Tunable signal processing through modular control of transcription factor translocation

HMGB1: A New Target for Ischemic Stroke and Hemorrhagic Transformation

Stroke in China is distinguished by its high rates of morbidity, recurrence, disability, and mortality. The ultra-early administration of rtPA is essential for restoring perfusion in acute ischemic stroke, though it concurrently elevates the risk of hemorrhagic transformation. High-mobility group box 1 (HMGB1) emerges as a pivotal player in neuroinflammation after brain ischemia and ischemia-reperfusion. Released passively by necrotic cells and actively secreted, including direct secretion of HMGB1 into the extracellular space and packaging of HMGB1 into intracellular vesicles by immune cells, glial cells, platelets, and endothelial cells, HMGB1 represents a prototypical damage-associated molecular pattern (DAMP). It is intricately involved in the pathogenesis of atherosclerosis, thromboembolism, and detrimental inflammation during the early phases of ischemic stroke. Moreover, HMGB1 significantly contributes to neurovascular remodeling and functional recovery in later stages. Significantly, HMGB1 mediates hemorrhagic transformation by facilitating neuroinflammation, directly compromising the integrity of the blood-brain barrier, and enhancing MMP9 secretion through its interaction with rtPA. As a systemic inflammatory factor, HMGB1 is also implicated in post-stroke depression and an elevated risk of stroke-associated pneumonia. The role of HMGB1 extends to influencing the pathogenesis of ischemia by polarizing various subtypes of immune and glial cells. This includes mediating excitotoxicity due to excitatory amino acids, autophagy, MMP9 release, NET formation, and autocrine trophic pathways. Given its multifaceted role, HMGB1 is recognized as a crucial therapeutic target and prognostic marker for ischemic stroke and hemorrhagic transformation. In this review, we summarize the structure and redox properties, secretion and pathways, regulation of immune cell activity, the role of pathophysiological mechanisms in stroke, and hemorrhage transformation for HMGB1, which will pave the way for developing new neuroprotective drugs, reduction of post-stroke neuroinflammation, and expansion of thrombolysis time window.

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle

The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical reconstructions from partial observations of cellular states. Here we show that complete microbial life cycles can be directly and continuously studied by combining microfluidic culturing, life cycle stage-specific segmentation of micrographs, and a novel cell tracking algorithm, FIEST, based on deep learning video frame interpolation. As proof of principle, we quantitatively imaged and compared cell growth and the activity state of the cell division kinase, Cdk1, across the life cycle of Saccharomyces cerevisiae for up to three sexually reproducing generations. Our analysis of S. cerevisiae's life cycle provided the following new insights: 1) the accumulation of cell cycle regulators, such as Whi5, is tailored to each life cycle stage; 2) cell growth always preceded exit from nonproliferative states in our conditions; 3) the temporal coordination of meiotic events is the same across sexually reproducing populations when each generation is exposed to same conditions; 4) information such as cell size and morphology resets after each sexual reproduction cycle. Image processing and tracking algorithms are available as the Python package Yeastvision, which could be used study pathogens such as Candida glabrata, Cryptococcus neoformans, Colletotrichum acutatum, and other unicellular systems.

Collective oscillatory signaling in Dictyostelium discoideum acts as a developmental timer initiated by weak coupling of a noisy pulsatile signal

Oscillatory phenomena play widespread roles in the control of biological systems. In D. discoideum, oscillatory cyclic adenosine monophosphate (cAMP) signaling drives collective behavior and induces a temporal developmental gene expression program. How collective cAMP oscillations emerge or how they encode temporal transcriptional information is still poorly understood. To address this, we identified a transcription factor required for the initiation of collective behavior. Hbx5 activity is cAMP dependent and provides a sensitive single-cell readout for cAMP signaling. Extensive stochastic pulsatile cAMP signaling is found to precede collective oscillations. Stochastic signaling induces Hbx5-dependent transcriptional feedback, which enhances signal sensitivity and cell-cell coupling. This results in the emergence of synchronized collective oscillations, which subsequently activates the GtaC transcription factor and triggers shifts in developmental gene expression. Our results suggest this temporal coordination is encoded by changes in the amplitude of cAMP oscillations and differential sensitivity of these transcription factors to the cAMP-regulated kinase ErkB.

Cpeb4-mediated Dclk2 promotes neuronal pyroptosis induced by chronic cerebral ischemia through phosphorylation of Ehf

Chronic cerebral ischemia (CCI) is a clinical syndrome characterised by brain dysfunction due to decreased chronic cerebral perfusion. CCI initiates several inflammatory pathways, including pyroptosis. RNA-binding proteins (RBPs) play important roles in CCI. This study aimed to explore whether the interaction between RBP-Cpeb4 and Dclk2 affected Ehf phosphorylation to regulate neuronal pyroptosis. HT22 cells and mice were used to construct oxygen glucose deprivation (OGD)/CCI models. We found that Cpeb4 and Dclk2 were upregulated in OGD-treated HT22 cells and CCI-induced hippocampal CA1 tissues. Cpeb4 upregulated Dclk2 expression by increasing Dclk2 mRNA stability. Knockdown of Cpeb4 or Dclk2 inhibited neuronal pyroptosis in OGD-treated HT22 cells and CCI-induced hippocampal CA1 tissues. By binding to the promoter regions of Caspase1 and Caspase3, the transcription factor Ehf reduced their promoter activities and inhibited the transcription. Dclk2 phosphorylated Ehf and changed its nucleoplasmic distribution, resulting in the exit of p-Ehf from the nucleus and decreased Ehf levels. It promoted the expression of Caspase1 and Caspase3 and stimulated neuronal pyroptosis of HT22 cells induced by OGD. Cpeb4/Dclk2/Ehf pathway plays an important role in the regulation of cerebral ischemia-induced neuronal pyroptosis.

A novel peptide encoded by circ-SLC9A6 promotes lipid dyshomeostasis through the regulation of H4K16ac-mediated CD36 transcription in NAFLD

BACKGROUND

As the leading cause of end-stage liver disease, nonalcoholic fatty liver disease (NAFLD) is mainly induced by lipid dyshomeostasis. The translation of endogenous circular RNAs (circRNAs) is closely related to the progression of various diseases, but the involvement of circRNAs in NAFLD has not been determined.

METHODS

Combined high-throughput circRNA profiles were used to identify circRNAs with translational potential. The underlying molecular mechanisms were investigated by RNA sequencing, pull-down/MS and site-specific mutagenesis.

