Systems approach to explore components and interactions in the presynapse
Open accessAbstract
The application of proteomic techniques to neuroscientific research provides an opportunity for a greater understanding of nervous system structure and function. As increasing amounts of neuroproteomic data become available, it is necessary to formulate methods to integrate these data in a meaningful way to obtain a more comprehensive picture of neuronal subcompartments. Furthermore, computational methods can be used to make biologically relevant predictions from large proteomic data sets. Here, we applied an integrated proteomics and systems biology approach to characterize the presynaptic (PRE) nerve terminal. For this, we carried out proteomic analyses of presynaptically enriched fractions, and generated a PRE literature‐based protein–protein interaction network. We combined these with other proteomic analyses to generate a core list of 117 PRE proteins, and used graph theory‐inspired algorithms to predict 92 additional components and a PRE complex containing 17 proteins. Some of these predictions were validated experimentally, indicating that the computational analyses can identify novel proteins and complexes in a subcellular compartment. We conclude that the combination of techniques (proteomics, data integration, and computational analyses) used in this study are useful in obtaining a comprehensive understanding of functional components, especially low‐abundance entities and/or interactions in the PRE nerve terminal.
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FMRP binds mRNAs encoding approximately one-third of proteins in the presynaptic proteome (p=6.4 × 10−33).
“comparison of FMRP target mRNAs with a comprehensive presynaptic proteome database (Abul-Husn et al., 2009) revealed that FMRP also binds mRNAs encoding approximately one-third of the proteins in the presynaptic proteome (p=6.4 × 10−33; Figure 2B, Tables S3A and S3F).”
From FMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism (2011) · cites this paper as Abul-Husn et al., 2009
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References 62 · Cited by 53
- Authors
- Abul‐Husn, N. S., Bushlin, I., Morón, J. A., Jenkins, S. L., Dolios, G., Wang, R., Iyengar, R., Ma'ayan, A., & Devi, L. A.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Corresponding author
- Devi, Lakshmi A.
- ORCID
- Venue
- PROTEOMICS
- Publisher
- Wiley
- Published
- 2009-06
- Volume
- 9
- Issue
- 12
- Pages
- 3303-3315
- ISSN
- 1615-9853 (ISSN-L)
- 1615-9861
- PMC
- PMC2766278
- OpenAlex
- W2012129116
- Cited by
- 53
- References
- 62
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 4 · 2020: 3 · 2019: 3 · 2018: 6 · 2017: 2 · 2016: 3 · 2015: 4 · 2014: 1 · 2013: 4 · 2012: 8
- FWCI
- 2.42
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- PROTEOMICS (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (DA08863)
- LAD (DA019521, GM54508)
- RI (DK 38761, CA88325)
- RW (RR017802)
- SBCNY (1P50GM071558-01A27398)
- MSSM Microscopy Shared Facility (R24 CA095823)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Keywords
- presynaptic terminals, protein-protein interaction network, presynaptic complex, protein complex prediction, graph theory, systems biology, proteomics data integration, low-abundance proteins, synaptic proteins
- MeSH terms
- Animals, Chromatography, High Pressure Liquid, Hippocampus, Immunohistochemistry, Male, Mice, Inbred C57BL, Reproducibility of Results, Signal Transduction, Rats, Sprague-Dawley, Presynaptic Terminals, Proteome, Databases, Protein, Proteomics, Mice, Rats, Tandem Mass Spectrometry
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