Browsing by Author "Khoomrung S."
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Item Metadata only Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion’s Polarizability and Molecular Mass with Limited Data(2023-01-01) Wisanpitayakorn P.; Sartyoungkul S.; Kurilung A.; Sirivatanauksorn Y.; Visessanguan W.; Sathirapongsasuti N.; Khoomrung S.; Wisanpitayakorn P.; Mahidol UniversityThe 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 (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.Item Metadata only Anti-Xanthine Oxidase 5′-Hydroxyhericenes A-D from the Edible Mushroom Hericium erinaceus and Structure Revision of 3-[2,3-Dihydroxy-4-(hydroxymethyl)tetrahydrofuran-1-yl]-pyridine-4,5-diol(2023-01-01) Thongkongkaew T.; Jariyasopit N.; Khoomrung S.; Siritutsoontorn S.; Jitrapakdee S.; Kittakoop P.; Ruchirawat S.; Mahidol UniversityHericium erinaceus 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 (1-4) as an inseparable mixture, together with known compounds (5-16) from the fruiting body of H. erinaceus. Based on NMR spectroscopic data and MS fragmentation analysis, the structure of a previously reported natural product, 3-[2,3-dihydroxy-4-(hydroxymethyl)tetrahydrofuran-1-yl]-pyridine-4,5-diol (5), should be revised to adenosine (6). Compounds 1-4 inhibit xanthine oxidase activity, while compounds 6, 9, and 10 scavenge reactive oxygen species generated by xanthine oxidase. Moreover, hericerin (13) exhibits strong growth inhibitory activity against T47D breast cancer cells and, to a lesser extent, against MDA-MB-231 breast cancer and MRC-5 normal embryonic cells. Exposure of T47D and MDA-MB-231 cells slightly increased PARP cleavage, suggesting that the growth inhibitory effect of hericerin may be mediated through nonapoptotic pathways. Our results suggest that the bioactive compounds of mushroom H. erinaceus hold promise as antibreast cancer agents.Item Metadata only Antiviral and virucidal activities against SARS-CoV-2 and antibacterial properties of bile acids and their salts with naturally occurring organic cations of l-carnitine, creatinine, and choline(2026-01-01) Varongkriengkrai C.; Chutiwitoonchai N.; Leerach N.; Sureram S.; Pooprasert T.; Aree T.; Khoomrung S.; Mahidol C.; Ruchirawat S.; Kittakoop P.; Varongkriengkrai C.; Mahidol UniversityBile acids have many roles in biological systems, and they have received great attention recently. Bile from a cow, known as gall, together with garlic, wine, and leeks, is used in the traditional medicine recipe of Bald's Leechbook, a thousand-year-old Anglo-Saxon formula for the treatment of infected eyelash follicles. Different aspects of previous works on bile acids have been reported, and this work adds antiviral, virucidal, and antibacterial properties of bile acids and their salts against SARS-CoV-2. Four bile acids, lithocholic acid (LCA, 1), deoxycholic acid (DCA, 5), ursodeoxycholic acid (UDCA, 9), and chenodeoxycholic acid (CDCA, 13), were used to form salts with l-carnitine [X], creatinine [Y], and choline [Z], which are naturally occurring compounds. Bile acids and their salts were evaluated for antiviral and virucidal activities against SARS-CoV-2 as well as for their antibacterial properties. Among the bile acids tested, LCA (1) was found to display virucidal activity against SARS-CoV-2 with an EC50of 9.69 µg mL−1and a selectivity index (SI) of >5.16. However, its salts, [LCA][X] (2), [LCA][Y] (3), and [LCA][Z] (4), were 1.31–3.27 times less active than the bile acid LCA (1), indicating that salt forms of this bile acid did not have improved virucidal activity. Bile acids DCA (5), UDCA (9), and CDCA (13) exhibited antibacterial activity against Gram-positive bacteria (Bacillus cereus, Staphylococcus aureus, Staphylococcus epidermidis, and Enterococcus faecalis) and against a Gram-negative bacterium (Escherichia coli). Cholinium salts of these bile acids exhibited enhanced antibacterial activity; for example, 41.4–41.5% antibacterial improvement was observed for the [DCA][Z] (8) salt when compared with its corresponding bile acid DCA (5). This work provides evidence that certain salts of bile acids have improved antibacterial activity, but they do not enhance antiviral properties.Item Metadata only Characterization of airborne