Mass spectrometry-based applications and analytical method development for metabolomics

Metabolites are small molecules present in a biological system that have multiple important biological functions. Changes in metabolite levels reflect genetic and environmental alterations and play a role in multiple diseases. Metabolomics is a discipline that aims to analyze all the small molecules in a biological system simultaneously. Since metabolites represent a diverse group of compounds with varying chemical and physical properties with a wide concentration range, metabolomic analysis is technically challenging. Due to its high sensitivity and selectivity, mass spectrometry coupled with chromatographic separation is the most commonly used analytical tool. Currently, there is no comprehensive universal analytical tool to detect all metabolites simultaneously and multiple methods are required. The aim of this study was to develop and apply mass spectrometry-based analytical methods for metabolomics studies. Neonatal rodents can fully regenerate their hearts after an injury. However, this regenerative capacity is lost within 7 days after birth. The molecular mechanism behind this phenomenon is unknown and understanding the biology behind this loss of regeneration capacity is necessary for the development of regeneration-inducing therapies. To investigate this mechanism, changes in mouse heart metabolite, protein, and transcript levels during the early postnatal period were studied. Non-targeted metabolomics methods utilizing liquid chromatography-mass spectrometry (LC-MS) and two-dimensional gas chromatography-mass spectrometry (GCxGC-MS) were applied to detect the metabolic changes of neonatal mouse hearts. Two complementary techniques increased metabolite coverage. A total of 151 identified metabolites showed differences in the neonatal period, reflecting changes in multiple metabolic pathways. The most significant changes observed in all levels (metabolite, protein, and transcript) were branched chain amino acid (BCAA) catabolism, fatty acid metabolism, and the mevalonate and ketogenesis pathways, thus revealing possible associations with regeneration capacity or regulation of the cardiomyocyte cell cycle. Insulin resistance (IR), metabolic syndrome, and type 2 diabetes have been shown to induce metabolic changes; the origin of the changes is unknown. In this study, human serum metabolite profiles from non-diabetic individuals were associated with IR. Gut microbiota were identified as a possible origin of the metabolic changes. Serum metabolites were detected with GCxGC-MS and lipids with LC-MS method. In total, 19 serum metabolite clusters were significantly associated with the IR phenotype, including 26 polar metabolites from five separate clusters and 367 lipids from 14 clusters. IR and changed metabolites were further associated with gut microbiota metagenomics and gut microbiota functional modules, showing that gut microbiota impacts the human serum metabolites associated with IR. Individuals with the IR phenotype had increased BCAA levels, which was influenced by bacterial species with increased BCAA biosynthesis potential and the absence of species with active bacterial inward BCAA transport. Sample throughput is often limited when chromatographic separation is used in metabolomics applications; a