Cenix BioScience (Germany)

Chronic Obstructive Pulmonary Disease (COPD) is a highly prevalent condition characterized by inflammation and progressive obstruction of the airways. At present, there is no treatment that suppresses the chronic inflammation of the disease, and COPD patients often succumb to the condition. Excessive oxidative stress caused by smoke inhalation is a major driving force of the disease. The transcription factor NRF2 is a critical player in the battle against oxidative stress and its function is impaired in COPD. Increasing NRF2 activity may therefore be a viable therapeutic option for COPD treatment. We show that down regulation of KEAP1, a NRF2 inhibitor, protects primary human lung epithelial cells from cigarette-smoke-extract (CSE) induced cell death in an established in vitro model of radical stress. To identify new potential drug targets with a similar effect, we performed a siRNA screen of the ‘druggable’ genome using a NRF2 transcriptional reporter cell line. This screen identified multiple genes that when down regulated increased NRF2 transcriptional activity and provided a survival benefit in the in vitro model. Our results suggest that inhibiting components of the ubiquitin-proteasome system will have the strongest effects on NRF2 transcriptional activity by increasing NRF2 levels. We also find that down regulation of the small GTPase Rab28 or the Estrogen Receptor ESRRA provide a survival benefit. Rab28 knockdown increased NRF2 protein levels, indicating that Rab28 may regulate NRF2 proteolysis. Conversely ESRRA down regulation increased NRF2 transcriptional activity without affecting NRF2 levels, suggesting a proteasome-independent mechanism.

The identification of diagnostic markers and therapeutic candidate genes in common diseases is complicated by the involvement of thousands of genes. We hypothesized that genes co-regulated with a key gene in allergy, IL13, would form a module that could help to identify candidate genes. We identified a T helper 2 (TH2) cell module by small interfering RNA-mediated knockdown of 25 putative IL13-regulating transcription factors followed by expression profiling. The module contained candidate genes whose diagnostic potential was supported by clinical studies. Functional studies of human TH2 cells as well as mouse models of allergy showed that deletion of one of the genes, S100A4, resulted in decreased signs of allergy including TH2 cell activation, humoral immunity, and infiltration of effector cells. Specifically, dendritic cells required S100A4 for activating T cells. Treatment with an anti-S100A4 antibody resulted in decreased signs of allergy in the mouse model as well as in allergen-challenged T cells from allergic patients. This strategy, which may be generally applicable to complex diseases, identified and validated an important diagnostic and therapeutic candidate gene in allergy.

RNA interference (RNAi) has become an important technique for loss-of-gene-function studies in mammalian cells. To achieve reliable results in an RNAi experiment, efficient and specific silencing triggers are required. Here we present genome-wide data sets for the production of endoribonuclease-prepared short interfering RNAs (esiRNAs) for human, mouse and rat. We used an algorithm to predict the optimal region for esiRNA synthesis for every protein-coding gene of these three species. We created a database, RiDDLE, for retrieval of target sequences and primer information. To test this in silico resource experimentally, we generated 16,242 esiRNAs that can be used for RNAi screening in human cells. Comparative analyses with chemically synthesized siRNAs demonstrated a high silencing efficacy of esiRNAs and a 12-fold reduction of downregulated off-target transcripts as detected by microarray analysis. Hence, the presented esiRNA libraries offer an efficient, cost-effective and specific alternative to presently available mammalian RNAi resources.

We describe a system for collecting usage metrics from widely distributed automation systems. An application that records and stores usage data centrally, calculates run times, and charts the data was developed. Data were collected over 20 months from at least 28 workstations. The application was used to plot bar charts of date versus run time for individual workstations, the automation in a specific laboratory, or automation of a specified type. The height of one bar represented the length of one run, and its position on the x-axis indicated the date the run started. Graphs were visually inspected and few bars on the graph(s) indicated infrequent use. Quantitative data were obtained by running custom SQL queries. Analyses showed that 90% of the automation was used frequently (>8 runs per week). Where usage was less, or limited to part of the day, the causes were investigated by interviewing users. We show that revised user training, redeployment of equipment, and running complimentary processes on one workstation can increase the average number of runs by up to 20-fold and run times by up to 450%. Active monitoring of usage leads to more effective use of automation. Usage data#could be used to determine whether purchasing particular automation was a good investment. (JALA 2006; 11: 16-22)

Zusammenfassung Ozeane bedecken zwei Drittel der Erdoberfläche und bilden damit das größte und sicherlich wertvollste Ökosystem der Erde. Mit einer nahezu unüberschaubaren Artenvielfalt bilden die Ozeane aber auch eine phantastische und einzigartige Quelle für die Entdeckung neuer, pharmakologisch aktiver Naturstoffe. Häufig handelt es sich bei diesen bioaktiven Stoffen um hochspezialisierte Jagdgifte. Zu den interessantesten Jagdgiften gehören die Conopeptide der tropischen Kegelschnecken (Familie Conidae). Die Mitglieder dieser Molluskenfamilie setzen hochkomplexe Giftseren, die zum Teil aus bis zu 200 Einzeltoxinen bestehen, zur Jagd auf Beute ein. Conopeptide sind kleine, an Cysteinbrücken reiche und daher rigide Peptide, die als Liganden spezifisch an bestimmte physiologische Zielstrukturen binden. Bei den meisten bisher bekannten molekularen Zielstrukturen handelt es sich um Ionenkanäle oder G-Protein gekoppelte Rezeptoren. Aufgrund der hohen Spezifität und Selektivität für diese Zielklassen gewinnen Conopeptide eine immer größere Bedeutung als Leitstrukturen (drug leads) in der pharmakologischen Forschung auf den Indikationsgebieten neurologischer und cardiovaskulärer Erkrankungen.