Vol 439 | 16 February 2006 | doi : 10.1038 / nature04504 LETTERS Detection of a direct carbon dioxide effect in continental river runoff records N. Gedney1 , P. M. Cox2 , R. A. Betts3 , O. Boucher3 , C. Huntingford4 & P. A. Stott5 Continental runoff has increased through the twentieth century1 ,2 despite more intensive human water consumption3 . Possible reasons for the increase include : climate change and variability , deforestation , solar dimming4 , and direct atmospheric carbon dioxide -LRB- CO2 -RRB- effects on plant transpiration5 . All of these mechanisms have the potential to affect precipitation and/or evaporation and thereby modify runoff . Here we use a mechanistic landsurface model6 and optimal fingerprinting statistical techniques7 to attribute observational runoff changes1 into contributions due to these factors . The model successfully captures the climatedriven inter-annual runoff variability , but twentieth-century climate alone is insufficient to explain the runoff trends . Instead we find that the trends are consistent with a suppression of plant transpiration due to CO2-induced stomatal closure . This result will affect projections of freshwater availability , and also represents the detection of a direct CO2 effect on the functioning of the terrestrial biosphere . On annual and longer timescales , continental river runoff is approximately equal to the difference between land precipitation and evapotranspiration . Changes in river runoff can arise from adjustment to either process . Evapotranspiration is a function of energy and water availability , near-surface atmospheric conditions -LRB- air temperature , humidity and wind-speed -RRB- and the control of transpiration by plants . Contemporary environmental changes can therefore affect runoff in a number of ways . Climate change and variability modify precipitation patterns and near-surface meteorology . An overall increase in atmospheric aerosol concentration over the past century appears to have reduced the amount of solar radiation reaching the land surface -LRB- so-called `` solar dimming `` 4 -RRB- , and may have led to reductions in open-pan evaporation8 . Landcover changes affect evapotranspiration in a number of ways , including modifying the depth of the soil from which plants can extract water and the available energy by changing the land-surface albedo . Finally , stomatal apertures on plant leaves are observed to close partially under increased CO2 -LRB- ref . 5 -RRB- , suppressing transpiration and providing a mechanism by which CO2 increase could lead directly to increases in runoff . Here we analyse observation-based continental river runoff records1 for evidence of runoff changes from the potential drivers . We adopted the formal detection and attribution techniques developed to isolate the causes of twentieth-century temperature change7 . A model is used to define the spatial and temporal responses associated with a known forcing factor . These distinct spatio-temporal patterns of response act as ` fingerprints ' that allow the observed change to be separated into contributions from each factor . We use the Met Office Surface Exchange Scheme -LRB- MOSES II ; ref . 6 -RRB- , which is the land-surface scheme in the Hadley Centre climate Figure 1 | Trends in continental water budgets . Observed precipitation -LRB- PreO ; red bars -RRB- and runoff -LRB- RoO ; dark blue bars -RRB- , and modelled runoff with all mechanisms -LRB- ALL ; light blue bars -RRB- and the individual components -LRB- CLIM , AER , CO2 and LUSE ; yellow bars -RRB- are shown . -LRB- ` Land ' in the first panel refers to the area-weighted sum of the individual regions . -RRB- Striped bars refer to trends over the whole analysis period and solid bars refer to post-1960 trends -LRB- see Methods for details -RRB- . 1 Met Office , Hadley Centre for Climate Prediction and Research -LRB- JCHMR -RRB- , Maclean Building , Wallingford OX10 8BB , UK . 2Centre for Ecology and Hydrology Dorset , Winfrith Technology Centre , Winfrith Newburgh , Dorchester DT2 8ZD , UK . 3Met Office , Hadley Centre for Climate Prediction and Research , Fitzroy Road , Exeter EX1 3 PB , UK . 4Centre for Ecology and Hydrology Wallingford , Maclean Building , Wallingford OX10 8BB , UK . 5Met Office , Hadley Centre for Climate Prediction and Research -LRB- Reading Unit -RRB- , Meteorology Building , University of Reading , Earley Gate , Reading RG6 6BB , UK . 2006 Nature Publishing Group 835 LETTERS NATURE | Vol 439 | 16 February 2006 Figure 2 | b scale factors obtained from the optimal fingerprinting technique . The 5 to 95 percentile ranges are shown for CLIM , AER , CO2 and LUSE . models . We drive MOSES using a monthly observational data set of the twentieth-century climate9 . This allows us to assess the extent to which changes in the observed climate can account for changes in runoff . Although here the land-surface scheme is not coupled to a model atmosphere , any feedbacks through the atmospheric boundary layer are implicitly included through changes in the observed near-surface meteorology . MOSES has been extensively validated against data from a number of field sites10 ,11 and performs well globally in its host climate model12 . MOSES is especially appropriate here because it includes a representation of the effect of CO2 concentration on stomatal conductance10 . We incorporate the effects of aerosols into the forcing data using diagnostics from the transient climate simulation with the HadGEM1 climate model13 -LRB- see Methods -RRB- . Changes in land use14 are used to prescribe related landcover changes to the MOSES plant types . To isolate the various effects we carry out five simulations of twentieth-century surface hydrology . We allow all factors