short analysis time is of great importance in large metabolic studies. The feasibility of direct infusion electrospray microchip MS (chip-MS) for global non-targeted metabolomics to detect metabolic differences between two cell types was studied and was compared to the more traditional LC-MS method. We observed that chip-MS was a rapid and simple method that allowed high sample throughput from small sample volumes. The chip-MS method was capable of separating cells based on their metabolic profiles and could detect changes of several metabolites. However, the selectivity of chip-MS was limited compared to LC-MS and chip-MS suffers more from ion suppression. Many biologically important low-abundance metabolites are not detectable with non-targeted metabolomics methods and separate more sensitive targeted methods are required. An in-house developed capillary photoionization (CPI) source was shown to have high ion transmission efficacy and high sensitivity towards non-polar compounds such as steroids. In this study, the CPI prototype was developed to increase its sensitivity. The feasibility of the ion source for the quantitative analysis of biological samples was studied by analyzing 18 endogenous steroids in urine with gas chromatography capillary photoionization tandem mass spectrometry (GC-CPI-MS/MS). The GC-CPI-MS/MS method showed good chromatographic resolution, acceptable linearity and repeatability, and low limits of detection (2-100 pg mL-1). In total, 15 steroids were quantified either as a free steroid or glucuronide conjugate from the human urine samples. Additionally, the applicability of the CPI interface for LC applications was explored for the first time using low flow rates. The feasibility of the LC-CPI-MS/MS for the quantitative analysis of four steroids was studied in terms of linearity, repeatability, and limits of detection. The method showed good quantitative performance and high sensitivity at a low femtomole level.Metaboliitit ovat molekyylipainoltaan pieniä aineenvaihduntatuotteita, joilla on merkittäviä biologisia tehtäviä elimistössä. Aineenvaihduntatuotteiden muutoksien on osoitettu liittyvän moniin sairauksiin, jonka takia niiden analysoiminen on tärkeää sairauksien diagnosoimiseksi, ennustamiseksi, sairausmekanismin selvittämiseksi, sekä lääkehoidon kehittämiseksi. Metabolomiikka pyrkii analysoimaan aineenvaihduntatuotteet samanaikaisesti biologisista näytteistä ja vertailemaan aineenvaihduntatuotteiden tasoja eri fysiologisten tilojen välillä ja sitä voidaankin hyödyntää useissa lääketieteellisen tutkimuksen eri vaiheissa. Aineenvaihduntatuotteiden pitoisuudet ja kemialliset ominaisuudet kuitenkin vaihtelevat merkittävästi, mikä tekee aineenvaihduntatuotteiden samanaikaisen analysoinnin haastavaksi. Tällä hetkellä ei ole olemassa yhtä kaikkien aineenvaihduntatuotteiden samanaikaiseen analyysiin soveltuvaa menetelmää. Parhaiten metaboliittien analyysiin soveltuu massaspektrometria, usein yhdistettynä kromatografisiin erotustekniikoihin, sen ylivoimaisen herkkyyden ja spesifisyyden vuoksi. Tässä työssä pyrittiin soveltamaan massaspektrometrisiä kohdentamattomia profilointimenetelmiä uuden biologisen tiedon tuottamiseksi muuttuneista aineenvaihduntatuotteista. Työssä pyrittiin myös kehittämään uusia herkempiä ja nopeampia massaspektrometrisiä menetelmiä metabolomiikkaan. Ensimmäisessä