Identification of low-level impurities in drug prototypes of carbocisteine by means of liquid chromatography-high-resolution mass spectrometry and general unknown comparative screening

High-resolution tandem quadrupole time-of-flight mass analysers enable new automated workflows for untargeted data evaluation of complex samples like drug products. An example of such procedure is the so-called general unknown comparative screening (GUCS), which is used for software-assisted, automated identification of components that are only present in a sample and not in a reference. The GUCS approach has been employed for the first time to detect both degradation products and reaction products in drug products. Two different carbocisteine containing syrup prototypes - one with sucrose and the other with artificial sweeteners - were selected as examples after nine months of storage at 40 °C and 75% relative humidity. The samples were analysed chromatographically using a Coresep SB mixed-mode column and high-resolution MS and MS/MS data were recorded in information dependant acquisition mode on a Sciex X500R quadrupole time-of-flight mass spectrometer. Data analysis was considerably facilitated using the corresponding placebo formulation as reference samples. With the GUCS approach two hitherto unknown degradation products of carbocisteine, i.e. the carbocisteine lactam of the sulfoxides and the disulfide between l-cysteine and thioglycolic acid, were detected at low concentrations in both of the syrup formulations. The presumed structures were confirmed by in silico analysis of the fragment spectra and high-resolution LC-MS experiments with reference substances. Two additional impurities were found in the sucrose-containing sample and identified as the N-glycosides of carbocisteine and its lactam, respectively, using binary mixtures with a 13C-labelled monosaccharide.

Metabolomics and Lipidomics Screening Reveal Reprogrammed Signaling Pathways toward Cancer Development in Non-Alcoholic Steatohepatitis

With the rising incidence of hepatocellular carcinoma (HCC) from non-alcoholic steatohepatitis (NASH), identifying new metabolic readouts that function in metabolic pathway perpetuation is still a demand. The study aimed to compare the metabolic signature between NASH and NASH-HCC patients to explore novel reprogrammed metabolic pathways that might modulate cancer progression in NASH patients. NASH and NASH-HCC patients were recruited and screened for metabolomics, and isotope-labeled lipidomics were targeted and profiled using the EXION-LCTM system equipped with a Triple-TOFTM 5600+ system. Results demonstrated significantly (p ≤ 0.05) higher levels of triacylglycerol, AFP, AST, and cancer antigen 19-9 in NASH-HCC than in NASH patients, while prothrombin time, platelet count, and total leukocyte count were decreased significantly (p ≤ 0.05). Serum metabolic profiling showed a panel of twenty metabolites with 10% FDR and p ≤ 0.05 in both targeted and non-targeted analysis that could segregate NASH-HCC from NASH patients. Pathway analysis revealed that the metabolites are implicated in the down-regulation of necroptosis, amino acid metabolism, and regulation of lipid metabolism by PPAR-α, biogenic amine synthesis, fatty acid metabolism, and the mTOR signaling pathway. Cholesterol metabolism, DNA repair, methylation pathway, bile acid, and salts metabolism were significantly upregulated in NASH-HCC compared to the NASH group. Metabolite-protein interactions network analysis clarified a set of well-known protein encoding genes that play crucial roles in cancer, including PEMT, IL4I1, BAAT, TAT, CDKAL1, NNMT, PNP, NOS1, and AHCYL. Taken together, reliable metabolite fingerprints are presented and illustrated in a detailed map for the most predominant reprogrammed metabolic pathways that target HCC development from NASH.

