A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization.

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.

An endogenous accelerator for viral gene expression confers a fitness advantage.

Many signaling circuits face a fundamental tradeoff between accelerating their response speed while maintaining final levels below a cytotoxic threshold. Here, we describe a transcriptional circuitry that dynamically converts signaling inputs into faster rates without amplifying final equilibrium levels. Using time-lapse microscopy, we find that transcriptional activators accelerate human cytomegalovirus (CMV) gene expression in single cells without amplifying steady-state expression levels, and this acceleration generates a significant replication advantage. We map the accelerator to a highly self-cooperative transcriptional negative-feedback loop (Hill coefficient ∼7) generated by homomultimerization of the virus's essential transactivator protein IE2 at nuclear PML bodies. Eliminating the IE2-accelerator circuit reduces transcriptional strength through mislocalization of incoming viral genomes away from PML bodies and carries a heavy fitness cost. In general, accelerators may provide a mechanism for signal-transduction circuits to respond quickly to external signals without increasing steady-state levels of potentially cytotoxic molecules.

Crowding-induced interactions of ring polymers.

Macromolecular crowding and the presence of surfaces can significantly impact the spatial organization of biopolymers. While the importance of crowding-induced depletion interactions in biology has been recognized, much remains to be understood about the effect of crowding on biopolymers such as DNA plasmids. A fundamental problem highlighted by recent experiments is to characterize the impact of crowding on polymer-polymer and polymer-surface interactions. Motivated by the need for quantitative insight, we studied flexible ring polymers in crowded environments using Langevin dynamics simulations. The simulations demonstrated that crowding can lead to compaction of isolated ring polymers and enhanced interactions between two otherwise repulsive polymers. Using umbrella sampling, we determined the potential of mean force (PMF) between two ring polymers as a function of their separation distance at different volume fractions of crowding particles, φ. An effective attraction emerged at φ≈ 0.4, which is similar to the degree of crowding in cells. Analogous simulations showed that crowding can lead to strong adsorption of a ring polymer to a wall, with an effective attraction to the wall emerging at a smaller volume fraction of crowders (φ≈ 0.2). Our results reveal the magnitude of depletion interactions in a biologically-inspired model and highlight how crowding can be used to tune interactions in both cellular and cell-free systems.

Adsorption of semiflexible polymers in crowded environments.

Macromolecular crowding is a feature of cellular and cell-free systems that, through depletion effects, can impact the interactions of semiflexible biopolymers with surfaces. In this work, we use computer simulations to study crowding-induced adsorption of semiflexible polymers on otherwise repulsive surfaces. Crowding particles are modeled explicitly, and we investigate the interplay between the bending stiffness of the polymer and the volume fraction and size of crowding particles. Adsorption to flat surfaces is promoted by stiffer polymers, smaller crowding particles, and larger volume fractions of crowders. We characterize transitions from non-adsorbed to partially and strongly adsorbed states as a function of bending stiffness. The crowding-induced transitions occur at smaller values of the bending stiffness as the volume fraction of crowders increases. Concomitant effects on the size and shape of the polymer are reflected by crowding- and stiffness-dependent changes to the radius of gyration. For various polymer lengths, we identify a critical crowding fraction for adsorption and analyze its scaling behavior in terms of polymer stiffness. We also consider crowding-induced adsorption in spherical confinement and identify a regime in which increasing the bending stiffness induces desorption. The results of our simulations shed light on the interplay of crowding and bending stiffness on the spatial organization of biopolymers in encapsulated cellular and cell-free systems.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean.

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where 2 alternate expression states simultaneously exist. Here, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV's fate decision between active replication and viral latency. We find that the HIV transactivator of transcription (Tat) protein manipulates the intrinsic toggling of HIV's promoter, the long terminal repeat (LTR), to generate bimodal ON-OFF expression and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit's noncooperative "nonlatching" feedback architecture is optimized to slow the promoter's toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that nonlatching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV's decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.

Transcriptional burst frequency and burst size are equally modulated across the human genome.

Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting--as opposed to constitutive expression--is the predominant mode of expression. Quantitative analysis of the expression dynamics at these 8,000 loci indicates that both the frequency and size of the transcriptional bursts varies equally across the human genome, independent of promoter sequence. Strikingly, weaker expression loci modulate burst frequency to increase activity, whereas stronger expression loci modulate burst size to increase activity. Transcriptional activators such as trichostatin A (TSA) and tumor necrosis factor α (TNF) only modulate burst size and frequency along a constrained trend line governed by the promoter. In summary, transcriptional bursting dominates across the human genome, both burst frequency and burst size vary by chromosomal location, and transcriptional activators alter burst frequency and burst size, depending on the expression level of the locus.

Expression optimization and synthetic gene networks in cell-free systems.

Synthetic biology offers great promise to a variety of applications through the forward engineering of biological function. Most efforts in this field have focused on employing living cells, yet cell-free approaches offer simpler and more flexible contexts. Here, we evaluate cell-free regulatory systems based on T7 promoter-driven expression by characterizing variants of TetR and LacI repressible T7 promoters in a cell-free context and examining sequence elements that determine expression efficiency. Using the resulting constructs, we then explore different approaches for composing regulatory systems, leading to the implementation of inducible negative feedback in Escherichia coli extracts and in the minimal PURE system, which consists of purified proteins necessary for transcription and translation. Despite the fact that negative feedback motifs are common and essential to many natural and engineered systems, this simple building block has not previously been implemented in a cell-free context. As a final step, we then demonstrate that the feedback systems developed using our cell-free approach can be implemented in live E. coli as well, illustrating the potential for using cell-free expression to fast track the development of live cell systems in synthetic biology. Our quantitative cell-free component characterizations and demonstration of negative feedback embody important steps on the path to harnessing biological function in a bottom-up fashion.

Evidence for Behavioral Autorepression in Covid-19 Epidemiological Dynamics.

It has long been hypothesized that behavioral reactions to epidemic severity autoregulate infection dynamics, for example when susceptible individuals self-sequester based on perceived levels of circulating disease. However, evidence for such 'behavioral autorepression' has remained elusive, and its presence could significantly affect epidemic forecasting and interventions. Here, we analyzed early COVID-19 dynamics at 708 locations over three epidemiological scales (96 countries, 50 US states, and 562 US counties). Signatures of behavioral autorepression were identified through: (i) a counterintuitive mobility-death correlation, (ii) fluctuation-magnitude analysis, and (iii) dynamics of SARS-CoV-2 infection waves. These data enabled calculation of the average behavioral-autorepression strength (i.e., negative feedback 'gain') across different populations. Surprisingly, incorporating behavioral autorepression into conventional models was required to accurately forecast COVID-19 mortality. Models also predicted that the strength of behavioral autorepression has the potential to alter the efficacy of non-pharmaceutical interventions. Overall, these results provide evidence for the long-hypothesized existence of behavioral autorepression, which could improve epidemic forecasting and enable more effective application of non-pharmaceutical interventions during future epidemics. Significance: Challenges with epidemiological forecasting during the COVID-19 pandemic suggested gaps in underlying model architecture. One long-held hypothesis, typically omitted from conventional models due to lack of empirical evidence, is that human behaviors lead to intrinsic negative autoregulation of epidemics (termed 'behavioral autorepression'). This omission substantially alters model forecasts. Here, we provide independent lines of evidence for behavioral autorepression during the COVID-19 pandemic, demonstrate that it is sufficient to explain counterintuitive data on 'shutdowns', and provides a mechanistic explanation of why early shutdowns were more effective than delayed, high-intensity shutdowns. We empirically measure autorepression strength, and show that incorporating autorepression dramatically improves epidemiological forecasting. The autorepression phenomenon suggests that tailoring interventions to specific populations may be warranted.

Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function.

