Lipids from microorganisms, and especially lipids from Archaea, are used as taxonomic markers. Unfortunately, knowledge is very limited due to the uncultivability of most Archaea, which greatly reduces the importance of the diversity of lipids and their ecological role. One possible solution is to use lipidomic analysis. Six radioactive sources were investigated, two of which are surface (Wettinquelle and Radonka) and four deep from the Svornost mine (Agricola, Behounek, C1, and Curie). A total of 15 core lipids and 82 intact polar lipids were identified from the membranes of microorganisms in six radioactive springs. Using shotgun lipidomics, typical Archaea lipids were identified in spring water, namely dialkyl glycerol tetraethers, archaeol, hydroxyarchaeol and dihydroxyarchaeol. Diverse groups of polar heads were formed in archaeal IPLs, whose polar heads are formed mainly by hexose, deoxyhexose, and phosphoglycerol. The analysis was performed using shotgun lipidomics and the structure of all molecular species was confirmed by tandem mass spectrometry. After acid hydrolysis, a mixture of polar compounds was obtained from the polar head. Further analysis by GC-MS confirmed that the carbohydrates were glucose and rhamnose. Analysis by HPLC-MS of diastereoisomers of 2-(polyhydroxyalkyl)-3-(O-tolylthiocarbamoyl)thiazolidine-4(R)-carboxylates revealed that both L-rhamnose and D-glucose are present in spring samples only in varying amounts. The glycoside composition depends on the type of spring, that is, Wettinquelle and Radonka springs are basically shallow groundwater, while the samples from the Svornost mine are deep groundwater and do not contain glycosides with rhamnose. This method enables quick screening for characteristic Archaea lipids, allowing decisions on whether to pursue further analyses, such as metagenomic analysis, to directly confirm the presence of Archaea.
BACKGROUND: Tick-borne encephalitis virus (TBEV) is a significant threat to human health. The virus causes potentially fatal disease of the central nervous system (CNS), for which no treatments are available. TBEV infected individuals display a wide spectrum of neuronal disease, the determinants of which are undefined. Changes to host metabolism and virus-induced immunity have been postulated to contribute to the neuronal damage observed in infected individuals. In this study, we evaluated the cytokine, chemokine, and metabolic alterations in the cerebrospinal fluid (CSF) of symptomatic patients infected with TBEV presenting with meningitis or encephalitis. Our aim was to investigate the host immune and metabolic responses associated with specific TBEV infectious outcomes. METHODS: CSF samples of patients with meningitis (n = 27) or encephalitis (n = 25) were obtained upon consent from individuals hospitalised with confirmed TBEV infection in Brno. CSF from uninfected control patients was also collected for comparison (n = 12). A multiplex bead-based system was used to measure the levels of pro-inflammatory cytokines and chemokines. Untargeted metabolomics followed by bioinformatics and integrative omics were used to profile the levels of metabolites in the CSF. Human motor neurons (hMNs) were differentiated from induced pluripotent stem cells (iPSCs) and infected with the highly pathogenic TBEV-Hypr strain to profile the role(s) of identified metabolites during the virus lifecycle. Virus infection was quantified via plaque assay. RESULTS: Significant differences in proinflammatory cytokines (IFN-α2, TSLP, IL-1α, IL-1β, GM-CSF, IL-12p40, IL-15, and IL-18) and chemokines (IL-8, CCL20, and CXCL11) were detected between neurological-TBEV and control patients. A total of 32 CSF metabolites differed in TBE patients with meningitis and encephalitis. CSF S-Adenosylmethionine (SAM), Fructose 1,6-bisphosphate (FBP1) and Phosphoenolpyruvic acid (PEP) levels were 2.4-fold (range ≥ 2.3-≥3.2) higher in encephalitis patients compared to the meningitis group. CSF urocanic acid levels were significantly lower in patients with encephalitis compared to those with meningitis (p = 0.012209). Follow-up analyses showed fluctuations in the levels of O-phosphoethanolamine, succinic acid, and L-proline in the encephalitis group, and pyruvic acid in the meningitis group. TBEV-infection of hMNs increased the production of SAM, FBP1 and PEP in a time-dependent manner. Depletion of the metabolites with characterised pharmacological inhibitors led to a concentration-dependent attenuation of virus growth, validating the identified changes as key mediators of TBEV infection. CONCLUSIONS: Our findings reveal that the neurological disease outcome of TBEV infection is associated with specific and dynamic metabolic signatures in the cerebrospinal fluid. We describe a new in vitro model for in-depth studies of TBEV-induced neuropathogenesis, in which the depletion of identified metabolites limits virus infection. Collectively, this reveals new biomarkers that can differentiate and predict TBEV-associated neurological disease. Additionally, we have identified novel therapeutic targets with the potential to significantly improve patient outcomes and deepen our understanding of TBEV pathogenesis.
