Noisy Delay Denoises Biochemical Oscillators.

Genetic oscillations are generated by delayed transcriptional negative feedback loops, wherein repressor proteins inhibit their own synthesis after a temporal production delay. This delay is distributed because it arises from a sequence of noisy processes, including transcription, translocation, translation, and folding. Because the delay determines repression timing and, therefore, oscillation period, it has been commonly believed that delay noise weakens oscillatory dynamics. Here, we demonstrate that noisy delay can surprisingly denoise genetic oscillators. Specifically, moderate delay noise improves the signal-to-noise ratio and sharpens oscillation peaks, all without impacting period and amplitude. We show that this denoising phenomenon occurs in a variety of well-studied genetic oscillators, and we use queueing theory to uncover the universal mechanisms that produce it.

Signaling in microbial communities with open boundaries.

Microbial communities such as swarms or biofilms often form at the interfaces of solid substrates and open fluid flows. At the same time, in laboratory environments these communities are commonly studied using microfluidic devices with media flows and open boundaries. Extracellular signaling within these communities is therefore subject to different constraints than signaling within classic, closed-boundary systems such as developing embryos or tissues, yet is understudied by comparison. Here, we use mathematical modeling to show how advective-diffusive boundary flows and population geometry impact cell-cell signaling in monolayer microbial communities. We reveal conditions where the intercellular signaling lengthscale depends solely on the population geometry and not on diffusion or degradation, as commonly expected. We further demonstrate that diffusive coupling with the boundary flow can produce signal gradients within an isogenic population, even when there is no flow within the population. We use our theory to provide new insights into the signaling mechanisms of published experimental results, and we make several experimentally verifiable predictions. Our research highlights the importance of carefully evaluating boundary dynamics and environmental geometry when modeling microbial cell-cell signaling and informs the study of cell behaviors in both natural and synthetic systems.

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia.

The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain's division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains-but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.

Bayesian inference of distributed time delay in transcriptional and translational regulation.

MOTIVATION: Advances in experimental and imaging techniques have allowed for unprecedented insights into the dynamical processes within individual cells. However, many facets of intracellular dynamics remain hidden, or can be measured only indirectly. This makes it challenging to reconstruct the regulatory networks that govern the biochemical processes underlying various cell functions. Current estimation techniques for inferring reaction rates frequently rely on marginalization over unobserved processes and states. Even in simple systems this approach can be computationally challenging, and can lead to large uncertainties and lack of robustness in parameter estimates. Therefore we will require alternative approaches to efficiently uncover the interactions in complex biochemical networks. RESULTS: We propose a Bayesian inference framework based on replacing uninteresting or unobserved reactions with time delays. Although the resulting models are non-Markovian, recent results on stochastic systems with random delays allow us to rigorously obtain expressions for the likelihoods of model parameters. In turn, this allows us to extend MCMC methods to efficiently estimate reaction rates, and delay distribution parameters, from single-cell assays. We illustrate the advantages, and potential pitfalls, of the approach using a birth-death model with both synthetic and experimental data, and show that we can robustly infer model parameters using a relatively small number of measurements. We demonstrate how to do so even when only the relative molecule count within the cell is measured, as in the case of fluorescence microscopy. AVAILABILITY AND IMPLEMENTATION: Accompanying code in R is available at https://github.com/cbskust/DDE_BD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Delay-induced uncertainty for a paradigmatic glucose-insulin model.

Medical practice in the intensive care unit is based on the assumption that physiological systems such as the human glucose-insulin system are predictable. We demonstrate that delay within the glucose-insulin system can induce sustained temporal chaos, rendering the system unpredictable. Specifically, we exhibit such chaos for the ultradian glucose-insulin model. This well-validated, finite-dimensional model represents feedback delay as a three-stage filter. Using the theory of rank one maps from smooth dynamical systems, we precisely explain the nature of the resulting delay-induced uncertainty (DIU). We develop a framework one may use to diagnose DIU in a general oscillatory dynamical system. For infinite-dimensional delay systems, no analog of the theory of rank one maps exists. Nevertheless, we show that the geometric principles encoded in our DIU framework apply to such systems by exhibiting sustained temporal chaos for a linear shear flow. Our results are potentially broadly applicable because delay is ubiquitous throughout mathematical physiology.

Heterogeneity Improves Speed and Accuracy in Social Networks.