likely to affect runoff to vary throughout the fully transient simulation ` ALL ' -LRB- climate , aerosol concentration , atmospheric CO2 and land use -RRB- . In the other four simulations , we allow three of the four factors to vary throughout the twentieth century while fixing the other component to initial conditions -LRB- see Methods -RRB- . The individual effects are found to combine approximately linearly . Hence the impact of each individual component can be calculated by comparing the fixedcomponent simulation with the ALL simulation -LRB- for example , the contribution of CO2 is given by ALL minus the fixed-CO2 simulation -RRB- . CLIM , AER , CO2 and LUSE refer to the diagnosed contributions of climate , aerosol , atmospheric CO2 and land use , respectively . Figure 1 shows the precipitation and modelled and observed runoff trends1 -LRB- see Methods -RRB- over the century . The post-1960 observed runoff trends for all regions tend to be more positive -LRB- or at least less negative -RRB- than the precipitation trends . This suggests that constraints other than precipitation are becoming more important in the latter part of the twentieth century . There is also a clear disparity between the climate-only -LRB- CLIM -RRB- modelled runoff and the observed runoff trends . With the exception of Europe , which shows a very small reduction in runoff , ALL appears closer to the observations than the climate-only response . The modelled response from climate forcing , aerosols -LRB- direct and indirect cloud albedo effects -RRB- and direct CO2 effects appear to be important over some regions . Land use -LRB- excluding irrigation -RRB- seems to have a small effect on the modelled continental-scale water balance . We use a standard optimal fingerprinting technique7 to see which factors are likely to be driving the long-term changes in continental runoff by comparing the modelled and observed annual anomalies relative to the long-term mean . This technique assumes that we can reproduce the observed anomalies by the linear addition of each individual modelled response x whose amplitude is scaled by a factor b x . The b factor for each modelled component is obtained by carrying out an ordinary least-squares regression fitted to the observed annual anomalies . This approach assumes that model signals are much less contaminated by noise than are the observed changes7 , an assumption that we expect to be valid in this case where 836 observed climatologies are used to force MOSES . If the 5 to 95 percentile range of b is greater than zero then the signal has been ` detected ' at the 5 % significance level . If this range of b also covers unity , then the modelled component is consistent with the observed response . If , in addition to detection and consistency described above , the signal is not consistent with alternative , physically plausible explanations , then it is said to be ` attributed ' 15 . We initially apply the regression over each individual region for the longer time periods given in Table 1 -LRB- for example , South America 1903 1994 -RRB- . Because the factors producing only long-term modelled runoff changes all show fairly similar temporal patterns even though their amplitudes are different , we initially carry out the regression analysis with two factors at a time -LRB- to avoid over-fitting the data -RRB- . Only the climate forcing produces considerable inter-annual variability , so we can combine this with each of the other components in separate regressions . The impact of climate change or variation on runoff is detected over all regions at the 5 % significance level , and in South America and Asia the model 's simulation of runoff due to climate is consistent with that observed -LRB- results not shown -RRB- . The direct CO2 effect is detected over Africa at the 5 % significance level . Aerosols and the CO2 effect are both consistent with the observed trends over Asia . The probability of b -LRB- CO2 -RRB- being greater than 0 is higher than for b -LRB- AER -RRB- and b -LRB- LUSE -RRB- for every region except South America , suggestive of the direct CO2 effect being the most likely global signal . To isolate these non-CLIM components , we combine the data for each continent so that spatial as well as temporal patterns are used in the fitting process : that is , we carry out a simultaneous best fit across all regions . We now require an estimate of the combined observation and model uncertainty for each region , which we take from the residual statistics calculated in the regional regressions . All the continental regions are considered together , and we carry out a four-component regression for CLIM , AER , CO2 and LUSE . Only climate and the direct CO2 effect are detected at the 5 % significance level -LRB- Fig. 2 -RRB- . -LRB- The time series of the fit for each region is shown in Supplementary Fig . S1 . -RRB- The simulation of runoff change due to the CO2 increase is consistent with that observed , whereas the model slightly over-estimates the climate effect -LRB- since b , 1 -RRB- -LRB- Fig. 2 -RRB- . We also consider different time series , and because the land-use effect appears to be very small we additionally carry out a three-way regression without land-use changes -LRB- not shown -RRB- . Both these sensitivity studies produce similar b values and result in the same conclusions . Figure 3 shows the trends attributable to the different factors -LRB- that is , with the modelled patterns scaled by b -RRB- . Most importantly , we find that runoff enhancement due to suppression of transpiration is detected in the observational records -LRB- Fig. 3 -RRB- . The records are not consistent with alternative explanations that exclude the effects of increasing CO2 on plant stomatal conductance . Therefore , we attribute increases in continental runoff to anthropogenic effects via the suppression of transpiration . This is consistent with the fact that there is only limited evidence for anthropogenic effects on global precipitation16 . Other mechanisms not considered here could also contribute to Figure 3 | Attribution of post-1960 overall runoff trend . The first two bars are the observed precipitation -LRB- red bar -RRB- and runoff -LRB- dark blue bar -RRB- trends . The remaining bars are the attributed runoff trends for the best fit -LRB- FIT ; light blue bar -RRB- and its individual components -LRB- yellow bars -RRB- . The 5 to 95 percentile ranges are shown . 