- MeSH
- cytokiny mozkomíšní mok MeSH
- dospělí MeSH
- klíšťová encefalitida * mozkomíšní mok metabolismus MeSH
- kultivované buňky MeSH
- lidé středního věku MeSH
- lidé MeSH
- metabolom * fyziologie MeSH
- metabolomika MeSH
- mladý dospělý MeSH
- neurony * metabolismus virologie MeSH
- senioři MeSH
- viry klíšťové encefalitidy * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Východiska: Hledání účinných biomarkerů pro včasnou diagnostiku ovariálního karcinomu (ovarian cancer – OC) patří k naléhavým úkolům moderní onkogynekologie. Metabolické profilování pomocí ultra vysokoúčinné kapalinové chromatografie a hmotnostní spektrometrie (ultraigh performance liquid chromatography and mass spectrometry – UHPLC-MS) poskytuje informace o souhrnu všech nízkomolekulárních metabolitů vzorku biologických tekutin pacienta, které odrážejí procesy probíhající v těle. Cílem studie bylo prozkoumat metabolomický profil krevní plazmy a moči pacientek se serózním ovariálním adenokarcinomem pomocí UHPLC-MS. Materiál a metody: K provedení metabolomické analýzy bylo odebráno 60 vzorků krevní plazmy a 60 vzorků moči pacientek s diagnózou serózního karcinomu vaječníků a 20 vzorků zdravých dobrovolníků. Chromatografická separace byla provedena na chromatografu Vanquish Flex UHPLC System (Thermo Scientific, Německo). Analýza hmotnostní spektrometrií byla provedena na Orbitrap Exploris 480 (Thermo Scientific, Německo) vybaveném elektrosprejovým ionizačním zdrojem. Bioinformatická analýza byla provedena pomocí Compound Discoverer Software (Thermo Fisher Scientific, USA), statistická analýza dat byla provedena v programovacím jazyce Python pomocí knihovny SciPy. Výsledky: Pomocí UHPLC-MS bylo v krevní plazmě identifikováno 1 049 metabolitů různých tříd. U pacientek s OC mělo 8 metabolitů významně nižší koncentraci (p < 0,01) ve srovnání se zdravými dárci, zatímco u 19 látek byly zjištěny vyšší hladiny (p < 0,01). Během metabolomického profilování vzorků moči bylo identifikováno 417 metabolitů: 12 látek mělo významně nižší koncentraci ve srovnání se zjevně zdravými jedinci a u 14 látek byly hladiny vyšší (p < 0,01). U pacientek se serózním adenokarcinomem vaječníků byla zjištěna významná změna v metabolomu krevní plazmy a moči, vyjádřená abnormálními koncentracemi lipidů a jejich derivátů, mastných kyselin a jejich derivátů, acylkarnitinů, fosfolipidů, aminokyselin a jejich derivátů, derivátů dusíkatých bází a steroidů. Mezi nejslibnější markery tohoto onemocnění přitom patří kynurenin, kyselina myristová, lysofosfatidylcholin a L-oktanoylkarnitin. Závěr: Odhalené změny v metabolomu se mohou stát základem pro zlepšení přístupů k diagnostice serózního ovariálního adenokarcinomu.