How does temporally structured private and social information shape collective decisions? To address this question we consider a network of rational agents who independently accumulate private evidence that triggers a decision upon reaching a threshold. When seen by the whole network, the first agent's choice initiates a wave of new decisions; later decisions have less impact. In heterogeneous networks, first decisions are made quickly by impulsive individuals who need little evidence to make a choice but, even when wrong, can reveal the correct options to nearly everyone else. We conclude that groups comprised of diverse individuals can make more efficient decisions than homogenous ones.

Modeling mechanical interactions in growing populations of rod-shaped bacteria.

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell's environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Engineered temperature compensation in a synthetic genetic clock.

Synthetic biology promises to revolutionize biotechnology by providing the means to reengineer and reprogram cellular regulatory mechanisms. However, synthetic gene circuits are often unreliable, as changes to environmental conditions can fundamentally alter a circuit's behavior. One way to improve robustness is to use intrinsic properties of transcription factors within the circuit to buffer against intra- and extracellular variability. Here, we describe the design and construction of a synthetic gene oscillator in Escherichia coli that maintains a constant period over a range of temperatures. We started with a previously described synthetic dual-feedback oscillator with a temperature-dependent period. Computational modeling predicted and subsequent experiments confirmed that a single amino acid mutation to the core transcriptional repressor of the circuit results in temperature compensation. Specifically, we used a temperature-sensitive lactose repressor mutant that loses the ability to repress its target promoter at high temperatures. In the oscillator, this thermoinduction of the repressor leads to an increase in period at high temperatures that compensates for the decrease in period due to Arrhenius scaling of the reaction rates. The result is a transcriptional oscillator with a nearly constant period of 48 min for temperatures ranging from 30 °C to 41 °C. In contrast, in the absence of the mutation the period of the oscillator drops from 60 to 30 min over the same temperature range. This work demonstrates that synthetic gene circuits can be engineered to be robust to extracellular conditions through protein-level modifications.

Effects of cell cycle noise on excitable gene circuits.

We assess the impact of cell cycle noise on gene circuit dynamics. For bistable genetic switches and excitable circuits, we find that transitions between metastable states most likely occur just after cell division and that this concentration effect intensifies in the presence of transcriptional delay. We explain this concentration effect with a three-states stochastic model. For genetic oscillators, we quantify the temporal correlations between daughter cells induced by cell division. Temporal correlations must be captured properly in order to accurately quantify noise sources within gene networks.

Timing and Variability of Galactose Metabolic Gene Activation Depend on the Rate of Environmental Change.

Modulation of gene network activity allows cells to respond to changes in environmental conditions. For example, the galactose utilization network in Saccharomyces cerevisiae is activated by the presence of galactose but repressed by glucose. If both sugars are present, the yeast will first metabolize glucose, depleting it from the extracellular environment. Upon depletion of glucose, the genes encoding galactose metabolic proteins will activate. Here, we show that the rate at which glucose levels are depleted determines the timing and variability of galactose gene activation. Paradoxically, we find that Gal1p, an enzyme needed for galactose metabolism, accumulates more quickly if glucose is depleted slowly rather than taken away quickly. Furthermore, the variability of induction times in individual cells depends non-monotonically on the rate of glucose depletion and exhibits a minimum at intermediate depletion rates. Our mathematical modeling suggests that the dynamics of the metabolic transition from glucose to galactose are responsible for the variability in galactose gene activation. These findings demonstrate that environmental dynamics can determine the phenotypic outcome at both the single-cell and population levels.

Modeling delay in genetic networks: from delay birth-death processes to delay stochastic differential equations.

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

Transcriptional delay stabilizes bistable gene networks.

Transcriptional delay can significantly impact the dynamics of gene networks. Here we examine how such delay affects bistable systems. We investigate several stochastic models of bistable gene networks and find that increasing delay dramatically increases the mean residence times near stable states. To explain this, we introduce a non-Markovian, analytically tractable reduced model. The model shows that stabilization is the consequence of an increased number of failed transitions between stable states. Each of the bistable systems that we simulate behaves in this manner.

A Rare Case of Moyamoya Disease in a Hispanic Woman: Unveiling Non-Asian Ethnicity and Atypical Risk Factors.

