date, only two studies have been reported to have applied this method, which involves the neutral loss of both a R and a MeR group, for a comprehensive examination of RNA modifications [58, 65].
The major fragment (product) ion, representing the modified nB part of the adduct, may undergo further fragmentation in LC-MSn analysis (Figure 5C). Recent studies have advanced the DNA/RNA adductomic method by integrating the conventional tracking of dR/R/MeR neutral loss and expanding this to detect the neutral loss of the nucleobase itself, a typical fragmentation pattern for nucleobase adducts [58, 66, 67], as shown in Figure 5C for pathway I. This dual screening enables the simultaneous identification of both nucleoside adducts and their corresponding aglycone nucleobases. Moreover, several studies [6, 57, 68, 69] have demonstrated that guanine-associated adducts frequently produce specific ions (m/z 152.0566; [guanine + H]+), while adenine-associated adducts could yield characteristic ions (m/z 136.0617; [adenine + H]+). Limited research [70] has demonstrated that cytosine- and thymine-associated adducts exhibit similar patterns to those of guanine- and adenine-associated adducts. However, if all four nucleobases show the same pattern of these characteristic ions, this technique may be extended to encompass all four DNA/RNA nucleobases (Figure 5C, pathway II) by detecting aglycone nucleobase ions themselves [58, 71], thereby complementing the nucleobase neutral loss approach.
This review emphasizes the utilization of an untargeted approach, referred to as 'untargeted adductomics', to explore the complex interactions between the body and reactive electrophiles by comprehensively investigating the diverse chemical modifications initiated by these agents. Conversely, the fragmentation pattern for modified nucleobases (Figure 5C) can also facilitate the identification of DNA and RNA adducts caused by particular agents, an approach termed 'targeted adductomics' [72]. Specifically, targeted adductomics studies primarily rely on detecting neutral loss or product ions from chemical modifications on nucleobases, significantly enhancing analysis precision and reliability, as demonstrated in Figure 5C by the detection of the modification's fragment ion ([M + H]+) or its neutral loss (M Da). This approach has been effectively employed in the detection of DNA adducts arising from chemotherapeutic drugs, for example [67, 73, 74].
Adduct formed at the N7 and N3 positions of purines and the O2 site on pyrimidines in DNA render the nucleobase susceptible to instability, often leading to spontaneous depurination. This process separates adducts from the 2-deoxyribose, generating aglycone nucleobase adducts [75, 76]. Furthermore, cellular base excision repair, the primary DNA repair pathway for non-bulky DNA adducts, generates nucleobase (nB) adducts. These, along with products from processes like spontaneous depurination, are eventually excreted in the urine [77, 78]. Urine offers a non-invasive, easily obtainable, and storable sample with minimal biological risk, not requiring pre-processing before storage, making it ideal to use biobanked specimens [8, 79]. The simplicity of sample preparation compared to cellular DNA/RNA makes urine an attractive medium for studying the exposome [55, 80]. Cooke et al. [38, 70] revealed maps of the human urinary adductome, highlighting a range of adducts including 2′-dN, rN and nB adducts, with a notable predominance of nB adducts. However, it is challenging to identify whether nB adducts in urine originate from DNA or RNA. This difficulty arises primarily because DNA is characterized by its 2-deoxyribose sugar, whereas RNA contains ribose sugar. This distinct characteristic disappears once nucleosides from DNA or RNA undergo alterations through processes like repair or depurination, transforming them into nB adducts [25]. Consequently, tracing their precise origins becomes difficult when they are detected in urine [8].
RNA stands out due to its diversity of forms, that it performs multiple functions and undergoes various modifications, and is also subject to various repair activities [21]. This includes alterations induced by both endogenous processes and interactions with exogenous electrophilic molecules, highlighting the dynamic nature of RNA within cellular environments [22]. The generation of RNA adducts closely mirrors that for DNA adducts in several aspects, including their chemical composition and properties and the nucleobases that are especially susceptible to reaction [81, 82]. They also exhibit similar patterns of tissue distribution and show potential as indicators of exposure to harmful substances [24]. While traditional focus has been on DNA, the impact of RNA repair mechanisms on the urinary adductome warrants further exploration, as noted by Cooke et al. in 2018 [70]. RNA adducts, though less well studied compared to their DNA equivalents, could significantly contribute to the composition of the urinary adductome [38, 83, 84]. More recently, a study successfully characterized twelve RNA modifications in human urine, consisting not just of modified nucleobases but also specifically the ribose moiety (i.e., C5'-O-formylation or C5'-O-methylation) [85].
Tables 1 and 2 provide a detailed summary, in chronological order, of research using LC-MS to analyze DNA and RNA adductomes, respectively. Table 1 outlines the evolution of DNA adductome research, ranging from basic components like 2'-dN to more complex specimens such as human tissue samples. It highlights the progression in detection methods, advancing alongside mass spectrometry technologies from QqQ-MS to advanced HRMS instruments such as Q-TOF and Q-LIT-Orbitrap. These advances have broadened our ability to identify various DNA modifications arising from environmental pollutants, dietary factors, internal physiological activities, and pharmaceuticals, thereby deepening our insight into the molecular mechanisms underlying pathogenesis. Conversely, Table 2 shows that RNA adductome research is a newer domain of interest. While fewer in number, these studies point to an emerging field with potential insights into the role of RNA in cellular regulation and pathology. Interestingly, a prominent trend in both Tables 1 and 2 is the increasing focus on endogenous modifications, indicating a shift towards understanding the complex interplay between genetic material and the internal biological environment. This shift emphasizes the need to explore both DNA and RNA adductomes simultaneously to capture the full spectrum of modifications that can affect cell functions and potentially contribute to the onset of diseases such as cancer.
Table 1.
Overview of DNA adductome studies using LC-MS.
| Sample | MS type a |
Scan mode | Fragmentation method b |
Features for untargeted detection |
Adducts identified | Year | Reference |
|---|---|---|---|---|---|---|---|
| 2'-Deoxynucleosides (2'-dN) | QqQ | CNL | Beam-type CID | NL of 2-deoxyribose (dR), NL of bis-trimethylsilyl derivatized dR | 4-Aminobiphenyl (4-ABP)- and 2-aminofluorene-derived DNA adducts | 1992 | [52] |
| 2'-dN | QqQ | CNL | Beam-type CID | NL of dR | Polycyclic aromatic hydrocarbon (PAH)- and amino-PAH-derived DNA adducts | 1992 | [53] |
| 2'-dN, salmon testes DNA | QqQ | CNL | Beam-type CID | NL of dR, NL of combined 2'-dN, water and carbon monoxide | PAH dihydrodiol-epoxides-derived DNA adducts | 1995 | [86] |
| 2'-dN, calf thymus DNA (CT-DNA) | QqQ | CNL | Beam-type CID | NL of dR | 2-Amino-l-methyl-6-phenylimidazo[4,5-b]lpyridine-derived DNA adducts | 1995 | [87] |
| 2'-dN, kidney tissue from cynomolgus monkey | QqQ | CNL | Beam-type CID | NL of dR | 2-Amino-3-methylimidazo[4,5-f]quinoline-derived DNA adducts | 1999 | [88] |
| Human lung tissue from a smoker and a non-smoker | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | N2-ethyl-dG, εdA, 1,N2-PdG1, 1,N2-PdG2 | 2006 | [54] |
| Human lung and esophagus tissue | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | N2-ethyl-dG, εdA, 1,N2-PdG1, 1,N2-PdG2, 8-OH-PdG, 6-OH-PdG | 2007 | [89] |
| CT-DNA, rat liver DNA, human hepatocytes, human buccal cells | Ion trap | DDA-CNL-MS3 | Trap-type CID | NL of dR | DNA adducts associated with cigarette smoke and cooked meat | 2009 | [90] |
| 2'-dN, CT-DNA | QqQ | Precursor ion scan | Beam-type CID | Protonated ions of guanine (Gua) and adenine (Ade) | Acrylamide-derived DNA adducts | 2010 | [91] |
| CT-DNA | QqQ | CNL | Beam-type CID | NL of dR | PAH-derived adducts | 2010 | [92] |
| DNA isolated from the food | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | DNA adducts derived from dietary DNA in Quorn, button mushroom and brewer’s yeast | 2010 | [93] |
| Human pulmonary, colon, heart, kidney, liver, lung, pancreas, small intestine, and spleen tissue | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Lipid peroxidation (LPO)-derived DNA adducts | 2010 | [94] |
| Chinese hamster lung cells | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | DNA adducts derived from in vitro micronucleus test-positive compounds | 2011 | [95] |
| Human gastric mucosa | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | LPO-derived DNA adducts | 2013 | [96] |
| Mice liver tissue, human leukocyte | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: trap-type CID | NL of dR | 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)-derived DNA adducts | 2014 | [97] |
| Kidneys from F344 gpt delta rats | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Madder color-, lucidin-3-O-primeveroside- and alizarin-derived DNA adducts | 2014 | [98] |
| CT-DNA, left colon tumor from patients diagnosed with colon cancer | Q-Orbitrap | Full scan | NA | NA | DNA adducts associated with dietary chemicals | 2015 | [99] |
| Soil bacterium (Sphingobium sp. strain KK22) | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Acrolein-derived DNA adducts | 2015 | [100] |
| Mice lung tissue | Q-TOF | MSE | Beam-type CID | NL of dR | Reactive oxygen species (ROS)-derived adducts | 2015 | [101] |
| Meat digests using fecal microbiota | Q-Orbitrap | Full scan | NA | NA | DNA adducts associated with diet | 2016 | [102] |
| 2'-dN | QTRAP | CNL | Beam-type CID | NL of dR | Phenyl glycidyl ether- and styrene-7,8-oxide-derived DNA adducts | 2016 | [103] |
| 2'-dN | QqQ | CNL | Beam-type CID | NL of dR | Naphthoquinone-, para-benzoquinonehydroquin one- and ROS-derived DNA adducts | 2016 | [104] |
| Follicular cell culture (granulosa cells and theca cells) | QTRAP | CNL | Beam-type CID | NL of dR | Benzo[a]pyrene (B[a]P)- and cigarette smoke condensate-derived DNA adducts | 2017 | [105] |
| Rat tissues (liver, duodenal mucosae and colonic mucosae) | Q-Orbitrap | Full scan | NA | NA | N-nitroso compounds- and LPO-derived DNA adducts | 2017 | [106] |
| CT-DNA, human prostate and renal tissue | Q-LIT-Orbitrap | Wide-SIM/MS2 | HCD | NL of dR | DNA adducts associated with diet, traditional medicines and LPO products | 2017 | [107] |
| CT-DNA, mice liver tissue and urine | QTRAP | CNL | Beam-type CID | NL of dR | N-nitrosamines- and methyl methanesulfonate-derived DNA adducts | 2018 | [76] |
| CT-DNA, formalin-fixed paraffin-embedded human bladder tissue | Q-LIT-Orbitrap | Wide-SIM/MS2 | HCD | NL of dR | Aromatic amines- and LPO-derived DNA adducts | 2018 | [108] |
| Human urine | QTRAP | CNL, precursor ion scan | Beam-type CID | NL of dR, and radical cations of nB (Gua, Ade, cytosine (Cyt), thymine (Thy)) | A variety of DNA modifications | 2018 | [70] |
| Red and white meat following fecal microbiota digestions | Q-Orbitrap | Full scan | NA | NA | N-nitroso compounds- and LPO-derived DNA adducts associated with dietary heme iron | 2018 | [109] |
| Mice lung tissue | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD | NL of dR | NNK- and lipopolysaccharide-derived endogenous DNA adducts | 2019 | [110] |
| HeLa cells infected with Escherichia coli (E. coli) and colonic epithelial cells from mice colonized with E. coli | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: HCD MS3: HCD | NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Colibactin-derived DNA adducts | 2019 | [111] |
| Hep G2 cells treated with safrole | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Safrole-derived DNA adducts | 2019 | [112] |
| Human tumorous and nontumorous tissue | Q-TOF | MSE | HCD | NL of dR | N-nitrosopiperidine-derived adducts | 2019 | [113] |
| Bacteria (Shewanella oneidensis and Bacillus subtilis) | Q-LIT-Orbitrap | DDA-CNL-MS3 | NR | NL of dR | DNA adducts resulting from oxidative stress, LPO, glycation and alkylation | 2020 | [114] |
| Baltic amphipods (Monoporeia affinis) | Q-Orbitrap | DIA | HCD | NL of dR, and protonated dR ion | Epigenetic DNA modifications | 2020 | [59] |
| CT-DNA, Human embryonic kidney 293 cells | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD | NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Pyrrolobenzodiazepine-derived DNA adducts | 2020 | [115] |
| Mice liver tissue | Q-TOF | DDA-MS2 | Beam-type CID | NL of dR | 1,4-Dioxane-derived DNA adducts | 2020 | [116] |
| Human gastric mucosa | QTRAP | Pseudo-CNL | Beam-type CID | NL of dR | Seven DNA adducts related to epigenetic modification, oxidative stress, tobacco smoking and alcohol drinking | 2021 | [117] |
| Baltic amphipod (Monoporeia affinis) | Q-Orbitrap | DIA | HCD | NL of dR | DNA modifications related to epigenetics and oxidative stress | 2021 | [118] |
| CT-DNA, human skin | TOF/TO F, LTQ-Orbitrap | DDA-MS2 | Beam-type CID | NL of deoxyribose phosphate, NL of combined deoxyribose phosphate and triethylamine moiety (a characteristic of cationic xylyl labeling agent) | Forty-two cationic xylyl bromide prelabeling DNA and RNA adducts | 2021 | [119] |
| HeLa cells infected with E. coli | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID or HCD MS3: HCD | NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Colibactin-derived DNA adducts | 2021 | [120] |
| CT-DNA, rat liver tissue, human prostate tissue | Q-LIT-Orbitrap | Wide-SIM/MS2, DDA-CNL-MS3 | HCD | NL of dR | Environmental toxicants-derived DNA adducts | 2021 | [121] |
| Rat tissues (liver, kidneys, brain and heart), human left ventricular myocardial tissue | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Tissue-, age- and sex-specific DNA modifications | 2023 | [122] |
| Baltic amphipods (Monoporeia affinis) | Q-Orbitrap | DIA | HCD | NL of dR | DNA modifications derived from contaminants in marine sediments | 2023 | [123] |
| Rat tissues (liver, duodenum and colon) | Q-LIT-Orbitrap | Full scan | NA | NA | Endogenous processes and/or dietary effects related DNA modifications | 2023 | [124] |
| Rat liver tissue | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | Elemicin-derived DNA modifications | 2023 | [125] |
| CT-DNA, whole blood | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD | NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Busulfan-derived DNA adducts | 2023 | [67] |
| Rat kidney and liver tissues | Q-LIT-Orbitrap | wide-SIM/MS2, DDA-CNL-MS3 | HCD | NL of dR | DNA adducts resulting from thirteen potential human carcinogens | 2024 | [126] |
| 2'-dN, HepaRG cells, SD male rat, 3D bioprinted human liver organoid | QqQ | Pseudo-CNL | Beam-type CID | NL of dR | DNA adducts derived from genotoxic impurities in drugs | 2024 | [127] |
| Bladder mucosal epithelium from F344 rat | Q-TOF | DDA-MS2 | Beam-type CID | NL of dR | DNA adducts derived from aromatic amines, acetoacet-o-toluidine, and o-toluidine | 2024 | [128] |
LRMS includes QqQ, ion trap and QTRAP instruments while HRMS includes Q-Orbitrap, Q-LIT-orbitrap, Q-TOF and TOF/TOF instruments.
Beam-type CID and HCD collisions in quadrupole or multipole cells typically produce numerous fragments, whereas trap-type CID collisions in ion traps yield fewer fragments.
NA: not available.
Table 2.
Overview of RNA adductome studies using LC-MS.
| Sample | MS type a |
Scan mode b |
Fragmentation method |
Features of untargeted detection |
Adducts identified | Year | Reference |
|---|---|---|---|---|---|---|---|
| Human urine | Ion trap | DDA-MS2 | Trap-type CID | NL of ribose (R), NL of methylthioribose | RNA modifications and their ribosylated metabolites | 2008 | [129] |
| Nucleosides (rN) | QqQ | CNL, precursor ion scan | Beam-type CID | NL of rN, protonated ions of rN | B[a]P-derived RNA adducts | 2011 | [130] |
| Human urine | QqQ | CNL | Beam-type CID | NL of R | A variety of RNA modifications | 2011 | [83] |
| Human urine | QqQ | CNL | Beam-type CID | NL of R, NL of acetonide (derivative with acetone) | A variety of RNA modifications | 2015 | [131] |
| Pool of arbitrary RNA species | QqQ | CNL | Beam-type CID | NL of R, NL of 2'-O-methylated ribose (MeR) | A variety of RNA modifications | 2016 | [65] |
| Human urine | Q-TOF | MSE | Beam-type CID | NL of R | Cis-diol-containing RNA modifications | 2017 | [132] |
| Bacteria (E. coli and Leishmania donovani) rRNA, and human and yeast tRNA | Q-Orbitrap | DDA-MS2 | HCD | MS-based RNA sequencing | Monomethylated RNA modifications and their positional isomers | 2019 | [133] |
| Human urine | Q-TOF | MSE | Beam-type CID | NL of R, NL of modified R with C5'-O-formylation or C5'-O-methylation, protonated aglycone ion | Twelve cis-diol-containing RNA modifications at nucleobase or ribose | 2022 | [85] |
| rN, yeast tRNA | Q-LIT-Orbitrap | DDA-MS2 | Trap-type CID or HCD | Specific mass increment on precursor ion due to benzo[a]pyrene diol epoxide (BPDE) adduction | BPDE-derived RNA adducts | 2023 | [134] |
LRMS includes QqQ and ion trap instruments while HRMS includes Q-Orbitrap, Q-LIT-orbitrap and Q-TOF instruments.
