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.

Fecal metabolite analysis of Japanese macaques in Yakushima by LC-MS/MS and LC-QTOF-MS.

We performed a comprehensive fecal metabolite analysis using LC-MS/MS and LC-QTOF-MS approaches as a preliminary study. Feces of Japanese macaques on Yakushima Island were collected from five monkeys at two separate locations. Using the former methodology, 59 substances such as free amino acids, nucleotides, nucleosides and nucleic acid bases, and organic acids in the citrate cycle were quantitatively detected and successfully differentiated in two different monkey groups by the concentrations of nucleic acid metabolites and free amino acids. In the latter, around 12,000 substances were detected both by positive and negative mode in each sample. Differences in signal intensities were observed between two monkey groups in the concentrations of plant secondary metabolites such as cyanogenic glycosides, flavonoids, and phenolics.

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.

Identification and visualization of oxidized lipids in atherosclerotic plaques by microscopic imaging mass spectrometry-based metabolomics.

BACKGROUND AND AIMS: Dysregulated lipid metabolism has emerged as one of the major risk factors of atherosclerosis. Presently, there is a consensus that oxidized LDL (oxLDL) promotes development of atherosclerosis and downstream chronic inflammatory responses. Due to the dynamic metabolic disposition of lipoprotein, conventional approach to purify bioactive lipids for subsequent comprehensive analysis has proven to be inadequate for elucidation of the oxidized lipids species accountable for pathophysiology of atherosclerotic lesions. Herein, we aimed to utilize a novel mass microscopic imaging technology, coupled with mass spectrometry (MS) to characterize oxidized lipids in atherosclerotic lesions. METHODS: We attempted to use MALDI-TOF-MS and iMScope to identify selected oxidized lipid targets and visualize their respective localizations in study models of atherosclerosis. RESULTS: Based on the MS analysis, detection of 7-K under positive ionization through product ion peak at m/z 383 [M + H-H2O] indicated the distinctive presence of targeted lipid within Cu2+-oxLDL and Cu2+-oxLDL loaded macrophage-like J774A.1 cells, along with other cholesterol oxidation products. Moreover, the application of two-dimensional iMScope has successfully visualized the localization of lipids in aortic atherosclerotic plaques of the Watanabe heritable hyperlipidemic (WHHL) rabbit. Distinctive lipid distribution profiles were observed in atherosclerotic lesions of different sizes, especially the localizations of lysoPCs in atherosclerotic plaques. CONCLUSIONS: Taken together, we believe that both MALDI-TOF-MS and iMScope metabolomics technology may offer a novel proposition for future pathophysiological studies of lipid metabolism in atherosclerosis.

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.

Metabolomic LC-MS/MS analyses and meta 16S rRNA gene analyses on cecal feces of Japanese rock ptarmigans reveal fundamental differences between semi-wild and captive raised individuals.

Ex situ conservation of Japanese rock ptarmigans began in 2015 with the aim of reintroducing artificially raised birds into their original habitat. However, the current raising method in captivity seems insufficient in terms of the survivability of artificially raised birds in natural conditions. Feeding management is one potential reason for such insufficiency. In this study, we performed a comprehensive analysis of the hydrophilic metabolites by LC-MS/MS for the cecal feces of Japanese rock ptarmigans under in situ and ex situ conservation to reveal their gut chemical environment. We also analyzed the developmental processes of cecal microbiomes both in situ semi-wild and ex situ captive individuals. Metabolites of nucleic acid were rich in the in situ individuals, and free amino acids were rich in the ex situ individuals. The differences in the microbiome composition between in situ and ex situ individuals were also pronounced; major genera of in situ individuals were not detected or few in ex situ individuals. The alpha diversity of the cecal microbiome of semi-wild chicks at 1 week of age was almost the same as that of their hens, while it was very low in captive individuals. Sub-therapeutic use of oxytetracycline, a diet rich in protein and energy, and isolation from adult birds are considered to be causes for these great differences in gut chemical and microbiological environment between in situ and ex situ individuals.

Improved MALDI-MS method for the highly sensitive and reproducible detection of biomarker peaks for the proteotyping of Salmonella serotypes.

