Adaptation to DNA damage checkpoint in senescent telomerase-negative cells promotes genome instability.

In cells lacking telomerase, telomeres gradually shorten during each cell division to reach a critically short length, permanently activate the DNA damage checkpoint, and trigger replicative senescence. The increase in genome instability that occurs as a consequence may contribute to the early steps of tumorigenesis. However, because of the low frequency of mutations and the heterogeneity of telomere-induced senescence, the timing and mechanisms of genome instability increase remain elusive. Here, to capture early mutation events during replicative senescence, we used a combined microfluidic-based approach and live-cell imaging in yeast. We analyzed DNA damage checkpoint activation in consecutive cell divisions of individual cell lineages in telomerase-negative yeast cells and observed that prolonged checkpoint arrests occurred frequently in telomerase-negative lineages. Cells relied on the adaptation to the DNA damage pathway to bypass the prolonged checkpoint arrests, allowing further cell divisions despite the presence of unrepaired DNA damage. We demonstrate that the adaptation pathway is a major contributor to the genome instability induced during replicative senescence. Therefore, adaptation plays a critical role in shaping the dynamics of genome instability during replicative senescence.

Implication of polymerase recycling for nascent transcript quantification by live cell imaging.

Transcription enables the production of RNA from a DNA template. Due to the highly dynamic nature of transcription, live-cell imaging methods play a crucial role in measuring the kinetics of this process. For instance, transcriptional bursts have been visualized using fluorescent phage-coat proteins that associate tightly with messenger RNA (mRNA) stem loops formed on nascent transcripts. To convert the signal emanating from a transcription site into meaningful estimates of transcription dynamics, the influence of various parameters on the measured signal must be evaluated. Here, the effect of gene length on the intensity of the transcription site focus was analyzed. Intuitively, a longer gene can support a larger number of transcribing polymerases, thus leading to an increase in the measured signal. However, measurements of transcription induced by hyper-osmotic stress responsive promoters display independence from gene length. A mathematical model of the stress-induced transcription process suggests that the formation of gene loops that favor the recycling of polymerase from the terminator to the promoter can explain the observed behavior. One experimentally validated prediction from this model is that the amount of mRNA produced from a short gene should be higher than for a long one as the density of active polymerase on the short gene will be increased by polymerase recycling. Our data suggest that this recycling contributes significantly to the expression output from a gene and that polymerase recycling is modulated by the promoter identity and the cellular state.

Timing of gene expression in a cell-fate decision system.

During development, morphogens provide extracellular cues allowing cells to select a specific fate by inducing complex transcriptional programs. The mating pathway in budding yeast offers simplified settings to understand this process. Pheromone secreted by the mating partner triggers the activity of a MAPK pathway, which results in the expression of hundreds of genes. Using a dynamic expression reporter, we quantified the kinetics of gene expression in single cells upon exogenous pheromone stimulation and in the physiological context of mating. In both conditions, we observed striking differences in the timing of induction of mating-responsive promoters. Biochemical analyses and generation of synthetic promoter variants demonstrated how the interplay between transcription factor binding and nucleosomes contributes to determine the kinetics of transcription in a simplified cell-fate decision system.

Highly variable individual donor cell fates characterize robust horizontal gene transfer of an integrative and conjugative element.

Horizontal gene transfer is an important evolutionary mechanism for bacterial adaptation. However, given the typical low transfer frequencies in a bacterial population, little is known about the fate and interplay of donor cells and the mobilized DNA during transfer. Here we study transfer of an integrative and conjugative element (ICE) among individual live bacterial cells. ICEs are widely distributed mobile DNA elements that are different than plasmids because they reside silent in the host chromosome and are maintained through vertical descent. Occasionally, ICEs become active, excise, and transmit their DNA to a new recipient, where it is reintegrated. We develop a fluorescent tool to differentiate excision, transfer, and reintegration of a model ICE named ICEclc (for carrying the clc genes for chlorocatechol metabolism) among single Pseudomonas cells by using time-lapse microscopy. We find that ICEclc activation is initiated in stationary phase cells, but excision and transfer predominantly occur only when such cells have been presented with new nutrients. Donors with activated ICE develop a number of different states, characterized by reduced cell division rates or growth arrest, persistence, or lysis, concomitant with ICE excision, and likely, ICE loss or replication. The donor cell state transitions can be described by using a stochastic model, which predicts that ICE fitness is optimal at low initiation rates in stationary phase. Despite highly variable donor cell fates, ICE transfer is remarkably robust overall, with 75% success after excision. Our results help to better understand ICE behavior and shed a new light on bacterial cellular differentiation during horizontal gene transfer.

Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.

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.

New families of single integration vectors and gene tagging plasmids for genetic manipulations in budding yeast.

The tractability of the budding yeast genome has provided many insights into the fundamental mechanisms regulating cellular life. With the advent of synthetic biology and single-cell measurements, novel tools are required to manipulate the yeast genome in a more controlled manner. We present, here, a new family of yeast shuttle vectors called single integration vectors (pSIV). Upon transformation in yeast, these plasmids replace the entire deficient auxotrophy marker locus by a cassette containing an exogenous marker. As shown using flow cytometry, this complete replacement results in a unique integration of the desired DNA fragment at the marker locus. In addition, a second transcriptional unit can be inserted to achieve the simultaneous integration of two constructs. The selection marker cassettes, present in the pSIV, were also used to generate a complete set of gene tagging plasmids (pGT) encompassing a large palette of fluorescent proteins, from a cyan fluorescent protein to a near-infrared tandem dimer red fluorescent protein. These tagging cassettes are orthogonal to each other thanks to the use of different TEF promoter and terminator couples, thereby avoiding marker cassette switching and favoring integration in the desired locus. In summary, we have created two sets of robust molecular tools for the precise genetic manipulation of the budding yeast.

Dynamic single cell measurements of kinase activity by synthetic kinase activity relocation sensors.

BACKGROUND: Mitogen activated protein kinases (MAPK) play an essential role in integrating extra-cellular signals and intra-cellular cues to allow cells to grow, adapt to stresses, or undergo apoptosis. Budding yeast serves as a powerful system to understand the fundamental regulatory mechanisms that allow these pathways to combine multiple signals and deliver an appropriate response. To fully comprehend the variability and dynamics of these signaling cascades, dynamic and quantitative single cell measurements are required. Microscopy is an ideal technique to obtain these data; however, novel assays have to be developed to measure the activity of these cascades. RESULTS: We have generated fluorescent biosensors that allow the real-time measurement of kinase activity at the single cell level. Here, synthetic MAPK substrates were engineered to undergo nuclear-to-cytoplasmic relocation upon phosphorylation of a nuclear localization sequence. Combination of fluorescence microscopy and automated image analysis allows the quantification of the dynamics of kinase activity in hundreds of single cells. A large heterogeneity in the dynamics of MAPK activity between individual cells was measured. The variability in the mating pathway can be accounted for by differences in cell cycle stage, while, in the cell wall integrity pathway, the response to cell wall stress is independent of cell cycle stage. CONCLUSIONS: These synthetic kinase activity relocation sensors allow the quantification of kinase activity in live single cells. The modularity of the architecture of these reporters will allow their application in many other signaling cascades. These measurements will allow to uncover new dynamic behaviour that previously could not be observed in population level measurements.

Quantifying intracellular protein binding thermodynamics during mechanotransduction based on FRET spectroscopy.

Mechanical force modulates myriad cellular functions including migration, alignment, proliferation, and gene transcription. Mechanotransduction, the transmission of mechanical forces and its translation into biochemical signals, may be mediated by force induced protein conformation changes, subsequently modulating protein signaling. For the paxillin and focal adhesion kinase interaction, we demonstrate that force-induced changes in protein complex conformation, dissociation constant, and binding Gibbs free energy can be quantified by lifetime-resolved fluorescence energy transfer microscopy combined with intensity imaging calibrated by fluorescence correlation spectroscopy. Comparison with in vitro data shows that this interaction is allosteric in vivo. Further, spatially resolved imaging and inhibitor assays show that this protein interaction and its mechano-sensitivity are equal in the cytosol and in the focal adhesions complexes indicating that the mechano-sensitivity of this interaction must be mediated by soluble factors but not based on protein tyrosine phosphorylation.

Moment-based inference predicts bimodality in transient gene expression.

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.

Cytosolic pH is a second messenger for glucose and regulates the PKA pathway through V-ATPase.

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 cAMP-dependent 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 beta-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.

Adapting to ever-changing conditions.

Experiments involving periodic stimuli shed light on the interplay between hyper-osmotic stress and glucose starvation in yeast cells.

Live cell microscopy: From image to insight.

