Pooled Sample Strategy in Conjunction with High-Resolution Liquid Chromatography−Mass Spectrometry-Based Background Subtraction to Identify Toxicological Markers in Dogs Treated with Ibipinabant

Integrating (Nutri-)Metabolomics into the One Health Tendency-The Key for Personalized Medicine Advancement

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment, can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases, or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals, and the environment is of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase in risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, and, in particular, nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

2-Pyridine Carboxaldehyde for Semi-Automated Soft Spot Identification in Cyclic Peptides

Cyclic peptides are an attractive option as therapeutics due to their ability to disrupt crucial protein-protein interactions and their flexibility in display type screening strategies, but they come with their own bioanalytical challenges in metabolite identification. Initial amide hydrolysis of a cyclic peptide results in a ring opening event in which the sequence is linearized. Unfortunately, the mass of the singly hydrolyzed sequence is the same (M + 18.0106 Da) irrespective of the initial site of hydrolysis, or soft spot. Soft spot identification at this point typically requires time-consuming manual interpretation of the tandem mass spectra, resulting in a substantial bottleneck in the hit to lead process. To overcome this, derivatization using 2-pyridine carboxaldehyde, which shows high selectivity for the alpha amine on the N-terminus, was employed. This strategy results in moderate- to high-efficiency derivatization with a unique mass tag and diagnostic ions that serve to highlight the first amino acid in the newly linearized peptide. The derivatization method and analytical strategy are demonstrated on a whole cell lysate digest, and the soft spot identification strategy is shown with two commercially available cyclic peptides: JB1 and somatostatin. Effective utilization of the automated sample preparation and interpretation of the resulting spectra shown here will serve to reduce the hit-to-lead time for generating promising proteolytically stable peptide candidates.

Canine metabolomics advances

INTRODUCTION

Canis lupus familiaris is a domestic dog and many owners consider their pets as a family member. Medical bills with dogs are overcame only by the health care received by humans. Medical care is constantly progressing, and so is veterinary care. Metabolomics is the ''omic" technique aimed to the study of metabolome, low-molecular weight molecules, through biofluids or tissue samples. And it also allows to evaluate disease diagnosis and prognosis, therapeutic evaluation and toxicological studies.

OBJECTIVES

The goal of this paper is to review the current and potential applications of metabolomics in domestic dogs.

METHOD

ScienceDirect, Scopus, Reaxys and PubMed were searched for papers that performed canine metabolomics in any research area.

RESULTS

We analysed 38 papers, published until April 2019 in canine metabolomics approach. Metabolomic research in dogs so far can be divided into three areas: (a) Metabolomics studies in veterinary science, such as improving pet dogs health and welfare. (b) Diet, breeds and species discrimination. (c) Use of dogs as animal model in different diseases and drug development (evaluation toxicity and effect).

CONCLUSIONS

The results of this review showed that interest in metabolomics is growing in veterinary research. Several canine diseases have been evaluated with some promise for potential biomarker and/or disease mechanism discovery. Because canine metabolomics is a relatively new area, the researches spread across different research areas and with few studies in each area.

The application of a novel high-resolution mass spectrometry-based analytical strategy to rapid metabolite profiling of a dual drug combination in humans

Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension. First, mass defect filter (MDF), as a targeted data mining tool, worked effectively except for those metabolites with similar MDF values. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, was able to recover all relevant metabolites of VER-IRB from the full-scan MS dataset except for trace metabolites buried in the background noise and/or combined drug-related signals. Third, the novel ring double bond (RDB; valence values of elements in structure) filter, could show rich structural information in more sensitive full-scan MS chromatograms; however, it had a low capability to remove background noise and was difficult to differentiate the metabolites with RDB coverage. Fourth, an integrated strategy, i.e., untargeted BS followed by RDB, was effective for metabolite identification of VER and IRB, which have different RDB values. Majority of matrix signals were firstly removed using BS. Metabolite ions for each parent drug were then isolated from remaining background matrix and combined drug-related signals by imposing of preset RDB values/ranges around the parent drug and selected core substructures. In parallel, MDF was used to recover potential metabolites with similar RDB. As a result, a total of 74 metabolites were found for VER-IRB in human plasma and urine, among which ten metabolites have not been previously reported in human. The results demonstrated that the combination of accurate mass-based multiple data-mining techniques, i.e., untargeted background subtraction followed by ring double bond filtering in parallel with targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drug.