microbial communities in northern Thailand: Impacts of smoke haze versus non-haze conditions(2025-01-01) Yabueng N.; Sansupa C.; Noirungsee N.; Kraisitnitikul P.; Chansuebsri S.; Janta R.; Khoomrung S.; Disayathanoowat T.; Chantara S.; Yabueng N.; Mahidol UniversityData on airborne microorganisms, particularly in Southeast Asia, are more limited compared to chemical data. This study is the first to examine the community and diversity of microorganisms on PM2.5 in an urban area of Northern Thailand during both smoke haze and non-smoke haze periods of 2020. This study evaluated the composition of airborne bacteria and fungi and analyzed their association with the chemical composition of PM2.5 and meteorological variables. Significantly higher concentrations of PM2.5 and more chemical compounds were observed during the smoke haze period compared to the non-smoke haze period. Increased PM2.5 concentrations significantly altered both bacterial and fungal communities. The diversity and richness of airborne bacteria increased, whereas those of fungi decreased. The level of PM2.5 concentration (the carrier), the chemical composition of PM2.5 (the resources for survival), and the local meteorological conditions (relative humidity (RH)) were associated with the differences in bacterial and fungal populations. In addition, air originating from the west of the receptor site, influenced by both terrestrial and marine air mass routes, contributed to higher bacterial diversity and richness during the smoke haze period. In contrast, fungal diversity and richness were greater when the air came from the southwest, following a marine route. However, the primary health concern is pathogens, which were present in both periods (such as Clostridium, Aspergillus, and Cladosporium) and were especially abundant during smoke haze periods. This study highlights those airborne microorganisms, along with the particles and their chemical composition, are important components that can impact health, including that of humans, animals, and the environment.Item Metadata only CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics(2022-03-10) Mathema V.B.; Duangkumpha K.; Wanichthanarak K.; Jariyasopit N.; Dhakal E.; Sathirapongsasuti N.; Kitiyakara C.; Sirivatanauksorn Y.; Khoomrung S.; Mathema V.B.; Mahidol UniversityTwo-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). CRISP integrates multiple customizable deep neural network architectures for assisting the semi-automated identification of ROIs, contour synthesis, resolution enhancement and classification of GC × GC-TOFMS-based contour images. The approach includes the novel aggregate feature representative contour (AFRC) construction and stacked ROIs. This generates an unbiased contour image dataset that enhances the contrasting characteristics between different test groups and can be suitable for small sample sizes. The utility of the generative models and the accuracy and efficacy of the platform were demonstrated using a dataset of GC × GC-TOFMS contour images from patients with late-stage diabetic nephropathy and healthy control groups. CRISP successfully constructed AFRC images and identified over five ROIs to create a deepstacked dataset. The high fidelity, 512 × 512-pixels generative model was trained as a generator with a Fréchet inception distance of <47.00. The trained classifier achieved an AUROC of >0.96 and a classification accuracy of >95.00% for datasets with and without column bleed. Overall, CRISP demonstrates good potential as a DL-based approach for the rapid analysis of 4-D GC × GC-TOFMS untargeted metabolite profiles by directly implementing contour images. CRISP is available at https://github.com/vivekmathema/GCxGC-CRISP.Item Metadata only Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0(2024-01-02) Wanichthanarak K.; In-On A.; Fan S.; Fiehn O.; Wangwiwatsin A.; Khoomrung S.; Wanichthanarak K.; Mahidol UniversityIn 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. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.Item Metadata only Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine(2023-01-01) Mathema V.B.; Sen P.; Lamichhane S.; Orešič M.; Khoomrung S.; Mahidol UniversityCancer 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. The identification of differentially expressed traits as molecular markers has traditionally relied on statistical techniques that are often limited to linear parametric modeling. The heterogeneity, epigenetic changes, and high degree of polymorphism observed in oncogenes demand biomarker-assisted personalized medication schemes. Deep learning (DL), a major subunit of machine learning (ML), has been increasingly utilized in recent years to investigate various diseases. The combination of ML/DL approaches for performance optimization across multi-omics datasets produces robust ensemble-learning prediction models, which are becoming useful in precision medicine. This review focuses on the recent development of ML/DL methods to provide integrative solutions in discovering cancer-related biomarkers, and their utilization in precision medicine.Item Metadata only Discovery of procyanidin condensed tannins of (−)-epicatechin from Kratom, Mitragyna speciosa, as virucidal agents against SARS-CoV-21(2024-07-01) Sureram S.; Chutiwitoonchai N.; Pooprasert T.; Sangsopha W.; Limjiasahapong S.; Jariyasopit N.; Sirivatanauksorn Y.; Khoomrung S.; Mahidol C.; Ruchirawat S.; Kittakoop P.; Sureram S.; Mahidol UniversityKratom, 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. speciosa, revealed that a crude extract displayed virucidal activity against the SARS-CoV-2. Activity-guided isolation of a methanol leaf extract of Kratom led to the identification of B-type procyanidin condensed tannins of (−)-epicatechin as virucidal compounds against SARS-CoV-2. The fraction containing condensed tannins exhibited virucidal activity with an EC50 value of 8.38 μg/mL and a selectivity index (SI) value >23.86. LC-MS/MS analysis and MALDI-TOF MS identified the structure of the virucidal compounds in Kratom as B-type procyanidin condensed tannins, while gel permeation chromatograph (GPC) revealed weight average molecular weight of 238,946 Da for high molecular-weight condensed tannins. In addition to alkaloids, (−)-epicatechin was found as a major component in the leaves of M. speciosa, but it did not have virucidal activity. Macromolecules of (−)-epicatechin, i.e., procyanidin condensed tannins, showed potent virucidal activity against SARS-CoV-2, suggesting that the high molecular weights of these polyphenols are important for virucidal activity.Item Metadata only GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure(2022-10-01) Duangkumpha K.; Jariyasopit N.; Wanichthanarak K.; Dhakal E.; Wisanpitayakorn P.; Thotsiri S.; Sirivatanauksorn Y.; Kitiyakara C.; Sathirapongsasuti N.; Khoomrung S.; Mahidol UniversityTwo 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. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.Item Metadata only Higher Plasma Kynurenine to Tryptophan Correlates with an Increased Incidence of Mild Cognitive Impairment in Treated Metabolic Syndrome Patients(2025-12-30) Jariyasopit N.; Phochmak T.; Manocheewa S.; Wanichthanarak K.; Limjiasahapong S.; Kleebkomut N.; Sirivatanauksorn Y.; Sirivatanauksorn V.; Phrommintikul A.; Chattipakorn N.; Chattipakorn S.; Khoomrung S.; Jariyasopit N.; Mahidol UniversityAn increase in cognitive impairment was observed in metabolic syndrome (MetS) patients. Although alterations in metabolomic profiles have been identified as potential plasma/serum biomarkers of mild cognitive impairment (MCI) and MetS, findings remain inconsistent─probably due to the heterogeneity among MetS patients and the lack of subsequent validation using targeted analysis after the initial untargeted analysis. In this study, we validated mass spectrometry-based quantitation methods and quantified amino acids, fatty acids, and tryptophan metabolites in the kynurenine pathway in the plasma of 95 treated MetS patients with and without MCI assessed by the Montreal Cognitive Assessment. We found that MCI was positively associated with the kynurenine-to-tryptophan ratio (KTR) after the adjustment for age, gender, and BMI, as well as negatively associated with C20:3 [all-Z-8,11,14] and lysine. A one-unit increase in KTR resulted in an increased probability of developing MCI by 371%. In contrast, one-unit increases in C20:3 and lysine were associated with decreased odds of developing MCI by 81 and 