Mass spectrometry for high-throughput metabolomics analysis of urine

Direct electrospray ionisation-mass spectrometry (direct ESI-MS), by omitting the chromatographic step, has great potential for application as a high-throughput approach for untargeted urine metabolomics analysis compared to liquid chromatography-mass spectrometry (LC-MS). The rapid development and technical innovations revealed in the field of ambient ionisation MS such as nanoelectrospray ionisation (nanoESI) chip-based infusion and liquid extraction surface analysis mass spectrometry (LESA-MS) suggest that they might be suitable for high-throughput metabolomics analysis. In this thesis, LC-MS and high-throughput direct ESI-MS methods using high resolution orbital trap mass spectrometer were developed and validated for untargeted metabolomics of human urine. Three different direct ESI-MS techniques were explored and compared with LC-MS: flow injection electrospray ionisation-MS (FIE-MS), chip-based infusion and LESA-MS of dried urine spots on a cell culture slide. A high-throughput sample preparation protocol was optimised using in-house artificial urine. Urine samples after consumption of green tea and healthy controls were used as a model to explore the performance and classification ability of the direct ESI-MS. High-throughput data pre-processing and multivariate analysis protocols were established for each method. The developed methods were finally applied for the analysis of clinical urine samples for biomarker discovery and to investigate the metabolic changes in osteoarthritis and malaria. Also, the methods were applied to study the effect of oligofructose diet on the gut microbial community of healthy subjects. The analytical performance of the methods for urine metabolomics was validated using quality control (QC) and principal component analysis (PCA) approaches. Rigorous validation including cross-validation, permutation test, prediction models and area under receiver operating characteristic (ROC) curve (AUC) was performed across the generated datasets using the developed methods. Analysis of green tea urine samples generated 4128, 748, 1064 and 1035 ions from LC-MS, FIE-MS, chip-based infusion and LESA-MS analysis, respectively. A selected set of known green tea metabolites in urine were used to evaluate each method for detection sensitivity. 15 metabolites were found with LC-MS compared to 8, 5 and 6 with FIE-MS, chip-based infusion and LESA, respectively. The developed methods successfully differentiated between the metabolic profiles of osteoarthritis active patients and healthy controls (Q2 0.465 (LC-MS), 0.562 (FIE-MS), 0.472 (chip-based infusion) and 0.493 (LESA-MS)). The altered level of metabolites detected in osteoarthritis patients showed a perturbed activity in TCA cycle, pyruvate metabolism, -oxidation pathway, amino acids and glycerophospholipids metabolism, which may provide evidence of mitochondrial dysfunction, inflammation, oxidative stress, collagen destruction and use of lipolysis as an alternative energy source in the cartilage cells of osteoarthritis patients. FIE-MS, chip-based infusion and LESA-MS increased the analysis throughput and yet they were able to provide 33%, 44% and 44%, respectively, of the LC-MS information, indicating their great potential for diagnostic application in osteoarthritis. Malaria samples datasets generated 9,744 and 576 ions from LC-MS and FIE-MS, respectively. Supervised multivariate analysis using OPLS-DA showed clear separation and clustering of malaria patients from controls in both LC-MS and FIE-MS methods. Cross-validation R2Y and Q2 values obtained by FIE-MS were 0.810 and 0.538, respectively, which are comparable to the values of 0.993 and 0.583 achieved by LC-MS. The sensitivity and specificity were 80% and 77% for LC-MS and FIE-MS, respectively, indicating valid, reliable and comparable results of both methods. With regards to biomarker discovery, altered level of 30 and 17 metabolites were found by LC-MS and FIE-MS, respectively, in the urine of malaria patients compared to healthy controls. Among these metabolites, pipecolic acid, taurine, 1,3-diacetylpropane, N-acetylspermidine and N-acetylputrescine may have the potential of being used as biomarkers of malaria. LC-MS and FIE-MS were able to separate urine samples of healthy subjects on oligofructose diet from controls (specificity/sensitivity 80%/88% (LC-MS) and 71%/64% (FIE-MS)). An altered level of short chain fatty acids (SCFAs), fatty acids and amino acids were observed in urine as a result of oligofructose intake, suggesting an increased population of the health-promoting Bifidobacterium and a decreased Lactobacillus and Enterococcus genera in the colon. In conclusion, the developed direct ESI-MS methods demonstrated the ability to differentiate between inherent types of urine samples in disease and health state. Therefore they are recommended to be used as fast diagnostic tools for clinical urine samples. The developed LC-MS method is necessary when comprehensive biomarker screening is required