A Novel Approach of SWATH-Based Metabolomics Analysis Using the Human Metabolome Database Spectral Library

Metabolomics is a potential approach to paving new avenues for clinical diagnosis, molecular medicine, and therapeutic drug monitoring and development. The conventional metabolomics analysis pipeline depends on the data-independent acquisition (DIA) technique. Although powerful, it still suffers from stochastic, non-reproducible ion selection across samples. Despite the presence of different metabolomics workbenches, metabolite identification remains a tedious and time-consuming task. Consequently, sequential windowed acquisition of all theoretical MS (SWATH) acquisition has attracted much attention to overcome this limitation. This article aims to develop a novel SWATH platform for data analysis with a generation of an accurate mass spectral library for metabolite identification using SWATH acquisition. The workflow was validated using inclusion/exclusion compound lists. The false-positive identification was 3.4% from the non-endogenous drugs with 96.6% specificity. The workflow has proven to overcome background noise despite the complexity of the SWATH sample. From the Human Metabolome Database (HMDB), 1282 compounds were tested in various biological samples to demonstrate the feasibility of the workflow. The current study identified 377 compounds in positive and 303 in negative modes with 392 unique non-redundant metabolites. Finally, a free software tool, SASA, was developed to analyze SWATH-acquired samples using the proposed pipeline.

The Origin and Implications of Artifact Ions in Bioanalytical LC–MS

Liquid chromatography–mass spectrometry (LC–MS) with electrospray ionization (ESI) is a widely used bioanalytical technique with both qualitative and quantitative applications. Ions are created by electrically charging a stream of droplets from the LC system, which evaporate and leave ions that are transferred to the mass spectrometer. Ideally, these are only from the analyte, but background ions, such as metals, impurities and coeluted species, can react with analytes producing adducts, such as [M + Na]+, [M + K]+, and multimers (2M + H+, 3M + H+, and so forth). Although well known, the extent of adduct ion formation and the implications for quantitative analysis and analyte characterization by tandem MS (MS/MS) are not fully appreciated. We summarize the problem and identify areas that should be considered when developing or using electrospray LC–MS.

MetaboKit: a comprehensive data extraction tool for untargeted metabolomics

We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent identification algorithm requiring matches by both MS and MS/MS data, MetaboKit provides identification results with significantly greater specificity than the competing software packages without loss in sensitivity. The proposed MS/MS-based screening of ISFs also reduces the chance of unverifiable identification of ISFs considerably. MetaboKit's quantification module produced peak area values highly correlated with known concentrations in a DIA analysis of the metabolite standards at both MS1 and MS2 levels. Moreover, the analysis of Cdk1Liv-/- mouse livers showed that MetaboKit can identify a wide range of lipid species and their ISFs, and quantitatively reconstitute the well-characterized fatty liver phenotype in these mice. In DIA data, the MS1-level and MS2-level peak area data produced similar fold change estimates in the differential abundance analysis, and the MS2-level peak area data allowed for quantitative comparisons in compounds whose precursor ion chromatogram was too noisy for peak integration.

An integrated analytical approach based on enhanced fragment ions interrogation and modified Kendrick mass defect filter data mining for in-depth chemical profiling of glucosinolates by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry

High resolution mass spectrometry (HRMS)-based analytical technique promotes the discovery and development of new bioactive molecules from natural sources. However, challenges for MS analysis of natural products include their structural diversity, numerous trace components, as well as the interference from complex matrices that limits the rapid detection and identification of all target analytes in the extracts. Herein, we presented an integrated analytical approach to obtain chemical profile of glucosinolates (GLSs) in Eutrema yunnanense, a perennial herb, which is used as a condiment (Wasabi), by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry (UHPLC-Orbitrap/HRMS). The intelligent AcquireX deep scan greatly improved the detection efficiency and coverage of data-dependent acquisition (DDA) mode, and enhanced structurally significant product ions interrogation by generating exhaustive MS/MS spectra with more informative fragmentation. Massive HRMS data mining for searching GLSs was then achieved by a modified Kendrick mass defect filter (MKMDF), which enabled the visualization of their homologous characteristics and reduced the complicacy of data post-processing. Ultimately, a total of 175 GLSs were tentatively identified or characterized based on the MS fragmentation patterns, including 52 potentially new compounds among which 37 malonylated GLSs were first discovered. These compounds were then applied to analyse the chemical differentiation between the rhizome and leaf of E. yunnanense. This study provides a feasible approach for screening and confident structure characterization of GLSs and has practical implications for profiling other natural bioactive homologous compounds.

Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MS^ALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MS^ALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91-113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis

INTRODUCTION

While liquid chromatography coupled to mass spectrometric detection in the selected reaction monitoring detection mode offers the best quantification sensitivity for omics, the number of target analytes is limited, must be predefined and specific methods developed. Data independent acquisition (DIA), including SWATH using quadrupole time of flight or orbitrap mass spectrometers and generic acquisition methods, has emerged as a powerful alternative technique for quantitative and qualitative analyses since it can cover a wide range of analytes without predefinition.

OBJECTIVES

Here we review the current state of DIA, SWATH-MS and highlight novel acquisition strategies for metabolomics and lipidomics and opportunities for data analysis tools.

METHOD

Different databases were searched for papers that report developments and applications of DIA and in particular SWATH-MS in metabolomics and lipidomics.

RESULTS

DIA methods generate digital sample records that can be mined retrospectively as further knowledge is gained and, with standardized acquisition schemes, used in multiple studies. The different chemical spaces of metabolites and lipids require different specificities, hence different acquisition and data processing approaches must be considered for their analysis.

CONCLUSIONS

Although the hardware and acquisition modes are well defined for SWATH-MS, a major challenge for routine use remains the lack of appropriate software tools capable of handling large datasets and large numbers of analytes.

DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS-Based Untargeted Metabolomics

SWATH-MS-based data-independent acquisition mass spectrometry (DIA-MS) technology has been recently developed for untargeted metabolomics due to its capability to acquire all MS2 spectra with high quantitative accuracy. However, software tools for deconvolving multiplexed MS/MS spectra from SWATH-MS with high efficiency and high quality are still lacking in untargeted metabolomics. Here, we developed a new software tool, namely, DecoMetDIA, to deconvolve multiplexed MS/MS spectra for metabolite identification and support the SWATH-based untargeted metabolomics. In DecoMetDIA, multiple model peaks are selected to model the coeluted and unresolved chromatographic peaks of fragment ions in multiplexed spectra and decompose them into a linear combination of the model peaks. DecoMetDIA enabled us to reconstruct the MS2 spectra of metabolites from a variety of different biological samples with high coverages. We also demonstrated that the deconvolved MS2 spectra from DecoMetDIA were of high accuracy through comparison to the experimental MS2 spectra from data-dependent acquisition (DDA). Finally, about 90% of deconvolved MS2 spectra in various biological samples were successfully annotated using software tools such as MetDNA and Sirius. The results demonstrated that the deconvolved MS2 spectra obtained from DecoMetDIA were accurate and valid for metabolite identification and structural elucidation. The comparison of DecoMetDIA to other deconvolution software such as MS-DIAL demonstrated that it performs very well for small polar metabolites. DecoMetDIA software is freely available at https://github.com/ZhuMSLab/DecoMetDIA .

Hybrid SWATH/MS and HR-SRM/MS acquisition for phospholipidomics using QUAL/QUANT data processing

A hybrid SWATH/MS and HR-SRM/MS acquisition approach using multiple unit mass windows and 100 u precursor selection windows has been developed to interface with a chromatographic lipid class separation. The method allows for the simultaneous monitoring of sum compositions in MS1 and up to 48 lipids in MS2 per lipid class. A total of 240 lipid sum compositions from five phospholipid classes could be monitored in MS2 (HR-SRM/MS) while there was no limitation in the number of analytes in MS1 (HR-SIM/MS). On average, 92 lipid sum compositions and 75 lipid species could be quantified in human plasma samples. The robustness and precision of the workflow has been assessed using technical triplicates of the subject samples. Lipid identification was improved using a combined qualitative and quantitative data processing based on prediction instead of library search. Lipid class specific extracted ion currents of precursors and the corresponding molecular species fragments were extracted based on the information obtained from lipid building blocks and a combinatorial strategy. The SWATH/MS approach with the post-acquisition processing is not limited to the analyzed phospholipid classes and can be applied to other analytes and samples of interest. Graphical abstract.

