Various expression-augmenting DNA elements benefit from STAR-Select, a novel high stringency selection system for protein expression

The creation of highly productive mammalian cell lines often requires the screening of large numbers of clones, and even then expression levels are often low. Previously, we identified DNA elements, anti-repressor or STAR elements, that increase protein expression levels. These positive effects of STAR elements are most apparent when stable clones are established under high selection stringency. We therefore developed a very high selection system, STAR-Select, that allows the formation of few but highly productive clones. Here we compare the influence of STAR and other expression-augmenting DNA elements on protein expression levels in CHO-K1 cells. The comparison is done in the context of the often-used cotransfection selection procedure and in the context of the STAR-Select system. We show that STAR elements, as well as MAR elements induce the highest protein expression levels with both selection systems. Furthermore, in trans cotransfection of multiple copies of STAR and MAR elements also results in higher protein expression levels. However, highest expression levels are achieved with the STAR-Select selection system, when STAR elements or MARs are incorporated in a single construct. Our results also show that the novel STAR-Select selection system, which was developed in the context of STAR elements, is also very beneficial for the use of MAR elements.     

Probabilistic Environmental Risk Assessment for Dibutylphthalate (DBP)

In the risk assessment methods for new and existing chemicals in the European Union (EU), environmental “risk” is characterized by the deterministic quotient of exposure and effects (PEC/PNEC). From a scientific viewpoint, the uncertainty in the risk quotient should be accounted for explicitly in the decision making, which can be done in a probabilistic risk framework. To demonstrate the feasibility and benefits of such a framework, a sample risk assessment for an existing chemical (dibutylphthalate, DBP) is presented in this paper. The example shows a probabilistic framework to be feasible with relatively little extra effort; such a framework also provides more relevant information. The deterministic risk quotients turned out to be worst cases at generally higher than the 95th percentile of the probability distributions. Sensitivity analysis proves to be a powerful tool in identifying the main sources of uncertainty and thus will be effective for efficient further testing. The distributions assigned to the assess ment factors (derivation of the PNEC) dominate the total uncertainty in the risk assessment; uncertainties in the release estimates come second. Large uncertainties are an inherent part of risk assessment that we have to deal with quantitatively. However, the most appropriate way to characterise effects and risks requires further attention. Recommendations for further study are identified.