Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study.

INTRODUCTION: Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. METHODS: Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12-18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. RESULTS: A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10-20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10-4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. CONCLUSIONS: This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

High-Precision Automated Workflow for Urinary Untargeted Metabolomic Epidemiology.

Urine is a noninvasive biofluid that is rich in polar metabolites and well suited for metabolomic epidemiology. However, because of individual variability in health and hydration status, the physiological concentration of urine can differ >15-fold, which can pose major challenges in untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. Although numerous urine normalization methods have been implemented (e.g., creatinine, specific gravity-SG), most are manual and, therefore, not practical for population-based studies. To address this issue, we developed a method to measure SG in 96-well-plates using a refractive index detector (RID), which exhibited accuracy within 85-115% and <3.4% precision. Bland-Altman statistics showed a mean deviation of -0.0001 SG units (limits of agreement: -0.0014 to 0.0011) relative to a hand-held refractometer. Using this RID-based SG normalization, we developed an automated LC-MS workflow for untargeted urinary metabolomics in a 96-well-plate format. The workflow uses positive and negative ionization HILIC chromatography and acquires mass spectra in data-independent acquisition (DIA) mode at three collision energies. Five technical internal standards (tISs) were used to monitor data quality in each method, all of which demonstrated raw coefficients of variation (CVs) < 10% in the quality controls (QCs) and < 20% in the samples for a small cohort (n = 87 urine samples, n = 22 QCs). Application in a large cohort (n = 842 urine samples, n = 248 QCs) demonstrated CVQC < 5% and CVsamples < 16% for 4/5 tISs after signal drift correction by cubic spline regression. The workflow identified >540 urinary metabolites including endogenous and exogenous compounds. This platform is suitable for performing urinary untargeted metabolomic epidemiology and will be useful for applications in population-based molecular phenotyping.

Spatiotemporal determination of metabolite activities in the corneal epithelium on a chip.

The corneal epithelial barrier maintains the metabolic activities of the ocular surface by regulating membrane transporters and metabolic enzymes responsible for the homeostasis of the eye as well as the pharmacokinetic behavior of drugs. Despite its importance, no established biomimetic in vitro methods are available to perform the spatiotemporal investigation of metabolism and determine the transportation of endogenous and exogenous molecules across the corneal epithelium barrier. This study introduces multiple corneal epitheliums on a chip namely, Corneal Epithelium on a Chip (CEpOC), which enables the spatiotemporal collection as well as analysis of micro-scaled extracellular metabolites from both the apical and basolateral sides of the barriers. Longitudinal samples collected during 48 h period were analyzed using untargeted liquid chromatography-mass spectrometry metabolomics method, and 104 metabolites were annotated. We observed the spatiotemporal secretion of biologically relevant metabolites (i.e., antioxidant, glutathione and uric acid) as well as the depletion of essential nutrients such as amino acids and vitamins mimicking the in vivo molecules trafficking across the human corneal epithelium. Through the shifts of extracellular metabolites and quantitative analysis of mRNA associated with transporters, we were able to investigate the secretion and transportation activities across the polarized barrier in a correlation with the expression of corneal transporters. Thus, CEpOC can provide a non-invasive, simple, yet effectively informative method to determine pharmacokinetics and pharmacodynamics as well as to discover novel biomarkers for drug toxicological and safety tests as advanced experimental model of the human corneal epithelium.

High levels of Tryptophan reduce cell wall or membrane stress tolerance in Saccharomyces cerevisiae.

Tryptophan (Trp) is a proteinogenic aromatic amino acid; however, high levels of Trp are toxic in animals and yeast with unknown mechanisms. Previously, we suggested that aromatic aminotransferase Aro9 is important for excess Trp degradation. Besides, Schroeder and Ikui showed that aro9Δ is sensitive to membrane stress by sodium dodecyl sulfate. Therefore, Trp accumulation may reduce the cell wall or membrane (CW/M) stress tolerance through participation of cell wall integrity (CWI) pathway, which detects and responds to CW/M perturbations. In this study, we found that yeast mutants of the CWI mitogen-activated protein kinase cascade were susceptible to excess Trp. Also, the Trp degradation deficient mutant aro8Δ aro9Δ cells, in which Trp accumulation was confirmed, were sensitive to several CW/M stresses. These results indicated that accumulation of Trp is adverse for the CW/M stress resistance and may disturb appropriate signal transduction responding to the stress.