osatutkimuksessa kohdentamatonta metabolomiikkaa sovellettiin lääkehoidon kohdemolekyylin etsintään solujen uusiutumisen aktivoimiseksi massiivisia soluvaurioita aiheuttavien sairauksien hoidossa. Aineenvaihduntareiteissä tapahtuvia muutoksia tutkittiin hiirien sydämistä, jotka menettävät sydänsolujen uusiutumiskyvyn pian syntymän jälkeen. Metabolomiikalla havaittiin muutoksia useilla aineenvaihduntareiteillä syntymän jälkeisellä ajanjaksolla, jolloin sydänsolujen uusiutumiskapasiteetti heikkenee. Tuloksia yhdistettiin muiden biomolekyylien analyysituloksiin ja saatiin kattavaa tietoa syntymän jälkeisistä molekyylimuutoksista. Erityisesti ketogeneesi-aineenvaihduntareitin havaittiin vaikuttavan solujen jakautumiseen ja lisääntymiseen. Insuliiniresistenssin, metabolisen oireyhtymän ja tyypin 2 diabeteksen on osoitettu aiheuttavan metabolisia muutoksia ihmisissä, mutta muutosten syy on ollut tuntematon. Työn toisessa osatutkimuksessa tutkittiin suoliston mikrobiston yhteyttä insuliiniresistenssiin ja metabolisiin muutoksiin seerumissa. Tutkimuksessa havaittiin seerumin metaboliittien muutoksilla olevan yhteys insuliiniresistenssiin, sekä yksilöiden suolistomikrobeihin ja niiden toimintoihin. Insuliiniresistentillä ryhmällä havaittiin kohonneet haaroittuneiden aminohappojen pitoisuudet seerumissa, sekä enemmän bakteerilajeja, jotka syntetisoivat haaroittuneita aminohappoja. Tutkimus antoi viitteitä, että suolistomikrobeilla on yhteys insuliiniresistenssin ja tyypin 2 diabeteksen puhkeamiseen. Kolmannessa osatutkimuksessa tutkittiin suorasyöttömikrosirun soveltuvuutta kohdentamattomaan metaboliseen profilointiin vertailemalla menetelmää yleisesti käytettyyn nestekromatografia-massaspektrometria menetelmään solujen metaboliittien erojen havaitsemiseksi. Mikrosiru-menetelmän etuna on nopea alle minuutin analyysiaika, joka mahdollistaa ison näytemäärän analysoinnin lyhyessä ajassa pienestä näytemäärästä. Erot solujen metabolisten profiileiden välillä pystyttiin havaitsemaan molemmilla menetelmillä. Mikrosiru-menetelmän selektiivisyys oli kuitenkin heikompi ja ionien supressio massaspektrometrissa oli merkittävämpää. Neljännessä ja viidennessä osatutkimuksessa tutkittiin kapillaarifotoionisaatio ionisaatiotekniikan soveltuvuutta metabolomiikkaan. Kohdentamattomien profilointimenetelmien herkkyys ei riitä matalien pitoisuuksien analysointiin, jonka vuoksi myös kohdennettuja herkempiä menetelmiä tarvitaan tiettyjen yhdisteryhmien määrittämiseksi. Kapillaarifotoionisaation soveltuvuutta tutkittiin kehittämällä menetelmä steroidien määrittämiseksi virtsasta kaasukromatografia-massaspektrometrilla. Menetelmällä saavutettiin hyvä herkkyys ja menetelmän todettiin soveltuvan steroidien kvantitatiiviseen analytiikkaan biologisesta matriisista. Kapillaarifotoionisaation soveltuvuutta steroidien analysoimiseksi myös nestekromatografia-massaspektrometrialla tutkittiin ensimmäistä kertaa. Tutkimuksessa havaittiin kapillaarifotoionisaation soveltuvan myös nestekromatografiaan pienillä virtausnopeuksilla. Kohdentamattomalla metabolomiikalla saavutettiin merkittävää tietoa muuttuneista aineenvaihduntatuotteista ja havaittavien metaboliittien määrää laajennettiin käyttämällä kahta rinnakkaista menetelmää. Työssä kapillaarifotoionisaation ja mikrosirutekniikan osoitettiin soveltuvan käytettäväksi metabolomiikassa

