Simultaneous analysis of large-scale RNAi screens for pathogen entry.

BACKGROUND: Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries. RESULTS: We show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied. CONCLUSIONS: Our results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Longitudinal Assessment of Amyloid Pathology in Transgenic ArcAß Mice Using Multi-Parametric Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) can be used to monitor pathological changes in Alzheimer's disease (AD). The objective of this longitudinal study was to assess the effects of progressive amyloid-related pathology on multiple MRI parameters in transgenic arcAß mice, a mouse model of cerebral amyloidosis. Diffusion-weighted imaging (DWI), T1-mapping and quantitative susceptibility mapping (QSM), a novel MRI based technique, were applied to monitor structural alterations and changes in tissue composition imposed by the pathology over time. Vascular function and integrity was studied by assessing blood-brain barrier integrity with dynamic contrast-enhanced MRI and cerebral microbleed (CMB) load with susceptibility weighted imaging and QSM. A linear mixed effects model was built for each MRI parameter to incorporate effects within and between groups (i.e. genotype) and to account for changes unrelated to the disease pathology. Linear mixed effects modelling revealed a strong association of all investigated MRI parameters with age. DWI and QSM in addition revealed differences between arcAß and wt mice over time. CMBs became apparent in arcAß mice with 9 month of age; and the CMB load reflected disease stage. This study demonstrates the benefits of linear mixed effects modelling of longitudinal imaging data. Moreover, the diagnostic utility of QSM and assessment of CMB load should be exploited further in studies of AD.