RESULTS

In this study, we focused on circ-SLC9A6, an abnormally highly expressed circRNA in human and mouse liver tissue during NAFLD development that exacerbates metabolic dyshomeostasis in hepatocytes by encoding a novel peptide called SLC9A6-126aa in vivo and in vitro. YTHDF2-mediated degradation of m6A-modified circ-SLC9A6 was found to be essential for the regulation of SLC9A6-126aa expression. We further found that the phosphorylation of SLC9A6-126aa by AKT was crucial for its cytoplasmic localization and the maintenance of physiological homeostasis, whereas high-fat stress induced substantial translocation of unphosphorylated SLC9A6-126aa to the nucleus, resulting in a vicious cycle of lipid metabolic dysfunction. Nuclear SLC9A6-126aa promotes transcriptional activation of the target gene CD36 and enhances its occupancy of the CD36 promoter locus by regulating MOF-mediated histone H4K16 acetylation. Hepatic CD36 depletion significantly ameliorated hyperactivated MAPK signalling and lipid disturbance in SLC9A6-126aa transgenic mice. Clinically, increasing levels of SLC9A6-126aa were observed during NAFLD progression and were found to be positively correlated with the CD36 and MAPK cascades.

CONCLUSION

This study revealed the role of circ-SLC9A6-derived SLC9A6-126aa in the epigenetic modification-mediated regulation of lipid metabolism. Our findings may provide promising therapeutic targets for NAFLD and new insights into the pathological mechanisms of metabolic diseases.

HIGHLIGHTS

Under normal circumstances, driven by m6A modification, YTHDF2 directly recognizes and degrades circ-SLC9A6, thereby inhibiting the translation of SLC9A6-126aa. Additionally, AKT1 phosphorylates and inhibits the nuclear translocation of SLC9A6-126aa. In NAFLD, lipid overload leads to YTHDF2 and AKT1 deficiency, ultimately increasing the expression and nuclear import of SLC9A6-126aa. Nuclear SLC9A6-126aa binds directly to the CD36 promoter and initiates CD36 transcription, which induces lipid dyshomeostasis.

On Effect of Chloroform on Electrical Activity of Proteinoids

Proteinoids, or thermal proteins, produce hollow microspheres in aqueous solutions. Ensembles of the microspheres produce endogenous spikes of electrical activity, similar to that of neurons. To make the first step toward the evaluation of the mechanisms of such electrical behaviour, we decided to expose proteinoids to chloroform. We found that while chloroform does not inhibit the electrical oscillations of proteinoids, it causes substantial changes in the patterns of electrical activity. Namely, incremental chloroform exposure strongly affects proteinoid microsphere electrical activity across multiple metrics. As chloroform levels rise, the spike potential drops from 0.9 mV under control conditions to 0.1 mV at 25 mg/mL. This progressive spike potential decrease suggests chloroform suppresses proteinoid electrical activity. The time between spikes, the interspike period, follows a similar pattern. Minimal chloroform exposure does not change the average interspike period, while higher exposures do. It drops from 23.2 min under control experiments to 3.8 min at 25 mg/mL chloroform, indicating increased frequency of the electrical activity. These findings might lead to a deeper understanding of the electrical activity of proteinoids and their potential application in the domain of bioelectronics.

Live-cell fluorescence imaging and optogenetic control of PKA kinase activity in fission yeast Schizosaccharomyces pombe

The cAMP-PKA signaling pathway plays a crucial role in sensing and responding to nutrient availability in the fission yeast Schizosaccharomyces pombe. This pathway monitors external glucose levels to control cell growth and sexual differentiation. However, the temporal dynamics of the cAMP-PKA pathway in response to external stimuli remains unclear mainly due to the lack of tools to quantitatively visualize the activity of the pathway. Here, we report the development of the kinase translocation reporter (KTR)-based biosensor spPKA-KTR1.0, which allows us to measure the dynamics of PKA activity in fission yeast cells. The spPKA-KTR1.0 is derived from the transcription factor Rst2, which translocates from the nucleus to the cytoplasm upon PKA activation. We found that spPKA-KTR1.0 translocates between the nucleus and cytoplasm in a cAMP-PKA pathway-dependent manner, indicating that the spPKA-KTR1.0 is a reliable indicator of the PKA activity in fission yeast cells. In addition, we implemented a system that simultaneously visualizes and manipulates the cAMP-PKA signaling dynamics by introducing bPAC, a photoactivatable adenylate cyclase, in combination with spPKA-KTR1.0. This system offers an opportunity for investigating the role of the signaling dynamics of the cAMP-PKA pathway in fission yeast cells with higher temporal resolution.

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle

The life cycle of biomedical and agriculturally relevant eukaryotic microorganisms involves complex transitions between proliferative and non-proliferative states such as dormancy, mating, meiosis, and cell division. New drugs, pesticides, and vaccines can be created by targeting specific life cycle stages of parasites and pathogens. However, defining the structure of a microbial life cycle often relies on partial observations that are theoretically assembled in an ideal life cycle path. To create a more quantitative approach to studying complete eukaryotic life cycles, we generated a deep learning-driven imaging framework to track microorganisms across sexually reproducing generations. Our approach combines microfluidic culturing, life cycle stage-specific segmentation of microscopy images using convolutional neural networks, and a novel cell tracking algorithm, FIEST, based on enhancing the overlap of single cell masks in consecutive images through deep learning video frame interpolation. As proof of principle, we used this approach to quantitatively image and compare cell growth and cell cycle regulation across the sexual life cycle of Saccharomyces cerevisiae. We developed a fluorescent reporter system based on a fluorescently labeled Whi5 protein, the yeast analog of mammalian Rb, and a new High-Cdk1 activity sensor, LiCHI, designed to report during DNA replication, mitosis, meiotic homologous recombination, meiosis I, and meiosis II. We found that cell growth preceded the exit from non-proliferative states such as mitotic G1, pre-meiotic G1, and the G0 spore state during germination. A decrease in the total cell concentration of Whi5 characterized the exit from non-proliferative states, which is consistent with a Whi5 dilution model. The nuclear accumulation of Whi5 was developmentally regulated, being at its highest during meiotic exit and spore formation. The temporal coordination of cell division and growth was not significantly different across three sexually reproducing generations. Our framework could be used to quantitatively characterize other single-cell eukaryotic life cycles that remain incompletely described. An off-the-shelf user interface Yeastvision provides free access to our image processing and single-cell tracking algorithms.