Capillary photoionization: interface for low flow rate liquid chromatography-mass spectrometry

This is the first report on capillary photoionization (CPI) interfacing a liquid chromatograph (LC) and mass spectrometer (MS). A new heated CPI ion source was developed, including a heated transfer capillary, a wide oval-shaped and low-depth ionization chamber with a vacuum ultraviolet (VUV) transparent magnesium fluoride (MgF2) window to increase the photoionization efficiency and thus the sensitivity. As both analytes and eluent are first vaporized and then photoionized inside the CPI ion source between the atmosphere and the vacuum of MS, the ion transfer efficiency into the MS and thus the sensitivity is improved. The effect of the most important operation parameters, the eluent flow rate and temperature of the CPI source, on the signal intensity was studied with selected steroids. The feasibility of LC-CPI-MS/MS for the quantitative analysis of steroids was also studied in terms of linearity, repeatability, and limits of detection. The method showed good quantitative performance and sensitivity down to the low femto-mole level.Peer reviewe

Comparison of liquid chromatography-mass spectrometry and direct infusion microchip electrospray ionization mass spectrometry in global metabolomics of cell samples

In this study, the feasibility of direct infusion electrospray ionization microchip mass spectrometry (chip-MS) was compared to the commonly used liquid chromatography-mass spectrometry (LC-MS) in non-targeted metabolomics analysis of human foreskin fibroblasts (HFF) and human induced pluripotent stem cells (hiPSC) reprogrammed from HFF. The total number of the detected features with chip-MS and LC-MS were 619 and 1959, respectively. Approximately 25% of detected features showed statistically significant changes between the cell lines with both analytical methods. The results show that chip-MS is a rapid and simple method that allows high sample throughput from small sample volumes and can detect the main metabolites and classify cells based on their metabolic profiles. However, the selectivity of chip-MS is limited compared to LC-MS and chip-MS may suffer from ion suppression.Peer reviewe

Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men

Background. There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods. We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. Results. A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lowerlevels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BM and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p 0; p <0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. Conclusion. This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors. (C) 2017 The Authors. Published by Elsevier Inc.Peer reviewe

A miniaturised 3D printed polypropylene reactor for online reaction analysis by mass spectrometry

Correction: Reaction Chemistry & Engineering, vol. 2:5, p. 811 DOI: 81110.1039/C7RE90018JA miniaturised polypropylene reactor was fabricated by 3D printing using fused deposition modeling. A stainless steel nanoelectrospray ionisation capillary and a magnetic stir bar were integrated into the reactor during the printing process. The integrated nanoelectrospray ionisation capillary allows direct sampling of a reaction solution without external pumping. It also allows ionisation of the analytes. Therefore, very rapid online mass spectrometric chemical reaction monitoring is possible. Operation of the miniaturised reactor is shown by the online nanoelectrospray mass spectrometry characterisation of a Diels–Alder reaction and the subsequent retro Diels–Alder reaction.Peer reviewe

Molecular profile of the rat peri-infarct region four days after stroke: Study with MANF

The peri-infarct region after ischemic stroke is the anatomical location for many of the endogenous recovery processes, and the molecular events in the peri-infarct region remain poorly characterized. In this study, we examine the molecular profile of the peri-infarct region on post-stroke day four, time when reparative processes are ongoing. We used a multiomics approach, involving RNA sequencing, and mass spectrometry-based proteomics and metabolomics to characterize molecular changes in the peri-infarct region. We also took advantage of our previously developed method to express transgenes in the peri-infarct region where self-complementary adeno-associated virus (AAV) vectors were injected into the brain parenchyma on post-stroke day 2. We have previously used this method to show that mesencephalic astrocyte-derived neurotrophic factor (MANF) enhances functional recovery from stroke and recruits phagocytic cells to the peri-infarct region. Here, we first analyzed the effects of stroke to the peri-infarct region on post-stroke day 4 in comparison to sham-operated animals, finding that stroke induced changes in 3345 transcripts, 341 proteins, and 88 metabolites. We found that after stroke genes related to inflammation, proliferation, apoptosis, and regeneration were upregulated, whereas genes encoding neuroactive ligand receptors and calcium-binding proteins were downregulated. In proteomics, we detected upregulation of proteins related to protein synthesis and downregulation of neuronal proteins. Metabolomic studies indicated that in after stroke tissue there is increase in saccharides, sugar phosphates, ceramides and free fatty acids and decrease of adenine, hypoxantine, adenosine and guanosine. We then compared the effects of post-stroke delivery AAV1-MANF delivery to AAV1-eGFP (enhanced green fluorescent protein). MANF administration increased the expression of 77 genes, most of which were related to immune response. In proteomics, MANF administration reduced S100A8 and S100A9 protein levels. In metabolomics, no significant differences between MANF and eGFP treatment were detected, but relative to sham surgery group, most of the changes in lipids were significant in the AAV-eGFP group only. This work describes the molecular profile of the peri-infarct region during recovery from ischemic stroke, and establishes a resource for further stroke studies. These results provide further support for parenchymal MANF as a modulator of phagocytic function.Peer reviewe

Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men

Background. There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM.Methods. We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids.Results. A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lowerlevels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BM and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p 0; p < 0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study.Conclusion. This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors

High-grade ovarian serous carcinoma patients exhibit profound alterations in lipid metabolism