Correlation-Based Deconvolution (CorrDec) To Generate High-Quality MS2 Spectra from Data-Independent Acquisition in Multisample Studies.

Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich spectral annotations in untargeted metabolomics. However, the acquired MS2 spectra are highly complex, posing significant annotation challenges. We have developed a correlation-based deconvolution (CorrDec) method that uses ion abundance correlations in multisample studies using DIA-MS as an update of our MS-DIAL software. CorrDec is based on the assumption that peak intensities of precursor and fragment ions correlate across samples and exploits this quantitative information to deconvolute complex DIA spectra. CorrDec clearly improved deconvolution of the original MS-DIAL deconvolution method (MS2Dec) in a dilution series of chemical standards and a 224-sample urinary metabolomics study. The primary advantage of CorrDec over MS2Dec is the ability to discriminate coeluting low-abundance compounds. CorrDec requires the measurement of multiple samples to successfully deconvolute DIA spectra; however, our randomized assessment demonstrated that CorrDec can contribute to studies with as few as 10 unique samples. The presented methodology improves compound annotation and identification in multisample studies and will be useful for applications in large cohort studies.

Individual variability in human blood metabolites identifies age-related differences.

Metabolites present in human blood document individual physiological states influenced by genetic, epigenetic, and lifestyle factors. Using high-resolution liquid chromatography-mass spectrometry (LC-MS), we performed nontargeted, quantitative metabolomics analysis in blood of 15 young (29 ± 4 y of age) and 15 elderly (81 ± 7 y of age) individuals. Coefficients of variation (CV = SD/mean) were obtained for 126 blood metabolites of all 30 donors. Fifty-five RBC-enriched metabolites, for which metabolomics studies have been scarce, are highlighted here. We found 14 blood compounds that show remarkable age-related increases or decreases; they include 1,5-anhydroglucitol, dimethyl-guanosine, acetyl-carnosine, carnosine, ophthalmic acid, UDP-acetyl-glucosamine,N-acetyl-arginine,N6-acetyl-lysine, pantothenate, citrulline, leucine, isoleucine, NAD(+), and NADP(+) Six of them are RBC-enriched, suggesting that RBC metabolomics is highly valuable for human aging research. Age differences are partly explained by a decrease in antioxidant production or increasing inefficiency of urea metabolism among the elderly. Pearson's coefficients demonstrated that some age-related compounds are correlated, suggesting that aging affects them concomitantly. Although our CV values are mostly consistent with those CVs previously published, we here report previously unidentified CVs of 51 blood compounds. Compounds having moderate to high CV values (0.4-2.5) are often modified. Compounds having low CV values, such as ATP and glutathione, may be related to various diseases because their concentrations are strictly controlled, and changes in them would compromise health. Thus, human blood is a rich source of information about individual metabolic differences.

Development of a Liquid Chromatography-High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition.

High-resolution mass spectrometry (HRMS)-based metabolomics approaches have made significant advances. However, metabolite identification is still a major challenge with significant bottleneck in translating metabolomics data into biological context. In the current study, a liquid chromatography (LC)-HRMS metabolomics method was developed using an all ion fragmentation (AIF) acquisition approach. To increase the specificity in metabolite annotation, four criteria were considered: (i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum, and (iv) product/precursor ion intensity ratios. We constructed an in-house mass spectral library of 408 metabolites containing AMRT and MS/MS spectra information at four collision energies. The percent relative standard deviations between ion ratios of a metabolite in an analytical standard vs sample matrix were used as an additional metric for establishing metabolite identity. A data processing method for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information for each of the 413 metabolites. In the data processing method, the precursor ion and product ion were considered as the quantifier and qualifier ion, respectively. We also included a scheme to distinguish coeluting isobaric compounds by selecting a specific product ion as the quantifier ion instead of the precursor ion. An advantage of the current AIF approach is the concurrent collection of full scan data, enabling identification of metabolites not included in the database. Our data acquisition strategy enables a simultaneous mixture of database-dependent targeted and nontargeted metabolomics in combination with improved accuracy in metabolite identification, increasing the quality of the biological information acquired in a metabolomics experiment.