Transcription factor localization dynamics and DNA binding drive distinct promoter interpretations

Environmental information may be encoded in the temporal dynamics of transcription factor (TF) activation and subsequently decoded by gene promoters to enact stimulus-specific gene expression programs. Previous studies of this behavior focused on the encoding and decoding of information in TF nuclear localization dynamics, yet cells control the activity of TFs in myriad ways, including by regulating their ability to bind DNA. Here, we use light-controlled mutants of the yeast TF Msn2 as a model system to investigate how promoter decoding of TF localization dynamics is affected by changes in the ability of the TF to bind DNA. We find that yeast promoters directly decode the light-controlled localization dynamics of Msn2 and that the effects of changing Msn2 affinity on that decoding behavior are highly promoter dependent, illustrating how cells could regulate TF localization dynamics and DNA binding in concert for improved control of gene expression.

Endogenous Enzyme-Operated Spherical Nucleic Acids for Cell-Selective Protein Capture and Localization Regulation

Precise regulation of protein activity and localization in cancer cells is crucial to dissect the function of the protein-involved cellular network in tumorigenesis, but there is a lack of suitable methodology. Here we report the design of enzyme-operated spherical nucleic acids (E-SNAs) for manipulation of the nucleocytoplasmic translocation of proteins with cancer-cell selectivity. The E-SNAs are constructed by programmable engineering of aptamer-based modules bearing enzyme-responsive units in predesigned sites and further combination with SNA nanotechnology. We demonstrate that E-SNAs are able to regulate cytoplasmic-to-nuclear shuttling of RelA protein efficiently and specifically in tumor cells, while they remain inactive in normal cells due to insufficient enzyme expression. We further confirmed the generality of this strategy by investigating the enzyme-modulated inhibition/activation of thrombin activity by varying the aptamer-based design.

Modulation of transcription factor dynamics allows versatile information transmission

Cells detect changes in their environment and generate responses, often involving changes in gene expression. In this paper we use information theory and a simple transcription model to analyze whether the resulting gene expression serves to identify extracellular stimuli and assess their intensity when they are encoded in the amplitude, duration or frequency of pulses of a transcription factor's nuclear concentration (or activation state). We find, for all cases, that about three ranges of input strengths can be distinguished and that maximum information transmission occurs for fast and high activation threshold promoters. The three input modulation modes differ in the sensitivity to changes in the promoters parameters. Frequency modulation is the most sensitive and duration modulation, the least. This is key for signal identification: there are promoter parameters that yield a relatively high information transmission for duration or amplitude modulation and a much smaller value for frequency modulation. The reverse situation cannot be found with a single promoter transcription model. Thus, pulses of transcription factors can selectively activate the "frequency-tuned" promoter while prolonged nuclear accumulation would activate promoters of all three modes simultaneously. Frequency modulation is therefore highly selective and better suited than the other encoding modes for signal identification without requiring other mediators of the transduction process.

Research on the Influence of Coil LC Parallel Resonance on Detection Effect of Inductive Wear Debris Sensor

The coil structure of the inductive wear debris sensor plays a significant role in the effect of wear debris detection. According to the characteristics of LC parallel resonance, the capacitor and coil are connected in parallel to make sensor coils in the LC parallel resonance state, which is beneficial to improve the ability to detect wear particles. In this paper, the mathematical model of output-induced electromotance of the detection coil is established to analyze the influence of the structure on the detection sensitivity and enhance the sensor's current rate of change to the disturbance magnetic field, which is essential to resist noise interference. Based on the coherent demodulation principle, the AD630 lock-in amplifier is applied to the test platform to amplify and identify weak signals. In addition, experiments are designed to test the output signals of debris under the condition of different original output voltages of the sensor with a parallel structure. Meanwhile, the near-resonance state of the detection coil with LC parallel circuit is tested by output signal information. Results show that the sensor detection sensitivity will be effectively improved with the LC parallel coil structure. For the sensor structure parameters designed in this paper, the optimal raw output amplification voltage for abrasive particle detection is 4.49 V. The detection performance of ferromagnetic particles and non-ferromagnetic particles is tested under this condition, realizing the detection ability of 103.33 μm ferromagnetic abrasive particles and 320.74 μm non-ferromagnetic abrasive particles.

Fungi-on-a-Chip: microfluidic platforms for single-cell studies on fungi

This review highlights new advances in the emerging field of 'Fungi-on-a-Chip' microfluidics for single-cell studies on fungi and discusses several future frontiers, where we envisage microfluidic technology development to be instrumental in aiding our understanding of fungal biology. Fungi, with their enormous diversity, bear essential roles both in nature and our everyday lives. They inhabit a range of ecosystems, such as soil, where they are involved in organic matter degradation and bioremediation processes. More recently, fungi have been recognized as key components of the microbiome in other eukaryotes, such as humans, where they play a fundamental role not only in human pathogenesis, but also likely as commensals. In the food sector, fungi are used either directly or as fermenting agents and are often key players in the biotechnological industry, where they are responsible for the production of both bulk chemicals and antibiotics. Although the macroscopic fruiting bodies are immediately recognizable by most observers, the structure, function, and interactions of fungi with other microbes at the microscopic scale still remain largely hidden. Herein, we shed light on new advances in the emerging field of Fungi-on-a-Chip microfluidic technologies for single-cell studies on fungi. We discuss the development and application of microfluidic tools in the fields of medicine and biotechnology, as well as in-depth biological studies having significance for ecology and general natural processes. Finally, a future perspective is provided, highlighting new frontiers in which microfluidic technology can benefit this field.

Proteomic and functional analyses of the periodic membrane skeleton in neurons

Actin, spectrin, and associated molecules form a membrane-associated periodic skeleton (MPS) in neurons. The molecular composition and functions of the MPS remain incompletely understood. Here, using co-immunoprecipitation and mass spectrometry, we identified hundreds of potential candidate MPS-interacting proteins that span diverse functional categories. We examined representative proteins in several of these categories using super-resolution imaging, including previously unknown MPS structural components, as well as motor proteins, cell adhesion molecules, ion channels, and signaling proteins, and observed periodic distributions characteristic of the MPS along the neurites for ~20 proteins. Genetic perturbations of the MPS and its interacting proteins further suggested functional roles of the MPS in axon-axon and axon-dendrite interactions and in axon diameter regulation, and implicated the involvement of MPS interactions with cell adhesion molecules and non-muscle myosin in these roles. These results provide insights into the interactome of the MPS and suggest previously unknown functions of the MPS in neurons.