Neural chips, which are capable of simultaneous multisite neural recording and stimulation, have been used to detect and modulate neural activity for almost thirty years. As neural interfaces, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface may potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single-cell level and even inside the cell. FROM THE CLINICAL EDITOR: The authors demonstrate the utility of a neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes. The new device can be used to stimulate and/or monitor signals from brain tissue in vitro and for monitoring dynamic information of neuroplasticity both intracellularly and at the single cell level including neuroelectrical and neurochemical activities.

Crowding-Induced Spatial Organization of Gene Expression in Cell-Sized Vesicles.

Cell-free protein synthesis is an important tool for studying gene expression and harnessing it for applications. In cells, gene expression is regulated in part by the spatial organization of transcription and translation. Unfortunately, current cell-free approaches are unable to control the organization of molecular components needed for gene expression, which limits the ability to probe and utilize its effects. Here, we show, using complementary computational and experimental approaches, that macromolecular crowding can be used to control the spatial organization and translational efficiency of gene expression in cell-sized vesicles. Computer simulations and imaging experiments reveal that, as crowding is increased, DNA plasmids become localized at the inner surface of vesicles. Ribosomes, in contrast, remain uniformly distributed, demonstrating that crowding can be used to differentially organize components of gene expression. We further carried out cell-free protein synthesis reactions in cell-sized vesicles and quantified mRNA and protein abundance. At sufficiently high levels of crowding, we observed localization of mRNA near vesicle surfaces, a decrease in translational efficiency and protein abundance, and anomalous scaling of protein abundance as a function of vesicle size. These results are consistent with high levels of crowding causing altered spatial organization and slower diffusion. Our work demonstrates a straightforward way to control the organization of gene expression in cell-sized vesicles and provides insight into the spatial regulation of gene expression in cells.

Using noise to probe and characterize gene circuits.

Stochastic fluctuations (or "noise") in the single-cell populations of molecular species are shaped by the structure and biokinetic rates of the underlying gene circuit. The structure of the noise is summarized by its autocorrelation function. In this article, we introduce the noise regulatory vector as a generalized framework for making inferences concerning the structure and biokinetic rates of a gene circuit from its noise autocorrelation function. Although most previous studies have focused primarily on the magnitude component of the noise (given by the zero-lag autocorrelation function), our approach also considers the correlation component, which encodes additional information concerning the circuit. Theoretical analyses and simulations of various gene circuits show that the noise regulatory vector is characteristic of the composition of the circuit. Although a particular noise regulatory vector does not map uniquely to a single underlying circuit, it does suggest possible candidate circuits, while excluding others, thereby demonstrating the probative value of noise in gene circuit analysis.

Transcriptional bursting from the HIV-1 promoter is a significant source of stochastic noise in HIV-1 gene expression.

Analysis of noise in gene expression has proven a powerful approach for analyzing gene regulatory architecture. To probe the regulatory mechanisms controlling expression of HIV-1, we analyze noise in gene-expression from HIV-1's long terminal repeat (LTR) promoter at different HIV-1 integration sites across the human genome. Flow cytometry analysis of GFP expression from the HIV-1 LTR shows high variability (noise) at each integration site. Notably, the measured noise levels are inconsistent with constitutive gene expression models. Instead, quantification of expression noise indicates that HIV-1 gene expression occurs through randomly timed bursts of activity from the LTR and that each burst generates an average of 2-10 mRNA transcripts before the promoter returns to an inactive state. These data indicate that transcriptional bursting can generate high variability in HIV-1 early gene products, which may critically influence the viral fate-decision between active replication and proviral latency.

Macromolecular Crowding Affects Voltage-Dependent Alamethicin Pore Formation in Lipid Bilayer Membranes.