2006 Nature Publishing Group NATURE | Vol 439 | 16 February 2006 LETTERS Table 1 | Trends in observational data Time period Shortwave radiation Net radiation Precipitation Runoff South America North America Africa Europe Asia 1903 94 1960 94 1901 94 1960 94 1901 84 1960 84 1901 94 1960 94 1930 94 1960 94 21.12 ^ 0.06 -LRB- 20.18 -RRB- 22.27 ^ 0.26 -LRB- 20.78 -RRB- 21.64 ^ 0.08 -LRB- 21.23 -RRB- 20.01 ^ 0.20 -LRB- 20.55 -RRB- 21.71 ^ 0.09 -LRB- 20.01 -RRB- 24.24 ^ 0.40 -LRB- 21.09 -RRB- 21.54 ^ 0.07 -LRB- 20.09 -RRB- 20.18 ^ 0.32 -LRB- 20.26 -RRB- 21.97 ^ 0.09 -LRB- 20.17 -RRB- 21.95 ^ 0.15 -LRB- 20.53 -RRB- 20.91 ^ 0.03 -LRB- 20.12 -RRB- 21.35 ^ 0.10 -LRB- 20.19 -RRB- 20.37 ^ 0.03 -LRB- 20.02 -RRB- 0.41 ^ 0.07 -LRB- 0.00 -RRB- 21.20 ^ 0.05 -LRB- 20.04 -RRB- 22.46 ^ 0.14 -LRB- 20.42 -RRB- 21.25 ^ 0.05 -LRB- 0.01 -RRB- 0.04 ^ 0.21 -LRB- 0.03 -RRB- 21.25 ^ 0.03 -LRB- 0.00 -RRB- 21.04 ^ 0.06 -LRB- 20.10 -RRB- 0.16 ^ 0.16 0.40 ^ 0.78 0.61 ^ 0.12 1.08 ^ 0.45 0.13 ^ 0.13 23.01 ^ 0.89 0.20 ^ 0.14 20.66 ^ 0.55 0.09 ^ 0.12 20.33 ^ 0.33 0.50 ^ 0.27 1.24 ^ 1.19 0.32 ^ 0.07 1.05 ^ 0.25 0.19 ^ 0.06 21.02 ^ 0.41 20.04 ^ 0.10 20.20 ^ 0.46 0.37 ^ 0.12 0.53 ^ 0.26 Continental trends -LRB- and fitted standard errors -RRB- for shortwave and net radiation and precipitation forcing data used in the ALL run , and the runoff are shown . Shortwave radiation values in brackets do not include direct and first-indirect aerosol effects -LRB- that is , CLIM-only trends -RRB- . Positive radiation trends indicate a surface energy increase . Units are in kg m22 yr22 . To directly compare water and energy availability changes for evaporation , radiation terms are converted by considering the amount of energy required to convert 1 kg of liquid water to vapour -LRB- 2.5 106 J kg21 -RRB- . Hence , 12.6 kg m22 yr21 of water is equivalent to 1 W m22 . changes in observed runoff . Expanding irrigation reduces continental-scale runoff17 , particularly over Asia and Europe , which has the largest fractional growth between 1960 and 1990 -LRB- ref . 18 -RRB- . Indeed , a majority of global human water consumption is used for irrigated agriculture3 . If we assume that most human extraction is from shortresidence-time sources , estimates of total human water usage3 would have contributed to a decrease of about 0.2 kg m22 yr22 between 1960 and 1995 . By combining urban population growth19 with a global urban map20 and assuming all urban precipitation is lost as runoff , we estimate the global urban runoff contribution to be , 0.03 kg m22 yr 22 . Overall , these additional terms would have contributed to a net reduction in observed runoff trends and therefore can not explain the difference between observed and climatedriven simulated runoff . The detection of a direct CO2 effect on global river runoff is important because , although laboratory experiments have shown that the stomatal openings of many plant species reduce under elevated CO2 -LRB- ref . 5 -RRB- , it was unclear whether this reduction would have any significance for the global water cycle , in which real ecosystems are typically limited by water and nutrient availability . Both atmospheric boundary layer feedbacks21 and changes in leaf area index22 have also been proposed as compensating mechanisms that could lead to the negligible impact of CO2-induced stomatal closure on large-scale evapotranspiration . As a result , most projections of future water availability have tended to neglect stomatalclosure effects23 . By contrast , our analysis suggests that raised CO2 levels are already having a direct influence on the water balance at the land surface . As the direct CO2 effect reduces surface energy loss due to evaporation , it is likely to add to surface warming24 ,25 as well as increasing freshwater availability . The existence of a direct CO2 signal in river runoff records also opens up the intriguing possibility of using long-term river records to monitor CO2 effects on the land carbon sink . METHODS Monthly forcing data . The 0.58 resolution observational data set from the Climate Research Unit contains monthly temperature -LRB- mean and diurnal range -RRB- , humidity , cloud cover and precipitation -LRB- amount and daily frequency -RRB- 9 . Climatological wind speed and surface pressure fields are taken from a Hadley Centre global climate model simulation of HadCM3 -LRB- ref . 26 -RRB- . The empirical formulations of Albrecht27 are used to derive surface downward shortwave and longwave radiation from the Climate Research Unit data set . These radiation components are compared to the monthly mean radiation data from the Second Global Soil Wetness Project28 , which is a combination of reanalysis and observations . The average difference between the two is less than 5 Wm22 for both longwave and shortwave radiation , implying that these formulations are sufficient for this purpose . As we are using cloud-cover observations in the reconstruction of surface downward shortwave radiation , a component of the second indirect aerosol effect -LRB- cloud lifetime -RRB- is already incorporated . Whether the enhanced cloudiness observed -LRB- for example , over North America29 -RRB- is due to aerosols can not , however , be ascertained . We use diagnostics from the Met Office HadGEM1 -LRB- ref . 