An integrated image analysis platform to quantify signal transduction in single cells

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.

Positive feedback induces switch between distributive and processive phosphorylation of Hog1

Cellular decision making often builds on ultrasensitive MAPK pathways. The phosphorylation mechanism of MAP kinase has so far been described as either distributive or processive, with distributive mechanisms generating ultrasensitivity in theoretical analyses. However, the in vivo mechanism of MAP kinase phosphorylation and its activation dynamics remain unclear. Here, we characterize the regulation of the MAP kinase Hog1 in Saccharomyces cerevisiae via topologically different ODE models, parameterized on multimodal activation data. Interestingly, our best fitting model switches between distributive and processive phosphorylation behavior regulated via a positive feedback loop composed of an affinity and a catalytic component targeting the MAP kinase-kinase Pbs2. Indeed, we show that Hog1 directly phosphorylates Pbs2 on serine 248 (S248), that cells expressing a non-phosphorylatable (S248A) or phosphomimetic (S248E) mutant show behavior that is consistent with simulations of disrupted or constitutively active affinity feedback and that Pbs2-S248E shows significantly increased affinity to Hog1 in vitro. Simulations further suggest that this mixed Hog1 activation mechanism is required for full sensitivity to stimuli and to ensure robustness to different perturbations.

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.

Mre11-Rad50 oligomerization promotes DNA double-strand break repair

The conserved Mre11-Rad50 complex is crucial for the detection, signaling, end tethering and processing of DNA double-strand breaks. While it is known that Mre11-Rad50 foci formation at DNA lesions accompanies repair, the underlying molecular assembly mechanisms and functional implications remained unclear. Combining pathway reconstitution in electron microscopy, biochemical assays and genetic studies, we show that S. cerevisiae Mre11-Rad50 with or without Xrs2 forms higher-order assemblies in solution and on DNA. Rad50 mediates such oligomerization, and mutations in a conserved Rad50 beta-sheet enhance or disrupt oligomerization. We demonstrate that Mre11-Rad50-Xrs2 oligomerization facilitates foci formation, DNA damage signaling, repair, and telomere maintenance in vivo. Mre11-Rad50 oligomerization does not affect its exonuclease activity but drives endonucleolytic cleavage at multiple sites on the 5'-DNA strand near double-strand breaks. Interestingly, mutations in the human RAD50 beta-sheet are linked to hereditary cancer predisposition and our findings might provide insights into their potential role in chemoresistance.

A convolutional neural network for segmentation of yeast cells without manual training annotations

MOTIVATION

Single-cell time-lapse microscopy is a ubiquitous tool for studying the dynamics of complex cellular processes. While imaging can be automated to generate very large volumes of data, the processing of the resulting movies to extract high-quality single-cell information remains a challenging task. The development of software tools that automatically identify and track cells is essential for realizing the full potential of time-lapse microscopy data. Convolutional neural networks (CNNs) are ideally suited for such applications, but require great amounts of manually annotated data for training, a time-consuming and tedious process.

RESULTS

We developed a new approach to CNN training for yeast cell segmentation based on synthetic data and present (i) a software tool for the generation of synthetic images mimicking brightfield images of budding yeast cells and (ii) a convolutional neural network (Mask R-CNN) for yeast segmentation that was trained on a fully synthetic dataset. The Mask R-CNN performed excellently on segmenting actual microscopy images of budding yeast cells, and a density-based spatial clustering algorithm (DBSCAN) was able to track the detected cells across the frames of microscopy movies. Our synthetic data creation tool completely bypassed the laborious generation of manually annotated training datasets, and can be easily adjusted to produce images with many different features. The incorporation of synthetic data creation into the development pipeline of CNN-based tools for budding yeast microscopy is a critical step toward the generation of more powerful, widely applicable and user-friendly image processing tools for this microorganism.