Beam-type CID and HCD collisions in quadrupole or multipole cells typically produce numerous fragments, whereas trap-type CID collisions in ion traps yield fewer fragments.
4. MS-based protein adductomics
Both human serum albumin (HSA) and hemoglobin (Hb) play pivotal roles in blood, and have been extensively employed in protein adductomics to track chemical exposures [135, 136]. Adducts form with these proteins that act as markers for various chemical interactions, thereby revealing insights into the human exposome and related health implications. Amino acid cysteine residue (Cys) is of interest due to its reactivity (with a relative order of nucleophilicity typically Cys >> histidine > arginine and lysine; [137], contributing significantly to its role in chemical interactions and adduct formation. HSA, the predominant protein in blood plasma, plays a critical role in maintaining blood volume and transporting various substances such as hormones and drugs, with its highly reactive cysteine residue (Cys34) located on the third largest tryptic (T3) peptide making it a central focus for adductomic studies across a wide range of chemicals [138, 139]. With a shorter circulation half-life of about 21 days compared to 120 days for Hb, HSA reflects more immediate exposure snapshots, making it invaluable for examining short-term chemical interactions and their immediate bodily impacts. We suggest that other highly reactive Cys residues of peroxiredoxins and other thiol-containing proteins [137, 140] could be explored for their potential as biomarkers in adductomics research.
Hb resides within red blood cells (RBCs), primarily facilitating the transport of oxygen from the lungs to tissues and vice versa for carbon dioxide. It is particularly sensitive to adduction by certain electrophiles, making it ideal for reflecting low-level chemical exposures, especially those forming adducts with its N-terminal valine. Given the long lifespan of RBCs, Hb adducts can document exposure over several months, serving as valuable tools in investigating occupational hazards, smoking effects, and exposures to electrophilic compounds such as ethylene oxide, acrylonitrile, methyl vinyl ketone, acrylamide and glycidamide [141].
In the field of HSA adductomics, early studies utilized low-resolution QqQ instruments to screen for adducts at the Cys34 site. Techniques such as precursor ion scanning and fixed-step selected reaction monitoring (FS-SRM) were employed for adduct identification. For instance, precursor ion scanning [142], involves scanning for precursor ions in the first stage of mass analysis and isolating a constant product ion in the second stage. This yields a spectrum of precursor ions producing a specific product ion, facilitating the identification of adducts formed at the Cys34 residue. The FS-SRM technique represents a refined method that sequences a series of SRM experiments, resembling a linked scan [143]. This method is particularly effective at identifying substitutions on the Cys34 residue by monitoring variable product ions of the tryptic T3 peptides derived from HSA. A significant methodological advancement involves utilizing LC-HRMS techniques to study Cys34 adducts [132, 139, 144-147], with efforts also made to extend coverage to a second commonly modified site on HSA, Lys525 [148]. To expand the investigation and explore additional nucleophilic sites beyond Cys and Lys, a sensitive and unbiased method named Pan-Protein adductomics has been introduced [149]. This method enables comprehensive discovery and relative quantification of adducts across multiple residues in HSA, revealing previously unexplored modifications on residues including histidine, tyrosine, serine, methionine and arginine.
The Törnqvist lab at Stockholm University has significantly contributed to the field of Hb-based protein adductomics through the development of the FIRE (‘Fluorescein isothiocyanate’, ‘R-group’ and ‘Edman degradation’) method (Figure 6) [136, 141, 150, 151]. This technique, which involves the use of fluorescein isothiocyanate (FITC) for the release of N-terminal adducts followed by LC-MS analysis, has been recognized for its ability to effectively screen for electrophile exposure by analyzing adducts to N-terminal valines (Val) in Hb. In the FIRE procedure for adductomics, specific fragmentation patterns were consistently observed in the analysis of Val adducts as fluorescein thiohydantoin (FTH) derivatives. These patterns allowed for the establishment of methods to screen for adducts by monitoring four specific diagnostic fragments for each m/z unit within a predetermined range of precursor ions (Figure 6). The monitored fragments, including m/z 445, 460, 489, and [M+H]+ – 43, indicate common fragmentation pathways observed in FTH derivatives of Val adducts, which involve the loss of the Val isopropyl group, either with or without the adduct itself. The FIRE method is notable for its enhanced sensitivity and specificity in detecting adducts, achieved through the application of FITC and other isothiocyanate Edman reagents, making it particularly valuable for measuring low-level background adducts [136]. However, the FIRE method still has some limitations, such as challenges in precisely pinpointing the location of adducts on the Hb molecule and difficulties in detecting larger aromatic electrophile adducts. Alternatively, recent proposed bottom-up proteomics approaches offer the ability to identify a broader range of electrophile adducts and their specific locations within hemoglobin's alpha and beta chains [152]. Despite these advantages, bottom-up proteomics requires higher levels of adduct formation for detection, which can be limiting in cases of low exposure levels [153].
Figure 6.
Illustration of the FIRE method for screening N-terminal Hb adducts. Adducted N-terminal amino acids are cleaved using fluorescein isothiocyanate (FITC), yielding adduct derivatives known as fluorescein thiohydantoins (FTHs). Upon untargeted MS/MS analysis, these FTH derivatives of N-terminal Hb adducts exhibit consistent fragmentation pathways. This figure is independently drawn in the present work with concepts taken from Refs. [136, 141, 150, 151].
Recently, the Uchida lab in Japan has developed a novel approach to protein adductomics, focusing on histidine and lysine, key nucleophilic amino acids susceptible to covalent interactions with electrophilic aldehydes [154, 155] (Figure 7). Their method involves accurately identifying a specific fragment ion from the adducts formed between these amino acids and lipid aldehydes, using a precursor ion scan under collision-induced dissociation (CID), and follows a concept similar to FS-SRM. For example, when histidine reacts with 2-alkenals, a distinct fragment ion at m/z 110 is detected, indicative of a histidine immonium ion. Similarly, lysine, when forming adducts with 2-alkenals through mechanisms such as Michael addition, Schiff base formation, and pyridinium adduct formation, yields a characteristic fragment ion at m/z 84. This ion corresponds to the lysine immonium ion without NH3. This non-derivatization, streamlined approach could offer a more direct and simplified method for exploring protein adducts in both HSA and Hb [156].
Figure 7.
A strategy for protein adductomics analysis targeting histidine and lysine residues. Reprinted and modified with permission from Ref. [154] with permission from Elsevier.
Bottom-up MS-based proteomics approaches have also been introduced into adductomics to explore the interactions between various compounds and their protein targets [157]. Typically, after digesting proteins into peptides, protein modifications were characterized and identified using MS-based proteomics. However, without the need for digesting proteins into peptides, combining intact protein measurement with parallel reaction monitoring (PRM) approach in HRMS can also be used to monitor adduction levels. The Chen lab in Taiwan used this technique to confirm that catechol estrogens (CEs) adducted to HSA and Hb (CE-HSA and CE-Hb adduction levels) in intact proteins serve as valuable biomarkers for CEs exposure and disease risk, particularly in diabetes and cancer [158, 159]. Additionally, advanced techniques such as click-chemistry combined with MS-based proteomics strategies have been adopted in targeted protein adductomics. These methods have been used to explore the interactions of antimicrobial 5-nitroimidazoles [160] and alpha, beta-unsaturated carbonyl compounds (e.g., the therapeutic drug dimethyl fumarate) [161] with target proteins. Novel chemical tools employing click-chemistry probes for the enrichment of covalent adducts with specific functional groups could significantly advance future protein adductomics research.
Table 3 details the progress and broad application of LC-MS in protein adductomics, highlighting its extensive utility across various biological samples, including serum, plasma, RBCs, tissues, cultured cells, and parasites. The shift from lower-resolution devices like QqQ and ion traps to higher-resolution instruments such as LIT-Orbitrap reflects significant technological progress, enhancing adduct detection's sensitivity and precision. The table shows a diverse range of identified adducts, including those associated with mercury, environmental exposures, and ROS, indicating the crucial role of LC-MS in unraveling the complexities of protein-electrophile interactions.
Table 3.
Overview of protein adductome studies using LC-MS.
| Sample | MS type a | Scan mode b |
Fragmentation method |
Features of untargeted detection |
Adducts identified | Year | Reference |
|---|---|---|---|---|---|---|---|
| Kidney tissue from male Eker rats | Ion trap | DDA-MS2 | Trap-type CID | Peptide sequencing | 2-(glutathion-S-yl)-1,4-benzoquinone-derived protein adducts | 2009 | [162] |
| Rabbit muscle, bacterium (E. coli) | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Peptide sequencing | Mercury-derived protein adducts | 2011 | [163] |
| Human serum albumin (HSA) | QqQ | FS-SRM | Beam-type CID | Specific product ions of HSA-cysteine-34 (Cys34) | Protein adducts associated with environmental exposure | 2012 | [164] |
| Human plasma | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts derived from oxidation and cysteinylation | 2014 | [165] |
| Red blood cells (RBCs) from smokers and nonsmokers | QTRAP | FS-SRM | Beam-type CID | Specific product ions of fluorescein thiohydantoin (FTH) derivatives | Hb N-terminal valine (Val) adducts | 2014 | [141] |
| Hemoglobin (Hb) peptide, human blood and plasma | Q-Orbitrap | DIA | HCD | Specific product ions of HSA-Cys34 and Hb cysteine-93 | HSA-Cys34 adducts associated with oxidative stress | 2015 | [147] |
| RBCs (human, bovine, rabbit, guinea pig and mice) | QTRAP | FS-SRM | Beam-type CID | Specific product ions of FTH derivatives | Ethyl vinyl ketone-derived Hb N-terminal Val adducts | 2015 | [166] |
| Human plasma | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with cigarette smoking | 2016 | [139] |
| Human and mice serum | QqQ | FS-SRM | Beam-type CID | Diagnostic product ion of Lys and histidine (His) | LPO-derived protein adducts | 2017 | [155] |
| RBCs from school-age children | Q-Orbitrap | DIA | HCD | Specific product ions of FTH derivatives | Genotoxic compounds-derived Hb N-terminal Val adducts | 2017 | [167] |
| Human plasma | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with solid fuel | 2017 | [132] |
| Human plasma | QqQ | FS-SRM | Beam-type CID | NL of b5 fragment in T3 peptide | HSA adducts associated with environmental exposure | 2017 | [144] |
| Human serum | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | Benzene oxide- and diolepoxide-derived protein adducts | 2018 | [168] |
| Human serum | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with chronic obstructive pulmonary disease and ischemic heart disease | 2018 | [169] |
| Human RBCs | Q-Orbitrap | DIA | HCD | Specific product ions of FTH derivatives | 4-Quinone methide- and 4-hydroxybenzaldehyde-derived Hb N-terminal Val adducts | 2018 | [170] |
| THLE-2 and Hep G2 cells | Q-TOF | DDA-MS2 | Beam-type CID | Methionine (Met) oxidation, specific mass increments corresponding to glycidamide incorporation at Lys, Cys, His, serine (Ser), arginine (Arg) | Glycidamide-derived protein adducts | 2019 | [157] |
| Human serum | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with colorectal cancer | 2019 | [171] |
| Newborn dried blood spots | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with smoking | 2019 | [138] |
| Human RBCs | QqQ | FS-SRM | Beam-type CID | Diagnostic fragment ion m/z 110 for His adduct and m/z 84 for Lys adduct | 2-Alkenal-derived His and Lys adducts | 2019 | [156] |
| Human serum | Q-TOF, LTQ-Orbitrap, Q-Orbitrap | Full scan, DDA-MS2, parallel reaction monitoring (PRM) | Trap-type CID, HCD | Peptide sequencing; bottom-up trypsin-PRM methods | Catechol estrogens (CEs)-derived HSA adducts | 2019 | [158] |
| THP-1 cells, human pulmonary macrophages | Q-Orbitrap | DDA-MS2 | HCD | Cys carbamidomethylation, Met oxidation, N-terminal glutamine deamidation, and Lys aSA-triazole-hexanoic acid modification | Oxysterols-derived protein adducts | 2020 | [172] |
| Human plasma | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with lung cancer | 2020 | [173] |
| Human plasma and RBCs | Q-Orbitrap | DDA-MS2 | HCD | Met oxidation, Cys carbamidomethylation, and specific mass increments corresponding to hapten incorporation at Cys, His, Lys, Arg, Ser, tyrosine (Tyr), threonine, and N-terminus of peptides | Protein adducts associated with skin allergens | 2020 | [174] |
| Newborn neonatal blood spots | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with childhood acute lymphoblastic leukemia and acute myeloid leukemia (AML) | 2020 | [175] |
| Giardia Lamblia (strain WB and GS/M) | Q-TOF | DDA-MS2 | Beam-type CID | Peptide sequencing; click-chemistry adduction of metronidazole alkyne-tagged proteins | 5-nitroimidazoles-derived protein adducts | 2020 | [160] |
| Human plasma from smokers and nonsmokers | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 and lysine-525 (Lys525) | HSA-Cys34 and HSA-Lys525 adducts | 2021 | [148] |
| Human plasma and RBCs | Q-TOF, LTQ-Orbitrap, Q-Orbitrap | Full scan, DDA-MS2, PRM | Trap-type CID, HCD | Peptide sequencing; bottom-up trypsin-PRM methods | CEs-derived Hb and HSA adducts | 2021 | [159] |
| Human plasma | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 and Lys525 | HSA-Cys34 and HSA-Lys525 adducts associated with diesel engine exhaust | 2022 | [176] |
| RBCs from schoolchildren, human adults and rodents | Q-Orbitrap | DDA-MS2 | HCD | Specific product ions of FTH derivatives | Hydroxypropanoic acid-Val adduct in Hb | 2022 | [151] |
| Human plasma and serum | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 adducts associated with AML | 2023 | [146] |
| Human serum | Q-LIT-Orbitrap | DIA | HCD | Specific mass increment (e.g., oxidation and acetylation) on Cys34 and other residues, including Lys, His, Tyr, Ser, Met, and Arg | HSA adducts associated with air pollution | 2023 | [149] |
| Human serum | LIT-Orbitrap | DDA-MS2 | Trap-type CID | Specific product ions of HSA-Cys34 | HSA-Cys34 and HSA-Lys525 adducts associated with non-Hodgkin lymphoma | 2023 | [177] |
| Human RBCs | Q-Orbitrap | PRM, DDA-MS2 | HCD | Specific product ions of FTH derivatives; bottom-up MS-based proteomics | Hb N-terminal Val adducts associated with allergens and electrophiles | 2023 | [153] |
| Human brain tumor tissue | Q-Orbitrap | DDA-MS2 | HCD | Peptide sequencing | Protein adducts associated with pesticides exposure | 2023 | [178] |
| Human coronary artery smooth muscle cells | TIMS-TOF | DDA-MS2, parallel accumulat ion-serial fragmenta tion combined with DIA (DIA-PASEF) | HCD | Peptide sequencing; click-chemistry adduction of alkyne-tagged proteins | Dimethylfumarate- and monomethylfumarate-derived protein adducts | 2023 | [161] |
| Human serum | Q-Orbitrap | DDA-MS2 | HCD | Specific product ions of HSA-Cys34 | HSA adducts associated with water-soluble organic molecules in inhaled PM2.5 | 2024 | [145] |
| Plasma from preterm and full-term infants | LTQ-Orbitrap | Full scan | NA | Peptide sequencing with manual inspection using Xcalibur™ software | HSA-Cys34 adducts linked to oxidative stress caused by bronchopulmonary dysplasia | 2024 | [179] |
LRMS includes QqQ, ion trap and QTRAP instruments while HRMS includes LIT-Orbitrap, Q-Orbitrap, Q-LIT-orbitrap, Q-TOF and TIMS-TOF instruments.
Beam-type CID and HCD collisions in quadrupole or multipole cells typically produce numerous fragments, whereas trap-type CID collisions in ion traps yield fewer fragments.
NA: not available.