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.

A novel AMPK activator shows therapeutic potential in hepatocellular carcinoma by suppressing HIF1α-mediated aerobic glycolysis

Hepatocellular carcinoma (HCC) is characterized by rapid growth, early vascular invasion, and high metastasis. Currently available US Food and Drug Administration (FDA)-approved drugs show low therapeutic efficacy, limiting HCC treatment to chemotherapy. We designed and synthesized a novel small molecule, SCT-1015, that allosterically activated adenosine monophosphate-activated protein kinase (AMPK) to suppress the aerobic glycolysis in HCC. SCT-1015 was shown to bind the AMPK α and β-subunit interface, thereby exposing the kinase α domain to the upstream kinases, resulting in the increased AMPK activity. SCT-1015 dramatically reduced HCC cell growth in vitro and tumor growth in vivo. We further found that AMPK formed protein complexes with hypoxia-inducible factor 1-alpha (HIF1α) and that SCT-1015-activated AMPK promoted hydroxylation of HIF1α (402P and 564P), resulting in HIF1α degradation by the ubiquitin-proteasome system. With declined HIF1α abundance, many glycolysis-related enzymes were downregulated, suppressing aerobic glycolysis, and promoting oxidative phosphorylation. These results indicated that SCT-1015 channeled HCC cells into an unfavorable metabolic status. Overall, we reported SCT-1015 as a direct activator of AMPK signaling that held therapeutic potential in HCC.

Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression

Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.

Cell cycle-independent integration of stress signals by Xbp1 promotes Non-G1/G0 quiescence entry

Cellular quiescence is a nonproliferative state required for cell survival under stress and during development. In most quiescent cells, proliferation is stopped in a reversible state of low Cdk1 kinase activity; in many organisms, however, quiescent states with high-Cdk1 activity can also be established through still uncharacterized stress or developmental mechanisms. Here, we used a microfluidics approach coupled to phenotypic classification by machine learning to identify stress pathways associated with starvation-triggered high-Cdk1 quiescent states in Saccharomyces cerevisiae. We found that low- and high-Cdk1 quiescent states shared a core of stress-associated processes, such as autophagy, protein aggregation, and mitochondrial up-regulation, but differed in the nuclear accumulation of the stress transcription factors Xbp1, Gln3, and Sfp1. The decision between low- or high-Cdk1 quiescence was controlled by cell cycle-independent accumulation of Xbp1, which acted as a time-delayed integrator of the duration of stress stimuli. Our results show how cell cycle-independent stress-activated factors promote cellular quiescence outside G1/G0.

Mapping the dynamic transfer functions of eukaryotic gene regulation

Biological information can be encoded within the dynamics of signaling components, which has been implicated in a broad range of physiological processes including stress response, oncogenesis, and stem cell differentiation. To study the complexity of information transfer across the eukaryotic promoter, we screened 119 dynamic conditions-modulating the pulse frequency, amplitude, and pulse width of light-regulating the binding of an epigenome editor to a fluorescent reporter. This system revealed tunable gene expression and filtering behaviors and provided a quantification of the limit to the amount of information that can be reliably transferred across a single promoter as ∼1.7 bits. Using a library of over 100 orthogonal chromatin regulators, we further determined that chromatin state could be used to tune mutual information and expression levels, as well as completely alter the input-output transfer function of the promoter. This system unlocks the information-rich content of eukaryotic gene regulation.

Establishment of a fluorescent reporter of RNA-polymerase II activity to identify dormant cells

Dormancy, a reversible quiescent cellular state characterized by greatly reduced metabolic activity, protects from genetic damage, prolongs survival and is crucial for tissue homeostasis and cellular response to injury or transplantation. Dormant cells have been characterized in many tissues, but their identification, isolation and characterization irrespective of tissue of origin remains elusive. Here, we develop a live cell ratiometric fluorescent Optical Stem Cell Activity Reporter (OSCAR) based on the observation that phosphorylation of RNA Polymerase II (RNApII), a hallmark of active mRNA transcription elongation, is largely absent in dormant stem cells from multiple lineages. Using the small intestinal crypt as a model, OSCAR reveals in real time the dynamics of dormancy induction and cellular differentiation in vitro, and allows the identification and isolation of several populations of transcriptionally diverse OSCAR^high and OSCAR^low intestinal epithelial cell states in vivo. In particular, this reporter is able to identify a dormant OSCAR^high cell population in the small intestine. OSCAR therefore provides a tool for a better understanding of dormant stem cell biology.

The identification and characterisation of dormant cells is currently difficult. Here the authors report Optical Stem Cell Activity Reporter (OSCAR) to assess RNA polymerase II activity and identify dormant cell populations in intestinal epithelial cells in vivo.

Yeast cell fate control by temporal redundancy modulation of transcription factor paralogs

Recent single-cell studies have revealed that yeast stress response involves transcription factors that are activated in pulses. However, it remains unclear whether and how these dynamic transcription factors temporally interact to regulate stress survival. Here we show that budding yeast cells can exploit the temporal relationship between paralogous general stress regulators, Msn2 and Msn4, during stress response. We find that individual pulses of Msn2 and Msn4 are largely redundant, and cells can enhance the expression of their shared targets by increasing their temporal divergence. Thus, functional redundancy between these two paralogs is modulated in a dynamic manner to confer fitness advantages for yeast cells, which might feed back to promote the preservation of their redundancy. This evolutionary implication is supported by evidence from Msn2/Msn4 orthologs and analyses of other transcription factor paralogs. Together, we show a cell fate control mechanism through temporal redundancy modulation in yeast, which may represent an evolutionarily important strategy for maintaining functional redundancy between gene duplicates.

A platform for post-translational spatiotemporal control of cellular proteins

Mammalian cells process information through coordinated spatiotemporal regulation of proteins. Engineering cellular networks thus relies on efficient tools for regulating protein levels in specific subcellular compartments. To address the need to manipulate the extent and dynamics of protein localization, we developed a platform technology for the target-specific control of protein destination. This platform is based on bifunctional molecules comprising a target-specific nanobody and universal sequences determining target subcellular localization or degradation rate. We demonstrate that nanobody-mediated localization depends on the expression level of the target and the nanobody, and the extent of target subcellular localization can be regulated by combining multiple target-specific nanobodies with distinct localization or degradation sequences. We also show that this platform for nanobody-mediated target localization and degradation can be regulated transcriptionally and integrated within orthogonal genetic circuits to achieve the desired temporal control over spatial regulation of target proteins. The platform reported in this study provides an innovative tool to control protein subcellular localization, which will be useful to investigate protein function and regulate large synthetic gene circuits.