Macromolecular crowding is known to modulate chemical equilibria, reaction rates, and molecular binding events, both in aqueous solutions and at lipid bilayer membranes, natural barriers that enclose the crowded environments of cells and their subcellular compartments. Previous studies on the effects of macromolecular crowding in aqueous compartments on conduction through membranes have focused on single-channel ionic conduction through previously formed pores at thermodynamic equilibrium. Here, the effects of macromolecular crowding on the mechanism of pore formation itself were studied using the droplet interface bilayer (DIB) technique with the voltage-dependent pore-forming peptide alamethicin (alm). Macromolecular crowding was varied using 8 kDa molecular weight polyethylene glycol (PEG8k) or 500 kDa dextran (DEX500k) in two aqueous droplets on both sides of the bilayer membrane. In general, voltage thresholds for pore formation in the presence of crowders in the droplets decreased compared to their values in the absence of crowders, due to excluded volume effects, water binding by PEG, and changes in the ordering of water molecules and hydrogen-bonding interactions involving the polar lipid headgroups. In addition, asymmetric crowder loading (e.g., PEG8k-DEX500k on either side of the membrane) resulted in transmembrane osmotic pressure gradients that either enhanced or degraded the ionic conduction through the pores.

Immobilization and release strategies for DNA delivery using carbon nanofiber arrays and self-assembled monolayers.

We report a strategy for immobilizing dsDNA (double-stranded DNA) onto vertically aligned carbon nanofibers and subsequently releasing this dsDNA following penetration and residence of these high aspect ratio structures within cells. Gold-coated nanofiber arrays were modified with self-assembled monolayers (SAM) to which reporter dsDNA was covalently and end-specifically bound with or without a cleavable linker. The DNA-modified nanofiber arrays were then used to impale, and thereby transfect, Chinese hamster lung epithelial cells. This mechanical approach enables the transport of bound ligands directly into the cell nucleus and consequently bypasses extracellular and cytosolic degradation. Statistically significant differences were observed between the expression levels from immobilized and releasable DNA, and these are discussed in relation to the distinct accessibility and mode of action of glutathione, an intracellular reducing agent responsible for releasing the bound dsDNA. These results prove for the first time that an end-specifically and covalently SAM-bound DNA can be expressed in cells. They further demonstrate how the choice of immobilization and release methods can impact expression of nanoparticle delivered DNA.

Nano-enabled synthetic biology.

Biological systems display a functional diversity, density and efficiency that make them a paradigm for synthetic systems. In natural systems, the cell is the elemental unit and efforts to emulate cells, their components, and organization have relied primarily on the use of bioorganic materials. Impressive advances have been made towards assembling simple genetic systems within cellular scale containers. These biological system assembly efforts are particularly instructive, as we gain command over the directed synthesis and assembly of synthetic nanoscale structures. Advances in nanoscale fabrication, assembly, and characterization are providing the tools and materials for characterizing and emulating the smallest scale features of biology. Further, they are revealing unique physical properties that emerge at the nanoscale. Realizing these properties in useful ways will require attention to the assembly of these nanoscale components. Attention to systems biology principles can lead to the practical development of nanoscale technologies with possible realization of synthetic systems with cell-like complexity. In turn, useful tools for interpreting biological complexity and for interfacing to biological processes will result.

Nanoscale lithography via electron beam induced deposition.

We demonstrate the resolution and characteristics of a nanolithography process utilizing electron beam induced deposition (EBID) of W(CO)(6) and C(10)H(8) to define the imaging and masking layers. Lines and dot matrices were defined/written with various electron beam doses onto both polymethylmethacrylate (PMMA) coated silicon substrates (PMMA-Si) and bare silicon substrates (Si). The selectivity of the W(CO)(x) for the PMMA dry development process (no measurable etching) and the silicon ( approximately 18:1) reactive ion etch was very good. C(10)H(8) directly patterned on Si also provided good selectivity for the silicon etch process, 21:1. The pattern transfer of the EBID material patterns into the silicon had high fidelity. The resolution scaled with exposure dose and was correlated with the EBID broadening/scattering via a Monte Carlo simulation. Using the bi-layer approach, imaging layers on PMMA-Si, a silicon nanowire resolution of 13.5 nm and linewidth of 24.5 nm are demonstrated. Furthermore, using the single-layer approach, EBID directly on Si, a silicon nanowire resolution of 33 nm is demonstrated.

