DNA–protein interactions play critical roles in the control of genome expression and other fundamental processes. An essential element in understanding how these systems function is to identify their molecular components. We present here a novel strategy, Hybridization Capture of Chromatin Associated Proteins for Proteomics (HyCCAPP), to identify proteins that are interacting with any given region of the genome. This technology identifies and quantifies the proteins that are specifically interacting with a genomic region of interest by sequence-specific hybridization capture of the target region from in vivo cross-linked chromatin, followed by mass spectrometric identification and quantification of associated proteins. We demonstrate the utility of HyCCAPP by identifying proteins associated with three multicopy and one single-copy loci in yeast. In each case, a locus-specific pattern of target-associated proteins was revealed. The binding of previously unknown proteins was confirmed by ChIP in 11 of 17 cases. The identification of many previously known proteins at each locus provides strong support for the ability of HyCCAPP to correctly identify DNA-associated proteins in a sequence-specific manner, while the discovery of previously unknown proteins provides new biological insights into transcriptional and regulatory processes at the target locus.

About one fourth of people diagnosed with kidney cancer in 2007, are expected to die of this disease within 5 years from the date of diagnosis. Recent years have produced novel drugs, some with FDA approval, and many in clinical trials, all showing very discrete results. Failure in finding effective treatments to improve survival with drugs mainly targeting VEGF and its downstream effectors, urges to shift the drug development targets to other unexploited pathways shown to be also involved in renal cancer. Several studies show alterations in the Wnt signaling pathway, many of which differ from those implicated in other human cancers. Unlike colorectal or hepatocellular carcinomas, where APC and axin mutations, respectively, are the main Wnt signaling deregulating event, renal carcinomas seem to be affected by other factors. Recent studies have presented VHL, a tumor suppressor gene strongly associated with renal cell carcinoma, as a beta-catenin target. This confirms that Wnt signaling is likely playing a central role during renal carcinoma development, which needs to be considered and addressed to treat this disease. This review outlines briefly the molecular biology of the most common renal cancers and the drug treatments currently used to treat the disease. The canonical Wnt pathway is reviewed more carefully adding specific features in a renal carcinoma context, which present potential targets for drug development and biomarker use.

BackgroundFas, a member of the tumor necrosis family, is responsible for initiating the apoptotic pathway when bound to its ligand, Fas-L. Defects in the Fas-mediated apoptotic pathway have been reported in colorectal cancer.Methodology/Principal FindingsIn the present study, a variant of the ApcMin/+ mouse, a model for the human condition, Familial Adenomatous Polyposis (FAP), was generated with an additional deficiency of Fas (ApcMin/+/Faslpr) by cross-breeding ApcMin/+ mice with Fas deficient (Faslpr) mice. One of the main limitations of the ApcMin/+ mouse model is that it only develops benign polyps. However, ApcMin/+/Faslpr mice presented with a dramatic increase in tumor burden relative to ApcMin/+ mice and invasive lesions at advanced ages. Proliferation and apoptosis markers revealed an increase in cellular proliferation, but negligible changes in apoptosis, while p53 increased at early ages. Fas-L was lower in ApcMin/+/Faslpr mice relative to ApcMin/+ cohorts, which resulted in enhanced inflammation.Conclusions/SignificanceThis study demonstrated that imposition of a Fas deletion in an ApcMin/+ background results in a more aggressive phenotype of the ApcMin/+ mouse model, with more rapid development of invasive intestinal tumors and a decrease in Fas-L levels.

Non-steroidal anti-inflammatory drugs (NSAIDs) have shown potential as chemopreventive agents against cancer formation, especially colorectal cancers. However, the mechanisms by which these drugs act are not fully understood. In this study, Apc(Min/+) mice, a genetic model of human familial adenomatous polyposis, were treated with sulindac, and these mice demonstrated tumor reduction of >80%, consistent with previous reports. Gene microarray analyses of RNA from adenoma-derived dysplastic epithelial cells revealed that collagen genes, viz. Col1a2, Col5a2, Col6a2 and Col6a3, were upregulated, and matrilysin matrix metalloproteases-7 (Mmp7) was downregulated, in sulindac-treated mice. Reverse transcription-polymerase chain reaction validated gene expression of the Col6a2 subunit of collagen VI and of Mmp7. Confocal microscopy and immunofluorescence showed that within the tumors of non-treated mice, collagen VI was present in low amounts, but was enhanced within the tumors of sulindac-treated mice. Collagens I and V demonstrated similar patterns, but were not as prominent as collagen VI. Mmp7 was found in 'hot spot' areas within the tumors of Apc(Min/+) mice treated with the vehicle, but was greatly diminished in those mice treated with sulindac. Studies with Apc(Min/+)/Mmp7(-/-) double-deficient mice demonstrated the reciprocal relationships of Mmp7 expression and the levels of these three collagens in vivo. The results of this study demonstrated that sulindac was effective in increasing the expression of different collagens and decreasing the expression of Mmp7, effects that may contribute to altered tumor burden in cancer patients undergoing NSAIDs treatments.

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of S. cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges.