Capturing and Understanding the Dynamics and Heterogeneity of Gene Expression in the Living Cell

The regulation of gene expression is a fundamental process enabling cells to respond to internal and external stimuli or to execute developmental programs. Changes in gene expression are highly dynamic and depend on many intrinsic and extrinsic factors. In this review, we highlight the dynamic nature of transient gene expression changes to better understand cell physiology and development in general. We will start by comparing recent in vivo procedures to capture gene expression in real time. Intrinsic factors modulating gene expression dynamics will then be discussed, focusing on chromatin modifications. Furthermore, we will dissect how cell physiology or age impacts on dynamic gene regulation and especially discuss molecular insights into acquired transcriptional memory. Finally, this review will give an update on the mechanisms of heterogeneous gene expression among genetically identical individual cells. We will mainly focus on state-of-the-art developments in the yeast model but also cover higher eukaryotic systems.

Cell-cycle-gated feedback control mediates desensitization to interferon stimulation

Cells use molecular circuits to interpret and respond to extracellular cues, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I interferon (IFN)-responsive regulatory network operates in single human cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1/early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback loops, enabling duration-dependent desensitization to repetitive stimulations.

Optogenetic Control Reveals Differential Promoter Interpretation of Transcription Factor Nuclear Translocation Dynamics

Gene expression is thought to be affected not only by the concentration of transcription factors (TFs) but also the dynamics of their nuclear translocation. Testing this hypothesis requires direct control of TF dynamics. Here, we engineer CLASP, an optogenetic tool for rapid and tunable translocation of a TF of interest. Using CLASP fused to Crz1, we observe that, for the same integrated concentration of nuclear TF over time, changing input dynamics changes target gene expression: pulsatile inputs yield higher expression than continuous inputs, or vice versa, depending on the target gene. Computational modeling reveals that a dose-response saturating at low TF input can yield higher gene expression for pulsatile versus continuous input, and that multi-state promoter activation can yield the opposite behavior. Our integrated tool development and modeling approach characterize promoter responses to Crz1 nuclear translocation dynamics, extracting quantitative features that may help explain the differential expression of target genes.

CLASP is a modular optogenetic strategy to control the nuclear localization of transcription factors (TFs) and elicit gene expression from their cognate promoters. CLASP control of Crz1 nuclear localization, coupled with computational modeling, revealed how promoters can differentially decode dynamic transcription factor signals. The integrated strategy of CLASP development and modeling presents a generalized approach to causally investigate the transcriptional consequences of dynamic TF nuclear shuttling.

A protein kinase A-regulated network encodes short- and long-lived cellular memories

Cells can store memories of prior experiences to modulate their responses to subsequent stresses, as seen for the protein kinase A (PKA)-mediated general stress response in yeast, which is required for resistance against future stressful conditions. Using microfluidics and time-lapse microscopy, we quantitatively analyzed how the cellular memory of stress adaptation is encoded in single yeast cells. We found that cellular memory was biphasic. Short-lived memory was mediated by trehalose synthase and trehalose metabolism. Long-lived memory was mediated by PKA-regulated stress-responsive transcription factors and cytoplasmic messenger ribonucleoprotein granules. Short- and long-lived memory could be selectively induced by different priming input dynamics. Computational modeling revealed how the PKA-mediated regulatory network could encode previous stimuli into memories with distinct dynamics. This biphasic memory-encoding scheme might represent a general strategy to prepare for future challenges in rapidly changing environments.

Genome-scale transcriptional dynamics and environmental biosensing

Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisely react to their environment. The importance of complex feedback in controlling the real-time response to external stimuli has led to a need for the next generation of cell-based technologies that enable both the collection and analysis of high-throughput temporal data. Toward this end, we have developed a microfluidic platform capable of monitoring temporal gene expression from over 2,000 promoters. By coupling the "Dynomics" platform with deep neural network (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learning can be harnessed to assess patterns in transcriptional data on a genome scale and identify which genes contribute to these patterns. Furthermore, we demonstrate the utility of the Dynomics platform as a field-deployable real-time biosensor through prediction of the presence of heavy metals in urban water and mine spill samples, based on the the dynamic transcription profiles of 1,807 unique Escherichia coli promoters.

Resolving noise-control conflict by gene duplication

Gene duplication promotes adaptive evolution in two main ways: allowing one duplicate to evolve a new function and splitting ancestral functions between the duplicates. The second scenario may resolve adaptive conflicts that can rise when one gene performs different functions. In an apparent departure from both scenarios, low-expressing transcription factor (TF) duplicates commonly bind to the same DNA motifs and act in overlapping conditions. To examine for possible benefits of this apparent redundancy, we examined the Msn2 and Msn4 duplicates in budding yeast. We show that Msn2,4 function as one unit by inducing the same set of target genes in overlapping conditions. Yet, the two-factor composition allows this unit's expression to be both environmentally responsive and with low noise, resolving an adaptive conflict that limits expression of single genes. We propose that duplication can provide adaptive benefit through cooperation rather than functional divergence, allowing two-factor dynamics with beneficial properties that cannot be achieved by a single gene.

Advances in quantitative biology methods for studying replicative aging in Saccharomyces cerevisiae

Aging is a complex, yet pervasive phenomenon in biology. As human cells steadily succumb to the deteriorating effects of aging, so too comes a host of age-related ailments such as neurodegenerative disorders, cardiovascular disease and cancer. Therefore, elucidation of the molecular networks that drive aging is of paramount importance to human health. Progress toward this goal has been aided by studies from simple model organisms such as Saccharomyces cerevisiae. While work in budding yeast has already revealed much about the basic biology of aging as well as a number of evolutionarily conserved pathways involved in this process, recent technological advances are poised to greatly expand our knowledge of aging in this simple eukaryote. Here, we review the latest developments in microfluidics, single-cell analysis and high-throughput technologies for studying single-cell replicative aging in S. cerevisiae. We detail the challenges each of these methods addresses as well as the unique insights into aging that each has provided. We conclude with a discussion of potential future applications of these techniques as well as the importance of single-cell dynamics and quantitative biology approaches for understanding cell aging.

p53 pulse modulation differentially regulates target gene promoters to regulate cell fate decisions

The p53 tumor suppressor regulates distinct responses to cellular stresses. Although different stresses generate different p53 dynamics, the mechanisms by which cells decode p53 dynamics to differentially regulate target genes are not well understood. Here, we determined in individual cells how canonical p53 target gene promoters vary in responsiveness to features of p53 dynamics. Employing a chemical perturbation approach, we independently modulated p53 pulse amplitude, duration, or frequency, and we then monitored p53 levels and target promoter activation in individual cells. We identified distinct signal processing features-thresholding in response to amplitude modulation, a refractory period in response to duration modulation, and dynamic filtering in response to frequency modulation. We then showed that the signal processing features not only affect p53 target promoter activation, they also affect p53 regulation and downstream cellular functions. Our study shows how different promoters can differentially decode features of p53 dynamics to generate distinct responses, providing insight into how perturbing p53 dynamics can be used to generate distinct cell fates.

