Canine models of copper toxicosis for understanding mammalian copper metabolism

Hereditary forms of copper toxicosis exist in man and dogs. In man, Wilson’s disease is the best studied disorder of copper overload, resulting from mutations in the gene coding for the copper transporter ATP7B. Forms of copper toxicosis for which no causal gene is known yet are recognized as well, often in young children. Although advances have been made in unraveling the genetic background of disorders of copper metabolism in man, many questions regarding disease mechanisms and copper homeostasis remain unanswered. Genetic studies in the Bedlington terrier, a dog breed affected with copper toxicosis, identified COMMD1, a gene that was previously unknown to be involved in copper metabolism. Besides the Bedlington terrier, a number of other dog breeds suffer from hereditary copper toxicosis and show similar phenotypes to humans with copper storage disorders. Unlike the heterogeneity of most human populations, the genetic structure within a purebred dog population is homogeneous, which is advantageous for unraveling the molecular genetics of complex diseases. This article reviews the work that has been done on the Bedlington terrier, summarizes what was learned from studies into COMMD1 function, describes hereditary copper toxicosis phenotypes in other dog breeds, and discusses the opportunities for genome-wide association studies on copper toxicosis in the dog to contribute to the understanding of mammalian copper metabolism and copper metabolism disorders in man

Liver-Specific Commd1 Knockout Mice Are Susceptible to Hepatic Copper Accumulation

Canine copper toxicosis is an autosomal recessive disorder characterized by hepatic copper accumulation resulting in liver fibrosis and eventually cirrhosis. We have identified COMMD1 as the gene underlying copper toxicosis in Bedlington terriers. Although recent studies suggest that COMMD1 regulates hepatic copper export via an interaction with the Wilson disease protein ATP7B, its importance in hepatic copper homeostasis is ill-defined. In this study, we aimed to assess the effect of Commd1 deficiency on hepatic copper metabolism in mice. Liver-specific Commd1 knockout mice (Commd1Δhep) were generated and fed either a standard or a copper-enriched diet. Copper homeostasis and liver function were determined in Commd1Δhep mice by biochemical and histological analyses, and compared to wild-type littermates. Commd1Δhep mice were viable and did not develop an overt phenotype. At six weeks, the liver copper contents was increased up to a 3-fold upon Commd1 deficiency, but declined with age to concentrations similar to those seen in controls. Interestingly, Commd1Δhep mice fed a copper-enriched diet progressively accumulated copper in the liver up to a 20-fold increase compared to controls. These copper levels did not result in significant induction of the copper-responsive genes metallothionein I and II, neither was there evidence of biochemical liver injury nor overt liver pathology. The biosynthesis of ceruloplasmin was clearly augmented with age in Commd1Δhep mice. Although COMMD1 expression is associated with changes in ATP7B protein stability, no clear correlation between Atp7b levels and copper accumulation in Commd1Δhep mice could be detected. Despite the absence of hepatocellular toxicity in Commd1Δhep mice, the changes in liver copper displayed several parallels with copper toxicosis in Bedlington terriers. Thus, these results provide the first genetic evidence for COMMD1 to play an essential role in hepatic copper homeostasis and present a valuable mouse model for further understanding of the molecular mechanisms underlying hepatic copper homeostasis

Exploring new physics frontiers through numerical relativity

The demand to obtain answers to highly complex problems within strong-field gravity has been met with significant progress in the numerical solution of Einstein's equations - along with some spectacular results - in various setups. We review techniques for solving Einstein's equations in generic spacetimes, focusing on fully nonlinear evolutions but also on how to benchmark those results with perturbative approaches. The results address problems in high-energy physics, holography, mathematical physics, fundamental physics, astrophysics and cosmology

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases