Caspase-1 and the inflammasome promote polycystic kidney disease progression.

We and others have previously shown that the presence of renal innate immune cells can promote polycystic kidney disease (PKD) progression. In this study, we examined the influence of the inflammasome, a key part of the innate immune system, on PKD. The inflammasome is a system of molecular sensors, receptors, and scaffolds that responds to stimuli like cellular damage or microbes by activating Caspase-1, and generating critical mediators of the inflammatory milieu, including IL-1ß and IL-18. We provide evidence that the inflammasome is primed in PKD, as multiple inflammasome sensors were upregulated in cystic kidneys from human ADPKD patients, as well as in kidneys from both orthologous (PKD1 RC/RC or RC/RC) and non-orthologous (jck) mouse models of PKD. Further, we demonstrate that the inflammasome is activated in female RC/RC mice kidneys, and this activation occurs in renal leukocytes, primarily in CD11c+ cells. Knock-out of Casp1, the gene encoding Caspase-1, in the RC/RC mice significantly restrained cystic disease progression in female mice, implying sex-specific differences in the renal immune environment. RNAseq analysis implicated the promotion of MYC/YAP pathways as a mechanism underlying the pro-cystic effects of the Caspase-1/inflammasome in females. Finally, treatment of RC/RC mice with hydroxychloroquine, a widely used immunomodulatory drug that has been shown to inhibit the inflammasome, protected renal function specifically in females and restrained cyst enlargement in both male and female RC/RC mice. Collectively, these results provide evidence for the first time that the activated Caspase-1/inflammasome promotes cyst expansion and disease progression in PKD, particularly in females. Moreover, the data suggest that this innate immune pathway may be a relevant target for therapy in PKD.

Mutations in Coagulation Factor VIII Are Associated with More Favorable Outcome in Patients with Cutaneous Melanoma.

Coagulation factor VIII (FVIII), von Willebrand factor (VWF), and ADAMTS13 play an important role in regulation of normal hemostasis. However, little is known about their roles in patients with malignancy, particularly with cutaneous melanoma. Whole genome sequencing data are available for 25,719 cases in 126 cancer genomic studies for analysis. All sequencing data and corresponding pathology findings were obtained from The Cancer Genome Atlas. The cBioportal bioinformatics tools were used for the data analysis. Our results demonstrated that mutations in genes encoding FVIII, VWF, and ADAMTS13 were reported in 92 of 126 cancer genomic studies and high mutation rates in these three genes were observed in patients with cutaneous melanoma from three independent studies. Moreover, high mutation rates in FVIII, VWF, and ADAMTS13 were also found in patients with diffuse large B cell lymphoma (22.9%), lung small cell carcinoma (20.7%), and colon adenocarcinoma (19.4%). Among 366 melanoma cases from TCGA provisional, the somatic mutation rates of FVIII, VWF and ADAMTS13 in tumor cells were 15%, 14%, and 5%, respectively. There was a strong tendency for coexisting mutations of FVIII, VWF, and ADAMTS13. Kaplan-Meier survival analysis demonstrated that melanoma patients with FVIII mutations had a more favorable overall survival rate than those without FVIII mutations (p=0.02). These findings suggest for the first time that the FVIII mutation burden may have a prognostic value for patients with cutaneous melanoma. Further studies are warranted to delineate the molecular mechanisms underlying the favorable prognosis associated with FVIII mutations.

Computational methods and resources for the interpretation of genomic variants in cancer.

The recent improvement of the high-throughput sequencing technologies is having a strong impact on the detection of genetic variations associated with cancer. Several institutions worldwide have been sequencing the whole exomes and or genomes of cancer patients in the thousands, thereby providing an invaluable collection of new somatic mutations in different cancer types. These initiatives promoted the development of methods and tools for the analysis of cancer genomes that are aimed at studying the relationship between genotype and phenotype in cancer. In this article we review the online resources and computational tools for the analysis of cancer genome. First, we describe the available repositories of cancer genome data. Next, we provide an overview of the methods for the detection of genetic variation and computational tools for the prioritization of cancer related genes and causative somatic variations. Finally, we discuss the future perspectives in cancer genomics focusing on the impact of computational methods and quantitative approaches for defining personalized strategies to improve the diagnosis and treatment of cancer.

