We propose to establish an Automation and Imaging Core to provide reagents, instruments, and expertise for protein analysis, image analysis, high throughput screening, and lab automation for the Projects in this program. The Core will leverage staff, lab automation, small molecule screening, RNAi screening, and computational resources from the Harvard Medical School (HMS) ICCB-Longwood Screening Facility. Core B will also provide education and outreach to the Boston scientific community on new assay technologies and best practices in running small molecule and RNAi screens.
Specific Aims for this Core are: 1. Develop standardized methods for quantitative analysis of proteins, including multiplexed bead-based detection methods, in-cell Western assays, and protein antibody arrays. 2. Support high throughput screening of compound libraries and of genome-scale siRNA libraries by the Projects. This includes liquid handling, assay readout, statistical analysis of data, and informatics support. 3. Provide expertise and resources for imaging and image analysis, including support for automated microscopy, obtaining/testing image analysis software, training investigators in the use of analysis software, and development of new image analysis algorithms. 4. Provide lab automation resources and expertise for cell-based and pure protein assays.
|Lee, Robin E C; Qasaimeh, Mohammad A; Xia, Xianfang et al. (2016) NF-ÎºB signalling and cell fate decisions in response to a short pulse of tumour necrosis factor. Sci Rep 6:39519|
|Sarosiek, Kristopher A; Letai, Anthony (2016) Directly targeting the mitochondrial pathway of apoptosis for cancer therapy using BH3 mimetics - recent successes, current challenges and future promise. FEBS J 283:3523-3533|
|Giedt, Randy J; Fumene Feruglio, Paolo; Pathania, Divya et al. (2016) Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response. Sci Rep 6:32985|
|Bhola, Patrick D; Mar, Brenton G; Lindsley, R Coleman et al. (2016) Functionally identifiable apoptosis-insensitive subpopulations determine chemoresistance in acute myeloid leukemia. J Clin Invest 126:3827-3836|
|Roux, JÃ©rÃ©mie; Hafner, Marc; Bandara, Samuel et al. (2015) Fractional killing arises from cell-to-cell variability in overcoming a caspase activity threshold. Mol Syst Biol 11:803|
|Fallahi-Sichani, Mohammad; Moerke, Nathan J; Niepel, Mario et al. (2015) Systematic analysis of BRAF(V600E) melanomas reveals a role for JNK/c-Jun pathway in adaptive resistance to drug-induced apoptosis. Mol Syst Biol 11:797|
|Chittajallu, Deepak R; Florian, Stefan; Kohler, Rainer H et al. (2015) In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy. Nat Methods 12:577-85|
|Montero, Joan; Sarosiek, Kristopher A; DeAngelo, Joseph D et al. (2015) Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy. Cell 160:977-89|
|Miller, Miles A; Zheng, Yao-Rong; Gadde, Suresh et al. (2015) Tumour-associated macrophages act as a slow-release reservoir of nano-therapeutic Pt(IV) pro-drug. Nat Commun 6:8692|
|Flusberg, Deborah A; Sorger, Peter K (2015) Surviving apoptosis: life-death signaling in single cells. Trends Cell Biol 25:446-58|
Showing the most recent 10 out of 57 publications