A practical guide to intelligent image-activated cell sorting

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software-hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.

Communication codes in developmental signaling pathways

A handful of core intercellular signaling pathways play pivotal roles in a broad variety of developmental processes. It has remained puzzling how so few pathways can provide the precision and specificity of cell-cell communication required for multicellular development. Solving this requires us to quantitatively understand how developmentally relevant signaling information is actively sensed, transformed and spatially distributed by signaling pathways. Recently, single cell analysis and cell-based reconstitution, among other approaches, have begun to reveal the 'communication codes' through which information is represented in the identities, concentrations, combinations and dynamics of extracellular ligands. They have also revealed how signaling pathways decipher these features and control the spatial distribution of signaling in multicellular contexts. Here, we review recent work reporting the discovery and analysis of communication codes and discuss their implications for diverse developmental processes.

Quantitative analysis of the yeast pheromone pathway

The pheromone response pathway of the yeast Saccharomyces cerevisiae is a well-established model for the study of G proteins and mitogen-activated protein kinase (MAPK) cascades. Our longstanding ability to combine sophisticated genetic approaches with established functional assays has provided a thorough understanding of signalling mechanisms and regulation. In this report, we compare new and established methods used to quantify pheromone-dependent MAPK phosphorylation, transcriptional induction, mating morphogenesis, and gradient tracking. These include both single-cell and population-based assays of activity. We describe several technical advances, provide example data for benchmark mutants, highlight important differences between newer and established methodologies, and compare the advantages and disadvantages of each as applied to the yeast model. Quantitative measurements of pathway activity have been used to develop mathematical models and reveal new regulatory mechanisms in yeast. It is our expectation that experimental and computational approaches developed in yeast may eventually be adapted to human systems biology and pharmacology.

Age-dependent deterioration of nuclear pore assembly in mitotic cells decreases transport dynamics

Nuclear transport is facilitated by the Nuclear Pore Complex (NPC) and is essential for life in eukaryotes. The NPC is a long-lived and exceptionally large structure. We asked whether NPC quality control is compromised in aging mitotic cells. Our images of single yeast cells during aging, show that the abundance of several NPC components and NPC assembly factors decreases. Additionally, the single-cell life histories reveal that cells that better maintain those components are longer lived. The presence of herniations at the nuclear envelope of aged cells suggests that misassembled NPCs are accumulated in aged cells. Aged cells show decreased dynamics of transcription factor shuttling and increased nuclear compartmentalization. These functional changes are likely caused by the presence of misassembled NPCs, as we find that two NPC assembly mutants show similar transport phenotypes as aged cells. We conclude that NPC interphase assembly is a major challenge for aging mitotic cells.

Signaling pathways in context

The last decade has seen a rise in the development of methods and models to analyze cellular networks on all levels. The applications of this knowledge are, however, often confined to specifics of the network in concrete conditions and leveraging it is hampered by the lack of information about this context and its implications on the system. While not all cellular networks have been deciphered yet, even for well-studied networks their versatility in different contexts is barely considered. Here, we focus on challenges and potentials when integrating signaling networks into their encompassing structures. We highlight three different consequences of this process: a) its fundamental importance for whole-cell and large-scale models, b) significant changes in contextual behavior imposed on entire systems by genetic variations, and c) species-specific conservation or divergence of signaling motifs can give important clues on how to handle cellular context. While important studies have been conducted on these topics to some extent, an increased focus on developing and exploiting solutions for integrative contextualization should turn out as a fruitful path for both theoretical and experimental research.

HMGB1 from Lampetra japonica promotes inflammatory activation in supraneural body cells

High mobility group box protein 1 (HMGB1) acts as a potent proinflammatory cytokine that involves in the pathogenesis of diverse inflammatory and infectious disorders. In previous study, we identified a homolog of HMGB1 in the Lampetra japonica(L-HMGB1), and further revealed that L-HMGB1 was able to induce the production of tumor necrosis factor-α (TNF-α) in activated human acute monocytic leukemia cells. However, the role of L-HMGB1 played in lamprey was unknown. Here, we found that L-HMGB1 was located in the cytoplasm of lamprey leukocytes and supraneural body (SB) cells. Importantly, we demonstrated that L-HMGB1 participated in activation of various key molecules in inflammation signaling pathway. LPS also promoted the release of L-HMGB1 from SB cells similar to Hu-HMGB1, and then extracellular L-HMGB1 in turn induced the release of cytokines. This study revealed that the synergistic action of LPS and L-HMGB1 played a crucial role in inflammation in lamprey. Our results suggested that lampreys used L-HMGB1 to activate their innate immunity for the purpose of pathogen defense.

Activation-induced deaminase (AID) localizes to the nucleus in brief pulses

Activation-induced deaminase (AID) converts C to U and 5-methyl-C to T. These mutagenic activities are critical to immunoglobulin (Ig) gene diversification and epigenetic reprogramming, but they must be tightly controlled to prevent compromising cell fitness. AID acts in the nucleus but localizes predominately to the cytoplasm. To address this apparent paradox, we have carried out time-lapse imaging of AID in single living B cells and fibroblasts. We demonstrate that AID enters the nucleus in brief (30 min) pulses, evident in about 10% of cells in the course of a single cell cycle (24 hr imaging). Pulses do not depend on AID catalytic activity, but they are coordinated with nuclear accumulation of P53. Pulsing may protect cells from pathologic consequences of excess exposure to AID, or enable AID to synchronize its activity with transcription of genes that are AID targets or with nuclear entry of factors that act at sites of AID-catalyzed DNA deamination to promote Ig gene diversification or epigenetic reprogramming.

