Development of a rapid-fire drug screening method by probe electrospray ionization tandem mass spectrometry for human urine (RaDPi-U).

Drug screening tests are mandatory in the search for drugs in forensic biological samples, and immunological methods and mass spectrometry (e.g., gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry) are commonly used for that purpose. However, these methods have some drawbacks, and developing new screening methods is required. In this study, we develop a rapid-fire drug screening method by probe electrospray ionization tandem mass spectrometry (PESI-MS/MS), which is an ambient ionization mass spectrometry method, for human urine, named RaDPi-U. RaDPi-U is carried out in three steps: (1) mixing urine with internal standard (IS) solution and ethanol, followed by vortexing; (2) pipetting the mixture onto a sample plate for PESI; and (3) rapid-fire analysis by PESI-MS/MS. RaDPi-U targets 40 forensically important drugs, which include illegal drugs, hypnotics, and psychoactive substances. The analytical results were obtained within 3 min because of the above-mentioned simple workflow of RaDPi-U. The calibration curves of each analyte were constructed using the IS method, and they were quantitatively valid, resulting in good linearity (0.972-0.999) with a satisfactory lower limit of detection and lower limit of quantitation (0.01-7.1 ng/mL and 0.02-21 ng/mL, respectively). Further, both trueness and precisions were 28% or less, demonstrating the high reliability and repeatability of the method. Finally, we applied RaDPi-U to three postmortem urine specimens and successfully detected different drugs in each urine sample. The practicality of the method is proven, and RaDPi-U will be a strong tool as a rapid-fire drug screening method not only in forensic toxicology but also in clinical toxicology.

Rapid quantification of extracellular neurotransmitters in mouse brain by PESI/MS/MS and longitudinal data analysis using the R and Stan-based Bayesian state-space model.

We developed a methodology for rapid quantification of extracellular neurotransmitters in mouse brain by PESI/MS/MS and longitudinal data analysis using the R and Stan-based Bayesian state-space model. We performed a rapid analysis for quantifying extracellular l-glutamic acid (L-Glu) and gamma-aminobutyric acid (GABA) in the mouse striatum by combined use of probe electrospray ionization/tandem mass spectrometry (PESI/MS/MS) and in vivo brain microdialysis. We optimized the PESI/MS/MS parameters with the authentic L-Glu, GABA, L-Glu-13C5,15N1, and GABA-D6 standards. We constructed calibration curves of L-Glu and GABA with the stable isotope internal standard correction method (L-Glu-13C5,15N1, and GABA-D6), demonstrating sufficient linearity (R > 0.999). Additionally, the quantitative method for L-Glu and GABA was validated with low-, middle-, and high-quality control samples. The intra- and inter-day accuracy and precision were 0.4%-7.5% and 1.7%-5.4% for L-Glu, respectively, and 0.1%-4.8% and 2.1%-5.7% for GABA, respectively, demonstrating high reproducibility of the method. To evaluate the feasibility of this method, microdialyses were performed on free-moving mice that were stimulated by high-K+-induced depolarization under different sampling conditions: 1) every 5 min for 150 min (n = 2) and 2) every 1 min for 30 min (n = 3). We applied the R and Stan-based Bayesian state-space model to each mouse's time-series data considering autocorrelation, and the model successfully detected abnormal changes in the L-Glu and GABA levels in each mouse. Thus, the L-Glu and GABA levels in all microdialysates approximately increased up to two- and seven-fold levels through high-K+-induced depolarization. Additionally, a 1-min temporal resolution was achieved using this method, thereby successfully monitoring microenvironmental changes in the extracellular L-Glu and GABA of the mouse striatum. In conclusion, this methodology using PESI/MS/MS and Bayesian state-space model allowed easy monitoring of neurotransmitters at high temporal resolutions and appropriate data interpretation considering autocorrelation of time-series data, which will reveal hidden pathological mechanisms of brain diseases, such as Parkinson's disease and Huntington's disease in the future.

Diagnostic significance of plasma lipid markers and machine learning-based algorithm for gastric cancer.

