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Comment on "Oscillations in NF-B Signaling Control the Dynamics of Gene Expression"
Fusing fluorescent moieties to signaling proteins of interesthas allowed for the imaging of subcellular events in live cellsin the hope of revealing the dynamic behavior of signal transductionnetworks (15). Nelson et al. (5) recently described atour de force experimental analysis to track signaling by thetranscription factor nuclear factor kappa B (NF-B) in individualliving cells in real time. As the authors point out, their observationsmatch a computational model (6) based on biochemical data derivedfrom cell population averages. Here, we comment on interpretingexperimental data derived from genetically manipulated cellsand on the physiological role of sustained oscillations in NF-Bsignal transduction.
Our previously published integrated computational and biochemicalanalysis of NF-B signaling (6) included simulations of cellswith altered concentrations of NF-B inhibitor proteins (IB)[figure 2D in (6)]. These analyses predicted that two IB isoforms,IBß and IB, have functional roles in damping the oscillatorypropensity of the NF-BIB negative feedback loop. Thiswas confirmed experimentally by observing damped nuclear NF-Bactivity oscillations in wild-type cells [figures 1C and in(6)] and much stronger oscillations in IBß/IB doubleknockouts [figure 2, A and B, in (6)]. However, such cell populationbasedanalyses may not always reveal oscillatory behavior that isoccurring on the single-cell level, because protein extractsaverage potentially asynchronous responses of individual cells.
To study the regulation of NF-B activity in real time in singlecells, Nelson et al. (5) used ectopic expression of IB and NF-B-p65fused to fluorescent moieties. They transiently transfectedHeLa (human cervical carcinoma) cells and SK-N-AS cells (humanS-type neuroblastoma cells) with p65-DsRed (red fluorescentprotein) and NF-Binducible IB-EGFP (enhanced green fluorescentprotein) expression plasmids. Nelson et al. estimate that NF-B-p65is overexpressed 3- to 5-fold in successfully transfected cellsand suggest that this has a negligible effect on the fundamentalcharacteristics of NF-B nuclear-cytoplasmic oscillations inresponse to stimulation by tumor necrosis factor alpha (TNF).However, model simulations (Fig. 1) predict that even 1.5- or2-fold overexpression of either of the two components formingthe negative feedback loop (NF-B-p65 and IB, separately or incombination) can significantly alter the dynamics of NF-B activityin response to TNF (7, 8). First, oscillations are more persistentbecause the damping effects mediated by IBß and IBare diminished relative to the negative feedback effects mediatedby both overexpressed NF-B and inducible IB. This situationis analogous to the relative strengthening of the negative feedbackby knocking out nonfeedback IBß and IB isoforms (6).Second, the oscillation frequency may dramatically change, whichsuggests that cells with different degrees of overexpressionmay have oscillatory responses with drastically different periods.We suggest that as a result of inevitable cell-to-cell variationsin the amount of plasmid DNA, transfected cells are likely tobe much less synchronous in their NF-B response than are untransfectedcells.
Fig. 1. NF-B activation profiles as a function of NF-B protein levels. Relative (peak normalized) nuclear NF-B activity graphed as a function of time in response to TNF stimulation. Data derive from model simulations that reflect cells transfected with expression vectors described in (5) encoding (A) NF-B-p65, (B) NF-B-p65 and IB, and (C) IB. Expression of these proteins may result in protein levels that are normal (black) or increased 1.5-fold (red), 2-fold (green), or 4-fold (blue).
[View Larger Version of this Image (28K GIF file)]
Nelson et al. (5) confirm that the negative feedback loop ofNF-B-p65 and IB has a strong propensity for oscillations andthat such dynamic behavior can be studied productively withcomputational models. In our view, their results also cautionabout interpreting the dynamic recordings of cells geneticallymanipulated with GFP fusion proteins: Oscillations recordedin overexpressed feedback systems do not allow us to concludethat oscillations of the same persistence, amplitude, and periodoccur in normal, genetically unaltered cells. GFP experimentsmay be more conclusive when clonal cell lines are establishedin which individual cells are genetically identical and expressionlevels of the exogenous fusion proteins and functionally relevantendogenous signaling proteins can be quantitated to inform computationalsimulations.
