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Leishrisk, Bridging Research and Leishmanianis Control

Leishrisk, Bridging Research and Leishmanianis Control

GeMInI 
 

 

GeMInI: the Genome and Metabolome Integrated Initiative


Abstract
Participating Investigators and Contact
Background, state of the art and main objectives
Specific objectives and Work Packages
References
GeMInI publications

 


ABSTRACT

From genome to the field: a global study of pathogen genetic and metabolic diversity and its relationship to clinical phenotypes

Characterising the diversity of pathogen populations is a major key for understanding the clinical polymorphism of infectious diseases. The past 2 years have brought new technologies that may revolutionise this field of research as they bring unprecedented potential for global pathogen exploration. On one hand, economic high-throughput sequencing technologies allow whole genome comparative analyses of multiple strains of a given species. On the other hand, advances in mass-spectrometry facilitate comprehensive metabolite profiling, hereby providing access to the ultimate expression of an organism’s genotype, the closest correlate to the phenotype. The integration of the new genome and metabolome technologies offer an unparalleled source of data, but its exploitation for an effective translation to health problems require alliances between the high-tech specialised centres currently developing the new technologies and institutions engaged in the field, at the front of infectious diseases.

GeMInI is an initiative of the Institute of Tropical Medicine of Antwerp, Belgium (ITM). We propose to build at ITM a multidisciplinary research platform with a holistic perception of diversity, equipped to analyse and interpret the massive data output of genome and metabolome studies. The prototype platform will be built in collaboration with BP Koirala Institute of Health Sciences (Nepal), Sanger Institute (UK), Strathclyde University (UK), University of Antwerp (Belgium) and Groningen University (NL). It will be validated using as paradigm treatment failure in visceral leishmaniasis and drug resistance in Leishmania donovani. Isolates from our previous clinical studies in Nepal will be submitted to genome- and metabolome-wide comparisons, and genetic and metabolic signatures associated with various drug resistance phenotypes will be identified, interpreted and validated. Our platform aims to interact with similar initiatives targeting other pathogens or the human host. GeMInI is expected to have a major impact by boosting post-genomic translational research in general, but also more specifically by bridging research and control of neglected diseases.
 
 
1. Participating investigators and contact
 
Official contact: sdecuypere@itg.be

Coordinators
Dujardin, Jean Claude Head of Molecular Parasitology Unit, Institute of Tropical Medicine
Nationalestraat, 155; B-2000 Antwerpen, Belgium
Phone: +32(0)32476358
Email: jcdujardin@itg.be
Decuypere, Saskia Molecular Parasitology Unit, Institute of Tropical Medicine
Nationalestraat, 155; B-2000 Antwerpen, Belgium
Phone: +32(0)32476586
email: sdecuypere@itg.be
Partners
Berriman, Matt Project Manager, Pathogen sequencing unit, Wellcome Trust Sanger Institute (WTSI)
Wellcome Trust Genome Campus, Cambridge CB10 1SA, UK
phone: + 44 (0)1223 834244
email: mb4@sanger.ac.uk
Hertz-Fowler, Christiane Project Manager, Pathogen Genomics, WTSI
Wellcome Trust Genome Campus, Cambridge CB10 1SA, UK
phone: + 44 (0)1223 834244 email: chf@sanger.ac.uk
Coombs, Graham Head of the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), University of Strathclyde
University of Strathclyde, SIPBS, Taylor street, Glasgow G40NR, UK
Phone: +44(0)1415482155
email: graham.coombs@strath.ac.uk
Watson, David Head of pharmaceutical analysis and toxicology group of SIPBS, University of Strathclyde
University of Strathclyde, SIPBS, Taylor street, Glasgow G40NR, UK
phone: +44(0)1415482651
email: D.G.Watson@strath.ac.uk
Sobott, Frank PI CeProMa, University of Antwerp
University of Antwerp, CeProMa, Groenenborgerlaan 171, Antwerpen 2020, Belgium
phone: +32(0)32653697
email: Frank.Sobott@ua.ac.be
Witters, Erwin Proteomics unit VITO/CeProMa, University of Antwerp
University of Antwerp, CeProMa, Groenenborgerlaan 171, Antwerpen 2020, Belgium
phone: +32(0)32653697
email: erwin.witters@ua.ac.be
Breitling, Rainer Assistant Professor, Groningen Bioinformatics Centre, Rijksuniversiteit Groningen (RUG)
University of Groningen, Kerklaan 30, 9751NN Haren, The Netherlands
Phone: +31-50-363-8088
Rijal, Suman Head of Tropical and Infectious Diseases Unit, BP Koirala Institute of Health Sciences (BPKIHS)
BPKIHS
Dharan, Nepal
phone: +977 25525668
email: sumanrijal2@yahoo.com
Post-Docs
Imamura, Hideo
Molecular Parasitology Unit, Institute of Tropical Medicine
(Genomics)
Nationalestraat, 155; B-2000 Antwerpen, Belgium
Phone: +32(0)32470794
Email: himamura@itg.be or hi1@sanger.ac.uk
Mannaert, An
Molecular Parasitology Unit, Institute of Tropical Medicine
(Genomics)
Nationalestraat, 155; B-2000 Antwerpen, Belgium
Phone: +32(0)32470794
Email: amannaert@itg.be
Berg, Maya
Molecular Parasitology Unit, Institute of Tropical Medicine
(Metabolomics)
Nationalestraat, 155; B-2000 Antwerpen, Belgium
Phone: +32(0)32470794
Email: mberg@itg.be
 
