LC-QTOF-MS with MS-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis.

This study presents the development and validation of a liquid chromatography-quadrupole-time-of-flight mass spectrometry method with data-independent acquisition (LC-QTOF-MS) for targeted quantification, post-targeted screening, and untargeted metabolite profiling. Using MS-based precursor ion quantification, the method demonstrated excellent analytical performance with linearity (² > 0.99), accuracy (84 %-131 %), and precision (1 %-17 % relative standard deviation (RSD)).

Perturbations in L-serine metabolism regulate protein quality control through the sensor of the retrograde response pathway RTG2 in Saccharomyces cerevisiae.

Cellular protein homeostasis relies on a complex network of protein synthesis, folding, sub-cellular localization, and degradation to sustain a functional proteome. Since most of these processes are energy-driven, proteostasis is inescapably afflicted by cellular metabolism. Proteostasis collapse and metabolic imbalance are both linked to aging and age-associated disorders, yet they have traditionally been studied as separate phenomena in the context of aging.

Investigation of southern Thailand sweet pickled mango metabolic profiles related to deterioration.

Southern Thailand sweet pickled mango (MBC) is a famous delicacy and economically important for the local communities. This study aimed to elucidate important metabolites related to MBC deterioration at 4 °C (STR4) and 30 °C (STR30). The results show that deterioration of MBCs was linked to increased levels of ethyl acetate, isopropyl alcohol, trans-β-ocimene, isopentyl acetate, 2-phenethyl acetate, glucose, and fructose, along with a decrease in sucrose.

Multi-Pass Arrival Time Correction in Cyclic Ion Mobility Mass Spectrometry for Imaging and Shotgun Lipidomics.

Direct-infusion mass spectrometry (DI-MS) and mass spectrometry imaging (MSI) are powerful techniques for lipidomics research. However, annotating isomeric and isobaric lipids with these methods is challenging due to the absence of chromatographic separation. Recently, cyclic ion mobility mass spectrometry (cIM-MS) has been proposed to overcome this limitation.

Discovery of procyanidin condensed tannins of (-)-epicatechin from Kratom, Mitragyna speciosa, as virucidal agents against SARS-CoV-2.

Kratom, Mitragyna speciosa, is one of the most popular herbs in the West and Southeast Asia. A number of previous works have focused on bioactive alkaloids in this plant; however, non-alkaloids have never been investigated for their biological activities. Antiviral and virucidal assays of a methanol leaf extract of Kratom, M.

Quantifying fecal and plasma short-chain fatty acids in healthy Thai individuals.

Short-chain fatty acids (SCFAs) are involved in important physiological processes such as gut health and immune response, and changes in SCFA levels can be indicative of disease. Despite the importance of SCFAs in human health and disease, reference values for fecal and plasma SCFA concentrations in healthy individuals are scarce. To address this gap in current knowledge, we developed a simple and reliable derivatization-free GC-TOFMS method for quantifying fecal and plasma SCFAs in healthy individuals.

Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples.

The collision cross-sections (CCS) measurement using ion mobility spectrometry (IMS) in combination with mass spectrometry (MS) offers a great opportunity to increase confidence in metabolite identification. However, owing to the lack of sensitivity and resolution, IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites (VLMs ≤ 250 Da). Here, we describe an analytical method using ultrahigh-performance liquid chromatography (UPLC) coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples.

Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0.

In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations.

Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data.

The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (/) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions.

Anti-Xanthine Oxidase 5'-Hydroxyhericenes A-D from the Edible Mushroom and Structure Revision of 3-[2,3-Dihydroxy-4-(hydroxymethyl)tetrahydrofuran-1-yl]-pyridine-4,5-diol.

is an edible mushroom with diverse pharmaceutical applications. Although this mushroom is an attractive source of natural products for cancer treatment, little is known about the bioactive compounds from this mushroom, which may possess antibreast cancer activity. Here, we report the isolation and structure elucidation of new compounds, 5'-hydroxyhericenes A-D () as an inseparable mixture, together with known compounds () from the fruiting body of .

Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids.

Small molecules derived from gut microbiota have been increasingly investigated to better understand the functional roles of the human gut microbiome. Microbial metabolites of aromatic amino acids (AAA) have been linked to many diseases, such as metabolic disorders, chronic kidney diseases, inflammatory bowel disease, diabetes, and cancer. Important microbial AAA metabolites are often discovered via global metabolite profiling of biological specimens collected from humans or animal models.

Prolonged Egg Supplement Advances Growing Child's Growth and Gut Microbiota.

Protein-energy malnutrition still impacts children's growth and development. We investigated the prolonged effects of egg supplementation on growth and microbiota in primary school children. For this study, 8-14-year-old students (51.

Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine.

Cancer progression is linked to gene-environment interactions that alter cellular homeostasis. The use of biomarkers as early indicators of disease manifestation and progression can substantially improve diagnosis and treatment. Large omics datasets generated by high-throughput profiling technologies, such as microarrays, RNA sequencing, whole-genome shotgun sequencing, nuclear magnetic resonance, and mass spectrometry, have enabled data-driven biomarker discoveries.

Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process.

Sweet pickled mango named (MBC), a delicacy from the Southern part of Thailand, has a unique aroma and taste. The employed immersion processes (brining 1, brining 2, and immersion in a hypertonic sugar solution, sequentially) in the MBC production process bring changes to the unripe mango, which indicate the occurrence of metabolic profiles alteration during the production process. This occurrence was never been explored.

Traveling Wave Ion Mobility-Derived Collision Cross Section Database for Plant Specialized Metabolites: An Application to Pierre.

The combination of ion mobility mass spectrometry (IM-MS) and chromatography is a valuable tool for identifying compounds in natural products. In this study, using an ultra-performance liquid chromatography system coupled to a high-resolution quadrupole/traveling wave ion mobility spectrometry/time-of-flight MS (UPLC-TWIMS-QTOF), we have established and validated a comprehensive CCS and MS database for 112 plant specialized metabolites. The database included 15 compounds that were isolated and purified in-house and are not commercially available.

GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure.

Two dimensional GC (GC × GC)-time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage.

CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics.

Two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) provides a large amount of molecular information from biological samples. However, the lack of a comprehensive compound library or customizable bioinformatics tool is currently a challenge in GC × GC-TOFMS data analysis. We present an open-source deep learning (DL) software called contour regions of interest (ROI) identification, simulation and untargeted metabolomics profiler (CRISP).

Predicting lupus membranous nephritis using reduced picolinic acid to tryptophan ratio as a urinary biomarker.

The current gold standard for classifying lupus nephritis (LN) progression is a renal biopsy, which is an invasive procedure. Undergoing a series of biopsies for monitoring disease progression and treatments is unlikely suitable for patients with LN. Thus, there is an urgent need for non-invasive alternative biomarkers that can facilitate LN class diagnosis.

High-Resolution QTOF-MRM for Highly Accurate Identification and Quantification of Trace Levels of Triterpenoids in Mycelium.

The accurate quantification of triterpenoids in mushroom in the mycelium stage is challenging due to their low concentrations, interference from other possible isomers, and the complex matrix. Here, a high-resolution quadrupole-time-of-flight mass spectrometry "multiple reaction monitoring" with target enhancement (HR-QTOF-MRM) method was developed to quantify seven target triterpenoids in . The performance of this method was compared against an optimized QQQ-MRM method.

UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From .

Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis.

Deep metabolome: Applications of deep learning in metabolomics.

In the past few years, deep learning has been successfully applied to various omics data. However, the applications of deep learning in metabolomics are still relatively low compared to others omics. Currently, data pre-processing using convolutional neural network architecture appears to benefit the most from deep learning.