5. MS-based crosslinkomics: analysis of crosslinks within and across macromolecules
In addition to forming mono-adducts, through single nucleobase modifications, bifunctional agents such as nitrogen mustards [180, 181] and 1,3-butadiene [182, 183] can form pairs of bonds on DNA, resulting in DNA-DNA crosslinks (DDCL). When these double bonds occur between two complementary DNA strands, they are known as inter-strand crosslinks (ICLs); when they occur on the same strand, they are called intra-strand crosslinks [184, 185]. ICLs hinder the unwinding of the DNA double helix, obstructing essential cellular functions such as DNA replication and transcription, leading to high levels of cytotoxicity [186]. Despite significant interest in ICLs, there has historically been a lack of comprehensive MS methods for their detection. Stornetta et al. (2015) [66] employed a novel LC-MS3 approach to identify DNA adducts formed by alkylating agents, based upon accurately detecting the loss of DNA nucleobases and a dR. This method aimed to screen both mono-adducts and crosslinked DNA adducts, involved precise tracking of mass loss from either a dR group or a nucleobase, which then initiated MS3 fragmentation. Although it successfully identified drug-induced crosslinks, the technique was not specifically tailored for DNA crosslink measurement. Hu et al. (2019) [73] introduced a novel screening method known as DNA ‘crosslinkomics’, which offers a detailed framework for screening ICLs (e.g., neutral losses of two dR or two DNA nucleobases). This approach has revealed previously unidentified ICLs induced by formaldehyde and chemotherapeutic agents, notably including those formed at apurinic/apyrimidinic (AP) sites in duplex DNA, where the absence of a DNA nucleobase results in crosslinking. Their work also was the first to describe the presence of crosslinks in which alkylating drugs connect a 2′-dN to a dR group, providing further insights into the complex interactions between drugs and DNA. Although a comprehensive screening method for DNA intra-strand crosslinks has not yet been fully developed, DNA crosslinkomics shows potential as a tool for identifying markers of exposure to both environmental and endogenous crosslinking agents. Subsequently, it could be of great use to evaluate the effectiveness of DNA crosslinking drugs in chemotherapy treatments [187].
DNA-protein crosslinks (DPCL) are bulky DNA adducts that form within cells following exposure to various agents, including ROS, ultraviolet light, ionizing radiation, environmental substances, and chemotherapeutic agents [188, 189]. Amino acids such as lysine, cysteine, and histidine on proteins, being highly nucleophilic, readily form crosslinks with DNA through bifunctional groups [190]. These DPCL hinder DNA replication, jeopardizing genome integrity and cell survival [191]. MS-based proteomics techniques have allowed the identification of the protein constituents involved in DPCL formation, providing initial insights into the identities of the proteins participating in crosslinking [188, 192]. Protein-protein crosslinks (PPCL) arise from covalent bonds between amino acid residues, occurring within a single protein polypeptide (intramolecular) or across different protein polypeptides (intermolecular). Research on environmentally induced PPCL has predominantly centered on formaldehyde [47, 193], with analytical techniques relying on MS-based proteomics, particularly crosslinking mass spectrometry (XL-MS). More detailed discussions on these methodologies and their applications can be found to in the corresponding literature [51, 194, 195].
In theory, cross-linking can occur with any RNA in close proximity to another RNA molecule, mirroring the process observed in DNA, as long as the chemistry of the cross-linker permits [196]. However, there is limited research on the potential for toxic substances to induce RNA-RNA crosslinks (RRCL). The instances where RRCL formation has been observed are primarily associated following UV irradiation [197, 198]. Investigations into RNA-protein crosslinks (RPCL) triggered by physicochemical agents are still emerging [199], with a primary emphasis on RPCL created by formaldehyde or exposure to UV irradiation [200]. The application of MS in crosslinkomics, especially in the study of hybrid species, remains limited. However, noteworthy advances have been made in specific niches. For example, the identification of formaldehyde-induced DNA-RNA crosslinks (DRCL) in mouse lung tissue [201] and the detection of DRCL, RRCL, and RPCL in human urine [38], attest to the existence and, in the case of urine, repair of these classes of adducts, detection of which is made possible via HRMS-based adductomic approaches.
The recent development of nucleic acid (NA) adductomics significantly broadens the scope of exposome research by incorporating DNA and RNA modifications, as well as a variety of crosslinks such as DDCL, RRCL, DRCL, DPCL, and RPCL [38, 58]. Through the examination of NA cross-linked products using collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and wide-HCD on a Q-LIT-Orbitrap mass spectrometer, essential characteristics and fragmentation patterns have been uncovered, particularly for hybrid species, as outlined in Figure 8. This advance not only deepens our knowledge of the breadth of NA modifications, but also lays the groundwork for exploring new pathways in protein/nucleic acid interaction studies, through demonstrating the potential of NA adductomics to analyze hybrid species.
Figure 8.
Proposed fragmentation patterns for various crosslinks. This figure was independently developed for the present work with concepts taken from Refs. [58, 66, 73].
Table 4 highlights the critical role of LC-MS in studying complex interactions within biological systems, particularly focusing on crosslinks between DNA, RNA, and proteins. Advanced MS tools, such as the Q-LIT-Orbitrap, have enhanced the depth of studies on multi-species interactions. Table 4 also includes previous studies that have made efforts to simultaneously measure multiple types, such as mono DNA/RNA adducts or mono DNA/protein adducts, rather than just one type of adducts. This transition from single-species/type to complex multi-species/types analyses represents a notable advance in the field, driven by a growing interest in understanding the dynamics between various biomolecular entities.
Table 4.
Overview of adductome studies on NA crosslinks and simultaneous measurement of multiple species using LC-MS.
| Type | Sample source | MS type a | Scan mode b |
Fragmentation method |
Features of untargeted detection |
Adducts identified | Year | Reference |
|---|---|---|---|---|---|---|---|---|
| Crosslinks (DDCL) | Oligodeoxyribonucl eotides (ODNs) | Ion trap | DDA-MS2 | Trap-type CID | Specific mass increment on precursor ion due to cisplatin adduction | Cisplatin-derived intrastrand DDCL | 2013 | [202] |
| Crosslinks (DDCL) | CT-DNA | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD |
NL of dR, NL of 2 dR, NL of nB (Gua, Ade, Cyt, Thy), NL of 2 nB | Formaldehyde- and chlorambucil-derived DDCL | 2019 | [73] |
| Crosslinks (RPCL/DPCL) | CCRF-CEM T and GM639 cells | Q-LIT-Orbitrap | DDA-MS2 | Trap-type CID, HCD | Cys carbamidomethylati on, Met oxidation, N-terminal acetylation | Chemotherapy drug- or formaldehyde-induced crosslinks | 2020 | [203] |
| Crosslinks (DDCL) | CT-DNA | LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: trap-type CID |
NL of dR, NL of 2 dR | Acrolein- and 4-hydroxy-2-nonenal-derived DDCL | 2010 | [204] |
| Crosslinks (DDCL) | CT-DNA, HT-29 cells | LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Alkylating drug-derived DNA adducts and interstrand DDCL | 2015 | [66] |
| Crosslinks (DDCL) | CT-DNA, HT-29 and HCEC cells | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Drug (PR104A)-derived DNA adducts and DDCL | 2017 | [205] |
| Crosslinks (DDCL) | CT-DNA, bacterium (E. coli), mice lung tissue, blood from dog with chemotherapy | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: wide-HCD MS3: HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Doxorubicin- and formaldehyde-derived DNA adducts and DDCL | 2021 | [206] |
| Crosslinks (DDCL) | 2'-dN, CT-DNA, oral rinse samples | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Alcohol-derived DNA adducts and DDCL | 2021 | [207] |
| Crosslinks (DDCL) | CT-DNA | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: wide-HCD |
NL of dR | Formaldehyde-derived DNA adducts and DDCL | 2021 | [56] |
| Crosslinks (DDCL) | CT-DNA, bacterium (E. coli), xenograft tumor tissue from NCr nude mice | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: wide-HCD MS3: wide-HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Drug (CP-506)-derived DNA adducts and DDCL | 2022 | [208] |
| Crosslinks (DDCL/DR CL) | 2'-dN, rN, mice lung tissue | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: trap-type CID MS3: trap-type CID |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy) | Formaldehyde-derived DDCL and DRCL | 2022 | [201] |
| Crosslinks (DDCL) | CT-DNA, bacterium (E. coli), whole blood | Q-LIT-Orbitrap | DDA-CNL-MS3 | MS2: HCD MS3: HCD |
NL of dR, NL of nB (Gua, Ade, Cyt, Thy), diagnostic product ion of fapy-specific fragments | Cyclophosphamide-derived DNA adducts and interstrand DDCL | 2023 | [180] |
| Crosslinks (RPCL) | U1 snRNP, snRNA | QTRAP | Precursor ion scan | Beam-type CID | Phosphate moiety (PO3−) | RPCL resulting from UV radiation | 2007 | [209] |
| Multi-species (DNA/RNA) | Garden cress (Lepidium sativum cv. Ogrodowa) | Ion trap | DDA-MS2 | Trap-type CID | NL of dR, NL of R | Methylated DNA and RNA adducts derived from cupric oxide nanoparticles | 2016 | [210] |
| Multi-species (DNA/RNA) | Hep G2 cells | QqQ | Pseudo-CNL | Beam-type CID | NL of dR, NL of R | B[a]P-derived DNA and RNA adducts | 2019 | [24] |
| Multi-species (DNA/protein) | ODNs, CT-DNA, human colorectal tumor tissue | Q-TOF | MSE | Beam-type CID | Cys methylation, Cys carbamidomethylation, Met oxidation, asparagine deamidation | O6-Alkylguanine species and alkylated cysteine | 2023 | [211] |
| Multi-species (DNA/RNA) | Baltic amphipod (Monoporeia affinis) | Q-Orbitrap | DIA | HCD | NL of dR, NL of R | DNA and RNA modifications | 2023 | [60] |
| Multi-species (DNA/RNA) and crosslinks) | 2'-dN, rN, amino acids, human urine | Q-LIT-Orbitrap | DDA-MS2 | Trap-type CID | NL of dR, NL of R, NL of MeR, NL of 2 dR, NL of 2 R, NL of 2 MeR, NL of R + MeR, NL of dR + R, NL of dR + MeR, NL of dR + Cys, NL of R + Cys, NL of MeR + Cys, diagnostic product ion of nB | DNA and RNA modifications, and a variety of crosslinks (DDCL/RRCL/DRC L/DPCL/RPCL) | 2023 | [38] |
| Multi-species (DNA/RNA) and crosslinks) | CT-DNA, yeast RNA, BSA, human urine | Q-LIT-Orbitrap | DDA-MS2 | Trap-type CID/wide-HCD | 132 features of NA modifications | DNA and RNA modifications, and a variety of crosslinks (DDCL/RRCL/DRC L/DPCL/RPCL) | 2024 | [58] |
LRMS includes QqQ, ion trap and QTRAP instruments while HRMS includes LIT-Orbitrap, Q-Orbitrap, Q-LIT-orbitrap, Q-TOF and TOF/TOF instruments.
Beam-type CID and HCD collisions in quadrupole or multipole cells typically produce numerous fragments, whereas trap-type CID collisions in ion traps yield fewer fragments.
6. Advances in HRMS data acquisition modes
Early adductomics primarily relied on LRMS (e.g., QqQ-MS) for CNL, pseudo-CNL, and precursor ion screening. However, advances in instrumentation have led to novel acquisition modes, thereby enhancing analytical capabilities [43]. Two acquisition modes have been successfully adopted by HRMS for adductomics, as described below.
6.1. Data dependent acquisition (DDA)
Data-dependent acquisition (DDA) is a scanning approach characterized by the acquisition of a full-scan spectrum (MS1) across a defined m/z range, followed by multiple fragmentation events (MSn). The instrument software in real-time swiftly and dynamically selects precursor ions for fragmentation, prioritizing signal intensity along with additional predetermined criteria, such as ion intensity threshold, charge state, neutral loss mass, diagnostic product ion, and more. The most commonly used approach for DNA adductomics is the DDA combined with constant neutral loss triggering MS3 (DDA-CNL-MS3) (as shown in Table 1). This approach is primarily performed on ion trap MS platforms, enabling detailed analysis through three stages of ion fragmentation (MS1, MS2 and MS3). This method involves selecting precursor ions from MS1 via DDA, then acquiring MS2 data. If a neutral loss characteristic feature of DNA or RNA modifications (NLs of dR, R or MeR) is detected in the MS2 spectra, triggering an MS3 event is initiated for further analysis. This event serves as a key indicator of DNA or RNA adduct detection, yielding critical fragments from aglycone ions that aid in identifying adduct structures (Figure 5C). The effectiveness of conventional DDA-CNL-MS3 in DNA or RNA adductomics usually relies on detecting the neutral loss of sugar moieties between MS1 and MS2 spectra, with the MS3 triggering event also facilitating subsequent data processing. However, its application can be limited by unexpected adduct types and complex chemical behaviors, as not all adducts follow the expected fragmentation patterns, such as 8,5'-cyclopurine-2'-deoxynucleosides (which do not display the characteristic loss of dR) [212] and pseudouridine (which does not lose the R group) [213]. To address these exceptions, a variety of screening methods have emerged, such as NL screening of canonical nB [71, 111] or 2'-dN (e.g., dG of 267.0967 Da) [121] for DNA adducts, NL screening of two nBs for DDCL [73], and NL screening of modification itself from aglycone ions [71, 91].
Alternatively, the recently proposed DDA-MS2 method, which records an initial full-scan MS1 spectrum followed by MS2 spectra of the top N most intense ions, offers greater versatility than the DDA-CNL-MS3 approach. However, its adoption in DNA or RNA adductomics is limited by the absence of automated tools for analyzing complex data. To tackle this challenge, advances in post-data analysis software, such as 'Thermo Scientific's Compound Discoverer' [214], 'DFBuilder' [120] and 'FeatureHunter' [58], have emerged. These tools significantly enhance the capacity of the DDA-MS2 method to accurately identify adducts by identifying specific neutral losses or diagnostic ions. Notably, the integration of FeatureHunter into the DDA-MS2 workflow has yielded promising results that extend beyond DNA and RNA adductomics, including protein adductomics and other ‘omics areas [58]. It is worth noting that although the conventional DDA-CNL-MS3 method includes MS2 spectra, under a fixed cycle time, performing MS2 data acquisition without MS3 (DDA-MS2) can increase the number of MS2 spectra collected, thereby enhancing the overall sensitivity of the analysis [58].
The DDA-based method has been criticized for favoring more abundant ions, possibly missing lower-level adducts present in biospecimens. The capability of this method largely depends on the MS scanning speed, which determines how many ions can be analyzed through MS2 fragmentation [107]. To further strengthen its effectiveness, the utilization of inclusion and exclusion lists informed by chemical exposure knowledge, DNA adduct formation chemistry, and reports in the literature can enhance the detection of relevant adducts while avoiding unnecessary MS2 spectra from common nucleosides, their metal adducts (e.g., [M + Na]+), and background ions [215]. Additionally, ongoing advances in MS technology continuously improve data acquisition speeds, facilitating more thorough analysis of MS spectra.
6.2. Data-independent acquisition (DIA)
Unlike DDA, data-independent acquisition (DIA) offers an unbiased approach by simultaneously fragmenting all analytes, capturing a more comprehensive dataset and ensuring that low-abundance ions are not overlooked. In this method, MS captures all precursor ions within a broad mass window (e.g., m/z 100-500) to gather MS1 data. Subsequently, these ions are collectively fragmented without selecting specific precursors, producing complex MS2 composite spectra consisting of all fragments ions produced from all the precursor ions present. This approach greatly reduces bias towards high-intensity ions. DIA variants, such as MSE (Waters Corporation) used in quadrupole time-of-flight (Q-TOF) instruments, have shown promise in adductomics. MSE alternates between high and low collision energies to generate a wide range of fragment ions, thereby enhancing precursor ion fragmentation and product ion yield, which aids in structural identification. Its application has been validated in various studies, demonstrating success in both DNA [101, 113] and RNA [132] adductomics.
Sequential window acquisition of all theoretical mass spectra (SWATH) has also been introduced to simplify mass spectra deconvolution. SWATH divides a wide m/z range into smaller segments (e.g., four 100-m/z segments within the range of 100-500 m/z) for the production of simpler MS2 spectra, corresponding to fewer precursor ions, and thereby assisting in the assignment of MS2 product ions to their corresponding precursor ions. Wide-SIM/MS2 [107], a variant of SWATH, selects precursor ions within broader m/z windows (approximately 30 m/z) in selected ion monitoring (SIM) mode, followed by their fragmentation in MS2 scans. It has been successfully demonstrated in non-targeted DNA adductomics by identifying various DNA adducts resulting from exposure to carcinogens or electrophiles [107, 108, 126, 216].
Generally speaking, the wide m/z windows of DIA methods produce complex, composite MS2 spectra, presenting challenges for data analysis especially when detecting analytes present at trace levels which is typically the case for adductome studies [217]. To tackle the data processing challenges in DIA-based DNA adductomics, two software, wSIM-City [121] and nLossFinder [118], have been developed. These tools are specifically designed to identify crucial characteristics, such as the neutral loss of a dR, across both MS1 and processed MS2 spectra, proving their capability in revealing numerous potential DNA adducts.
Overall, both DDA- and DIA-based approaches serve as essential and complementary tools for investigating the extensive DNA, RNA, or protein adductomes. DDA simplifies MS spectral analysis and data interpretation, facilitating the inclusion of MS3 fragmentation for adduct identification. Conversely, DIA excels in its unbiased gathering of extensive MS spectra. Both methods necessitate specialized post-data analysis software for their full utilization.
7. Development of mass spectral libraries for adductomics
Despite the detection of numerous putative adducts in HRMS analyses, identifying their exact identities remains a significant challenge, limiting adductomics applications. While existing MS-based databases and spectral libraries like HMDB, METLIN, NIST, MoNA, and mzCloud aid in annotating small molecules, they are not specifically tailored for adductomics and lack comprehensive coverage of DNA, RNA, and protein adducts [35]. Lately, several databases specifically created for adduct searches, particularly focusing on DNA adducts, have emerged to bridge this identification gap.
