Functional and genomic analyses of α-solenoid proteins

{alpha}-solenoids are flexible protein structural domains formed by ensembles of alpha-helical repeats (Armadillo and HEAT repeats among others). While homology can be used to detect many of these repeats, some {alpha}-solenoids have very little sequence homology to proteins of known structure and we expect that many remain undetected. We previously developed a method for detection of {alpha}-helical repeats based on a neural network trained on a dataset of protein structures. Here we improved the detection algorithm and updated the training dataset using recently solved structures of {alpha}-solenoids. Unexpectedly, we identified occurrences of {alpha}-solenoids in solved protein structures that escaped attention, for example within the core of the catalytic subunit of PI3KC. Our results expand the current set of known {alpha}-solenoids. Application of our tool to the protein universe allowed us to detect their significant enrichment in proteins interacting with many proteins, confirming that {alpha}-solenoids are generally involved in protein-protein interactions. We then studied the taxonomic distribution of {alpha}-solenoids to discuss an evolutionary scenario for the emergence of this type of domain, speculating that {alpha}-solenoids have emerged in multiple taxa in independent events by convergent evolution. We observe a higher rate of {alpha}-solenoids in eukaryotic genomes and in some prokaryotic families, such as Cyanobacteria and Planctomycetes, which could be associated to increased cellular complexity. The method is available at http://cbdm.mdc-berlin.de/~ard2/

Forward Individualized Medicine from Personal Genomes to Interactomes

When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships

Adding Protein Context to the Human Protein-Protein Interaction Network to Reveal Meaningful Interactions

<div><p>Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.</p> </div

Context-based retrieval of functional modules in protein-protein interaction networks

Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein–protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference

The Drosophila Interactions Database: Integrating The Interactome And Transcriptome

In this thesis I describe the integration of heterogeneous interaction data for Drosophila into DroID, the Drosophilainteractions database, making it a one-stop public resource for interaction data. I have also made it possible to filter the interaction data using gene expression data to generate context-relevant networks making DroID a one-of-a kind resource for biologists. In the two years since the upgraded DroID has been available, several studies have used the heterogeneous interaction data in DroID to advance our understanding of Drosophila biology thus validating the need for such a resource for biologists. In addition to this, I have identified organizing principles of interaction networks based on genome-wide gene expression data in the tissues and the entire life cycle of Drosophila. I have shown that all tissues and stages have a core ubiquitously expressed PPI network to which tissue and stage specific proteins attach to potentially modulate specific functions. In view of these organizing principles, I developed a normalized expression filter for interaction networks. I have shown that networks generated by using this filter are context-relevant as evidenced by their enrichment for genes with relevant mutant phenotypes. This filter has been implemented in DroID and I anticipate that studies on interactome networks using this filter will further our understanding of biology

Biochemical effects of inherited MMR gene mutations and diet on colon cancer risk

