Predicting ion mobility collision cross sections and assessing prediction variation by combining conventional and data driven modeling.

The use of collision cross section (CCS) values derived from ion mobility studies is proving to be an increasingly important tool in the characterization and identification of molecules detected in complex mixtures. Here, a novel machine learning (ML) based method for predicting CCS integrating both molecular modeling (MM) and ML methodologies has been devised and shown to be able to accurately predict CCS values for singly charged small molecular weight molecules from a broad range of chemical classes. The model performed favorably compared to existing models, improving compound identifications for isobaric analytes in terms of ranking and assigning identification probability values to the annotation. Furthermore, charge localization was seen to be correlated with CCS prediction accuracy and with gas-phase proton affinity demonstrating the potential to provide a proxy for prediction error based on chemical structural properties. The presented approach and findings represent a further step towards accurate prediction and application of computationally generated CCS values.

Increasing coverage of the urinary polar metabolome using ultra high-performance hydrophobic interaction liquid chromatography combined with linear and cyclic travelling wave ion mobility and mass spectrometry.

The use of HILIC-based separations for the analysis of polar metabolites in metabolic phenotyping studies is well established. Here, we demonstrate the increased coverage of the polar metabolome obtained by travelling wave (TW) ion mobility (IM) instruments combined with HILIC and mass spectrometry (MS) for metabotyping rat and mouse urine samples. Profiling was performed using either a linear TW IM-MS based instrument with a path length of 40 cm or an instrument with a cyclic travelling wave analyser (cIM) with a path length of 95 cm. Due to the added resolution afforded by using both the linear and cyclic IM geometries with MS detection (IM-MS) significant increases in feature count (m/z-tR pairs) were generally obtained compared to HILIC-MS alone. In addition, the use of both linear and cyclic IM-MS improved the quality of the mass spectra obtained as a result of the separation of co-eluting analytes. As would be expected from the increased path length of the cyclic IM-MS instrument compared to the linear device, the largest gains in feature detection were obtained for the HILIC-cIM-MS combination. By increasing the resolution of coeluting components, the cyclic IM-MS instrumentation also provided the largest improvement in the quality of the mass spectral data obtained. When applied to mouse urines obtained from both control and gefitinib-dosed mice, time-related changes were detected in those obtained from the treated animals that were not seen in the controls. Polar metabolites affected by drug administration included, but were not limited to, hypoxanthine, 1,3-dimethyluracil and acetylcarnitine. The changes seen in the relative concentrations of these endogenous metabolites appeared to be related to drug concentrations in the plasma and urine suggesting a pharmacometabodynamic link.

Operation Moonshot: rapid translation of a SARS-CoV-2 targeted peptide immunoaffinity liquid chromatography-tandem mass spectrometry test from research into routine clinical use.

OBJECTIVES: During 2020, the UK's Department of Health and Social Care (DHSC) established the Moonshot programme to fund various diagnostic approaches for the detection of SARS-CoV-2, the pathogen behind the COVID-19 pandemic. Mass spectrometry was one of the technologies proposed to increase testing capacity. METHODS: Moonshot funded a multi-phase development programme, bringing together experts from academia, industry and the NHS to develop a state-of-the-art targeted protein assay utilising enrichment and liquid chromatography tandem mass spectrometry (LC-MS/MS) to capture and detect low levels of tryptic peptides derived from SARS-CoV-2 virus. The assay relies on detection of target peptides, ADETQALPQRK (ADE) and AYNVTQAFGR (AYN), derived from the nucleocapsid protein of SARS-CoV-2, measurement of which allowed the specific, sensitive, and robust detection of the virus from nasopharyngeal (NP) swabs. The diagnostic sensitivity and specificity of LC-MS/MS was compared with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) via a prospective study. RESULTS: Analysis of NP swabs (n=361) with a median RT-qPCR quantification cycle (Cq) of 27 (range 16.7-39.1) demonstrated diagnostic sensitivity of 92.4% (87.4-95.5), specificity of 97.4% (94.0-98.9) and near total concordance with RT-qPCR (Cohen's Kappa 0.90). Excluding Cq>32 samples, sensitivity was 97.9% (94.1-99.3), specificity 97.4% (94.0-98.9) and Cohen's Kappa 0.95. CONCLUSIONS: This unique collaboration between academia, industry and the NHS enabled development, translation, and validation of a SARS-CoV-2 method in NP swabs to be achieved in 5 months. This pilot provides a model and pipeline for future accelerated development and implementation of LC-MS/MS protein/peptide assays into the routine clinical laboratory.

