An artificial protein cage made from a 12-membered ring

Artificial protein cages have great potential in diverse fields including as vaccines and drug delivery vehicles. TRAP-cage is an artificial protein cage notable for the way in which the interface between its ring-shaped building blocks can be modified such that the conditions under which cages disassemble can be controlled. To date, TRAP-cages have been constructed from homo-11mer rings, i.e., hendecamers. This is interesting as convex polyhedra with identical regular faces cannot be formed from hendecamers. TRAP-cage overcomes this limitation due to intrinsic flexibility, allowing slight deformation to absorb any error. The resulting TRAP-cage made from 24 TRAP 11mer rings is very close to regular with only very small errors necessary to allow the cage to form. The question arises as to the limits of the error that can be absorbed by a protein structure in this way before the formation of an apparently regular convex polyhedral becomes impossible. Here we use a naturally occurring TRAP variant consisting of twelve identical monomers (i.e., a dodecamer) to probe these limits. We show that it is able to form an apparently regular protein cage consisting of twelve TRAP rings. Comparison of the cryo-EM structure of the new cage with theoretical models and related cages gives insight into the rules of cage formation and allows us to predict other cages that may be formed given TRAP-rings consisting of different numbers of monomers

ParkDB: a Parkinson's disease gene expression database

Parkinson's disease (PD) is a common, adult-onset, neuro-degenerative disorder characterized by the degeneration of cardinal motor signs mainly due to the loss of dopaminergic neurons in the substantia nigra. To date, researchers still have limited understanding of the key molecular events that provoke neurodegeneration in this disease. Here, we present ParkDB, the first queryable database dedicated to gene expression in PD. ParkDB contains a complete set of re-analyzed, curated and annotated microarray datasets. This resource enables scientists to identify and compare expression signatures involved in PD and dopaminergic neuron differentiation under different biological conditions and across species. Database URL: http://www2.cancer.ucl.ac.uk/Parkinson_Db2

Comparative analysis of the testis and ovary transcriptomes in Zebrafish by combining experimental and computational tools

Studies on the zebrafish model have contributed to our understanding of several important developmental processes, especially those that can be easily studied in the embryo. However, our knowledge on late events such as gonad differentiation in the zebrafish is still limited. Here we provide an analysis on the gene sets expressed in the adult zebrafish testis and ovary in an attempt to identify genes with potential role in (zebra)fish gonad development and function. We produced 10,533 expressed sequence tags (ESTs) from zebrafish testis or ovary and downloaded an additional 23,642 gonad-derived sequences from the zebrafish EST database. We clustered these sequences together with over 13,000 kidney-derived zebrafish ESTs to study partial transcriptomes for these three organs. We searched for genes with gonad-specific expression by screening macroarrays containing at least 2600 unique cDNA inserts with testis-, ovary- and kidney-derived cDNA probes. Clones hybridizing to only one of the two gonad probes were selected, and subsequently screened with computational tools to identify 72 genes with potentially testis-specific and 97 genes with potentially ovary-specific expression, respectively. PCR-amplification confirmed gonad-specificity for 21 of the 45 clones tested (all without known function). Our study, which involves over 47,000 EST sequences and specialized cDNA arrays, is the first analysis of adult organ transcriptomes of zebrafish at such a scale. The study of genes expressed in adult zebrafish testis and ovary will provide useful information on regulation of gene expression in teleost gonads and might also contribute to our understanding of the development and differentiation of reproductive organs in vertebrates

HMGA1 promotes breast cancer angiogenesis supporting the stability, nuclear localization and transcriptional activity of FOXM1

Background Breast cancer is the most common malignancy in women worldwide. Among the breast cancer subtypes, triple-negative breast cancer (TNBC) is the most aggressive and the most difficult to treat. One of the master regulators in TNBC progression is the architectural transcription factor HMGA1. This study aimed to further explore the HMGA1 molecular network to identify molecular mechanisms involved in TNBC progression. Methods RNA from the MDA-MB-231 cell line, silenced for HMGA1 expression, was sequenced and, with a bioinformatic analysis, molecular partners HMGA1 could cooperate with in regulating common downstream gene networks were identified. Among the putative partners, the FOXM1 transcription factor was selected. The relationship occurring between HMGA1 and FOXM1 was explored by qRT-PCR, co-immunoprecipitation and protein stability assays. Subsequently, the transcriptional activity of HMGA1 and FOXM1 was analysed by luciferase assay on the VEGFA promoter. The impact on angiogenesis was assessed in vitro, evaluating the tube formation ability of endothelial cells exposed to the conditioned medium of MDA-MB-231 cells silenced for HMGA1 and FOXM1 and in vivo injecting MDA-MB-231 cells, silenced for the two factors, in zebrafish larvae. Results Here, we discover FOXM1 as a novel molecular partner of HMGA1 in regulating a gene network implicated in several breast cancer hallmarks. HMGA1 forms a complex with FOXM1 and stabilizes it in the nucleus, increasing its transcriptional activity on common target genes, among them, VEGFA, the main inducer of angiogenesis. Furthermore, we demonstrate that HMGA1 and FOXM1 synergistically drive breast cancer cells to promote tumor angiogenesis both in vitro in endothelial cells and in vivo in a zebrafish xenograft model. Moreover, using a dataset of breast cancer patients we show that the co-expression of HMGA1, FOXM1 and VEGFA is a negative prognostic factor of distant metastasis-free survival and relapse-free survival. Conclusions This study reveals FOXM1 as a crucial interactor of HMGA1 and proves that their cooperative action supports breast cancer aggressiveness, by promoting tumor angiogenesis. Therefore, the possibility to target HMGA1/FOXM1 in combination should represent an attractive therapeutic option to counteract breast cancer angiogenesis

