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For any enquiries related to the Biomolecular Medicine research area, please contact

Fiona Pereira
CSM Research Manager
csm@imperial.ac.uk

+44 (0)20 7594 3197

Data-driven approaches for systems biology

The complex interactions that influence human health are a challenging yet fundamental part of modern medicine. Understanding such complexity is therefore great importance to our ability to advance clinical practice, public health, drug development and environmental assessment.

Top-down systems biology approaches have been proposed as an efficient means of gaining a better understanding of how these various factors interact by considering global profiles that describe various level of biological organisation an complexity, including genes, proteins and metabolites.

By studying systemic responses, these top-down approaches can efficiently provide an overview of complex, multi-stage processes that are displaced in time and/or space.


Find out more about our key focus areas:

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Personalised Healthcare

Many pharmaceuticals have idiosyncratic action when administered. The concept that healthcare solutions can be tailored to the individual is one that is attractive as it potentially allows a better match of patient and drug. Identifying signatures indicative of treatment outcome are key to personalising medicine. Top-down systems biology offers an opportunity to help predict drug efficiacy and avoid adverse reactions. Providing optimised healthcare on an individual basis will benefit both patients and clinicians through improved drug choice, efficacy and reduced costs. From the work we have conducted using large scales molecular epidemiology studies using metabolic phenotyping, it is clearer than ever before that a one-size-fits-all solution to drug therapy is not a sustainable or desirable model. Given the diversity of human biochemistry, such phenotypes are important in personalising medicine as they provide clues as to the influences of a variety of factors including underlying genetics, environmental stress, nutritional status and gut microbial activity.

We have shown that is possible to use predose metabolic profiles to predict xenobiotic metabolic outcomes in both experimental animals and humans in what has been termed “pharmacometabonomics” :

“the prediction of the drug metabolism and toxicity in an individual using a mathematical model of preintervention metabolite signatures”

Clayton et al. (2006).

This has huge implications for optimising drug treatment as it will allow patient stratification and the identification of non- and hyper-responsive individuals, and provides a complementary approach to that of pharmacogenomics.

Strat Med

Molecular Phenotyping

Metabonomic approaches have major application in epidemiological research. that open up the possibility of testing epidemiologically generated hypotheses at the cellular and physiological level, with discovery of novel metabolic biomarkers that link to environmental exposures and phenotypic traits. Integrating individual-level molecular profiles within small-area and large-scale population epidemiological studies promises to provide new insight into the environmental and lifestyle factors that influences high-priority diseases such as hypertension, diabetes and cancer. Metabolic profiling provides the opportunity to identify biomarkers of exposure, early effect, early onset and disease progression, and to generate hypotheses about how physiological measurements routinely collected in epidemiological studies are mechanistically related to metabolic phenotype. CSM researchers have used large-scale epidemiological sample sets to clearly demonstrate the metabolic phenotypic clustering by geographical location, and that variation within populations can be meaningfully related to physiological measurements (Holmes et al. 2008). This work has helped derive novel associations between urinary metabolites and blood pressure that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships. Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007). Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.

CSM researchers have used large-scale epidemiological sample sets to clearly demonstrate the metabolic phenotypic clustering by geographical location, and that variation within populations can be meaningfully related to physiological measurements (Holmes et al. 2008). This work has helped derive novel associations between urinary metabolites and blood pressure that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships. Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007). Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.

SampleJet

Metabolic profiling provides the opportunity to identify biomarkers of exposure, early effect, early onset and disease progression, and to generate hypotheses about how physiological measurements routinely collected in epidemiological studies are mechanistically related to metabolic phenotype. e have used large-scale epidemiological sample sets to clearly demonstrate the metabolic phenotypic clustering by geographical location, and that variation within populations can be meaningfully related to physiological measurements (Holmes et al. 2008). This work has helped derive novel associations between urinary metabolites and blood pressure that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships. Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007). Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.

This work has helped derive novel associations between urinary metabolites and blood pressure that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships. Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007). Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.

Tubes

We have used large-scale epidemiological sample sets to clearly demonstrate the metabolic phenotypic clustering by geographical location, and that variation within populations can be meaningfully related to physiological measurements (Holmes et al. 2008). This work has helped derive novel associations between urinary metabolites and blood pressure that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships.Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. 