Cov2MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein.

The pandemic readiness toolbox needs to be extended, targeting different biomolecules, using orthogonal experimental set-ups. Here, we build on our Cov-MS effort using LC-MS, adding SISCAPA technology to enrich proteotypic peptides of the SARS-CoV-2 nucleocapsid (N) protein from trypsin-digested patient samples. The Cov2MS assay is compatible with most matrices including nasopharyngeal swabs, saliva, and plasma and has increased sensitivity into the attomole range, a 1000-fold improvement compared to direct detection in a matrix. A strong positive correlation was observed with qPCR detection beyond a quantification cycle of 30-31, the level where no live virus can be cultured. The automatable sample preparation and reduced LC dependency allow analysis of up to 500 samples per day per instrument. Importantly, peptide enrichment allows detection of the N protein in pooled samples without sensitivity loss. Easily multiplexed, we detect variants and propose targets for Influenza A and B detection. Thus, the Cov2MS assay can be adapted to test for many different pathogens in pooled samples, providing longitudinal epidemiological monitoring of large numbers of pathogens within a population as an early warning system.

Paper Spray Ionization Ion Mobility Mass Spectrometry of Sebum Classifies Biomarker Classes for the Diagnosis of Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, and identification of robust biomarkers to complement clinical diagnosis will accelerate treatment options. Here, we demonstrate the use of direct infusion of sebum from skin swabs using paper spray ionization coupled with ion mobility mass spectrometry (PS-IM-MS) to determine the regulation of molecular classes of lipids in sebum that are diagnostic of PD. A PS-IM-MS method for sebum samples that takes 3 min per swab was developed and optimized. The method was applied to skin swabs collected from 150 people and elucidates ∼4200 features from each subject, which were independently analyzed. The data included high molecular weight lipids (>600 Da) that differ significantly in the sebum of people with PD. Putative metabolite annotations of several lipid classes, predominantly triglycerides and larger acyl glycerides, were obtained using accurate mass, tandem mass spectrometry, and collision cross section measurements.

Evaluation of acquisition modes for semi-quantitative analysis by targeted and untargeted mass spectrometry.

RATIONALE: Analyte quantitation by mass spectrometry underpins a diverse range of scientific endeavors. The fast-growing field of mass spectrometer development has resulted in several targeted and untargeted acquisition modes suitable for these applications. By characterizing the acquisition methods available on an ion mobility (IM)-enabled orthogonal acceleration time-of-flight (oa-ToF) instrument, the optimum modes for analyte semi-quantitation can be deduced. METHODS: Serial dilutions of commercial metabolite, peptide, or cross-linked peptide analytes were prepared in matrices of human urine or Escherichia coli digest. Each analyte dilution was introduced into an IM separation-enabled oa-ToF mass spectrometer by reversed-phase liquid chromatography and electrospray ionization. Data were acquired for each sample in duplicate using nine different acquisition modes, including four IM-enabled acquisitions modes, available on the mass spectrometer. RESULTS: Five (metabolite) or seven (peptide/cross-linked peptide) point calibration curves were prepared for analytes across each of the acquisition modes. A nonlinear response was observed at high concentrations for some modes, attributed to saturation effects. Two correction methods, one MS1 isotope-correction and one MS2 ion intensity-correction, were applied to address this observation, resulting in an up to twofold increase in dynamic range. By averaging the semi-quantitative results across analyte classes, two parameters, linear dynamic range (LDR) and lower limit of quantification (LLOQ), were determined to evaluate each mode. CONCLUSION: A comparison of the acquisition modes revealed that data-independent acquisition and parallel reaction monitoring methods are most robust for semi-quantitation when considering achievable LDR and LLOQ. IM-enabled modes exhibited sensitivity increases, but a simultaneous reduction in dynamic range required correction methods to recover. These findings will assist users in identifying the optimum acquisition mode for their analyte quantitation needs, supporting a diverse range of applications and providing guidance for future acquisition mode developments.

