Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that ...reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
Display omitted
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference ...Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.
The Keap1-Nrf2 system is central for mammalian cytoprotection against various stresses and a drug target for disease prevention and treatment. One model for the molecular mechanisms leading to Nrf2 ...activation is the Hinge-Latch model, where the DLGex-binding motif of Nrf2 dissociates from Keap1 as a latch, while the ETGE motif remains attached to Keap1 as a hinge. To overcome the technical difficulties in examining the binding status of the two motifs during protein-protein interaction (PPI) simultaneously, we utilized NMR spectroscopy titration experiments. Our results revealed that latch dissociation is triggered by low-molecular-weight Keap1-Nrf2 PPI inhibitors and occurs during p62-mediated Nrf2 activation, but not by electrophilic Nrf2 inducers
This study demonstrates that Keap1 utilizes a unique Hinge-Latch mechanism for Nrf2 activation upon challenge by non-electrophilic PPI-inhibiting stimuli, and provides critical insight for the pharmacological development of next-generation Nrf2 activators targeting the Keap1-Nrf2 PPI.
The oomycete pathogen Phytophthora infestans causes potato late blight, one of the most economically damaging plant diseases worldwide. P. infestans produces AVR3a, an essential modular virulence ...effector with an N-terminal RXLR domain that is required for host-cell entry. In host cells, AVR3a stabilizes and inhibits the function of the E3 ubiquitin ligase CMPG1, a key factor in host immune responses including cell death triggered by the pathogen-derived elicitor protein INF1 elicitin. To elucidate the molecular basis of AVR3a effector function, we determined the structure of Phytophthora capsici AVR3a4, a close homolog of P. infestans AVR3a. Our structural and functional analyses reveal that the effector domain of AVR3a contains a conserved, positively charged patch and that this region, rather than the RXLR domain, is required for binding to phosphatidylinositol monophosphates (PIPs) in vitro. Mutations affecting PIP binding do not abolish AVR3a recognition by the resistance protein R3a but reduce its ability to suppress INF1-triggered cell death in planta. Similarly, stabilization of CMPG1 in planta is diminished by these mutations. The steady-state levels of non–PIP-binding mutant proteins in planta are reduced greatly, although these proteins are stable in vitro. Furthermore, overexpression of a phosphatidylinositol phosphate 5-kinase results in reduction of AVR3a levels in planta. Our results suggest that the PIP-binding ability of the AVR3a effector domain is essential for its accumulation inside host cells to suppress CMPG1-dependent immunity.
Full text
Available for:
BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Signal overlapping is a major bottleneck for protein NMR analysis. We propose a new method, stable-isotope-assisted parameter extraction (SiPex), to resolve overlapping signals by a combination of ...amino-acid selective isotope labeling (AASIL) and tensor decomposition. The basic idea of Sipex is that overlapping signals can be decomposed with the help of intensity patterns derived from quantitative fractional AASIL, which also provides amino-acid information. In SiPex, spectra for protein characterization, such as
15
N relaxation measurements, are assembled with those for amino-acid information to form a four-order tensor, where the intensity patterns from AASIL contribute to high decomposition performance even if the signals share similar chemical shift values or characterization profiles, such as relaxation curves. The loading vectors of each decomposed component, corresponding to an amide group, represent both the amino-acid and relaxation information. This information link provides an alternative protein analysis method that does not require “assignments” in a general sense; i.e., chemical shift determinations, since the amino-acid information for some of the residues allows unambiguous assignment according to the dual selective labeling. SiPex can also decompose signals in time-domain raw data without Fourier transform, even in non-uniformly sampled data without spectral reconstruction. These features of SiPex should expand biological NMR applications by overcoming their overlapping and assignment problems.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related ...complications. Some studies have constructed models to evaluate pregnancy status and predict gestational age using omics data from blood biospecimens; however, less invasive methods are desired. Here we propose a model to predict gestational age, using urinary metabolite information. In our prospective cohort study, we collected 2741 urine samples from 187 healthy pregnant women, 23 patients with hypertensive disorders of pregnancy, and 14 patients with spontaneous preterm birth. Using gas chromatography-tandem mass spectrometry, we identified 184 urinary metabolites that showed dynamic systematic changes in healthy pregnant women according to gestational age. A model to predict gestational age during normal pregnancy progression was constructed; the correlation coefficient between actual and predicted weeks of gestation was 0.86. The predicted gestational ages of cases with hypertensive disorders of pregnancy exhibited significant progression, compared with actual gestational ages. This is the first study to predict gestational age in normal and complicated pregnancies by using urinary metabolite information. Minimally invasive urinary metabolomics might facilitate changes in the prediction of gestational age in various clinical settings.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Chronic kidney disease (CKD) is a syndrome characterized by a gradual loss of kidney function with decreased estimated glomerular filtration rate (eGFR), which may be accompanied by an increase in ...the urine albumin-to-creatinine ratio (UACR). Although trans-ethnic genome-wide association studies (GWASs) have been conducted for kidney-related traits, there have been few analyses in the Japanese population, especially for the UACR trait. In this study, we conducted a GWAS to identify loci related to multiple kidney-related traits in Japanese individuals. First, to detect loci associated with CKD, eGFR, and UACR, we performed separate GWASs with the following two datasets: 475 cases of CKD diagnosed at seven university hospitals and 3471 healthy subjects (dataset 1) and 3664 cases of CKD-suspected individuals with eGFR <60 ml/min/1.73 m
or urinary protein ≥ 1+ and 5952 healthy subjects (dataset 2). Second, we performed a meta-analysis between these two datasets and detected the following associated loci: 10 loci for CKD, 9 loci for eGFR, and 22 loci for UACR. Among the loci detected, 22 have never been reported previously. Half of the significant loci for CKD were shared with those for eGFR, whereas most of the loci associated with UACR were different from those associated with CKD or eGFR. The GWAS of the Japanese population identified novel genetic components that were not previously detected. The results also suggest that the group primarily characterized by increased UACR possessed genetically different features from the group characterized by decreased eGFR.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the ...instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Display omitted
Kidney injury often causes anemia due to a lack of production of the erythroid growth factor erythropoietin (EPO) in the kidneys. Roxadustat is one of the first oral medicines ...inducing EPO production in patients with renal anemia by activating hypoxia-inducible factors (HIFs), which are activators of EPO gene expression. In this study, to develop prodrugs of roxadustat with improved permeability through cell membrane, we investigated the effects of 8 types of esterification on the pharmacokinetics and bioactivity of roxadustat using Hep3B hepatoma cells that HIF-dependently produce EPO. Mass spectrometry of cells incubated with the esterified roxadustat derivatives revealed that the designed compounds were deesterified after being taken up by cells and showed low cytotoxicity compared to the original compound. Esterification prolonged the effective duration of roxadustat with respect to EPO gene induction and HIF activation in cells transiently exposed to the compounds. In the kidneys and livers of mice, both of which are unique sites of EPO production, a majority of the methyl-esterified roxadustat was deesterified within 6 h after drug administration. The deesterified roxadustat derivative was continuously detectable in plasma and urine for at least 48 h after administration, while the administered compound became undetectable 24 h after administration. Additionally, we confirmed that methyl-esterified roxadustat activated erythropoiesis in mice by inducing Epo mRNA expression exclusively in renal interstitial cells, which have intrinsic EPO-producing potential. These data suggest that esterification could lead to the development of roxadustat prodrugs with improvements in cell membrane permeability, effective duration and cytotoxicity.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the ...NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55–59 to 60–64 years being a period of significant metabolic change, particularly in men, and from 45–49 to 50–54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
PDF