BackgroundSensorineural hearing loss (SNHL) is a common form of hearing loss that can be inherited or triggered by environmental insults; auditory neuropathy spectrum disorder (ANSD) is a SNHL subtype with unique diagnostic criteria. The genetic factors associated with these impairments are vast and diverse, but causal genetic factors are rarely characterized.MethodsA family dyad, both cochlear implant recipients, presented with a hearing history of bilateral, progressive SNHL, and ANSD. Whole‐exome sequencing was performed to identify coding sequence variants shared by both family members, and screened against genes relevant to hearing loss and variants known to be associated with SNHL and ANSD.ResultsBoth family members are successful cochlear implant users, demonstrating effective auditory nerve stimulation with their devices. Genetic analyses revealed a mutation (rs35725509) in the TMTC2 gene, which has been reported previously as a likely genetic cause of SNHL in another family of Northern European descent.ConclusionThis study represents the first confirmation of the rs35725509 variant in an independent family as a likely cause for the complex hearing loss phenotype (SNHL and ANSD) observed in this family dyad.

Introduction: Reliable and effective label-free quantification (LFQ) analyses are dependent not only on the method of data acquisition in the mass spectrometer, but also on the downstream data processing, including software tools, query database, data normalization and imputation. In non-human primates (NHP), LFQ is challenging because the query databases for NHP are limited since the genomes of these species are not comprehensively annotated. This invariably results in limited discovery of proteins and associated Post Translational Modifications (PTMs) and a higher fraction of missing data points. While identification of fewer proteins and PTMs due to database limitations can negatively impact uncovering important and meaningful biological information, missing data also limits downstream analyses (e.g., multivariate analyses), decreases statistical power, biases statistical inference, and makes biological interpretation of the data more challenging. In this study we attempted to address both issues: first, we used the MetaMorphues proteomics search engine to counter the limits of NHP query databases and maximize the discovery of proteins and associated PTMs, and second, we evaluated different imputation methods for accurate data inference. Results: Using the MetaMorpheus proteomics search engine we obtained quantitative data for 1,622 proteins and 10,634 peptides including 58 different PTMs (biological, metal and artifacts) across a diverse age range of NHP brain frontal cortex. However, among the 1,622 proteins identified, only 293 proteins were quantified across all samples with no missing values, emphasizing the importance of implementing an accurate and statically valid imputation method to fill in missing data. In our imputation analysis we demonstrate that Single Imputation methods that borrow information from correlated proteins such as Generalized Ridge Regression (GRR), Random Forest (RF), local least squares (LLS), and a Bayesian Principal Component Analysis methods (BPCA), are able to estimate missing protein abundance values with great accuracy. Conclusions: Overall, this study offers a detailed comparative analysis of LFQ data generated in NHP and proposes strategies for improved LFQ in NHP proteomics data.

Guillen-Ahlers H, Shortreed MR, Smith LM, Olivier M. Advanced methods for the analysis of chromatin-associated proteins. Physiol Genomics 46: [441][442][443][444][445][446][447] 2014. First published May 6, 2014; doi:10.1152/physiolgenomics.00041.2014.-DNA-protein interactions are central to gene expression and chromatin regulation and have become one of the main focus areas of the ENCODE consortium. Advances in mass spectrometry and associated technologies have facilitated studies of these interactions, revealing many novel DNA-interacting proteins and histone posttranslational modifications. Proteins interacting at a single locus or at multiple loci have been targeted in these recent studies, each requiring a separate analytical strategy for isolation and analysis of DNA-protein interactions. The enrichment of target chromatin fractions occurs via a number of methods including immunoprecipitation, affinity purification, and hybridization, with the shared goal of using proteomics approaches as the final readout. The result of this is a number of exciting new tools, with distinct strengths and limitations that can enable highly robust and novel chromatin studies when applied appropriately. The present review compares and contrasts these methods to help the reader distinguish the advantages of each approach.DNA-protein interactions; chromatin; mass spectrometry; chromatin enrichment; affinity purification THE COMPLETION OF THE HUMAN genome project has provided the scientific community with invaluable information about our genetic makeup. With the actual nucleotide sequence in hand, the key question in genomics and human biology is now how this genetic information is used and regulated. How is the expression of genes controlled on the molecular level? What molecules regulate and modulate the levels of expression of individual genes, and how do these regulatory mechanisms allow a cell and an entire organism to effectively respond to physiological stimuli and stressors? In an initial effort to address these questions and to identify parts of the genome that are essential for this regulatory control of the expression of all genes in the genome, the Encyclopedia of DNA Elements (ENCODE) consortium (9) has begun to identify and catalog the functional elements encoded in the genome. Investigators focused on three interactions that are important for gene regulation: the binding of specific transcription factors (TF) and other DNA-binding proteins to sequence elements in the genome, the characterization of histone modifications and nucleosome positioning as a local regulator of chromatin structure, and the analysis of long-range structural interactions between distal regions of the genome, believed to affect accessibility of chromatin regions for transcription.With this large-scale effort, significant progress has been made in understanding how individual proteins that are part of the transcription machinery mediate the expression of genes by binding to specific elements in the DNA (For review see Ref.