Biomarkers may be of value for the early detection of gastric cancer (GC) and the preoperative identification of tumor characteristics to guide treatment strategies. The present study analyzed the expression levels of phospholipids in plasma from patients with GC using liquid chromatography/electrospray ionization-mass spectrometry (LC/ESI-MS) to detect reliable biomarkers for GC. Furthermore, combining the results with a machine learning strategy, the present study attempted to establish a diagnostic system for GC. A total of 20 plasma samples from preoperative patients with GC and 16 plasma samples from tumor-free patients (controls) were selected from our biobank named 'SHINGEN (Yamanashi Biobank of Gastroenterological Cancers)', which includes a total of 1,592 plasma samples, and were analyzed by LC/ESI-MS. The obtained data were discriminated using a machine learning-based diagnostic algorithm, whose discriminant ability was confirmed through leave-one-out cross-validation. Using LC/ESI-MS, the levels of 236 lipid molecules were determined. Biomarker analysis revealed that a few lipids that were downregulated in the GC group could discriminate between the GC and control groups. Whole lipid composition analysis using partial least squares regression revealed good discrimination ability between the GC and control groups. Integrative analysis of all molecules using the aforementioned machine learning method exhibited a diagnostic accuracy of 94.4% (specificity, 93.8%; sensitivity, 95.0%). In conclusion, the outcomes of the present study suggested the potential future application of the aforementioned system in clinical settings. By accumulating more reliable data, the present system will be able to detect early-stage cancer and will be capable of predicting the efficacy of each therapeutic strategy.

High-performance Collective Biomarker from Liquid Biopsy for Diagnosis of Pancreatic Cancer Based on Mass Spectrometry and Machine Learning.

Background: Most pancreatic cancers are found at progressive stages when they cannot be surgically removed. Therefore, a highly accurate early detection method is urgently needed. Methods: This study analyzed serum from Japanese patients who suffered from pancreatic ductal adenocarcinoma (PDAC) and aimed to establish a PDAC-diagnostic system with metabolites in serum. Two groups of metabolites, primary metabolites (PM) and phospholipids (PL), were analyzed using liquid chromatography/electrospray ionization mass spectrometry. A support vector machine was employed to establish a machine learning-based diagnostic algorithm. Results: Integrating PM and PL databases improved cancer diagnostic accuracy and the area under the receiver operating characteristic curve. It was more effective than the algorithm based on either PM or PL database, or single metabolites as a biomarker. Subsequently, 36 statistically significant metabolites were fed into the algorithm as a collective biomarker, which improved results by accomplishing 97.4% and was further validated by additional serum. Interestingly, specific clusters of metabolites from patients with preoperative neoadjuvant chemotherapy (NAC) showed different patterns from those without NAC and were somewhat comparable to those of the control. Conclusion: We propose an efficient screening system for PDAC with high accuracy by liquid biopsy and potential biomarkers useful for assessing NAC performance.

RECiQ: A Rapid and Easy Method for Determining Cyanide Intoxication by Cyanide and 2-Aminothiazoline-4-carboxylic Acid Quantification in the Human Blood Using Probe Electrospray Ionization Tandem Mass Spectrometry.

In this study, we developed a rapid and easy method to determine cyanide (CN) intoxication by quantification of CN and 2-aminothiazoline-4-carboxylic acid (ATCA), which is a new and reliable indicator of CN exposure, in the human blood using probe electrospray ionization tandem mass spectrometry (PESI/MS/MS) named RECiQ. For CN, we applied the previously reported one-pot derivatization method using 2,3-naphthalenedialdehyde and taurine, which can directly derivatize CN in the blood. The analytical conditions of the CN derivatization were optimized as a 10 min reaction time at room temperature. In contrast, ATCA could be directly detected in the blood by PESI/MS/MS. We developed quantitative methods for the derivatized CN and ATCA using an internal standard method and validated them using quality control samples, demonstrating that the linearities of each calibration curve were greater than 0.995, and intra- and interday precisions and accuracies were 5.1-15 and 1.1-14%, respectively. Moreover, the lower limit of detections for CN and ATCA were 42 and 43 ng/mL, respectively. Finally, we applied RECiQ to three postmortem blood specimens obtained from victims of fire incidents, which resulted in the successful quantification of CN and ATCA in all samples. As PESI/MS/MS can be completed within 0.5 min, and the sample volume requirement of RECiQ is only 2 µL of blood, these methods are useful not only for the rapid determination of CN exposure but also for the estimation of the CN intoxication levels during an autopsy.

Optimal inter-batch normalization method for GC/MS/MS-based targeted metabolomics with special attention to centrifugal concentration.

