Protein-protein interaction networks: probing disease mechanisms using model systems

Kuzmanov, Uroš; Emili, Andrew

doi:10.1186/gm441

Cited by 149 publications

(106 citation statements)

References 92 publications

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“…Disruption of protein-protein interactions can contribute to disease and defining how these interactions change across the proteome can provide important insights into pathogenic mechanisms and ultimately improved therapies. 1 Conventional methods to study protein-protein interactions involve large-scale affinity purification or separation of protein complexes combined with protein identification using mass spectrometry. [2][3][4][5][6][7] These methods typically require ectopic expression of proteins, affinity tags for purification or separation of protein complexes from extracts and other non-physiological conditions, which can produce artifacts and disruption of of native protein interactions.…”

Section: Introductionmentioning

confidence: 99%

Optimized cross-linking mass spectrometry for in situ interaction proteomics

Ser¹,

Cifani²,

Kentsis³

2018

Preprint

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Recent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS).Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the density and coverage of protein-protein interaction maps can be significantly improved through the use of multiple proteases. In addition, the use of sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching.Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems. 5 Experimental Section Reagents. Disuccinimidyl sulfoxide (DSSO), formic acid, dimethyl sulfoxide (DMSO), and LC-MS grade solvents were obtained from Thermo Scientific. Bovine serum albumin (BSA), (4-(2hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), sodium chloride, magnesium chloride, potassium chloride, sucrose, ethylenediaminetetraacetic acid (EDTA), dithiothreitol, guanidinium hydrochloride, Staphylococcus aureus micrococcal nuclease, iodoacetamide, ammonium bicarbonate and formic acid were obtained from Millipore Sigma. Protease inhibitors 4-(2-aminoethyl)-benzenesulfonyl fluoride hydrochloride (AEBSF) and pepstatin were obtatined from Santa Cruz, bestatin from Alfa Aesar and leupeptin from EMD Millipore. Trypsin and GluC proteases were obtained from Promega. Chymotrypsin protease was obtained from Pierce Thermo. LysC was obtained from Wako Pure Chemical Industries.Cell culture and protein isolation. HEK293T cells were cultured in DMEM supplemented with 10% (v/v) fetal bovine serum, penicillin and streptomycin. HEK293T cells (50 million) were sedimented by centrifugation at 500 g and lysed in 500 µl 6M guanidine hydrochloride in 100 mM ammonium bicarbonate buffer, pH 8. The lysate was sonicated (E210 adaptive focused acoustic sonicator, Covaris) for 5 minutes at 4°C and homogenized by passing through a 27G needle. The lysate was then clarified by centrifugation at 18,000 g for 10 min at 4°C. Protein concentration of clarified lysates was determined using the bicinchoninic acid (BCA) assay, according to manufacturer's instructions (Thermo Scientific).Preparation of cross-linked bovine serum albumin and peptide purification. 50 µg of BSA was solubilized in 50 µl HEPES buffer (20 mM HE...

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Section: Introductionmentioning

confidence: 99%

Optimized cross-linking mass spectrometry for in situ interaction proteomics

Ser¹,

Cifani²,

Kentsis³

2018

Preprint

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“…These various modes by which proteins cluster into functional neighborhoods in the brain provide unique pathways for behavioral complexity, but also for the emergence of disease. Indeed, many brain diseases result from disruptions in protein interactions (Kuzmanov and Emili, 2013;Li et al, 2015;Malty et al, 2017) , though the etiology of complex psychiatric disorders like schizophrenia and autism, and their precise relationship to protein interactions, are only just beginning to be understood (Abraham et al, 2019;Flint and Ideker, 2019;Lyall et al, 2017) .…”

Section: Introductionmentioning

confidence: 99%

Mapping Functional Protein Neighborhoods in the Mouse Brain

Liebeskind

Young

Halling

et al. 2020

Preprint

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New proteomics methods make it possible to determine protein interaction maps at the proteome scale without the need for genetically encoded tags, opening up new organisms and tissue types to investigation. Current molecular and computational methods are oriented towards protein complexes that are soluble, stable, and discrete. However, the mammalian brain, among the most complicated and most heavily studied tissue types, derives many of its unique functions from protein interactions that are neither discrete nor soluble. Proteomics investigations into the global protein interaction landscape of the brain have therefore leveraged non-proteomics datasets to supplement their experiments. Here, we develop a novel, integrative proteomics pipeline and apply it to infer a global map of functional protein neighborhoods in the mouse brain without the aid of external datasets. By leveraging synaptosome enrichment and interactomics methods that target both soluble and insoluble protein fractions, we resolved protein interactions for key neural pathways, including those from refractory subcellular fractions such as the membrane and cytoskeleton. In comparison to external datasets, our observed interactions perform similarly to hand-curated synaptic protein interactions while also suggesting thousands of novel connections. We additionally employed cleavable chemical cross-linkers to detect direct binding partners and provide structural context. Our combined map suggests new protein pathways and novel mechanisms for proteins that underlie neurological diseases, including autism and epilepsy. Our results show that proteomics methods alone are sufficient to determine global interaction maps for proteins that are of broad interest to neuroscience. We anticipate that our map will be used to prioritize new research avenues and will pave the way towards future proteomics techniques that resolve protein interactions at ever greater resolution.

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“…The dynamic cooperation of biomolecules is the foundation of all cellular functions. Proteins constitute half of the dry mass of a cell and protein‐protein interactions (PPIs) are essential in the conversion of genotypes to phenotypes, while disruption often causes disease . With the total amount of PPIs in humans estimated to approximate 650 000 and the content of the protein complexes under constant change, comprehensive analysis is challenging but central to our understanding of biology and disease.…”

Section: Introductionmentioning

confidence: 99%

Discovering cellular protein‐protein interactions: Technological strategies and opportunities

Titeca

Lemmens

Tavernier

et al. 2018

Mass Spectrometry Reviews

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The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

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Protein-protein interaction networks: probing disease mechanisms using model systems

Cited by 149 publications

References 92 publications

Optimized cross-linking mass spectrometry for in situ interaction proteomics

Optimized cross-linking mass spectrometry for in situ interaction proteomics

Mapping Functional Protein Neighborhoods in the Mouse Brain

Discovering cellular protein‐protein interactions: Technological strategies and opportunities

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