Hemeryck et al. (2015) [99] developed an in-house database covering 123 diet-related DNA adducts. Carrà et al. (2019) [110] introduced a database that includes 152 endogenous DNA adducts resulting from alkylation, lipid peroxidation, and reactive oxygen species. Guo et al. (2017) [107] created a database featuring various DNA adducts derived from heterocyclic aromatic amines, aromatic amines, lipid peroxides, and polycyclic aromatic hydrocarbons. While these databases provide exact masses of precursors and adduct information including exposure sources and chemical structures, their capability for unbiased identification is often limited by the lack of MS/MS fragmentation data. La Barbera et al. (2022) [218] compiled an extensive database of reported DNA adducts through thorough literature reviews, available at https://nexs-metabolomics.gitlab.io/projects/dna_adductomics_database/index.html. This resource includes detailed information such as chemical structures, exact masses, molecular formulas, exposure origins, IUPAC names, SMILES, InChI, and InChIKey structural designations. Additionally, it integrates the necessary MS/MS fragmentation data, obtained from reference standards or generated using the in silico fragmentation prediction software 'CFM-ID'. Recently, Walmsley and colleagues have significantly enhanced their mass spectral reference library [219] by incorporating comprehensive datasets of MS2 and MS3 spectra from 280 DNA adducts [35]. In addition to modified nucleosides, the library now features MS/MS fragmentation spectra of 135 modified nucleobases, expanding the range of species covered and increasing its utility. Access to the MS spectral library by Walmsley et al. is facilitated through direct searches on the online MoNA database or by downloading the MS2 and MS3 spectra files in .MSP and .db formats. These formats are compatible with various open-source or commercial MS data processing software, including NIST MS Search, MS-Dial, MZmine, FreeStyle, and Compound Discoverer. Additionally, the .MSP file is versatile, as it can be converted into different library formats suitable for use with NIST, MassBank, HMDB, and PubChem.
Databases dedicated to RNA or protein adducts are limited. MODOMICS (https://iimcb.genesilico.pl/modomics/) stands out as a comprehensive database, featuring more than 170 RNA modifications mainly associated with naturally cellular functions, and it is consistently updated [20]. It provides comprehensive details on the chemical structures of modified rN, their biosynthetic pathways, the locations of modified residues in RNA sequences, and the enzymes that modify RNA. However, MODOMICS does not specifically include RNA adducts caused by exogenous or endogenous reactive/electrophilic chemicals resulting from environmental exposures. For protein adducts, UNIMOD (www.unimod.org) is a valuable resource for cataloging numerous protein modifications. Additionally, databases such as the Toxic Exposome Database (T3DB) (http://www.t3db.ca) and the Exposome-Explorer Database (http://exposome-explorer.iarc.fr), which are tailored to exposome research, may be relevant for adductomics [220]. However, none of the above databases offer MS/MS spectra or facilitate automated searching functions to identify adduct signals through HRMS analysis.
Advancements in databases and MS spectral libraries are key to advancing adductomics. Despite expansions in these areas, building a unified repository that includes DNA, RNA, and protein adducts remains a challenge. However, contributions from La Barbera et al. (2022) [218] and Walmsley et al. (2024) [35], along with ongoing enhancements in data processing technologies, suggest that the comprehensive integration of adductome databases may soon be achievable.
8. New challenges and solutions
Although adductomics has made significant advances in recent years, several technical challenges remain. Here, we outline these new challenges and explore potential solutions.
8.1. Retention time (RT) standardization in adductomics
Adductomics studies characterize each adduct, known or putative, by its RT, m/z, and peak intensity. In current adductomics data processing, minor variations in retention time can significantly impact comparisons across runs, emphasizing the critical need for retention time alignment as a foundational step in the research workflow [221]. Although RT is a critical factor in identifying adducts, many studies focus primarily on analyzing molecular structures through precise m/z from MS1 to MSn fragments, often overlooking the importance of RT. This oversight can compromise the specificity necessary for accurate adduct identification. Recently, the use of normalized retention time (iRT) has been adopted for analyzing modified nucleosides. Wang's team at UC Riverside employed the four canonical 2′-dNs as reference points, assigning an iRT score of 0 to 2′-deoxycytidine (the earliest eluting) and 100 to 2′-deoxyguanosine (the latest eluting) [221]. Similarly, for modified rN, they assigned arbitrary iRT values of 10 for cytidine and 100 for adenosine [222], establishing a framework for assigning iRT values to modified nucleosides.
We believe that the RT standardization using the iRT score will significantly enhance the comparability of adductomic studies across different laboratories, even when chromatographic conditions vary. Moreover, it has the potential to be incorporated into databases as a criterion to strengthen confidence in adduct identification, offering a very promising direction for future advancements in the field.
8.2. Integration of DNA, RNA, and protein adductome analyses: towards more comprehensive assessment of exposure
Currently, there are existing technologies [223] and commercial kits [224] capable of simultaneously extracting DNA, RNA, and protein as separate fractions. This will be advantageous for the innovative approach of simultaneous analysis of DNA, RNA, and protein adducts, which forms a cornerstone in multi-modifications analysis, particularly crucial when handling samples of limited size that permit only one extraction and analysis opportunity. As adductomics techniques advance to include crosslinks between DNA, RNA, and proteins, such as DRCL, DPCL, and RPCL, it will be crucial to determine in which extracted fraction specific crosslinks will be found. To date, there is no research to inform on this question. Additionally, when extracting DNA, RNA, and proteins, enzymatic hydrolysis processes are often required for adductome analysis. Therefore, the future development of universal enzymatic hydrolysis protocols (including the conversion of DNA/RNA to nucleosides and proteins to amino acids), capable of thoroughly releasing complex and diverse modifications in separate solutions of DNA, RNA, and protein, would facilitate subsequent exploration and analysis in adductomics. Although research has started to develop a protocol capable of fully enzymatically hydrolyzing DNA, RNA, and proteins, its effectiveness has yet to be fully verified (Figure 9) [58].
Figure 9.
A proposed universal method for comprehensive enzymatic hydrolysis of DNA, RNA, and proteins to streamline the integration of adductome analyses for DNA, RNA, and proteins. A protocol was proposed to release the adducts and crosslinks from the DNA/RNA/protein solutions, involving nuclease P1, alkaline phosphatase, snake venom phosphodiesterase I, RNase A, and protease. Prior to analysis, the digested solution underwent filtration using a centrifugal filter with a 3,000 Dalton (Da) molecular weight cutoff (MWCO). This figure was independently drawn for the present work with concepts taken from Refs. [58, 60, 126, 154].
For MS-based adductome analysis, enzymatic hydrolysis is the most frequently used method to release modifications from DNA, RNA and proteins. However, caution is required as adducts can hinder the activity of enzymes, leading to incomplete hydrolysis [73, 225]. Alternatively, acid hydrolysis, involving the direct digestion of modifications to free nucleobases under thermal-acid conditions, provides a straightforward and economical approach. Nonetheless, a significant drawback of this method is its inability to distinguish between DNA and RNA-derived adducts due to the loss of sugar moieties, and the potential for degradation of some adducts, in particular those generated from oxidation [226].
8.3. Differentiation between exogenously- and endogenously-derived modifications
Identifying whether DNA, RNA, and protein modifications originate from external environmental toxicants or internal processes is key to understanding the impact of the exposome on biological functions. We suggest that stable isotope labeling and MS-based adductomics (SILMS-adductomics) will provide a potent method for distinguishing exogenously derived adducts from those formed internally [227]. Figure 10 illustrates an innovative SILMS-adductomics strategy for determining the external/internal source of adducts, which is achieved by comparing unlabeled agent (with a molecular weight of M) and isotopically-labeled agent (with a molecular weight of M + Δ mass). Both agents are mixed in a 1:1 mole ratio and subjected to co-exposure, followed by LC-HRMS and subsequent post-data analysis. When an unlabeled adduct is compared with its isotope-labeled counterpart, both sharing identical RTs but differing in mass (Δ mass), we can infer the origins of adducts as follows: (i) When two adduct peaks elute at identical RTs with a consistent mass difference (Δ mass) and similar intensities (intensity ratio ≈ 1), it indicates that the external agent is directly associated with the modifications, without significant endogenous contribution. (ii) If two adduct peaks have the same RT and a certain Δ mass but show a substantial difference in peak intensities (unlabeled/labeled intensity ratio > 1), it suggests that the adduct is derived from both external and internal processes. This scenario indicates that in addition to the influence of external substances, internal biological activities also contribute to the formation of the adduct, such as modifications resulting from alcohol consumption [207]. Finally, (iii) if an adduct lacks a corresponding labeled peak, it indicates that the modification is entirely formed or induced endogenously.
Figure 10.
Proposed SILMS adductomics strategy for distinguishing between exogenously- and endogenously derived DNA/RNA/protein modifications.
9. Perspectives
Aristotle's insight that 'The whole is greater than the sum of its parts' resonates deeply within the field of adductomics. Adductomics utilizes advanced mass spectrometry, particularly high-resolution mass spectrometry (HRMS), to study stable covalent adducts, providing insights into the enduring molecular changes and their effects on cellular functions. It is noteworthy that ongoing efforts, including the incorporation of AI techniques (e.g., deep learning, ensemble learning, transfer learning etc.), show potential in exploring solutions for addressing the challenges associated with integrating multi-omics data [228], although a comprehensive solution remains elusive. We anticipate that the integrated approach of multi-adductomics will do more than simply document adducts; it will substantially deepen our understanding of the exposome, potentially transforming future perspectives within the field. Furthermore, we predict that multi-adductomics will become a major player in the biomedical sector, driving significant advancements in personalized healthcare and therapeutic discoveries. This will be achieved through a detailed analysis of DNA, RNA, and protein adducts. The establishment of the International Adductomics Consortium (IAC; https://adductomics.weebly.com/) is strategically positioned to address key gaps in our understanding and methodologies, fostering the development of innovative approaches that enhance the comprehensiveness and applicability of adductomics research. Similarly, the Exposomics Consortium (https://www.exposomicsconsortium.org/) aims to unite experts to pragmatically define the exposome for healthcare and public health professionals, identify gaps in knowledge or techniques, and cultivate a new generation of scientists dedicated to exploring the complex environmental influences on health. Together, these consortia are driving significant advances in the study of environmental and molecular interactions, expanding our understanding of the exposome to accelerate precision environmental health and personalized medicine.
Highlights.
Significance of multi-adductomics analysis for elucidating the exposome
Current developments for DNA, RNA and protein adductomics
Advances in HRMS technology facilitating multi-adductomics analysis
Discussion of challenges and perspectives for multi-adductomics
Acknowledgements
This work was funded by the National Science and Technology Council, Taiwan [grant numbers NSTC 112-2314-B-040-013-MY3, NSTC 112-2628-B-040-002 and NSTC 112-2628-B-040-001] and Chung Shan Medical University [grant number CSMU-INT-112-001-MY2]. The research reported in this publication was also supported, in part, by the National Institute of Environmental Health Sciences of the National Institutes of Health under award number R01ES030557. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Abbreviations
- 2'-dN
2'-deoxyribonucleoside(s)
- 4-ABP
4-aminobiphenyl
- AA
Amino acids
- Ade
Adenine
- AML
Acute myeloid leukemia
- AP
Apurinic/apyrimidinic
- Arg
Arginine
- B[a]P
Benzo[a]pyrene
- CEs
Catechol estrogens
- CID
Collision-induced dissociation
- CNL
Constant neutral loss
- Cys34
Cysteine-34
- Cyt
Cytosine
- Da
Dalton
- DDA
Data-dependent acquisition
- DDA-CNL-MS3
Data-dependent acquisition combining constant neutral loss triggering MS3
- DDA-MS2
Data-dependent acquisition triggering MS2
- DDCL
DNA-DNA crosslinks
- DIA
Data-independent acquisition
- DIA-PASEF
Parallel accumulation-serial fragmentation combined with data-independent acquisition
- DPCL
DNA-protein crosslinks
- dR
2-deoxyribose
- DRCL
DNA-RNA crosslinks
- E. coli
Escherichia coli
- FIRE
‘Fluorescein isothiocyanate’, ‘R-group’ and ‘Edman degradation’
- FITC
Fluorescein isothiocyanate
- FS-SRM
Fixed-step selected reaction monitoring
- FTH
Fluorescein thiohydantoin
- Gua
Guanine
- Hb
Hemoglobin
- HCD
Higher energy collisional dissociation
- His
Histidine
- HMDB
Human Metabolome Database
- HRMS
High-resolution mass spectrometry
- HSA
Human serum albumin
- ICLs
Inter-strand crosslinks
- iRT
Normalized retention time
- LC
Liquid chromatography
- LC-MS
Liquid chromatography-mass spectrometry
- LIT
Linear ion trap
- LIT-Orbitrap
Linear ion trap-Orbitrap MS
- lncRNA
Long noncoding RNA
- LPO
lipid peroxidation
- LRMS
Low-resolution mass spectrometry
- Lys
Lysine
- Lys525
Lysine-525
- m/z
Mass-to-charge ratio
- MeR
2'-O-methylated ribose
- Met
Methionine
- MoNA
MassBank of North America
- mRNA
Messenger RNA
- MS
Mass spectrometry
- MSn
Multistage fragmentation
- MWCO
Molecular weight cutoff
- NA
Nucleic acids
- nB
Nucleobase
- NBS
Neonatal blood spots
- NIST
National Institute of Standards and Technology
- NL
Neutral loss
- NNK
4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone
- ODNs
Oligodeoxyribonucleotides
- PAH
Polycyclic aromatic hydrocarbon
- PPCL
Protein-protein crosslinks
- PRM
Parallel reaction monitoring
- Q
Quadrupole
- Q-LIT-Orbitrap
Quadrupole-Linear ion trap-Orbitrap MS
- Q-Orbitrap
Quadrupole-Orbitrap MS
- QqQ-MS
Triple-Quadrupole MS
- Q-TOF
Quadrupole Time-of-Flight
- R
Ribose
- RBCs
Red blood cells
- rN
Ribonucleosides
- ROS
Reactive oxygen species
- RPCL
RNA-protein crosslinks
- RRCL
RNA-RNA crosslinks
- rRNA
Ribosomal RNA
- RT
Retention time
- Ser
Serine
- SILMS
Stable isotope labeling mass spectrometry
- SIM
Selected ion monitoring
- snRNA
Small nuclear RNA
- SWATH
Sequential window acquisition of all theoretical mass spectra
- TIMS-TOF
Trapped ion mobility spectrometry-time of flight mass spectrometry
- Thy
Thymine
- tRNA
Transfer RNA
- Tyr
Tyrosine
- Val
Valine
- Wide-SIM/MS2
Wide selected ion monitoring tandem mass spectrometry
- XL-MS
Crosslinking mass spectrometry
Footnotes
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Mu-Rong Chao reports financial support was provided by Chung Shan Medical University. Yuan-Jhe Chang reports financial support was provided by Chung Shan Medical University. Marcus S. Cooke reports financial support was provided by University of South Florida. Chiung-Wen Hu reports financial support was provided by Chung Shan Medical University. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Data availability
Data will be made available on request.