Constructing network topologies for multiple signal-encoding functions

Background

Cells use signaling protein networks to sense their environment and mediate specific responses. Information about environmental stress is usually encoded in the dynamics of the signaling molecules, and qualitatively distinct dynamics of the same signaling molecule can lead to dramatically different cell fates. Exploring the design principles of networks with multiple signal-encoding functions is important for understanding how distinct dynamic patterns are shaped and integrated by real cellular networks, and for building cells with targeted sensing–response functions via synthetic biology.

Results

In this paper, we investigate multi-node enzymatic regulatory networks with three signal-encoding functions, i.e., dynamic responses of oscillation, transient activation, and sustained activation upon step stimulation by three different inducers, respectively. Taking into account competition effects of the substrates for the same enzyme in the enzymatic reactions, we searched for robust subnetworks for each signal-encoding function by three-node-network enumeration and then integrated the three subnetworks together via node-merging. The obtained tri-functional networks consisted of four to six nodes, and the core structures of these networks were hybrids of the motifs for the subfunctions.

Conclusions

The simplest but relatively robust tri-functional networks demonstrated that the three functions were compatible within a simple negative feedback loop. Depending on the network structure, the competition effects of the substrates for the same enzyme within the networks could promote or hamper the target functions, and can create implicit functional motifs. Overall, the networks we obtained could in principle be synthesized to construct dynamic control circuits with multiple target functions.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0676-5) contains supplementary material, which is available to authorized users.

Control of nongenetic heterogeneity in growth rate and stress tolerance of Saccharomyces cerevisiae by cyclic AMP-regulated transcription factors

Genetically identical cells exhibit extensive phenotypic variation even under constant and benign conditions. This so-called nongenetic heterogeneity has important clinical implications: within tumors and microbial infections, cells show nongenetic heterogeneity in growth rate and in susceptibility to drugs or stress. The budding yeast, Saccharomyces cerevisiae, shows a similar form of nongenetic heterogeneity in which growth rate correlates positively with susceptibility to acute heat stress at the single-cell level. Using genetic and chemical perturbations, combined with high-throughput single-cell assays of yeast growth and gene expression, we show here that heterogeneity in intracellular cyclic AMP (cAMP) levels acting through the conserved Ras/cAMP/protein kinase A (PKA) pathway and its target transcription factors, Msn2 and Msn4, underlies this nongenetic heterogeneity. Lower levels of cAMP correspond to slower growth, as shown by direct comparison of cAMP concentration in subpopulations enriched for slower vs. faster growing cells. Concordantly, an endogenous reporter of this pathway’s activity correlates with growth in individual cells. The paralogs Msn2 and Msn4 differ in their roles in nongenetic heterogeneity in a way that demonstrates slow growth and stress tolerance are not inevitably linked. Heterogeneity in growth rate requires each, whereas only Msn2 is required for heterogeneity in expression of Tsl1, a subunit of trehalose synthase that contributes to acute-stress tolerance. Perturbing nongenetic heterogeneity by mutating genes in this pathway, or by culturing wild-type cells with the cell-permeable cAMP analog 8-bromo-cAMP or the PKA inhibitor H89, significantly impacts survival of acute heat stress. Perturbations that increase intracellular cAMP levels reduce the slower-growing subpopulation and increase susceptibility to acute heat stress, whereas PKA inhibition slows growth and decreases susceptibility to acute heat stress. Loss of Msn2 reduces, but does not completely eliminate, the correlation in individual cells between growth rate and acute-stress survival, suggesting a major role for the Msn2 pathway in nongenetic heterogeneity but also a residual benefit of slow growth. Our results shed light on the genetic control of nongenetic heterogeneity and suggest a possible means of defeating bet-hedging pathogens or tumor cells by making them more uniformly susceptible to treatment.

Nongenetic heterogeneity exists when a trait differs among individuals that have identical genotypes and environments. A clonal population can maximize its long-term success in an uncertain environment by diversifying its phenotypes via nongenetic heterogeneity: the currently unfavored ones may become the favored ones when conditions change. Nongenetic heterogeneity has clinical relevance. For example, populations of tumor cells or infectious microbes show cell-to-cell differences in growth and in drug or stress tolerance. This heterogeneity hampers efficient treatment and can potentiate harmful evolution of a tumor or pathogen. We show that in budding yeast, heterogeneity in intracellular cyclic AMP levels acting through the conserved Ras/cAMP/protein kinase A (PKA) pathway and its target transcription factors, Msn2 and Msn4, underlies the nongenetic heterogeneity of both single-cell growth rate and acute heat-stress tolerance. Perturbations of this pathway significantly affect population survival upon acute heat stress. These results illuminate a mechanism of nongenetic heterogeneity and suggest the potential value of antitumor or antifungal treatment strategies that target nongenetic heterogeneity to render the tumor or pathogen population more uniformly susceptible to a second drug that aims to kill.

Active dendrites regulate the spatiotemporal spread of signaling microdomains

Microdomains that emerge from spatially constricted spread of biochemical signaling components play a central role in several neuronal computations. Although dendrites, endowed with several voltage-gated ion channels, form a prominent structural substrate for microdomain physiology, it is not known if these channels regulate the spatiotemporal spread of signaling microdomains. Here, we employed a multiscale, morphologically realistic, conductance-based model of the hippocampal pyramidal neuron that accounted for experimental details of electrical and calcium-dependent biochemical signaling. We activated synaptic N-Methyl-d-Aspartate receptors through theta-burst stimulation (TBS) or pairing (TBP) and assessed microdomain propagation along a signaling pathway that included calmodulin, calcium/calmodulin-dependent protein kinase II (CaMKII) and protein phosphatase 1. We found that the spatiotemporal spread of the TBS-evoked microdomain in phosphorylated CaMKII (pCaMKII) was amplified in comparison to that of the corresponding calcium microdomain. Next, we assessed the role of two dendritically expressed inactivating channels, one restorative (A-type potassium) and another regenerative (T-type calcium), by systematically varying their conductances. Whereas A-type potassium channels suppressed the spread of pCaMKII microdomains by altering the voltage response to TBS, T-type calcium channels enhanced this spread by modulating TBS-induced calcium influx without changing the voltage. Finally, we explored cross-dependencies of these channels with other model components, and demonstrated the heavy mutual interdependence of several biophysical and biochemical properties in regulating microdomains and their spread. Our conclusions unveil a pivotal role for dendritic voltage-gated ion channels in actively amplifying or suppressing biochemical signals and their spatiotemporal spread, with critical implications for clustered synaptic plasticity, robust information transfer and efficient neural coding.