An alternative way to experimentally address the response insingle cells is to perform immunohistochemical analysis of individual,but genetically unmodified, cells (Fig. 2A). This approach doesnot allow tracking of individual cells over time, but can revealthe variance of responses across the cell population at differenttime points. Variance in measured data may be the result oftechnical variation (error in measurement) or biological variation,(e.g., due to asynchrony). If the responses of individual cellsare asynchronous and show undamped oscillations (Fig. 2B), onewould expect higher variance at late times than at early timesand lower averages due to prolonged phases between peaks (Fig. 2C).However, we consistently found that the variance of theresponses is lower at late times than at early times and thataverages remain high (Fig. 2D). Such a variance distributionis more consistent with a simulation in which the observed varianceis derived from technical measurement errors that may be assumedto be proportional to the measured value itself (Fig. 2E). Thesedata suggest that NF-B activation in genetically unmodifiedfibroblasts is synchronous and highly damped.
Fig. 2. NF-B activation in single cells. (A) Immunohistochemistry for endogenous NF-B in NIH 3T3 cells (mouse fibroblasts) stimulated with TNF. Cells were fixed and stained at 10 min, 30 min, 190 min, and 290 min after administration of TNF and stained with an antibody to p65 (9). (B) Computational simulations of oscillatory NF-B in IBß/-deficient cells that contain NF-B protein levels that are "wild-type" (black), 1.2x (blue), or 0.8x (green). (C) The mean NF-B activity (black line) produced by computational simulations of IBß/-deficient cells containing a distribution of NF-B protein levels with a standard deviation of 10%. Red lines indicate the mean ±1 SD. (D) NF-B localization data derived from immunohistological analysis graphed as nucleus:cytoplasm (N:C) ratio as a function of time in response to TNF stimulation. Vertical bars indicate the standard deviation in the data for each time point. (E) Computational simulation of NF-B activity in wild-type cells (6) in response to TNF stimulation. Red lines indicate 1.2x and 0.8x NF-B activity.
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The regulation of NF-B may vary greatly between different celltypes, and it is often misregulated in disease-associated cells.Persistent oscillations might occur in some of the many possiblephysiological or pathological scenarios, even if they have notbeen observed in the genetically unaltered cells examined sofar. Nelson et al. show that persistently oscillatory NF-B activityleads to a higher expression of an exogenous reporter gene thana single transient pulse of NF-B activity [figure 2, G to J,in (5)]. Similarly, we showed that sustained activity allowsfor quantitative and qualitative changes in the expression ofsome endogenous genes [figure 4, B and C, in (6)]. To investigatewhether persistent oscillations of NF-B could play a physiologicalrole in gene expression, persistently oscillating NF-B shouldbe compared with sustained steady NF-B activity. To determinewhether oscillations are important in NF-B functionality, weexamined the expression of NF-B target genes in cells harboringa single IB isoform that either provides for negative feedbackinducedoscillations or does not (Fig. 3). Our results do not revealmarked differences in resultant gene expression, and mice deficientin the nonfeedback IB isoforms do not present strong phenotypes(data not shown). Thus, it remains unclear whether persistentoscillations of NF-B activity regulate gene expression qualitatively,quantitatively, or in dynamics.
Fig. 3. Target-gene expression in response to different NF-B activity profiles. (A) NF-B activity profiles in response to persistent TNF stimulation in IBß// (left) and IB// (right) murine embryonic fibroblasts, as measured in (6). (B) mRNAs of known NF-B response genes (10) were measured by RNAse protection assay at the indicated times during persistent TNF stimulation.