References
- [1].Krawic C, Zhitkovich A, Chemical mechanisms of DNA damage by carcinogenic chromium(VI), Adv. Pharmacol 96 (2023) 25–46, 10.1016/bs.apha.2022.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Poirier MC, Chemical-induced DNA damage and human cancer risk, Discov. Med 14 (2012) 283–288. [PMC free article] [PubMed] [Google Scholar]
- [3].Wild CP, Environmental exposure measurement in cancer epidemiology, Mutagenesis 24 (2009) 117–125, 10.1093/mutage/gen061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Islam MT, Radiation interactions with biological systems, Int. J. Radiat. Biol 93 (2017) 487–493, 10.1080/09553002.2017.1286050. [DOI] [PubMed] [Google Scholar]
- [5].Park SL, Le Marchand L, Cheng G, Balbo S, Chen ML, Carmella SG, Thomson NM, Lee YH, Patel YM, Stram DO, Jensen J, Hatsukami DK, Murphy SE, Hecht SS, Quantitation of DNA adducts resulting from acrolein exposure and lipid peroxidation in oral cells of cigarette smokers from three racial/ethnic groups with differing risks for lung cancer, Chem. Res. Toxicol 35 (2022) 1914–1922, 10.1021/acs.chemrestox.2c00171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Liao PC, Li CM, Hung CW, Chen SH, Quantitative detection of N7-(2-hydroxyethyl)guanine adducts in DNA using high-performance liquid chromatography/electrospray ionization tandem mass spectrometry, J. Mass Spectrom 36 (2001) 336–343, 10.1002/jms.132. [DOI] [PubMed] [Google Scholar]
- [7].Bukowska B, Duchnowicz P, Tumer TB, Michalowicz J, Krokosz A, Precarcinogens in food-mechanism of action, formation of DNA adducts and preventive measures, Food Control 152 (2023) 109884, 10.1016/j.foodcont.2023.109884. [DOI] [Google Scholar]
- [8].Shih YM, Cooke MS, Pan CH, Chao MR, Hu CW, Clinical relevance of guanine-derived urinary biomarkers of oxidative stress, determined by LC-MS/MS, Redox Biol. 20 (2019) 556–565, 10.1016/j.redox.2018.11.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Moldogazieva NT, Zavadskiy SP, Astakhov DV, Terentiev AA, Lipid peroxidation: Reactive carbonyl species, protein/DNA adducts, and signaling switches in oxidative stress and cancer, Biochem. Biophys. Res. Commun 687 (2023) 149167, 10.1016/j.bbrc.2023.149167. [DOI] [PubMed] [Google Scholar]
- [10].Patrasso EA, Raikundalia S, Arango D, Regulation of the epigenome through RNA modifications, Chromosoma 132 (2023) 231–246, 10.1007/s00412-023-00794-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Zittlau K, Nashier P, Cavarischia-Rega C, Macek B, Spät P, Nalpas N, Recent progress in quantitative phosphoproteomics, Expert Rev. Proteomics 20 (2023) 469–482, 10.1080/14789450.2023.2295872. [DOI] [PubMed] [Google Scholar]
- [12].Amente S, Scala G, Majello B, Azmoun S, Tempest HG, Premi S, Cooke MS, Genome-wide mapping of genomic DNA damage: Methods and implications, Cell. Mol. Life Sci 78 (2021) 6745–6762, 10.1007/s00018-021-03923-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Gorini F, Scala G, Cooke MS, Majello B, Amente S, Towards a comprehensive view of 8-oxo-7,8-dihydro-2′-deoxyguanosine: Highlighting the intertwined roles of DNA damage and epigenetics in genomic instability, DNA Repair 97 (2021) 103027, 10.1016/j.dnarep.2020.103027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Poirier MC, Linking DNA adduct formation and human cancer risk in chemical carcinogenesis, Environ. Mol. Mutagen 57 (2016) 499–507, 10.1002/em.22030. [DOI] [PubMed] [Google Scholar]
- [15].Nestmann ER, Bryant DW, Carr CJ, Toxicological significance of DNA adducts: Summary of discussions with an expert pane, Regul. Toxicol. Pharmacol 24 (1996) 9–18, 10.1006/rtph.1996.0059. [DOI] [PubMed] [Google Scholar]
- [16].Krieger KL, Mann EK, Lee KJ, Bolterstein E, Jebakumar D, Ittmann MM, Dal Zotto VL, Shaban M, Sreekumar A, Gassman NR, Spatial mapping of the DNA adducts in cancer, DNA Repair 128 (2023) 103529, 10.1016/j.dnarep.2023.103529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Hecht SS, Hatsukami DK, Smokeless tobacco and cigarette smoking: Chemical mechanisms and cancer prevention, Nat. Rev. Cancer 22 (2022) 143–155, 10.1038/s41568-021-00423-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Esteve-Puig R, Bueno-Costa A, Esteller M, Writers, readers and erasers of RNA modifications in cancer, Cancer Lett. 474 (2020) 127–137, 10.1016/j.canlet.2020.01.021. [DOI] [PubMed] [Google Scholar]
- [19].Yeates JAM, Nghe P, Lehman N, Topological and thermodynamic factors that influence the evolution of small networks of catalytic RNA species, RNA 23 (2017) 1088–1096, 10.1261/rna.061093.117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Cappannini A, Ray A, Purta E, Mukherjee S, Boccaletto P, Moafinejad SN, Lechner A, Barchet C, Klaholz BP, Stefaniak F, Modomics: A database of RNA modifications and related information. 2023 update, Nucleic Acids Res. 52 (2024) D239–D244, 10.1093/nar/gks1007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Knight HM, Öz MD, PerezGrovas-Saltijeral A, Dysregulation of RNA modification systems in clinical populations with neurocognitive disorders, Neural Regener. Res 19 (2024) 1256–1261, 10.4103/1673-5374.385858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22].Zhou MY, Wang DO, Li WW, Zheng J, RNA adduction derived from electrophilic species in vitro and in vivo, Chem.-Biol. Interact 351 (2022) 109748, 10.1016/j.cbi.2021.109748. [DOI] [PubMed] [Google Scholar]
- [23].Liu ZQ, Chen XT, Li Z, Ye W, Ding HY, Li PF, Aung LHH, Role of RNA oxidation in neurodegenerative diseases, Int. J. Mol. Sci 21 (2020) 5022, 10.3390/ijms21145022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24].Takeshita T, Kanaly RA, In vitro DNA/RNA adductomics to confirm DNA damage caused by benzo[a]pyrene in the Hep G2 cell line, Front. Chem 7 (2019) 491, 10.3389/fchem.2019.00491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Hu CW, Chang YJ, Hsu YW, Chen JL, Wang TS, Chao MR, Comprehensive analysis of the formation and stability of peroxynitrite-derived 8-nitroguanine by LC-MS/MS: Strategy for the quantitative analysis of cellular 8-nitroguanine, Free Radical Biol. Med 101 (2016) 348–355, 10.1016/j.freeradbiomed.2016.10.505. [DOI] [PubMed] [Google Scholar]
- [26].Tsao N, Scharer OD, Mosammaparast N, The complexity and regulation of repair of alkylation damage to nucleic acids, Crit. Rev. Biochem. Mol. Biol 56 (2021) 125–136, 10.1080/10409238.2020.1869173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Bellacosa A, Moss EG, RNA repair: Damage control, Curr. Biol 13 (2003) R482–R484, 10.1016/S0960-9822(03)00408-1. [DOI] [PubMed] [Google Scholar]
- [28].Chao MR, Evans MD, Hu CW, Ji YHE, Moller P, Rossner P, Cooke MS, Biomarkers of nucleic acid oxidation - a summary state-of-the-art, Redox Biol. 42 (2021) 101872, 10.1016/j.redox.2021.101872. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [29].Keenan KE, Zachman DK, Hirschey MD, Discovering the landscape of protein modifications, Mol. Cell 81 (2021) 1868–1878, 10.1016/j.molcel.2021.03.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Riffle M, Hoopmann MR, Jaschob D, Zhong G, Moritz RL, MacCoss MJ, Davis TN, Isoherranen N, Zelter A, Discovery and visualization of uncharacterized drug-protein adducts using mass spectrometry, Anal. Chem 94 (2022) 3501–3509, 10.1021/acs.analchem.1c04101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Karran P, Brem R, Protein oxidation, UVA and human DNA repair, DNA Repair 44 (2016) 178–185, 10.1016/j.dnarep.2016.05.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].Gan JP, Zhang HY, Humphreys WG, Drug-protein adducts: Chemistry, mechanisms of toxicity, and methods of characterization, Chem. Res. Toxicol 29 (2016) 2040–2057, 10.1021/acs.chemrestox.6b00274. [DOI] [PubMed] [Google Scholar]
- [33].Nakamura T, Oh CK, Zhang X, Tannenbaum SR, Lipton SA, Protein transnitrosylation signaling networks contribute to inflammaging and neurodegenerative disorders, Antioxid. Redox Signaling 35 (2021) 531–550, 10.1089/ars.2021.0081. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [34].Hurben AK, Tretyakova NY, Role of protein damage inflicted by dopamine metabolites in parkinson's disease: Evidence, tools, and outlook, Chem. Res. Toxicol 35 (2022) 1789–1804, 10.1021/acs.chemrestox.2c00193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [35].Walmsley SJ, Guo J, Tarifa A, DeCaprio AP, Cooke MS, Turesky RJ, Villalta PW, Mass spectral library for DNA adductomics, Chem. Res. Toxicol 37 (2024) 302–310, 10.1021/acs.chemrestox.3c00302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [36].Chen HJC, Mass spectrometry analysis of DNA and protein adducts as biomarkers in human exposure to cigarette smoking: Acrolein as an example, Chem. Res. Toxicol 36 (2023) 132–140, 10.1021/acs.chemrestox.2c00354. [DOI] [PubMed] [Google Scholar]
- [37].Phillips DH, Preston G, Sozeri O, Adductomics - measurement of DNA and protein adducts in human tissues as an approach to defining the exposome, Mutagenesis 29 (2014) 502–502. [Google Scholar]
- [38].Cooke MS, Chang YJ, Chen YR, Hu CW, Chao MR, Nucleic acid adductomics - the next generation of adductomics towards assessing environmental health risks, Sci. Total Environ 856 (2023) 159192, 10.1016/j.scitotenv.2022.159192. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [39].Behl T, Rachamalla M, Najda A, Sehgal A, Singh S, Sharma N, Bhatia S, Al-Harrasi A, Chigurupati S, Vargas-De-La-Cruz C, Hobani YH, Mohan S, Goyal A, Katyal T, Solarska E, Bungau S, Applications of adductomics in chemically induced adverse outcomes and major emphasis on DNA adductomics: A pathbreaking tool in biomedical research, Int. J. Mol. Sci 22 (2021) 10141, 10.3390/ijms221810141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [40].Balbo S, Turesky RJ, Villalta PW, DNA adductomics, Chem. Res. Toxicol 27 (2014) 356–366, 10.1021/tx4004352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [41].Cooke MS, Hu CW, Chao MR, Editorial: Mass spectrometry for adductomic analysis, Front. Chem 7 (2019) 794, 10.3389/fchem.2019.00794. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [42].Wild CP, The exposome: From concept to utility, Int. J. Epidemiol 41 (2012) 24–32, 10.1093/ije/dyr236. [DOI] [PubMed] [Google Scholar]
- [43].Vineis P, Robinson O, Chadeau-Hyam M, Dehghan A, Mudway I, Dagnino S, What is new in the exposome?, Environ. Int 143 (2020) 105887, 10.1016/j.envint.2020.105887. [DOI] [PubMed] [Google Scholar]
- [44].Rappaport SM, Barupal DK, Wishart D, Vineis P, Scalbert A, The blood exposome and its role in discovering causes of disease, Environ. Health Perspect 122 (2014) 769–774, 10.1289/ehp.1308015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [45].Dennis KK, Marder E, Balshaw DM, Cui YX, Lynes MA, Patti GJ, Rappaport SM, Shaughnessy DT, Vrijheid M, Barr DB, Biomonitoring in the era of the exposome, Environ. Health Perspect 125 (2017) 502–510, 10.1289/Ehp474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [46].Maitre L, Bustamante M, Hernández-Ferrer C, Thiel D, Lau CHE, Siskos A, Vives-Usano M, Ruiz-Arenas C, Pelegri-Sisó D, Robinson O, Mason D, Wright J, Cadiou S, Slama R, Heude B, Casas M, Sunyer J, Papadopoulou EZ, Gutzkow KB, Andrusaityte S, Grazuleviciene R, Vafeiadi M, Chatzi L, Sakhi AK, Thomsen C, Tamayo I, Nieuwenhuijsen M, Urquiza J, Borràs E, Sabidó E, Quintela I, Carracedo A, Estivill X, Coen M, González JR, Keun HC, Vrijheid M, Multi-omics signatures of the human early life exposome, Nat. Commun 13 (2022) 7024, 10.1038/s41467-022-34422-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].Piersimoni L, Kastritis PL, Arlt C, Sinz A, Cross-linking mass spectrometry for investigating protein conformations and protein-protein interactions-a method for all seasons, Chem. Rev 122 (2022) 7500–7531, 10.1021/acs.chemrev.1c00786. [DOI] [PubMed] [Google Scholar]
- [48].Zhang P, Carlsten C, Chaleckis R, Hanhineva K, Huang MN, Isobe T, Koistinen VM, Meister I, Papazian S, Sdougkou K, Xie HY, Martin JW, Rappaport SM, Tsugawa H, Walker D, Woodruff TJ, Wright RO, Wheelock CE, Defining the scope of exposome studies and research needs from a multidisciplinary perspective, Environ. Sci. Technol. Lett 8 (2021) 839–852, 10.1021/acs.estlett.1c00648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [49].Totsuka Y, New horizons of DNA adductome for exploring environmental causes of cancer, Cancer Sci. 63 (2022) 9–9, 10.1111/cas.14666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [50].Nie MH, Li HL, Innovation in cross-linking mass spectrometry workflows: Toward a comprehensive, flexible, and customizable data analysis platform, J. Am. Soc. Mass Spectrom 34 (2023) 1949–1956, 10.1021/jasms.3c00123. [DOI] [PubMed] [Google Scholar]
- [51].Sinz A, Chemical cross-linking and mass spectrometry to map three-dimensional protein structures and protein-protein interactions, Mass Spectrom. Rev 25 (2006) 663–682, 10.1002/mas.20082. [DOI] [PubMed] [Google Scholar]
- [52].Bryant M, Lay J Jr, Chiarelli M, Development of fast atom bombardment mass spectral methods for the identification of carcinogen-nucleoside adducts, J. Am. Soc. Mass Spectrom 3 (1992) 360–371, 10.1016/1044-0305(92)87064-6. [DOI] [PubMed] [Google Scholar]
- [53].Wolf SM, Vouros P, Norwood C, Jackim E, Identification of deoxynucleoside-polyaromatic hydrocarbon adducts by capillary zone electrophoresis-continuous flow-fast atom bombardment mass spectrometry, J. Am. Soc. Mass Spectrom 3 (1992) 757–761, 10.1016/1044-0305(92)87089-H. [DOI] [PubMed] [Google Scholar]
- [54].Kanaly RA, Hanaoka T, Sugimura H, Toda H, Matsui S, Matsuda T, Development of the adductome approach to detect DNA damage in humans, Antioxid. Redox Signaling 8 (2006) 993–1001, 10.1089/ars.2006.8.993. [DOI] [PubMed] [Google Scholar]
- [55].Chen YC, Hsu JF, Chang CW, Li SW, Yang YC, Chao MR, Chen HJC, Liao PC, Connecting chemical exposome to human health using high-resolution mass spectrometry-based biomonitoring: Recent advances and future perspectives, Mass Spectrom. Rev 42 (2023) 2466–2486, 10.1002/mas.21805. [DOI] [PubMed] [Google Scholar]
- [56].Chang YJ, Cooke MS, Chen YR, Yang SF, Li PS, Hu CW, Chao MR, Is high resolution a strict requirement for mass spectrometry-based cellular DNA adductomics?, Chemosphere 274 (2021) 129991, 10.1016/j.chemosphere.2021.129991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [57].Singh R, Farmer PB, Liquid chromatography-electrospray ionization-mass spectrometry: The future of DNA adduct detection, Carcinogenesis 27 (2006) 178–196, 10.1093/carcin/bgi260. [DOI] [PubMed] [Google Scholar]
- [58].Hu CW, Chang YJ, Chang WH, Cooke MS, Chen YR, Chao MR, A novel adductomics workflow incorporating FeatureHunter software: Rapid detection of nucleic acid modifications for studying the exposome, Environ. Sci. Technol 58 (2024) 75–89, 10.1021/acs.est.3c04674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [59].Gorokhova E, Martella G, Motwani NH, Tretyakova NY, Sundelin B, Motwani HV, DNA epigenetic marks are linked to embryo aberrations in amphipods, Sci. Rep 10 (2020) 655, 10.1038/s41598-020-57465-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [60].Martella G, Motwani NH, Khan Z, Sousa PF, Gorokhova E, Motwani HV, Simultaneous RNA and DNA adductomics using single data-independent acquisition mass spectrometry analysis, Chem. Res. Toxicol 36 (2023) 1471–1482, 10.1021/acs.chemrestox.3c00041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [61].Höfler S, Carlomagno T, Structural and functional roles of 2′-o-ribose methylations and their enzymatic machinery across multiple classes of RNAs, Curr. Opin. Struct. Biol 65 (2020) 42–50, 10.1016/j.sbi.2020.05.008. [DOI] [PubMed] [Google Scholar]
- [62].Delaunay S, Helm M, Frye M, RNA modifications in physiology and disease: Towards clinical applications, Nat. Rev. Genet 25 (2024) 104–122, 10.1038/s41576-023-00645-2. [DOI] [PubMed] [Google Scholar]
- [63].He CC, Hamlow LA, Devereaux ZJ, Zhu Y, Nei YW, Fan L, McNary CP, Maitre P, Steinmetz V, Schindler B, Compagnon I, Armentrout PB, Rodgers MT, Structural and energetic effects of O2′-ribose methylation of protonated purine nucleosides, J. Phys. Chem. B 122 (2018) 9147–9160, 10.1021/acs.jpcb.8b07687. [DOI] [PubMed] [Google Scholar]
