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201
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Introduction
Research Experience
January 2005 - present
Leibniz Institute for Plant Biochemistry
Position
- Group Leader
Publications
Publications (201)
Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology,...
Chronic diseases affecting the central nervous system (CNS) like Alzheimer’s or Parkinson’s disease typically develop with advanced chronological age. Yet, aging at the metabolic level has been explored only sporadically in humans using biofluids in close proximity to the CNS such as the cerebrospinal fluid (CSF). We have used an untargeted liquid...
Plants produce thousands of compounds, collectively called the metabolome, which mediate interactions with other organisms. The metabolome of an individual plant may change according to the number and nature of these interactions. We tested the hypothesis that tree diversity level affects the metabolome of four subtropical tree species in a biodive...
Als Fachkonsortium für die Chemie hat sich NFDI4Chem innerhalb der Nationalen For-schungsdateninfrastruktur (NFDI) gebildet. In diesem Beitrag stellt sich das Konsor-tium kurz vor und legt seine zentralen Ziele und wichtigsten Verbesserungen für dasForschungsdatenmanagement (FDM) in der Chemie sowie die praktischen Heraus-forderungen dar. Die Visio...
In plant ecology, biochemical analyses of bryophytes and vascular plants are often con- ducted on dried herbarium specimen as species typically grow in distant and inaccessible locations. Here, we present an automated in silico compound classification framework to annotate metabolites using an untargeted data independent acquisition (DIA)–LC/MS–QTo...
Compound (or chemical) databases are an invaluable resource for many scientific disciplines. Exposomics researchers need to find and identify relevant chemicals that cover the entirety of potential (chemical and other) exposures over entire lifetimes. This daunting task, with over 100 million chemicals in the largest chemical databases, coupled wit...
Die Vision der NFDI4Chem ist die Digitalisierung aller wichtigen Schritte in der chemischen Forschung, um Wissenschaftler bei der Erhebung, Speicherung, Verarbeitung, Analyse, Veröffentlichung und Wiederverwendung von Forschungsdaten bestmöglich zu unterstützen. NFDI4Chem will alle Disziplinen der Chemie in der Wissenschaft vertreten. In der Anfang...
In plants, secondary metabolite profiles provide a unique opportunity to explore seasonal variation and responses to the environment. These include both abiotic and biotic factors. In field experiments, such stress factors occur in combination. This variation alters the plant metabolic profiles in yet uninvestigated ways. This data set contains tra...
Global change exposes forest ecosystems to many risks including novel climatic conditions, increased frequency of climatic extremes and sudden emergence and spread of pests and pathogens. At the same time, forest landscape restoration has regained global attention as an integral strategy for climate change mitigation. Owing to unpredictable future...
Plants produce thousands of compounds, collectively called the metabolome, which mediate interactions with other organisms. The metabolome of an individual plant may change according to the number and nature of these interactions. We tested the hypothesis that tree diversity level affects the metabolome of four subtropical tree species in a biodive...
Compound (or chemical) databases are an invaluable resource for many scientific disciplines. Exposomics researchers need to find and identify relevant chemicals that cover the entirety of potential (chemical and other) exposures over entire lifetimes. This daunting task, with over 100 million chemicals in the largest chemical databases, coupled wit...
Proteome remodeling is a fundamental adaptive response and proteins in complex and functionally related proteins are often co-expressed. Using a deep sampling strategy we define Arabidopsis thaliana tissue core proteomes at around 10,000 proteins per tissue and absolutely quantify (copy numbers per cell) nearly 16,000 proteins throughout the plant...
Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment t...
The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve t...
The growth of online mass spectrometry metabolomics resources, including data repositories, spectral library databases, and online analysis platforms has created an environment of online/web accessibility. Here, we introduce the Metabolomics Spectrum Resolver (https://metabolomics-usi.ucsd.edu/), a tool that builds upon these exciting developments...
Abstract
Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in...
Molecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global N...
The central aim in ecometabolomics and chemical ecology is to pinpoint chemical features that explain molecular functioning. The greatest challenge is the identification of compounds due to the lack of constitutive reference spectra, the large number of completely unknown compounds, and bioinformatic methods to analyze the big data. In this study w...
Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and...
How plants respond to changing environments is commonly studied in semi-natural biodiversity experiments and analysed on a morphological trait level. On the other hand, secondary metabolites, known to play a key role in, e.g. plant defence strategies, are mainly studied under controlled conditions. However, changes in plant communities and across s...