Modeling dry eye with an air-liquid interface in corneal epithelium-on-a-chip.

Dry eye syndrome (DES) is a complex ocular condition characterized by an unstable tear film and inadequate tear production, leading to tissue damage. Despite its common occurrence, there is currently no comprehensive in vitro model that accurately reproduce the cellular characteristics of DES. Here we modified a corneal epithelium-on-a-chip (CEpOC) model to recapitulate DES by subjecting HCE-T human corneal epithelial cells to an air-liquid (AL) interface stimulus. We then assessed the effects of AL stimulation both in the presence and absence of diclofenac (DCF), non-steroidal anti-inflammatory drug. Transcriptomic analysis revealed distinct gene expression changes in response to AL and AL_DCF, affecting pathways related to development, epithelial structure, inflammation, and extracellular matrix remodeling. Both treatments upregulated PIEZO2, linked to corneal damage signaling, while downregulating OCLN, involved in cell-cell junctions. They increased the expression of inflammatory genes (e.g., IL-6) and reduced mucin production genes (e.g., MUC16), reflecting dry eye characteristics. Metabolomic analysis showed increased secretion of metabolites associated with cell damage and inflammation (e.g., methyl-2-oxovaleric acid, 3-methyl-2-oxobutanoic acid, lauroyl-carnitine) in response to AL and even more with AL_DCF, indicating a shift in cellular metabolism. This study showcases the potential use of AL stimulus within the CEpOC to induce cellular characteristics relevant to DES.

Capillary electrophoresis using triple layer modified capillary facilitating salivary ion analyses: Application to search for potential stress markers induced by cold pressure test.

In this study, we introduce a novel approach for the analysis of salivary ions using capillary electrophoresis (CE) with a triple-layer coated capillary. The capillary is sequentially coated with cationic silylating reagents, poly(vinylsulfonate), and polybrene to form a custom designed surface that effectively inhibits adsorption of protein matrix on the capillary inner wall and allows for reproducible ion analysis. For the CE with capacitively coupled contactless conductivity detection, we used suitable background electrolytes (BGEs) for salivary ion analysis. Anions were separated using a mixture of 2-(N-morpholino)ethanesulfonic acid and l-arginine, and cations were separated using that with 18-crown-6. This setup enabled rapid separation, within 4 min, together with sensitive detection. We quantified nine common anions and five cations typically found in saliva samples using this CE method, both before and after a cold pressure test (CPT, a standard stress test). The CE system demonstrated consistent ion separation across 30 consecutive measurements without requiring capillary replacement. Notably, the salivary ion balance remained predominantly anion-rich, regardless of the CPT. Cold water exposure induced greater variation in the total anion concentration than in the total cation concentration. Further analysis using multiple regression analysis revealed strong relationships between nitrate and nitrite, formate and phosphate, and potassium and nitrate, before and after the CPT. Notably, potassium and nitrate ions exhibited variations in response to stress. These results provided a method for assessing salivary ion composition and insights into the potential of salivary ions as biomarkers for stress.

Intrakinetochore localization and essential functional domains of Drosophila Spc105.

The kinetochore is assembled during mitotic and meiotic divisions within the centromeric region of chromosomes. It is composed of more than eighty different proteins. Spc105 (also designated as Spc7, KNL-1 or Blinkin in different eukaryotes) is a comparatively large kinetochore protein, which can bind to the Mis12/MIND and Ndc80 complexes and to the spindle assembly checkpoint components Bub1 and BubR1. Our genetic characterization of Drosophila Spc105 shows that a truncated version lacking the rapidly evolving, repetitive central third still provides all essential functions. Moreover, in comparison with Cenp-C that has previously been observed to extend from the inner to the outer kinetochore region, full-length Spc105 is positioned further out and is not similarly extended along the spindle axis. Thus, our results indicate that Spc105 forms neither an extended link connecting inner Cenp-A chromatin with outer kinetochore regions nor a scaffold constraining kinetochore subcomplexes and spindle assembly checkpoint components together into a geometrically rigid supercomplex. Spc105 seems to provide a platform within the outer kinetochore allowing independent assembly of various kinetochore components.