High-resolution MS/MS metabolomics by data-independent acquisition reveals urinary metabolic alteration in experimental colitis

INTRODUCTION

Traditional high-resolution MS1 based untargeted metabolomics suffers from low sensitivity, while low-resolution MS/MS based multiple reaction monitoring increases sensitivity at the cost of metabolite coverage and the mass accuracy.

OBJECTIVES

To evaluate and apply the high-resolution MS/MS level untargeted metabolomics.

METHODS

SWATH based data-independent acquisition (DIA) was optimized to obtain MS/MS of all precursor ions.

RESULTS

SWATH-MS/MS could rescue MS1 obscured or saturated metabolites and potentially provide diagnostic fragments to differentiate isomers. For SWATH-MS/MS, 4944 out of 21492 (23.0%) and 2289 out of 12831 (17.8%) fragment ion features significantly changed (Fold change > 1.5, P < 0.05) between Normal and experimental acute ulcerative colitis (UC) groups in positive and negative ion mode, respectively. For SWATH-MS1, 1022 out of 4818 (21.2%) and 353 out of 2266 (15.6%) features significantly changed in positive and negative ion mode, respectively. By deciphering the metabolite profiles with high-resolution MS/MS, it allows versatile post-acquisition data mining such as open detection of different sub-metabolome. The method revealed a global urinary metabolic alteration and increased glucuronide and sulfate sub-metabolome in UC. The major limitation of untargeted SWATH-MS/MS is increased interferences derived from wider Q1 isolation window.

CONCLUSIONS

SWATH-MS/MS is a versatile metabolomics strategy, merging the coverage of high-resolution untargeted metabolomics and the sensitivity of MS/MS.

A combined targeted/untargeted LC-MS/MS-based screening approach for mammalian cell lines treated with ionic liquids: Toxicity correlates with metabolic profile

This work presents the development and validation of a quantitative HILIC UHPLC-ESI-QTOF-MS/MS method for amino acids combined with untargeted metabolic profiling of human corneal epithelial (HCE) cells after treatment with ionic liquids. The work included a preliminary metabotoxicity screening of 14 different ionic liquids, of which 9 carefully selected ionic liquids were chosen for a metabolomics study. This study is focused on the correlation between the toxicity of the ionic liquids and their metabolic profiles. The method development included the comparison of different MS/MS acquisition modes. A sequential window acquisition of all theoretical fragment ion mass spectra (SWATH) method with variable Q1 window widths and narrow Q1 target windows of 5 Da for most of the amino acids was selected as the optimal acquisition mode. Due to the absence of a true blank matrix, ¹³C,¹⁵N-isotopically labelled amino acids were utilized as surrogate calibrants, instead of proteinogenic amino acids. Partial least squares (PLS) analysis of the median effective concentrations (EC₅₀) of 9 selected ionic liquids showed a correlation with their metabolic profile measured by the untargeted screening.

Exploiting High-Resolution Mass Spectrometry for Targeted Metabolite Quantification and 13C-Labeling Metabolism Analysis

Quantification of targeted metabolites, especially trace metabolites and structural isomers, in complex biological materials is an ongoing challenge for metabolomics. In this chapter, we summarize high-resolution mass spectrometry-based approaches mainly used for targeted metabolite and metabolomics analysis, and then introduce an MS1/MS2-combined PRM workflow for quantification of central carbon metabolism intermediates, amino acids, and shikimate pathway-related metabolites. Major steps in the workflow, including cell culture, metabolite extraction, LC-MS analysis and data processing, are described. Furthermore, we adapt this new approach to a dynamic ¹³C-labeling experiment and demonstrate its unique advantage in capturing and correcting isotopomer labeling curves to facilitate nonstationary ¹³C-labeling metabolism analysis.