Positional control of catalyst nanoparticles for the synthesis of high density carbon nanofiber arrays.

Precise arrangement of nanoscale elements within larger systems, is essential to controlling higher order functionality and tailoring nanophase material properties. Here, we present findings on growth conditions for vertically aligned carbon nanofibers that enable synthesis of high density arrays and individual rows of nanofibers, which could be used to form barriers for restricting molecular transport, that have regular spacings and few defects. Growth through plasma-enhanced chemical vapor deposition was initiated from precisely formed nickel catalyst dots of varying diameter and spacing that were patterned through electron beam lithography. Nanofiber growth conditions, including power, precursor gas ratio, growth temperature and pressure were varied to optimize fiber uniformity and minimize defects that result from formation and migration of catalyst particles prior to growth. It was determined that both catalyst dot diameter and initial plasma power have a considerable influence on the number and severity of defects, while growth temperature, gas ratio (C(2)H(2):NH(3)) and pressure can be varied within a considerable range to fine-tune nanofiber morphology.

Cytoplasmic Amplification of Transcriptional Noise Generates Substantial Cell-to-Cell Variability.

Transcription is an episodic process characterized by probabilistic bursts, but how the transcriptional noise from these bursts is modulated by cellular physiology remains unclear. Using simulations and single-molecule RNA counting, we examined how cellular processes influence cell-to-cell variability (noise). The results show that RNA noise is higher in the cytoplasm than the nucleus in ∼85% of genes across diverse promoters, genomic loci, and cell types (human and mouse). Measurements show further amplification of RNA noise in the cytoplasm, fitting a model of biphasic mRNA conversion between translation- and degradation-competent states. This multi-state translation-degradation of mRNA also causes substantial noise amplification in protein levels, ultimately accounting for ∼74% of intrinsic protein variability in cell populations. Overall, the results demonstrate how noise from transcriptional bursts is intrinsically amplified by mRNA processing, leading to a large super-Poissonian variability in protein levels.

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns.

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting-the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increase in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA ("spatial noise") that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. These results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.

Direct quantification of N-(3-oxo-hexanoyl)-L-homoserine lactone in culture supernatant using a whole-cell bioreporter.

The autoinducer N-(3-oxo-hexanoyl)-L-homoserine lactone (3-oxo-C6-HSL) plays a significant role in the quorum-sensing system of the marine bacterium Vibrio fischeri. Upon forming a transcriptional activation complex with LuxR, 3-oxo-C6-HSL induces transcription of the luxICDABEG operon, leading to the increased production of both the 3-oxo-C6-HSL synthase (LuxI) and the bioluminescent proteins. In order to quantitatively analyze this regulatory mechanism, a novel approach was developed to measure 3-oxo-C6-HSL concentrations in V. fischeri cell culture supernatant. A bioluminescent strain of Escherichia coli that responds to 3-oxo-C6-HSL was used as a bioreporter. Although a linear response of the bioreporter to exogenously added synthetic 3-oxo-C6-HSL was found over several orders of magnitude, we show that bioreporter performance was dramatically impacted by variations in the supernatants using samples from a V. fischeri LuxI- strain. However, when maintained in the same supernatant background, the normalized peak bioluminescence maintained a linear response to 3-oxo-C6-HSL concentrations. Therefore, a standard additions technique was developed in which a known concentration of 3-oxo-C6-HSL was added to supernatant samples from wild-type V. fischeri cultures, and the incremental increase of the normalized peak bioluminescence relative to the untreated sample was determined. The concentration of 3-oxo-C6-HSL in the supernatant of the unknown sample was then quantified from the slope of the response between the normalized bioluminescent peaks with and without the addition of 3-oxo-C6-HSL. Advantages of this method are that it is rapid, does not require concentration or extraction, uses a small sample volume (ca. 2 ml), and accounts for effects caused by the composition of the supernatant. Furthermore, the findings can be broadly applicable to other bioreporter systems involving variable background conditions.