Existing mRNA quantification methods As it is becoming increasingly apparent that gene expression in individuai cells deviates substantially from the average behavior of cell populations (Raj and van Oudenaarden, 2008), new methods that provide accurate integer counts of mRNA copy numbers in individual cells are needed. Ideally, such methods should also reveal the intracellular locations of the mRNAs, as mRNA localization is often used by cells to spatially restrict the activity of RNA binding proteins (St Johnston, 2005). One of the methods sensitive enough to detect single mRNA molecules is the MS2 mRNA detection technique developed simultaneously by the Bloom laboratory (Beach et al., 1999) and Robert Singer and colleagues (Bertrand et al., 1998). In this method, a gene is engineered to transcribe an mRNA containing many copies of a specific RNA hairpin in its untranslated region, each of which binds tightly to the coat protein of the bacteriophage MS2. This gene is then expressed in a cell that already expresses the MS2 coat protein fused to GFP. When many of the MS2-GFP proteins bind to an individual mRNA, enough fluorescent signal is generated that the individual mRNAs are detectable as diffraction limited spots using conventional fluorescence microscopy, allowing one to count the number of mRNAs in single cells. Although this technique provides quantitative and spatial information about mRNAs, its use is hindered by two substantial limitations: first, the target organism needs to be genetically modified;and second, detection of more than one mRNA species is impossible. Additionally, adding the tandem MS2 binding sites signiflcantly changes the RNA stability and the MS2-GFP fusion proteins tends to aggregate in large clusters hindering the detection of single molecules.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZCA1-SRLB-9)
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Massachusetts Institute of Technology
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McFarland, Christopher D (2016) A modified ziggurat algorithm for generating exponentially- and normally-distributed pseudorandom numbers. J Stat Comput Simul 86:1281-1294
Cermak, Nathan; Olcum, Selim; Delgado, Francisco Feijó et al. (2016) High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays. Nat Biotechnol 34:1052-1059
Hosios, Aaron M; Hecht, Vivian C; Danai, Laura V et al. (2016) Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells. Dev Cell 36:540-9
Stevens, Mark M; Maire, Cecile L; Chou, Nigel et al. (2016) Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate. Nat Biotechnol 34:1161-1167
Kimmerling, Robert J; Lee Szeto, Gregory; Li, Jennifer W et al. (2016) A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages. Nat Commun 7:10220
Hecht, Vivian C; Sullivan, Lucas B; Kimmerling, Robert J et al. (2016) Biophysical changes reduce energetic demand in growth factor-deprived lymphocytes. J Cell Biol 212:439-47
Akutagawa, J; Huang, T Q; Epstein, I et al. (2016) Targeting the PI3K/Akt pathway in murine MDS/MPN driven by hyperactive Ras. Leukemia 30:1335-43
Shaw Bagnall, Josephine; Byun, Sangwon; Miyamoto, David T et al. (2016) Deformability-based cell selection with downstream immunofluorescence analysis. Integr Biol (Camb) 8:654-64
Ramanan, Vyas; Trehan, Kartik; Ong, Mei-Lyn et al. (2016) Viral genome imaging of hepatitis C virus to probe heterogeneous viral infection and responses to antiviral therapies. Virology 494:236-47
Shaw Bagnall, Josephine; Byun, Sangwon; Begum, Shahinoor et al. (2015) Deformability of Tumor Cells versus Blood Cells. Sci Rep 5:18542

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