Biofuel alternatives to ethanol: pumping the microbial well

Engineered microorganisms are currently used for the production of food products, pharmaceuticals, ethanol fuel and more. Even so, the enormous potential of this technology has yet to be fully exploited. The need for sustainable sources of transportation fuels has generated a tremendous interest in technologies that enable biofuel production. Decades of work have produced a considerable knowledge-base for the physiology and pathway engineering of microbes, making microbial engineering an ideal strategy for producing biofuel. Although ethanol currently dominates the biofuel market, some of its inherent physical properties make it a less than ideal product. To highlight additional options, we review advances in microbial engineering for the production of other potential fuel molecules, using a variety of biosynthetic pathways.     

Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices

Biological systems have evolved efficient sensing and decision‐making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non‐living biomolecular devices could offer promising avenues toward various real‐world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell‐like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof‐of‐concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.     

Dynamic Interaction of Spindles and Gamma Activity during Cortical Slow Oscillations and Its Modulation by Subcortical Afferents

Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations.     

Live visualization and quantification of pathway signaling with dual fluorescent and bioluminescent reporters

Despite their fundamental importance, the dynamics of signaling pathways in living cells remain challenging to study, due to a lack of non-invasive tools for temporal assessment of signal transduction in desired cell models. Here we report a dual-reporter strategy that enables researchers to monitor signal transduction in mammalian cells in real-time, both temporally and quantitatively. This is achieved by co-expressing green fluorescent protein and firefly luciferase in response to signaling stimuli. To display the versatility of this approach, we constructed and assessed eight unique signaling pathway reporters. We further validated the system by establishing stable NF-κB pathway reporter cell lines. Using these stable cell lines, we monitored the activity of NF-κB-mediated inflammatory pathway in real-time, both visually and quantitatively. Live visualization has the power to reveal individual cell responses and is compatible with single cell analysis, In addition, we provide evidence that this system is readily amenable to a high-throughput format. Together, our findings demonstrate the potential of the dual reporter system, which significantly improves the capacity to study signal transduction pathways in mammalian cells.     

Transient Responses to Rapid Changes in Mean and Variance in Spiking Models

The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode.     

Phenotypic Signatures Arising from Unbalanced Bacterial Growth

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.     

Two-component signal transduction pathways regulating growth and cell cycle progression in a bacterium: a system-level analysis

Two-component signal transduction systems, comprised of histidine kinases and their response regulator substrates, are the predominant means by which bacteria sense and respond to extracellular signals. These systems allow cells to adapt to prevailing conditions by modifying cellular physiology, including initiating programs of gene expression, catalyzing reactions, or modifying protein–protein interactions. These signaling pathways have also been demonstrated to play a role in coordinating bacterial cell cycle progression and development. Here we report a system-level investigation of two-component pathways in the model organism Caulobacter crescentus. First, by a comprehensive deletion analysis we show that at least 39 of the 106 two-component genes are required for cell cycle progression, growth, or morphogenesis. These include nine genes essential for growth or viability of the organism. We then use a systematic biochemical approach, called phosphotransfer profiling, to map the connectivity of histidine kinases and response regulators. Combining these genetic and biochemical approaches, we identify a new, highly conserved essential signaling pathway from the histidine kinase CenK to the response regulator CenR, which plays a critical role in controlling cell envelope biogenesis and structure. Depletion of either cenK or cenR leads to an unusual, severe blebbing of cell envelope material, whereas constitutive activation of the pathway compromises cell envelope integrity, resulting in cell lysis and death. We propose that the CenK–CenR pathway may be a suitable target for new antibiotic development, given previous successes in targeting the bacterial cell wall. Finally, the ability of our in vitro phosphotransfer profiling method to identify signaling pathways that operate in vivo takes advantage of an observation that histidine kinases are endowed with a global kinetic preference for their cognate response regulators. We propose that this system-wide selectivity insulates two-component pathways from one another, preventing unwanted cross-talk.     

Single‐cell imaging of genome organization and dynamics

Probing the architecture, mechanism, and dynamics of genome folding is fundamental to our understanding of genome function in homeostasis and disease. Most chromosome conformation capture studies dissect the genome architecture with population‐ and time‐averaged snapshots and thus have limited capabilities to reveal 3D nuclear organization and dynamics at the single‐cell level. Here, we discuss emerging imaging techniques ranging from light microscopy to electron microscopy that enable investigation of genome folding and dynamics at high spatial and temporal resolution. Results from these studies complement genomic data, unveiling principles underlying the spatial arrangement of the genome and its potential functional links to diverse biological activities in the nucleus.     

A Tangled Web: Regulatory Connections between Quorum Sensing and Cyclic Di-GMP

Bacteria sense and respond to environmental cues to control important developmental processes. Two widely conserved and important strategies that bacteria employ to sense changes in population density and local environmental conditions are quorum sensing (QS) and cyclic di-GMP (c-di-GMP) signaling, respectively. The importance of these pathways in controlling a broad variety of functions, including virulence, biofilm formation, and motility, has been recognized in many species. Recent research has shown that these pathways are intricately intertwined. Here we review the regulatory connections between QS and c-di-GMP signaling. We propose that the integration of QS with c-di-GMP allows bacteria to assimilate information about the local bacterial population density with other physicochemical environmental signals within the broader c-di-GMP signaling network.     