78%, respectively. Our finding underscores prominent neuroinflammation, beyond normal aging, in MetS patients, even under ongoing clinical treatment. It also points to the potential of KTR as a risk marker for MCI, offering a valuable complement to the existing cognitive assessments that may be influenced by the educational background. In addition, the validated metabolite data serve as an invaluable resource for future research. They can facilitate comparisons across different studies, contribute to large-scale analyses, and be used in machine learning models for discovering and validating new biomarkers.Item Metadata only Influence of Prolonged Whole Egg Supplementation on Insulin-like Growth Factor 1 and Short-Chain Fatty Acids Product: Implications for Human Health and Gut Microbiota(2023-11-16) Suta S.; Ophakas S.; Manosan T.; Honwichit O.; Charoensiddhi S.; Surawit A.; Pongkunakorn T.; Pumeiam S.; Mongkolsucharitkul P.; Pinsawas B.; Sutheeworapong S.; Puangsombat P.; Khoomrung S.; Mayurasakorn K.; Mahidol UniversityThe gut microbiota exert a profound influence on human health and metabolism, with microbial metabolites playing a pivotal role in shaping host physiology. This study investigated the impact of prolonged egg supplementation on insulin-like growth factor 1 (IGF-1) and circulating short-chain fatty acids (SCFAs). In a subset of a cluster-randomized trial, participants aged 8-14 years were randomly assigned into three groups: (1) Whole Egg (WE)-consuming 10 additional eggs per week [n = 24], (2) Protein Substitute (PS)-consuming yolk-free egg substitute equivalent to 10 eggs per week [n = 25], and (3) Control Group (C) [n = 26]. At week 35, IGF-1 levels in WE significantly increased (66.6 ± 27.7 ng/mL, p < 0.05) compared to C, with positive SCFA correlations, except acetate. Acetate was stable in WE, increasing in PS and C. Significant propionate differences occurred between WE and PS (14.8 ± 5.6 μmol/L, p = 0.010). WE exhibited notable changes in the relative abundance of the Bifidobacterium and Prevotella genera. Strong positive SCFA correlations were observed with MAT-CR-H4-C10 and Libanicoccus, while Roseburia, Terrisporobacter, Clostridia_UCG-014, and Coprococcus showed negative correlations. In conclusion, whole egg supplementation improves growth factors that may be related to bone formation and growth; it may also promote benefits to gut microbiota but may not affect SCFAs.Item Metadata only Investigation of southern Thailand sweet pickled mango metabolic profiles related to deterioration(2025-06-30) Indrati N.; Phonsatta N.; Poungsombat P.; Khoomrung S.; Panya A.; Sumpavapol P.; Indrati N.; Mahidol UniversitySouthern 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. Moreover, isopentyl acetate, ethyl acetate, and 2-phenethyl acetate were significantly higher in STR4 compared to STR30 with log 2[fold change (FC)] 3.2, 2.0, and 1.0, respectively. Meanwhile, STR4 had a lower sucrose level (log [FC] -1.4) than STR30. It was postulated that a longer storage time of STR4 than STR30 affects sucrose hydrolysis. Due to the abundance of volatile metabolites in deteriorated MBC, applying odor/flavor absorber film on MBC packaging might help prolong its shelf life.Item Metadata only LC-MS/MS identifies elevated imidazole propionate and gut-derived metabolite alterations in peritoneal dialysis patients(2025-01-01) Manokasemsan W.; Jariyasopit N.; Wanichthanarak K.; Poungsombat P.; Kurilung A.; Limjiasahapong S.; Thapa K.; Sirivatanauksorn Y.; Raksasuk S.; Srithongkul T.; Kitiyakara C.; Khoomrung S.; Manokasemsan W.; Mahidol UniversityWe developed a robust LC–MS/MS method for the simultaneous quantification of 16 uremic toxins (UTs) and 14 bile acids (BAs) in plasma and fecal samples within a single method. The method demonstrated high sensitivity, broad metabolite coverage, and excellent accuracy, precision, and throughput. Using this platform, targeted metabolites were quantified in peritoneal dialysis (PD) patients (n = 31) and healthy controls (HC; n = 60). Of the 30 targeted metabolites included in the validation method, 20 were detected in fecal samples and 12 in plasma in this study. Fecal samples exhibited greater BA diversity, whereas UTs were evenly distributed across both matrices. Fecal