1. Konstantinos Thalassinos
Science City Away Day
Konstantinos Thalassinos

2. Education and employment
BSc Genetics
University of Leicester
MRes Bioinformatics
University of York
PhD Mass Spectrometry-Based Proteomics and Computational Proteomics
University of Warwick, CASE Award ICI
Welcome VIP Fellowship
Postdoctoral Fellow

3. Research to date Instrumentation (Mass Spectrometry) Computation
Life Sciences
Materials

4. Research to date
Instrumentation
(Mass Spectrometry)
Development of a new shape- selective mass spectrometer
Collaboration with Waters Corp.
More than 200 instruments have been sold to date
Pringle, S. D., Giles, K., Wildgoose, J. L., Williams, J. P., Slade, S. E., Thalassinos, K., et al., (2007) International Journal of Mass Spectrometry 261: 1-12.
Thalassinos, K., Slade, S. E., Jennings, K. R., et al., (2004) International Journal of Mass Spectrometry 236:
Thalassinos, K. and Scrivens, J. H. Applications of Travelling-Wave Ion Mobility Mass Spectrometry. Chapter in Practical Aspects of Ion Trap Mass Spectrometry Volume 5, edited by R. E. March and J. F. J. Todd

5. Research to date
Protein structure using ion mobility mass spectrometry
TSE diagnostics (Prion diseases)
Life Sciences
Wyttenbach, T., Grabenauer, M., Thalassinos, K., et al., (Accepted). Journal of Physical Chemistry B
Scarff, C. A., Patel, V. J., Thalassinos, K., Scrivens, J. H. (2009). Journal of the American Society for Mass Spectrometry 20:
Leary, J. A., Schenauer, M. R., Stefanescu, R., Andaya, A., Ruotolo, B., Robinson, C. V., Thalassinos, K., et al., (2009) Journal of the American Society for Mass Spectrometry 20:
Scarff, C. A., Thalassinos, K., Hilton, G. R. and Scrivens, J. H. (2008). Rapid Communications in Mass Spectrometry 22:

6. Research to date Mass spectrometry-based proteomics
Post-translational modifications
Life Sciences
Patel, V. J.$, Thalassinos, K.$, Slade, S. E., et al., (2009) Journal of Proteome Research 8: 3752–3759. $Joint first author
Thalassinos, K., Grabenauer, M., Slade, S. E., et al., (2009) Analytical Chemistry 81: 248–254.
Clokie, M. R.$, Thalassinos, K.$, Boulanger, P., et al., (2008) Microbiology 154: $Joint first author

7. Research to date
Characterisation of synthetic macromolecular structure using:
Novel instrumentation
Alternative ionisation methods
Newly-developed software
Materials
Jackson, A. T., Slade, S. E., Thalassinos, K. and Scrivens, J. H. (2008). Analytical and Bioanalytical Chemistry 392:
Hilton, G. R., Jackson, A. T., Thalassinos, K. and Scrivens, J. H. (2008). Analytical Chemistry 80:
Thalassinos, K., Jackson, A. T., et al., (2007). Journal of the American Society for Mass Spectrometry 18:
Williams, J. P., Hilton, G. R., Thalassinos, K., et al., (2007). Rapid Communications in Mass Spectrometry 21:

8. Research to date Diagnosis of hemoglobinopathies
Creation of a framework to manage diverse proteomics datasets
Collaboration with Beckman Coulter
Proteomics data mining
Polymer microstructure
Cross sectional modelling / Protein structure
Computation

9. Current Research Themes
Creation of a computational infrastructure for the implementation of a mass spectrometry-based approach to hemoglobin disorder diagnosis.
Development of a framework to manage mass spectrometry-generated proteomic data from biomarker discovery programmes.
Protein conformational studies using ion mobility mass spectrometry.

10. Hemoglobinopathy diagnosis
Mass spectrometry offers
Unambiguous identification of all single point mutations including novel variants
Indication of β thalassemia trait via quantitation of A2 peak
Indication of level of glycosylation
In order for mass spectrometry to be used in a clinical setting there is a requirement for automating the interpretation of the data generated
I have developed a prototype program to perform this task
Test the program in a clinical trial
Implement the approach in a clinical setting

11. Biomarker discovery
Clinical proteomics and metabolomics data can be used to:
Identify biomarkers to be used for the diagnosis of a disease
Monitor disease progress
Monitor response to treatment
Managing and integrating the large amounts of data generated is key to:
Using data mining approaches for the discovery of biomarkers
Developing predictive statistical models, with high sensitivity and specificity for disease diagnosis
Generating ‘systems’ models to be used for
creating testable hypotheses

12. Protein conformation Protein conformation is key to function
Protein folding, interaction with ligands, and interactions with other proteins is important in a number of disease states
Protein misfolding diseases
Advantages of ion mobility mass spectrometry
Sensitivity
Speed
Low sample requirements
Can distinguish between co-existing forms of a protein
Monitoring and separation of distinct
conformational families co-existing in solution