Target practice: informatic and metabolomic assessment of biological network changes and of drug-cell interactions

Lead Research Organisation: University of Manchester
Department Name: Chemistry

Abstract

There are many occasions where one may wish to know the site of interaction of a drug or other substance with a complex biological system (i.e. network), typically by detecting changes something that can be measured. These are usually hard problems, since there are many ways of explaining the changes if one does not in fact know the network. However, in contrast to biological signalling and gene regulatory networks, we normally DO know the structure and outline properties of METABOLIC networks. This makes it MUCH easier to determine the parts of the network changes might have been focussed. Initially using baker's yeast as a model organism, we wish to demonstrate that this strategy does indeed work. It is necessary to make simple assumptions about the general form of the the equations describing the interactions within these networks, and we shall develop and exploit modern numerical methods for parameter estimation. As stated, we shall initially develop and test these strategies in baker's yeast, Saccharomyces cerevisiae, since this is a well understood organism. However, our collaborative partner Unilever are extremely interested in Corynebacterium jeikeium, for which a genome sequence and network model exist, and using resources made available by them for this project we shall also exploit these methods in the analysis of metabolic fluxes in this organism. The deliverable will be a suite of novel methods with which to infer the site of action of any drug-like molecule in a reasonably well understood metabolic network.

Technical Summary

There are many occasions where one may wish to know the site of interaction of an effector molecule with a complex biological system (i.e. network), typically by measuring changes in the accessible state variables. These are usually ill-conditioned problems, in the sense that many models can account for the observable data, and to make progress it is necessary to apply constraints and simplifications of various kinds. In contrast to cognate analyses of signalling and gene regulatory networks, the analysis of METABOLIC networks and their fluxes is attractive since they NECESSARILY possess stoichiometric and thermodynamic constraints, which are known, and measurement of the molecules they excrete as end products creates further constraints on the fluxes through the different parts of the network. Initially using baker's yeast as a model organism, we wish to demonstrate that this strategy does indeed work. The necessary simplifications include the use of mass action and lin-log kinetics, while we shall develop and exploit modern methods of multivariate statistical optimisation and machine learning for parameter estimation. These include multi-objective evolutionary algorithms, and the exploitation of probabilistic graphical methods and Gaussian process models. We shall initially develop and test these strategies in baker's yeast, Saccharomyces cerevisiae, since this is a well understood organism. However, our collaborative partner Unilever are extremely interested in Corynebacterium jeikeium, for which a genome sequence and network model exist, and using resources made available by them for this project we shall also exploit these methods in the analysis of metabolic fluxes in this organism. The deliverable will be a suite of novel methods with which to infer the site of action of any effector in a reasonably well understood metabolic network.

Publications

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Westerhoff H (2009) Systems Biology: The elements and principles of Life in FEBS Letters

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Villéger AC (2010) Arcadia: a visualization tool for metabolic pathways. in Bioinformatics (Oxford, England)

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Swainston N (2010) Enzyme kinetics informatics: from instrument to browser. in The FEBS journal

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Le Novère N (2009) The Systems Biology Graphical Notation. in Nature biotechnology

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Hekkelman ML (2010) WIWS: a protein structure bioinformatics Web service collection. in Nucleic acids research

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Dada JO (2010) SBRML: a markup language for associating systems biology data with models. in Bioinformatics (Oxford, England)

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Attwood TK (2010) Utopia documents: linking scholarly literature with research data. in Bioinformatics (Oxford, England)

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Ananiadou S (2010) Event extraction for systems biology by text mining the literature. in Trends in biotechnology

 
Description The project produced a number of outputs in the biomedical domain that have not been published because of the collaboration with Unilever. These are summarised here, with sensitive details omitted.

(1) Development of metabolomic approaches to profile bacteria from the skin surface
(2) Comparison of metabolic profiles from skin equivalents and skin samples
(3) The quantification of pyroglutamic acid and urocanic acid in sweat samples by GC-MS (results used to assist in development of artificial media)
(4) Qualitative analysis of sweat samples, the objective was to identify the metabolites present in human sweat (results used to assist in development of artificial media)
(5) Metabolome analysis of organism samples, with specific interest in metabolites associated with the metabolism of tryptophan. In this objective quantification analysis was performed for 32 metabolites of particular interest in four species of bacteria cultured in different conditions in both intracellular and exometabolome samples. In addition metabolic profiling was performed on the samples to determine widespread and unexpected changes in metabolism.

Arcadia is a visualisation tool offering novel ways of representing and interacting with metabolic pathway diagrams. Arcadia translates text-based descriptions of biological networks (SBML files) into standardised diagrams (SBGN PD maps). Users can view the same model from different perspectives and easily alter the layout to emulate traditional textbook representations. The software is available from http://arcadiapathways.sourceforge.net/. The software has been downloaded around 900 times.