Quantitative analysis of chemoresistance-inducing fatty acid in food supplements using UHPLC-ESI-MS/MS

Polyunsaturated fatty acids are important signaling molecules. A recent study reported hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid, 12-oxo-5Z,8E,10E-heptadecatrienoic acid, and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid as chemotherapy resistance-inducing factors when tumor cells were treated with cisplatin. Marine-based food supplements like fish oil or algae extracts are rich in polyunsaturated fatty acids and can contain large amounts of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid. Thus, it was concluded that oral uptake of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid might induce chemoresistance as shown in a mouse model. Cancer patients tend to consume food supplements containing polyunsaturated fatty acids on a regular basis. The uptake of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid should be controlled, because even low concentrations of 0.5 ng mL^-1 showed chemoresistance-inducing effects in animal experiments. For accurate analysis of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid a validated method was developed by using ultrahigh-performance liquid chromatography hyphenated to quadrupole time of flight mass spectrometry via electrospray ionization and sample preparation by solid-phase extraction (SPE) with 3-aminopropyl silica. A combined targeted/untargeted approach was utilized using MS/MS by data-independent acquisition with SWATH and applied to commercial food supplements (refined fish oil, fish oil capsules, algae oil capsules, and flaxseed capsules). Accurate quantification of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid on the MS/MS level with simultaneous untargeted fatty acid screening revealed additional information. The LODs for hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid were 0.036 ng mL^-1 and 0.054 ng mL^-1, respectively. Since hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid was present in the samples in large amounts and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic was not expected to be present in high concentrations, two calibration ranges, namely, 0.5-20 ng mL^-1 and 5-200 ng mL^-1, were validated. An untargeted screening identified 18-39 free fatty acids being present in the lipid extracts of the food supplement samples. Graphical abstract ᅟ.

Ion-Pair Selection Method for Pseudotargeted Metabolomics Based on SWATH MS Acquisition and Its Application in Differential Metabolite Discovery of Type 2 Diabetes

The pseudotargeted metabolomics method integrates advantages of nontargeted and targeted analysis because it can acquire data of metabolites in the multireaction monitoring (MRM) mode of mass spectrometry (MS) without needing standards. The key is the ion-pair information collection from samples to be analyzed. It is well-known that sequential windowed acquisition of all theoretical Fragment ion (SWATH) MS mode can acquire MS2 information to a maximum extent. To expediently acquire as many ion-pairs as possible with optimal collision energy (CE), an ion-pair selection approach based on SWATH MS acquisition with variable isolation windows was developed in this study. Initially, nontargeted acquisition of all metabolites information in plasma Standard Reference Material (SRM 1950) was performed by ultra high-performance liquid chromatography (UHPLC)-quadrupole time-of-flight (Q-TOF) MS platform with three CEs. With the help of software tool, the ion-pairs of unique metabolites were gained. Then they were validated in scheduled MRM coupled with UHPLC. After removing false positive, the ion-pairs with an optimal CE was integrated. A total of 1373 unique metabolite ion-pairs were obtained at positive ion mode. And repeatability of the established pseudotargeted approach was evaluated by intraday and interday precision. The results demonstrated the method was stable, reliable, and suitable for metabolomics study. As an application example, alterations of serum metabolites in Type 2 diabetes were investigated by using the established method. This work provides a pseudotargeted ion-pair selection method based on SWATH MS acquisition with the characters of increased metabolite coverage, suitable CE, and convenient processing.

SWATHHM-Based Metabolomics of Follicular Fluid in Patients Shows That Progesterone Adversely Affects Oocyte Quality

Objective

We reveal the relationship between progesterone level in follicular fluid and oocyte quality based on sequential window acquisition of all theoretical fragment-ion spectra (SWATH™), a powerful high-resolution mass spectrometric data independent acquisition technique.