ContrastRank: a new method for ranking putative cancer driver genes and classification of tumor samples.

MOTIVATION: The recent advance in high-throughput sequencing technologies is generating a huge amount of data that are becoming an important resource for deciphering the genotype underlying a given phenotype. Genome sequencing has been extensively applied to the study of the cancer genomes. Although a few methods have been already proposed for the detection of cancer-related genes, their automatic identification is still a challenging task. Using the genomic data made available by The Cancer Genome Atlas Consortium (TCGA), we propose a new prioritization approach based on the analysis of the distribution of putative deleterious variants in a large cohort of cancer samples. RESULTS: In this paper, we present ContastRank, a new method for the prioritization of putative impaired genes in cancer. The method is based on the comparison of the putative defective rate of each gene in tumor versus normal and 1000 genome samples. We show that the method is able to provide a ranked list of putative impaired genes for colon, lung and prostate adenocarcinomas. The list significantly overlaps with the list of known cancer driver genes previously published. More importantly, by using our scoring approach, we can successfully discriminate between TCGA normal and tumor samples. A binary classifier based on ContrastRank score reaches an overall accuracy >90% and the area under the curve (AUC) of receiver operating characteristics (ROC) >0.95 for all the three types of adenocarcinoma analyzed in this paper. In addition, using ContrastRank score, we are able to discriminate the three tumor types with a minimum overall accuracy of 77% and AUC of 0.83. CONCLUSIONS: We describe ContrastRank, a method for prioritizing putative impaired genes in cancer. The method is based on the comparison of exome sequencing data from different cohorts and can detect putative cancer driver genes. ContrastRank can also be used to estimate a global score for an individual genome about the risk of adenocarcinoma based on the genetic variants information from a whole-exome VCF (Variant Calling Format) file. We believe that the application of ContrastRank can be an important step in genomic medicine to enable genome-based diagnosis. AVAILABILITY AND IMPLEMENTATION: The lists of ContrastRank scores of all genes in each tumor type are available as supplementary materials. A webserver for evaluating the risk of the three studied adenocarcinomas starting from whole-exome VCF file is under development. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Draft Genome Sequence of Pseudomonas sp. Strain Ant30-3, a Psychrotolerant Bacterium with Biodegradative Attribute Isolated from Antarctica.

Pseudomonas sp. strain Ant30-3, isolated from fuel-contaminated Antarctic soil, exhibited distinctive psychrotolerant attributes and the potential for degrading aromatic hydrocarbon compounds at cold temperatures. We report here the 6.14-Mb draft genome of Ant30-3, which will provide insights into the genomic basis for the psychrotolerant and biodegradative properties of this bacterium.

TIGRFAMs and Genome Properties in 2013.

TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.

ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process.

BACKGROUND: Phylogenetic profiling is a technique of scoring co-occurrence between a protein family and some other trait, usually another protein family, across a set of taxonomic groups. In spite of several refinements in recent years, the technique still invites significant improvement. To be its most effective, a phylogenetic profiling algorithm must be able to examine co-occurrences among protein families whose boundaries are uncertain within large homologous protein superfamilies. RESULTS: Partial Phylogenetic Profiling (PPP) is an iterative algorithm that scores a given taxonomic profile against the taxonomic distribution of families for all proteins in a genome. The method works through optimizing the boundary of each protein family, rather than by relying on prebuilt protein families or fixed sequence similarity thresholds. Double Partial Phylogenetic Profiling (DPPP) is a related procedure that begins with a single sequence and searches for optimal granularities for its surrounding protein family in order to generate the best query profiles for PPP. We present ProPhylo, a high-performance software package for phylogenetic profiling studies through creating individually optimized protein family boundaries. ProPhylo provides precomputed databases for immediate use and tools for manipulating the taxonomic profiles used as queries. CONCLUSION: ProPhylo results show universal markers of methanogenesis, a new DNA phosphorothioation-dependent restriction enzyme, and efficacy in guiding protein family construction. The software and the associated databases are freely available under the open source Perl Artistic License from ftp://ftp.jcvi.org/pub/data/ppp/.