Investigation into Small Molecule Isomeric Glucuronide Metabolite Differentiation Using In Silico and Experimental Collision Cross-Section Values.

Identifying isomeric metabolites remains a challenging and time-consuming process with both sensitivity and unambiguous structural assignment typically only achieved through the combined use of LC-MS and NMR. Ion mobility mass spectrometry (IMMS) has the potential to produce timely and accurate data using a single technique to identify drug metabolites, including isomers, without the requirement for in-depth interpretation (cf. MS/MS data) using an automated computational pipeline by comparison of experimental collision cross-section (CCS) values with predicted CCS values. An ion mobility enabled Q-Tof mass spectrometer was used to determine the CCS values of 28 (14 isomeric pairs of) small molecule glucuronide metabolites, which were then compared to two different in silico models; a quantum mechanics (QM) and a machine learning (ML) approach to test these approaches. The difference between CCS values within isomer pairs was also assessed to evaluate if the difference was large enough for unambiguous structural identification through in silico prediction. A good correlation was found between both the QM- and ML-based models and experimentally determined CCS values. The predicted CCS values were found to be similar between ML and QM in silico methods, with the QM model more accurately describing the difference in CCS values between isomer pairs. Of the 14 isomeric pairs, only one (naringenin glucuronides) gave a sufficient difference in CCS values for the QM model to distinguish between the isomers with some level of confidence, with the ML model unable to confidently distinguish the studied isomer pairs. An evaluation of analyte structures was also undertaken to explore any trends or anomalies within the data set.

Use of Cyclic Ion Mobility Spectrometry (cIM)-Mass Spectrometry to Study the Intramolecular Transacylation of Diclofenac Acyl Glucuronide.

1-ß-O-Acyl-glucuronides (AGs) are common metabolites of carboxylic acid-containing xenobiotics, including, e.g., many nonsteroidal anti-inflammatory drugs (NSAIDs). They are of concern to regulatory authorities because of the association of these metabolites with the hepatotoxicity that has resulted in drug withdrawal. One factor in assessing the potential risk posed by AGs is the rate of transacylation of the biosynthetic 1-ß-O-acyl form to the 2-, 3-, and 4-O-acyl isomers. While transacylation can be measured using 1H NMR spectroscopy or liquid chromatography-mass spectrometry (LC-MS), the process can be time consuming and involve significant method development. The separation of these positional isomers by ion mobility spectrometry (IMS) has the potential to allow their rapid analysis, but conventional instruments lacked the resolving power to do this. Prediction of the collision cross section (CCS) using a machine learning model suggested that greater IMS resolution might be of use in this area. Cyclic IMS was evaluated for separating mixtures of isomeric AGs of diclofenac and was compared with a conventional ultraperformance liquid chromatography (UPLC)-MS method as a means for studying transacylation kinetics. The resolution of isomeric AGs was not seen using a conventional traveling wave IMS device; however, separation was seen after several passes around a cyclic IMS. The cyclic IMS enabled the degradation of the 1-ß-O-acyl-isomer to be analyzed much more rapidly than by LC-MS. The ability of cyclic IMS to monitor the rate of AG transacylation at different pH values, without the need for a prior chromatographic separation, should allow high-throughput, real-time, monitoring of these types of reactions.

Application of Predicted Collisional Cross Section to Metabolome Databases to Probabilistically Describe the Current and Future Ion Mobility Mass Spectrometry.

