Protein interaction affinity determination by quantitative FRET technology

The dissociation constant, K_d, is an important parameter for characterizing protein–protein interaction affinities. SUMOylation is one of the important protein post‐translational modifications and it involves a multi‐step enzymatic cascade reaction, resulting in peptide activation and substrate conjugation. Multiple covalent and non‐covalent protein–protein interactions are involved in this cascade. Techniques involving Förster resonance energy transfer (FRET) have been widely used in biological studies in vitro and in vivo, and they are very powerful tools for elucidating protein interactions in many regulatory cascades. In our previous studies, we reported the attempt to develop a new method for the determination of the K_d by FRET assay using the interaction of SUMO1 and its E2 ligase, Ubc9 as a test system. However, the generality and specifications of this new method have not been fully determined. Here we report a systematic approach for determining the dissociation constant (K_d) in the SUMOylation cascade and for further sensitivity and accuracy testing by the FRET technology. From a FRET donor to acceptor concentration ratio range of 4–40, the K_ds of SUMO1 and Ubc9 consistently agree well with values from surface plasmon resonance and isothermal titration calorimetry. These results demonstrate the high sensitivity and accuracy of the FRET‐based K_d determination approach. This technology, therefore, can be used in general for protein–protein interaction dissociation constant determination. Biotechnol. Bioeng. 2012; 109: 2875–2883. © 2012 Wiley Periodicals, Inc.     

Differential analysis of high-throughput quantitative genetic interaction data

Synthetic genetic arrays have been very effective at measuring genetic interactions in yeast in a high-throughput manner and recently have been expanded to measure quantitative changes in interaction, termed ''differential interactions'', across multiple conditions. Here, we present a strategy that leverages statistical information from the experimental design to produce a novel, quantitative differential interaction score, which performs favorably compared to previous differential scores. We also discuss the added utility of differential genetic-similarity in differential network analysis. Our approach is preferred for differential network analysis, and our implementation, written in MATLAB, can be found at http://chianti.ucsd.edu/~gbean/compute_differential_scores.m.     

Derivation of genetic interaction networks from quantitative phenotype data

We have generalized the derivation of genetic-interaction networks from quantitative phenotype data. Familiar and unfamiliar modes of genetic interaction were identified and defined. A network was derived from agar-invasion phenotypes of mutant yeast. Mutations showed specific modes of genetic interaction with specific biological processes. Mutations formed cliques of significant mutual information in their large-scale patterns of genetic interaction. These local and global interaction patterns reflect the effects of gene perturbations on biological processes and pathways.     

Dual-fluorophore quantitative high-throughput screen for inhibitors of BRCT-phosphoprotein interaction

Finding specific small-molecule inhibitors of protein-protein interactions remains a significant challenge. Recently, attention has grown toward "hot spot" interactions where binding is dominated by a limited number of amino acid contacts, theoretically offering an increased opportunity for disruption by small molecules. Inhibitors of the interaction between BRCT (the C-terminal portion of BRCA1, a key tumor suppressor protein with various functions) and phosphorylated proteins (Abraxas/BACH1/CtIP), implicated in DNA damage response and repair pathways, should prove to be useful in studying BRCA1's role in cancer and in potentially sensitizing tumors to chemotherapeutic agents. We developed and miniaturized to a 1536-well format and 3-mul final volume a pair of fluorescence polarization (FP) assays using fluorescein- and rhodamine-labeled pBACH1 fragment. To minimize the effect of fluorescence artifacts and to increase the overall robustness of the screen, the 75,552 compound library members all were assayed against both the fluorescein- and rhodamine-labeled probe-protein complexes in separate but interleaved reactions. In addition, every library compound was tested over a range of concentrations following the quantitative high-throughput screening (qHTS) paradigm. Analyses of the screening results led to the selection and subsequent confirmation of 16 compounds active in both assays. Faced with a traditionally difficult protein-protein interaction assay, by performing two-fluorophore qHTS, we were able to confidently select a number of actives for further studies.     

An alternative model of olfactory quantitative interaction in binary mixtures

The "vectorial model" proposed in 1973 by Berglund et al. certainlyconstitutes an important progress in the field of olfactoryquantitative interaction. An alternative model called "U model",based also upon perceived odorous intensity of a mixture asa function of perceived odorous intensity of the components,is here presented. The "U model" fits the experimental data of Cain and Drexler(1974) and of Cain (1975) slightly better than the "vectorialmodel". ^*Presented at the VIth International Symposium Olfaction andTaste, Gif-sur-Yvette, Paris, France, 15–17th July, 1977.     

A quantitative model of actin-myosin interaction in skeletal muscle.

Biochemical schemes for the actomyosin ATPase cycle as well as the cooperative regulation of ATPase activity are incorporated into a model of the contractile process of intact muscle. This model is shown to describe accurately the tension developed by skinned muscle fibers in the absence of Ca. This work adds to the evidence that the extrapolation of results from purified protein systems to intact muscle may be valid. Extensions to the case of Ca-activated tensions are discussed.     

Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci

The interval mapping method is widely used for the genetic mapping of quantitative trait loci (QTLs), though true resolution of quantitative variation into QTLs is hampered with this method. Separation of QTLs is troublesome, because single-QTL is models are fitted. Further, genotype-by-environment interaction, which is of great importance in many quantitative traits, can only be approached by separately analyzing the data collected in multiple environments. Here, we demonstrate for the first time a novel analytic approach (MQM mapping) that accommodates both the mapping of multiple QTLs and genotype-by-environment interaction. MQM mapping is compared to interval mapping in the mapping of QTLs for flowering time in Arabidopsis thaliana under various photoperiod and vernalization conditions.     

Functional maps of protein complexes from quantitative genetic interaction data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function.     