Mass spectrometry for high-throughput metabolomics analysis of urine

Direct electrospray ionisation-mass spectrometry (direct ESI-MS), by omitting the chromatographic step, has great potential for application as a high-throughput approach for untargeted urine metabolomics analysis compared to liquid chromatography-mass spectrometry (LC-MS). The rapid development and technical innovations revealed in the field of ambient ionisation MS such as nanoelectrospray ionisation (nanoESI) chip-based infusion and liquid extraction surface analysis mass spectrometry (LESA-MS) suggest that they might be suitable for high-throughput metabolomics analysis. In this thesis, LC-MS and high-throughput direct ESI-MS methods using high resolution orbital trap mass spectrometer were developed and validated for untargeted metabolomics of human urine. Three different direct ESI-MS techniques were explored and compared with LC-MS: flow injection electrospray ionisation-MS (FIE-MS), chip-based infusion and LESA-MS of dried urine spots on a cell culture slide. A high-throughput sample preparation protocol was optimised using in-house artificial urine. Urine samples after consumption of green tea and healthy controls were used as a model to explore the performance and classification ability of the direct ESI-MS. High-throughput data pre-processing and multivariate analysis protocols were established for each method. The developed methods were finally applied for the analysis of clinical urine samples for biomarker discovery and to investigate the metabolic changes in osteoarthritis and malaria. Also, the methods were applied to study the effect of oligofructose diet on the gut microbial community of healthy subjects. The analytical performance of the methods for urine metabolomics was validated using quality control (QC) and principal component analysis (PCA) approaches. Rigorous validation including cross-validation, permutation test, prediction models and area under receiver operating characteristic (ROC) curve (AUC) was performed across the generated datasets using the developed methods. Analysis of green tea urine samples generated 4128, 748, 1064 and 1035 ions from LC-MS, FIE-MS, chip-based infusion and LESA-MS analysis, respectively. A selected set of known green tea metabolites in urine were used to evaluate each method for detection sensitivity. 15 metabolites were found with LC-MS compared to 8, 5 and 6 with FIE-MS, chip-based infusion and LESA, respectively. The developed methods successfully differentiated between the metabolic profiles of osteoarthritis active patients and healthy controls (Q2 0.465 (LC-MS), 0.562 (FIE-MS), 0.472 (chip-based infusion) and 0.493 (LESA-MS)). The altered level of metabolites detected in osteoarthritis patients showed a perturbed activity in TCA cycle, pyruvate metabolism, -oxidation pathway, amino acids and glycerophospholipids metabolism, which may provide evidence of mitochondrial dysfunction, inflammation, oxidative stress, collagen destruction and use of lipolysis as an alternative energy source in the cartilage cells of osteoarthritis patients. FIE-MS, chip-based infusion and LESA-MS increased the analysis throughput and yet they were able to provide 33%, 44% and 44%, respectively, of the LC-MS information, indicating their great potential for diagnostic application in osteoarthritis. Malaria samples datasets generated 9,744 and 576 ions from LC-MS and FIE-MS, respectively. Supervised multivariate analysis using OPLS-DA showed clear separation and clustering of malaria patients from controls in both LC-MS and FIE-MS methods. Cross-validation R2Y and Q2 values obtained by FIE-MS were 0.810 and 0.538, respectively, which are comparable to the values of 0.993 and 0.583 achieved by LC-MS. The sensitivity and specificity were 80% and 77% for LC-MS and FIE-MS, respectively, indicating valid, reliable and comparable results of both methods. With regards to biomarker discovery, altered level of 30 and 17 metabolites were found by LC-MS and FIE-MS, respectively, in the urine of malaria patients compared to healthy controls. Among these metabolites, pipecolic acid, taurine, 1,3-diacetylpropane, N-acetylspermidine and N-acetylputrescine may have the potential of being used as biomarkers of malaria. LC-MS and FIE-MS were able to separate urine samples of healthy subjects on oligofructose diet from controls (specificity/sensitivity 80%/88% (LC-MS) and 71%/64% (FIE-MS)). An altered level of short chain fatty acids (SCFAs), fatty acids and amino acids were observed in urine as a result of oligofructose intake, suggesting an increased population of the health-promoting Bifidobacterium and a decreased Lactobacillus and Enterococcus genera in the colon. In conclusion, the developed direct ESI-MS methods demonstrated the ability to differentiate between inherent types of urine samples in disease and health state. Therefore they are recommended to be used as fast diagnostic tools for clinical urine samples. The developed LC-MS method is necessary when comprehensive biomarker screening is required