Background: The search for effective biomarkers for ovarian cancer (OC) early diagnosis is an urgent task of modern oncogynecology. Metabolic profiling by ultra-high performance liquid chromatography and mass spectrometry (UHPLC-MS) provides information on the totality of all low molecular weight metabolites of patient’s biological fluids sample, reflecting the processes occurring in the body. The aim of the study was to research blood plasma and urine metabolomic profile of patients with serous ovarian adenocarcinoma by UHPLC-MS. Material and methods: To perform metabolomic analysis, 60 blood plasma samples and 60 urine samples of patients diagnosed with serous ovarian carcinoma and 20 samples of apparently healthy volunteers were taken. Chromatographic separation was performed on a Vanquish Flex UHPLC System chromatograph (Thermo Scientific, Germany). Mass spectrometric analysis was performed on an Orbitrap Exploris 480 (Thermo Scientific, Germany) equipped with an electrospray ionization source. Bioinformatic analysis was performed using Compound Discoverer Software (Thermo Fisher Scientific, USA), statistical data analysis was performed in the Python programming language using the SciPy library. Results: Using UHPLC-MS, 1,049 metabolites of various classes were identified in blood plasma. In patients with OC, 8 metabolites had a significantly lower concentration (P < 0.01) compared with conditionally healthy donors, while the content of 19 compounds, on the contrary, increased (P < 0.01). During the metabolomic profiling of urine samples, 417 metabolites were identified: 12 compounds had a significantly lower concentration compared to apparently healthy individuals, the content of 14 compounds increased (P < 0.01). In patients with ovary serous adenocarcinoma, a significant change in the metabolome of blood plasma and urine was found, expressed in abnormal concentrations of lipids and their derivatives, fatty acids and their derivatives, acylcarnitines, phospholipids, amino acids and their derivatives, derivatives of nitrogenous bases and steroids. At the same time, kynurenine, myristic acid, lysophosphatidylcholine and L-octanoylcarnitine are the most promising markers of this disease. Conclusion: The revealed changes in the metabolome can become the basis for improving approaches to the diagnosis of serous ovarian adenocarcinoma.
Autism spectrum disorder (ASD) has been associated with disruptions in tryptophan (TRP) metabolism, affecting the production of key neuroactive metabolites. Investigating these metabolic pathways could yield valuable biomarkers for ASD severity and progression. We included 44 children with ASD and 44 healthy children, members of the same family. The average age in the ASD group was 10.7 years, while the average age in the control group was 9.4 years. Urinary tryptophan metabolites were quantified via liquid chromatography-mass spectrometry operating multiple reaction monitoring (MRM). Urinary creatinine was analyzed on an Advia 2400 analyzer using the Jaffe reaction. Statistical comparisons were made between ASD subgroups based on CARS scores. Our findings indicate that children with ASD have higher TRP concentrations (19.94 vs. 16.91; p = 0.04) than their siblings. Kynurenine (KYN) was found at higher levels in children with ASD compared to children in the control group (82.34 vs. 71.20; p = 0.86), although this difference was not statistically significant. The ASD group showed trends of higher KYN/TRP ratios and altered TRP/ indole-3-acetic acid (IAA) and TRP/5-hydroxyindoleacetic acid (5-HIAA) ratios, correlating with symptom severity. Although the numbers of the two groups were different, our findings suggest that mild and severe illnesses involve separate mechanisms. However, further comprehensive studies are needed to validate these ratios as diagnostic tools for ASD.
- MeSH
- biologické markery * moč MeSH
- dítě MeSH
- kynurenin * moč metabolismus MeSH
- kyselina hydroxyindoloctová moč MeSH
- kyseliny indoloctové moč metabolismus MeSH
- lidé MeSH
- metabolom MeSH
- metabolomika * metody MeSH
- mladiství MeSH
- poruchy autistického spektra * moč metabolismus MeSH
- studie případů a kontrol MeSH
- tryptofan * moč metabolismus MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND AND OBJECTIVE: Metabolomic interaction networks provide critical insights into the dynamic relationships between metabolites and their regulatory mechanisms. This study introduces MInfer, a novel computational framework that integrates outputs from MetaboAnalyst, a widely used metabolomic analysis tool, with Jacobian analysis to enhance the derivation and interpretation of these networks. METHODS: MInfer combines the comprehensive data processing capabilities of MetaboAnalyst with the mathematical modeling power of Jacobian analysis. This framework was applied to various metabolomic datasets, employing advanced statistical tests to construct interaction networks and identify key metabolic pathways. RESULTS: The application of MInfer revealed significant metabolic pathways and potential regulatory mechanisms across multiple datasets. The framework demonstrated high precision, sensitivity, and specificity in identifying interactions, enabling robust network interpretations. CONCLUSIONS: MInfer enhances the interpretation of metabolomic data by providing detailed interaction networks and uncovering key regulatory insights. This tool holds significant potential for advancing the study of complex biological systems.