AVAILABILITY AND IMPLEMENTATION

The synthetic data generation code can be found at https://github.com/prhbrt/synthetic-yeast-cells. The Mask R-CNN as well as the tuning and benchmarking scripts can be found at https://github.com/ymzayek/yeastcells-detection-maskrcnn. We also provide Google Colab scripts that reproduce all the results of this work.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Roles of High Osmolarity Glycerol and Cell Wall Integrity Pathways in Cadmium Toxicity in Saccharomyces cerevisiae

Cadmium is a carcinogen that can induce ER stress, DNA damage, oxidative stress and cell death. The yeast mitogen-activated protein kinase (MAPK) signalling pathways paly crucial roles in response to various stresses. Here, we demonstrate that the unfolded protein response (UPR) pathway, the high osmolarity glycerol (HOG) pathway and the cell wall integrity (CWI) pathway are all essential for yeast cells to defend against the cadmium-induced toxicity, including the elevated ROS and cell death levels induced by cadmium. We show that the UPR pathway is required for the cadmium-induced phosphorylation of HOG_MAPK Hog1 but not for CWI_MAPK Slt2, while Slt2 but not Hog1 is required for the activation of the UPR pathway through the transcription factors of Swi6 and Rlm1. Moreover, deletion of HAC1 and IRE1 could promote the nuclear accumulation of Hog1, and increase the cytosolic and bud neck localisation of Slt2, indicating crucial roles of Hog1 and Slt2 in regulating the cellular process in the absence of UPR pathway. Altogether, our findings highlight the significance of these two MAPK pathways of HOG and CWI and their interrelationship with the UPR pathway in responding to cadmium-induced toxicity in budding yeast.

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.

A convolutional neural network segments yeast microscopy images with high accuracy

The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exhibit irregular features. We present a convolutional neural network (CNN) named YeaZ, the underlying training set of high-quality segmented yeast images (>10 000 cells) including mutants, stressed cells, and time courses, as well as a graphical user interface and a web application ( www.quantsysbio.com/data-and-software ) to efficiently employ, test, and expand the system. A key feature is a cell-cell boundary test which avoids the need for fluorescent markers. Our CNN is highly accurate, including for buds, and outperforms existing methods on benchmark images, indicating it transfers well to other conditions. To demonstrate how efficient large-scale image processing uncovers new biology, we analyze the geometries of ≈2200 wild-type and cyclin mutant cells and find that morphogenesis control occurs unexpectedly early and gradually.

Quantitative analysis of yeast MAPK signaling networks and crosstalk using a microfluidic device

Eukaryotic cells developed complex mitogen-activated protein kinase (MAPK) signaling networks to sense their intra- and extracellular environment and respond to various stress conditions. For example, S. cerevisiae uses five distinct MAP kinase pathways to orchestrate meiosis or respond to mating pheromones, osmolarity changes and cell wall stress. Although each MAPK module has been studied individually, the mechanisms underlying crosstalk between signaling pathways remain poorly understood, in part because suitable experimental systems to monitor cellular outputs when applying different signals are lacking. Here, we investigate the yeast MAPK signaling pathways and their crosstalk, taking advantage of a new microfluidic device coupled to quantitative microscopy. We designed specific micropads to trap yeast cells in a single focal plane, and modulate the magnitude of a given stress signal by microfluidic serial dilution while keeping other signaling inputs constant. This approach enabled us to quantify in single cells nuclear relocation of effectors responding to MAPK activation, like Yap1 for oxidative stress, and expression of stress-specific reporter expression, like pSTL1-qV and pFIG1-qV for high-osmolarity or mating pheromone signaling, respectively. Using this quantitative single-cell analysis, we confirmed bimodal behavior of gene expression in response to Hog1 activation, and quantified crosstalk between the pheromone- and cell wall integrity (CWI) signaling pathways. Importantly, we further observed that oxidative stress inhibits pheromone signaling. Mechanistically, this crosstalk is mediated by Pkc1-dependent phosphorylation of the scaffold protein Ste5 on serine 185, which prevents Ste5 recruitment to the plasma membrane.

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.

