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Mass Spectrometry and Microbial Primary Metabolites Downloaded from orbit.dtu.dk on: Oct 06, 2021 Metabolome analysis - mass spectrometry and microbial primary metabolites Højer-Pedersen, Jesper Juul Publication date: 2008 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Højer-Pedersen, J. J. (2008). Metabolome analysis - mass spectrometry and microbial primary metabolites. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Metabolome analysis – mass spectrometry and microbial primary metabolites Jesper Juul Højer-Pedersen June 2008 Copyright c 2003-2008 Jesper Juul Højer-Pedersen. All rights reserved The thesis is typeset in LATEX Technical University of Denmark Center for Microbial Biotechnology Building 223, DK-2800 Kgs. Lyngby, Denmark http://www.cmb.dtu.dk Summary While metabolite profiling has been carried out for decades, the scope for metabo- lite analysis have recently been broadened to aim at all metabolites in a living organism – also referred to as the metabolome. This is a great challenge, which requires versatile analytical technologies that are highly sensitive and specific, and to undertake this challenge mass spectrometry (MS) is among the best can- didates. Along with analysis of the metabolome the research area of metabolomics has evolved. Metabolomics combines metabolite profiles, data mining and bio- chemistry and aims at understanding the interplay between metabolites. In this thesis, different topics have been addressed and discussed with the aim of advanc- ing metabolomics to explore the concept in a physiological context. The metabolome comprises a wide variety of chemical compounds that act dif- ferently upon sample preparation, and therefore sample preparation is critical for metabolome analysis. The three major steps in sample preparation for metabo- lite analysis are sampling, extraction and concentration. These three steps were evaluated for the yeast Saccharomyces cerevisiae with primary focus on analysis of a large number of metabolites by one method. The results highlighted that there were discrepancies between different methods. To increase the throughput of cultivation, S. cerevisiae was grown in microti- tier plates (MTPs), and the growth was found to be comparable with cultivations in shake flasks. The carbon source was either glucose, galactose or ethanol, and metabolic footprinting by mass spectrometry was used to study the influence of carbon source on the extracellular metabolites. The results showed that footprints clustered according to the carbon source. Advances in technologies for analytical chemistry have mediated increased amounts of data generated in high resolution. One major limitation though is the digestion of data coverting the information into a format that can be interpreted in a biological context and take metabolomics beyond the principle of guilt-by- association. To analyze the data there is a general need for databases that contain metabolite specific information, which will speed up the identification of profiled i ii SUMMARY metabolites. To address the capabilities of electrospray ionization (ESI)-MS in detecting the metabolome of S. cerevisiae, the in silico metabolome of this or- ganism was used as a template to present a theoretical metabolome. This showed that in combination with the specificity of MS up to 84% of the metabolites can be identified in a high-accuracy ESI-spectrum. A total of 66 metabolites were systematically analyzed by positive and negative ESI-MS/MS with the aim of initiating a spectral library for ESI of microbial metabolites. This systematic analysis gave insight into the ionization and fragmentation characteristics of the different metabolites. With this insight, a small study of metabolic footprint- ing with ESI-MS demonstrated that biological information can be extracted from footprinting spectra. Statistical analysis of the footprinting data revealed dis- criminating ions, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool for extraction of metabolic differences, which can guide new targeted biological experiments. Dansk sammenfatning Analyse af metabolitter og sammenligning af profiler af disse har været udført i ˚artier, og inden for de senest ˚arer der kommet fornyet fokus p˚adenne disci- plin, hvor man nu ønsker at m˚alesamtlige metabolitter i en celle — ogs˚akaldet metabolomet. Det