- [64].He CC, Hamlow LA, Zhu Y, Nei YW, Fan L, McNary CP, Maître P, Steinmetz V, Schindler B, Compagnon I, Armentrout PB, Rodgers MT, Structural and energetic effects of O2′-ribose methylation of protonated pyrimidine nucleosides, J. Am. Soc. Mass Spectrom 30 (2019) 2318–2334, 10.1007/s13361-019-02300-9. [DOI] [PubMed] [Google Scholar]
- [65].Thüring K, Schmid K, Keller P, Helm M, Analysis of RNA modifications by liquid chromatography–tandem mass spectrometry, Methods 107 (2016) 48–56, 10.1016/j.ymeth.2016.03.019. [DOI] [PubMed] [Google Scholar]
- [66].Stornetta A, Villalta PW, Hecht SS, Sturla SJ, Balbo S, Screening for DNA alkylation mono and cross-linked adducts with a comprehensive LC-MS3 adductomic approach, Anal. Chem 87 (2015) 11706–11713, 10.1021/acs.analchem.5b02759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [67].Guidolin V, Li Y, Jacobs FC, MacMillan ML, Villalta PW, Hecht SS, Balbo S, Characterization and quantitation of busulfan DNA adducts in the blood of patients receiving busulfan therapy, Mol. Ther. Oncolytics 28 (2023) 197–210, 10.1016/j.omto.2023.01.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [68].Iannitti-Tito P, Weimann A, Wickham G, Sheil MM, Structural analysis of drug-DNA adducts by tandem mass spectrometry, Analyst 125 (2000) 627–633, 10.1039/a908920i. [DOI] [PubMed] [Google Scholar]
- [69].Tang Y, Zhang JL, Recent developments in DNA adduct analysis using liquid chromatography coupled with mass spectrometry, J. Sep. Sci 43 (2020) 31–55, 10.1002/jssc.201900737. [DOI] [PubMed] [Google Scholar]
- [70].Cooke MS, Hu CW, Chang YJ, Chao MR, Urinary DNA adductomics–a novel approach for exposomics, Environ. Int 121 (2018) 1033–1038, 10.1016/j.envint.2018.10.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [71].Villalta PW, Balbo S, The future of DNA adductomic analysis, Int. J. Mol. Sci 18 (2017) 1870, 10.3390/ijms18091870. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [72].Lockridge O, Overview of adductomics in toxicology, Curr. Protoc 3 (2023) e672, 10.1002/cpz1.672. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [73].Hu CW, Chang YJ, Cooke MS, Chao MR, DNA crosslinkomics: A tool for the comprehensive assessment of interstrand crosslinks using high resolution mass spectrometry, Anal. Chem 91 (2019) 15193–15203, 10.1021/acs.analchem.9b04068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [74].Krassnig SC, Maser M, Probst NA, Werner J, Schlett C, Schumann N, von Scheven G, Mangerich A, Burkle A, Comparative analysis of chlorambucil-induced DNA lesion formation and repair in a spectrum of different human cell systems, Toxicol. Rep 10 (2023) 171–189, 10.1016/j.toxrep.2023.01.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [75].Hu CW, Chen CM, Ho HH, Chao MR, Simultaneous quantification of methylated purines in DNA by isotope dilution LC-MS/MS coupled with automated solid-phase extraction, Anal. Bioanal. Chem 402 (2012) 1199–1208, 10.1007/s00216-011-5559-1. [DOI] [PubMed] [Google Scholar]
- [76].Chang YJ, Cooke MS, Hu CW, Chao MR, Novel approach to integrated DNA adductomics for the assessment of in vitro and in vivo environmental exposures, Arch. Toxicol 92 (2018) 2665–2680, 10.1007/s00204-018-2252-6. [DOI] [PubMed] [Google Scholar]
- [77].Baiken Y, Kanayeva D, Taipakova S, Groisman R, Ishchenko AA, Begimbetova D, Matkarimov B, Saparbaev M, Role of base excision repair pathway in the processing of complex DNA damage generated by oxidative stress and anticancer drugs, Front. Cell Dev. Biol 8 (2021) 617884, 10.3389/fcell.2020.617884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [78].Hu CW, Hsu YW, Chen JL, Tam LM, Chao MR, Direct analysis of tobacco-specific nitrosamine NNK and its metabolite NNAL in human urine by LC-MS/MS: Evidence of linkage to methylated DNA lesions, Arch. Toxicol 88 (2014) 291–299, 10.1007/s00204-013-1137-y. [DOI] [PubMed] [Google Scholar]
- [79].Elliott P, Peakman TC, Biobank U, The UK biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine, Int. J. Epidemiol 37 (2008) 234–244, 10.1093/ije/dym276. [DOI] [PubMed] [Google Scholar]
- [80].Hu CW, Cooke MS, Wang YJ, Chao MR, Commentary on: Is preheat necessary for the measurement of 8-oxo-7,8-dihydroguanosine and 8-oxo-7,8-dihydro-2′-deoxyguanosine in urine samples, J. Clin. Lab. Anal 37 (2023) e24874, 10.1002/jcla.24874. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [81].Wang YA, Wong TY, Chan W, Quantitation of the DNA adduct of semicarbazide in organs of semicarbazide-treated rats by isotope-dilution liquid chromatography-tandem mass spectrometry: A comparative study with the RNA adduct, Chem. Res. Toxicol 29 (2016) 1560–1564, 10.1021/acs.chemrestox.6b00232. [DOI] [PubMed] [Google Scholar]
- [82].Hankin JA, Jones DNM, Murphy RC, Covalent binding of leukotriene A4 to DNA and RNA, Chem. Res. Toxicol 16 (2003) 551–561, 10.1021/tx034018+. [DOI] [PubMed] [Google Scholar]
- [83].Teichert F, Winkler S, Keun HC, Steward WP, Gescher AJ, Farmer PB, Singh R, Evaluation of urinary ribonucleoside profiling for clinical biomarker discovery using constant neutral loss scanning liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom 25 (2011) 2071–2082, 10.1002/rcm.5086. [DOI] [PubMed] [Google Scholar]
- [84].Leung EMK, Chan W, Quantification of aristolochic acid-RNA adducts in the urine of aristolochic acid-treated rats by liquid chromatography-tandem mass spectrometry, Chem. Res. Toxicol 28 (2015) 567–569, 10.1021/acs.chemrestox.5b00021. [DOI] [PubMed] [Google Scholar]
- [85].Lu ZW, Liu XY, Li XJ, Zhai CJ, Shi YL, Gao XY, BH+/MH+-matching method for discovery of cis-diol-containing modified nucleosides in urine by ribose-targeted solid phase extraction followed by dual-mass spectrometry platform identification, J. Pharm. Biomed. Anal 210 (2022) 114555, 10.1016/j.jpba.2021.114555. [DOI] [PubMed] [Google Scholar]
- [86].Branco PS, Chiarelli MP, Lay JO, Beland FA, Low energy tandem mass spectrometry of deoxynucleoside adducts of polycyclic aromatic hydrocarbon dihydrodiol-epoxides, J. Am. Soc. Mass Spectrom 6 (1995) 248–256, 10.1016/1044-0305(94)00162-S. [DOI] [PubMed] [Google Scholar]
- [87].Rindgen D, Turesky RJ, Vouros P, Determination of in vitro formed DNA adducts of 2-amino-1-methyl-6-phenylimidazo [4, 5-b] pyridine using capillary liquid chromatography/electrospray ionization/tandem mass spectrometry, Chem. Res. Toxicol 8 (1995) 1005–1013, 10.1021/tx00050a003. [DOI] [PubMed] [Google Scholar]
- [88].Gangl ET, Turesky RJ, Vouros P, Determination of in vitro-and in vivo-formed DNA adducts of 2-amino-3-methylimidazo [4, 5-f] quinoline by capillary liquid chromatography/microelectrospray mass spectrometry, Chem. Res. Toxicol 12 (1999) 1019–1027, 10.1021/tx990060m. [DOI] [PubMed] [Google Scholar]
- [89].Kanaly RA, Matsui S, Hanaoka T, Matsuda T, Application of the adductome approach to assess intertissue DNA damage variations in human lung and esophagus, Mutat. Res., Fundam. Mol. Mech. Mutagen 625 (2007) 83–93, 10.1016/j.mrfmmm.2007.05.006. [DOI] [PubMed] [Google Scholar]
- [90].Bessette EE, Goodenough AK, Langouët S, Yasa I, Kozekov ID, Spivack SD, Turesky RJ, Screening for DNA adducts by data-dependent constant neutral loss-triple stage mass spectrometry with a linear quadrupole ion trap mass spectrometer, Anal. Chem 81 (2009) 809–819, 10.1021/ac802096p. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [91].Inagaki S, Hirashima H, Esaka Y, Higashi T, Min JZ, Toyo’oka T, Screening DNA adducts by LC–ESI–MS–MS: Application to screening new adducts formed from acrylamide, Chromatographia 72 (2010) 1043–1048, 10.1365/s10337-010-1783-7. [DOI] [Google Scholar]
- [92].Singh R, Teichert F, Seidel A, Roach J, Cordell R, Cheng MK, Frank H, Steward WP, Manson MM, Farmer PB, Development of a targeted adductomic method for the determination of polycyclic aromatic hydrocarbon DNA adducts using online column-switching liquid chromatography/tandem mass spectrometry, Rapid Commun. Mass Spectrom 24 (2010) 2329–2340, 10.1002/rcm.4645. [DOI] [PubMed] [Google Scholar]
- [93].Spilsberg B, Rundberget T, Johannessen LE, Kristoffersen AB, Holst-Jensen A, Berdal KG, Detection of food-derived damaged nucleosides with possible adverse effects on human health using a global adductomics approach, J. Agric. Food Chem 58 (2010) 6370–6375, 10.1021/jf903065a. [DOI] [PubMed] [Google Scholar]
- [94].Chou PH, Kageyama S, Matsuda S, Kanemoto K, Sasada Y, Oka M, Shinmura K, Mori H, Kawai K, Kasai H, Detection of lipid peroxidation-induced DNA adducts caused by 4-oxo-2 (E)-nonenal and 4-oxo-2 (E)-hexenal in human autopsy tissues, Chem. Res. Toxicol 23 (2010) 1442–1448, 10.1021/tx100047d. [DOI] [PubMed] [Google Scholar]
- [95].Kato K, Yamamura E, Kawanishi M, Yagi T, Matsuda T, Sugiyama A, Uno Y, Application of the DNA adductome approach to assess the DNA-damaging capability of in vitro micronucleus test-positive compounds, Mutat. Res., Genet. Toxicol. Environ. Mutagen 721 (2011) 21–26, 10.1016/j.mrgentox.2010.11.012. [DOI] [PubMed] [Google Scholar]
- [96].Matsuda T, Tao H, Goto M, Yamada H, Suzuki M, Wu Y, Xiao N, He Q, Guo W, Cai Z, Lipid peroxidation-induced DNA adducts in human gastric mucosa, Carcinogenesis 34 (2013) 121–127, 10.1093/carcin/bgs327. [DOI] [PubMed] [Google Scholar]
- [97].Balbo S, Hecht SS, Upadhyaya P, Villalta PW, Application of a high-resolution mass-spectrometry-based DNA adductomics approach for identification of DNA adducts in complex mixtures, Anal. Chem 86 (2014) 1744–1752, 10.1021/ac403565m. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [98].Ishii Y, Takasu S, Kuroda K, Matsushita K, Kijima A, Nohmi T, Ogawa K, Umemura T, Combined application of comprehensive analysis for DNA modification and reporter gene mutation assay to evaluate kidneys of gpt delta rats given madder color or its constituents, Anal. Bioanal. Chem 406 (2014) 2467–2475, 10.1007/s00216-014-7621-2. [DOI] [PubMed] [Google Scholar]
- [99].Hemeryck LY, Decloedt AI, Bussche JV, Geboes KP, Vanhaecke L, High resolution mass spectrometry based profiling of diet-related deoxyribonucleic acid adducts, Anal. Chim. Acta 892 (2015) 123–131, 10.1016/j.aca.2015.08.019. [DOI] [PubMed] [Google Scholar]
- [100].Kanaly RA, Micheletto R, Matsuda T, Utsuno Y, Ozeki Y, Hamamura N, Application of DNA adductomics to soil bacterium Sphingobium sp. strain KK 22, Microbiologyopen 4 (2015) 841–856, 10.1002/mbo3.283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [101].Ishino K, Kato T, Kato M, Shibata T, Watanabe M, Wakabayashi K, Nakagama H, Totsuka Y, Comprehensive DNA adduct analysis reveals pulmonary inflammatory response contributes to genotoxic action of magnetite nanoparticles, Int. J. Mol. Sci 16 (2015) 3474–3492, 10.3390/ijms16023474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [102].Hemeryck LY, Rombouts C, Hecke TV, Van Meulebroek L, Bussche JV, De Smet S, Vanhaecke L, In vitro DNA adduct profiling to mechanistically link red meat consumption to colon cancer promotion, Toxicol. Res 5 (2016) 1346–1358, 10.1039/c6tx00079g. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [103].Yao C, Feng YL, A nontargeted screening method for covalent DNA adducts and DNA modification selectivity using liquid chromatography-tandem mass spectrometry, Talanta 159 (2016) 93–102, 10.1016/j.talanta.2016.05.074. [DOI] [PubMed] [Google Scholar]
- [104].Schmied-Tobies MI, Paschke H, Reemtsma T, Combined chemoassay and mass spectrometric approach to study the reactive potential of electrophiles towards deoxynucleosides as model for DNA, Chemosphere 151 (2016) 263–270, 10.1016/j.chemosphere.2016.02.052. [DOI] [PubMed] [Google Scholar]
- [105].Yao C, Foster WG, Sadeu JC, Siddique S, Zhu J, Feng Y-L, Screening for DNA adducts in ovarian follicles exposed to benzo[a]pyrene and cigarette smoke condensate using liquid chromatography-tandem mass spectrometry, Sci. Total Environ 575 (2017) 742–749, 10.1016/j.scitotenv.2016.09.122. [DOI] [PubMed] [Google Scholar]
- [106].Hemeryck LY, Van Hecke T, Vossen E, De Smet S, Vanhaecke L, DNA adductomics to study the genotoxic effects of red meat consumption with and without added animal fat in rats, Food Chem. 230 (2017) 378–387, 10.1016/j.foodchem.2017.02.129. [DOI] [PubMed] [Google Scholar]
- [107].Guo J, Villalta PW, Turesky RJ, Data-independent mass spectrometry approach for screening and identification of DNA adducts, Anal. Chem 89 (2017) 11728–11736, 10.1021/acs.analchem.7b03208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [108].Guo J, Villalta PW, Weight CJ, Bonala R, Johnson F, Rosenquist TA, Turesky RJ, Targeted and untargeted detection of DNA adducts of aromatic amine carcinogens in human bladder by ultra-performance liquid chromatography-high-resolution mass spectrometry, Chem. Res. Toxicol 31 (2018) 1382–1397, 10.1021/acs.chemrestox.8b00268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [109].Hemeryck LY, Rombouts C, De Paepe E, Vanhaecke L, DNA adduct profiling of in vitro colonic meat digests to map red vs. White meat genotoxicity, Food Chem. Toxicol 115 (2018) 73–87, 10.1016/j.fct.2018.02.032. [DOI] [PubMed] [Google Scholar]
- [110].Carrà A, Guidolin V, Dator RP, Upadhyaya P, Kassie F, Villalta PW, Balbo S, Targeted high resolution LC/MS3 adductomics method for the characterization of endogenous DNA damage, Front. Chem 7 (2019) 658, 10.3389/fchem.2019.00658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [111].Wilson MR, Jiang Y, Villalta PW, Stornetta A, Boudreau PD, Carrá A, Brennan CA, Chun E, Ngo L, Samson LD, The human gut bacterial genotoxin colibactin alkylates DNA, Science 363 (2019) eaar7785, 10.1126/science.aar7785. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [112].Takeshita T, Tao F, Kojima N, Kanaly RA, Triple quadrupole mass spectrometry comparative DNA adductomics of Hep G2 cells following exposure to safrole, Toxicol. Lett 300 (2019) 92–104, 10.1016/j.toxlet.2018.10.023. [DOI] [PubMed] [Google Scholar]
- [113].Totsuka Y, Lin Y, He Y, Ishino K, Sato H, Kato M, Nagai M, Elzawahry A, Totoki Y, Nakamura H, DNA adductome analysis identifies N-nitrosopiperidine involved in the etiology of esophageal cancer in Cixian, China, Chem. Res. Toxicol 32 (2019) 1515–1527, 10.1021/acs.chemrestox.9b00017. [DOI] [PubMed] [Google Scholar]