Nanoadhesive layer to prevent protein absorption in a poly(dimethylsiloxane) microfluidic device

Poly(dimethylsiloxane) (PDMS) is widely used as a microfluidics platform material; however, it absorbs various molecules, perturbing specific chemical concentrations in microfluidic channels. We present a simple solution to prevent adsorption into a PDMS microfluidic device. We used a vapor-phase-deposited nanoadhesive layer to seal PDMS microfluidic channels. Absorption of fluorescent molecules into PDMS was efficiently prevented in the nanolayer-treated PDMS device. Importantly, when cultured in a nanolayer-treated PDMS device, yeast cells exhibited the expected concentration-dependent response to a mating pheromone, including mating-specific morphological and gene expression changes, while yeast cultured in an untreated PDMS device did not properly respond to the pheromone. Our method greatly expands microfluidic applications that require precise control of molecule concentrations.

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

This study shows that Pkc1 inhibits yeast pheromone signaling upon intrinsic and extrinsic mechanical stress. Pkc1 phosphorylates the RING-H2 domains of the scaffolds Ste5 and Far1, thereby preventing their interaction with Gβγ at the plasma membrane. This crosstalk mechanism regulates polarized growth and cell–cell fusion during mating.

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 Gβγ 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.

Morphologically constrained and data informed cell segmentation of budding yeast

Motivation

Although high-content image cytometry is becoming increasingly routine, processing the large amount of data acquired during time-lapse experiments remains a challenge. The majority of approaches for automated single-cell segmentation focus on flat, uniform fields of view covered with a single layer of cells. In the increasingly popular microfluidic devices that trap individual cells for long term imaging, these conditions are not met. Consequently, most techniques for segmentation perform poorly. Although potentially constraining the generalizability of software, incorporating information about the microfluidic features, flow of media and the morphology of the cells can substantially improve performance.

Results

Here we present DISCO (Data Informed Segmentation of Cell Objects), a framework for using the physical constraints imposed by microfluidic traps, the shape based morphological constraints of budding yeast and temporal information about cell growth and motion to allow tracking and segmentation of cells in microfluidic devices. Using manually curated datasets, we demonstrate substantial improvements in both tracking and segmentation when compared with existing software.

Availability and implementation

The MATLAB code for the algorithm and for measuring performance is available at https://github.com/pswain/segmentation-software and the test images and the curated ground-truth results used for comparing the algorithms are available at http://datashare.is.ed.ac.uk/handle/10283/2002.

Contact

mcrane2@uw.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Reversible protein aggregation is a protective mechanism to ensure cell cycle restart after stress

Protein aggregation is mostly viewed as deleterious and irreversible causing several pathologies. However, reversible protein aggregation has recently emerged as a novel concept for cellular regulation. Here, we characterize stress-induced, reversible aggregation of yeast pyruvate kinase, Cdc19. Aggregation of Cdc19 is regulated by oligomerization and binding to allosteric regulators. We identify a region of low compositional complexity (LCR) within Cdc19 as necessary and sufficient for reversible aggregation. During exponential growth, shielding the LCR within tetrameric Cdc19 or phosphorylation of the LCR prevents unscheduled aggregation, while its dephosphorylation is necessary for reversible aggregation during stress. Cdc19 aggregation triggers its localization to stress granules and modulates their formation and dissolution. Reversible aggregation protects Cdc19 from stress-induced degradation, thereby allowing cell cycle restart after stress. Several other enzymes necessary for G1 progression also contain LCRs and aggregate reversibly during stress, implying that reversible aggregation represents a conserved mechanism regulating cell growth and survival.