Early Differentiation Signatures in Human Induced Pluripotent Stem Cells Determined by Non-Targeted Metabolomics Analysis.

Human induced pluripotent stem cells (hiPSCs) possess immense potential as a valuable source for the generation of a wide variety of human cells, yet monitoring the early cell differentiation towards a specific lineage remains challenging. In this study, we employed a non-targeted metabolomic analysis technique to analyze the extracellular metabolites present in samples as small as one microliter. The hiPSCs were subjected to differentiation by initiating culture under the basal medium E6 in combination with chemical inhibitors that have been previously reported to direct differentiation towards the ectodermal lineage such as Wnt/ß-catenin and TGF-ß kinase/activin receptor, alone or in combination with bFGF, and the inhibition of glycogen kinase 3 (GSK-3), which is commonly used for the diversion of hiPSCs towards mesodermal lineage. At 0 h and 48 h, 117 metabolites were identified, including biologically relevant metabolites such as lactic acid, pyruvic acid, and amino acids. By determining the expression of the pluripotency marker OCT3/4, we were able to correlate the differentiation status of cells with the shifted metabolites. The group of cells undergoing ectodermal differentiation showed a greater reduction in OCT3/4 expression. Moreover, metabolites such as pyruvic acid and kynurenine showed dramatic change under ectodermal differentiation conditions where pyruvic acid consumption increased 1-2-fold, while kynurenine secretion decreased 2-fold. Further metabolite analysis uncovered a group of metabolites specifically associated with ectodermal lineage, highlighting the potential of our findings to determine the characteristics of hiPSCs during cell differentiation, particularly under ectodermal lineage conditions.

Untargeted LC-MS Metabolomics for the Analysis of Micro-scaled Extracellular Metabolites from Hepatocytes.

Metabolome analysis in micro physiological models is a challenge due to the low volume of the cell culture medium (CCM). Here, we report a LC-MS-based untargeted metabolomics protocol for the detection of hepatocyte extracellular metabolites from micro-scale samples of CCM. Using a single LC-MS method we have detected 57 metabolites of which 27 showed >2-fold shifts after 72-hour incubation. We demonstrate that micro-scale CCM samples can be used for modelling micro-physiological temporal dynamics in metabolite intensities.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective.

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Challenges, progress and promises of metabolite annotation for LC-MS-based metabolomics.

Accurate annotation is vital for data interpretation; however, metabolite identification is a major bottleneck in untargeted metabolomics. Although community guidelines for metabolite identification were published over a decade ago, adaptation of the recommended standards has been limited. The complexity of LC-MS data due to combinations of various chromatographic and mass spectrometric acquisition methods has resulted in the advent of diverse workflows, which often involve non-standardized manual curation. Herein, we review the parameters involved in metabolite reporting and provide a workflow to estimate the level of confidence in reported metabolite annotation. The future of metabolite identification will be heavily based upon the use of metabolome data repositories and associated data analysis tools, which will enable data to be shared, re-analyzed and re-annotated in an automated fashion.

Diverse metabolic reactions activated during 58-hr fasting are revealed by non-targeted metabolomic analysis of human blood.

During human fasting, metabolic markers, including butyrates, carnitines, and branched-chain amino acids, are upregulated for energy substitution through gluconeogenesis and use of stored lipids. We performed non-targeted, accurate semiquantitative metabolomic analysis of human whole blood, plasma, and red blood cells during 34-58 hr fasting of four volunteers. During this period, 44 of ~130 metabolites increased 1.5~60-fold. Consistently fourteen were previously reported. However, we identified another 30 elevated metabolites, implicating hitherto unrecognized metabolic mechanisms induced by fasting. Metabolites in pentose phosphate pathway are abundant, probably due to demand for antioxidants, NADPH, gluconeogenesis and anabolic metabolism. Global increases of TCA cycle-related compounds reflect enhanced mitochondrial activity in tissues during fasting. Enhanced purine/pyrimidine metabolites support RNA/protein synthesis and transcriptional reprogramming, which is promoted also by some fasting-related metabolites, possibly via epigenetic modulations. Thus diverse, pronounced metabolite increases result from greatly activated catabolism and anabolism stimulated by fasting. Anti-oxidation may be a principal response to fasting.

