Novel Venom Proteins Produced by Differential Domain-Expression Strategies in Beaded Lizards and Gila Monsters (genus Heloderma)

The origin and evolution of venom proteins in helodermatid lizards were investigated by multidisciplinary techniques. Our analyses elucidated novel toxin types resultant from three unique domain-expression processes: 1) The first full-length sequences of lethal toxin isoforms (helofensins) revealed this toxin type to be constructed by an ancestral monodomain, monoproduct gene (beta-defensin) that underwent three tandem domain duplications to encode a tetradomain, monoproduct with a possible novel protein fold; 2) an ancestral monodomain gene (encoding a natriuretic peptide) was medially extended to become a pentadomain, pentaproduct through the additional encoding of four tandemly repeated proline-rich peptides (helokinestatins), with the five discrete peptides liberated from each other by posttranslational proteolysis; and 3) an ancestral multidomain, multiproduct gene belonging to the vasoactive intestinal peptide (VIP)/glucagon family being mutated to encode for a monodomain, monoproduct (exendins) followed by duplication and diversification into two variant classes (exendins 1 and 2 and exendins 3 and 4). Bioactivity characterization of exendin and helokinestatin elucidated variable cardioactivity between isoforms within each class. These results highlight the importance of utilizing evolutionary-based search strategies for biodiscovery and the virtually unexplored potential of lizard venoms in drug design and discovery.

Doxorubicin In Vivo Rapidly Alters Expression and Translation of Myocardial Electron Transport Chain Genes, Leads to ATP Loss and Caspase 3 Activation

Background: Doxorubicin is one of the most effective anti-cancer drugs but its use is limited by cumulative cardiotoxicity that restricts lifetime dose. Redox damage is one of the most accepted mechanisms of toxicity, but not fully substantiated. Moreover doxorubicin is not an efficient redox cycling compound due to its low redox potential. Here we used genomic and chemical systems approaches in vivo to investigate the mechanisms of doxorubicin cardiotoxicity, and specifically test the hypothesis of redox cycling mediated cardiotoxicity.

Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

Background: The bioenergetic status of non-small cell lung cancer correlates with tumour aggressiveness. The voltage dependent anion channel type 1 (VDAC1) is a component of the mitochondrial permeability transition pore, regulates mitochondrial ATP/ADP exchange suggesting that its over-expression could be associated with energy dependent processes including increased proliferation and invasiveness. To test this hypothesis, we conducted an in vivo gene-expression meta-analysis of surgically resected non-small cell lung cancer (NSCLC) using 602 individual expression profiles, to examine the impact of VDAC1 on survival.

Elevated expression of Runx2 as a key parameter in the etiology of osteosarcoma

To understand the molecular etiology of osteosarcoma, we isolated and characterized a human osteosarcoma cell line (OS1). OS1 cells have high osteogenic potential in differentiation induction media. Molecular analysis reveals OS1 cells express the pocket protein pRB and the runt-related transcription factor Runx2. Strikingly, Runx2 is expressed at higher levels in OS1 cells than in human fetal osteoblasts. Both pRB and Runx2 have growth suppressive potential in osteoblasts and are key factors controlling competency for osteoblast differentiation. The high levels of Runx2 clearly suggest osteosarcomas may form from committed osteoblasts that have bypassed growth restrictions normally imposed by Runx2. Interestingly, OS1 cells do not exhibit p53 expression and thus lack a functional p53/p21 DNA damage response pathway as has been observed for other osteosarcoma cell types. Absence of this pathway predicts genomic instability and/or vulnerability to secondary mutations that may counteract the anti-proliferative activity of Runx2 that is normally observed in osteoblasts. We conclude OS1 cells provide a valuable cell culture model to examine molecular events that are responsible for the pathologic conversion of phenotypically normal osteoblast precursors into osteosarcoma cells.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Sequence characterisation and expression of homeobox HOX A7 in the multi-potential erythroleukaemic cell line TF-1

Homeobox gene expression was examined in the erythroleukaemic cell line TF-1. Expression of a number of HOX A, B and C genes, including HOX A7 was detected. Expression of this gene has not previously been reported in erythroleukaemic cell lines. A 2.1 kb full length cDNA of the HOX A7 gene was cloned. The predicted amino acid sequence C-terminal to the homeodomain consists of an alanine-rich region and a strongly negatively charged domain consisting entirely of aspartic and glutamic acid residues.

Applied aspects of Rhodococcus genetics

Eubacteria of the genus Rhodococcus are a diverse group of microorganisms commonly found in many environmental niches from soils to seawaters and as plant and animal pathogens. They exhibit a remarkable ability to degrade many organic compounds and their economic importance is becoming increasingly apparent. Although their genetic organisation is still far from understood, there have been many advances in recent years. Reviewed here is the current knowledge of rhodococci relating to gene transfer, recombination, plasmid replication and functions, cloning vectors and reporter genes, gene expression and its control, bacteriophages, insertion sequences and genomic rearrangements. Further fundamental studies of Rhodococcus genetics and the application of genetic techniques to the these bacteria will be needed for their continued biotechnological exploitation.

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.