- MeSH
- algoritmy MeSH
- lidé MeSH
- metabolické sítě a dráhy * MeSH
- metabolomika * MeSH
- software MeSH
- výpočetní biologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Kidney dysfunction often leads to neurological impairment, yet the complex kidney-brain relationship remains elusive. We employed spatial and bulk metabolomics to investigate a mouse model of rapid kidney failure induced by mouse double minute 2 (Mdm2) conditional deletion in the kidney tubules to interrogate kidney and brain metabolism. Pathway enrichment analysis of a focused plasma metabolomics panel pinpointed tryptophan metabolism as the most altered pathway with kidney failure. Spatial metabolomics showed toxic tryptophan metabolites in the kidneys and brains, revealing a connection between advanced kidney disease and accelerated kynurenine degradation. In particular, the excitotoxic metabolite quinolinic acid was localized in ependymal cells in the setting of kidney failure. These findings were associated with brain inflammation and cell death. Separate mouse models of ischemia-induced acute kidney injury and adenine-induced chronic kidney disease also exhibited systemic inflammation and accumulating toxic tryptophan metabolites. Patients with advanced chronic kidney disease (stage 3b-4 and stage 5) similarly demonstrated elevated plasma kynurenine metabolites, and quinolinic acid was uniquely correlated with fatigue and reduced quality of life. Overall, our study identifies the kynurenine pathway as a bridge between kidney decline, systemic inflammation, and brain toxicity, offering potential avenues for diagnosis and treatment of neurological issues in kidney disease.
- MeSH
- akutní poškození ledvin metabolismus chemicky indukované patologie MeSH
- chronická renální insuficience metabolismus patologie komplikace MeSH
- kynurenin * metabolismus MeSH
- kyselina chinolinová * toxicita metabolismus krev MeSH
- ledviny metabolismus patologie MeSH
- lidé MeSH
- metabolomika MeSH
- modely nemocí na zvířatech MeSH
- mozek * metabolismus patologie MeSH
- myši MeSH
- tryptofan * metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- myši MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: Insulin-sensitizing drugs, despite their broad use against type 2 diabetes, can adversely affect bone health, and the mechanisms underlying these side effects remain largely unclear. Here, we investigated the different metabolic effects of a series of thiazolidinediones, including rosiglitazone, pioglitazone, and the second-generation compound MSDC-0602K, on human mesenchymal stem cells (MSCs). METHODS: We developed 13C subcellular metabolomic tracer analysis measuring separate mitochondrial and cytosolic metabolite pools, lipidomic network-based isotopologue models, and bioorthogonal click chemistry, to demonstrate that MSDC-0602K differentially affected bone marrow-derived MSCs (BM-MSCs) and adipose tissue-derived MSCs (AT-MSCs). In BM-MSCs, MSDC-0602K promoted osteoblastic differentiation and suppressed adipogenesis. This effect was clearly distinct from that of the earlier drugs and that on AT-MSCs. RESULTS: Fluxomic data reveal unexpected differences between this drug's effect on MSCs and provide mechanistic insight into the pharmacologic inhibition of mitochondrial pyruvate carrier 1 (MPC). Our study demonstrates that MSDC-0602K retains the capacity to inhibit MPC, akin to rosiglitazone but unlike pioglitazone, enabling the utilization of alternative metabolic pathways. Notably, MSDC-0602K exhibits a limited lipogenic potential compared to both rosiglitazone and pioglitazone, each of which employs a distinct lipogenic strategy. CONCLUSIONS: These findings indicate that the new-generation drugs do not compromise bone structure, offering a safer alternative for treating insulin resistance. Moreover, these results highlight the ability of cell compartment-specific metabolite labeling by click reactions and tracer metabolomics analysis of complex lipids to discover molecular mechanisms within the intersection of carbohydrate and lipid metabolism.