This study investigated the optimal inter-batch normalization method for gas chromatography/tandem mass spectrometry (GC/MS/MS)-based targeted metabolome analysis of rodent blood samples. The effect of centrifugal concentration on inter-batch variation was also investigated. Six serum samples prepared from a mouse and 2 quality control (QC) samples from pooled mouse serum were assigned to each batch, and the 3 batches were analyzed by GC/MS/MS at different days. The following inter-batch normalization methods were applied to metabolome data: QC-based methods with quadratic (QUAD)- or cubic spline (CS)-fitting, total signal intensity (TI)-based method, median signal intensity (MI)-based method, and isotope labeled internal standard (IS)-based method. We revealed that centrifugal concentration was a critical factor to cause inter-batch variation. Unexpectedly, neither the QC-based normalization methods nor the IS-based method was able to normalize inter-batch variation, though MI- or TI-based normalization methods were effective in normalizing inter-batch variation. For further validation, 6 disease model rat and 6 control rat plasma were evenly divided into 3 batches, and analyzed as different batches. Same as the results above, MI- or TI-based methods were able to normalize inter-batch variation. In particular, the data normalized by TI-based method showed similar metabolic profiles obtained from their intra-batch analysis. In conclusion, the TI-based normalization method is the most effective to normalize inter-batch variation for GC/MS/MS-based metabolome analysis. Graphical abstract.

Preparation of Dimethyl Disulfide Adducts from the Mono-Trans Octadecadienoic Acid Methyl Esters.

The dimethyl disulfide (DMDS) adduct method is one of the more effective methods for determining double bond positions of dienoic acid. The DMDS method can be simply used to obtain the characteristic ions in which cleavage occurs between the methylthio group-added double-bond carbons as can be seen in the mass spectrum obtained using gas chromatography/electron ionization-mass spectrometry. In the case of the methylene-interrupted di-cis type and di-trans type dienoic acid, the DMDS addition reaction only occurs at one double-bond position, and cannot occur at the remaining double-bond position due to steric hindrance. As a result, two types of adducts are produced in the addition reaction. However, in the case of the methylene-interrupted mono-trans (mono-cis) type dienoic acid, the DMDS addition reaction only occurs at the cis-double bond. As a result, one type of adduct is produced in the addition reaction. In this report, we investigate the cause of the reaction selectivity by focusing on the addition reaction time.

Direct detection of the psychoactive substance MT-45 in human tissue samples by probe electrospray ionization-tandem mass spectrometry.

Analyses of drugs and poisons in tissue samples are essential in forensic toxicology and pharmacology. However, current procedures for tissue analysis are laborious and time-consuming. Therefore, we assessed the utility of a newly devised probe electrospray ionization (PESI) technique with tandem mass spectrometry (MS/MS) for easy, ultra-rapid drug detection in human tissue samples. Using this system, typical pretreatment procedures, such as solid-phase extraction, liquid-liquid extraction, deproteinization, or homogenization, can be avoided. Briefly, a tissue sample of 1-2 mm3 was supplemented with a solution of ethanol and 10 mmol/L ammonium formate, and measurements were obtained. We demonstrated the successful application of this method in a forensic case by detecting an opioid analgesic, MT-45, in all tissue samples (liver, kidney, lung, brain, and heart). We also detected oxidized metabolites of MT-45 in the liver. Since the analysis required only 0.5 minutes per sample, PESI-MS/MS is an ultra-rapid detection method. Furthermore, for a quantitative approach, the total analysis time for the combination of PESI-MS/MS with the quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction method (from instrument start-up to extraction and PESI-analysis) was within 8 minutes. MT-45 concentrations obtained by QuEChERS-PESI-MS/MS and liquid chromatography (LC) -MS/MS were similar for all tissue samples. PESI-MS/MS cannot be used to separate isobars/isomers (ie, compounds with the same m/z value), similar to other direct introduction techniques. Further studies are needed to validate the quantitation method. However, our results indicate that PESI-MS/MS is a potentially easy and rapid technique for the analysis of drugs and poisons in human tissue samples.

In Vivo Real-Time Monitoring System Using Probe Electrospray Ionization/Tandem Mass Spectrometry for Metabolites in Mouse Brain.