Further development of standard operating procedures (SOPs) for the quenching of metabolism and extraction of metabolites from cultures of Saccharomyces cerevisiae in global metabolomic approaches. To maximize the coverage of the metabolome the employment of two analytical platforms was explored (UPLC-Orbitrap and GC-ToF-MS) and methodologies to sample both the intracellular and exo-metabolome were optimized. These methodologies were extended and adapted to a numbers of microorganisms of interest to Unilever and the protocols for sample preparation were subsequently adopted within the Unilever research laboratories.

The development of metabolomic approaches as a tool to determine the intervention sites for chemical effectors. In developing the tool, proof of principle experiments were performed by exposing cultures of Saccharomyces cerevisiae to a number of chemical effectors (Fluconazole, Methionine Sulphoximine and Methotrexate) with known target sites. The effect of the chemical effectors on the metabolome was investigate with the application of global metabolic profiling to explore both the expected (and any un-expected) effects on the metabolome to develop the approach as a tool to investigate chemical effectors with un-known modes of action.

Utopia documents is a novel PDF viewer, enabling the content of scientific articles to be linked to source databases and visualisation tools (e.g. Arcadia, biomodels.net). The IP for Utopia Documents was transferred to a spinout company, Lost Island Labs, which provides consultancy and software services to the pharma industry.


In addition, the project played an important role in establishing LibSBGN, an ongoing community project initiated at SBGN4.5 in April 2009 which aims to provide a free library for manipulating graphical representations of Systems Biology diagrams.

The Systems Biology Graphical Notation defines a standardized way to draw maps of biochemical and cellular processes studied in systems biology. The specifications describe a visual language which consist in a number of visual symbols.
These symbols can be assembled according to a set of syntactic rules, allowing to express complex systems biology knowledge in a concise and unambiguous manner. A number of pathway editors and network visualization tools (including our own Arcadia tool) have independently started to implement graphical support for the notation.
But as there is no standardized way to express SBGN concepts electronically, these tools are rarely interoperable:
- users can't transfer their maps from one application to another, even though the features they need (e.g. validation, layout) may be scattered across different tools;
- developers can't reuse each others' code, resulting in the same set of core features (e.g. conversion to and from usual file formats) getting reimplemented multiple times.

The goal of the LibSBGN project is to accelerate the adoption of SBGN by facilitating:
- the implementation of SBGN-compliant tools
- interoperability between these tools

MODEL0072364382 (deposited in in biomodels.net, ) is a reconstruction of the biochemical network of the yeast Saccharomyces cerevisiae carried out at a jamboree organized in April 2007 in the Manchester Centre for Integrative Systems Biology. It is the result of a consensus merger of two previous reconstructions. The model, and the process by which it was generated are described in detail in Herrgård et al. (2008)
Exploitation Route Utopia Documents is now Open Source and has a growing community of developers and users.

MODEL0072364382 (deposited in in biomodels.net, ) is a reconstruction of the biochemical network of the yeast Saccharomyces cerevisiae and is freely available for use in simulations.
Sectors Agriculture

Food and Drink

Chemicals

 
Title MODEL0072364382 a reconstruction of the biochemical network of the yeast Saccharomyces cerevisiae 
Description This is a reconstruction of the biochemical network of the yeast Saccharomyces cerevisiae carried out at a jamboree organized in April 2007 in the Manchester Centre for Integrative Systems Biology. It is the result of a consensus merger of two previous reconstructions. This yeast metabolic reconstruction has since been further improved by Dobson PD, 2010, Heavner BD, 2012 and Heavner BD, 2013. The up to date data set is available from http://yeast.sf.net/. 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact The associated paper has been cited >300 times since its publication in 2008. 
URL http://www.ebi.ac.uk/biomodels-main/MODEL0072364382
 
Title Arcadia 
Description Arcadia translates text-based descriptions of biological networks (SBML files) into standardized diagrams (SBGN PD maps). Users can view the same model from different perspectives and easily alter the layout to emulate traditional textbook representations. 
Type Of Technology Webtool/Application 
Year Produced 2010 
Impact None yet 
URL https://sourceforge.net/projects/arcadiapathways/
 
Title Utopia Documents 
Description Utopia Documents is a PDF reader optimised for reading scientific literature. By analysing the content of an article in real time, Utopia provides links to realtime data relating to the article and its content, allowing the user to browse from paper-to-paper through citations/references, and retrieve definitions of terms. 
Type Of Technology Software 
Year Produced 2014 
Open Source License? Yes  
Impact Creation of a spin-out company, Lost Island Labs which provides services to the pharma industry based on Utopia Documents Release of the source code under the GNU Public Licence, and its inclusion as part of the Debian Linux distribution. 
URL http://utopiadocs.com
 
Company Name Lost Island Labs Ltd 
Description  
Year Established 2011 
Impact None yet
Website http://www.utopiadocs.com