 
2. Background, state of the art and main objectives
 
The challenge: clinical polymorphism vs pathogen genetic polymorphism.

Every day, health professionals are confronted with the clinical polymorphism of infectious diseases. This polymorphism results from the interaction between several actors (including host, pathogen and vector) and integrated studies are needed to explore their relative role. However, such integrated explorations need to be preceded by studies establishing the diversity baseline of each component in a clinical context. With respect to pathogens, most studies relating genetic and phenotypic diversity done so far were considering only limited sets of characters. These hypothesis-driven approaches lead to understanding parts of the jigsaw, but are too limited to conjure up the whole biological picture1,2. Very recently, dramatic technological advances opened doors for comprehensive whole system molecular studies using genomics, transcriptomics, proteomics and metabolomics. Now, the major challenge is to integrate and apply this new generation of analytical techniques to tackle pressing biological and clinical issues. Here we will address the pathogen genetic/phenotypic diversity question by developing an analytical research platform that integrates comprehensive pathogen studies, from genome to metabolome, to study the role of the pathogen’s genetic diversity in clinical polymorphism. Such a platform aims in the long-term to interact with similar initiatives targeting the human host.
 
The genome approach: overcoming past restrictions and addressing population diversity.

Genome sequencing has spearheaded a revolution in biological sciences and produced the reference genomes of many pathogens. For long this was restricted by technical and economic constraints to the study of one individual for each targeted pathogen. First reports on comparative analyses of multiple strains of a given species are very recent: initial surveys of genetic variation across the Plasmodium falciparum genome was published in 20073-5, demonstrating the potential use of genetic diversity maps in identifying genes related to specific traits and in understanding pathogen population structure. The arrival of new sequencing technologies that allow economic high-throughput parallel DNA sequencing (e.g. 8 microbial genomes in 1 run), will boost the exploration of population genetic diversity6. However, further technological and conceptual developments are needed if the genetic diversity of clinical phenotypes is to be dissected. More specifically, methods and models for sequence alignment and detection of genetic diversity elements need to be adapted to work optimally with the new sequence data-format. Furthermore, in order to fully understand the biological significance of whole genetic diversity in a population, the genome sequencing efforts need to be linked to comprehensive phenotype studies of the sequenced organisms.
 
The metabolome approach: lifting phenotyping from single-trait study to comprehensive response characterisation studies.

Pathogen phenotyping was until recently mostly limited to what can be observed in a controlled in vitro or in vivo environment. However, the arrival of comprehensive metabolite analytical methods is drastically changing the concept of phenotyping. The metabolome (the set of metabolites present in a biological system) lies downstream of the transcriptome, proteome and any post-translational events, and can be regarded as the ultimate expression of an organism’s genotype, the closest correlate to the phenotype7. Hence metabolome studies offer advantages over transcriptomics and proteomics as (i) the total effect of all post-transcriptional and post-translational events is captured by the metabolome, and (ii) the changes in the metabolome are amplified relative to changes in the transcriptome and proteome, which in general results in a higher sensitivity of metabolome studies1. Metabolome studies rely on the simultaneous quantitation and identification of thousands of metabolites in a biological sample. Current technologies allow rapid, accurate and precise whole metabolome profiling (=metabolite fingerprint) which can be used in subsequent metabolic signature analyses and biological sample classification. This metabolite fingerprint approach is already being explored in clinical phenotyping of human diseases from cancer to mental illness. For example, fingerprinting is used to identify metabolite signatures distinguishing good and poor drug-responders8. Similar to the genome sequencing component, metabolite fingerprint data is extensive and multi-dimensional, needing implementation of specialised mathematical, statistical and bioinformatic tools.
 