profiles showed minimal differences between PD and HC, suggesting limited gut-level alteration. In contrast, plasma analysis revealed nine metabolites significantly elevated in PD, including indoxyl sulfate, phenyl sulfate, hippuric acid, and imidazole propionate (ImP), lithocholic acid, cinnamoylglycine, m-hydroxyhippuric acid, phenylacetylglutamine, and phenylacetylglycine. Notably, plasma ImP—an underexplored metabolite—was elevated independently of diabetes or cardiovascular disease, implicating impaired renal clearance as its primary driver. These results highlight the systemic impact of gut-derived metabolites in kidney failure and position targeted UT–BA profiling as a powerful complementary tool for clinical metabolomics in chronic kidney disease and PD.Item Metadata only LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis(2025-01-01) Kurilung A.; Limjiasahapong S.; Wanichthanarak K.; Manokasemsan W.; Kaewnarin K.; Duangkumpha K.; Manocheewa S.; Tansawat R.; Chaiteerakij R.; Nookaew I.; Sirivatanauksorn Y.; Khoomrung S.; Kurilung A.; Mahidol UniversityThis study presents the development and validation of a liquid chromatography–quadrupole-time-of-flight mass spectrometry method with data-independent acquisition (LC-QTOF-MSE) for targeted quantification, post-targeted screening, and untargeted metabolite profiling. Using MS1-based precursor ion quantification, the method demonstrated excellent analytical performance with linearity (R² > 0.99), accuracy (84 %–131 %), and precision (1 %–17 % relative standard deviation (RSD)). Although LC-QTOF‑MSE sensitivity is at least nine-fold lower than LC-triple quadrupole MS with multiple reaction monitoring, it remains adequate for quantifying urinary metabolites, particularly those that fragment poorly or yield low‑intensity product ions. For post‑targeted screening and untargeted profiling, an in‑house reference library (the Siriraj Metabolomics Data Warehouse, SiMD), comprising 174 curated metabolite standards, was integrated into the workflow to enhance metabolite identification confidence. The official website for SiMD can be accessed at https://si-simd.com/. To demonstrate the method's utility, 11 amino and organic acids were quantified in urine samples from 100 healthy individuals. Four compounds—L-methionine, L-histidine, L-tryptophan, and trans-ferulic acid—were significantly higher levels in females (P < 0.05), likely reflecting sex-specific physiological or dietary intake differences. Post‑targeted screening identified 29 additional metabolites and assigned them to level 1 (m/z, RT, isotope pattern, and MS/MS spectra matched to reference standards) based on the Metabolomics Standards Initiative guidelines. Untargeted retrospective profiling revealed level 1 seven metabolites, including ribitol, creatine, glucuronic acid, trans-ferulic acid, succinic acid, dimethylglycine, and 3-hydroxyphenylacetic acid related to sex variation (VIP > 1.5). In summary, the LC-QTOF-MSE method coupled with SiMD provides a robust and comprehensive workflow for metabolomics analysis. It enables reliable target quantification and enhances confidence in metabolite identification while also reducing sample and instrumental demands. These features make it particularly well-suited for clinical metabolomics studies.Item Metadata only Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples(2024-05-01) Kurilung A.; Limjiasahapong S.; Kaewnarin K.; Wisanpitayakorn P.; Jariyasopit N.; Wanichthanarak K.; Sartyoungkul S.; Wong S.C.C.; Sathirapongsasuti N.; Kitiyakara C.; Sirivatanauksorn Y.; Khoomrung S.; Kurilung A.; Mahidol UniversityThe 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. The experimental CCS values, along with mass spectral properties, were reported for the 174 metabolites. The experimental data included the mass-to-charge ratio (m/z), retention time (RT), tandem MS (MS/MS) spectra, and CCS values. Among the studied metabolites, 263 traveling wave ion mobility spectrometry (TWIMS)-derived CCS values (TWCCSN2) were reported for the first time, and more than 70% of these were CCS values of VLMs. The TWCCSN2 values were highly repeatable, with inter-day variations of <1% relative standard deviation (RSD). The developed method revealed excellent TWCCSN2 