Chromatographic peak reconstruction algorithm to improve qualitative and quantitative analysis of trace pesticide residues

RATIONALE

In order to improve analysis of analytes in trace amounts in a complex matrix, we developed a novel post-processing method, named Chromatographic Peak Reconstruction (CPR), to process the recorded data from gas chromatography/time-of-flight mass spectrometry (GC/TOFMS).

METHODS

For a trace ion, the relative deviation (δ) between the adjacent scanned mass-to-charge ratios (m/z) was found to be inversely proportional to its MS peak intensity. Based on this relationship, the thresholds of δ value within the specified intensity segments were estimated by the CPR and used to screen out the suspicious scan-points in the extracted ion chromatographic (EIC) peak. Then, the intensities of these suspicious scan-points were calibrated to reconstruct a new EIC peak.

RESULTS

In the qualitative analysis of 118 pesticides, 107 out of the test pesticides can be confirmed. The corrected response ratios of the qualitative ion (q) over the quantitative ion (Q), q/Q, became closer to their references. In the quantitative analysis of 10 test pesticides at 5 ppb, the relative errors of the calculated concentrations after using the CPR were below ±1.55%, down from ±2.29% without using the CPR.

CONCLUSIONS

The developed CPR showed great potential in the analysis of trace analytes in complex matrices. It was proved to be a helpful data processing method for the monitoring of trace pesticide residues. Copyright © 2016 John Wiley & Sons, Ltd.

An Integrated Approach for Studying Exposure, Metabolism, and Disposition of Multiple Component Herbal Medicines Using High-Resolution Mass Spectrometry and Multiple Data Processing Tools

A typical prescription of traditional Chinese medicine (TCM) contains up to a few hundred prototype components. Studying their absorption, metabolism, distribution, and elimination (ADME) presents great challenges. The objective of this study was to develop a practical approach for investigating ADME of individual prototypes in TCM. An active fraction of Xiao-Xu-Ming decoction (AF-XXMD) as a model TCM prescription was orally administered to rats. AF-XXMD-related components in plasma, urine, bile, and feces were detected using high-resolution mass spectrometry and background subtraction, an untargeted data-mining tool. Components were then structurally characterized on the basis of MS(n) spectral data. Connection of detected AF-XXMD metabolites to their precursor species, either prototypes or upstream metabolites, were determined on the basis of mass spectral similarity and the matching of biotransformation reactions. As a result, 247 AF-XXMD-related components were detected and structurally characterized in rats, 134 of which were metabolites. Among 198 AF-XXMD prototypes dosed, 65 were fully or partially absorbed and 13 prototypes and 34 metabolites were found in the circulation. Glucuronidation, isomerization, and deglycosylation followed by biliary and urinary excretions and direct elimination of prototypes via kidney and liver were the major clearance pathways of AF-XXMD prototypes. As an example, the ADME profile of H56, the single major AF-XXMD component in rat plasma, was elucidated on the basis of profiles of H56-related components in plasma and excreta. The results demonstrate that the new analytical approach is a useful tool for rapid and comprehensive detection and characterization of TCM components in biologic matrix in a TCM ADME study.

Innovations in Canine and Feline Nutrition: Technologies for Food and Nutrition Assessment

Pet owners have increasing concerns about the nutrition of their pets, and they desire foods and treats that are safe, traceable, and of high nutritive value. To meet these high expectations, detailed chemical composition characterization of ingredients well beyond that provided by proximate analysis will be required, as will information about host physiology and metabolism. Use of faster and more precise analytical methodology and novel technologies that have the potential to improve pet food safety and quality will be implemented. In vitro and in vivo assays will continue to be used as screening tools to evaluate nutrient quality and adequacy in novel ingredients prior to their use in animal diets. The use of molecular and high-throughput technologies allows implementation of noninvasive studies in dogs and cats to investigate the impact of dietary interventions by using systems biology approaches. These approaches may further improve the health and longevity of pets.