Colorectal cancer (CRC) is one of the leading causes of death in developed countries. Although, a small fraction of cancers are caused by inherited genetic predisposition most of the CRCs are sporadic. In CRC, cancer risk is associated with lifestyle factors and aging. Even in dominantly inherited CRC predisposition such as in Lynch syndrome (LS), which is linked to germline mu- tations in the mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2, cancer develops as a result of accumulation of genetic and epigenetic changes. After diagnosing an LS family, to be able to offer contiguous pre-symptomatic surveillance and predictive gene counseling to mutation carriers in a family, the pathogenicity assessment of a mutation is needed. Dependent on the type and the site of a germline mutation, inherited cancer risk may vary from high to low and especially in the latter case cancer risk may be strongly affected by lifestyle factors such as diet. Epidemiological studies on humans and previous studies on mice have shown that especially a Western-style diet (WD) may predispose colon mucosa to CRC. However, the mechanisms, which mediate the effects of diet on tumorigenesis are largely unknown. Since both genetic and lifestyle factors have been shown to predispose to cancer, this the- sis analyzed biochemical defects caused by inherited MMR gene mutations and Western diet exposure. Different MMR gene mutations may compromise MMR function through various biochemical defects. Here, we studied 18 inherited non-truncating mutations in MSH2, the second most frequently mutated gene among Lynch syndrome patients. We assessed protein stability, DNA binding, and ATP mediated DNA release abilities of the MSH2 variants. The majority of variants in the amino terminal region including the connector and lever domains p.V161D, p.G162R, p.G164R, p.L173P, p.L187P, p.C333Y, p.D603N) affected protein stabil- ity. Variations in the ATPase domain (p.A636P, p.G674A, p.C697F, p.I745-I746del, p.E749K) totally abolished either mismatch binding or release. Four protein variants (p.T33P, p.A272 V, p.G322D, p.V923E) expressed slightly reduced mismatch binding and/or release efficiencies compared to wild-type (WT) MSH2 protein, while two variants (p.N127S, p.A834T) were in- distinguishable from WT. To define the effects of Western-style diet, we analyzed protein expression changes in histolog- ically normal colon mucosa of wild type (Mlh1+/+) and CRC predisposed mice (Mlh1+/-) after a long-term feeding experiment with WD and AIN-93G control diet. Using network analysis and data mining we also determined which of the affected proteins might be putative play- ers in early CRC development. Our results pinpoint changes in a complex protein interaction network involved in ATP synthesis coupled proton transport, oxidoreduction coenzyme and nicotinamide nucleotide metabolic processes, which are important in the generation of reactive oxygen species (ROS) and cellular protection against ROS toxicity. Additionally, we detected SELENBP1 and LGALS4, which are implied in neoplastic processes. Our studies show that mutations in the MMR gene affect the biochemistry of MMR, can have an effect on the phenotype of the mutation carriers and in the latest study suggest that the high sensitivity to Western diet may be linked to haplo-insufficiency caused by a loss of function mutation in the Mlh1+/- mice.Colorectal cancer (CRC) is one of the leading causes of death in developed countries. Although, a small fraction of cancers are caused by inherited genetic predisposition most of the CRCs are sporadic. In CRC, cancer risk is associated with lifestyle factors and aging. Even in dominantly inherited CRC predisposition such as in Lynch syndrome (LS), which is linked to germline mu- tations in the mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2, cancer develops as a result of accumulation of genetic and epigenetic changes. After diagnosing an LS family, to be able to offer contiguous pre-symptomatic surveillance and predictive gene counseling to mutation carriers in a family, the pathogenicity assessment of a mutation is needed. Dependent on the type and the site of a germline mutation, inherited cancer risk may vary from high to low and especially in the latter case cancer risk may be strongly affected by lifestyle factors such as diet. Epidemiological studies on humans and previous studies on mice have shown that especially a Western-style diet (WD) may predispose colon mucosa to CRC. However, the mechanisms, which mediate the effects of diet on tumorigenesis are largely unknown. Since both genetic and lifestyle factors have been shown to predispose to cancer, this the- sis analyzed biochemical defects caused by inherited MMR gene mutations and Western diet exposure. Different MMR gene mutations may compromise MMR function through various biochemical defects. Here, we studied 18 inherited non-truncating mutations in MSH2, the second most frequently mutated gene among Lynch syndrome patients. We assessed protein stability, DNA binding, and ATP mediated DNA release abilities of the MSH2 variants. The majority of variants in the amino terminal region including the connector and lever domains p.V161D, p.G162R, p.G164R, p.L173P, p.L187P, p.C333Y, p.D603N) affected protein stabil- ity. Variations in the ATPase domain (p.A636P, p.G674A, p.C697F, p.I745-I746del, p.E749K) totally abolished either mismatch binding or release. Four protein variants (p.T33P, p.A272 V, p.G322D, p.V923E) expressed slightly reduced mismatch binding and/or release efficiencies compared to wild-type (WT) MSH2 protein, while two variants (p.N127S, p.A834T) were in- distinguishable from WT. To define the effects of Western-style diet, we analyzed protein expression changes in histolog- ically normal colon mucosa of wild type (Mlh1+/+) and CRC predisposed mice (Mlh1+/-) after a long-term feeding experiment with WD and AIN-93G control diet. Using network analysis and data mining we also determined which of the affected proteins might be putative play- ers in early CRC development. Our results pinpoint changes in a complex protein interaction network involved in ATP synthesis coupled proton transport, oxidoreduction coenzyme and nicotinamide nucleotide metabolic processes, which are important in the generation of reactive oxygen species (ROS) and cellular protection against ROS toxicity. Additionally, we detected SELENBP1 and LGALS4, which are implied in neoplastic processes. Our studies show that mutations in the MMR gene affect the biochemistry of MMR, can have an effect on the phenotype of the mutation carriers and in the latest study suggest that the high sensitivity to Western diet may be linked to haplo-insufficiency caused by a loss of function mutation in the Mlh1+/- mice