The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007). Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.

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  • JOURNAL ARTICLE
    Biggs MB, Medlock GL, Moutinho TJ, Lees HJ, Swann JR, Kolling GL, Papin JAet al.,

    Systems-level metabolism of the Altered Schaedler Flora, a complete gut microbiota

    , ISME Journal, ISSN: 1751-7362

    The Altered Schaedler Flora (ASF) is a model microbial community with both in vivo and in vitro relevance. Here we provide the first characterization of the ASF community in vitro, independent of a murine host. We compared the functional genetic content of the ASF to wild murine metagenomes and found that the ASF functionally represents wild microbiomes better than random consortia of similar taxonomic composition. We developed a chemically-defined medium that supported growth of seven of the eight ASF members. To elucidate the metabolic capabilities of these ASF species—including potential for interactions such as cross feeding—we performed a spent media screen and analyzed the results through dynamic growth measurements and non-targeted metabolic profiling. We found that cross-feeding is relatively rare (32 of 3 570 possible cases), but is enriched between Clostridium ASF356 and Parabacteroides ASF519. We identified many cases of emergent metabolism (856 of 3 570 possible cases). These data will inform efforts to understand ASF dynamics and spatial distribution in vivo, to design pre- and probiotics that modulate relative abundances of ASF members, and will be essential for validating computational models of ASF metabolism. Well-characterized, experimentally tractable microbial communities enable research that can translate into more effective microbiome-targeted therapies to improve human health.

  • CONFERENCE PAPER
    Li JV,

    Metabonomics in Clinical Research

    , International Conference on Genomics
  • CONFERENCE PAPER
    Li JV,

    Short-term reciprocal diet exchanges impact colonic fermentation and hydrogenotrophic microbiota for native Africans consuming a typical Western diet and African Americans consuming a traditional African diet

    , Digestive Disease Week
  • JOURNAL ARTICLE
    Mayneris-Perxachs J, Bolick DT, Leng J, Medlock GL, Kolling GL, Papin JA, Swann JR, Guerrant RLet al.,

    Protein and zinc deficient diets modulate the murine microbiome and metabolic phenotype

    , American Journal of Clinical Nutrition, ISSN: 1938-3207

    Background: Environmental enteropathy, linked to undernutrition and chronic infections, affects the physical and mental growth of children in developing areas worldwide. Key to understanding how these factors combine to shape developmental outcomes is first understanding the effects of nutritional deficiencies on the mammalian system, including the effect on the gut microbiota.Objective: We dissect the nutritional components of environmental enteropathy by analyzing the specific metabolic and gut microbiota changes that occur in weaned mouse models of zinc or protein deficiency as compared to well-nourished controls. Design: Using a 1H NMR spectroscopy-based metabolic profiling approach with matching 16S microbiota analyses, the metabolic consequences and specific effects on the fecal microbiota of protein and zinc deficiency were probed independently in a murine model.Results: We find considerable shifts within the intestinal microbiota 14-24d post-weaning in mice maintained on a normal diet (including increases in Proteobacteria and striking decreases in Bacterioidetes). While the zinc deficient microbiota were comparable to the age-matched well-nourished profile, the protein-restricted microbiota remained closer in composition to the weaned enterotype with retention of Bacteroidetes. Striking increases in Verrucomicrobia (predominantly Akkermansia muciniphila) were observed in both well-nourished and protein-deficient mice 14d post-weaning. We find that protein malnutrition impairs growth and has major metabolic consequences (much more than zinc deficiency) that include altered energy, polyamine and purine/pyrimidine metabolism. Consistent with major changes in the gut microbiota, reductions in microbial proteolysis and increases in microbial dietary choline processing were observed.

  • JOURNAL ARTICLE
    Alexander J, Gildea L, Balog J, Speller A, McKenzie J, Muirhead L, Scott A, Kontovounisios C, Rasheed S, Teare J, Hoare J, Veselkov K, Goldin R, Tekkis P, Darzi A, Nicholson J, Kinross J, Takats Zet al., 2017,

    A novel methodology for in vivo endoscopic phenotyping of colorectal cancer based on real-time analysis of the mucosal lipidome: a prospective observational study of the iKnife

    , SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES, Vol: 31, Pages: 1361-1370, ISSN: 0930-2794

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

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