Metabolomics is a vibrant field, developing fast and attracting many scientists from adjacent disciplines. Its multidisciplinarity is one of the defining features of metabolomics: in order to describe, quantify and understand the diversity of metabolite composition of biological samples one needs chemistry, biology, mathematics and statistics, and...
Site-directed methods for the generation of genetic diversity are essential tools in the field of directed enzyme evolution. The Golden Gate cloning technique has been proven to be an efficient tool for a variety of cloning setups. The utilization of restriction enzymes which cut outside of their recognition domain allows the assembly of multiple g...
Background:
Molecule identification is a crucial step in metabolomics and environmental sciences. Besides in silico fragmentation, as performed by MetFrag, also machine learning and statistical methods evolved, showing an improvement in molecule annotation based on MS/MS data. In this work we present a new statistical scoring method where annotati...
Plants, grown in the field, face an undefined number of stresses. How plants respond to these factors, is often studied on the level of visible traits. However, changing communities and seasons will also be reflected in the metabolic fingerprint of a plant. Understanding those dynamics will help to unravel the underlying mechanisms of ecosystem fun...
Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is increasingly popular for the non-targeted exploration of complex samples, where tandem mass spectrometry (MS/MS) is used to characterize the structure of unknown compounds. However, mass spectra do not always contain sufficient information to unequivocally identify th...
Motivation:
Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected int...
Mass spectrometry (MS) is one of the primary techniques used for large scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition and...
Background
Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data fo...
Making reproducible, auditable and scalable data-processing analysis workflows is an important challenge in the field of bioinformatics. Recently, software containers and cloud computing introduced a novel solution to address these challenges. They simplify software installation, management and reproducibility by packaging tools and their dependenc...
Site-directed methods for the generation of genetic diversity are essential tools in the field of directed enzyme evolution. The Golden Gate cloning technique has been proven to be an efficient tool for a variety of cloning setups. The utilization of restriction enzymes which cut outside of their recognition domain allows the assembly of multiple g...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further...
The use of mass spectrometry-based metabolomics to study human, plant and microbial biochemistry and their interactions with the environment largely depends on the ability to annotate metabolite structures by matching mass spectral features of the measured metabolites to curated spectra of reference standards. While reference databases for metabolo...
Background: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data f...
In Eco-Metabolomics interactions are studied of non-model organisms in their natural environment and relations are made between biochemistry and ecological function. Current challenges when processing such metabolomics data involve complex experiment designs which are often carried out in large field campaigns involving multiple study factors, peak...
Bryophytes occur in almost all land ecosystems and contribute to global biogeochemical cycles, ecosystem functioning, and influence vegetation dynamics. As growth and biochemistry of bryophytes are strongly dependent on the season, we analyzed metabolic variation across seasons with regard to ecological characteristics and phylogeny. Using bioinfor...
Identification and structural determination of small molecules by mass spectrometry is an important step in chemistry and biochemistry. However, the chemically realistic annotation of a fragment ion spectrum can be a difficult challenge. We developed ChemFrag, for the detection of fragmentation pathways and the annotation of fragment ions with chem...
Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific...
The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, includi...
Metabolomics, the youngest of the major omics technologies, is supported byan active community of researchers and infrastructure developers acrossEurope. To coordinate and focus efforts around infrastructure building formetabolomics within Europe, a workshop on the “Future of metabolomics inELIXIR” was organised at Frankfurt Airport in Germany. Thi...
Several ecosystem-functioning-experiments revealed that plants grown in more diverse plant communities perform better in terms of resource uptake, biomass production and, in general, compensation of antagonistic effects of related pathogens, herbivores, and competitors.
We hypothesise that these processes leave biochemical signatures in plants; mo...
Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany....
NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format fo...
Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany....
Metabolomics is the modern term for the field of small molecule research in biology and biochemistry. Currently, metabolomics is undergoing a transition where the classic analytical chemistry is combined with modern cheminformatics and bioinformatics methods, paving the way for large-scale data analysis. We give some background on past developments...
Background
The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest (www.casmi-contest.org) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluatio...
Lipid identification is a major bottleneck in high-throughput lipidomics studies. However, tools for the analysis of lipid tandem MS spectra are rather limited. While the comparison against spectra in reference libraries is one of the preferred methods, these libraries are far from being complete. In order to improve identification rates, the in si...