A quantitative characterization of interaction between prion protein with nucleic acids

Binding of recombinant prion protein with small highly structured RNAs, prokaryotic and eukaryotic prion protein mRNA pseudoknots, tRNA and polyA has been studied by the change in fluorescence anisotropy of the intrinsic tryptophan groups of the protein. The affinities of these RNAs to the prion protein and the number of sites where the protein binds to the nucleic acids do not vary appreciably although the RNAs have very different compositions and structures. The binding parameters do not depend upon pH of the solution and show a poor co-operativity. The reactants form larger nucleoprotein complexes at pH 5 compared to that at neutral pH. The electrostatic force between the protein and nucleic acids dominates the binding interaction at neutral pH. In contrast, nucleic acid interaction with the incipient nonpolar groups exposed from the structured region of the prion protein dominates the reaction at pH 5. Prion protein of a particular species forms larger complexes with prion protein mRNA pseudoknots of the same species. The structure of the pseudoknots and not their base sequences probably dominates their interaction with prion protein. Possibilities of the conversion of the prion protein to its infectious form in the cytoplasm by nucleic acids have been discussed.     

A strategy for extracting and analyzing large-scale quantitative epistatic interaction data

Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions.     

Two-loci interaction confirms arthritis-regulating quantitative trait locus on rat chromosome 6

A form of genetic interaction, or epistasis, occurs when one gene interferes with the phenotypic effect of another nonallelic gene. In pristane-induced arthritis (PIA) in rats we have previously identified Pia3, on chromosome 6, to be a locus that regulates onset of disease. In a single congenic strain containing Pia3 on the arthritis-susceptible DA background, DA.Pia3, no difference in onset of disease or early disease severity could be detected. After a two-loci interaction analysis of (E3 x DA)F2 intercross data, Pia3 was found to interact with Pia4 (chromosome 12). Subsequently, the DA.Pia3 congenic strain was combined with the DA.Pia4 congenic strain so that an effect of Pia3 could be observed. The effect of heterozygosity in Pia4 results in lower severity and thus in combination with Pia3 made it possible to observe that Pia3 alleles from the arthritis-resistant E3 strain rendered more severe arthritis into the otherwise 100% susceptible DA strain. As the introduction of Pia4 heterozygosity results in a lower level of arthritis severity we regard this as an additive interaction with a severity threshold-lowering effect.     

Genotype-environment interaction for quantitative trait loci affecting life span in Drosophila melanogaster

The nature of genetic variation for Drosophila longevity in a population of recombinant inbred lines was investigated by estimating quantitative genetic parameters and mapping quantitative trait loci (QTL) for adult life span in five environments: standard culture conditions, high and low temperature, and heat-shock and starvation stress. There was highly significant genetic variation for life span within each sex and environment. In the analysis of variance of life span pooled over sexes and environments, however, the significant genetic variation appeared in the genotype x sex and genotype x environment interaction terms. The genetic correlation of longevity across the sexes and environments was not significantly different from zero in these lines. We estimated map positions and effects of QTL affecting life span by linkage to highly polymorphic roo transposable element markers, using a multiple-trait composite interval mapping procedure. A minimum of 17 QTL were detected; all were sex and/or environment-specific. Ten of the QTL had sexually antagonistic or antagonistic pleiotropic effects in different environments. These data provide support for the pleiotropy theory of senescence and the hypothesis that variation for longevity might be maintained by opposing selection pressures in males and females and variable environments. Further work is necessary to assess the generality of these results, using different strains, to determine heterozygous effects and to map the life span QTL to the level of genetic loci.     

Identifying specific protein interaction partners using quantitative mass spectrometry and bead proteomes

The identification of interaction partners in protein complexes is a major goal in cell biology. Here we present a reliable affinity purification strategy to identify specific interactors that combines quantitative SILAC-based mass spectrometry with characterization of common contaminants binding to affinity matrices (bead proteomes). This strategy can be applied to affinity purification of either tagged fusion protein complexes or endogenous protein complexes, illustrated here using the well-characterized SMN complex as a model. GFP is used as the tag of choice because it shows minimal nonspecific binding to mammalian cell proteins, can be quantitatively depleted from cell extracts, and allows the integration of biochemical protein interaction data with in vivo measurements using fluorescence microscopy. Proteins binding nonspecifically to the most commonly used affinity matrices were determined using quantitative mass spectrometry, revealing important differences that affect experimental design. These data provide a specificity filter to distinguish specific protein binding partners in both quantitative and nonquantitative pull-down and immunoprecipitation experiments.     

Protein interaction screening by quantitative immunoprecipitation combined with knockdown (QUICK)

Present screening methods for protein-protein interactions (PPIs) rely on the overexpression of artificial fusion proteins, making it difficult to assess in vivo relevance. Here we combine stable isotope labeling with amino acids in cell culture (SILAC), RNA interference (RNAi), coimmunoprecipitation and quantitative mass-spectrometry analysis to detect cellular interaction partners of endogenous proteins in mammalian cells with very high confidence. We used this screen to identify interaction partners of beta-catenin and Cbl.     

A quantitative study of organic phosphate-amine interaction by 31P nuclear magnetic resonance

Interactions between the phosphate group of 4-deoxypyridoxine 5′-phosphate and different protonated amines were quantitatively measured by means of {³¹P}-¹H nuclear magnetic double resonance technique combined with pD titration. An interaction of the phosphate group with added amine resulted in a measurable difference in the ³¹P chemical shift of these phosphate-containing samples with and without amine [Δδ(³¹P)]. Basic amino acids and biogenic amines had significant measurable Δδ(³¹P) values. No interactions were observed for acidic or neutral α, β and γ-amino acids.