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In summary, we suggest that perturbations of genetic circuitswith ectopic expression of fluorescently labeled proteins shouldbe interpreted with caution, as significant deviations fromnormal cellular signaling characteristics might result. Althoughoscillatory behavior of endogenous proteins in cell cycle andcircadian regulatory mechanisms is well documented, it remainsunclear whether the propensity for oscillations in cytokineor stress response signaling is functionally and physiologicallyimportant or is merely a consequence of post-induction repressionmechanisms that allow for rapid adaptation after productivetransduction of signals.
Derren Barken*
Signaling Systems Laboratory Department of Chemistry and Biochemistry and Bioinformatics Graduate Program University of California, San Diego 9500 Gilman Drive La Jolla, CA 920930375, USA
Chiaochun Joanne Wang*
The Whitaker Institute for Biomedical Engineering Department of Biomedical Engineering Johns Hopkins University 3400 North Charles Street Baltimore, MD 21218, USA
Jeff Kearns
Signaling Systems Laboratory Department of Chemistry and Biochemistry University of California, San Diego
Raymond Cheong
The Whitaker Institute for Biomedical Engineering Department of Biomedical Engineering Johns Hopkins University
Alexander Hoffmann
Signaling Systems Laboratory Department of Chemistry and Biochemistry University of California, San Diego
Andre Levchenko
The Whitaker Institute for Biomedical Engineering Department of Biomedical Engineering Johns Hopkins University
To whom correspondence should be addressed. E-mail: ahoffmann{at}ucsd.edu (A.H.); alev{at}bme.jhu.edu (A.L.)
*These authors contributed equally to this work.
References and Notes
1. M. Jacquet, G. Renault, S. Lallet, J. De Mey, A. Goldbeter, J. Cell Biol.161, 497 (2003).[Abstract/Free Full Text]
6. A. Hoffmann, A. Levchenko, M. L. Scott, D. Baltimore, Science298, 1241 (2002).[Abstract/Free Full Text]
7. Simulations were done with the computational model described in (6) and also used in (5). Parameters values were as described, with the exception that the NF-B concentration and the parameters tr2 and tr2a (accounting for the rates of constitutive and NF-Binduced transcription) were increased as shown in the Fig.1 legend to account for overexpression effects due to transfected plasmids.
8. Simulations of the NF-B response in IBß/-deficient cells were done as described (6), with tr2b and tr2e parameters set to zero. Starting amounts of NF-B were as stated in the legends or were varied according to a normal distribution with a standard deviation of 10%. Mean and standard deviation of the NF-B activity normalized to the maximum were calculated for the time course and graphed.
9. Nuclear and cytoplasmic fluorescence intensities of individual cells were measured using IPLab; background of each captured fluorescence image was subtracted out. The Hoechst 33342 stained nucleus was used to determine the nuclear region by IPLab's Autosegment function. Nuclear segments were eroded twice to avoid contamination from cytoplasmic regions. Representative cytoplasmic regions were selected by taking the boundary pixels of the oncedilated nuclear segment (to minimize nuclear overlap). Relative fluorescence was calculated by taking the ratio of the mean intensity of the nuclear region to that of the cytoplasmic region. Forty to 100 cells were analyzed for each time point to assure statistical significance.
11. This work was supported by NIH grant GM072024-01.
Received for publication 24 November 2004. Accepted for publication 7 March 2005.
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TECHNICAL COMMENTS
D. E. Nelson, C. A. Horton, V. See, J. R. Johnson, G. Nelson, D. G. Spiller, D. B. Kell, and M. R. H. White (1 April 2005) Science308 (5718), 52b.
[DOI: 10.1126/science.1108198] |Full Text »|PDF »
REPORTS
D. E. Nelson, A. E. C. Ihekwaba, M. Elliott, J. R. Johnson, C. A. Gibney, B. E. Foreman, G. Nelson, V. See, C. A. Horton, D. G. Spiller, S. W. Edwards, H. P. McDowell, J. F. Unitt, E. Sullivan, R. Grimley, N. Benson, D. Broomhead, D. B. Kell, and M. R. H. White (22 October 2004) Science306 (5696), 704.
[DOI: 10.1126/science.1099962] |Abstract »|Full Text »|PDF »|Supporting Online Material »
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