Sustained adenosine release:Revealing its impact on osteogenic signalling pathways of human mesenchymal stromal cells

Non-healing fractures, a global health concern arising from trauma, osteoporosis, and tumours, can lead to severe disabilities. Adenosine, integral to cellular energy metabolism, gains prominence in bone regeneration via adenosine A2B receptor activation. This study introduces a controlled-release system for localized adenosine delivery, fostering human mesenchymal stromal cell (hMSC) differentiation into functional bone cells. The study investigates how the ratio of lactic acid to glycolic acid in microparticles can influence adenosine release and explores the downstream effects on gene expression and metabolic profiles of osteogenic differentiation in hMSCs cultured in growth and osteoinductive media. Insights into adenosine-modulated signalling pathways during MSC differentiation, with osteogenic factors, provide a comprehensive understanding of the pathways involved. Analysing gene expression and metabolic profiles unravels adenosine's regulatory mechanisms in MSC differentiation. Sustained adenosine release from microparticles induces mineralization, synergizing with osteogenic media supplements, showcasing the potential of adenosine for treating critical bone defects and metabolic disorders. This study highlights the efficacy of a polymeric microparticle-based delivery system, offering novel strategies for bone repair. Unveiling adenosine's roles and associated signalling pathways advances our comprehension of molecular mechanisms steering bone regeneration, propelling innovative biomaterial, combined with metabolites, approaches for clinical use

Metabolic characterisation of Magnetospirillum gryphiswaldense MSR-1 using LC-MS-based metabolite profiling

Magnetosomes are nano-sized magnetic nanoparticles with exquisite properties that can be used in a wide range of healthcare and biotechnological applications. They are biosynthesised by magnetotactic bacteria (MTB), such as Magnetospirillum gryphiswaldense MSR-1 (Mgryph). However, magnetosome bioprocessing yields low quantities compared to chemical synthesis of magnetic nanoparticles. Therefore, an understanding of the intracellular metabolites and metabolic networks related to Mgryph growth and magnetosome formation are vital to unlock the potential of this organism to develop improved bioprocesses. In this work, we investigated the metabolism of Mgryph using untargeted metabolomics. Liquid chromatography-mass spectrometry (LC-MS) was performed to profile spent medium samples of Mgryph cells grown under O2-limited (n ¼ 6) and O2-rich conditions (n = 6) corresponding to magnetosome- and non-magnetosome producing cells, respectively. Multivariate, univariate and pathway enrichment analyses were conducted to identify significantly altered metabolites and pathways. Rigorous metabolite identification was carried out using authentic standards, the Mgryph-specific metabolite database and MS/MS mzCloud database. PCA and OPLS-DA showed clear separation and clustering of sample groups with cross-validation values of R2X ¼ 0.76, R2Y ¼ 0.99 and Q2 ¼ 0.98 in OPLS-DA. As a result, 50 metabolites linked to 45 metabolic pathways were found to be significantly altered in the tested conditions, including: glycine, serine and threonine; butanoate; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis and; pyruvate and citric acid cycle (TCA) metabolisms. Our findings demonstrate the potential of LC-MS to characterise key metabolites in Mgryph and will contribute to further understanding the metabolic mechanisms that affect Mgryph growth and magnetosome formation

Sustained adenosine release:Revealing its impact on osteogenic signalling pathways of human mesenchymal stromal cells

Non-healing fractures, a global health concern arising from trauma, osteoporosis, and tumours, can lead to severe disabilities. Adenosine, integral to cellular energy metabolism, gains prominence in bone regeneration via adenosine A2B receptor activation. This study introduces a controlled-release system for localized adenosine delivery, fostering human mesenchymal stromal cell (hMSC) differentiation into functional bone cells. The study investigates how the ratio of lactic acid to glycolic acid in microparticles can influence adenosine release and explores the downstream effects on gene expression and metabolic profiles of osteogenic differentiation in hMSCs cultured in growth and osteoinductive media. Insights into adenosine-modulated signalling pathways during MSC differentiation, with osteogenic factors, provide a comprehensive understanding of the pathways involved. Analysing gene expression and metabolic profiles unravels adenosine's regulatory mechanisms in MSC differentiation. Sustained adenosine release from microparticles induces mineralization, synergizing with osteogenic media supplements, showcasing the potential of adenosine for treating critical bone defects and metabolic disorders. This study highlights the efficacy of a polymeric microparticle-based delivery system, offering novel strategies for bone repair. Unveiling adenosine's roles and associated signalling pathways advances our comprehension of molecular mechanisms steering bone regeneration, propelling innovative biomaterial, combined with metabolites, approaches for clinical use

Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry

Introduction: Osteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA. Objectives: To investigate possible surrogate biomarkers of knee OA in urine using metabolomics to contribute towards a better understanding of OA progression and possible targeted treatment. Method: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) was applied in a case–control approach to explore the possible metabolic differences between the urinary profiles of symptomatic knee OA patients (n = 74) (subclassified into inflammatory OA, n = 22 and non-inflammatory OA, n = 52) and non-OA controls (n = 68). Univariate, multivariate and pathway analyses were performed with a rigorous validation including cross-validation, permutation test, prediction and receiver operating characteristic curve to identify significantly altered metabolites and pathways in OA. Results: OA datasets generated 7405 variables and multivariate analysis showed clear separation of inflammatory OA, but not non-inflammatory OA, from non-OA controls. Adequate cross-validation (R2Y = 0.874, Q2 = 0.465) was obtained. The prediction model and the ROC curve showed satisfactory results with a sensitivity of 88%, specificity of 71% and accuracy of 77%. 26 metabolites were identified as potential biomarkers of inflammatory OA using HMDB, authentic standards and/or MS/MS database. Conclusion: Urinary metabolic profiles were altered in inflammatory knee OA subjects compared to those with non-inflammatory OA and non-OA controls. These altered profiles associated with perturbed activity of the TCA cycle, pyruvate and amino acid metabolism linked to inflammation, oxidative stress and collagen destruction. Of note, 2-keto-glutaramic acid level was > eightfold higher in the inflammatory OA patients compared to non-OA control, signalling a possible perturbation in glutamine metabolism related to OA progression

Metabolic Signatures of Surface-Modified Poly(lactic- co-glycolic acid) Nanoparticles in Differentiated THP-1 Cells Derived with Liquid Chromatography-Mass Spectrometry-based Metabolomics

Polymeric nanoparticles (NPs) are widely used in preclinical drug delivery investigations, and some formulations are now in the clinic. However, the detailed effects of many NPs at the subcellular level have not been fully investigated. In this study, we used differentiated THP-1 macrophage cells, as a model, to investigate the metabolic changes associated with the use of poly (lactic-co-glycolic acid) (PLGA) NPs with different surface coating or conjugation chemistries. Liquid chromatography-mass spectrometry-based metabolic profiling was performed on the extracts (n = 6) of the differentiated THP-1 cells treated with plain, Pluronic (F-127, F-68, and P-85)-coated and PEG-PLGA NPs and control (no treatment). Principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA) in conjunction with univariate and pathway analyses were performed to identify significantly changed metabolites and pathways related to exposure of the cells to NPs. OPLS-DA of each class in the study compared to the control showed clear separation and clustering with cross-validation values of R2 and Q2 > 0.5. A total of 105 metabolites and lipids were found to be significantly altered in the differentiated THP-1 cell profiles due to the NP exposure, whereas more than 20 metabolic pathways were found to be affected. These pathways included glycerophospholipid, sphingolipid, linoleic acid, arginine and proline, and alpha-linolenic acid metabolisms. PLGA NPs were found to perturb some amino acid metabolic pathways and altered membrane lipids to a different degree. The metabolic effect of the PLGA NPs on the cells were comparable to those caused by silver oxide NPs and other inorganic nanomaterials. However, PEG-PLGA NPs demonstrated a reduced impact on the cellular metabolism compared to Pluronic copolymer-coated PLGA and plain PLGA NPs

Quantitative isotope-dilution high-resolution-mass-apectrometry analysis of multiple intracellular metabolites in Clostridium autoethanogenum with uniformly 13C-labeled standards derived from Spirulina

