Characterization of an Italian founder mutation in the RING-finger domain of BRCA1

The identification of founder mutations in cancer predisposing genes is important to improve risk assessment in geographically defined populations, since it may provide specific targets resulting in cost-effective genetic testing. Here, we report the characterization of the BRCA1 c.190T>C (p.Cys64Arg) mutation, mapped to the RING-finger domain coding region, that we detected in 43 hereditary breast/ovarian cancer (HBOC) families, for the large part originating from the province of Bergamo (Northern Italy). Haplotype analysis was performed in 21 families, and led to the identification of a shared haplotype extending over three BRCA1-associated marker loci (0.4 cM). Using the DMLE+2.2 software program and regional population demographic data, we were able to estimate the age of the mutation to vary between 3,100 and 3,350 years old. Functional characterization of the mutation was carried out at both transcript and protein level. Reverse transcriptase-PCR analysis on lymphoblastoid cells revealed expression of full length mRNA from the mutant allele. A green fluorescent protein (GFP)-fragment reassembly assay showed that the p.Cys64Arg substitution prevents the binding of the BRCA1 protein to the interacting protein BARD1, in a similar way as proven deleterious mutations in the RING-domain. Overall, 55 of 83 (66%) female mutation carriers had a diagnosis of breast and/or ovarian cancer. Our observations indicate that the BRCA1 c.190T>C is a pathogenic founder mutation present in the Italian population. Further analyses will evaluate whether screening for this mutation can be suggested as an effective strategy for the rapid identification of at-risk individuals in the Bergamo area

A Novel Genetic Screen Implicates Elm1 in the Inactivation of the Yeast Transcription Factor SBF

BACKGROUND: Despite extensive large scale analyses of expression and protein-protein interactions (PPI) in the model organism Saccharomyces cerevisiae, over a thousand yeast genes remain uncharacterized. We have developed a novel strategy in yeast that directly combines genetics with proteomics in the same screen to assign function to proteins based on the observation of genetic perturbations of sentinel protein interactions (GePPI). As proof of principle of the GePPI screen, we applied it to identify proteins involved in the regulation of an important yeast cell cycle transcription factor, SBF that activates gene expression during G1 and S phase. METHODOLOGY/PRINCIPLE FINDINGS: The principle of GePPI is that if a protein is involved in a pathway of interest, deletion of the corresponding gene will result in perturbation of sentinel PPIs that report on the activity of the pathway. We created a fluorescent protein-fragment complementation assay (PCA) to detect the interaction between Cdc28 and Swi4, which leads to the inactivation of SBF. The PCA signal was quantified by microscopy and image analysis in deletion strains corresponding to 25 candidate genes that are periodically expressed during the cell cycle and are substrates of Cdc28. We showed that the serine-threonine kinase Elm1 plays a role in the inactivation of SBF and that phosphorylation of Elm1 by Cdc28 may be a mechanism to inactivate Elm1 upon completion of mitosis. CONCLUSIONS/SIGNIFICANCE: Our findings demonstrate that GePPI is an effective strategy to directly link proteins of known or unknown function to a specific biological pathway of interest. The ease in generating PCA assays for any protein interaction and the availability of the yeast deletion strain collection allows GePPI to be applied to any cellular network. In addition, the high degree of conservation between yeast and mammalian proteins and pathways suggest GePPI could be used to generate insight into human disease

Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins

<p>Abstract</p> <p>Background</p> <p>Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residue preferences have been widely used in many studies but the results are often not satisfactory. Although different amino acid compositions among the interaction sites of different complexes have been observed, such differences have not been integrated into the prediction process. Furthermore, the evolution information has not been exploited to achieve a more powerful propensity.</p> <p>Result</p> <p>In this study, the residue interface propensities of four kinds of complexes (homo-permanent complexes, homo-transient complexes, hetero-permanent complexes and hetero-transient complexes) are investigated. These propensities, combined with sequence profiles and accessible surface areas, are inputted to the support vector machine for the prediction of protein binding sites. Such propensities are further improved by taking evolutional information into consideration, which results in a class of novel propensities at the profile level, i.e. the binary profiles interface propensities. Experiment is performed on the 1139 non-redundant protein chains. Although different residue interface propensities among different complexes are observed, the improvement of the classifier with residue interface propensities can be negligible in comparison with that without propensities. The binary profile interface propensities can significantly improve the performance of binding sites prediction by about ten percent in term of both precision and recall.</p> <p>Conclusion</p> <p>Although there are minor differences among the four kinds of complexes, the residue interface propensities cannot provide efficient discrimination for the complicated interfaces of proteins. The binary profile interface propensities can significantly improve the performance of binding sites prediction of protein, which indicates that the propensities at the profile level are more accurate than those at the residue level.</p

Codon Size Reduction as the Origin of the Triplet Genetic Code

The genetic code appears to be optimized in its robustness to missense errors and frameshift errors. In addition, the genetic code is near-optimal in terms of its ability to carry information in addition to the sequences of encoded proteins. As evolution has no foresight, optimality of the modern genetic code suggests that it evolved from less optimal code variants. The length of codons in the genetic code is also optimal, as three is the minimal nucleotide combination that can encode the twenty standard amino acids. The apparent impossibility of transitions between codon sizes in a discontinuous manner during evolution has resulted in an unbending view that the genetic code was always triplet. Yet, recent experimental evidence on quadruplet decoding, as well as the discovery of organisms with ambiguous and dual decoding, suggest that the possibility of the evolution of triplet decoding from living systems with non-triplet decoding merits reconsideration and further exploration. To explore this possibility we designed a mathematical model of the evolution of primitive digital coding systems which can decode nucleotide sequences into protein sequences. These coding systems can evolve their nucleotide sequences via genetic events of Darwinian evolution, such as point-mutations. The replication rates of such coding systems depend on the accuracy of the generated protein sequences. Computer simulations based on our model show that decoding systems with codons of length greater than three spontaneously evolve into predominantly triplet decoding systems. Our findings suggest a plausible scenario for the evolution of the triplet genetic code in a continuous manner. This scenario suggests an explanation of how protein synthesis could be accomplished by means of long RNA-RNA interactions prior to the emergence of the complex decoding machinery, such as the ribosome, that is required for stabilization and discrimination of otherwise weak triplet codon-anticodon interactions