Signs of positive selection of somatic mutations in human cancers detected by EST sequence analysis.

BACKGROUND: Carcinogenesis typically involves multiple somatic mutations in caretaker (DNA repair) and gatekeeper (tumor suppressors and oncogenes) genes. Analysis of mutation spectra of the tumor suppressor that is most commonly mutated in human cancers, p53, unexpectedly suggested that somatic evolution of the p53 gene during tumorigenesis is dominated by positive selection for gain of function. This conclusion is supported by accumulating experimental evidence of evolution of new functions of p53 in tumors. These findings prompted a genome-wide analysis of possible positive selection during tumor evolution. METHODS: A comprehensive analysis of probable somatic mutations in the sequences of Expressed Sequence Tags (ESTs) from malignant tumors and normal tissues was performed in order to access the prevalence of positive selection in cancer evolution. For each EST, the numbers of synonymous and non-synonymous substitutions were calculated. In order to identify genes with a signature of positive selection in cancers, these numbers were compared to: i) expected numbers and ii) the numbers for the respective genes in the ESTs from normal tissues. RESULTS: We identified 112 genes with a signature of positive selection in cancers, i.e., a significantly elevated ratio of non-synonymous to synonymous substitutions, in tumors as compared to 37 such genes in an approximately equal-sized EST collection from normal tissues. A substantial fraction of the tumor-specific positive-selection candidates have experimentally demonstrated or strongly predicted links to cancer. CONCLUSION: The results of EST analysis should be interpreted with extreme caution given the noise introduced by sequencing errors and undetected polymorphisms. Furthermore, an inherent limitation of EST analysis is that multiple mutations amenable to statistical analysis can be detected only in relatively highly expressed genes. Nevertheless, the present results suggest that positive selection might affect a substantial number of genes during tumorigenic somatic evolution.

APOBEC4, a new member of the AID/APOBEC family of polynucleotide (deoxy)cytidine deaminases predicted by computational analysis.

Using iterative database searches, we identified a new subfamily of the AID/APOBEC family of RNA/DNA editing cytidine deaminases. The new subfamily, which is represented by readily identifiable orthologs in mammals, chicken, and frog, but not fishes, was designated APOBEC4. The zinc-coordinating motifs involved in catalysis and the secondary structure of the APOBEC4 deaminase domain are evolutionarily conserved, suggesting that APOBEC4 proteins are active polynucleotide (deoxy)cytidine deaminases. In reconstructed maximum likelihood phylogenetic trees, APOBEC4 forms a distinct clade with a high statistical support. APOBEC4 and APOBEC1 are joined in a moderately supported cluster clearly separated from AID, APOBEC2 and APOBEC3 subfamilies. In mammals, APOBEC4 is expressed primarily in testis which suggests the possibility that it is an editing enzyme for mRNAs involved in spermatogenesis.

Evolution of eukaryotic cysteine sulfinic acid reductase, sulfiredoxin (Srx), from bacterial chromosome partitioning protein ParB.

Sufiredoxin (Srx) is a sulfinic acid reductase, a recently identified eukaryotic enzyme, which is involved in the reduction of the hyperoxidized sulfinic acid form of the catalytic cysteine of 2-Cys peroxiredoxins (Prx). This reaction contributes to the oxidative stress response and H2O2 mediated signaling. We show that Srx has significant sequence and structural similarity to a functionally unrelated protein, ParB, a DNA-binding protein with a helix-turn-helix (HTH) domain which is involved in chromosome partitioning in bacteria. Sequence comparison and phylogenetic analysis of the Srx and ParB protein families suggest that Srx evolved via truncation of ParB, which removed the entire C-terminal half of the protein, including the HTH domain, and a substitution of cysteine for a glutamic acid in a highly conserved structural motif of ParB. The latter substitution apparently created the sulfinic acid reductase catalytic site. Evolution of a redox enzyme from a DNA-binding protein, with retention of highly significant sequence similarity, is unusual, even when compared to functional switches accompanying recruitment of other prokaryotic proteins for new functions in eukaryotes.