A website http://msbi.ipb-halle.de/msbi/lipidfrag has been created to provide additional material for this manuscript.
All files are provided for both positive and negative ion mode. The peaklist archives contain the actual MetFrag query files of the standard and C. elegans MS/MS spectra. Furthermore, the result files are attached containing the Me...
Histograms of MetFrag score distributions for negative ion mode.
Histograms show back- (red) and foreground (green) datasets with their modeled distributions from specific lipid sub-classes.
(TIF)
Scatterplots of raw MetFrag scores from lipid standard material MS/MS spectra.
The score are shown for negative (A) and positive (B) ion mode.
(TIF)
Target lipids and used interfering species for overlapping experiments.
(PDF)
LipidFrag results for C. elegans MS/MS spectrum shown in S6 Fig derived from [M-H]- annotation.
(PDF)
LipidFrag?s improvement of ranks for training MS/MS spectra in positive ion mode.
(PDF)
Histograms of MetFrag score distributions for positive ion mode.
Histograms of back- (red) and foreground (green) datasets with their respective modeled distributions from specific lipid sub-classes.
(TIF)
MetFrag results from overlapping experiment.
Rank as function of different mixtures is shown.
(TIF)
Statistics on training MS/MS spectra from positive ion mode.
(PDF)
Number of used MS/MS spectra for training in negative ion mode.
(PDF)
LipidFrag annotation example from C. elegans dataset.
(A) Extracted ion chromatogram of an example lipid and one MS/MS spectrum acquired at 13.11 minutes. Under this peak two isomeric PC species are co-eluting. LipidFrag identified all four isomer (fatty acid isomers and positional isomers) with high scores and probabilities (S6 Table). (B) MS/MS s...
Statistics on training MS/MS spectra from negative ion mode.
(PDF)
Number of used MS/MS spectra for training in positive ion mode.
(PDF)
LipidFrag?s improvement of ranks for training MS/MS spectra in negative ion mode.
(PDF)
LipidFrag results on C. elegans data.
The maximal foreground class probabilities (FCPs) and their histogramms calculated by LipidFrag are plotted in descending order for 2,355 MS/MS spectra in positive (A) and 1,518 MS/MS spectra in negative (B) ion mode originating from the C. elegans lipid extract.
(TIF)
Projects
Projects (5)
Metabolism is a key biological process which is modulated in living organisms in response to environmental exposure, genetic variations and diet. Understanding metabolism is essential to improve plant performance, nutritional content, and to understand Human health and well-being. The metabolic response can be complex, involving hundreds to thousands of small molecules (metabolites) connected by thousands of biochemical reactions. Together, they constitute a dense network, in its entirety often called Genome Scale Metabolic Network (GSMN). Within this context, metabolomics is a cornerstone approach to experimentally observe changes in the metabolome (set of metabolites). One of the main analytical platforms to measure the metabolome is Mass Spectrometry (MS) which is often coupled to separation methods (e.g. Liquid Chromatography, LC-MS). Even though the technology is advancing rapidly, several challenges remain for widespread adoption of metabolomics. Metabolite identification remains one of these challenges. Nevertheless, experimentally obtained data and in silico generated GSMN overlap only partially and are generally not studied simultaneously. In MetClassNet, we hypothesis that these difficulties could be overcome by designing new data structures and algorithms which will exploit the connectivity (network) between molecules. This integrative approach will boost the power of data analysis by unifying GSMNs and networks obtained from experimental data. Hence, MetClassNet will propose a new computational framework and novel methods to help with tackling main metabolomics challenges in data analysis and data interpretation. This framework will integrate information from experimentally derived information and GSMNs by bridging them using direct mapping, ontologies and chemical class information.At the end of the project, MetClassNet will offer the community an innovative tool set where it will be possible to go beyond table based analysis of metabolomics data by integrating (and not just exporting) them into a network system. To this end, MetClassNet will create novel algorithms and tools to mine these networks allowing to increase our knowledge of the metabolome. The developed framework will also ease the connection between metabolomics and GSMNs, hence allowing to fill the gaps in current databases of metabolic networks. Within MetClassNet project, we will showcase the benefit of the computational framework to address the study of metabolic modulations related to ageing, toxicology, cancer and nutrition. Finally, MetClas





















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