Live-cell microscopy is a powerful tool that can reveal cellular behavior as well as the underlying molecular processes. A key advantage of microscopy is that by visualizing biological processes, it can provide direct insights. Nevertheless, live-cell imaging can be technically challenging and prone to artifacts. For a successful experiment, many careful decisions are required at all steps from hardware selection to downstream image analysis. Facing these questions can be particularly intimidating due to the requirement for expertise in multiple disciplines, ranging from optics, biophysics, and programming to cell biology. In this review, we aim to summarize the key points that need to be considered when setting up and analyzing a live-cell imaging experiment. While we put a particular focus on yeast, many of the concepts discussed are applicable also to other organisms. In addition, we discuss reporting and data sharing strategies that we think are critical to improve reproducibility in the field.

Environmental connectivity controls diversity in soil microbial communities.

Interspecific interactions are thought to govern the stability and functioning of microbial communities, but the influence of the spatial environment and its structural connectivity on the potential of such interactions to unfold remain largely unknown. Here we studied the effects on community growth and microbial diversity as a function of environmental connectivity, where we define environmental connectivity as the degree of habitat fragmentation preventing microbial cells from living together. We quantitatively compared growth of a naturally-derived high microbial diversity community from soil in a completely mixed liquid suspension (high connectivity) to growth in a massively fragmented and poorly connected environment (low connectivity). The low connectivity environment consisted of homogenously-sized miniature agarose beads containing random single or paired founder cells. We found that overall community growth was the same in both environments, but the low connectivity environment dramatically reduced global community-level diversity compared to the high connectivity environment. Experimental observations were supported by community growth modeling. The model predicts a loss of diversity in the low connectivity environment as a result of negative interspecific interactions becoming more dominant at small founder species numbers. Counterintuitively for the low connectivity environment, growth of isolated single genotypes was less productive than that of random founder genotype cell pairs, suggesting that the community as a whole profited from emerging positive interspecific interactions. Our work demonstrates the importance of environmental connectivity for growth of natural soil microbial communities, which aids future efforts to intervene in or restore community composition to achieve engineering and biotechnological objectives.

Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation.

Parameterized models of biophysical and mechanical cell properties are important for predictive mathematical modeling of cellular processes. The concepts of turgor, cell wall elasticity, osmotically active volume, and intracellular osmolarity have been investigated for decades, but a consistent rigorous parameterization of these concepts is lacking. Here, we subjected several data sets of minimum volume measurements in yeast obtained after hyper-osmotic shock to a thermodynamic modeling framework. We estimated parameters for several relevant biophysical cell properties and tested alternative hypotheses about these concepts using a model discrimination approach. In accordance with previous reports, we estimated an average initial turgor of 0.6 ± 0.2 MPa and found that turgor becomes negligible at a relative volume of 93.3 ± 6.3% corresponding to an osmotic shock of 0.4 ± 0.2 Osm/l. At high stress levels (4 Osm/l), plasmolysis may occur. We found that the volumetric elastic modulus, a measure of cell wall elasticity, is 14.3 ± 10.4 MPa. Our model discrimination analysis suggests that other thermodynamic quantities affecting the intracellular water potential, for example the matrix potential, can be neglected under physiological conditions. The parameterized turgor models showed that activation of the osmosensing high osmolarity glycerol (HOG) signaling pathway correlates with turgor loss in a 1:1 relationship. This finding suggests that mechanical properties of the membrane trigger HOG pathway activation, which can be represented and quantitatively modeled by turgor.

Single-particle imaging of stress-promoters induction reveals the interplay between MAPK signaling, chromatin and transcription factors.

Precise regulation of gene expression in response to environmental changes is crucial for cell survival, adaptation and proliferation. In eukaryotic cells, extracellular signal integration is often carried out by Mitogen-Activated Protein Kinases (MAPK). Despite a robust MAPK signaling activity, downstream gene expression can display a great variability between single cells. Using a live mRNA reporter, here we monitor the dynamics of transcription in Saccharomyces cerevisiae upon hyper-osmotic shock. We find that the transient activity of the MAPK Hog1 opens a temporal window where stress-response genes can be activated. We show that the first minutes of Hog1 activity are essential to control the activation of a promoter. Chromatin repression on a locus slows down this transition and contributes to the variability in gene expression, while binding of transcription factors increases the level of transcription. However, soon after Hog1 activity peaks, negative regulators promote chromatin closure of the locus and transcription progressively stops.