BACKGROUND Moyamoya disease is a rare and progressive cerebrovascular disorder caused by narrowed or blocked arteries supplying the brain. First described in Japan, the disease's incidence is higher in Asian countries and primarily affects children, although adults can also be afflicted. Following a literature review, very little was found regarding non-Asian ethnicities and the lack of typically associated risk factors that are known correlates of Moyamoya disease. CASE REPORT We present the case of a 41-year-old Hispanic woman with a history of type 1 diabetes mellitus and asthma who presented to the Emergency Department with concerns of recurrent transient episodes of left upper extremity weakness and paresthesia followed by confusion. The patient's blood pressure on arrival was 215/134 mmHg, and heart rate was 124 beats per min. Computed tomography of the head was unremarkable, but a computed tomography angiogram of the head demonstrated several areas of severe and bilateral stenosis with radiographic appearances, suggestive of Moyamoya disease. Magnetic resonance imaging of the brain would later illustrate two 6×2-mm ischemic infarcts in the right posterior centrum semiovale. CONCLUSIONS Moyamoya disease in the non-Asian population is rarely reported. We present a case of this condition in a patient of Hispanic ethnicity. Although it is generally considered a non-atherosclerotic disease, some literature suggests that atherosclerotic disease may also contribute to the development and possible acceleration of clinical features of Moyamoya disease. Given our patient's risk factors, we postulated that our patient's presentation was likely multifactorial, with both non-sclerotic and atherosclerotic disease.

Pneumocephalus secondary to epidural analgesia: a case report.

INTRODUCTION: Epidural anesthesia is commonly used for analgesia during labor, and headache is a common complaint following this procedure. Pneumocephalus, on the other hand, is a rare and potentially serious complication of epidural anesthesia, which is most often caused by accidental puncture of the dura with the introduction of air into intrathecal space. CASE PRESENTATION: We present the case of a 19-year-old Hispanic female who developed a severe frontal headache and neck pain eight hours following epidural catheter placement to deliver analgesia during labor. Physical examination was within normal limits without any neurological deficits. Computed tomography of the head and neck would later demonstrate small to moderate amounts of pneumocephalus, predominantly within the frontal horn of the lateral ventricles, and a moderate amount of air within the spinal canal. She was treated conservatively with analgesia. Though headache recurred after discharge, repeat imaging showed improvement in the volume of pneumocephalus and conservative management was continued. CONCLUSIONS: Although a rare complication and an uncommon cause of headache following epidural anesthesia, a high index of suspicion must remain for pneumocephalus as it may cause significant morbidity and, in some cases, be potentially life-threatening.

A Complicated Clinical Course of Community-Acquired Staphylococcus aureus Infective Endocarditis.

Infective endocarditis (IE) is an infection of the heart's endocardial surface, heart valves, or implanted cardiac devices, with the most common causative organism being Staphylococcus aureus. The clinical presentation of IE can be variable, with some patients presenting with multisystemic complications, including renal, pulmonary, cutaneous, and neurologic complications. Cerebral infarction is the most common complication of IE. Here we present a case of a young male with S. aureus IE of a native cardiac valve who developed multiple complications during his clinical course.

Signaling in microbial communities with open boundaries.

Microbial communities such as swarms or biofilms often form at the interfaces of solid substrates and open fluid flows. At the same time, in laboratory environments these communities are commonly studied using microfluidic devices with media flows and open boundaries. Extracellular signaling within these communities is therefore subject to different constraints than signaling within classic, closed-boundary systems such as developing embryos or tissues, yet is understudied by comparison. Here, we use mathematical modeling to show how advective-diffusive boundary flows and population geometry impact cell-cell signaling in monolayer microbial communities. We reveal conditions where the intercellular signaling lengthscale depends solely on the population geometry and not on diffusion or degradation, as commonly expected. We further demonstrate that diffusive coupling with the boundary flow can produce signal gradients within an isogenic population, even when there is no flow within the population. We use our theory to provide new insights into the signaling mechanisms of published experimental results, and we make several experimentally verifiable predictions. Our research highlights the importance of carefully evaluating boundary dynamics and environmental geometry when modeling microbial cell-cell signaling and informs the study of cell behaviors in both natural and synthetic systems.

Acquired Long QT Syndrome: Ventricular Fibrillation in an Otherwise Healthy Young Female.