Metabolomics is a powerful phenotyping platform with potential for high-throughput analyses. The primary technology for metabolite profiling is mass spectrometry. In recent years, the coupling of mass spectrometry with ion mobility spectrometry (IMS) has offered the promise of faster analysis time and greater resolving power. Our understanding of the potential impact of IMS on the field of metabolomics is limited by availability of comprehensive experimental data. In this analysis, we use a probabilistic approach to enumerate the strengths and limitations, the present and future, of this technology. This is accomplished through use of "model" metabolomes, predicted physicochemical properties, and probabilistic descriptions of resolving power. This analysis advances our understanding of the importance of orthogonality in resolving (separation) dimensions, describes the impact of the metabolome composition on resolution demands, and offers a system resolution landscape that may serve to guide practitioners in the coming years.

Dynamic changes in the brain protein interaction network correlates with progression of Aß42 pathology in Drosophila.

Alzheimer's disease (AD), the most prevalent form of dementia, is a progressive and devastating neurodegenerative condition for which there are no effective treatments. Understanding the molecular pathology of AD during disease progression may identify new ways to reduce neuronal damage. Here, we present a longitudinal study tracking dynamic proteomic alterations in the brains of an inducible Drosophila melanogaster model of AD expressing the Arctic mutant Aß42 gene. We identified 3093 proteins from flies that were induced to express Aß42 and age-matched healthy controls using label-free quantitative ion-mobility data independent analysis mass spectrometry. Of these, 228 proteins were significantly altered by Aß42 accumulation and were enriched for AD-associated processes. Network analyses further revealed that these proteins have distinct hub and bottleneck properties in the brain protein interaction network, suggesting that several may have significant effects on brain function. Our unbiased analysis provides useful insights into the key processes governing the progression of amyloid toxicity and forms a basis for further functional analyses in model organisms and translation to mammalian systems.

The influence of hypoxia on the prostate cancer proteome.

Prostate cancer accounts for around 15% of male deaths in Western Europe and is the second leading cause of cancer death in men after lung cancer. Mounting evidence suggests that prostate cancer deposits exist within a hypoxic environment and this contributes to radio-resistance thus hampering one of the major therapies for this cancer. Recent reports have shown that nitric oxide (NO) donating non-steroidal anti-inflammatory drugs (NSAIDs) reduced tumour hypoxia as well as maintaining a radio-sensitising/therapeutic effect on prostate cancer cells. The aim of this study was to evaluate the impact of hypoxia on the proteome of the prostate and to establish whether NO-NSAID treatment reverted the protein profiles back to their normoxic status. To this end an established hormone insensitive prostate cancer cell line, PC-3, was cultured under hypoxic and normoxic conditions before and following exposure to NO-NSAID in combination with selected other common prostate cancer treatment types. The extracted proteins were analysed by ion mobility-assisted data independent acquisition mass spectrometry (MS), combined with multivariate statistical analyses, to measure hypoxia-induced alterations in the proteome of these cells. The analyses demonstrated that under hypoxic conditions there were well-defined, significantly regulated/differentially expressed proteins primarily involved with structural and binding processes including, for example, TUBB4A, CIRP and PLOD1. Additionally, the exposure of hypoxic cells to NSAID and NO-NSAID agents, resulted in some of these proteins being differentially expressed; for example, both PCNA and HNRNPA1L were down-regulated, corresponding with disruption in the nucleocytoplasmic shuttling process.

An Analytical Perspective on Protein Analysis and Discovery Proteomics by Ion Mobility-Mass Spectrometry.