er en betydelig udfordring at analysere metabolomet, og det stiller store krav til analysemetoderne, der skal besidde stor følsomhed og speci- ficitet. Der er et begrænset antal analyseteknikker til r˚adighed for at klare denne udfordring og heriblandt m˚amassespektrometri anses for en af de bedre mu- ligheder. H˚and i h˚and med analysen af metabolomet er der opst˚aetet forskn- ingsomr˚ade kaldet metabolomics, hvor metabolitprofiler, dataanalyse og biokemi kombineres for at opn˚aen helhedsforst˚aelse af metabolitternes sammenspil. I denne afhandling diskuteres forskellige emner inden for metabolomics med hen- blik p˚aat bringe metabolomics et skridt videre i forst˚aelseaf, hvordan det kan bruges i en fysiologisk sammenhæng. Metabolomet er sammensat af en lang række kemisk forskellige forbindelser og prøveforberedelse er derfor kristisk for metabolomanalyse. De tre primære trin i prøveforberedelse er prøveudtagning, ekstraktion og opkoncentrering. Disse tre trin er blevet undersøgt for gæren Saccharomyces cerevisiae med henblik p˚aat m˚ales˚amange metabolitter s˚amuligt p˚aen gang. Forsøgene understregede at de forskellige metoder gav forskellige resultater. Med henblik p˚aat kunne gennemføre flere forsøg blev S. cerevisiae dyrket i mikrotiterplader, og væksten synes at være sammenlignelig med vækst i en rysteflaske. Som en del af forsøget blev der brugt 3 forskellige kulstofkilder: glukose, galactose og ethanol og kulturvæsken blev analyseret for ekstracellulære metabolitter ved metabolic footprinting. Data blev opn˚aetved massespektrometri, og dataanalysen viste, at det var muligt at skelne prøverne, efter hvilken kulstofk- ilde der var brugt. Inden for analytisk kemi sker der store tekniske fremskridt, og det har bl.a. betydet at data bliver generet i stadig højere opløsning. Dette kræver en effektiv fortolkning af data, s˚aledes at det bliver muligt at ekstrahere biologisk informa- iii iv SUMMARY – IN DANISH tion. Denne fortolkning kan assisteres af databaser, der indeholder reference- data, og disse databaser vil kunne effektivisere dataanalysen og identifikationen af metabolitter. For at belyse muligheden for at bruge elektrosprayionisering- massespektrometri (ESI-MS) til detektion af hele metabolomet for S. cerevisiae blev der taget udgangspunkt i in silico metabolomet af denne organisme. Det viste sig, at med specificiteten fra massespektrometri var det muligt at skelne mellem op til 84% af metabolitterne i et massespektrum. Yderligere blev der indsamlet data fra 66 metabolitter med henblik p˚aat lave en database med ESI- MS spektre for mikrobielle metabolitter. Data blev systematisk genereret, og med udgangspunkt i disse data har det været muligt at forbedre fortolkningen af metabolomdata opn˚aetved massespektrometri. Som et eksempel herp˚avar det muligt at udlede biologisk information p˚abaggrund af metabolic footprinting. Normalt bruges metabolic footprinting til klassifikation, men med udgangspunkt i massespektrene blev det muligt at tage metabolic footprinting skridtet videre og udlede fysiologiske forskelle. Preface The present thesis concludes 3 years research started in March 2003 at Cen- ter for Microbial Biotechnology resided at the department Sysmtems Biology at Technical University of Denmark (DTU). The work has been carried out under supervision by Professor Jens Nielsen and co-supervision by Associated Professor Jørn Smedsgaard. The thesis comprises the primary work of several distinct projects aiming at ad- vancing metabolomics to explore the concept in a physiological context. The research has been a journey within bioanalytical chemistry spiced with microbial physiology and informatics. Mass spectrometry has had a central position in the work, which is reflected in the thesis. Acknowledgements Numerous people have been interacting with me during the study. Let me start by recognizing Professor Jens Nielsen as being my supervisor throughout the project. I thank him for the many good and fruitful discussions we had along the way. I appreciate his support when it was needed in the very end. Associated Professor Jørn Smedsgaard has been co-supervisor throughout the project, and I thank him for generously sharing his expertise in analytical chemistry and especially mass spectrometry. Professor Gregory Stephanopoulos from Massachusetts Institute of Technology (MIT) is
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