My Neuroproteomics team aims to (1) describe the protein complex nano-machinery that underlies synapse function and plasticity, and (2) reveal the alteration of synapse/tissue proteomes in cases of neuro-degenerative and neuropsychiatric disorders. Mass spectrometry based quantitative proteomics analysis is the leading technology behind these studies.
Abnormalities in neuronal activity and synaptic dysfunction are known to underlie a large number of brain disorders, including neurodegenerative and psychiatric disorders. Classic approach to study brain function and/or disorders often focus on single or a few proteins. This fails to capture that protein function depends primarily on the coordination of extended series of molecular events. Using advanced quantitative proteomics we are now in a position to examine the global changes of proteins in a biological system of interest.
In my team I apply state-of-the-art proteomics techniques to study brain function and/ or disorders. Specifically, I use (1) expression proteomics to reveal the alteration of protein expression patterns of a particular sample type under different conditions, and (2) functional proteomics to examine the constituents of protein complexes to understand how multi-protein complexes drive physiological processes.
My main focus is on animal models of disease in which I focus mainly on synapse, the organelle that governs the majority of communication, information processing and storage in the brain. For human post-mortem tissues, I opt for total tissue analysis to accommodate the unforeseeable changes in for example non-neuronal cell types and extracellular proteins. The sample types for proteomics are diverse. Main sources are mouse brain regions (in particular, hippocampus and cerebellum), primary neuronal cell cultures, human post-mortem brain tissues from patients, and iPSC cells. Species include mouse, rat, monkey, fly and worms.
Proteomics workflow
The proteomics workflow is evolving rapidly. At this moment we use mainly SWATH (Data Independent Analysis) for quantitative proteomics, with Data Dependent Analysis (DDA) for specific samples that do not have spectral library. For interaction proteomics we use classic immunoprecipitation-based method to capture the protein complexes that then are subjected to treatment of filter-aided sample preparation (FASP), and finally analysed with DDA. Currently we perform proteomics experiments with LTQ-Orbitrap and TripleTof Mass spectrometers.
Among the ongoing projects of the Neuroproteomics team:
• Global analysis of synaptic protein complexes. We pursue large-scale interaction proteomics to map the synaptic protein interactome. This provides insight into the nano-machineries in the synapse that underlie neurotransmission and neuroplasticity.
• We identify proteins of the GluA and GABAA receptor interactome, which aids functional analysis of novel interactions. We are molecularly dissecting the sub-complexes of AMPA receptor using blue-native gel electrophoresis-mass spectrometry, which is followed by super-resolution microscopy and HEK cell co-expression.
• We are mapping the interactors of proteins that were genetically implicated in psychiatric disorders, especially schizophrenia and autism spectrum disorders.
• We downscale analyses in the human postmortem brain to resolve ongoing mechanisms of disease in frontal temporal lobe dementia (FTD) and Alzheimer’s Disease (AD) and healthy cognitive aging.
• We are putting effort in various collaborative projects in which proteomics analysis can make a difference in scientific discovery.
Pioneer researches in peptidomics/proteomics, selected articles
– Direct peptide profiling by mass spectrometry of single identified neurons reveals complex neuropeptide-processing pattern. Li KW, Hoek RM, Smith F, Jiménez CR, van der Schors RC, van Veelen PA, Chen S, van der Greef J, Parish DC, Benjamin PR, et al. J Biol Chem. 1994 Dec 2;269(48):30288-92.
– Pattern changes of pituitary peptides in rat after salt-loading as detected by means of direct, semiquantitative mass spectrometric profiling. Jiménez CR, Li KW, Dreisewerd K, Mansvelder HD, Brussaard AB, Reinhold BB, Van der Schors RC, Karas M, Hillenkamp F, Burbach JP, Costello CE,Geraerts WP. Proc Natl Acad Sci U S A. 1997 Aug 19;94(17):9481-6
– Proteomics analysis of rat brain postsynaptic density. Implications of the diverse protein functional groups for the integration of synaptic physiology. Li KW, Hornshaw MP, Van Der Schors RC, Watson R, Tate S, Casetta B, Jimenez CR, Gouwenberg Y, Gundelfinger ED, Smalla KH, Smit AB. J Biol Chem. 2004 Jan 9;279(2):987-1002
– Differential transport and local translation of cytoskeletal, injury-response, and neurodegeneration protein mRNAs in axons. Li KW, Willis D, Zheng JQ, Chang JH, Smit AB, Kelly T, Merianda TT, Sylvester J, van Minnen J, Twiss JL. J Neurosci. 2005 Jan 26;25(4):778-91
Book
Neuroproteomics, (Neuromethods, Vol.57 Springer protocols), 2011, 318 pp.
Ka wan Li (editor)
To view complete list of my publication (>150), please visit researchgate for details.