Method

Follicular fluid samples were collected from 22 subjects (the level of progesterone > 1.5 ng/mL) of progesterone group, as well as from 22 subjects (the level of progesterone < 1.5 ng/mL) of control group, and analyzed using UPLC-Q-TOF. All methods were performed in accordance with ISO 9001:2008. Novel SWATH acquisition mode on an ultra-high performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (with resolving power 20,000–40,000) was investigated for the analysis of human follicular fluid. The principal component variable grouping detects intersample variable correlation and groups variables with similar profiles which simplifies interpretation and highlights related ions and fragments. It can also extract product ion spectra from the data collected by fragmenting a wide precursor ion window.

Results

Follicular fluid from the two groups differed with respect to five metabolites. Follicular fluid from the progesterone group contained elevated levels of 8-hydroxyguanosine and 4-hydroxynonenal and reduced levels of ATP, estradiol, and L-carnitine. The increased progesterone level on the day of HCG injection could negatively impact oocyte quality, thus reducing the pregnancy rate of IVF patients.

Metabolomic spectral libraries for data-independent SWATH liquid chromatography mass spectrometry acquisition

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100 eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70 eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70 eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H]⁺ and 483 in negative mode [M-H]^-. MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

Data-Independent Mass Spectrometry Approach for Screening and Identification of DNA Adducts

Long-term exposures to environmental toxicants and endogenous electrophiles are causative factors for human diseases including cancer. DNA adducts reflect the internal exposure to genotoxicants and can serve as biomarkers for risk assessment. Liquid chromatography-multistage mass spectrometry (LC-MSn) is the most common method for biomonitoring DNA adducts, generally targeting single exposures and measuring up to several adducts. However, the data often provide limited evidence for a role of a chemical in the etiology of cancer. An "untargeted" method is required that captures global exposures to chemicals, by simultaneously detecting their DNA adducts in the genome; some of which may induce cancer-causing mutations. We established a wide selected ion monitoring tandem mass spectrometry (wide-SIM/MS2) screening method utilizing ultraperformance-LC nanoelectrospray ionization Orbitrap MSn with online trapping to enrich bulky, nonpolar adducts. Wide-SIM scan events are followed by MS2 scans to screen for modified nucleosides by coeluting peaks containing precursor and fragment ions differing by -116.0473 Da, attributed to the neutral loss of deoxyribose. Wide-SIM/MS2 was shown to be superior in sensitivity, specificity, and breadth of adduct coverage to other tested adductomic methods with detection possible at adduct levels as low as 4 per 109 nucleotides. Wide-SIM/MS2 data can be analyzed in a "targeted" fashion by generation of extracted ion chromatograms or in an "untargeted" fashion where a chromatographic peak-picking algorithm can be used to detect putative DNA adducts. Wide-SIM/MS2 successfully detected DNA adducts, derived from chemicals in the diet and traditional medicines and from lipid peroxidation products, in human prostate and renal specimens.

Data acquisition workflows in liquid chromatography coupled to high resolution mass spectrometry-based metabolomics: Where do we stand?

Typical mass spectrometry (MS) based untargeted metabolomics protocols are tedious as well as time- and sample-consuming. In particular, they often rely on "full-scan-only" analyses using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) from which metabolites of interest are first highlighted, and then tentatively identified by using targeted MS/MS experiments. However, this situation is evolving with the emergence of integrated HRMS based-data acquisition protocols able to perform multi-event acquisitions. Most of these protocols, referring to as data dependent and data independent acquisition (DDA and DIA, respectively), have been initially developed for proteomic applications and have recently demonstrated their applicability to biomedical studies. In this context, the aim of this article is to take stock of the progress made in the field of DDA- and DIA-based protocols, and evaluate their ability to change conventional metabolomic and lipidomic data acquisition workflows, through a review of HRMS instrumentation, DDA and DIA workflows, and also associated informatics tools.

Post-acquisition data mining techniques for LC–MS/MS-acquired data in drug metabolite identification

Metabolite identification is a crucial part of the drug discovery process. LC–MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC–MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.