- MeSH
- adipogeneze * účinky léků MeSH
- buněčná diferenciace účinky léků MeSH
- hypoglykemika farmakologie MeSH
- kultivované buňky MeSH
- lidé MeSH
- metabolomika MeSH
- mezenchymální kmenové buňky * účinky léků metabolismus MeSH
- osteogeneze * účinky léků MeSH
- pioglitazon farmakologie MeSH
- rosiglitazon farmakologie MeSH
- thiazolidindiony * farmakologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Karcinom prostaty je jedním z nejčastějších onkologických onemocnění mužů ve světě. Diagnostika a stratifikace pacientů jsou klíčové pro zajištění včasné a adekvátní terapie. Současné standardy se opírají převážně o PSA, jehož nádorová specificita je limitována. Tento přehled se zaměřuje na neinvazivní potenciální onkomarkery získané z moči včetně oxidačního stresu, metabolomiky a analýzy nukleových kyselin. V rámci některých studií se ukazuje, že zvýšené hladiny markerů jako F2-isoprostanáza, sarcosin a PCA3 mohou indikovat přítomnost a agresivitu karcinomu prostaty. Nové kombinované testy Prostarix, Mi-Prostate Score, SelectMDX nebo ExoDX nabízejí potenciál pro zlepšení stratifikace pacientů a snížení počtu negativních biopsií. Klinické využití těchto nových markerů je zatím omezené. Vzhledem k heterogenitě tohoto onemocnění je nezbytné pokračovat ve výzkumu, který usnadní personalizovaný přístup v léčbě.
Prostate cancer is one of the most common oncological diseases among men worldwide. Accurate diagnosis and patient stratification are crucial for ensuring timely and appropriate therapy. Current standards primarily rely on PSA, whose tumor specificity is limited. This review focuses on non-invasive potential oncological markers derived from urine, including oxidative stress, metabolomics and nucleic acid analysis. Some studies indicate that elevated levels of markers such as F2-isoprostane, sarcosine or PCA3 may signify the presence and aggressiveness of prostate cancer. New combined tests Prostarix, Mi-Prostate Score, SelectMDX and ExoDX offer potential for improved diagnosis and patient stratification, as well as a reduction in negative biopsies. However, the clinical application of these new markers remains limited. Considering the heterogeneity of this disease, ongoing research is essential to support a personalized approach to treatment.
- MeSH
- aminokyseliny moč MeSH
- biopsie metody MeSH
- časná detekce nádoru metody MeSH
- diagnostické techniky molekulární MeSH
- exozómy fyziologie MeSH
- lidé MeSH
- metabolomika metody MeSH
- mikro RNA moč MeSH
- nádorové biomarkery * moč MeSH
- nádory prostaty * diagnóza MeSH
- oxidační stres fyziologie MeSH
- prostatický specifický antigen krev MeSH
- Check Tag
- lidé MeSH
Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.
- MeSH
- apolipoproteiny E MeSH
- chromatografie kapalinová metody MeSH
- fenotyp MeSH
- kapalinová chromatografie-hmotnostní spektrometrie * MeSH
- lidé MeSH
- lipidomika MeSH
- reprodukovatelnost výsledků MeSH
- tandemová hmotnostní spektrometrie * metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering insights into lipid biology.
- MeSH
- data mining * metody MeSH
- fosfatidylcholiny metabolismus chemie MeSH
- HeLa buňky MeSH
- hmotnostní spektrometrie metody MeSH
- lidé MeSH
- lipidomika * metody MeSH
- lipidy chemie analýza MeSH
- metabolomika metody MeSH
- nenasycené mastné kyseliny metabolismus chemie MeSH
- software MeSH
- tandemová hmotnostní spektrometrie metody MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
