Accelerating Live Single-Cell Signalling Studies.

The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state.

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

[2]  D. Lauffenburger,et al.  Modeling a Snap-Action, Variable-Delay Switch Controlling Extrinsic Cell Death , 2008, PLoS biology.

[3]  B. Kholodenko Cell-signalling dynamics in time and space , 2006, Nature Reviews Molecular Cell Biology.

[4]  Trevor Darrell,et al.  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Bo Huang,et al.  A scalable strategy for high-throughput GFP tagging of endogenous human proteins , 2016, Proceedings of the National Academy of Sciences.

[6]  Brendan J. Frey,et al.  Classifying and segmenting microscopy images with deep multiple instance learning , 2015, Bioinform..

[7]  B. Chow,et al.  Optogenetic Control of Calcium Oscillation Waveform Defines NFAT as an Integrator of Calcium Load. , 2016, Cell systems.

[8]  Benjamin L. Oakes,et al.  Programmable RNA recognition and cleavage by CRISPR/Cas9 , 2014, Nature.

[9]  Chris Bakal,et al.  A Dynamical Framework for the All-or-None G1/S Transition , 2016, Cell systems.

[10]  Le Cong,et al.  Multiplex Genome Engineering Using CRISPR/Cas Systems , 2013, Science.

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

[12]  S. Jaffrey,et al.  RNA Mimics of Green Fluorescent Protein , 2011, Science.

[13]  E. O’Shea,et al.  Global analysis of protein localization in budding yeast , 2003, Nature.

[14]  G. Lahav,et al.  Schedule-dependent interaction between anticancer treatments , 2016, Science.

[15]  Marc Hafner,et al.  Fractional killing arises from cell-to-cell variability in overcoming a caspase activity threshold , 2015, Molecular Systems Biology.

[16]  M. Elowitz,et al.  A synthetic oscillatory network of transcriptional regulators , 2000, Nature.

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

[18]  O. Pertz,et al.  Spatio-temporal co-ordination of RhoA, Rac1 and Cdc42 activation during prototypical edge protrusion and retraction dynamics , 2016, Scientific Reports.

[19]  Timm Schroeder,et al.  Probing cellular processes by long-term live imaging – historic problems and current solutions , 2013, Journal of Cell Science.

[20]  David G Spiller,et al.  Multi-parameter analysis of the kinetics of NF-kappaB signalling and transcription in single living cells. , 2002, Journal of cell science.

[21]  Yaron E. Antebi,et al.  Dynamics of epigenetic regulation at the single-cell level , 2016, Science.

[22]  Erik Sahai,et al.  Intravital Imaging Reveals How BRAF Inhibition Generates Drug-Tolerant Microenvironments with High Integrin β1/FAK Signaling , 2015, Cancer cell.

[23]  Megan N. McClean,et al.  Signal processing by the HOG MAP kinase pathway , 2008, Proceedings of the National Academy of Sciences.

[24]  P. Swain,et al.  Gene Regulation at the Single-Cell Level , 2005, Science.

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

[26]  Jin Zhang,et al.  Genetically encoded fluorescent biosensors for live-cell visualization of protein phosphorylation. , 2014, Chemistry & biology.

[27]  G. Lahav,et al.  Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing , 2016, Cell.

[28]  Haluk Resat,et al.  Rapid and sustained nuclear–cytoplasmic ERK oscillations induced by epidermal growth factor , 2009, Molecular systems biology.

[29]  B. Cui,et al.  Optogenetic control of intracellular signaling pathways. , 2015, Trends in biotechnology.

[30]  Karl Mechtler,et al.  BAC TransgeneOmics: a high-throughput method for exploration of protein function in mammals , 2008, Nature Methods.

[31]  B. Kholodenko,et al.  The dynamic control of signal transduction networks in cancer cells , 2015, Nature Reviews Cancer.

[32]  K. Jaqaman,et al.  Robust single particle tracking in live cell time-lapse sequences , 2008, Nature Methods.