13 -RRB- global climate model to incorporate other changes in surface shortwave radiation due to aerosol . These include the direct -LRB- clear-sky scattering and absorption -RRB- and indirect effects of the following aerosol species : ammonium sulphate , fossil-fuel black carbon -LRB- direct effect only -RRB- , biomass-burning aerosol and sea salt . We can therefore estimate the long-term trends in direct and firstindirect -LRB- cloud albedo -RRB- effects and modify the reconstructed clear-sky shortwave radiation and cloud albedo accordingly . Table 1 shows the regional trends in the data used to force MOSES over the past century and after 1960 . -LRB- These ` continental ' values are only based on catchments with gauged rivers . -RRB- Except over North America , the reduction in reconstructed shortwave radiation is mainly due to the direct and first-indirect -LRB- cloud albedo -RRB- aerosol effects , rather than cloud cover . This is partially offset by the increasing downward longwave radiation -LRB- not shown -RRB- resulting in a reduction in net radiation at the surface . Model set-up . All the monthly forcing data are regridded onto the HadCM3 2.58 3.758 grid and disaggregated to hourly data . A half-sinewave is used to calculate the shortwave radiation during the daytime and a sinewave is used to represent the daily temperature cycle . We use a random number generator to specify when a rainfall event occurs . A representative precipitation duration has been set for large-scale and convective precipitation events by analysing HadCM3 runs . -LRB- Modelled continental runoff anomalies are found to be insensitive to a range of physically reasonable precipitation event durations . -RRB- The MOSES soil water and temperature are ` spun up ' by repeatedly forcing the model with monthly data averaged over the period 1901 1905 and setting CO2 and land cover to 1901 values . MOSES is then run over the 1901 1994 period . The variation in total annual runoff over a number of regions is compared with the observationally based data set1 . We only analyse the period during which the regional data1 are based on observations from at least 20 % of the total river basin area -LRB- see Table 1 for details -RRB- , as below this threshold we find a large drop in the correlation between observed precipitation and runoff -LRB- not shown -RRB- . Our catchment area estimates are from a different -LRB- digital -RRB- source30 , so we rescale our total continental runoff by the ratio of the sum of catchment areas used in each study -LRB- corresponding to a 5 % change globally -RRB- . The modelled global mean runoff for the 1901 1994 study period is 3.92 104 km3 yr21 as compared to 3.94 104 km3 yr21 -LRB- ref . 1 -RRB- . Received 5 July ; accepted 7 December 2005 . 1 . 2 . Labat , D. , Godderis , Y. , Probst , J. L. & Guyot , J. L. Evidence for global runoff increase related to climate warming . Adv. Water Res . 27 , 631 -642 -LRB- 2004 -RRB- . Probst , J. L. & Tardy , Y. 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Henning , D. in Atlas of the Surface Heat Balance of the Continents 6 -LRB- Gebruder -9 Borntraeger , Berlin , 1989 -RRB- . Zhao , M. & Dirmeyer , P. Production and analysis of GSWP2 near-surface meteorology data sets . COLA Technic . Rep. 159 , 1 -LRB- 2003 -RRB- . -36 Liepert , B. G. Observed reductions of surface solar radiation at sites in the United States and worldwide from 1961 to 1990 . Geophys . Res . Lett . 29 , 1421 , doi : 10.1029 / 2002GL014910 -LRB- 2002 -RRB- . Fekete , B. M. , Vorosmarty , C. J. & Grabs , W. High-resolution fields of global runoff combining observed river discharge and simulated water balances . Glob . Biogechem . Cycles 16 , 1042 , doi : 10.1029 / 1999GB001254 -LRB- 2002 -RRB- . Supplementary Information is linked to the online version of the paper at www.nature.com/nature . Acknowledgements We thank D. Labat -LRB- Laboratoire de Mecanisme de Transferts en Geologie , UMR CNRS , Toulouse , France -RRB- for providing the observational runoff data . We thank D. Sexton for statistical advice and A. Jones for discussions . N.G. , R.A.B. , O.B. and P.A.S. were supported by the UK Department for Environment , Food and Rural Affairs , and P.M.C. and C.H. by the UK Natural Environment Research Council . Author Information Reprints and permissions information is available at npg.nature.com/reprintsandpermissions . The authors declare no competing financial interests . Correspondence and requests for materials should be addressed to N.G. -LRB- nicola.gedney@metoffice.gov.uk -RRB- . 838 2006 Nature Publishing Group

O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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Vol 440 | 16 March 2006 | doi : 10.1038 / nature04599 LETTERS Stochastic protein expression in individual cells at the single molecule level Long Cai1 * , Nir Friedman1 * & X. Sunney Xie1 In a living cell , gene expression -- the transcription of DNA to messenger RNA followed by translation to protein -- occurs stochastically , as a consequence of the low copy number of DNA and mRNA molecules involved1 6 . These stochastic events of protein production are difficult to observe directly with measurements on large ensembles of cells owing to lack of synchronization among cells . Measurements so far on single cells lack the sensitivity to resolve individual events of protein production . Here we demonstrate a microfluidic-based assay that allows real-time observation of the expression of b-galactosidase in living Escherichia