Genetic alterations and cancer formation in a European flatfish at sites of different contamination burdens

Fish diseases are an indicator for marine ecosystem health since they provide a biological end-point of historical exposure to stressors. Liver cancer has been used to monitor the effects of exposure to anthropogenic pollution in flatfish for many years. The prevalence of liver cancer can exceed 20%. Despite the high prevalence and the opportunity of using flatfish to study environmentally induced cancer, the genetic and environmental factors driving tumor prevalence across sites are poorly understood. This study aims to define the link between genetic deterioration, liver disease progression, and anthropogenic contaminant exposures in the flatfish dab (Limanda limanda). We assessed genetic changes in a conserved cancer gene, Retinoblastoma (Rb), in association with histological diagnosis of normal, pretumor, and tumor pathologies in the livers of 165 fish from six sites in the North Sea and English Channel. The highest concentrations of metals (especially cadmium) and organic chemicals correlated with the presence of tumor pathology and with defined genetic profiles of the Rb gene, from these sites. Different Rb genetic profiles were found in liver tissue near each tumor phenotype, giving insight into the mechanistic molecular-level cause of the liver pathologies. Different Rb profiles were also found at sampling sites of differing contaminant burdens. Additionally, profiles indicated that histological “normal” fish from Dogger sampling locations possessed Rb profiles associated with pretumor disease. This study highlights an association between Rb and specific contaminants (especially cadmium) in the molecular etiology of dab liver tumorigenesis

Hepatocellular adenoma in a European flatfish (Limanda limanda) : genetic alterations in laser-capture microdissected tissue and global transcriptomic approach

Liver tumours in flatfish have been diagnosed using histopathology for decades to monitor the impacts of marine pollution. Here we describe the application of specific gene (retinoblastoma, Rb) profiling in laser capture micro-dissected samples, and a suppression subtractive hybridization (SSH) approach to isolate differentially expressed genes in hepatocellular adenoma (HCA) samples from dab, Limanda limanda. The Rb profiles from apparently normal and HCA micro-dissected samples of fish from the North Sea showed no significant difference, and genotypic heterogeneity within defined histological phenotypes was observed. In the SSH, sequences associated with cell signalling, cell cycle, gene expression regulation, protein transport and protein degradation were isolated. These included up-regulation of arrestin domain containing 3 (arrdc3), Rac-1 and tribbles, and down-regulation of ankyrin repeat/sterile alpha-motif domain-containing protein 1B-like (ANKS1B-like), c-fos, CDKN1B and RhoA-like sequences, previously implicated in mammalian HCA. This study offers new candidates involved in fish liver tumour development

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of distributions that commonly appear in the analysis of such data. These distributions present some interesting features: they are discontinuous in the rational numbers, but continuous in the irrational numbers, and possess a certain self-similar (fractal-like) structure. The first set of examples which we present here are drawn from a high-throughput sequencing experiment. Here, the self-similar distributions appear as part of the evaluation of the error rate of the sequencing technology and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in electronic clinical data. The distributions are also relevant to identification of subclonal populations in tumors and the study of the evolution of infectious diseases, and more precisely the study of quasi-species and intrahost diversity of viral populations

Plasmonic light yield enhancement of a liquid scintillator

We demonstrate modifications to the light yield properties of an organic liquid scintillator due to the localization of the tertiary fluorophore component to the surface of Ag-core silica-shell nanoparticles. We attribute this enhancement to the near-field interaction of Ag nanoparticle plasmons with these fluor molecules. The scintillation light yield enhancement is shown to be equal to the fluorescence enhancement within measurement uncertainties. With a suitable choice of plasmon energy and scintillation fluor, this effect may be used to engineer scintillators with enhanced light yields for radiation detection applications

Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process

Breakage-Fusion-Bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. The process has parallels with paper folding sequences that arise when a piece of paper is folded several times and then unfolded. Here we adapt such methods to study the breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are 2^(n(n-1)/2) qualitatively distinct evolutions involving n breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the fold positions, to determine evolution likelihoods, and also describe how amplicons become localised. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples

CYLD negatively regulates cell-cycle progression by inactivating HDAC6 and increasing the levels of acetylated tubulin

CYLD is a tumour-suppressor gene that is mutated in a benign skin tumour syndrome called cylindromatosis. The CYLD gene product is a deubiquitinating enzyme that was shown to regulate cell proliferation, cell survival and inflammatory responses, mainly through inhibiting NF-κB signalling. Here we show that CYLD controls cell growth and division at the G1/S-phase as well as cytokinesis by associating with α-tubulin and microtubules through its CAP-Gly domains. Translocation of activated CYLD to the perinuclear region of the cell is achieved by an inhibitory interaction of CYLD with histone deacetylase-6 (HDAC6) leading to an increase in the levels of acetylated α-tubulin around the nucleus. This facilitates the interaction of CYLD with Bcl-3, leading to a significant delay in the G1-to-S-phase transition. Finally, CYLD also interacts with HDAC6 in the midbody where it regulates the rate of cytokinesis in a deubiquitinase-independent manner. Altogether these results identify a mechanism by which CYLD regulates cell proliferation at distinct cell-cycle phases

A catalogue of ULX coincidences with FIRST radio sources

We search for ultra luminous X-ray source (ULXs) radio counterparts located in nearby galaxies in order to constrain their physical nature. Our work is based on a systematic cross-identification of the most recent and extensive available ULX catalogues and archival radio data. A catalogue of 70 positional coincidences is reported. Most of them are located within the galaxy nucleus. Among them, we find 11 new cases of non-nuclear ULX sources with possibly associated radio emission.Comment: Accepted for publication in A&A; 17 pages, 9 figure

Genotyping and annotation of Affymetrix SNP arrays

In this paper we develop a new method for genotyping Affymetrix single nucleotide polymorphism (SNP) array. The method is based on (i) using multiple arrays at the same time to determine the genotypes and (ii) a model that relates intensities of individual SNPs to each other. The latter point allows us to annotate SNPs that have poor performance, either because of poor experimental conditions or because for one of the alleles the probes do not behave in a dose–response manner. Generally, our method agrees well with a method developed by Affymetrix. When both methods make a call they agree in 99.25% (using standard settings) of the cases, using a sample of 113 Affymetrix 10k SNP arrays. In the majority of cases where the two methods disagree, our method makes a genotype call, whereas the method by Affymetrix makes a no call, i.e. the genotype of the SNP is not determined. By visualization it is indicated that our method is likely to be correct in majority of these cases. In addition, we demonstrate that our method produces more SNPs that are in concordance with Hardy–Weinberg equilibrium than the method by Affymetrix. Finally, we have validated our method on HapMap data and shown that the performance of our method is comparable to other methods