A high surface area pn-heterojunction between TiO 2 and an organic p-type charge transport material (spiro-OMeTAD) was sensitized to visible light using lead sulfide (PbS) quantum dots. PbS quantum dots were formed in situ on a nanocrystalline TiO 2 electrode using chemical bath deposition techniques. 1 The organic hole conductor was applied from solution to form the sensitized heterojunction. The structure of the quantum dots was analyzed using HRTEM technique. Ultrafast laser photolysis experiments suggested the initial charge separation to proceed in the subpicosecond time range. Transient absorption laser spectroscopy revealed that interfacial charge recombination of the initially formed charge carriers is much faster than in comparable dye-sensitized systems. 2,3 The sensitized heterojunction showed incident photon-to-electron conversion efficiencies (IPCE) of up to 45% and energy conversion efficiencies under simulated sunlight AM1.5 (10 mW/cm2) of 0.49%.

Specific adsorption of cations (H + , Li + , ...) on TiO 2 nanocrystalline particles is known to control the energetics of the conduction band and therefore the ability for molecular sensitizers to inject electrons into the semiconductor upon irradiation. In photoelectrochemical energy conversion devices employing dye-sensitized titanium dioxide mesoporous electrodes, back electron transfer is generally intercepted by the use of the iodide/triiodide couple as a charge mediator. Kinetics of the oxidation of I -by the oxidized state of cis-Ru II -(dcbpy) 2 (NCS) 2 sensitizer adsorbed on TiO 2 was measured by flash photolysis in propylene carbonate. The rate of this reaction was found to depend on the nature and concentration of added cations such as Mg 2+ , Li + , Na + , and K + . A brusque acceleration of the process was in particular observed at a critical concentration. Electrophoretic measurements showed that this step in the dye regeneration reaction kinetics corresponds to the reversal of particle surface charge upon adsorption of potential-determining species, which causes I -to efficiently adsorb onto the oxide. These observations strongly suggest that the specific adsorption of cations on TiO 2 nanoparticles governs the formation of (I -, I -) ion pairs on the surface, and allows the more energetically favorable and faster mechanism involving oxidation of I -to I 2•-radical to take place.

Glucose is the preferred carbon source for most cell types and a major determinant of cell growth. In yeast and certain mammalian cells, glucose activates the cAMPdependent protein kinase A (PKA), but the mechanisms of PKA activation remain unknown. Here, we identify cytosolic pH as a second messenger for glucose that mediates activation of the PKA pathway in yeast. We find that cytosolic pH is rapidly and reversibly regulated by glucose metabolism and identify the vacuolar ATPase (V-ATPase), a proton pump required for the acidification of vacuoles, as a sensor of cytosolic pH. V-ATPase assembly is regulated by cytosolic pH and is required for full activation of the PKA pathway in response to glucose, suggesting that it mediates, at least in part, the pH signal to PKA. Finally, V-ATPase is also regulated by glucose in the Min6 b-cell line and contributes to PKA activation and insulin secretion. Thus, these data suggest a novel and potentially conserved glucose-sensing pathway and identify a mechanism how cytosolic pH can act as a signal to promote cell growth.

Recent computational studies indicate that the molecular noise of a cellular process may be a rich source of information about process dynamics and parameters. However, accessing this source requires stochastic models that are usually difficult to analyze. Therefore, parameter estimation for stochastic systems using distribution measurements, as provided for instance by flow cytometry, currently remains limited to very small and simple systems. Here we propose a new method that makes use of low-order moments of the measured distribution and thereby keeps the essential parts of the provided information, while still staying applicable to systems of realistic size. We demonstrate how cell-to-cell variability can be incorporated into the analysis obviating the need for the ubiquitous assumption that the measurements stem from a homogeneous cell population. We demonstrate the method for a simple example of gene expression using synthetic data generated by stochastic simulation. Subsequently, we use time-lapsed flow cytometry data for the osmo-stress induced transcriptional response in budding yeast to calibrate a stochastic model, which is then used as a basis for predictions. Our results show that measurements of the mean and the variance can be enough to determine the model parameters, even if the measured distributions are not well-characterized by low-order moments only-e.g., if they are bimodal.extrinsic variability | high-osmolarity glycerol pathway | moment dynamics | parameter inference | stochastic kinetic models B uilding predictive computational models of intracellular reaction kinetics is still a dauntingly ill-posed task (1), characterized by low-dimensional experimental readouts of the hypothesized high-dimensional process. Single-cell technologies hold promise to partly alleviate this ill-posedness by exploiting the observed variability for the calibration of stochastic kinetic models (2, 3). The same technologies, however, also reveal that isogenic cells in a single population exhibit large cell-to-cell variability (4, 5). The variation can be shown to be a convolution of two sources, namely the intrinsic molecular noise and extrinsic factors that render single cells different even in the absence of molecular noise; in many cases, the latter was reported to dominate the former (4, 5). Extrinsic factors comprise difference in cell size, cell-cycle stage, expression capacity, local growth conditionsto name but a few (6, 7). Thus, although single-cell technology offers a way out of the predicament of ill-posedness, it requires new methods to deal properly with intrinsic and extrinsic variability. The effect of extrinsic variability on the dynamics of stochastic models is studied in refs. 7 and 8, whereas first attempts have been made to address the inverse problem of quantifying the extrinsic (9) and any additional intrinsic (10) components from measurements. Because the latter is based on path sampling, its applicability remains limited to small systems. Naturally, extrinsic variability is bypassed when...