coli cells with single molecule sensitivity . We observe that protein production occurs in bursts , with the number of molecules per burst following an exponential distribution . We show that the two key parameters of protein expression -- the burst size and frequency -- can be either determined directly from real-time monitoring of protein production or extracted from a measurement of the steady-state copy number distribution in a population of cells . Application of this assay to probe gene expression in individual budding yeast and mouse embryonic stem cells demonstrates its generality . Many important proteins are expressed at low levels7 ,8 , and are thus inaccessible by current genomic and proteomic techniques . This microfluidic single cell assay opens up possibilities for system-wide characterization of the expression of these low copy number proteins . b-galactosidase -LRB- b-gal -RRB- has been the standard reporter for gene expression in both prokaryotic and eukaryotic cells9 12 . Only active as a tetramer , a single molecule of b-gal can produce a large number of fluorescent product molecules by hydrolysing a synthetic fluorogenic substrate -LRB- Fig. 1b -RRB- , leading to amplification of the fluorescent signal , as was first demonstrated in 1961 -LRB- ref . 13 -RRB- . However , given its potential as a high-sensitivity cellular reporter , b-gal has an Achilles ' heel : its fluorescent products are not retained in the cell10 , because efflux pumps on the cell membrane actively and efficiently expel Figure 1 | Single reporter molecule sensitivity in a microfluidic device . a , Schematic diagram of the microfluidic chamber used for the enzymatic assay . Cells are trapped inside a volume of 100 pl , formed by compression of a flow channel by two control channels . b , Enzymatic amplification : hydrolysis of the synthetic substrate FDG by the reporter enzyme b-gal yields a fluorescent product , fluorescein . c , Differential interference contrast -LRB- DIC -RRB- image of a microfluidic chip after actuation of the control channels . The boundaries of one closed chamber are boxed in blue . d , DIC image of budding yeast cells trapped in a chamber . e , f , FDG hydrolysis by purified b-gal . e , Fluorescein concentration increases with time in chambers . The discrete slopes are due to , in decreasing order , 3 , 2 , 1 , 0 -LRB- autohydrolysis -RRB- b-gal molecules . f , A histogram of hydrolysis rates -LRB- 48 chambers -RRB- . The red curve is a fit to the data with three gaussians of equal widths . The peaks are attributed to 0 , 1 and 2 enzyme molecules per chamber . The distribution is well-fitted by a Poisson distribution -LRB- black line -RRB- , with an average of 0.7 b-gal molecules per chamber . 1 Department of Chemistry and Chemical Biology , Harvard University , 12 Oxford Street , Cambridge , Massachusetts 02138 , USA . * These authors contributed equally to this work . 358 2006 Nature Publishing Group NATURE | Vol 440 | 16 March 2006 LETTERS foreign organic molecules from the cytoplasm14 -LRB- see Supplementary Information -RRB- . As the fluorescent product molecules are pumped to the surrounding medium and rapidly diffuse away , the advantage of enzymatic amplification is lost . To circumvent the efflux problem , we trap cells in closed microfluidic chambers , such that the fluorescent product expelled from the cells can accumulate in the small volume of the chambers , recovering the fluorescence signal due to enzymatic amplification . The fast efflux rate and short mixing time of the fluorescent molecules in the miniature chambers guarantee that the fluorescence signal outside the cells accurately reflects the enzymatic activity inside . The microfluidic device is made of a soft polymer , polydimethylsiloxane -LRB- PDMS -RRB- , and consists of a flow layer that contains the cells and a top control layer -LRB- Fig. 1a -RRB- 15,16 . Actuation of two adjacent valves in the control layer forms an enclosure of dimensions 100 100 10 mm3 -LRB- 100 pl -RRB- in which cells can be trapped and cultured17 ,18 -LRB- Fig. 1c , d ; see also Supplementary Fig . S1 -RRB- . The microfluidic chip is mounted on an inverted fluorescence microscope and translated by a motorized stage , allowing multiplexing of data acquisition by repeatedly scanning the chambers . Typically , 100 chambers can be scanned within less than 2 min . Fluorescence is excited with a tightly focused laser beam -LRB- Fig. 1a -RRB- that does not directly illuminate the cell , avoiding cellular autofluorescence and photo-damage to the cell . We first show the ability to detect single enzyme molecules using this technique by injecting a diluted solution of purified b-gal enzyme and 300 mM of the fluorogenic substrate fluorescein-di-bD - galactopyranoside -LRB- FDG -RRB- into the chambers19 . Fluorescence signals from different chambers increase with time , and the slopes give the rates of hydrolysis -LRB- Fig. 1e -RRB- . The distribution of hydrolysis rates measured in the different chambers shows quantized and evenly spaced peaks -LRB- Fig. 1f -RRB- . We attribute these discrete peaks to integer numbers of b-gal molecules . The spacing between the peaks is 60 pM min21 , which gives a calibration for the rate of increase in fluorescein concentration corresponding to one enzyme molecule in a chamber . Another challenge for using b-gal to monitor gene expression in live cells is that the cell wall acts as a barrier for FDG influx . We quantify this effect in E. coli by measuring the hydrolysis rate for live cells compared to cells treated with chloroform , which completely permeabilizes cell membrane -LRB- Supplementary Fig . S4a -RRB- . The ratio of hydrolysis rates between these two cases is defined as the