[33]  John G. Albeck,et al.  Frequency-modulated pulses of ERK activity transmit quantitative proliferation signals. , 2013, Molecular cell.

[34]  J. Ouellet RNA Fluorescence with Light-Up Aptamers , 2016, Front. Chem..

[35]  Gang Bao,et al.  Fluorescent probes for live-cell RNA detection. , 2009, Annual review of biomedical engineering.

[36]  S. Gaudet,et al.  Redefining Signaling Pathways with an Expanding Single-Cell Toolbox. , 2016, Trends in biotechnology.

[37]  G. Lahav,et al.  Encoding and Decoding Cellular Information through Signaling Dynamics , 2013, Cell.

[38]  Kirsten L. Frieda,et al.  Synthetic recording and in situ readout of lineage information in single cells , 2016, Nature.

[39]  Rey-Huei Chen,et al.  Molecular interpretation of ERK signal duration by immediate early gene products , 2002, Nature Cell Biology.

[40]  Michael B Elowitz,et al.  Synthetic biology of multicellular systems: new platforms and applications for animal cells and organisms. , 2014, ACS synthetic biology.

[41]  Erik Meijering,et al.  Methods for cell and particle tracking. , 2012, Methods in enzymology.

[42]  Joakim Jaldén,et al.  A batch algorithm using iterative application of the Viterbi algorithm to track cells and construct cell lineages , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

[43]  T. Terwilliger,et al.  Protein tagging and detection with engineered self-assembling fragments of green fluorescent protein , 2005, Nature Biotechnology.

[44]  M. Bennett,et al.  Microfluidic devices for measuring gene network dynamics in single cells , 2009, Nature Reviews Genetics.

[45]  Carsten Marr,et al.  Software tools for single-cell tracking and quantification of cellular and molecular properties , 2016, Nature Biotechnology.

[46]  Sabrina L. Spencer,et al.  Basal p21 controls population heterogeneity in cycling and quiescent cell cycle states , 2014, Proceedings of the National Academy of Sciences.

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

[48]  D. Lauffenburger,et al.  Quantitative analysis of pathways controlling extrinsic apoptosis in single cells. , 2008, Molecular cell.

[49]  Ryan A. Kellogg,et al.  High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics , 2014, Nature Protocols.

[50]  K. Hahn,et al.  Spatiotemporal dynamics of RhoA activity in migrating cells , 2006, Nature.

[51]  Ryan A. Kellogg,et al.  Noise Facilitates Transcriptional Control under Dynamic Inputs , 2015, Cell.

[52]  Gaudenz Danuser,et al.  Coordination of Rho GTPase activities during cell protrusion , 2009, Nature.

[53]  Jacco van Rheenen,et al.  A Versatile Toolkit to Produce Sensitive FRET Biosensors to Visualize Signaling in Time and Space , 2013, Science Signaling.

[54]  Anders S Hansen,et al.  Limits on information transduction through amplitude and frequency regulation of transcription factor activity , 2015, eLife.

[55]  Andrew R. Cohen,et al.  Vertebrate neural stem cell segmentation, tracking and lineaging with validation and editing , 2011, Nature Protocols.

[56]  E. O’Shea,et al.  Encoding four gene expression programs in the activation dynamics of a single transcription factor , 2016, Current Biology.

[57]  L. Tsimring,et al.  Accurate information transmission through dynamic biochemical signaling networks , 2014, Science.

[58]  C. Marshall,et al.  Specificity of receptor tyrosine kinase signaling: Transient versus sustained extracellular signal-regulated kinase activation , 1995, Cell.

[59]  Ryoichiro Kageyama,et al.  Oscillatory Control of Factors Determining Multipotency and Fate in Mouse Neural Progenitors , 2013, Science.

[60]  Sally Temple,et al.  LEVER: software tools for segmentation, tracking and lineaging of proliferating cells , 2016, Bioinform..

[61]  Bernd Fischer,et al.  CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging , 2010, Nature Methods.

[62]  R. Jaenisch,et al.  Tracing Dynamic Changes of DNA Methylation at Single-Cell Resolution , 2015, Cell.