The rapid identification and classification of pathogenic microorganisms, including Salmonella enterica, is important for the surveillance and prevention of foodborne diseases. Matrix-assisted laser desorption\ionization time-of-flight mass spectrometry (MALDI-TOFMS) has been shown to be an effective tool for the rapid identification of microorganisms. In a previous report, a mass database consisting of 12 biomarker proteins, S8, L15, L17, L21, L25, S7, superoxide dismutase (SodA), peptidylprolyl cis-trans isomerase C, Gns, YibT, YaiA, and YciF, was introduced for the serotyping of S. enterica via MALDI-MS (Applied Microbiology and Biotechnology, 2017, 101, 8557-8569). However, the reproducibility of peak detection of biomarkers such as SodA at m\z 23 000 was poor. We report here an optimized MALDI-MS method for detecting these biomarkers with high sensitivity and reproducibility. The issue was solved by controlling the bacterial concentration at 1 × 10 to 1 × 102 MFU (3 × 106 to 3 × 107 CFU\µL, as calculated from the MFU), using the colony suspension supernatant obtained by centrifugation, and using matrix additives such as methylenediphosphonic acid and N-decyl-ß-D-maltopyranoside. We propose that the method including the above steps is one of the best for detecting biomarkers with high sensitivity and reproducibility.

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.

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.

Development of Antibody-Drug Conjugates Using DDS and Molecular Imaging.

Antibody-drug conjugate (ADC), as a next generation of antibody therapeutics, is a combination of an antibody and a drug connected via a specialized linker. ADC has four action steps: systemic circulation, the enhanced permeability and retention (EPR) effect, penetration within the tumor tissue, and action on cells, such as through drug delivery system (DDS) drugs. An antibody with a size of about 10 nm has the same capacity for passive targeting as some DDS carriers, depending on the EPR effect. In addition, some antibodies are capable of active targeting. A linker is stable in the bloodstream but should release drugs efficiently in the tumor cells or their microenvironment. Thus, the linker technology is actually a typical controlled release technology in DDS. Here, we focused on molecular imaging. Fluorescent and positron emission tomography (PET) imaging is useful for the visualization and evaluation of antibody delivery in terms of passive and active targeting in the systemic circulation and in tumors. To evaluate the controlled release of the ADC in the targeted area, a mass spectrometry imaging (MSI) with a mass microscope, to visualize the drug released from ADC, was used. As a result, we succeeded in confirming the significant anti-tumor activity of anti-fibrin, or anti-tissue factor-ADC, in preclinical settings by using DDS and molecular imaging.

Multi-imaging of Cytokinin and Abscisic Acid on the Roots of Rice (Oryza sativa) Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry.

Plant hormones act as important signaling molecules that regulate responses to abiotic stress as well as plant growth and development. Because their concentrations of hormones control the physiological responses in the target tissue, it is important to know the distributions and concentrations in the tissues. However, it is difficult to determine the hormone concentration on the plant tissue as a result of the limitations of conventional methods. Here, we report the first multi-imaging of two plant hormones, one of cytokinin [i.e., trans-zeatin (tZ)] and abscisic acid (ABA) using a new technology, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) imaging. Protonated signals of tZ (m/z 220.1) and ABA (m/z 265.3) were chosen on longitudinal sections of rice roots for MS imaging. tZ was broadly distributed about 40 mm behind the root apex but was barely detectable at the apex, whereas ABA was mainly detected at the root apex. Multi-imaging using MALDI-TOF-MS enabled the visualization of the localization and quantification of plant hormones. Thus, this tool is applicable to a wide range of plant species growing under various environmental conditions.

Development of ADCs Using Molecular Imaging.

Antibody-drug conjugates (ADCs) comprise an antibody, a linker, and a drug or payload. The selection of a tumor-specific antibody and development of a linker having an efficient controlled drug release (CDR) are critical steps in developing a fully functional and effective ADC. In our research strategy, molecular imaging technologies have been employed to evaluate the efficiency of antibody delivery and CDR of the linker. In preclinical setting, antibody delivery into the tumor area or antibody penetration through the tumor stroma in malignant lymphoma or pancreatic tumor was evaluated by in vivo fluorescence imaging technique. Positron emission tomography (PET) imaging studies were conducted using 89Zr-labeled antibody to evaluate tumor targeting in a spontaneous carcinogenesis model. The model had dense stroma and was pathophysiologically very similar to human cancer. The drug imaging system, using microscopic mass spectroscopy (MMS) with enhanced resolution and sensitivity, was used for the evaluation of CDR. Paclitaxel (PTX)-incorporated micelle, a high-molecular-weight (HMW) carrier with CDR, showing similar properties as those of ADC, was analyzed. In contrast to free PTX, micelle selectively increased drug accumulation into the tumor and reduced toxicity in normal tissues by the enhanced permeability and retention (EPR) effect. Our drug imaging system has been used recently to evaluate the CDR of the ADC-linker. We present our work on the development of ADC using a molecular imaging technique.

In situ label-free visualization of orally dosed strictinin within mouse kidney by MALDI-MS imaging.

