The discovery of RNA interference (RNAi) and the major advances in the understanding of small RNA biology have provided researchers with an invaluable tool for wide-scale and rapid genetic screening. A central goal of our research program has been to develop methodology for efficient application of RNAi screening technology in hematopoietic cell lineages, and to implement screens in both human and mouse hematopoietic cells to interrogate the mechanistic basis of immune cell responses to pathogenic stimuli. Our current efforts are focused on macrophages as they form the first line of defense against numerous bacterial and viral pathogens and characterization of these initial encounters are central to the LSB-wide efforts to generate quantitative models of host-pathogen interactions. We have previously described the generation of reporter cell lines for mouse and human macrophages that provide a comprehensive range of biosensors for evaluation of the macrophage activation profile in response to various pathogenic inputs. We have also described the development of robust siRNA delivery protocols that avoid non-specific activation of the macrophage response to dsRNA and we have confirmed our assays conform to the reproducibility and uniformity criteria established in the NCATS high throughput screening best practices guidelines. We have implemented two genome wide siRNA screens to identify genes involved in the human and mouse LPS responses. As the best characterized TLR stimulus, data from these screens will provide a valuable comparison of the endotoxin response in mouse and human cells, with important potential clinical relevance in the context of septic shock and endotoxin tolerance. We have previously described the completion of the primary and secondary phases of these screens, and the selection of candidate regulators of the LPS-induced inflammatory response. In 2014, we completed a comprehensive screening analysis of the canonical TLR signaling components in human and mouse macrophages. This 126-gene set included TLR receptors, proximal signaling components, NF-kB and MAPK pathway proteins, transcription factors, cytokines and negative regulators. We targeted this canonical TLR gene set with six different individual siRNAs for every gene, which significantly reduces the occurrence of off-target effects. We screened both human and mouse macrophages with multiple TLR ligands to compare the pathway component usage in response to varied stimuli. While confirming the expected specificity for the TLRs and some of the core pathway components, this study has identify some unexpected selectivity in signaling responses through different TLR pathways, and also some particularly striking differences between human and mouse macrophages. We are currently completing a study on specific findings from these screens which suggest differences in how human and mouse macrophages respond to bacterial stimuli, and these data will be submitted shortly for publication. RNAi screen data are susceptible to a myriad of experimental biases, some of which can be mitigated by computational analysis. During the analysis of the primary and secondary screen data from our genome-wide LPS screens, we sought to improve the integration of the screen analysis process. This year, in collaboration with Bhaskar Dutta in the LSB bioinformatics support team, we have developed a user-friendly platform for integrated analysis and visualization of RNAi screen data, named Comprehensive Analysis of RNAi Data (CARD). CARD allows the user to seamlessly carry out sequential steps in a data analysis workflow, including data import and normalization, filtering, hit selection, and functional analysis. For each of these steps, CARD allows the user to employ widely used existing algorithms, incorporate extended versions of existing algorithms, and also to implement novel algorithms that we have developed as part of the CARD workflow. The results are visualized as interactive figures and the user has the ability to modify visualization parameters. In summary, CARD is a new computational framework that integrates and visualizes all the steps required for computation-based analyses of siRNA screen data by combining existing and novel algorithms in a user-friendly application. We are currently finalizing the user interface for CARD prior to preparing a report for publication. Completion of the CARD application will also facilitate the prioritization of novel genes identified in our aforementioned LPS screens. The signaling pathways and transcription factor responses induced in macrophages upon TLR stimulation are regulated by feedback loops that modulate the kinetics and magnitude of gene transcription. Among these, NF-kB has been a paradigm for a signal- responsive transcription factor that operates in a feedback regulatory network. Despite the considerable literature on NF-kB activation and function, there remains a lack of data on NF-kB single cell dynamics in hematopoietic cells (especially macrophages) responding to pathogenic stimuli. The development of a mouse macrophage cell line expressing a GFP tagged NF-kB component (p65/relA) for our siRNA screen provided an opportunity for us to address this question. Moreover, a coupled TNF alpha promoter-driven transcriptional reporter expressed in the same cell line provided a unique secondary readout that allows evaluation of the consequences of NF-kB activation at a single cell level. In collaboration with Mia Sung and Gordon Hager at the NCI, we have used these cells to study how macrophages interpret different LPS doses in the context of NF-kB activation and TNF alpha transcriptional output. Using live cell imaging, we monitored both NF-kB signaling dynamics and TNF alpha transcription in single macrophages exposed to bacterial lipopolysaccharide (LPS). Our analysis revealed a novel positive feedback loop: induction of Rela, encoding the active subunit of NF-kB. This feedback rewires the regulatory network above a distinct dose. Mathematical modeling and experimental validation showed that the positive feedback overrides negative feedback and discriminates LPS doses that elicit an authentic innate immune response. Taking advantage of our genome-wide siRNA screens in the same mouse macrophage cell line, we identified the transcription factor Ikaros as a key component underlying the switch from negative to positive feedback at higher LPS dose. This year, we validated this key role of Ikaros using macrophages derived from Ikaros deficient mice. Switching of feedback dominance may be a general mechanism in immune cells for integrating opposing feedback on a key transcriptional regulator and setting a host response threshold. A paper describing these data was published in Science Signaling this year. This year, we also developed an assay for using our siRNA screening platforms to interrogate the macrophage response to infection with intact bacteria. We have used Burkholderia cenocepacia as a model, as we have established macrophage infection protocols with this bacteria from our Innate Immune Signaling Networks project (AI001107). We developed a high content imaging assay that permits quantification of bacterial replication in human THP1 cells, and we have used this assay to screen the canonical components of the TLR signaling pathways to evaluate their contribution to the macrophage response to infection. Since this same TLR gene set was also screened using single TLR ligands (described above), this has allowed us to identify both similarities and differences in the macrophage response to single and combined bacterial stimuli. This study has also highlighted some specific signaling modules in the TLR pathway that appear to be hijacked by B. cenocepacia during infection. These findings are currently under further investigation.
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