The Cyst Nematode SPRYSEC Protein RBP-1 Elicits Gpa2- and RanGAP2-Dependent Plant Cell Death

Plant NB-LRR proteins confer robust protection against microbes and metazoan parasites by recognizing pathogen-derived avirulence (Avr) proteins that are delivered to the host cytoplasm. Microbial Avr proteins usually function as virulence factors in compatible interactions; however, little is known about the types of metazoan proteins recognized by NB-LRR proteins and their relationship with virulence. In this report, we demonstrate that the secreted protein RBP-1 from the potato cyst nematode Globodera pallida elicits defense responses, including cell death typical of a hypersensitive response (HR), through the NB-LRR protein Gpa2. Gp-Rbp-1 variants from G. pallida populations both virulent and avirulent to Gpa2 demonstrated a high degree of polymorphism, with positive selection detected at numerous sites. All Gp-RBP-1 protein variants from an avirulent population were recognized by Gpa2, whereas virulent populations possessed Gp-RBP-1 protein variants both recognized and non-recognized by Gpa2. Recognition of Gp-RBP-1 by Gpa2 correlated to a single amino acid polymorphism at position 187 in the Gp-RBP-1 SPRY domain. Gp-RBP-1 expressed from Potato virus X elicited Gpa2-mediated defenses that required Ran GTPase-activating protein 2 (RanGAP2), a protein known to interact with the Gpa2 N terminus. Tethering RanGAP2 and Gp-RBP-1 variants via fusion proteins resulted in an enhancement of Gpa2-mediated responses. However, activation of Gpa2 was still dependent on the recognition specificity conferred by amino acid 187 and the Gpa2 LRR domain. These results suggest a two-tiered process wherein RanGAP2 mediates an initial interaction with pathogen-delivered Gp-RBP-1 proteins but where the Gpa2 LRR determines which of these interactions will be productive

Formation and Toxicity of Soluble Polyglutamine Oligomers in Living Cells

Aggregation and cytotoxicity of mutant proteins containing an expanded number of polyglutamine (polyQ) repeats is a hallmark of several diseases, including Huntington's disease (HD). Within cells, mutant Huntingtin (mHtt) and other polyglutamine expansion mutant proteins exist as monomers, soluble oligomers, and insoluble inclusion bodies (IBs). Determining which of these forms constitute a toxic species has proven difficult. Recent studies support a role for IBs as a cellular coping mechanism to sequester levels of potentially toxic soluble monomeric and oligomeric species of mHtt.When fused to a fluorescent reporter (GFP) and expressed in cells, the soluble monomeric and oligomeric polyglutamine species are visually indistinguishable. Here, we describe two complementary biophysical fluorescence microscopy techniques to directly detect soluble polyglutamine oligomers (using Htt exon 1 or Htt(ex1)) and monitor their fates in live cells. Photobleaching analyses revealed a significant reduction in the mobilities of mHtt(ex1) variants consistent with their incorporation into soluble microcomplexes. Similarly, when fused to split-GFP constructs, both wildtype and mHtt(ex1) formed oligomers, as evidenced by the formation of a fluorescent reporter. Only the mHtt(ex1) split-GFP oligomers assembled into IBs. Both FRAP and split-GFP approaches confirmed the ability of mHtt(ex1) to bind and incorporate wildtype Htt into soluble oligomers. We exploited the irreversible binding of split-GFP fragments to forcibly increase levels of soluble oligomeric mHtt(ex1). A corresponding increase in the rate of IBs formation and the number formed was observed. Importantly, higher levels of soluble mHtt(ex1) oligomers significantly correlated with increased mutant cytotoxicity, independent of the presence of IBs.Our study describes powerful and sensitive tools for investigating soluble oligomeric forms of expanded polyglutamine proteins, and their impact on cell viability. Moreover, these methods should be applicable for the detection of soluble oligomers of a wide variety of aggregation prone proteins

Phylogenetic spread of sequence data affects fitness of SOD1 consensus enzymes: Insights from sequence statistics and structural analyses

Non-natural protein sequences with native-like structures and functions can be constructed successfully using consensus design. This design strategy is relatively well understood in repeat proteins with simple binding function, however detailed studies are lacking in globular enzymes. The SOD1 family is a good model for such studies due to the availability of large amount of sequence and structure data motivated by involvement of human SOD1 in the fatal motor neuron disease amyotrophic lateral sclerosis (ALS). We constructed two consensus SOD1 enzymes from multiple sequence alignments from all organisms and eukaryotic organisms. A significant difference in their catalytic activities shows that the phylogenetic spread of the sequences used affects the fitness of the construct obtained. A mutation in an electrostatic loop and overall design incompatibilities between bacterial and eukaryotic sequences were implicated in this disparity. Based on this analysis, a bioinformatics approach was used to classify mutations thought to cause familial ALS providing a unique high level view of the physical basis of disease-causing aggregation of human SOD1

High-Throughput Protein–Protein Interaction Assays Using Tripartite Split-GFP Complementation

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