We have investigated the applicability of commercially available lyophilized spirulina (Arthrospira platensis), a microorganism uniformly labeled with 13C, as a readily accessible source of multiple 13C-labeled metabolites suitable as internal standards for the quantitative determination of intracellular bacterial metabolites. Metabolites of interest were analyzed by hydrophilic-interaction liquid chromatography coupled with high-resolution mass spectrometry. Multiple internal standards obtained from uniformly (U)-13C-labeled extracts from spirulina were used to enable isotope-dilution mass spectrometry (IDMS) in the identification and quantification of intracellular metabolites. Extraction of the intracellular metabolites of Clostridium autoethanogenum using 2:1:1 chloroform/methanol/water was found to be the optimal method in comparison with freeze–thaw, homogenization, and sonication methods. The limits of quantification were ≤1 μM with excellent linearity for all of the calibration curves (R2 ≥ 0.99) for 74 metabolites. The precision and accuracy were found to be within relative standard deviations (RSDs) of 15% for 49 of the metabolites and within RSDs of 20% for all of the metabolites. The method was applied to study the effects of feeding different levels of carbon monoxide (as a carbon source) on the central metabolism and Wood–Ljungdahl pathway of C. autoethanogenum grown in continuous culture over 35 days. Using LC-IDMS with U-13C spirulina allowed the successful quantification of 52 metabolites in the samples, including amino acids, carboxylic acids, sugar phosphates, purines, and pyrimidines. The method provided absolute quantitative data on intracellular metabolites that was suitable for computational modeling to understand and optimize the C. autoethanogenum metabolic pathways active in gas fermentation

Apoferritin-Encapsulated Jerantinine A for Transferrin Receptor Targeting and Enhanced Selectivity in Breast Cancer Therapy

he O-acetyl (or acetate) derivative of the Aspidosperma alkaloid Jerantinine A (JAa) elicits anti-tumor activity against cancer cell lines including mammary carcinoma cell lines irrespective of receptor status (0.14 < GI50 < 0.38 μM), targeting microtubule dynamics. By exploiting breast cancer cells’ upregulated transferrin receptor 1 (TfR1) expression and apoferritin (AFt) recognition, we sought to develop an AFt JAa-delivery vehicle to enhance tumor-targeting and reduce systemic toxicity. Optimizing pH-mediated reassembly, ∼120 JAa molecules were entrapped within AFt. Western blot and flow cytometry demonstrate TfR1 expression in cancer cells. Enhanced internalization of 5-carboxyfluorescein-conjugated human AFt in SKBR3 and MDA-MB-231 cancer cells is observed compared to MRC5 fibroblasts. Accordingly, AFt–JAa delivers significantly greater intracellular JAa levels to SKBR3 and MDA-MB-231 cells than naked JAa (0.2 μM) treatment alone. Compared to naked JAa (0.2 μM), AFt–JAa achieves enhanced growth inhibition (2.5–14-fold; <0.02 μM < GI50 < 0.15 μM) in breast cancer cells; AFt–JAa treatment results in significantly reduced clonal survival, more profound cell cycle perturbation including G2/M arrest, greater reduction in cell numbers, and increased apoptosis compared to the naked agent (p < 0.01). Decreased PLK1 and Mcl-1 expression, together with the appearance of cleaved poly (ADP-ribose)-polymerase, corroborate the augmented potency of AFt–JAa. Hence, we demonstrate that AFt represents a biocompatible vehicle for targeted delivery of JAa, offering potential to minimize toxicity and enhance JAa activity in TfR1-expressing tumors

Integrated Metabolomics and Transcriptomics Using an Optimised Dual Extraction Process to Study Human Brain Cancer Cells and Tissues

The integration of untargeted metabolomics and transcriptomics from the same population of cells or tissue enhances the confidence in the identified metabolic pathways and understanding of the enzyme–metabolite relationship. Here, we optimised a simultaneous extraction method of metabolites/lipids and RNA from ependymoma cells (BXD-1425). Relative to established RNA (mirVana kit) or metabolite (sequential solvent addition and shaking) single extraction methods, four dual-extraction techniques were evaluated and compared (methanol:water:chloroform ratios): cryomill/mirVana (1:1:2); cryomill-wash/Econospin (5:1:2); rotation/phenol-chloroform (9:10:1); Sequential/mirVana (1:1:3). All methods extracted the same metabolites, yet rotation/phenol-chloroform did not extract lipids. Cryomill/mirVana and sequential/mirVana recovered the highest amounts of RNA, at 70 and 68% of that recovered with mirVana kit alone. sequential/mirVana, involving RNA extraction from the interphase of our established sequential solvent addition and shaking metabolomics-lipidomics extraction method, was the most efficient approach overall. Sequential/mirVana was applied to study a) the biological effect caused by acute serum starvation in BXD-1425 cells and b) primary ependymoma tumour tissue. We found (a) 64 differentially abundant metabolites and 28 differentially expressed metabolic genes, discovering four gene-metabolite interactions, and (b) all metabolites and 62% lipids were above the limit of detection, and RNA yield was sufficient for transcriptomics, in just 10 mg of tissue