Ion mobility combined with mass spectrometry (IM-MS) is a powerful technique for the analysis of biomolecules and complex mixtures. This chapter reviews the current state-of-the-art in ion mobility technology and its application to biology, protein analysis, and quantitative discovery proteomics in particular, from an analytical perspective. IM-MS can be used as a technique to separate mixtures, to determine structural information (rotationally averaged cross-sectional area) and to enhance MS duty cycle and sensitivity. Moreover, IM-MS is ideally suited for hyphenating with liquid chromatography, or other front-end separation techniques such as, GC, microcolumn LC, capillary electrophoresis, and direct analysis, including MALDI and DESI, providing an semiorthogonal layer of separation, which affords the more unambiguous and confident detection of a wide range of analytes. To illustrate these enhancements, as well as recent developments, the principle of in-line IM separation and hyphenation to orthogonal acceleration time-of-flight mass spectrometers are discussed, in addition to the enhancement of biophysical MS-based analysis using typical proteomics and related application examples.

A comparison of collision cross section values obtained via travelling wave ion mobility-mass spectrometry and ultra high performance liquid chromatography-ion mobility-mass spectrometry: Application to the characterisation of metabolites in rat urine.

A comprehensive Collision Cross Section (CCS) library was obtained via Travelling Wave Ion Guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TWCCSN2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility enabled orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TWCCSN2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TWCCSN2 data sources and predicted TWCCSN2 values indicated to be within 1-2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (tr), m/z and TWCCSN2 values (with the latter compared with the DI-IM-MS data). Analytes for which TWCCSN2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TWCCSN2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of tr, TWCCSN2 and MS data.

Expanding the Use of Spectral Libraries in Proteomics.

The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.

Specificity of the osmotic stress response in Candida albicans highlighted by quantitative proteomics.

Stress adaptation is critical for the survival of microbes in dynamic environments, and in particular, for fungal pathogens to survive in and colonise host niches. Proteomic analyses have the potential to significantly enhance our understanding of these adaptive responses by providing insight into post-transcriptional regulatory mechanisms that contribute to the outputs, as well as testing presumptions about the regulation of protein levels based on transcript profiling. Here, we used label-free, quantitative mass spectrometry to re-examine the response of the major fungal pathogen of humans, Candida albicans, to osmotic stress. Of the 1,262 proteins that were identified, 84 were down-regulated in response to 1M NaCl, reflecting the decrease in ribosome biogenesis and translation that often accompanies stress. The 64 up-regulated proteins included central metabolic enzymes required for glycerol synthesis, a key osmolyte for this yeast, as well as proteins with functions during stress. These data reinforce the view that adaptation to salt stress involves a transient reduction in ribosome biogenesis and translation together with the accumulation of the osmolyte, glycerol. The specificity of the response to salt stress is highlighted by the small proportion of quantified C. albicans proteins (5%) whose relative elevated abundances were statistically significant.

BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology.

Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI.

Scanning Quadrupole Data-Independent Acquisition, Part A: Qualitative and Quantitative Characterization.

A novel data-independent acquisition (DIA) method incorporating a scanning quadrupole in front of a collision cell and orthogonal acceleration time-of-flight mass analyzer is described. The method has been characterized for the qualitative and quantitative label-free proteomic analysis of complex biological samples. The principle of the scanning quadrupole DIA method is discussed, and analytical instrument characteristics, such as the quadrupole transmission width, scan/integration time, and chromatographic separation, have been optimized in relation to sample complexity for a number of different model proteomes of varying complexity and dynamic range including human plasma, cell lines, and bacteria. In addition, the technological merits over existing DIA approaches are described and contrasted. The qualitative and semiquantitative performance of the method is illustrated for the analysis of relatively simple protein digest mixtures and a well-characterized human cell line sample using untargeted and targeted search strategies. Finally, the results from a human cell line were compared against publicly available data that used similar chromatographic conditions but were acquired with DDA technology and alternative mass analyzer systems. Qualitative comparison showed excellent concordance of results with >90% overlap of the detected proteins.

Scanning Quadrupole Data-Independent Acquisition, Part B: Application to the Analysis of the Calcineurin-Interacting Proteins during Treatment of Aspergillus fumigatus with Azole and Echinocandin Antifungal Drugs.