accuracy with a CCS difference (ΔCCS) within ±2% of the reported drift tube IMS (DTIMS) and TWIMS CCS values. The complexity of the urine matrix did not affect the precision of the method, as evidenced by ΔCCS within ±1.92%. According to the Metabolomics Standards Initiative, 55 urinary metabolites were identified with a confidence level of 1. Among these 55 metabolites, 53 (96%) were VLMs. The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values, which clearly increased metabolite identification confidence.Item Metadata only Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process(2022-09-08) Indrati N.; Phonsatta N.; Poungsombat P.; Khoomrung S.; Sumpavapol P.; Panya A.; Mahidol UniversitySweet pickled mango named Ma-Muang Bao Chae-Im (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. Thus, this study investigated metabolic profile alteration during the MBC production process. The untargeted metabolomics profiling method was used to reveal the changes in volatile and non-volatile metabolites. Headspace solid-phase micro-extraction tandem with gas chromatography quadrupole time of flight (GC/QTOF) was employed for the volatile analysis, while metabolites derivatization for non-volatile analysis. In conclusion, a total of 82 volatile and 41 non-volatile metabolites were identified during the production process. Terpenes, terpenoids, several non-volatile organic acids, and sugars were the major mango metabolites that presented throughout the process. Gamma-aminobutyric acid (GABA) was only observed during the brining processes, which suggested the microorganism’s stress response mechanism to an acidic environment and high chloride ions in brine. Esters and alcohols were abundant during the last immersion process, which had an important role in MBC flavor characteristics. The knowledge of metabolites development during the MBC production process would be beneficial for product development and optimization.Item Metadata only Multi-Pass Arrival Time Correction in Cyclic Ion Mobility Mass Spectrometry for Imaging and Shotgun Lipidomics(2024-01-01) Wisanpitayakorn P.; Jariyasopit N.; Duangkumpha K.; Goh J.X.; Palmer M.E.; Sirivatanauksorn Y.; Khoomrung S.; Wisanpitayakorn P.; Mahidol UniversityDirect-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. However, fluctuations in room conditions can affect ion mobility multipass arrival times, potentially reducing annotation confidence. In this study, we developed a multipass arrival time correction method that proved effective across various dates, room temperatures, ion mobility settings, and laboratories using mixtures of reference standards. We observed slight variations in the linear correction lines between lipid and nonlipid molecules, underscoring the importance of choosing appropriate reference molecules. Based on these results, we demonstrated that an accurate multipass arrival time database can be constructed from corrected t0 and tp for interlaboratory use and can effectively identify isomeric lipids in MSI using only a single measurement. This approach significantly simplifies the identification process compared to determining multipass collision cross-section, which requires multiple measurements that are both sample- and time-intensive for MSI. Additionally, we validated our multipass drift time correction method in shotgun lipidomics analyses of human and mouse serum samples and observed no matrix effect for the analysis. Despite variations in dates, room temperatures, instruments, and ion mobility settings, our approach reduced the mean drift time differences from over 2% to below 0.2%.Item Metadata only Perturbations in L-serine metabolism regulate protein quality control through the sensor of the retrograde response pathway RTG2 in Saccharomyces cerevisiae(2025-07-01) Saxena K.; Andersson R.; Widlund P.O.; Khoomrung S.; Hanzén S.; Nielsen J.; Kumar N.; Molin M.; Nyström T.; Saxena K.; Mahidol UniversityCellular 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. In this study, we indicate that reduced proteostasis capacity is a result of a metabolic imbalance associated with age. We observed increased accumulation of L-serine and L-threonine in replicative old cells of Saccharomyces cerevisiae, indicating an imbalance in amino