Research Activities

Liquid extraction surface analysis (LESA)

LESA is an exciting new tool that enables the direct analysis of metabolites/proteins/lipids from biological samples such as thin tissue sections, dried blood spots and bacterial colonies growing on agar. During LESA, analytes are extracted via a liquid microjunction before being injected into the mass spectrometer via nanoelectrospray ionisation. As extraction occurs at defined locations, LESA may be used for spatial profiling of analytes.  Traditional mass spectrometry techniques require sample pre-treatment that can be time consuming. Research on-going in the Cooper lab has shown that LESA can offer the potential to circumvent this labour intensive sample preparation procedure, enabling protein analysis to be performed directly from biological samples within minutes.

For more information, please refer to Professor Helen Cooper's academic profile

Ion Mobility Spectrometry (IMS)

At Birmingham, research is on-going into the use of ion mobility spectrometry (IMS) to study proteins. In particular, our research focuses on FAIMS (high field asymmetric waveform IMS) which is also known as differential IMS (DMS). FAIMS adds an additional level of separation prior to MS analysis, improving signal-to-noise, reducing chemical noise, and separating isomers. More recently, we have been using traveling wave ion mobility spectrometry (TWIMS) to study protein conformation.

Research in the Cooper lab uses FAIMS and TWIMS, in combination with LESA, to study proteins directly from biological substrates. FAIMS enables the separation of proteins from interfering ions, thus improving the number of proteins we can detect and image. TWIMS enables us to obtain information on the 3-D structure of proteins. We have also coupled FAIMS with proteomics, enabling detection of previously unobserved peptides.

For more information, please refer to Professor Helen Cooper's academic profile

Native Mass Spectrometry

Native mass spectrometry (native MS) refers to the analysis of proteins and protein complexes under non-denaturing conditions. Native MS can, therefore, provide information on the nature of non-covalent protein interactions including information on subunit stoichiometry, binding affinity, subunit topology and sample heterogeneity. The School of Biosciences is currently using native MS to solve a variety of fascinating biological problems.

Proteomics

  • Dr Cunningham is an expert in the use of quantitative proteomics techniques to characterise regulatory phosphorylation events and protein-protein interactions that occur during cell signalling. Current projects include characterisation of aberrant signalling events in cancer cells reliant on growth factor signalling for survival, and regulation of cellular metabolism by LAR tyrosine phosphatase.

    For more information, please refer to Dr Debbie Cunningham's academic profile
  • Dr Grant, within the periodontal research group at the University, is using mass spectrometry based clinical proteomics to: discover biomarkers in oral fluids, such as saliva, for disease detection, particularly periodontitis; understand the changes in peripheral blood neutrophils in healthy and diseased mammals, including humans; and explore protein post translational modifications. The work has given rise to ten patents and several publications over the last decade.

    For more information, please refer to Dr Melissa Grant's academic profile
  • Dr Leney’s research focus on the combined use of proteomics and native mass spectrometry to study protein post translational modifications. Her research interests focus on the post translational modification crosstalk that exists when proteins are modified by multiple, different post translational modifications. Indeed, understanding crosstalk is crucial to unravel how cells communicate or more importantly why cells misfunction in the case of disease.

  • Dr Heath studies Receptor Kinase-mediated signal transduction pathways in cancer using both discovery (SILAC) and targeted (SRM and RPM) phospho-proteomics techniques. The data are used to build executable computer models to predict the consequences of drug interventions.

    For more information, please refer to Professor John Heath's academic profile