Nuclear relocation of Kss1 contributes to the specificity of the mating response

Mitogen Activated Protein Kinases (MAPK) play a central role in transducing extra-cellular signals into defined biological responses. These enzymes, conserved in all eukaryotes, exert their function via the phosphorylation of numerous substrates located throughout the cell and by inducing a complex transcriptional program. The partitioning of their activity between the cytoplasm and the nucleus is thus central to their function. Budding yeast serves as a powerful system to understand the regulation of these fundamental biological phenomena. Under vegetative growth, the MAPK Kss1 is enriched in the nucleus of the cells. Stimulation with mating pheromone results in a rapid relocation of the protein in the cytoplasm. Activity of either Fus3 or Kss1 in the mating pathway is sufficient to drive this change in location by disassembling the complex formed between Kss1, Ste12 and Dig1. Artificial enrichment of the MAPK Kss1 in the nucleus in presence of mating pheromone alters the transcriptional response of the cells and induces a cell-cycle arrest in absence of Fus3 and Far1.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar, a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others.

Real-time quantification of protein expression at the single-cell level via dynamic protein synthesis translocation reporters

Protein expression is a dynamic process, which can be rapidly induced by extracellular signals. It is widely appreciated that single cells can display large variations in the level of gene induction. However, the variability in the dynamics of this process in individual cells is difficult to quantify using standard fluorescent protein (FP) expression assays, due to the slow maturation of their fluorophore. Here we have developed expression reporters that accurately measure both the levels and dynamics of protein synthesis in live single cells with a temporal resolution under a minute. Our system relies on the quantification of the translocation of a constitutively expressed FP into the nucleus. As a proof of concept, we used these reporters to measure the transient protein synthesis arising from two promoters responding to the yeast hyper osmolarity glycerol mitogen-activated protein kinase pathway (pSTL1 and pGPD1). They display distinct expression dynamics giving rise to strikingly different instantaneous expression noise.

Parallel feedback loops control the basal activity of the HOG MAPK signaling cascade

Tight regulation of the MAP kinase Hog1 is crucial for survival under changing osmotic conditions. Interestingly, we found that Hog1 phosphorylates multiple upstream components, implying feedback regulation within the signaling cascade. Taking advantage of an unexpected link between glucose availability and Hog1 activity, we used quantitative single cell measurements and computational modeling to unravel feedback regulation operating in addition to the well-known adaptation feedback triggered by glycerol accumulation. Indeed, we found that Hog1 phosphorylates its activating kinase Ssk2 on several sites, and cells expressing a non-phosphorylatable Ssk2 mutant are partially defective for feedback regulation and proper control of basal Hog1 activity. Together, our data suggest that Hog1 activity is controlled by intertwined regulatory mechanisms operating with varying kinetics, which together tune the Hog1 response to balance basal Hog1 activity and its steady-state level after adaptation to high osmolarity.

A Cellular System for Spatial Signal Decoding in Chemical Gradients

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.

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.

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.

A rapid and effective vignetting correction for quantitative microscopy

We describe a novel and versatile algorithm for vignetting correction and demonstrate its usefulness for quantitative microscopy.

Temporal quantification of MAPK induced expression in single yeast cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

tRNA tKUUU, tQUUG, and tEUUC wobble position modifications fine-tune protein translation by promoting ribosome A-site binding

tRNA modifications are crucial to ensure translation efficiency and fidelity. In eukaryotes, the URM1 and ELP pathways increase cellular resistance to various stress conditions, such as nutrient starvation and oxidative agents, by promoting thiolation and methoxycarbonylmethylation, respectively, of the wobble uridine of cytoplasmic (tK(UUU)), (tQ(UUG)), and (tE(UUC)). Although in vitro experiments have implicated these tRNA modifications in modulating wobbling capacity and translation efficiency, their exact in vivo biological roles remain largely unexplored. Using a combination of quantitative proteomics and codon-specific translation reporters, we find that translation of a specific gene subset enriched for AAA, CAA, and GAA codons is impaired in the absence of URM1- and ELP-dependent tRNA modifications. Moreover, in vitro experiments using native tRNAs demonstrate that both modifications enhance binding of tK(UUU) to the ribosomal A-site. Taken together, our data suggest that tRNA thiolation and methoxycarbonylmethylation regulate translation of genes with specific codon content.

An algorithm to automate yeast segmentation and tracking

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.