acid metabolism with replicative aging. Replicating this metabolic imbalance in young cells through deletion of serine-dependent transcriptional activator, CHA4, resulted in increased aggregation of endogenous proteins along with misfolding-prone proteins Guk1-7ts-GFP and Luciferase-GFP in both young and old cells. Aggregate formation in the cha4Δ strain required a functional sensor of mitochondrial dysfunction and an activator of the retrograde signaling gene, RTG2. CHA4 and RTG2 exhibited genetic interaction and together regulated mitochondrial metabolism, replicative lifespan, and aggregate formation in young cells, connecting metabolic regulation with proteostasis and aging. Constitutive activation of retrograde signaling through overexpression of RTG2 or deletion of MKS-1, a negative regulator of Rtg1-Rtg3 nuclear translocation, resulted in faster resolution of aggregates upon heat shock through RTG3 and was found to be independent of molecular chaperone upregulation.Item Metadata only Plasma metabolomic analysis in Thai EGFR-mutated non-small cell lung cancer patients(2025-01-01) Thamlikitkul L.; Wanichthanarak K.; Manocheewa S.; Limjiasahapong S.; Phonsatta N.; Thangvichien S.; Panya A.; Sirivatanauksorn Y.; Poungvarin N.; Khoomrung S.; Thamlikitkul L.; Mahidol UniversityLung cancer remains the leading cause of cancer-related mortality worldwide, underscoring the urgent need for non-invasive approaches to improve diagnosis, patient stratification, and therapeutic monitoring. Metabolic reprogramming driven by oncogenic alterations—particularly Epidermal Growth Factor Receptor (EGFR) mutations in non-small cell lung cancer (NSCLC)—creates distinctive plasma signatures with clinical relevance. In this study, plasma metabolomic profiling revealed that amino acid and sugar metabolism exhibited the strongest discriminatory patterns. NSCLC patients consistently showed elevated glycine and reduced tryptophan and inositol compared with healthy controls. Distinct amino acid and organic acid shifts further differentiated EGFR-mutated from wild-type NSCLC, while alterations in tryptophan, valine, and oxalic acid characterized patients with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs). These findings underscore biologically relevant metabolic alterations associated with EGFR mutation and TKI resistance, supporting the potential of plasma metabolite profiles as minimally invasive indicators for molecular classification and treatment response in NSCLC.Item Metadata only Prolonged Egg Supplement Advances Growing Child’s Growth and Gut Microbiota(2023-03-01) Suta S.; Surawit A.; Mongkolsucharitkul P.; Pinsawas B.; Manosan T.; Ophakas S.; Pongkunakorn T.; Pumeiam S.; Sranacharoenpong K.; Sutheeworapong S.; Poungsombat P.; Khoomrung S.; Akarasereenont P.; Thaipisuttikul I.; Suktitipat B.; Mayurasakorn K.; Mahidol UniversityProtein-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 (51.5% F) in six rural schools in Thailand were randomly assigned into three groups: (1) whole egg (WE), consuming 10 additional eggs/week (n = 238) (n = 238); (2) protein substitute (PS), consuming yolk-free egg substitutes equivalent to 10 eggs/week (n = 200); and (3) control group (C, (n = 197)). The outcomes were measured at week 0, 14, and 35. At the baseline, 17% of the students were underweight, 18% were stunted, and 13% were wasted. At week 35, compared to the C group the weight and height difference increased significantly in the WE group (3.6 ± 23.5 kg, p < 0.001; 5.1 ± 23.2 cm, p < 0.001). No significant differences in weight or height were observed between the PS and C groups. Significant decreases in atherogenic lipoproteins were observed in the WE, but not in PS group. HDL-cholesterol tended to increase in the WE group (0.02 ± 0.59 mmol/L, ns). The bacterial diversity was similar among the groups. The relative abundance of Bifidobacterium increased by 1.28-fold in the WE group compared to the baseline and differential abundance analysis which indicated that Lachnospira increased and Varibaculum decreased significantly. In conclusion, prolonged whole egg supplementation is an effective intervention to improve growth, nutritional biomarkers, and gut microbiota with unaltered adverse effects on blood lipoproteins.