The UniTrap resource: tools for the biologist enabling optimized use of gene trap clones

We have developed a comprehensive resource devoted to biologists wanting to optimize the use of gene trap clones in their experiments. We have processed 300 602 such clones from both public and private projects to generate 28 199 ‘UniTraps’, i.e. distinct collections of unambiguous insertions at the same subgenic region of annotated genes. The UniTrap resource contains data relative to 9583 trapped genes, which represent 42.3% of the mouse gene content. Among the trapped genes, 7 728 have a counterpart in humans, and 677 are known to be involved in the pathogenesis of human diseases. The aim of this analysis is to provide the wet lab researchers with a comprehensive database and curated tools for (i) identifying and comparing the clones carrying a trap into the genes of interest, (ii) evaluating the severity of the mutation to the protein function in each independent trapping event and (iii) supplying complete information to perform PCR, RT-PCR and restriction experiments to verify the clone and identify the exact point of vector insertion. To share this unique resource with the scientific community, we have designed and implemented a web interface that is freely accessible at http://unitrap.cbm.fvg.it/

BASC: an integrated bioinformatics system for Brassica research

The BASC system provides tools for the integrated mining and browsing of genetic, genomic and phenotypic data. This public resource hosts information on Brassica species supporting the Multinational Brassica Genome Sequencing Project, and is based upon five distinct modules, ESTDB, Microarray, MarkerQTL, CMap and EnsEMBL. ESTDB hosts expressed gene sequences and related annotation derived from comparison with GenBank, UniRef and the genome sequence of Arabidopsis. The Microarray module hosts gene expression information related to genes annotated within ESTDB. MarkerQTL is the most complex module and integrates information on genetic markers, maps, individuals, genotypes and traits. Two further modules include an Arabidopsis EnsEMBL genome viewer and the CMap comparative genetic map viewer for the visualization and integration of genetic and genomic data. The database is accessible at

Genome-wide signatures of convergent evolution in echolocating mammals

Evolution is typically thought to proceed through divergence of genes, proteins, and ultimately phenotypes(1-3). However, similar traits might also evolve convergently in unrelated taxa due to similar selection pressures(4,5). Adaptive phenotypic convergence is widespread in nature, and recent results from a handful of genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level(6-9). Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution(9,10) although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show for the first time that convergence is not a rare process restricted to a handful of loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four new bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Surprisingly we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognised

Genome-wide mapping of Myc binding and gene regulation in serum-stimulated fibroblasts

The transition from quiescence to proliferation is a key regulatory step that can be induced by serum stimulation in cultured fibroblasts. The transcription factor Myc is directly induced by serum mitogens and drives a secondary gene expression program that remains largely unknown. Using mRNA profiling, we identify close to 300 Myc-dependent serum response (MDSR) genes, which are induced by serum in a Myc-dependent manner in mouse fibroblasts. Mapping of genomic Myc-binding sites by ChIP-seq technology revealed that most MDSR genes were directly targeted by Myc, but represented a minor fraction (5.5%) of all Myc-bound promoters (which were 22.4% of all promoters). Other target loci were either induced by serum in a Myc-independent manner, were not significantly regulated or were negatively regulated. MDSR gene products were involved in a variety of processes, including nucleotide biosynthesis, ribosome biogenesis, DNA replication and RNA control. Of the 29 MDSR genes targeted by RNA interference, three showed a requirement for cell-cycle entry upon serum stimulation and 11 for long-term proliferation and/or survival. Hence, proper coordination of key regulatory and biosynthetic pathways following mitogenic stimulation relies upon the concerted regulation of multiple Myc-dependent genes

The Bioperl toolkit: Perl modules for the life sciences

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort

The IKMC web portal: a central point of entry to data and resources from the International Knockout Mouse Consortium

The International Knockout Mouse Consortium (IKMC) aims to mutate all protein-coding genes in the mouse using a combination of gene targeting and gene trapping in mouse embryonic stem (ES) cells and to make the generated resources readily available to the research community. The IKMC database and web portal (www.knockoutmouse.org) serves as the central public web site for IKMC data and facilitates the coordination and prioritization of work within the consortium. Researchers can access up-to-date information on IKMC knockout vectors, ES cells and mice for specific genes, and follow links to the respective repositories from which corresponding IKMC products can be ordered. Researchers can also use the web site to nominate genes for targeting, or to indicate that targeting of a gene should receive high priority. The IKMC database provides data to, and features extensive interconnections with, other community databases