permeability ratio , and is measured to be R 13 at 300 mm FDG . To increase FDG influx , we transformed E. coli cells with a plasmid conferring ampicillin resistance and grew the cells in media with b-lactam antibiotics -LRB- see Methods -RRB- . Under these conditions , cell wall synthesis is partially inhibited , making the cells more permeable to FDG , as evident by a lower value of R 2 ^ 0.3 -LRB- Supplementary Fig . S4b -RRB- . In determining the number of enzyme molecules in live cells below , R 2 is used as a correction factor to the in vitro calibration -LRB- Fig. 1f -RRB- . We then monitored gene expression in live E. coli cells in real time . b-gal is expressed from the lacZ gene on the chromosomal DNA , which is under the control of the lac promoter . Cells are grown in glucose-containing medium without inducer to exponential phase ; hence the expression level is highly repressed20 . We observed abrupt changes in hydrolysis rates in chambers with dividing cells , as shown in Fig. 2a , b . These step-wise increases in the rates indicate the stochastic burst-like expression of new b-gal molecules . We attribute the bursts to stochastic and transient dissociation events of the Lac repressor from the promoter , followed by transcription of mRNA , which is then translated into a few copies of the reporter protein before the mRNA is degraded . The expression of proteins from a given gene can be characterized by two key parameters : the average frequency of expression bursts per cell cycle , a ; and the average number of protein molecules per burst , b. Under conditions of exponential growth in minimal medium , the burst frequency for protein expression from the repressed E. coli lacZ gene is measured to be a 0.11 ^ 0.03 bursts per cell cycle . The average burst size is measured to be b 5 ^ 2 enzymes , or 20 ^ 8 monomers per burst , which is consistent with biochemical estimates of 25 30 b-gal monomers per mRNA21 ,22 . This real-time assay also allows us to measure the distribution of the number of enzymes produced per burst -LRB- Fig. 2c -RRB- . It can be well fitted with an exponential distribution , P n C exp 2n = b , where n is the number of b-gal molecules per burst and C is a normalization constant . We attribute this distribution to the fact that the cellular lifetime of the mRNA is exponentially distributed21 ,23 . Previously only theoretically predicted 1,24 , the exponential P -LRB- n -RRB- can be accounted for by the competition between mRNA degradation by Figure 2 | Quantitative real-time measurement of individual protein expression events in live E. coli cells . b-gal is under the control of a repressed lac promoter . a , Trace of a chamber containing dividing cells shows abrupt changes in hydrolysis rates -LRB- arrows on black curve -RRB- . An empty chamber shows a constant background -LRB- red curve -RRB- . b , Discrete jumps in b-gal number are due to burst-like production of proteins . The number of b-gal molecules is calculated by taking the time derivative of the traces in a and compensating for fluorescein photobleaching -LRB- Supplementary Information -RRB- . c , Histogram of copy number of b-gal molecules per burst . The distribution is well-fitted with an exponential function -LRB- black line -RRB- , with an average of five proteins per burst , and is a consequence of exponential cellular lifetime of the mRNA . 359 2006 Nature Publishing Group LETTERS NATURE | Vol 440 | 16 March 2006 Figure 3 | Steady-state protein copy number distributions in a population of cells . a , Histogram of FDG hydrolysis rates from 48 chambers containing chloroform-treated E. coli cells shows discrete , evenly spaced peaks , with spacing equal to that measured with purified enzyme -LRB- Fig. 1f -RRB- . b , Copy number distribution of b-gal molecules in chambers containing a single E. coli cell , under the repressed condition -LRB- 120 cells -RRB- . The solid line shows a gamma distribution -LRB- equation -LRB- 1 -RRB- -RRB- with a 0.16 bursts per cell cycle and b 7.8 b-gal molecules per burst . Inset : average hydrolysis rate grows linearly with the number of cells per chamber with a slope of 0.9 enzymes per cell . c , Histogram of the number of b-gal molecules in chloroform-treated yeast cells -LRB- 116 cells -RRB- expressing b-gal from the repressed GAL1 promoter carried on a low copy number plasmid . The solid line is a gamma distribution with a 0.2 and b 1.7 . RNaseE and translation by ribosome . Our single-molecule experiment demonstrates the ability to provide quantitative real-time information on gene expression in a live cell . Stochasticity of gene expression is exhibited not only in the temporal evolution of protein production in a single cell , but also in the distribution of protein copy number in a population of cells at a particular time . Such distributions have been measured using flow cytometry3 ,4 or fluorescence microscopy2 ,5,6 , but have been limited to only high expression levels . Our method allows measurements of the reporter 's distribution in a cell population with single copy sensitivity . To do this , we treated E. coli cells with chloroform , which completely permeabilizes cell membrane and stops protein production , while keeping existing b-gal molecules active inside the cell -LRB- Fig. 3b , inset -RRB- . The treated cells are immediately injected into the microfluidic device together with FDG and the hydrolysis rate is measured . We first demonstrate the detection of single enzyme molecules inside those chloroform-treated cells . The histogram of hydrolysis rates of all chambers shows quantized peaks -LRB- Fig. 3a and Supplementary Fig . S12 -RRB- . The spacing between peaks is in agreement with that measured in vitro -LRB- Fig. 1f -RRB- . We compiled