Calcineurin is a critical cell-signaling protein that orchestrates growth, stress response, virulence, and antifungal drug resistance in several fungal pathogens. Blocking calcineurin signaling increases the efficacy of several currently available antifungals and suppresses drug resistance. We demonstrate the application of a novel scanning quadrupole DIA method for the analysis of changes in the proteins coimmunoprecipitated with calcineurin during therapeutic antifungal drug treatments of the deadly human fungal pathogen Aspergillus fumigatus. Our experimental design afforded an assessment of the precision of the method as demonstrated by peptide- and protein-centric analysis from eight replicates of the study pool QC samples. Two distinct classes of clinically relevant antifungal drugs that are guideline recommended for the treatment of invasive "aspergillosis" caused by Aspergillus fumigatus, the azoles (voriconazole) and the echinocandins (caspofungin and micafungin), which specifically target the fungal plasma membrane and the fungal cell wall, respectively, were chosen to distinguish variations occurring in the proteins coimmunoprecipitated with calcineurin. Novel potential interactors were identified in response to the different drug treatments that are indicative of the possible role for calcineurin in regulating these effectors. Notably, treatment with voriconazole showed increased immunoprecipitation of key proteins involved in membrane ergosterol biosynthesis with calcineurin. In contrast, echinocandin (caspofungin or micafungin) treatments caused increased immunoprecipitation of proteins involved in cell-wall biosynthesis and septation. Furthermore, abundant coimmunoprecipitation of ribosomal proteins with calcineurin occurred exclusively in echinocandins treatment, indicating reprogramming of cellular growth mechanisms during different antifungal drug treatments. While variations in the observed calcineurin immunoprecipitated proteins may also be due to changes in their expression levels under different drug treatments, this study suggests an important role for calcineurin-dependent cellular mechanisms in response to antifungal treatment of A. fumigatus that warrants future studies.

Determination of Protein Haptenation by Chemical Sensitizers Within the Complexity of the Human Skin Proteome.

Skin sensitization associated with the development of allergic contact dermatitis occurs via a number of specific key events at the cellular level. The molecular initiating event (MIE), the first in the sequence of these events, occurs after exposure of the skin to an electrophilic chemical, causing the irreversible haptenation of proteins within skin. Characterization of this MIE is a key step in elucidating the skin sensitization adverse outcome pathway and is essential to providing parameters for mathematical models to predict the capacity of a chemical to cause sensitization. As a first step to addressing this challenge, we have exposed complex protein lysates from a keratinocyte cell line and human skin tissue with a range of well characterized sensitizers, including dinitrochlorobenzene, 5-chloro-2-methylisothiazol-3-one, cinnamaldehyde, and the non (or weak) sensitizer 6-methyl coumarin. Using a novel stable isotope labeling approach combined with ion mobility-assisted data independent mass spectrometry (HDMSE), we have characterized the haptenome for these sensitizers. Although a significant proportion of highly abundant proteins were haptenated, we also observed the haptenation of low abundant proteins by all 3 of the chemical sensitizers tested, indicating that within a complex protein background, protein abundance is not the sole determinant driving haptenation, highlighting a relationship to tertiary protein structure and the amino acid specificity of these chemical sensitizers and sensitizer potency.

Lipid profiling of complex biological mixtures by liquid chromatography/mass spectrometry using a novel scanning quadrupole data-independent acquisition strategy.

RATIONALE: A novel data-independent acquisition method is detailed that incorporates a scanning quadrupole in front of an orthogonal acceleration time-of-flight (TOF) mass analyser. This approach is described and the attributes are compared and contrasted to other DIA approaches. METHODS: Specific application of the method to both targeted and untargeted lipidomic identification strategies is discussed, with data from both shotgun and LC separated lipidomics experiments presented. RESULTS: The benefits of the fast quadrupole scanning technique are highlighted, and include improvements in speed and specificity for complex mixtures providing high quality qualitative and quantitative data. CONCLUSIONS: In particular the high specificity afforded by the scanning quadrupole improves qualitative information for lipid identification.