A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology.

[1]  Gürol M. Süel,et al.  An excitable gene regulatory circuit induces transient cellular differentiation , 2006, Nature.

[2]  Uri Alon,et al.  Dynamics and variability of ERK2 response to EGF in individual living cells. , 2009, Molecular cell.

[3]  Nir Friedman,et al.  Dynamic response diversity of NFAT isoforms in individual living cells. , 2013, Molecular cell.

[4]  Thomas Höfer,et al.  Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response , 2012, Molecular systems biology.

[5]  Jeremy E. Purvis,et al.  p53 Dynamics Control Cell Fate , 2012, Science.

[6]  Timothy K Lee,et al.  Single-cell NF-κB dynamics reveal digital activation and analogue information processing , 2010, Nature.

[7]  Myong-Hee Sung,et al.  Live cell imaging and systems biology , 2011, Wiley interdisciplinary reviews. Systems biology and medicine.

[8]  Anne E Carpenter,et al.  Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins , 2006, Nature Methods.

[9]  David A. Rand,et al.  Measurement of single-cell dynamics , 2010, Nature.

[10]  A. Nias Book reviewBiological Response Modifiers: Subcommittee Report (NCI Monograph 63). Ed. by MihichEnrico and FeferAlexander, pp. 252, 1983 (National Institutes of Health, Bethesda, Md., USA. , 1984 .

[11]  T. Geng,et al.  Observing single cell NF-κB dynamics under stimulant concentration gradient. , 2012, Analytical chemistry.

[12]  M. Sung,et al.  Sustained Oscillations of NF-κB Produce Distinct Genome Scanning and Gene Expression Profiles , 2009, PloS one.

[13]  D B Kell,et al.  Oscillations in NF-kappaB signaling control the dynamics of gene expression. , 2004, Science.

[14]  Avinash Bhandoola,et al.  Faculty Opinions recommendation of In vivo genome editing using a high-efficiency TALEN system. , 2013 .

[15]  Timothy K Lee,et al.  A Noisy Paracrine Signal Determines the Cellular NF-κB Response to Lipopolysaccharide , 2009, Science Signaling.

[16]  Uri Alon,et al.  Dynamics of the p53-Mdm2 feedback loop in individual cells , 2004, Nature Genetics.

[17]  Thomas F Meyer,et al.  High-throughput and single-cell imaging of NF-κB oscillations using monoclonal cell lines , 2010, BMC Cell Biology.

[18]  R. Milo,et al.  Dynamic Proteomics of Individual Cancer Cells in Response to a Drug , 2008, Science.

[19]  Sejal Vyas,et al.  Dual roles for PARP1 during heat shock: transcriptional activator and posttranscriptional inhibitor of gene expression. , 2013, Molecular cell.

[20]  Julian R. E. Davis,et al.  Dynamic Analysis of Stochastic Transcription Cycles , 2011, PLoS biology.

[21]  W. Raub From the National Institutes of Health. , 1990, JAMA.

[22]  James R. Johnson,et al.  Oscillations in NF-κB Signaling Control the Dynamics of Gene Expression , 2004, Science.

[23]  M. Elowitz,et al.  Frequency-modulated nuclear localization bursts coordinate gene regulation , 2008, Nature.

[24]  Conrad D James,et al.  Nuclear translocation kinetics of NF-κB in macrophages challenged with pathogens in a microfluidic platform , 2009, Biomedical microdevices.

[25]  Jeffry D Sander,et al.  FLAsH assembly of TALeNs for high-throughput genome editing , 2022 .