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.</p

High Throughput LC-MS Platform for Large Scale Screening of Bioactive Polar Lipids in Human Plasma and Serum

Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples

A two-way interaction between methotrexate and the gut microbiota of male Sprague Dawley rats

Methotrexate (MTX) is a chemotherapeutic agent that can cause a range of toxic side effects including gastrointestinal damage, hepatotoxicity, myelosuppression, and nephrotoxicity and has potentially complex interactions with the gut microbiome. Following untargeted UPLC-qtof-MS analysis of urine and fecal samples from male Sprague–Dawley rats administered at either 0, 10, 40, or 100 mg/kg of MTX, dose-dependent changes in the endogenous metabolite profiles were detected. Semiquantitative targeted UPLC-MS detected MTX excreted in urine as well as MTX and two metabolites, 2,4-diamino-N-10-methylpteroic acid (DAMPA) and 7-hydroxy-MTX, in the feces. DAMPA is produced by the bacterial enzyme carboxypeptidase glutamate 2 (CPDG2) in the gut. Microbiota profiling (16S rRNA gene amplicon sequencing) of fecal samples showed an increase in the relative abundance of Firmicutes over the Bacteroidetes at low doses of MTX but the reverse at high doses. Firmicutes relative abundance was positively correlated with DAMPA excretion in feces at 48 h, which were both lower at 100 mg/kg compared to that seen at 40 mg/kg. Overall, chronic exposure to MTX appears to induce community and functionality changes in the intestinal microbiota, inducing downstream perturbations in CPDG2 activity, and thus may delay MTX detoxication to DAMPA. This reduction in metabolic clearance might be associated with increased gastrointestinal toxicity

Detection of pharmacolipidodynamic effects following the intravenous and oral administration of gefitinib to C57Bl/6JRj mice by rapid UHPLC-MS analysis of plasma

Abstract Omics-based biomarker technologies, including metabolic profiling (metabolomics/metabonomics) and lipidomics, are making a significant impact on disease understanding, drug development, and translational research. A wide range of patho-physiological processes involve lipids and monitoring changes in lipid abundance can give valuable insights into mechanisms of drug action, off target pharmacology and toxicity. Here we report changes, detected by untargeted LC–MS, in the plasma lipid profiles of male C57Bl/6JRj mice following the PO and IV administration of the epidermal growth factor receptor (EGFR) inhibitor gefitinib. Statistical analysis of the data obtained for both the IV and PO samples showed time-related changes in the amounts of lipids from several different classes. The largest effects were associated with a rapid onset of these changes following gefitinib administration followed by a gradual return by 24 h post dose to the type of lipid profile seen in predose samples. Investigation of the lipids responsible for the variance observed in the data showed that the PI, PC, LPC, PE and TG were subject to the largest disruption with both transient increases and decreases in relative amounts seen in response to administration of the drug. The pattern of the changes in the relative abundances of those lipids subject to variation appeared to be correlated to the pharmacokinetics of gefitinib (and its major metabolites). These observations support the concept of a distinct pharmacolipidodynamic relationship between drug exposure and plasma lipid abundance

Metabolic Phenotyping Using UPLC–MS and Rapid Microbore UPLC–IM–MS: Determination of the Effect of Different Dietary Regimes on the Urinary Metabolome of the Rat

A rapid reversed-phase gradient method employing a 50 mm × 1 mm i.d., C18 microbore column, combined with ion mobility and high-resolution mass spectrometry, was applied to the metabolic phenotyping of urine samples obtained from rats receiving different diets. This method was directly compared to a “conventional” method employing a 150 × 2.1 mm i.d. column packed with the same C18 bonded phase using the same samples. Multivariate statistical analysis of the resulting data showed similar class discrimination for both microbore and conventional methods, despite the detection of fewer mass/retention time features by the former. Multivariate statistical analysis highlighted a number of ions that represented diet-specific markers in the samples. Several of these were then identified using the combination of mass, ion-mobility-derived collision cross section and retention time including N-acetylglutamate, urocanic acid, and xanthurenic acid. Kynurenic acid was tentatively identified based on mass and ion mobility data.</p

Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia

There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants diagnosed with PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model separated PCa from controls with sensitivity of 0.82 and specificity of 0.95, adding BPH resulted in a statistically significant decline in specificity for prostate cancer to 0.76, with half of BPH cases being misclassified by the model as PCa. A small number of biomarkers differentiating between BPH and prostate cancer were identified, including proteins in MAP Kinase pathways, as well as in lipids containing oleic acid; these may offer a route to greater specificity. These results highlight, however, that whilst there are opportunities for machine learning, these will only be achieved by use of appropriate training sets that include confounding comorbidities, especially when calculating the specificity of a test