Imaging and manipulating the structural machinery of living cells on the micro- and nanoscale

The structure, physiology, and fate of living cells are all highly sensitive to mechanical forces in the cellular microenvironment, including stresses and strains that originate from encounters with the extracellular matrix (ECM), blood and other flowing materials, and neighbouring cells. This relationship between context and physiology bears tremendous implications for the design of cellular micro-or nanotechnologies, since any attempt to control cell behavior in a device must provide the appropriate physical microenvironment for the desired cell behavior. Cells sense, process, and respond to biophysical cues in their environment through a set of integrated, multi-scale structural complexes that span length scales from single molecules to tens of microns, including small clusters of force-sensing molecules at the cell surface, micron-sized cell-ECM focal adhesion complexes, and the cytoskeleton that permeates and defines the entire cell. This review focuses on several key technologies that have recently been developed or adapted for the study of the dynamics of structural micro-and nanosystems in living cells and how these systems contribute to spatially-and temporally-controlled changes in cellular structure and mechanics. We begin by discussing subcellular laser ablation, which permits the precise incision of nanoscale structural elements in living cells in order to discern their mechanical properties and contributions to cell structure. We then discuss fluorescence recovery after photobleaching and fluorescent speckle microscopy, two live-cell fluorescence imaging methods that enable quantitative measurement of the binding and transport properties of specific proteins in the cell. Finally, we discuss methods to manipulate cellular structural networks by engineering the extracellular environment, including microfabrication of ECM distributions of defined geometry and microdevices designed to measure cellular traction forces at micron-scale resolution. Together, these methods form a powerful arsenal that is already adding significantly to our understanding of the nanoscale architecture and mechanics of living cells and may contribute to the rational design of new cellular micro-and nanotechnologies.     

Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signaling

Cells sense their surrounding by employing intracellular signaling pathways that transmit hormonal signals from the cell membrane to the nucleus. TGF-β/SMAD signaling encodes various cell fates, controls tissue homeostasis and is deregulated in diseases such as cancer. The pathway shows strong heterogeneity at the single-cell level, but quantitative insights into mechanisms underlying fluctuations at various time scales are still missing, partly due to inefficiency in the calibration of stochastic models that mechanistically describe signaling processes. In this work we analyze single-cell TGF-β/SMAD signaling and show that it exhibits temporal stochastic bursts which are dose-dependent and whose number and magnitude correlate with cell migration. We propose a stochastic modeling approach to mechanistically describe these pathway fluctuations with high computational efficiency. Employing high-order numerical integration and fitting to burst statistics we enable efficient quantitative parameter estimation and discriminate models that assume noise in different reactions at the receptor level. This modeling approach suggests that stochasticity in the internalization of TGF-β receptors into endosomes plays a key role in the observed temporal bursting. Further, the model predicts the single-cell dynamics of TGF-β/SMAD signaling in untested conditions, e.g., successfully reflects memory effects of signaling noise and cellular sensitivity towards repeated stimulation. Taken together, our computational framework based on burst analysis, noise modeling and path computation scheme is a suitable tool for the data-based modeling of complex signaling pathways, capable of identifying the source of temporal noise.     

Macrophage cell death in microbial infections

Macrophages can respond to microbial infections with programmed cell death. The major cell death pathways of apoptosis, pyroptosis and necroptosis are tightly regulated to ensure adequate immune reactions to virulent and persistent invaders. Macrophage death eliminates the replicative niche of intracellular pathogens and induces immune attack. Not surprisingly, successful pathogens have evolved strategies to modulate macrophage cell death pathways to enable microbial survival and replication. Uncontrolled macrophage death can also lead to tissue damage, which may augment bacterial dissemination and pathology. In this review, we highlight how pathogens hijack macrophage cell death signals to promote microbial survival and immune evasion.     

Light-based feedback for controlling intracellular signaling dynamics

The ability to apply precise inputs to signaling species in live cells would be transformative for interrogating and understanding complex cell-signaling systems. Here we report an 'optogenetic' method for applying custom signaling inputs using feedback control of a light-gated protein-protein interaction. We applied this strategy to perturb protein localization and phosphoinositide 3-kinase activity, generating time-varying signals and clamping signals to buffer against cell-to-cell variability or changes in pathway activity.     

Oscillation-Induced Signal Transmission and Gating in Neural Circuits

Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay.     

CAPRI and RASAL impose different modes of information processing on Ras due to contrasting temporal filtering of Ca2+

The versatility of Ca2+ as a second messenger lies in the complex manner in which Ca2+ signals are generated. How information contained within the Ca2+ code is interpreted underlies cell function. Recently, we identified CAPRI and RASAL as related Ca2+-triggered Ras GTPase-activating proteins. RASAL tracks agonist-stimulated Ca2+ oscillations by repetitively associating with the plasma membrane, yet CAPRI displays a long-lasting Ca2+-triggered translocation that is refractory to cytosolic Ca2+ oscillations. CAPRI behavior is Ca2+- and C2 domain-dependent but sustained recruitment is predominantly Ca2+ independent, necessitating integration of Ca2+ by the C2 domains with agonist-evoked plasma membrane interaction sites for the pleckstrin homology domain. Using an assay to monitor Ras activity in real time, we correlate the spatial and temporal translocation of CAPRI with the deactivation of H-Ras. CAPRI seems to low-pass filter the Ca2+ signal, converting different intensities of stimulation into different durations of Ras activity in contrast to the preservation of Ca2+ frequency information by RASAL, suggesting sophisticated modes of Ca2+-regulated Ras deactivation.