Recent improvements in ambient ionization techniques combined with mass spectrometry has enabled to achieve real-time monitoring of analytes of interest, even for biogenic molecules in living animals. Here, we demonstrate a newly developed system for in vivo real-time monitoring of metabolites in a living mouse brain. It consists of a semiautomated manipulation system and a unique probe electrospray ionization unit, which uses an extremely thin solid needle (tip dia.: 700 nm) for direct sampling and ionization, coupled to a conventional tandem mass spectrometer. The system successfully monitored 8 cerebrum metabolites related to central energy metabolism in an isoflurane-anesthetized mouse in real time with a 20 s interval. Moreover, our system succeeded in capturing dynamics of energy metabolism in a mouse administered with cannabinoid type-1 receptor agonist, which is known to disrupt cerebrum energy metabolism. The present system now opens the door to the next stage of cutting-edge technique in achieving in vivo real-time monitoring.

Intact metabolite profiling of mouse brain by probe electrospray ionization/triple quadrupole tandem mass spectrometry (PESI/MS/MS) and its potential use for local distribution analysis of the brain.

Probe electrospray ionization (PESI), which is an ambient ionization technique, enables us to analyze intact endogenous metabolites without sample preparation. In this study, we applied the newly developed method of PESI coupled to tandem mass spectrometry (PESI/MS/MS) to analyze metabolites in mouse brain, where its lipid composition often interfere with MS-based metabolome analysis. As a result, PESI/MS/MS directly detected 25 metabolites in a mouse frontal cortex, and clearly discriminated the metabolic profiles of mice model with energy metabolism disruption from control mice. PESI/MS/MS also allowed us to perform local distribution analysis of the hippocampus as well as the frontal cortex in each mouse (n = 5), discriminating their subtle metabolic differences. These results showed high potential of PESI/MS/MS for direct metabolome profiling of mouse brain.

Determination of Double Bond Positions and Geometry of Methyl Linoleate Isomers with Dimethyl Disulfide Adducts by GC/MS.

The dimethyl disulfide (DMDS) adduct method is one of the convenient and effective methods for determining double bond positions of unsaturated fatty acid methyl esters (FAME) except conjugated FAME. When analyzed using gas chromatography/electron ionization-mass spectrometry (GC/EI-MS), unsaturated FAME with DMDS added to the double bonds yields high intensity MS spectra of characteristic ions. The MS spectra of characteristic ions can then be used to easily confirm double bond positions. Here we explore the GC/EI-MS analysis of the DMDS adducts of methyl linoleate geometrical isomers isolated by high performance liquid chromatography (HPLC) with a silver nitrate column. For C18:2-c9, c12 and C18:2-t9, t12, DMDS randomly formed adducts with double bonds at either carbon 9-10 or carbon 12-13, but not both at the same time due to steric hindrance. For C18:2-c9, t12 and C18:2-t9, c12, however, DMDS only formed adducts with the double bond in the cis configuration. Consequently, when analyzing fatty acids with methylene interrupted double bonds, with one double bond in the cis and one in the trans configuration, double bond positions cannot be completely confirmed.

Intact Endogenous Metabolite Analysis of Mice Liver by Probe Electrospray Ionization/Triple Quadrupole Tandem Mass Spectrometry and Its Preliminary Application to in Vivo Real-Time Analysis.

Probe electrospray ionization (PESI) is a recently developed ionization technique that enables the direct detection of endogenous compounds like metabolites without sample preparation. In this study, we have demonstrated the first combination use of PESI with triple quadrupole tandem mass spectrometry (MS/MS), which was then applied to intact endogenous metabolite analysis of mice liver, achieving detection of 26 metabolites including amino acids, organic acids, and sugars. To investigate its practicality, metabolic profiles of control and CCl4-induced acute hepatic injury mouse model were measured by the developed method. Results showed clear separation of the two groups in score plots of principal component analysis and identified taurine as the primary contributor to group separation. The results were further validated by the established gas chromatography/MS/MS method, demonstrating the present method's usefulness. In addition, we preliminarily applied the method to real-time analysis of an intact liver of a living mouse. We successfully achieved monitoring of the real-time changes of two tricarboxylic acid cycle intermediates, α-ketoglutaric acid and fumaric acid, in the liver immediately after pyruvic acid injection via a cannulated tube to the portal vein. The present method achieved an intact analysis of metabolites in liver without sample preparation, and it also demonstrates future possibility to establish in vivo real-time metabolome analysis of living animals by PESI/MS/MS.