Proteomics and neuroscience round up
Proteomics is a growing field that can drive powerful new insights into everything from toxicology to the human brain. Indeed, proteomics applications in neuroscience are some of the most exciting areas of research, where increasingly powerful proteomics techniques are enabling scientists to link diseases to specific proteins and protein networks. This could help researchers identify new protein biomarkers for disease, as well as advance our understanding of the fundamental biology of Alzheimer’s disease and more.
In our applications of proteomics series, we recently profiled seven excellent examples of papers leveraging the proteome to investigate key questions in neuroscience. These papers identify hundreds of potential protein biomarkers, highlight the importance of combining genomics and proteomics, and shed light on the mechanisms of common neurodegenerative diseases. To read more in-depth synopses of these papers, click the links below. You can also find more insights into the incredible potential of proteomics in neuroscience research by reading our Proteomics and neuroscience eBook.
Watch this animation to learn how next-generation proteomics technologies can fuel neuroscience
Applications of proteomics in neuroscience – Proximity proteomics for the identification of axonal proteomes
Assessing the proteomes of axons, structures that allow neurons to communicate with each other, is difficult with traditional techniques. To study the axonal proteome, Dumrongprechachan et al. leveraged proximity proteomics, which uses specially engineered labeling proteins to tag nearby proteins in a location of interest. Tagged proteins can then be identified with a proteomic technique like mass spectrometry.
Using proximity proteomics, the researchers were able to identify proteins and post-translational modifications associated with axonal development. They also took their dataset a step further by finding associations between axonal proteins, protein activity, and the risk of neurological diseases like autism spectrum disorder, epilepsy, and Alzheimer’s disease.
Applications of proteomics in neuroscience – Linking genes and proteins in neurological disease
To better link the genome to the proteome in neurological disease, Yang et al. conducted a multiomic analysis of samples from patients with Alzheimer’s and matched controls. Using a genome-wide association study (GWAS), they linked genetic variations to 1,305 proteins identified in a broadscale proteomic analysis of the samples.
Learn about broadscale proteomics on the NautilusTM Platform.
In all, the researchers’ broadscale proteomics approach found hundreds of protein quantitative trait loci (pQTLs) linked to specific proteins, including 23 proteins that significantly impacted Alzheimer’s risk. Many of these proteins had multiple genes acting on them, and some genes affected more than one protein. For example, the APOE gene was associated with impacts on 13 different proteins.
The multifactorial nature of gene-protein interactions shows how complex the underpinnings of Alzheimer’s disease are and highlights the intertwined genetic and proteomic mechanisms behind it.
Applications of proteomics in neuroscience – Diving into the role of tau in health and disease with interaction proteomics
How exactly the tau protein changes in Alzheimer’s disease was the focus of this research from Tracy et al. They leveraged interaction proteomics to assess both wild-type and mutated versions of the tau protein in neurons. Interaction proteomics uses mass spectrometry or another proteomics technique to reveal what other proteins interact with a protein of interest, pointing to links between them.
Using two different kinds of interaction proteomics techniques, the researchers found that the proteins that interact with neuronal tau change when neurons are stimulated, and that wild-type tau proteins behave differently than mutated versions. Mutated tau proteins seemed to impair cell energetics, which could explain how they cause neurons to malfunction and die in Alzheimer’s disease.
Applications of proteomics in neuroscience – Identifying disrupted pathways in dementia
To search for the proteomic roots of neurodegenerative diseases, Swarup and Chang et al. looked for protein modules associated with a few different neurodegenerative diseases, including Alzheimer’s, frontotemporal dementia, and Parkinson’s disease. Using a discovery proteomics approach, they found several protein modules implicated in just the dementia-related diseases, indicating similar roles in different kinds of disease.
Then, the authors attempted to link these protein modules to changes in mRNA abundance as well as genetic variants. While they found some overlap between changes in mRNA and protein modules, they found many instances where mRNA abundance did not correlate with protein abundance. They also found that genes associated with Alzheimer’s or PSP (another type of dementia) were enriched in distinct, non-overlapping protein modules. This suggests that the enriched modules may be causal for each disease. These findings demonstrate the importance of linking the proteome to the genome to develop a mechanistic understanding of dementia.
Applications of proteomics in neuroscience – Uncovering protein networks in Alzheimer’s
Johnson, Carter, and Dammer et al used mass spectrometry to conduct discovery proteomics experiments on post-mortem brain tissue samples and learn more about the role of proteins in Alzheimer’s disease. Their proteomic analysis identified protein networks likely linked to the disease, including four protein modules strongly associated with symptoms of Alzheimer’s.
Then, the researchers used a transcriptomic analysis to compare RNA modules to protein modules to see if they lined up. Nearly half the RNA modules had no associated protein module, indicating that changes to biology at the protein level, such as post-translational modifications, play a significant role in Alzheimer’s. Finally, the researchers identified links between genetic variants and protein modules, finding a number of single nucleotide polymorphisms (SNPs) affecting the protein modules. This multiomic approach shows how different levels of biological complexity combine to drive Alzheimer’s disease, and highlights the importance of comprehensively studying proteomics, genomics, and transcriptomics to understand complex diseases like Alzheimer’s.
Applications of proteomics in neuroscience – Assessing tau modifications during Alzheimer’s disease progression
Aggregates of the tau protein are known to be associated with Alzheimer’s disease progression. An important component of this process may be the ways that tau proteins are modified during progression. To learn more about tau modifications, Wesseling et al. used a bottom-up proteomics approach to measure both tau isoforms and tau post-translational modifications in samples from people with Alzheimer’s.
By correlating Alzheimer’s progression to different versions of the tau protein, the researchers were able to reveal which tau proteoforms may play a role in driving the disease forward. Important tau modifications included the ubiquitination of K311 and K317 and phosphorylation of T217 and S262, which differed significantly between people with Alzheimer’s disease and controls. Targeting specific tau isoforms and modifications could yield more precise treatments for the disease.
Creating an atlas of protein changes during Alzheimer’s disease progression
In their recent systemic literature review, Askenazi et al. analyze a variety of publications leveraging proteomics to study Alzheimers. By compiling data from multiple studies they answer questions such as:
- What proteins are enriched in amyloid plaques, NFTs, and cerebral amyloid angiopathy?
- What are the earliest protein changes in Alzheimer’s disease?
- How do protein abundance changes associated with Alzheimer’s disease vary between brain regions during AD progression?
Next-generation proteomics technologies will expand the possibilities of proteomics in neuroscience
All of the above research was accomplished using existing proteomics technologies, typically some variant of mass spectrometry. New and more powerful proteomics applications are on the horizon and may enable far deeper and more powerful insights. With tools like the Nautilus Proteome Analysis Platform, more labs will have access to proteomics technologies that are higher throughput, more sensitive, and cover a wider dynamic range than ever before. With these advancements, proteomics will drive the development of more insights into complex diseases like Alzheimers and may lead to the creation of more effective diagnostics and treatments.
Check out the Translating Proteomics podcast for an exciting discussion about the applications of proteomics
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