a histogram of the number of b-gal molecules in chambers containing only a single cell -LRB- Fig. 3b -RRB- for cells cultured under the same repressed condition as in the real-time experiment . The mean of this distribution is m 1.2 ^ 0.4 copies of b-gal molecules per cell , and the standard deviation is j 3.3 . The mean agrees with the ensemble measurement of 1 ^ 0.5 b-gal per cell , as well as the observation that the average number of b-gal molecules per chamber increases with the number of cells trapped in a chamber with a slope of 0.9 enzymes per cell -LRB- Fig. 3b inset -RRB- . We created a model to relate the measured steady-state protein copy number distributions to the parameters a and b that are defined above . We used a continuous form of the master equation25 to analytically describe that distribution given the burst dynamics of protein production . We assume that : -LRB- 1 -RRB- distribution of protein molecules produced per expression event is exponential ; -LRB- 2 -RRB- expression events are temporally uncorrelated ; and -LRB- 3 -RRB- protein molecule copy numbers are halved at cell division . At steady-state , protein production is balanced by protein dilution due to cell growth and division . We found that the steady-state probability distribution of protein number per cell , p -LRB- x -RRB- , is a gamma distribution , which is uniquely determined by the parameters a and b -LRB- Supplementary Information -RRB- : xa21 e2x = b 1 p x a b G a where G denotes the gamma function . The parameters a and b are 360 related to the mean , m , and standard deviation , j , by a m 2/j 2 and b j 2/m . Figure 3b shows that the data fits well with equation -LRB- 1 -RRB- , with b 7.8 ^ 2.6 reporters per burst and a 0.16 ^ 0.05 bursts per cell cycle , which are consistent with the real-time data above within error bars . This demonstrates that the information about the underlying dynamic process , namely the values of a and b , is preserved in both the temporal fluctuations in a single cell and the instantaneous variability within a population . Notably , the profile of p -LRB- x -RRB- with a , 1 that we measured for the repressed lac operon is distinct from p -LRB- x -RRB- with a . 1 that was measured previously for the induced lac operon2 . These correspond to two different regimes of equation -LRB- 1 -RRB- , schematically illustrated in Fig. 4 . For a , 1 , p -LRB- x -RRB- peaks at zero and a large fraction of cells contains no b-gal regardless of the burst size b -LRB- Fig. 4a -RRB- ; however , for Figure 4 | Two regimes of stochasticity in protein expression . Protein molecules are produced in bursts -LRB- red -RRB- , in addition to existing molecules -LRB- blue -RRB- , and diluted upon cell division , leading to a steady-state distribution , p -LRB- x -RRB- , of protein copy number , x , in the cell population . a , With a , 1 , p -LRB- x -RRB- peaks at x 0 and a large fraction of cells do not contain a single copy of the protein regardless of the burst size , b . The repressed lac operon is well described by this regime . b , With a . 1 , most cells contain the protein at some level . Both regimes can be described by the gamma distribution -LRB- equation -LRB- 1 -RRB- -RRB- . 2006 Nature Publishing Group NATURE | Vol 440 | 16 March 2006 LETTERS a . 1 , p -LRB- x -RRB- peaks at a non-zero x and most cells contain b-gal -LRB- Fig. 4b -RRB- . The profile of p -LRB- x -RRB- for a , 1 may be significant for the response of a population of E. coli cells to an increase in lactose concentration , which is transported into the cell by Lac permease . Because b-gal and Lac permease are expressed from the same operon , the large subpopulation of cells containing no b-gal would generally have no Lac permease . These cells can not respond to a rise of lactose concentration in the environment , and thus are distinct from cells containing permease , which can respond and induce further expression of the lac operon by way of positive feedback . Thus , a , 1 provides a mechanism for ` all-or-none ' induction responses that cells exhibit under suboptimal inducer concentrations11 ,26 . This microfluidic assay can be applied to other cell types expressing b-gal as a reporter . We demonstrate applicability by measuring low-level expression from repressed promoters in yeast and mammalian cells . Figure 3c shows the distribution of reporter number in a population of chloroform-treated Saccharomyces cerevisiae -LRB- yKT32 -RRB- cells expressing b-gal from the repressed GAL1 promoter . Here , the promoter reporter fusion is carried on a low copy number plasmid . Cells were grown in the presence of glucose , such that the promoter is expected to be highly repressed . The average expression level is measured to be 0.4 ^ 0.07 reporters per cell , with j 0.6 . Using the above model -LRB- equation -LRB- 1 -RRB- -RRB- we can extract a and b from the measured mean and j : a 0.2 ^ 0.08 bursts per cell cycle and b 1.7 ^ 0.4 reporters per burst . This is consistent with our realtime experiments with permeable mutant yeast strain -LRB- pdr1 2 pdr3 2 -RRB- in which we do not observe abrupt large jumps as seen with E. coli . The low burst size in this case may reflect the non-optimal codon usage of the bacterial reporter gene in yeast . Finally , we measured b-gal expression also from the ROSA26 promoter in embryonic mouse stem cells -LRB- ES 54A -RRB- . The average expression level was 425 ^ 80 enzymes per cell with j 375 -LRB- Supplementary Information -RRB- . The single cell version of the b-gal assay9 presented here exhibits single molecule sensitivity for single prokaryotic and eukaryotic cells . This method , together with other newly developed single cell and single molecule techniques at the mRNA27 ,28 