Proteomics of multiprotein complexes: answering fundamental questions in neuroscience

Cell-type-specific visualisation and biochemical isolation of endogenous synaptic proteins in mice

In recent years, the remarkable molecular complexity of synapses has been revealed, with over 1,000 proteins identified in the synapse proteome. Although it is known that different receptors and other synaptic proteins are present in different types of neurons, the extent of synapse diversity across the brain is largely unknown. This is mainly due to the limitations of current techniques. Here, we report an efficient method for the purification of synaptic protein complexes, fusing a high‐affinity tag to endogenous PSD95 in specific cell types. We also developed a strategy, which enables the visualisation of endogenous PSD95 with fluorescent‐protein tag in Cre‐recombinase‐expressing cells. We demonstrate the feasibility of proteomic analysis of synaptic protein complexes and visualisation of these in specific cell types. We find that the composition of PSD95 complexes purified from specific cell types differs from those extracted from tissues with diverse cellular composition. The results suggest that there might be differential interactions in the PSD95 complexes in different brain regions. We have detected differentially interacting proteins by comparing data sets from the whole hippocampus and the CA3 subfield of the hippocampus. Therefore, these novel conditional PSD95 tagging lines will not only serve as powerful tools for precisely dissecting synapse diversity in specific brain regions and subsets of neuronal cells, but also provide an opportunity to better understand brain region‐ and cell‐type‐specific alterations associated with various psychiatric/neurological diseases. These newly developed conditional gene tagging methods can be applied to many different synaptic proteins and will facilitate research on the molecular complexity of synapses.

Pathway Proteomics and Chemical Proteomics Team Up in Drug Discovery

Over the last 5 years, impressive technical advances in mass spectrometry-based analysis of proteins have enabled the parallel analysis of subproteomes and entire proteomes, thus triggering the departure from the traditional single gene-single protein-single target paradigm. Today, immunoaffinity chromatography as well as generic purification methods employing engineered composite affinity tags make streamlined identification of protein complexes as molecular machines possible. In addition, use of stable isotope techniques in protein mass spectrometry allows for the characterization of protein complex composition and posttranslational modifications in an increasingly quantitative fashion. Together, these methodologies allow the elucidation of medically relevant biological pathways, and the study of the interaction of their protein components with therapeutic agents, on a much larger scale. The present review discusses some of the current experimental strategies, with a focus on applications in neurobiology.

Application of proteomics technologies in the investigation of the brain

Approximately 30-50% of the genes in mammals are expressed in the nervous system. A differential expression of genes in distinct patterns is necessary for the generation of the large variety of neuronal phenotypes. Proteomic analysis of brain compartments may be useful to understand the complexity, to investigate disorders of the central nervous system, and to search for corresponding early markers. Up to now, proteomics has mainly studied the identity and levels of the abundant human, rat, and mouse brain proteins as well as changes of their levels and the modifications that result from various neurological disorders, like Alzheimer's disease and Down's syndrome in humans and in animal models of those diseases. The proteins, for which altered levels in these disorders have been observed, exert mainly neurotransmission, guidance, and signal-transduction functions, or are involved in detoxification, metabolism, and conformational changes. Some of those proteins may be potential drug targets. Further improvement of proteomics technologies to increase sensitivity and efficiency of detection of certain protein classes is necessary for a more detailed analysis of the brain proteome. In this review, a description of the proteomics technologies applied in the investigation of the brain, the major findings that resulted from their application, and the potential and limitations of the current technologies are discussed.

Application of proteomics technology to the field of neurotrauma

Near-completion of the Human Genome Project has stimulated scientists to begin looking for the next step in unraveling normal and abnormal functions within biological systems. Consequently, there is new focus on the role of proteins in these processes. Proteomics is a burgeoning field that may provide a valuable approach to evaluate the post-traumatic central nervous system (CNS). Although we cannot provide a comprehensive assessment of all methods for protein analysis, this report summarizes some of the newer proteomic technologies that have propelled this field into the limelight and that are available to most researchers in neurotrauma. Three technical approaches (two-dimensional gel electrophoresis, direct analysis by mass spectrometry, including two-dimensional chromatography coupled to mass spectrometry and isotope coded affinity tags, and antibody technologies) are reviewed, and their advantages and disadvantages presented. A discussion of proteomic technology in the context of brain and spinal cord trauma follows, addressing current and future challenges. Proteomics will likely be very useful for developing diagnostic predictors after CNS injury and for mapping changes in proteins after injury in order to identify new therapeutic targets. Neurotrauma results in complex alterations to the biological systems within the nervous system, and these changes evolve over time. Exploration of the "new nervous system" that follows injury will require methods that can both fully assess and simplify this complexity.