- [114].Qiu TA, Guidolin V, Hoang KNL, Pho T, Villalta PW, He J, Yao X, Hamers RJ, Balbo S, Feng ZV, Nanoscale battery cathode materials induce DNA damage in bacteria, Chem. Sci 11 (2020) 11244–11258, 10.1039/d0sc02987d. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [115].Alexander EM, Kreitler DF, Guidolin V, Hurben AK, Drake E, Villalta PW, Balbo S, Gulick AM, Aldrich CC, Biosynthesis, mechanism of action, and inhibition of the enterotoxin tilimycin produced by the opportunistic pathogen Kebsiella oxytoca, ACS Infect. Dis 6 (2020) 1976–1997, 10.1021/acsinfecdis.0c00326. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [116].Totsuka Y, Maesako Y, Hanako O, Nagai M, Mamoru K, Min G, Wanibuchi H, Fukushima S, Shiizaki K, Nakagama H, Comprehensive analysis of DNA adducts (DNA adductome analysis) in the liver of rats treated with 1, 4-dioxane, Proc. Jpn. Acad., Ser. B 96 (2020) 180–187, 10.2183/pjab.96.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [117].Ohnishi I, Iwashita Y, Matsushita Y, Ohtsuka S, Yamashita T, Inaba K, Fukazawa A, Ochiai H, Matsumoto K, Kurono N, Matsushima Y, Mori H, Suzuki S, Suzuki S, Tanioka F, Sugimura H, Mass spectrometric profiling of DNA adducts in the human stomach associated with damage from environmental factors, Genes Environ. 43 (2021) 12, 10.1186/s41021-021-00186-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [118].Sousa PF, Martella G, Åberg KM, Esfahani B, Motwani HV, nLossFinder—a graphical user interface program for the nontargeted detection of DNA adducts, Toxics 9 (2021) 78, 10.3390/toxics9040078. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [119].Wang P, Roider E, Coulter ME, Walsh CA, Kramer CS, Beuning PJ, Giese RW, DNA adductomics by mass tag prelabeling, Rapid Commun. Mass Spectrom 35 (2021) e9095, 10.1002/rcm.9095. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [120].Murray KJ, Carlson ES, Stornetta A, Balskus EP, Villalta PW, Balbo S, Extension of diagnostic fragmentation filtering for automated discovery in DNA adductomics, Anal. Chem 93 (2021) 5754–5762, 10.1021/acs.analchem.0c04895. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [121].Walmsley SJ, Guo J, Murugan P, Weight CJ, Wang J, Villalta PW, Turesky RJ, Comprehensive analysis of DNA adducts using data-independent wSIM/MS2 acquisition and wSIM-City, Anal. Chem 93 (2021) 6491–6500, 10.1021/acs.analchem.1c00362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [122].Guilbaud A, Ghanegolmohammadi F, Wang Y, Leng J, Kreymerman A, Gamboa Varela J, Garbern J, Elwell H, Cao F, Ricci-Blair EM, Discovery adductomics provides a comprehensive portrait of tissue-, age-and sex-specific DNA modifications in rodents and humans, Nucleic Acids Res. 51 (2023) 10829–10845, 10.1093/nar/gkad822. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [123].Martella G, Gorokhova E, Sousa PF, Tretyakova NY, Sundelin B, Motwani HV, DNA adductomics for the biological effect assessment of contaminant exposure in marine sediments, Environ. Sci. Technol 57 (2023) 10591–10603, 10.1021/acs.est.3c00499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [124].De Graeve M, Van de Walle E, Van Hecke T, De Smet S, Vanhaecke L, Hemeryck LY, Exploration and optimization of extraction, analysis and data normalization strategies for mass spectrometry-based DNA adductome mapping and modeling, Anal. Chim. Acta 1274 (2023) 341578, 10.1016/j.aca.2023.341578. [DOI] [PubMed] [Google Scholar]
- [125].Ishii Y, Shi L, Takasu S, Ogawa K, Umemura T, A 13-week comprehensive toxicity study with adductome analysis demonstrates the toxicity, genotoxicity, and carcinogenicity of the natural flavoring agent elemicin, Food Chem. Toxicol 179 (2023) 113965, 10.1021/acs.chemrestox.3c00008. [DOI] [PubMed] [Google Scholar]
- [126].Ragi N, Walmsley SJ, Jacobs FC, Rosenquist TA, Sidorenko VS, Yao L, Maertens LA, Weight CJ, Balbo S, Villalta PW, Screening DNA damage in the rat kidney and liver by untargeted DNA adductomics, Chem. Res. Toxicol 37 (2024) 340–360, 10.1021/acs.chemrestox.3c00333. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [127].Li Y, Xu C, Zhou X, Li J, Xu S, Tu Y, Mu X, Huang J, Huang Q, Kang L, DNA adductomics aided rapid screening of genotoxic impurities using nucleosides and 3D bioprinted human liver organoids, Talanta 273 (2024) 125902, 10.1016/j.talanta.2024.125902. [DOI] [PubMed] [Google Scholar]
- [128].Suzuki S, Gi M, Komiya M, Obikane A, Vachiraarunwong A, Fujioka M, Kakehashi A, Totsuka Y, Wanibuchi H, Evaluation of the mechanisms involved in the development of bladder toxicity following exposure to occupational bladder cancer causative chemicals using DNA adductome analysis, Biomolecules 14 (2024) 36, 10.3390/biom14010036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [129].Bullinger D, Fux R, Nicholson G, Plontke S, Belka C, Laufer S, Gleiter CH, Kammerer B, Identification of urinary modified nucleosides and ribosylated metabolites in humans via combined ESI-FTICR MS and ESI-IT MS analysis, J. Am. Soc. Mass Spectrom 19 (2008) 1500–1513, 10.1016/j.jasms.2008.06.015. [DOI] [PubMed] [Google Scholar]
- [130].Compagnone D, Curini R, D’Ascenzo G, Del Carlo M, Montesano C, Napoletano S, Sergi M, Neutral loss and precursor ion scan tandem mass spectrometry for study of activated benzopyrene–DNA adducts, Anal. Bioanal. Chem 401 (2011) 1983–1991, 10.1007/s00216-011-5261-3. [DOI] [PubMed] [Google Scholar]
- [131].Li S, Jin Y, Tang Z, Lin S, Liu H, Jiang Y, Cai Z, A novel method of liquid chromatography–tandem mass spectrometry combined with chemical derivatization for the determination of ribonucleosides in urine, Anal. Chim. Acta 864 (2015) 30–38, 10.1016/j.aca.2015.01.044. [DOI] [PubMed] [Google Scholar]
- [132].Lu SS, Grigoryan H, Edmands WM, Hu W, Iavarone AT, Hubbard A, Rothman N, Vermeulen R, Lan Q, Rappaport SM, Profiling the serum albumin Cys34 adductome of solid fuel users in Xuanwei and Fuyuan, China, Environ. Sci. Technol 51 (2017) 46–57, 10.1021/acs.est.6b03955. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [133].Nakayama H, Yamauchi Y, Nobe Y, Sato K, Takahashi N, Shalev-Benami M, Isobe T, Taoka M, Method for direct mass-spectrometry-based identification of monomethylated RNA nucleoside positional isomers and its application to the analysis of Leishmania rRNA, Anal. Chem 91 (2019) 15634–15643, 10.1021/acs.analchem.9b03735. [DOI] [PubMed] [Google Scholar]
- [134].Herbert C, Ohrnberger CL, Quinlisk E, Addepalli B, Limbach PA, Characterizing benzo[a]pyrene adducts in transfer RNAs using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), Biomedicines 11 (2023) 3270, 10.3390/biomedicines11123270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [135].Preston GW, Phillips DH, Protein adductomics: Analytical developments and applications in human biomonitoring, Toxics 7 (2019) 29, 10.3390/toxics7020029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [136].Carlsson H, Rappaport SM, Tornqvist M, Protein adductomics: Methodologies for untargeted screening of adducts to serum albumin and hemoglobin in human blood samples, High-Throughput 8 (2019), 10.3390/ht8010006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [137].Bischoff R, Schlüter H, Amino acids: Chemistry, functionality and selected non-enzymatic post-translational modifications, J. Proteomics 75 (2012) 2275–2296, 10.1016/j.jprot.2012.01.041. [DOI] [PubMed] [Google Scholar]
- [138].Yano Y, Grigoryan H, Schiffman C, Edmonds W, Petrick L, Hall K, Whitehead T, Metayer C, Dudoit S, Rappaport S, Untargeted adductomics of Cys34 modifications to human serum albumin in newborn dried blood spots, Anal. Bioanal. Chem 411 (2019) 2351–2362, 10.1007/s00216-019-01675-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [139].Grigoryan H, Edmands WMB, Lu SS, Yano Y, Regazzoni L, Iavarone AT, Williams ER, Rappaport SM, Adductomics pipeline for untargeted analysis of modifications to Cys34 of human serum albumin, Anal. Chem 88 (2016) 10504–10512, 10.1021/acs.analchem.6b02553. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [140].Davies MJ, Protein oxidation and peroxidation, Biochem. J 473 (2016) 805–825, 10.1042/BJ20151227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [141].Carlsson H, von Stedingk H, Nilsson U, Törnqvist M, LC–MS/MS screening strategy for unknown adducts to N-terminal valine in hemoglobin applied to smokers and nonsmokers, Chem. Res. Toxicol 27 (2014) 2062–2070, 10.1021/tx5002749. [DOI] [PubMed] [Google Scholar]
- [142].Aldini G, Regazzoni L, Orioli M, Rimoldi I, Facino RM, Carini M, A tandem MS precursor-ion scan approach to identify variable covalent modification of albumin Cys34: A new tool for studying vascular carbonylation, J. Mass Spectrom 43 (2008) 1470–1481, 10.1002/jms.1419. [DOI] [PubMed] [Google Scholar]
- [143].Li H, Grigoryan H, Funk WE, Lu SS, Rose S, Williams ER, Rappaport SM, Profiling Cys34 adducts of human serum albumin by fixed-step selected reaction monitoring, Mol. Cell. Proteomics 10 (2011) M110.004606, 10.1074/mcp.M110.004606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [144].Preston GW, Plusquin M, Sozeri O, van Veldhoven K, Bastian L, Nawrot TS, Chadeau-Hyam M, Phillips DH, Refinement of a methodology for untargeted detection of serum albumin adducts in human populations, Chem. Res. Toxicol 30 (2017) 2120–2129, 10.1021/acs.chemrestox.7b00186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [145].Zeng Y, Zhang A, Yang X, Xing C, Zhai J, Wang Y, Cai B, Shi S, Zhang Y, Shen Z, Fu TM, Zhu L, Shen H, Ye J, Wang C, Internal exposure potential of water-soluble organic molecules in urban PM(2.5) evaluated by non-covalent adductome of human serum albumin, Environ. Int 184 (2024) 108492, 10.1016/j.envint.2024.108492. [DOI] [PubMed] [Google Scholar]
- [146].Rahman ML, Bassig BA, Grigoryan H, Hu W, Hosgood HD, Huang WY, Wong JYY, Strickland P, Rappaport SM, Lan Q, Rothman N, A nested case-control study of untargeted albumin adductomics and acute myeloid leukemia, Int. J. Cancer 153 (2023) 539–546, 10.1002/ijc.34550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [147].Porter CJ, Bereman MS, Data-independent-acquisition mass spectrometry for identification of targeted-peptide site-specific modifications, Anal. Bioanal. Chem 407 (2015) 6627–6635, 10.1007/s00216-015-8819-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [148].Grigoryan H, Imani P, Dudoit S, Rappaport SM, Extending the HSA-Cys34-adductomics pipeline to modifications at Lys525, Chem. Res. Toxicol 34 (2021) 2549–2557, 10.1021/acs.chemrestox.1c00311. [DOI] [PubMed] [Google Scholar]
- [149].Smith JW, O’Meally RN, Burke SM, Ng DK, Chen J-G, Kensler TW, Groopman JD, Cole RN, Global discovery and temporal changes of human albumin modifications by Pan-Protein adductomics: Initial application to air pollution exposure, J. Am. Soc. Mass Spectrom 34 (2023) 595–607, 10.1021/jasms.2c00314. [DOI] [PubMed] [Google Scholar]
- [150].Carlsson H, Törnqvist M, An adductomic approach to identify electrophiles, Basic Clin. Pharmacol. Toxicol 121 (2017) 44–54, 10.1111/bcpt.12715. [DOI] [PubMed] [Google Scholar]
- [151].Vryonidis E, Karlsson I, Aasa J, Carlsson H, Motwani HV, Pedersen M, Eriksson J, Törnqvist MÅ, Pathways to identify electrophiles in vivo using hemoglobin adducts: Hydroxypropanoic acid valine adduct and its possible precursors, Chem. Res. Toxicol 35 (2022) 2227–2240, 10.1021/acs.chemrestox.2c00208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [152].Rajczewski AT, Ndreu L, Pujari SS, Griffin TJ, Törnqvist MÅ, Karlsson I, Tretyakova NY, Novel 4-hydroxybenzyl adducts in human hemoglobin: Structures and mechanisms of formation, Chem. Res. Toxicol 34 (2021) 1769–1781, 10.1021/acs.chemrestox.1c00111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [153].Rajczewski AT, Ndreu L, Vryonidis E, Hurben AK, Jamshidi S, Griffin TJ, Törnqvist MÅ, Tretyakova NY, Karlsson I, Mass spectrometry-based strategies for assessing human exposure using hemoglobin adductomics, Chem. Res. Toxicol 36 (2023) 2019–2030, 10.1021/acs.chemrestox.3c00294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [154].Shibata T, Uchida K, Protein adductomics: A comprehensive analysis of protein modifications by electrophiles, Free Radical Biol. Med 144 (2019) 218–222, 10.1016/j.freeradbiomed.2019.02.034. [DOI] [PubMed] [Google Scholar]
- [155].Shibata T, Shimizu K, Hirano K, Nakashima F, Kikuchi R, Matsushita T, Uchida K, Adductome-based identification of biomarkers for lipid peroxidation, J. Biol. Chem 292 (2017) 8223–8235, 10.1074/jbc.M116.762609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [156].Yoshitake J, Shibata T, Shimayama C, Uchida K, 2-Alkenal modification of hemoglobin: Identification of a novel hemoglobin-specific alkanoic acid-histidine adduct, Redox Biol. 23 (2019) 101115, 10.1016/j.redox.2019.101115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [157].Nunes J, Charneira C, Morello J, Rodrigues J, Pereira SA, Antunes AMM, Mass spectrometry-based methodologies for targeted and untargeted identification of protein covalent adducts (adductomics): Current status and challenges, High-Throughput 8 (2019) 9, 10.3390/ht8020009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [158].Huang YS, Lin YM, Chen H, Wu CH, Syu CH, Huang TE, Do QT, Chen SH, Targeting endogenous adduction level of serum albumin by parallel reaction monitoring via standard additions and intact protein measurement: Biological dosimetry of catechol estrogens, Anal. Chem 91 (2019) 15922–15931, 10.1021/acs.analchem.9b04425. [DOI] [PubMed] [Google Scholar]
- [159].Jen HH, Kafeenah H, Chang TY, Lin YM, Shan YS, Wu CH, Chen SH, Quantification of the endogenous adduction level on hemoglobin and correlation with albumin adduction via proteomics: Multiple exposure markers of catechol estrogen, J. Proteome Res 20 (2021) 4248–4257, 10.1021/acs.jproteome.1c00097. [DOI] [PubMed] [Google Scholar]
- [160].Lauwaet T, Miyamoto Y, Ihara S, Le C, Kalisiak J, Korthals KA, Ghassemian M, Smith DK, Sharpless KB, Fokin VV, Click chemistry-facilitated comprehensive identification of proteins adducted by antimicrobial 5-nitroimidazoles for discovery of alternative drug targets against giardiasis, PLoS Neglected Trop. Dis 14 (2020) e0008224, 10.1371/journal.pntd.0008224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [161].Sauerland MB, Helm C, Lorentzen LG, Manandhar A, Ulven T, Gamon LF, Davies MJ, Identification of galectin-1 and other cellular targets of alpha, beta-unsaturated carbonyl compounds, including dimethylfumarate, by use of click-chemistry probes, Redox Biol. 59 (2023) 102560, 10.1016/j.redox.2022.102560. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [162].Labenski MT, Fisher AA, Lo H-H, Monks TJ, Lau SS, Protein electrophile-binding motifs: Lysine-rich proteins are preferential targets of quinones, Drug Metab. Dispos 37 (2009) 1211–1218, 10.1124/dmd.108.026211. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [163].Polacco BJ, Purvine SO, Zink EM, LaVoie SP, Lipton MS, Summers AO, Miller SM, Discovering mercury protein modifications in whole proteomes using natural isotope distributions observed in liquid chromatography-tandem mass spectrometry, Mol. Cell. Proteomics 10 (2011) M110.004853, 10.1002/rcm.5086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [164].Rappaport SM, Li H, Grigoryan H, Funk WE, Williams ER, Adductomics: Characterizing exposures to reactive electrophiles, Toxicol. Lett 213 (2012) 83–90, 10.1016/j.toxlet.2011.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [165].Chung MK, Grigoryan H, Iavarone AT, Rappaport SM, Antibody enrichment and mass spectrometry of albumin-Cys34 adducts, Chem. Res. Toxicol 27 (2014) 400–407, 10.1021/tx400337k. [DOI] [PubMed] [Google Scholar]
- [166].Carlsson H, Motwani HV, Osterman Golkar S, Törnqvist M, Characterization of a hemoglobin adduct from ethyl vinyl ketone detected in human blood samples, Chem. Res. Toxicol 28 (2015) 2120–2129, 10.1021/acs.chemrestox.5b00287. [DOI] [PubMed] [Google Scholar]
- [167].Carlsson H, Aasa J, Kotova N, Vare D, Sousa PF, Rydberg P, Abramsson-Zetterberg L, Törnqvist M, Adductomic screening of hemoglobin adducts and monitoring of micronuclei in school-age children, Chem. Res. Toxicol 30 (2017) 1157–1167, 10.1021/acs.chemrestox.6b00463. [DOI] [PubMed] [Google Scholar]
- [168].Grigoryan H, Edmands WMB, Lan Q, Carlsson H, Vermeulen R, Zhang L, Yin SN, Li GL, Smith MT, Rothman N, Adductomic signatures of benzene exposure provide insights into cancer induction, Carcinogenesis 39 (2018) 661–668, 10.1093/carcin/bgy042. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [169].Liu S, Grigoryan H, Edmands WM, Dagnino S, Sinharay R, Cullinan P, Collins P, Chung KF, Barratt B, Kelly FJ, Cys34 adductomes differ between patients with chronic lung or heart disease and healthy controls in central London, Environ. Sci. Technol 52 (2018) 2307–2313, 10.1021/acs.est.7b05554. [DOI] [PubMed] [Google Scholar]
- [170].Degner A, Carlsson H, Karlsson I, Eriksson J, Pujari SS, Tretyakova NY, Tornqvist M, Discovery of novel N-(4-hydroxybenzyl) valine hemoglobin adducts in human blood, Chem. Res. Toxicol 31 (2018) 1305–1314, 10.1021/acs.chemrestox.8b00173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [171].Grigoryan H, Schiffman C, Gunter MJ, Naccarati A, Polidoro S, Dagnino S, Dudoit S, Vineis P, Rappaport SM, Cys34 adductomics links colorectal cancer with the gut microbiota and redox biology, Cancer Res. 79 (2019) 6024–6031, 10.1158/0008-5472.CAN-19-1529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [172].Duffney PF, Kim H-YH, Porter NA, Jaspers I, Ozone-derived oxysterols impair lung macrophage phagocytosis via adduction of some phagocytosis receptors, J. Biol. Chem 295 (2020) 12727–12738, 10.1074/jbc.RA120.013699. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [173].Dagnino S, Bodinier B, Grigoryan H, Rappaport SM, Karimi M, Guida F, Polidoro S, Edmands WB, Naccarati A, Fiorito G, Agnostic Cys34-albumin adductomics and DNA methylation: Implication of N-acetylcysteine in lung carcinogenesis years before diagnosis, Int. J. Cancer 146 (2020) 3294–3303, 10.1002/ijc.32680. [DOI] [PubMed] [Google Scholar]