The spatiotemporal spread of biochemical signals in neurons and other cells regulate signaling specificity, tuning of signal propagation, along with specificity and clustering of adaptive plasticity. Theoretical and experimental studies have demonstrated a critical role for cellular morphology and the topology of signaling networks in regulating this spread. In this study, we add a significantly complex dimension to this narrative by demonstrating that voltage-gated ion channels on the plasma membrane could actively amplify or suppress the strength and spread of downstream signaling components. Given the expression of different ion channels with wide-ranging heterogeneity in gating kinetics, localization and density, our results point to an increase in complexity of and degeneracy in signaling spread, and unveil a powerful mechanism for regulating biochemical-signaling pathways across different cell types.

Self-Amplifying Pulsatile Protein Dynamics without Positive Feedback

Many proteins exhibit dynamic activation patterns in the form of irregular pulses. Such behavior is typically attributed to a combination of positive and negative feedback loops in the underlying regulatory network. However, the presence of positive feedbacks is difficult to demonstrate unequivocally, raising the question of whether stochastic pulses can arise from negative feedback only. Here, we use the protein kinase A (PKA) system, a key regulator of the yeast pulsatile transcription factor Msn2, as a case example to show that irregular pulses of protein activity can arise from a negative feedback loop alone. Simplification to two variables reveals that a combination of zero-order ultrasensitivity, timescale separation between the activator and the repressor, and an effective delay in the feedback are sufficient to amplify a perturbation into a pulse. The same circuit topology can account for both activation and inactivation pulses, pointing toward a general mechanism of stochastic pulse generation.

A constitutive active allele of the transcription factor Msn2 mimicking low PKA activity dictates metabolic remodeling in yeast

In yeast, protein kinase A (PKA) adjusts transcriptional profiles, metabolic rates, and cell growth in accord with carbon source availability. PKA affects gene expression mostly via the transcription factors Msn2 and Msn4, two key regulators of the environmental stress response. Here we analyze the role of the PKA-Msn2 signaling module using an Msn2 allele that harbors serine-to-alanine substitutions at six functionally important PKA motifs (Msn2A6) . Expression of Msn2A6 mimics low PKA activity, entails a transcription profile similar to that of respiring cells, and prevents formation of colonies on glucose-containing medium. Furthermore, Msn2A6 leads to high oxygen consumption and hence high respiratory activity. Substantially increased intracellular concentrations of several carbon metabolites, such as trehalose, point to a metabolic adjustment similar to diauxic shift. This partial metabolic switch is the likely cause for the slow-growth phenotype in the presence of glucose. Consistently, Msn2A6 expression does not interfere with growth on ethanol and tolerated is to a limited degree in deletion mutant strains with a gene expression signature corresponding to nonfermentative growth. We propose that the lethality observed in mutants with hampered PKA activity resides in metabolic reprogramming that is initiated by Msn2 hyperactivity.

mTOR-dependent phosphorylation controls TFEB nuclear export

During starvation the transcriptional activation of catabolic processes is induced by the nuclear translocation and consequent activation of transcription factor EB (TFEB), a master modulator of autophagy and lysosomal biogenesis. However, how TFEB is inactivated upon nutrient refeeding is currently unknown. Here we show that TFEB subcellular localization is dynamically controlled by its continuous shuttling between the cytosol and the nucleus, with the nuclear export representing a limiting step. TFEB nuclear export is mediated by CRM1 and is modulated by nutrient availability via mTOR-dependent hierarchical multisite phosphorylation of serines S142 and S138, which are localized in proximity of a nuclear export signal (NES). Our data on TFEB nucleo-cytoplasmic shuttling suggest an unpredicted role of mTOR in nuclear export.

Distributed and dynamic intracellular organization of extracellular information

Although cells respond specifically to environments, how environmental identity is encoded intracellularly is not understood. Here, we study this organization of information in budding yeast by estimating the mutual information between environmental transitions and the dynamics of nuclear translocation for 10 transcription factors. Our method of estimation is general, scalable, and based on decoding from single cells. The dynamics of the transcription factors are necessary to encode the highest amounts of extracellular information, and we show that information is transduced through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can encode the nature of multiple stresses, but only if stress is high; specialists (Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly and for a wider range of magnitudes. In particular, Dot6 encodes almost as much information as Msn2, the master regulator of the environmental stress response. Each transcription factor reports differently, and it is only their collective behavior that distinguishes between multiple environmental states. Changes in the dynamics of the localization of transcription factors thus constitute a precise, distributed internal representation of extracellular change. We predict that such multidimensional representations are common in cellular decision-making.

An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis.

Network Motifs Capable of Decoding Transcription Factor Dynamics

Transcription factors (TFs) can encode the information of upstream signal in terms of its temporal activation dynamics. However, it remains unclear how different types of TF dynamics are decoded by downstream signalling networks. In this work, we studied all three-node transcriptional networks for their ability to distinguish two types of TF dynamics: amplitude modulation (AM), where the TF is activated with a constant amplitude, and frequency modulation (FM), where the TF activity displays an oscillatory behavior. We found two sets of network topologies: one set can differentially respond to AM TF signal but not to FM; the other set to FM signal but not to AM. Interestingly, there is little overlap between the two sets. We identified the prevalent topological features in each set and gave a mechanistic explanation as to why they can differentially respond to only one type of TF signal. We also found that some network topologies have a weak (not robust) ability to differentially respond to both AM and FM input signals by using different values of parameters for AM and FM cases. Our results provide a novel network mechanism for decoding different TF dynamics.

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

Genetically identical cells growing in the same environment can vary in their cellular state and behavior. Such heterogeneity may explain why some cells in an isogenic population can survive sudden severe environmental stress whereas other cells succumb. Cell-to-cell variation in gene expression has been linked to variable stress survival, but how and why transcript levels vary across the transcriptome in single cells is only beginning to emerge. Here, we used single-cell RNA sequencing (scRNA-seq) to measure cell-to-cell heterogeneity in the transcriptome of budding yeast (Saccharomyces cerevisiae). We find surprising patterns of variation across known sets of transcription factor targets, indicating that cells vary in their transcriptome profile both before and after stress exposure. scRNA-seq analysis combined with live-cell imaging of transcription factor activation dynamics revealed some cells in which the stress response was coordinately activated and other cells in which the traditional response was decoupled, suggesting unrecognized regulatory nuances that expand our understanding of stress response and survival.