Ovarian cancer is a very severe type of disease with poor prognosis. Treatment of ovarian cancer is challenging because of the lack of tests for early detection and effective therapeutic targets. Thus, new biomarkers are needed for both diagnostics and better understanding of the cellular processes of the disease. Small molecules, consisting of metabolites or lipids, have shown emerging potential for ovarian cancer diagnostics. Here we performed comprehensive lipidomic profiling of serum and tumor tissue samples from high-grade serous ovarian cancer patients to find lipids that were altered due to cancer and also associated with progression of the disease. Ovarian cancer patients exhibited an overall reduction of most lipid classes in their serum as compared to a control group. Despite the overall reduction, there were also specific lipids showing elevation, and especially alterations in ceramide and triacylglycerol lipid species were dependent on their fatty acyl side chain composition. Several lipids showed progressive alterations in patients with more advanced disease and poorer overall survival, and outperformed CA-125 as prognostic markers. The abundance of many serum lipids correlated with their abundance in tumor tissue samples. Furthermore, we found a negative correlation of serum lipids with 3-hydroxybutyric acid, suggesting an association between decreased lipid levels and fatty acid oxidation. In conclusion, here we present a comprehensive analysis of lipid metabolism alterations in ovarian cancer patients, with clinical implications.Peer reviewe

Molecular Atlas of Postnatal Mouse Heart Development

Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource of mRNA, protein, and metabolite changes in the neonatal heart for identification of metabolism‐related mechanisms associated with cardiac regeneration. Methods and Results Methods and results Mouse ventricular tissue samples taken on postnatal day 1 (P01), P04, P09, and P23 were analyzed with RNA sequencing and global proteomics and metabolomics. Gene ontology analysis, KEGG pathway analysis, and fuzzy c‐means clustering were used to identify up‐ or downregulated biological processes and metabolic pathways on all 3 levels, and Ingenuity pathway analysis (Qiagen) was used to identify upstream regulators. Differential expression was observed for 8547 mRNAs and for 1199 of 2285 quantified proteins. Furthermore, 151 metabolites with significant changes were identified. Differentially regulated metabolic pathways include branched chain amino acid degradation (upregulated at P23), fatty acid metabolism (upregulated at P04 and P09; downregulated at P23) as well as the HMGCS (HMG‐CoA [hydroxymethylglutaryl‐coenzyme A] synthase)–mediated mevalonate pathway and ketogenesis (transiently activated). Pharmacological inhibition of HMGCS in primary neonatal cardiomyocytes reduced the percentage of BrdU‐positive cardiomyocytes, providing evidence that the mevalonate and ketogenesis routes may participate in regulating the cardiomyocyte cell cycle. Conclusions This study is the first systems‐level resource combining data from genomewide transcriptomics with global quantitative proteomics and untargeted metabolomics analyses in the mouse heart throughout the early postnatal period. These integrated data of molecular changes associated with the loss of cardiac regeneration may open up new possibilities for the development of regenerative therapiesPeer reviewe

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression toward Type 1 Diabetes

SummaryColonization of the fetal and infant gut microbiome results in dynamic changes in diversity, which can impact disease susceptibility. To examine the relationship between human gut microbiome dynamics throughout infancy and type 1 diabetes (T1D), we examined a cohort of 33 infants genetically predisposed to T1D. Modeling trajectories of microbial abundances through infancy revealed a subset of microbial relationships shared across most subjects. Although strain composition of a given species was highly variable between individuals, it was stable within individuals throughout infancy. Metabolic composition and metabolic pathway abundance remained constant across time. A marked drop in alpha-diversity was observed in T1D progressors in the time window between seroconversion and T1D diagnosis, accompanied by spikes in inflammation-favoring organisms, gene functions, and serum and stool metabolites. This work identifies trends in the development of the human infant gut microbiome along with specific alterations that precede T1D onset and distinguish T1D progressors from nonprogressors