- [174].Ndreu L, Erber LN, Törnqvist M, Tretyakova NY, Karlsson I, Characterizing adduct formation of electrophilic skin allergens with human serum albumin and hemoglobin, Chem. Res. Toxicol 33 (2020) 2623–2636, 10.1021/acs.chemrestox.0c00271. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [175].Yano Y, Schiffman C, Grigoryan H, Hayes J, Edmands W, Petrick L, Whitehead T, Metayer C, Dudoit S, Rappaport S, Untargeted adductomics of newborn dried blood spots identifies modifications to human serum albumin associated with childhood leukemia, Leuk. Res 88 (2020) 106268, 10.1016/j.leukres.2019.106268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [176].Wong JY, Imani P, Grigoryan H, Bassig BA, Dai Y, Hu W, Blechter B, Rahman ML, Ji B-T, Duan H, Exposure to diesel engine exhaust and alterations to the Cys34/Lys525 adductome of human serum albumin, Environ. Toxicol. Pharmacol 95 (2022) 103966, 10.1016/j.etap.2022.103966. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [177].Grigoryan H, Imani P, Sacerdote C, Masala G, Grioni S, Tumino R, Chiodini P, Dudoit S, Vineis P, Rappaport SM, HSA adductomics reveals sex differences in NHL incidence and possible involvement of microbial translocation, Cancer Epidemiol., Biomarkers Prev 32 (2023) 1217–1226, 10.1158/1055-9965.EPI-23-0231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [178].Louati K, Maalej A, Kolsi F, Kallel R, Gdoura Y, Borni M, Hakim LS, Zribi R, Choura S, Sayadi S, Shotgun proteomic-based approach with a Q-Exactive hybrid quadrupole-orbitrap high-resolution mass spectrometer for protein adductomics on a 3D human brain tumor neurospheroid culture model: The identification of adduct formation in calmodulin-dependent protein kinase-2 and annexin-A1 induced by pesticide mixture, J. Proteome Res 22 (2023) 3811–3832, https://doi.org/1021/acs.jproteome.3c00484. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [179].Lin ET, Bae Y, Birkett R, Sharma AM, Zhang R, Fisch KM, Funk W, Mestan KK, Cord blood adductomics reveals oxidative stress exposure pathways of bronchopulmonary dysplasia, Antioxidants 13 (2024) 494. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [180].Guidolin Y, Jacobs FC, MacMillan ML, Villalta PW, Balbo S, Liquid chromatography–mass spectrometry screening of cyclophosphamide DNA damage in vitro and in patients undergoing chemotherapy treatment, Chem. Res. Toxicol 36 (2023) 1278–1289, 10.1021/acs.chemrestox.3c00008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [181].Gruppi F, Hejazi L, Christov PP, Krishnamachari S, Turesky RJ, Rizzo CJ, Characterization of nitrogen mustard formamidopyrimidine adduct formation of bis(2-chloroethyl)ethylamine with calf thymus DNA and a human mammary cancer cell line, Chem. Res. Toxicol 28 (2015) 1850–1860, 10.1021/acs.chemrestox.5b00297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [182].Boysen G, Arora R, Degner A, Vevang KR, Chao C, Rodriguez F, Walmsley SJ, Erber L, Tretyakova NY, Peterson LA, Effects of GSTT1 genotype on the detoxification of 1,3-butadiene derived diepoxide and formation of promutagenic DNA-DNA cross-links in human hapmap cell lines, Chem. Res. Toxicol 34 (2021) 119–131, 10.1021/acs.chemrestox.0c00376. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [183].Sangaraju D, Goggin M, Walker V, Swenberg J, Tretyakova N, NanoHPLC-nanoESI+-MS/MS quantitation of bis-N7-guanine DNA–DNA cross-links in tissues of B6C3F1 mice exposed to subppm levels of 1,3-butadiene, Anal. Chem 84 (2012) 1732–1739, 10.1021/ac203079c. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [184].Noll DM, Mason TM, Miller PS, Formation and repair of interstrand cross-links in DNA, Chem. Rev 106 (2006) 277–301, 10.1021/cr040478b. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [185].Housh K, Jha JS, Haldar T, Amin SBM, Islam T, Wallace A, Gomina A, Guo X, Nel C, Wyatt JW, Gates KS, Formation and repair of unavoidable, endogenous interstrand cross-links in cellular DNA, DNA Repair 98 (2021) 103029, 10.1016/j.dnarep.2020.103029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [186].Lopez-Martinez D, Liang CC, Cohn MA, Cellular response to DNA interstrand crosslinks: the Fanconi anemia pathway, Cell. Mol. Life Sci 73 (2016) 3097–3114, 10.1007/s00018-016-2218-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [187].Rycenga HB, Long DT, The evolving role of DNA inter-strand crosslinks in chemotherapy, Curr. Opin. Pharmacol 41 (2018) 20–26, 10.1016/j.coph.2018.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [188].Groehler A, Degner A, Tretyakova NY, Mass spectrometry-based tools to characterize DNA-protein cross-linking by bis-electrophiles, Basic Clin. Pharmacol. Toxicol 121 (2017) 63–77, 10.1111/bcpt.12751. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [189].Nakano T, Xu X, Salem AMH, Shoulkamy MI, Ide H, Radiation-induced DNA-protein cross-links: Mechanisms and biological significance, Free Radical Biol. Med 107 (2017) 136–145, 10.1016/j.freeradbiomed.2016.11.041. [DOI] [PubMed] [Google Scholar]
- [190].Tretyakova NY, Groehler A, Ji SF, DNA-protein cross-links: Formation, structural identities, and biological outcomes, Acc. Chem. Res 48 (2015) 1631–1644, 10.1021/acs.accounts.5b00056. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [191].Nakamura J, Nakamura M, DNA-protein crosslink formation by endogenous aldehydes and AP sites, DNA Repair 88 (2020) 102806, 10.1016/j.dnarep.2020.102806. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [192].Ming X, Groehler A, Michaelson-Richie ED, Villalta PW, Campbell C, Tretyakova NY, Mass spectrometry based proteomics study of cisplatin-induced DNA-protein cross-linking in human fibrosarcoma (HT1080) cells, Chem. Res. Toxicol 30 (2017) 980–995, 10.1021/acs.chemrestox.6b00389. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [193].Tayri-Wilk T, Slavin M, Zamel J, Blass A, Cohen S, Motzik A, Sun X, Shalev DE, Ram O, Kalisman N, Mass spectrometry reveals the chemistry of formaldehyde cross-linking in structured proteins, Nat. Commun 11 (2020) 3128, 10.1038/s41467-020-16935-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [194].Jiang SW, Hägglund P, Carroll L, Rasmussen LM, Davies MJ, Crosslinking of human plasma C-reactive protein to human serum albumin via disulfide bond oxidation, Redox Biol. 41 (2021) 101925, 10.1016/j.redox.2021.101925. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [195].Klykov O, Steigenberger B, Pektas S, Fasci D, Heck AJR, Scheltema RA, Efficient and robust proteome-wide approaches for cross-linking mass spectrometry, Nat. Protoc 13 (2018) 2964–2990, 10.1038/s41596-018-0074-x. [DOI] [PubMed] [Google Scholar]
- [196].Velema WA, Lu ZP, Chemical RNA cross-linking: Mechanisms, computational analysis, and biological applications, Jacs Au 3 (2023) 316–332, 10.1021/jacsau.2c00625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [197].Wurtmann EJ, Wolin SL, RNA under attack: Cellular handling of RNA damage, Crit. Rev. Biochem. Mol. Biol 44 (2009) 34–49, 10.1080/10409230802594043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [198].Zhou Y, Panhale A, Shvedunova M, Balan M, Gomez-Auli A, Holz H, Seyfferth J, Helmstadter M, Kayser S, Zhao Y, Erdogdu NU, Grzadzielewska I, Mittler G, Manke T, Akhtar A, RNA damage compartmentalization by DHX9 stress granules, Cell 187 (2024) 1701–1718, 10.1016/j.cell.2024.02.028. [DOI] [PubMed] [Google Scholar]
- [199].Steinmetz B, Smok I, Bikaki M, Leitner A, Protein-RNA interactions: From mass spectrometry to drug discovery, Essays Biochem. 67 (2023) 175–186, 10.1042/Ebc20220177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [200].Van Ende R, Balzarini S, Geuten K, Single and combined methods to specifically or bulk-purify RNA-protein complexes, Biomolecules 10 (2020) 1160, 10.3390/biom10081160. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [201].Dator RP, Murray KJ, Luedtke MW, Jacobs FC, Kassie F, Nguyen HD, Villalta PW, Balbo S, Identification of formaldehyde-induced DNA–RNA cross-links in the A/J mouse lung tumorigenesis model, Chem. Res. Toxicol 35 (2022) 2025–2036, 10.1021/acs.chemrestox.2c00206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [202].Williams RT, Nalbandian JN, Tu A, Wang Y, Nuclease digestion and mass spectrometric characterization of oligodeoxyribonucleotides containing 1, 2-gpg, 1, 2-GpG, 1, 2-ApG, and 1, 3-GpXpG cisplatin intrastrand cross-links, Clin. Chim. Acta 420 (2013) 160–170, 10.1016/j.cca.2012.12.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [203].Kiianitsa K, Maizels N, The “adductome”: A limited repertoire of adducted proteins in human cells, DNA Repair 89 (2020) 102825, 10.1016/j.dnarep.2020.102825. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [204].Kozekov ID, Turesky RJ, Alas GR, Harris CM, Harris TM, Rizzo CJ, Formation of deoxyguanosine cross-links from calf thymus DNA treated with acrolein and 4-hydroxy-2-nonenal, Chem. Res. Toxicol 23 (2010) 1701–1713, 10.1021/tx100179g. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [205].Stornetta A, Villalta RW, Gossner F, Wilson WR, Balbo S, Sturla SJ, DNA adduct profiles predict in vitro cell viability after treatment with the experimental anticancer prodrug PR104A, Chem. Res. Toxicol 30 (2017) 830–839, 10.1021/acs.chemrestox.6b00412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [206].Walters K, Stornetta A, Jacobs F, Villalta PW, Razzoli M, Grant M, Zordoky B, Bartolomucci A, Borgatti A, Balbo S, Identification of new candidate biomarkers to support doxorubicin treatments in canine cancer patients, BMC Vet. Res 17 (2021) 378, 10.1186/s12917-021-03062-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [207].Guidolin V, Carlson E, Carrà A, Villalta P, Maertens L, Hecht S, Balbo S, Identification of new markers of alcohol-derived DNA damage in humans, Biomolecules 11 (2021) 366, 10.3390/biom11030366. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [208].Solivio MJ, Stornetta A, Gilissen J, Villalta PW, Deschoemaeker S, Heyerick A, Dubois L, Balbo S, In vivo identification of adducts from the new hypoxia-activated prodrug CP-506 using DNA adductomics, Chem. Res. Toxicol 35 (2022) 275–282, 10.1021/acs.chemrestox.1c00329. [DOI] [PubMed] [Google Scholar]
- [209].Lenz C, Kühn-Hölsken E, Urlaub H, Detection of protein-RNA crosslinks by NanoLC-ESI-MS/MS using precursor ion scanning and multiple reaction monitoring (MRM) experiments, J. Am. Soc. Mass Spectrom 18 (2007) 869–881, 10.1016/j.jasms.2007.01.013. [DOI] [PubMed] [Google Scholar]
- [210].Alcazar Magana A, Wrobel K, Corrales Escobosa AR, Wrobel K, Application of liquid chromatography/electrospray ionization ion trap tandem mass spectrometry for the evaluation of global nucleic acids: Methylation in garden cress under exposure to CuO nanoparticles, Rapid Commun. Mass Spectrom 30 (2016) 209–220, 10.1002/rcm.7440. [DOI] [PubMed] [Google Scholar]
- [211].Abdelhady R, Senthong P, Eyers CE, Reamtong O, Cowley E, Cannizzaro L, Stimpson J, Cain K, Wilkinson OJ, Williams NH, Mass spectrometric analysis of the active site tryptic peptide of recombinant O6-methylguanine-DNA methyltransferase following incubation with human colorectal DNA reveals the presence of an O6-alkylguanine adductome, Chem. Res. Toxicol 36 (2023) 1921–1929, 10.1021/acs.chemrestox.3c00207. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [212].Wang J, Yuan B, Guerrero C, Bahde R, Gupta S, Wang Y, Quantification of oxidative DNA lesions in tissues of Long-Evans Cinnamon rats by capillary high-performance liquid chromatography– tandem mass spectrometry coupled with stable isotope-dilution method, Anal. Chem 83 (2011) 2201–2209, 10.1021/ac103099s. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [213].Jora M, Burns AP, Ross RL, Lobue PA, Zhao R, Palumbo CM, Beal PA, Addepalli B, Limbach PA, Differentiating positional isomers of nucleoside modifications by higher-energy collisional dissociation mass spectrometry (HCD MS), J. Am. Soc. Mass Spectrom 29 (2018) 1745–1756, 10.1007/s13361-018-1999-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [214].Cooper B, Yang R, An assessment of AcquireX and Compound Discoverer software 3.3 for non-targeted metabolomics, Sci. Rep 14 (2024) 4841, 10.1038/s41598-024-55356-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [215].Guo J, Turesky RJ, Emerging technologies in mass spectrometry-based DNA adductomics, High-Throughput 8 (2019) 13, 10.3390/ht8020013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [216].Walmsley SJ, Guo J, Wang J, Villalta PW, Turesky RJ, Methods and challenges for computational data analysis for DNA adductomics, Chem. Res. Toxicol 32 (2019) 2156–2168, 10.1021/acs.chemrestox.9b00196. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [217].Cui Y, Wang Y, Mass spectrometry-based DNA adductomics, TrAC, Trends Anal. Chem 157 (2022) 116773, 10.3390/ht8020013. [DOI] [Google Scholar]
- [218].La Barbera G, Nommesen KD, Cuparencu C, Stanstrup J, Dragsted LO, A comprehensive database for DNA adductomics, Front. Chem 10 (2022) 908572, 10.3389/fchem.2022.908572. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [219].Guo J, Turesky RJ, Tarifa A, DeCaprio AP, Cooke MS, Walmsley SJ, Villalta PW, Development of a DNA adductome mass spectral database, Chem. Res. Toxicol 33 (2020) 852–854, 10.1021/acs.chemrestox.0c00031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [220].Rattray NJ, Deziel NC, Wallach JD, Khan SA, Vasiliou V, Ioannidis JP, Johnson CH, Beyond genomics: Understanding exposotypes through metabolomics, Hum. Genomics 12 (2018) 4, 10.1186/s40246-018-0134-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [221].Cui YX, Wang PC, Yu Y, Yuan J, Wang YS, Normalized retention time for targeted analysis of the DNA adductome, Anal. Chem 90 (2018) 14111–14115, 10.1021/acs.analchem.8b04660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [222].Gonzalez G, Cui YX, Wang PC, Wang YS, Normalized retention time for scheduled liquid chromatography-multistage mass spectrometry analysis of epitranscriptomic modifications, J. Chromatogr. A 1623 (2020) 461181, 10.1016/j.chroma.2020.461181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [223].Peña-Llopis S, Brugarolas J, Simultaneous isolation of high-quality DNA, RNA, miRNA and proteins from tissues for genomic applications, Nat. Protoc 8 (2013) 2240–2255, 10.1038/nprot.2013.141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [224].Zhang JX, Lau E, Paik DT, Zhuge Y, Wu JC, High-throughput preparation of DNA, RNA, and protein from cryopreserved human iPSCs for multi-omics analysis, Curr. Protoc. Stem Cell Biol 54 (2020) e114, 10.1002/cpsc.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [225].Tretyakova N, Villalta PW, Kotapati S, Mass spectrometry of structurally modified DNA, Chem. Rev 113 (2013) 2395–2436, 10.1021/cr300391r. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [226].Halliwell B, Why and how should we measure oxidative DNA damage in nutritional studies? How far have we come?, Am. J. Clin. Nutr 72 (2000) 1082–1087, 10.1093/ajcn/72.5.1082. [DOI] [PubMed] [Google Scholar]
- [227].Lu K, Hsiao YC, Liu CW, Schoeny R, Gentry R, Starr TB, A review of stable isotope labeling and mass spectrometry methods to distinguish exogenous from endogenous DNA adducts and improve dose-response assessments, Chem. Res. Toxicol 35 (2022) 7–29, 10.1021/acs.chemrestox.1c00212. [DOI] [PubMed] [Google Scholar]
- [228].Babu M, Snyder M, Multi-omics profiling for health, Mol. Cell. Proteomics 22 (2023) 100561, 10.1016/j.mcpro.2023.100561. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data will be made available on request.