Luis A. Espinoza

PARP-1 binds E2F-1 independently of its DNA binding and catalytic domains, and acts as a novel coactivator of E2F-1-mediated transcription during re-entry of quiescent cells into S phase.

The transcription factor E2F-1 is implicated in the activation of S-phase genes as well as induction of apoptosis, and is regulated by interactions with Rb and by cell cycle-dependent alterations in E2F-1 abundance. We earlier demonstrated a pivotal role for poly(ADP-ribose) polymerase-1 (PARP-1) in the regulation of E2F-1 expression and promoter activity during S-phase re-entry when quiescent cells re-enter the cell cycle. We now investigate the putative mechanism(s) by which PARP-1 may upregulate E2F-1 promoter activity during S-phase re-entry. DNase-1 footprint assays with purified PARP-1 showed that PARP-1 did not directly bind the E2F-1 promoter in a sequence-specific manner. In contrast to p53, a positive acceptor in poly(ADP-ribosyl)ation reactions, E2F-1 was not poly(ADP-ribosyl)ated by wild-type PARP-1 in vitro, indicating that PARP-1 does not exert a dual effect on E2F-1 transcriptional activation. Protein-binding reactions and coimmunoprecipitation experiments with purified PARP-1 and E2F-1, however, revealed that PARP-1 binds to E2F-1 in vitro. More significantly, physical association of PARP-1 and E2F-1 in vivo also occurred in wild-type fibroblasts 5 h after re-entry into S phase, coincident with the increase in E2F-1 promoter activity and expression of E2F-1-responsive S-phase genes cyclin A and c-Myc. Mapping of the interaction domains revealed that full-length PARP-1 as well as PARP-1 mutants lacking either the catalytic active site or the DNA-binding domain equally bind E2F-1, whereas a PARP-1 mutant lacking the automodification domain does not, suggesting that the protein interaction site is located in this central domain. Finally, gel shift analysis with end-blocked E2F-1 promoter sequence probes verified that the binding of PARP-1 to E2F-1 enhances binding to the E2F-1 promoter, indicating that PARP-1 acts as a positive cofactor of E2F-1-mediated transcription.

Protection by antioxidants against toxicity and apoptosis induced by the sulphur mustard analog 2-chloroethylethyl sulphide (CEES) in Jurkat T cells and normal human lymphocytes

The mechanism of toxicity of sulphur mustard was investigated by examining the biochemical effects of the analog 2‐chloroethylethyl sulphide (CEES) in both human Jurkat cells as well as normal human lymphocytes. Exposure of both types of cells to CEES resulted in a marked decrease in the intracellular concentration of the reduced form of glutathione (GSH), and CEES‐induced cell death was potentiated by L‐buthionine sulphoximine, an inhibitor of GSH synthesis. CEES increased the endogenous production of reactive oxygen species (ROS) in Jurkat cells, and CEES‐induced cell death was potentiated by hydrogen peroxide. CEES induced various hallmarks of apoptosis, including collapse of the mitochondrial membrane potential, proteolytic processing and activation of procaspase‐3, and cleavage of poly (ADP‐ribose) polymerase. The effects of CEES on the accumulation of ROS, the intracellular concentration of GSH, the mitochondrial membrane potential, and caspase‐3 activity were all inhibited by pretreatment of cells with the GSH precursor N‐acetyl cysteine or with GSH‐ethyl ester. Furthermore, CEES‐induced cell death was also prevented by these antioxidants. CEES toxicity appears to be mediated, at least in part, by the generation of ROS and consequent depletion of GSH. Given that sulphur mustard is still a potential biohazard, the protective effects of antioxidants against CEES toxicity demonstrated in Jurkat cells and normal human lymphocytes may provide the basis for the development of a therapeutic strategy to counteract exposure to this chemical weapon.

Macroarray analysis of the effects of JP-8 jet fuel on gene expression in Jurkat cells.

The jet fuel JP-8 is widely used and a large number of military and civilian personnel is, therefore, exposed to it. Treatment of several cell lines, including human Jurkat cells, with JP-8 induces cell death that exhibits various biochemical and morphological characteristics of apoptosis. The molecular mechanism of JP-8 cytotoxicity, however, has remained unclear. The effects of exposure of Jurkat cells to JP-8 (1/10,000 dilution) for 4 h on gene expression have now been examined by cDNA macroarray analysis. We had previously shown in these cells that under the above conditions, JP-8 causes significant apoptosis, based upon the observation that caspase-3 activation occurs at approximately 4 h and consequently most of the other classical apoptotic biochemical and morphological alterations progress until apoptotic cell death at 24 h. Of the 439 apoptosis- or stress response-related genes examined, the expression of 16 genes was up-regulated and that of ten genes was down-regulated by a factor of > or =2. The changes in the expression of 11 of these 26 genes were confirmed by reverse transcription and polymerase chain reaction analysis. These results provide insight into the mechanism of JP-8 toxicity and the associated induction of apoptosis.

Pharmacogenomics of Pulmonary and Respiratory Diseases

The identification of variations or mutations in genes encoding proteins that are involved in drug processing or metabolism can provide key information relevant to differential responses to therapeutic agents in specific genetic populations groups. It is well accepted that genetic variability (functional polymorphisms) may explain the failure of therapies and/or serious adverse side effects during and after treatment. Therefore, there is enormous interest in identifying these variants and determining their clinical relevance. In this regard, the main focus of pharmacogenomics is the study of inherited variations in genes that modulate drug response and their influence in predicting patient response to a specific treatment. For this purpose, pharmacogenomics integrates genomic information and technologies driving drug discovery and developing large-scale genomic studies to identify genetic variations. These findings may provide benefits in designing therapies more targeted to specific diseases, maximizing therapeutic effects, decreasing adverse reactions, and developing better methods to determine effective drug dosages. In addition to the anticipated benefit of personalized medicine, the identification of genetic markers may also influence the lifestyle, environment, and diet of those individuals with high susceptibility to develop a particular disease(s) and to prevent or delay the development of diseases. This chapter will focus on mutations and the variety of polymorphisms that may be associated with therapy resistance for people with different types of lung diseases such as chronic obstructive pulmonary disease (COPD), tuberculosis (TB), idiopathic pulmonary fibrosis (IPF), pulmonary arterial hypertension (PAH), and interstitial lung damage (ILD). In fact, insights from recent evidences strongly support the notion that pharmacogenomics will be essential in improving innovative genomic-based therapies based on the genomic profiles of patients.

Pharmacogenomics of Allergy and Asthma

Allergy and asthma are the diseases of multifactorial etiologies increasing dramatically all over the world. Numerous factors (e.g., aeroallergen, toxin, pathogen, food, chemical insect debris, and drugs) play a key role in the pathophysiology of allergy and asthma. Recent advances in the field of genetics have led to the identification of genetic factors which are involved not only in the pathogenesis of asthma and allergy but also significantly (60–70 %) contribute toward the interindividual variability to drug response and adverse drug reactions. There are several common categories of medications for treating asthma and allergy. Significant heterogeneity in the efficacy and adverse drug reactions of anti-allergic and anti-asthmatic drugs have been observed and efforts have been made to study the role of genetic determinants in the variable interindividual response to medication. Armed with the knowledge of a patient’s pharmacogenomic information, a clinician could predict the response to certain drugs and adverse drug reactions to improve the efficacy and tolerability of the therapeutic interventions.