The paradigm: VL treatment failure and L. donovani drug resistance.

Leishmania parasites have a very diverse clinical expression, hence they represent an excellent model for exploring the power of the new techniques to identify pathogen genetic/phenotypic features and relate them to clinical phenotypes. Treatment failure in visceral leishmaniasis (VL) currently represents the most challenging issue from a public health perspective, and the most relevant for biological reasons. VL is a lethal condition if not adequately treated, and an increasing unresponsiveness to first line drugs such as antimonials and miltefosine, are jeopardising its control9,10. This issue could seriously disrupt the current target of Kala Azar elimination in the Indian sub-continent, hence drug resistance research is required to strengthen and sustain this international control program. Biologically, we have clear indications that phenotype diversity (in the form of in vitro drug resistance) of the causative agent L. donovani contributes to clinical VL treatment failure11. However, the current fragmentary knowledge (obtained with hypothesis-driven approaches) suggests natural drug resistance is a complex phenomenon. Natural resistance to antimonials (the most extensively studied so far) involves multiple genetic factors, and influences the general biology of the parasites, apparently making them more virulent12,13. Studying the diversity on whole genome and metabolome level in a natural population of L. donovani would (i) give us a global overview of factors involved (expected and unexpected) in drug resistance, (ii) give us an idea of how heterogeneous the adaptations of the different genetic subgroups are, (iii) enhance our understanding of parasite flexibility, and (iv) help in understanding the general biological and clinical behaviour of drug resistant parasites.
 
Strategic context and general aim of the study.

The new technologies mentioned above offer an unprecedented source of data, but its exploitation for an effective translation to health problems requires alliances between the high-tech specialized centres currently developing the new technologies and institutions engaged on the field, at the front of infectious diseases. The present project is embedded in such an alliance between ITM, BPKIHS and four world-leader groups, WTSI, SIPBS, UA and RUG. Our main scientific objective is to undertake a global analysis of genetic and metabolic diversity in L. donovani and explore its relevance for the understanding of clinical phenotypic diversity, using as paradigm treatment failure and drug resistance. For this purpose, we propose to build a cadre of ITM analysts close to the field, equipped to analyse, interpret and integrate the parasite data output of parallel DNA sequencing and metabolome analysis, with the matching clinical and epidemiological data. These analysts will collaborate closely with BPKIHS, WTSI, SIPBS, UA and RUG and the consecutive L. donovani platform will interact with similar initiatives just starting on other pathogens (Plasmodium, T. brucei, …), which should boost technological development per se and allow comparison of the different pathogen models. However, our platform will be unique through its anchoring in a broader existing network actively studying clinical and epidemiological aspects of VL in the Indian sub-continent (EU-funded project Kaladrug-R). This will guarantee bridging from genome to the field.
 

3. Specific objectives and work packages
 
Our specific objectives are to:
·         Select a sample of L. donovani strains representing clinical relevant drug susceptibility phenotypes.
·         Develop methods and models for genome-wide comparison of Leishmania strains.
·         Unravel the scale and nature of genetic diversity in L. donovani population and identify genetic signatures associated with drug resistance.
·         Develop methods and models for metabolome-wide comparison of Leishmania strains.
·         Highlight the metabolic pathways targeted by drugs and modified in drug resistant strains and identify metabolic signatures associated with various drug resistant phenotypes.
·         Interpret the biological significance of paired metabolic/genetic signatures marking each phenotypic parasite group and identify genomic/metabolic parasite factors associated with various clinical phenotypes.
·         Validate the identified parasite marker-clinical phenotype associations through a genotypic/metabolic screening of documented clinical samples.
 

