A Protein Interaction Network Links GIT1, an Enhancer of Huntingtin Aggregation, to Huntington's Disease

Goehler, Heike; Łałowski, Maciej; Stelzl, Ulrich; Waelter, Stephanie; Stroedicke, Martin; Worm, Uwe; Droege, Anja; Lindenberg, Katrin S.; Knoblich, Maria; Haenig, Christian; Herbst, Martin; Suopanki, Jaana; Scherzinger, Eberhard; Abraham, Claudia; Bauer, Bianca; Hasenbank, Renate; Fritzsche, Anja; Ludewig, Andreas H.; Buessow, K.; Coleman, Sarah H.; Gutekunst, Claire‐Anne; Landwehrmeyer, G. Bernhard; Lehrach, Hans; Wanker, Erich E.

doi:10.1016/j.molcel.2004.09.016

Cited by 390 publications

(300 citation statements)

References 40 publications

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“…This approach is bolstered by the fact that surveys of protein-protein interactions have revealed many interactions that, when disrupted, are deleterious. [39][40][41][42][43][44] Moreover, protein interactions can reveal defects in protein folding and stability, which helps to explain why approximately one-third of disease-related variants in proteins with multiple interaction partners disrupt all of the interactions of that protein. 45 Variants of protein-coding genes can also result in pathogenicity by altering splicing.…”

Section: Annotating Every Possible Variant In Disease-related Functiomentioning

confidence: 99%

Variant Interpretation: Functional Assays to the Rescue

Starita

Ahituv

Dunham

et al. 2017

The American Journal of Human Genetics

293

286

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Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of ''lookup tables'' of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.

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Section: Annotating Every Possible Variant In Disease-related Functiomentioning

confidence: 99%

Variant Interpretation: Functional Assays to the Rescue

Starita

Ahituv

Dunham

et al. 2017

The American Journal of Human Genetics

293

286

View full text Add to dashboard Cite

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“…To this day, systematic mapping of binary interactions between human proteins has been predominantly performed in yeast cells 3 Here, we present a second generation LUMIER PPI screening assay, which allows quantification of both bait and prey hybrid proteins using two different luciferase tags. DULIP (for dual luminescence-based co-immunoprecipitation assay)…”

Section: Introductionmentioning

confidence: 99%

DULIP: A Dual Luminescence-Based Co-Immunoprecipitation Assay for Interactome Mapping in Mammalian Cells

Trepte

Buntru

Klockmeier

et al. 2015

Journal of Molecular Biology

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Mapping of protein-protein interactions (PPIs) is critical for understanding protein function and complex biological processes. Here, we present DULIP, a dual luminescence-based co-immunoprecipitation assay, for systematic PPI mapping in mammalian cells. DULIP is a second-generation luminescence-based PPI screening method for the systematic and quantitative analysis of co-immunoprecipitations using two different luciferase tags. Benchmarking studies with positive and negative PPI reference sets revealed that DULIP allows the detection of interactions with high sensitivity and specificity. Furthermore, the analysis of a PPI reference set with known binding affinities demonstrated that both low-and high-affinity interactions can be detected with DULIP assays. Finally, using the well-characterized interaction between Syntaxin-1 and Munc18, we found that DULIP is capable of detecting the effects of point mutations on interaction strength. Taken together, our studies demonstrate that DULIP is a sensitive and reliable method of great utility for 2 systematic interactome research. It can be applied for interaction screening as well as for the validation of PPIs in mammalian cells. Moreover, DULIP permits the specific analysis of mutation-dependent binding patterns. HIGHLIGHTS• DULIP is a dual luminescence-based co-immunoprecipitation assay suitable for systematic analysis of PPIs

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“…18,19 MAP1A/1B LC3A is involved in the filamentous cross-bridging between microtubules and other skeletal elements and can associate with MAP1A and MAP1B proteins. 20,21 The bait proteins were expressed recombinantly in Escherischia coli, as GST fusion proteins. For the affinity pull-down experiment, each bait protein bound to glutathione-sepharose beads was incubated with a protein extract of human brain.…”

Section: Resultsmentioning

confidence: 99%

Method for Qualitative Comparisons of Protein Mixtures Based on Enzyme-Catalyzed Stable-Isotope Incorporation

et al. 2005

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Determining which proteins are unique among one or several protein populations is an oftenencountered task in proteomics. To this purpose, we present a new method based on trypsin-catalyzed incorporation of the stabile isotope 18 O in the C-termini of tryptic peptides, followed by LC-MALDI MS analysis. The analytical strategy was designed such that proteins unique to a given population out of several can be assigned in a single experiment by the isotopic signal intensity distributions of their tryptic peptides in the recorded mass spectra. The method is demonstrated for protein-protein interaction analysis, in which the differential isotope labeling was used to distinguish endogenous human brain proteins interacting with a recombinant bait protein from nonbiospecific background binders.

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A Protein Interaction Network Links GIT1, an Enhancer of Huntingtin Aggregation, to Huntington's Disease

Cited by 390 publications

References 40 publications

Variant Interpretation: Functional Assays to the Rescue

Variant Interpretation: Functional Assays to the Rescue

DULIP: A Dual Luminescence-Based Co-Immunoprecipitation Assay for Interactome Mapping in Mammalian Cells

Method for Qualitative Comparisons of Protein Mixtures Based on Enzyme-Catalyzed Stable-Isotope Incorporation

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