[63]  Erin K O'Shea,et al.  Signal-dependent dynamics of transcription factor translocation controls gene expression , 2011, Nature Structural &Molecular Biology.

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

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

[66]  Nathalie Harder,et al.  A benchmark for comparison of cell tracking algorithms , 2014, Bioinform..

[67]  R. Tsien,et al.  The Fluorescent Toolbox for Assessing Protein Location and Function , 2006, Science.

[68]  Ryoichiro Kageyama,et al.  Oscillatory control of Delta-like1 in cell interactions regulates dynamic gene expression and tissue morphogenesis , 2016, Genes & development.

[69]  Honda Naoki,et al.  Intercellular propagation of extracellular signal-regulated kinase activation revealed by in vivo imaging of mouse skin , 2015, eLife.

[70]  Jennifer A. Doudna,et al.  Programmable RNA Tracking in Live Cells with CRISPR/Cas9 , 2016, Cell.

[71]  William J. Godinez,et al.  Objective comparison of particle tracking methods , 2014, Nature Methods.

[72]  Eric Batchelor,et al.  p53 Pulses Diversify Target Gene Expression Dynamics in an mRNA Half-Life-Dependent Manner and Delineate Co-regulated Target Gene Subnetworks. , 2016, Cell systems.

[73]  P. Cobbold,et al.  Repetitive transient rises in cytoplasmic free calcium in hormone-stimulated hepatocytes , 1986, Nature.

[74]  Frederick R. Cross,et al.  Positive feedback of G1 cyclins ensures coherent cell cycle entry , 2008, Nature.

[75]  Muffy Calder,et al.  The Mammalian MAPK/ERK Pathway Exhibits Properties of a Negative Feedback Amplifier , 2010, Science Signaling.

[76]  Otto Hudecz,et al.  Live-cell imaging RNAi screen identifies PP2A–B55α and importin-β1 as key mitotic exit regulators in human cells , 2010, Nature Cell Biology.

[77]  Jacob J. Hughey,et al.  High-Sensitivity Measurements of Multiple Kinase Activities in Live Single Cells , 2014, Cell.

[78]  Takeo Kanade,et al.  Reliable cell tracking by global data association , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[79]  Ming-Hsuan Yang,et al.  Hierarchical Convolutional Features for Visual Tracking , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

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

[81]  Joakim Jalden,et al.  Global Linking of Cell Tracks Using the Viterbi Algorithm , 2015, IEEE Transactions on Medical Imaging.

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

[83]  Silvia D. M. Santos,et al.  Positive Feedback Keeps Duration of Mitosis Temporally Insulated from Upstream Cell-Cycle Events , 2016, Molecular cell.

[84]  Sanjay Tyagi,et al.  Imaging intracellular RNA distribution and dynamics in living cells , 2009, Nature Methods.

[85]  P. Sorger,et al.  Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis , 2009, Nature.

[86]  Sabrina L. Spencer,et al.  The Proliferation-Quiescence Decision Is Controlled by a Bifurcation in CDK2 Activity at Mitotic Exit , 2013, Cell.

[87]  Stefan Roth,et al.  MOT16: A Benchmark for Multi-Object Tracking , 2016, ArXiv.

[88]  Yolanda T. Chong,et al.  Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis , 2015, Cell.

[89]  Luke A. Gilbert,et al.  Versatile protein tagging in cells with split fluorescent protein , 2016, Nature Communications.

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

[91]  Joshua T. Jones,et al.  Quantitative analysis of cell cycle phase durations and PC12 differentiation using fluorescent biosensors , 2009, Cell cycle.

[92]  A. Naderi,et al.  Synergy between inhibitors of androgen receptor and MEK has therapeutic implications in estrogen receptor-negative breast cancer , 2011, Breast Cancer Research.

[93]  Marco Y. Hein,et al.  A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances , 2015, Cell.

[94]  S. Spencer,et al.  Irreversible APCCdh1 Inactivation Underlies the Point of No Return for Cell-Cycle Entry , 2016, Cell.