4. References
  
      1.  Hollywood,K., Brison,D.R. & Goodacre,R. Metabolomics: current technologies and future trends. Proteomics. 6, 4716-4723 (2006).
      2.  Kaddurah-Daouk,R., Kristal,B.S. & Weinshilboum,R.M. Metabolomics: a global biochemical approach to drug response and disease. Annu. Rev. Pharmacol. Toxicol. 48, 653-683 (2008).
      3.  Jeffares,D.C. et al. Genome variation and evolution of the malaria parasite Plasmodium falciparum. Nat. Genet. 39, 120-125 (2007).
      4.  Mu,J. et al. Genome-wide variation and identification of vaccine targets in the Plasmodium falciparum genome. Nat. Genet. 39, 126-130 (2007).
      5.  Volkman,S.K. et al. A genome-wide map of diversity in Plasmodium falciparum. Nat. Genet. 39, 113-119 (2007).
      6.  Hall,N. Advanced sequencing technologies and their wider impact in microbiology. J Exp. Biol. 210, 1518-1525 (2007).
      7.  Steinfath,M., Groth,D., Lisec,J. & Selbig,J. Metabolite profile analysis: from raw data to regression and classification. Physiol Plant 132, 150-161 (2008).
      8.  Kaddurah-Daouk,R. et al. Metabolomic mapping of atypical antipsychotic effects in schizophrenia. Mol. Psychiatry 12, 934-945 (2007).
      9.  Chappuis,F. et al. Visceral leishmaniasis: what are the needs for diagnosis, treatment and control? Nat. Rev. Microbiol. 5, 873-882 (2007).
    10.  Sundar,S. & Chatterjee,M. Visceral leishmaniasis - current therapeutic modalities. Indian J. Med. Res. 123, 345-352 (2006).
    11.  Rijal,S. et al. Antimonial treatment of visceral leishmaniasis: are current in vitro susceptibility assays adequate for prognosis of in vivo therapy outcome? Microbes. Infect. 9, 529-535 (2007).
    12.  Carter,K.C. et al. Sodium stibogluconate resistance in Leishmania donovani correlates with greater tolerance to macrophage antileishmanial responses and trivalent antimony therapy. Parasitology 131, 747-757 (2005).
    13.  Decuypere,S. Antimonial treatment failure in anthroponotic visceral leishmaniasis: towards improved tools and strategies for epidemiological surveillance and disease control. Doctoral Thesis. 2007. University of Antwerp.
           
5. GeMInI publications
  
Dujardin, J.C. (2009) Structure, dynamics and function of Leishmania genome: resolving the puzzle of infection, genetics and evolution? IGE, 9(2):290-7 - abstract

t'Kindt R, Scheltema RA, Jankevics A, Brunker K, Rijal S, Dujardin JC, Breitling R, Watson DG, Coombs GH, Decuypere S. (2010) Metabolomics to unveil and understand phenotypic diversity between pathogen populations. PLoS Negl Trop Dis.  Nov 30;4(11):e904. - full text

t'Kindt R, Jankevics A, Scheltema RA, Zheng L, Watson DG, Dujardin JC, Breitling R, Coombs GH, Decuypere S. (2010) Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis. Anal Bioanal Chem. Nov;398(5):2059-69. Epub 2010 Sep 8. Erratum published in  Analytical and Bioanalytical Chemistry: Volume 400, Issue 2 (2011), Page 635 - abstract

Zheng L, T'Kind R, Decuypere S, von Freyend SJ, Coombs GH, Watson DG. (2010) Profiling of lipids in Leishmania donovani using hydrophilic interaction chromatography in combination with Fourier transform mass spectrometry. Rapid Commun Mass Spectrom. Jul 30;24(14):2074-82. PubMed PMID: 20552712. - abstract

Scheltema RA*, Decuypere S*, T'kindt R, Dujardin JC, Coombs GH, Breitling R. (2010) The potential of metabolomics for Leishmania research in the post-genomics era. Parasitology. Aug;137(9):1291-302. Epub 2010 Jan 29. ‘ (* equally contribution authors) - abstract

Jean-Claude Dujardin, Dolores González Pacanowska, Simon L. Croft, Ole F. Olesen, and Gerald F. Späth. (2010) Collaborative actions in anti-trypanosomatid chemotherapy with partners from disease endemic countries. Trends in Parasitology, 26: 395-403 - abstract

Scheltema R.A., Decuypere S., Dujardin JC, Watson D.G., Jansen R.C. and Breitling R. (2009)‘Simple data-reduction method for high-resolution LC-MS data in metabolomics’. Bioanalysis 1 (9): 1551-1557  - abstract

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