and protein29 levels , opens up possibilities for studying low-level gene expression in single cells of diverse cell types -LRB- for example , transcription factors involved in gene regulation , or the leakiness of supposedly silenced promoters in differentiated cells -RRB- . The ease of scaling up the microfluidic assay will enable characterization of gene expression on a whole-genome scale , especially in the unexplored regime of low expression levels . METHODS Cell strains and growth conditions . E. coli K12 -LRB- MG1655 -RRB- cells are transformed with a medium copy number plasmid , pBR293 .3 , which confers ampicillin resistance . Cells were cultured in M9 media supplemented with amino acids and vitamins . Experiments were performed at 30 8C . Under these conditions cells grow with a cell cycle time of about 145 min -LRB- Supplementary Fig . S1 -RRB- . S. cerevisiae cells -LRB- yKT0032 -RRB- express b-gal from the GAL1 promoter , carried on a low-copy 2 mm plasmid -LRB- pYES2-lacZ -RRB- . Cells were cultured in SD glucose ura medium -LRB- BD Bioscience -RRB- at 30 8C . Mouse embryonic stem cells ES54A -LRB- Smo / 2 , Rosa26 lacZ -RRB- and ES17 -LRB- lacZ2 -RRB- from a 129SVJ background were cultured in a defined medium to prevent differentiation . Single cell suspension is derived by adding trypsin to the cell culture and resuspending . Microfluidic chip fabrication . The master mould for the bottom channels is made by spin-coating positive photoresist -LRB- Shipley SPR 220-7 , MicroChem -RRB- onto a silicon wafer -LRB- University Wafer -RRB- to a height of 7 mm . After patterning with high-resolution transparency mask -LRB- PageWorks -RRB- , the features are rounded by heating15 ,16 . The control layer master is patterned with negative photoresist at 40 mm height . PDMS -LRB- 10:1 Dow Corning Sylgard 184 A : B , Ellsworth Adhesives -RRB- is spun onto the bottom master at 2,000 r.p.m. for 1 min and partially cured . Control layer PDMS mould is also partially cured and baked at the thickness of 5 mm . The two PDMS pieces are aligned and cured overnight . The two-layer device is cut out , plasma oxidized for 3 min and bonded permanently to a coverslip . Fluorescence detection . Fluorescence was excited by a tightly focused beam of a 488-nm Ar-ion laser -LRB- Melles Griot -RRB- , with a power of 27 mW . A high NA objective lens -LRB- Nikon 60 Plan Apo NA 1.4 -RRB- was used in an inverted fluorescence microscope -LRB- Nikon -RRB- for excitation and collection of the fluorescence signal . A CCD camera -LRB- Andor Technology -RRB- with on-chip amplification and a large dynamic range was used for detection . Filters used were : excitation , 488 nm narrow bandpass ; emission , 535 nm/50 bandpass ; dichroic , 495 nm high pass -LRB- Chroma Corp -RRB- . Measurement of signals from multiple chambers was multiplexed by scanning the microfluidic chip using a motorized stage , ASI MS2000 XY -LRB- ASI -RRB- . Data analysis . Analysis of the fluorescent signal was performed using Matlab -LRB- Mathworks -RRB- . Signal was averaged over the 100 brightest pixels from each image , and background was subtracted . The measured fluorescence time traces F -LRB- t -RRB- were corrected for photobleaching and time derivative was taken to obtain the number of enzymes in a chamber as a function of time . A median filter of length 11 was used to smooth F -LRB- t -RRB- . With a sampling rate of once every 20 s per chamber , the effective time resolution is about 4 min . The error in calculating the parameters a and b from the copy number distribution was estimated with bootstrap analysis30 . The original data set was re-sampled 1,000 times . The a and b parameters were calculated for each of those re-sampled data sets , from which the error was estimated . Additional details are provided in the Supplementary Information . Received 12 September 2005 ; accepted 23 January 2006 . 1 . 2 . 3 . McAdams , H. H. & Arkin , A. Stochastic mechanisms in gene expression . Proc . Natl Acad . Sci . USA 94 , 814 -819 -LRB- 1997 -RRB- . Elowitz , M. B. , Levine , A. J. , Siggia , E. D. & Swain , P. S. Stochastic gene expression in a single cell . Science 297 , 1183 -1186 -LRB- 2002 -RRB- . Ozbudak , E. M. , Thattai , M. , Kurtser , I. , Grossman , A. D. & van Oudenaarden , A. Regulation of noise in the expression of a single gene . Nature Genet . 31 , 69 -LRB- 2002 -RRB- . -73 Blake , W. J. , K rn , M. , Cantor , C. R. & Collins , J. J. Noise in eukaryotic gene expression . Nature 422 , 633 -637 -LRB- 2003 -RRB- . Raser , J. M. & O'Shea , E. K. Control of stochasticity in eukaryotic gene expression . 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Zare groups , and the Harvard Center for Nanoscale Systems for help with microfluidic fabrication . We thank K. Thorn for yeast strains , and A. and J. McMahon for stem cell strains . This work was funded by Department of Energy , Office of Biological and Environmental Research , Genomics : GTL Program , and in part by National Institute of Health -LRB- NIH -RRB- Director 's Pioneer Award to X.S.X. , and an NIH grant . L.C. is supported by a National Science Foundation Graduate Research Fellowship and N.F. by a Human Frontiers Science Program Long Term Fellowship . Author Information Reprints and permissions information is available at npg.nature.com/reprintsandpermissions . The authors declare no competing financial interests . Correspondence and requests for materials should be addressed to X.S.X. -LRB- xie@chemistry.harvard.edu -RRB- . Supplementary Information is linked to the online version of the paper at www.nature.com/nature . 362 2006 Nature Publishing Group

O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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