NEW YORK (GenomeWeb) – A team from the University of Edinburgh has profiled the postsynaptic proteome of several regions of the human neocortex.
In a study published this week in Nature Neuroscience, the researchers identified 1,213 proteins across twelve regions of the neocortex identifying both a core set of proteins that appear common to the different regions analyzed as well as differences in protein expression between these regions.
They also used the proteomic data to link fMRI data and GWAS data, showing in a proof-of-principle experiment that genomic and fMRI analysis identified the same cortical region as linked to smoking behavior.
The project is part of an ongoing effort to improve proteomic coverage of the human brain, said Seth Grant, professor of molecular neuroscience at University of Edinburgh and senior author on the paper.
Grant's work on the proteomics of synapses dates back to 2000 when he and his colleagues performed one of the first proteomic analyses of these structures, finding an unexpected depth and complexity to their protein content.
"People thought for quite a few years that synaptic transmission and plasticity were mediated by just a handful of proteins when in fact there is a very large number of proteins there, and we know that a lot of those proteins are very important for aspects of behavior and the physiology of the synapse," Grant said. "That complexity is very important, and proteomics was responsible for opening that up."
While much of the initial brain proteome work was done in mice, Grant and his colleagues published in 2010 a Nature Neuroscience study looking at the postsynaptic proteome in humans. In that work they identified more than 1,400 proteins, including proteins linked to more than 130 brain diseases.
This indicated that the synapse might be much more involved in brain pathologies than previously thought, he said. "If you go back into medical textbooks of only a few years ago what you'll discover is that synapses have nothing to do with brain disease in those books. But now [it's thought] they have everything to do with brain disease because a huge number of [disease-linked] mutations disrupt synaptic proteins."
In their study out this week, Grant and his colleagues aimed to develop a map of the human synapse proteome, characterizing the distinct proteomic profiles of synapses in different parts of the brain.
"In general, we think of synapses like excitatory and inhibitory synapses as basically the same all over the brain," he said. "But that is completely wrong. There is, in fact, tremendous variation in the individual synapses, there is terrific diversity of them."
The researchers approached this question by analyzing the postsynaptic proteome of 12 different brain Brodmann areas (Bas). These areas are regions of the cerebral cortex defined more than a century ago by German neurologist Korbinian Brodmann.
"Different nerve cells have different morphologies in different parts of the brain," Grant said, noting that Brodmann divided regions of the cortex in BAs based on their differing cellular architecture. Use of these divisions continues into the present day with specific brain function and behaviors linked to different BAs.
The Edinburgh researchers used mass spec analysis on a Thermo Fisher Scientific Q Exactive instrument to profile 12 different BAs in a total of 48 samples taken from four normal brains. Of the 1,213 proteins they identified, 27 appeared to be conserved across all 12 regions, indicating that they are core components key to function of the postsynaptic region across the human neocortex.
Investigating differences in the postsynaptic proteomes of these different regions, they found that each BA had a distinct protein signature and that the distribution of multiprotein complexes and signaling networks are different across different brain regions.
In addition to providing a molecular underpinning to existing understandings of brain structure, this proteomic data also allowed the researchers to link molecular information like GWAS data to imaging studies based on methods like fMRI, Grant said.
Researchers have performed GWAS analysis looking at a wide range of neurological diseases and behaviors. They have likewise done extensive fMRI studies looking at what specific regions of the brain are activated under different conditions or while subjects are performing different tasks.
However, Grant noted, it has been difficult to establish a link between this genetic information and brain structural and regional information.
"From the brain imaging data you might be able to say, look Broadman area nine is important in [for instance] smoking behavior," he said. "And then you have the GWAS data [showing genes implicated in smoking]. But nobody knows how they are connected."
With the proteomic data, the researchers can look to see if proteins produced by the genes identified as linked to smoking by the GWAS data are differentially expressed in the brain regions identified as important by the fMRI data, thus providing a link between the two.
Using smoking behavior as a proof of principle, Grant and his colleagues showed that they were, in fact, able to link genes identified via four previous GWAS studies as involved in smoking behavior to BA 9, which fMRI and PET imaging studies have found are involved in smoking and substance abuse.
Grant said this finding suggest the potential of such an approach and noted that there are vast quantities of GWAS and fMRI data that could be similarly analyzed.
However, he said, his primary interest moving forward is improving proteome coverage of the postsynaptic region, both in normal and diseased brains.
While the recent study looked at differences in postsynaptic proteomes across 12 different BAs, this analysis could be sliced much more finely, Grant said.
"I think there is a pressing need to do much more systematic human brain proteomic studies," he said. "Our maps are incomplete. They need to be improved both in coverage and also in resolution. We could subdivide the neocortex into many more smaller pieces and do very detailed proteomics in each."
"The samples [in the Nature Neuroscience study] reflect populations of synapses," he said. "There are many thousands if not millions of synapses in any one of our samples. But synapses individually also have synaptic diversity. So I think a fantastic challenge… is to have really high-sensitivity [methods] that can be used with extremely limited samples, ideally at the level of individual synapses."