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a powerful technique for visualizing the distribution of a wide range of biomolecules within tissue sections. However, methodology for visualizing a bioactive ellagitannin has not yet been established. This paper presents a novel in situ label-free MALDI-MSI technique for visualizing the distribution of strictinin, a bioactive ellagitannin found in green tea, within mammalian kidney after oral dosing. Among nine representative matrix candidates, 1,5-diaminonaphthalene (1,5-DAN), harmane, and ferulic acid showed higher sensitivity to strictinin spotted onto a MALDI sample plate. Of these, 1,5-DAN enables visualization of a two-dimensional image of strictinin directly spotted on mouse kidney sections with the highest sensitivity. Furthermore, 1,5-DAN-based MALDI-MSI could detect the unique distribution of orally dosed strictinin within kidney sections. This in situ label-free imaging technique will contribute to the localization analysis of strictinin and its biological mechanisms.

The significance of microscopic mass spectrometry with high resolution in the visualisation of drug distribution.

The visualisation and quantitative analysis of the native drug distribution in a pre-clinical or clinical setting are desirable for evaluating drug effects and optimising drug design. Here, using matrix-assisted laser desorption ionisation imaging mass spectrometry (MALDI-IMS) with enhanced resolution and sensitivity, we compared the distribution of a paclitaxel (PTX)-incorporating micelle (NK105) with that of PTX alone after injection into tumour-bearing mice. We demonstrated optically and quantitatively that NK105 delivered more PTX to the tumour, including the centre of the tumour, while delivering less PTX to normal neural tissue, compared with injection with PTX alone. NK105 treatment yielded a greater antitumour effect and less neural toxicity in mice than did PTX treatment. The use of high-resolution MALDI-IMS may be an innovative approach for pharmacological evaluation and drug design support.

Complete nucleotide sequence of the freshwater unicellular cyanobacterium Synechococcus elongatus PCC 6301 chromosome: gene content and organization.

The entire genome of the unicellular cyanobacterium Synechococcus elongatus PCC 6301 (formerly Anacystis nidulans Berkeley strain 6301) was sequenced. The genome consisted of a circular chromosome 2,696,255 bp long. A total of 2,525 potential protein-coding genes, two sets of rRNA genes, 45 tRNA genes representing 42 tRNA species, and several genes for small stable RNAs were assigned to the chromosome by similarity searches and computer predictions. The translated products of 56% of the potential protein-coding genes showed sequence similarities to experimentally identified and predicted proteins of known function, and the products of 35% of the genes showed sequence similarities to the translated products of hypothetical genes. The remaining 9% of genes lacked significant similarities to genes for predicted proteins in the public DNA databases. Some 139 genes coding for photosynthesis-related components were identified. Thirty-seven genes for two-component signal transduction systems were also identified. This is the smallest number of such genes identified in cyanobacteria, except for marine cyanobacteria, suggesting that only simple signal transduction systems are found in this strain. The gene arrangement and nucleotide sequence of Synechococcus elongatus PCC 6301 were nearly identical to those of a closely related strain Synechococcus elongatus PCC 7942, except for the presence of a 188.6 kb inversion. The sequences as well as the gene information shown in this paper are available in the Web database, CYORF (http://www.cyano.genome.jp/).

Interactions between SNP alleles at multiple Loci and variation in skin pigmentation in 122 Caucasians.

This study was undertaken to clarify the molecular basis for human skin color variation and the environmental adaptability to ultraviolet irradiation, with the ultimate goal of predicting the impact of changes in future environments on human health risk. One hundred twenty-two Caucasians living in Toledo, Ohio participated. Back and cheek skin were assayed for melanin as a quantitative trait marker. Buccal cell samples were collected and used for DNA extraction. DNA was used for SNP genotyping using the Masscode system, which entails two-step PCR amplification and a platform chemistry which allows cleavable mass spectrometry tags. The results show gene-gene interaction between SNP alleles at multiple loci (not necessarily on the same chromosome) contributes to inter-individual skin color variation while suggesting a high probability of linkage disequilibrium. Confirmation of these findings requires further study with other ethic groups to analyze the associations between SNP alleles at multiple loci and human skin color variation. Our overarching goal is to use remote sensing data to clarify the interaction between atmospheric environments and SNP allelic frequency and investigate human adaptability to ultraviolet irradiation. Such information should greatly assist in the prediction of the health effects of future environmental changes such as ozone depletion and increased ultraviolet exposure. If such health effects are to some extent predictable, it might be possible to prepare for such changes in advance and thus reduce the extent of their impact.

Techniques of SNP genotyping and remote sensing applied for elucidation of the contribution of polygene and environmental factors to inter-individual variation in skin pigmentation phenotype.

We present a conceptual framework for applying techniques of SNP genotyping as a molecular biological approach and remote sensing as an ecological approach to elucidation of the contribution of polygene and environmental factors to inter-individual variation in skin pigmentation phenotype. Additionally, we discuss the obstacles that frustrate our efforts to identify how the human genome encodes the complex phenotype and suggest the use of computational methods designed for knowledge discovery within hereditary database.