Metabolomic Analysis of Yeast and Human Cells: Latest Advances and Challenges.

Liquid chromatography-mass spectrometry (LC-MS) based nontargeted metabolomics has been applied to a wide range of biological samples and can provide information on thousands of compounds. However, reliable identification of the compounds remains a challenge affecting result interpretation. In this protocol, we describe comparable yeast cell and whole blood metabolome sample preparation for extracting similar compound groups, and we present a LC-MS method using the all ion fragmentation (AIF) approach for the purposes of increasing accuracy in metabolite annotation. Our method enables database-dependent targeted as well as nontargeted metabolomics analysis from the same data acquisition, while simultaneously improving the accuracy in metabolite identification to increase the quality of the resulting biological information.

RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) Gene Variants with Predisposition to Age-Related Macular Degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is a progressive neurodegenerative disease of a central part of the neural retina (macula) and a leading cause of blindness in elderly people. While it is known that the AMD is a multifactorial disease, genetic factors involved in lipid metabolism, inflammation, and neovascularization are currently being widely studied in genome-wide association studies (GWAS). The aim of our study was to evaluate the impact of new single nucleotide polymorphisms (SNPs) in RAD51B, TRIB1, COL8A1, and COL10A1 genes on AMD development. METHODS: Case-control study involved 254 patients diagnosed with early AMD, 244 patients with exudative AMD, and 942 control subjects. The genotyping of RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) was carried out using TaqMan assays by a real-time polymerase chain reaction (RT-PCR) method. RESULTS: Statistically significant difference was found in genotype (TT, TC, and CC) distribution of COL8A1 rs13095226 between exudative AMD and control groups (60.2%, 33.6%, and 6.1% vs. 64.9%, 32.3%, and 2.9%, respectively, p = 0.036). Also, comparing with TT+TC, rs13095226 CC genotype was associated with 3.5-fold increased odds of exudative AMD development (OR = 3.540; 95% CI: 1.415-8.856; p = 0.007). CONCLUSION: Our study revealed a strong association between a variant in COL8A1 (rs13095226) and exudative AMD development.

Creating a Reliable Mass Spectral-Retention Time Library for All Ion Fragmentation-Based Metabolomics.

Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupled to mass spectrometry (LC-MS) methods across laboratories. Here, we illustrate how the combination of MS2 spectra, accurate mass, and retention time can improve the confidence of annotation and provide techniques to create a reliable library for all ion fragmentation (AIF) data with a focus on the characterization of the retention time. The resulting spectral library incorporates information on adducts and in-source fragmentation in AIF data, while noise peaks are effectively minimized through multiple deconvolution processes. We also report the development of the Mass Spectral LIbrary MAnager (MS-LIMA) tool to accelerate library sharing and transfer across laboratories. This library construction strategy improves the confidence in annotation for AIF data in LC-MS-based metabolomics and will facilitate the sharing of retention time and mass spectral data in the metabolomics community.

Tackling the Complexity of the Exposome: Considerations from the Gunma University Initiative for Advanced Research (GIAR) Exposome Symposium.

The attempt to describe complex diseases by solely genetic determination has not been successful. There is increasing recognition that the development of disease is often a consequence of interactions between multiple genetic and environmental factors. To date, much of the research on environmental determinants of disease has focused on single exposures generally measured at a single time point. In order to address this limitation, the concept of the exposome has been introduced as a comprehensive approach, studying the full complement of environmental exposures from conception onwards. However, exposures are vast, dynamic, and diverse, and only a small proportion can be reasonably measured due to limitations in technology and feasibility. In addition, the interplay between genes and exposure as well as between different exposures is complicated and multifaceted, which leads to difficulties in linking disease or health outcomes with exposures. The large numbers of collected samples require well-designed logistics. Furthermore, the immense data sets generated from exposome studies require a significant computational investment for both data analysis and data storage. This report summarizes discussions during an international exposome symposium held at Gunma University in Japan regarding the concept of the exposome, challenges in exposome research, and future perspectives in the field.