Visualizing cellular heterogeneity by quantifying the dynamics of MAPK activity in live mammalian cells with synthetic fluorescent biosensors.

Mitogen-Activated Protein Kinases (MAPKs) control a wide array of cellular functions by transducing extracellular information into defined biological responses. In order to understand how these pathways are regulated, dynamic single cell measurements are highly needed. Fluorescence microscopy is well suited to perform these measurements. However, more dynamic and sensitive biosensors that allow the quantification of signaling activity in living mammalian cells are required. We have engineered a synthetic fluorescent substrate for human MAPKs (ERK, JNK and p38) that relocates from the nucleus to the cytoplasm when phosphorylated by the kinases. We demonstrate that this reporter displays an improved response compared to other relocation biosensors. This assay allows to monitor the heterogeneity in the MAPK response in a population of isogenic cells, revealing pulses of ERK activity upon a physiological EGFR stimulation. We show applicability of this approach to the analysis of multiple cancer cell lines and primary cells as well as its application in vivo to developing tumors. Using this ERK biosensor, dynamic single cell measurements with high temporal resolution can be obtained. These MAPK reporters can be widely applied to the analysis of molecular mechanisms of MAPK signaling in healthy and diseased state, in cell culture assays or in vivo.

Crosstalk and spatiotemporal regulation between stress-induced MAP kinase pathways and pheromone signaling in budding yeast.

Budding yeast, Saccharomyces cerevisiae, has been widely used as a model system to study cellular signaling in response to internal and external cues. Yeast was among the first organisms in which the architecture, feedback mechanisms and physiological responses of various MAP kinase signaling cascades were studied in detail. Although these MAP kinase pathways are activated by different signals and elicit diverse cellular responses, such as adaptation to stress and mating, they function as an interconnected signaling network, as they influence each other and, in some cases, even share components. Indeed, various stress signaling pathways interfere with pheromone signaling that triggers a distinct cellular differentiation program. However, the molecular mechanisms responsible for this crosstalk are still poorly understood. Here, we review the general topology of the yeast MAP kinase signaling network and highlight recent and new data revealing how conflicting intrinsic and extrinsic signals are interpreted to orchestrate appropriate cellular responses.

Mechanical stress impairs pheromone signaling via Pkc1-mediated regulation of the MAPK scaffold Ste5.

Cells continuously adapt cellular processes by integrating external and internal signals. In yeast, multiple stress signals regulate pheromone signaling to prevent mating under unfavorable conditions. However, the underlying crosstalk mechanisms remain poorly understood. Here, we show that mechanical stress activates Pkc1, which prevents lysis of pheromone-treated cells by inhibiting polarized growth. In vitro Pkc1 phosphorylates conserved residues within the RING-H2 domains of the scaffold proteins Far1 and Ste5, which are also phosphorylated in vivo. Interestingly, Pkc1 triggers dispersal of Ste5 from mating projections upon mechanically induced stress and during cell-cell fusion, leading to inhibition of the MAPK Fus3. Indeed, RING phosphorylation interferes with Ste5 membrane association by preventing binding to the receptor-linked Gßγ protein. Cells expressing nonphosphorylatable Ste5 undergo increased lysis upon mechanical stress and exhibit defects in cell-cell fusion during mating, which is exacerbated by simultaneous expression of nonphosphorylatable Far1. These results uncover a mechanical stress-triggered crosstalk mechanism modulating pheromone signaling, polarized growth, and cell-cell fusion during mating.

Spectrally resolved fluorescence correlation spectroscopy based on global analysis.

Multicolor fluorescence correlation spectroscopy has been recently developed to study chemical interactions of multiple chemical species labeled with spectrally distinct fluorophores. In the presence of spectral overlap, there exists a lower detectability limit for reaction products with multicolor fluorophores. In addition, the ability to separate bound product from reactants allows thermodynamic properties such as dissociation constants to be measured for chemical reactions. In this report, we utilize a spectrally resolved two-photon microscope with single-photon counting sensitivity to acquire spectral and temporal information from multiple chemical species. Further, we have developed a global fitting analysis algorithm that simultaneously analyzes all distinct auto- and cross-correlation functions from 15 independent spectral channels. We have demonstrated that the global analysis approach allows the concentration and diffusion coefficients of fluorescent particles to be resolved despite the presence of overlapping emission spectra.