Mitogen-activated protein kinase (MAPK) cascades are conserved signalling modules that control many cellular processes by integrating intra-and extracellular cues. The p38/Hog1 MAPK is transiently activated in response to osmotic stress, leading to rapid translocation into the nucleus and induction of a specific transcriptional program. When investigating the dynamic interplay between Hog1 activation and Hog1-driven gene expression, we found that Hog1 activation increases linearly with stimulus, whereas the transcriptional output is bimodal. Modelling predictions, corroborated by single cell experiments, established that a slow stochastic transition from a repressed to an activated transcriptional state in conjunction with transient Hog1 activation generates this behaviour. Together, these findings provide a molecular mechanism by which a cell can impose a transcriptional threshold in response to a linear signalling behaviour. The authors declare that they have no competing financial interests. Transcriptional activation of mating genes occurs with linear kinetics and high fidelity (5,6), and the observed cell-to-cell variation in protein expression is governed by the ability of cells to express proteins (expression capacity) (5). While the mating pathway can be compared to a cell-fate decision system with sustained MAPK activity, the HOG pathway is an adaptation response, which is only transiently induced like other stress-activated pathways (7). We therefore investigated whether this transient response would trigger different expression behaviour. Mitogen-activated protein kinase (MAPKTo quantitatively measure the transcriptional output induced by osmotic stress, we engineered a reporter system based on a quadruple Venus (qV) fluorescent protein expressed under the control of specific osmo-stress-inducible promoters dependant on the three main transcription factors orchestrating the transcriptional response to osmotic 3 stress (Hot1 and Sko1: pSTL1, Msn2,4: pALD3 or Msn2,4 and Hot1: pHSP12) (8). Flow cytometry revealed a Pbs2-dependent 20-fold increase in pSTL1-qV reporter expression when 0.4M NaCl was added to the growth medium ( Fig. 1 A and B). also generated a bimodal expression output of the Ste12-specific reporter pFIG1-qV.However, signalling in the mating pathway is prevented from "Start" through S phase (9), and expression output became unimodal after relieving this cell-cycle dependent restriction ( Fig. 1B and Fig. S1B).To investigate the source of the HOG pathway bimodal expression behaviour, we integrated two reporters driving the expression of a quadruple cyan fluorescent protein (qCFP) and a qV construct in the same cell. Correlation of the cyan and yellow intensities measures the contribution of cell-to-cell (extrinsic) and intra-cellular (intrinsic) variability to the overall expression noise (5, 10). The two pFIG1-reporters induced by !-factor demonstrated that the mating pathway is governed by extrinsic noise. In contrast,we observed a lack of correlation between the two pSTL1-repor...

Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.

Directional cell growth requires that cells read and interpret shallow chemical gradients, but how the gradient directional information is identified remains elusive. We use single-cell analysis and mathematical modeling to define the cellular gradient decoding network in yeast. Our results demonstrate that the spatial information of the gradient signal is read locally within the polarity site complex using double-positive feedback between the GTPase Cdc42 and trafficking of the receptor Ste2. Spatial decoding critically depends on low Cdc42 activity, which is maintained by the MAPK Fus3 through sequestration of the Cdc42 activator Cdc24. Deregulated Cdc42 or Ste2 trafficking prevents gradient decoding and leads to mis-oriented growth. Our work discovers how a conserved set of components assembles a network integrating signal intensity and directionality to decode the spatial information contained in chemical gradients.

Spectral resolved tissue imaging has a broad range of biomedical applications such as the minimally invasive diagnosis of diseases and the study of wound healing and tissue engineering processes. Two-photon microscopy imaging of endogenous fluorescence has been shown to be a powerful method for the quantification of tissue structure and biochemistry. While two-photon excited autofluorescence is observed ubiquitously, the identities and distributions of endogenous fluorophores have not been completely characterized in most tissues. We develop an image-guided spectral analysis method to analyze the distribution of fluorophores in human skin from 3-D resolved two-photon images. We identify five factors that contribute to most of the luminescence signals from human skin. Luminescence species identified include tryptophan, NAD(P)H, melanin, and elastin, which are autofluorescent, and collagen that contributes to a second harmonic signal.