Development and application of a comparative fatty acid analysis method to investigate voriconazole-induced hepatotoxicity

BACKGROUND

As fatty acids play an important role in biological regulation, the profiling of fatty acid expression has been used to discover various disease markers and to understand disease mechanisms. This study developed an effective and accurate comparative fatty acid analysis method using differential labeling to speed up the metabolic profiling of fatty acids.

METHODS

Fatty acids were derivatized with unlabeled (D0) or deuterated (D3) methanol, followed by GC-MS analysis. The comparative fatty acid analysis method was validated using a series of samples with different ratios of D0/D3-labeled fatty acid standards and with mouse liver extracts.

RESULTS

Using a lipopolysaccharide (LPS)-treated mouse model, we found that the fatty acid profiles after LPS treatment were similar between the conventional single-sample analysis approach and the proposed comparative approach, with a Pearson's correlation coefficient of approximately 0.96. We applied the comparative method to investigate voriconazole-induced hepatotoxicity and revealed the toxicity mechanism as well as the potential of using fatty acids as toxicity markers.

CONCLUSIONS

In conclusion, the comparative fatty acid profiling technique was determined to be fast and accurate and allowed the discovery of potential fatty acid biomarkers in a more economical and efficient manner.

Cannabinoid receptor antagonist-induced striated muscle toxicity and ethylmalonic-adipic aciduria in beagle dogs

Ibipinabant (IBI), a potent cannabinoid-1 receptor (CB1R) antagonist, previously in development for the treatment of obesity, causes skeletal and cardiac myopathy in beagle dogs. This toxicity was characterized by increases in muscle-derived enzyme activity in serum and microscopic striated muscle degeneration and accumulation of lipid droplets in myofibers. Additional changes in serum chemistry included decreases in glucose and increases in non-esterified fatty acids and cholesterol, and metabolic acidosis, consistent with disturbances in lipid and carbohydrate metabolism. No evidence of CB1R expression was detected in dog striated muscle as assessed by polymerase chain reaction, immunohistochemistry, Western blot analysis, and competitive radioligand binding. Investigative studies utilized metabonomic technology and demonstrated changes in several intermediates and metabolites of fatty acid metabolism including plasma acylcarnitines and urinary ethylmalonate, methylsuccinate, adipate, suberate, hexanoylglycine, sarcosine, dimethylglycine, isovalerylglycine, and 2-hydroxyglutarate. These results indicated that the toxic effect of IBI on striated muscle in beagle dogs is consistent with an inhibition of the mitochondrial flavin-containing enzymes including dimethyl glycine, sarcosine, isovaleryl-CoA, 2-hydroxyglutarate, and multiple acyl-CoA (short, medium, long, and very long chain) dehydrogenases. All of these enzymes converge at the level of electron transfer flavoprotein (ETF) and ETF oxidoreductase. Urinary ethylmalonate was shown to be a biomarker of IBI-induced striated muscle toxicity in dogs and could provide the ability to monitor potential IBI-induced toxic myopathy in humans. We propose that IBI-induced toxic myopathy in beagle dogs is not caused by direct antagonism of CB1R and could represent a model of ethylmalonic-adipic aciduria in humans.

Drug metabolite profiling and identification by high-resolution mass spectrometry

Mass spectrometry plays a key role in drug metabolite identification, an integral part of drug discovery and development. The development of high-resolution (HR) MS instrumentation with improved accuracy and stability, along with new data processing techniques, has improved the quality and productivity of metabolite identification processes. In this minireview, HR-MS-based targeted and non-targeted acquisition methods and data mining techniques (e.g. mass defect, product ion, and isotope pattern filters and background subtraction) that facilitate metabolite identification are examined. Methods are presented that enable multiple metabolite identification tasks with a single LC/HR-MS platform and/or analysis. Also, application of HR-MS-based strategies to key metabolite identification activities and future developments in the field are discussed.