Long QT syndrome (LQTS) occurs when there is an abnormality of myocardial repolarization characterized specifically by a prolonged QT interval on an electrocardiogram (ECG). This can be particularly dangerous as it is associated with an increased risk of polymorphic ventricular tachycardia and a life-threatening arrhythmia otherwise known as torsades de pointes (TdP). We present a case of a 40-year-old Indian female whose medical history was significant only for anemia and depression/anxiety that presented in a ventricular fibrillation cardiac arrest after becoming dyspneic and light-headed while dancing. Of relevance, she was taking sertraline 50mg once daily, a class of medications known to prolong the QT interval as well as having low serum calcium on presentation. Both her initial and subsequent electrocardiograms illuminated significantly prolonged QTc intervals. She subsequently sustained a ventricular tachycardia cardiac arrest, which degenerated into ventricular fibrillation in the cardiac intensive care unit two days later. Ultimately, the patient was pronounced brain-dead by the end of the week. We concluded this to be a case of LQTS predisposing to TdP, which then would degenerate into ventricular fibrillation. This case highlights multiple risk factors that are known to predispose to the aforementioned etiology. Further research is needed not only on common medications and their dose-dependent relationship on the QT interval across different ethnic groups but also on educating providers regarding multiple risk factors they may or may not have the power to control.

Tunable Dynamics in a Multistrain Transcriptional Pulse Generator.

One challenge in synthetic biology is the tuning of regulatory components within gene circuits to elicit a specific behavior. This challenge becomes more difficult in synthetic microbial consortia since each strain's circuit must function at the intracellular level and their combination must operate at the population level. Here we demonstrate that circuit dynamics can be tuned in synthetic consortia through the manipulation of strain fractions within the community. To do this, we construct a microbial consortium comprised of three strains of engineered Escherichia coli that, when cocultured, use homoserine lactone-mediated intercellular signaling to create a multistrain incoherent type-1 feedforward loop (I1-FFL). Like naturally occurring I1-FFL motifs in gene networks, this engineered microbial consortium acts as a pulse generator of gene expression. We demonstrate that the amplitude of the pulse can be easily tuned by adjusting the relative population fractions of the strains. We also develop a mathematical model for the temporal dynamics of the microbial consortium. This model allows us to identify population fractions that produced desired pulse characteristics, predictions that were confirmed for all but extreme fractions. Our work demonstrates that intercellular gene circuits can be effectively tuned simply by adjusting the starting fractions of each strain in the consortium.

Stochastic delay accelerates signaling in gene networks.

The creation of protein from DNA is a dynamic process consisting of numerous reactions, such as transcription, translation and protein folding. Each of these reactions is further comprised of hundreds or thousands of sub-steps that must be completed before a protein is fully mature. Consequently, the time it takes to create a single protein depends on the number of steps in the reaction chain and the nature of each step. One way to account for these reactions in models of gene regulatory networks is to incorporate dynamical delay. However, the stochastic nature of the reactions necessary to produce protein leads to a waiting time that is randomly distributed. Here, we use queueing theory to examine the effects of such distributed delay on the propagation of information through transcriptionally regulated genetic networks. In an analytically tractable model we find that increasing the randomness in protein production delay can increase signaling speed in transcriptional networks. The effect is confirmed in stochastic simulations, and we demonstrate its impact in several common transcriptional motifs. In particular, we show that in feedforward loops signaling time and magnitude are significantly affected by distributed delay. In addition, delay has previously been shown to cause stable oscillations in circuits with negative feedback. We show that the period and the amplitude of the oscillations monotonically decrease as the variability of the delay time increases.

Gastric Volvulus, An Important Yet Commonly Overlooked Etiology of Upper Gastrointestinal Bleeding: A Case Study.

Gastric volvulus is a distinct and uncommon pathology that usually presents with vomiting secondary to gastric outlet obstruction and gastrointestinal bleeding with an association with hiatal hernia. We present a case of a 71-year-old female who presented to the emergency department (ED) with a three-day history of coffee ground emesis. Of note, the patient was recently in the hospital under medical observation two weeks prior, with similar complaints of hematemesis. Chest X-ray revealed a left basilar opacity representing bowel gas suggestive of a hiatal hernia. Intravenous proton pump inhibitors were initiated but due to persistent recurrence of symptoms and progressive discomfort, a computed tomography (CT) of the chest and abdomen was ordered. This revealed a partial gastric volvulus with signs suggestive of vascular compromise of the herniated part of the stomach. She subsequently underwent emergent laparotomy, repair of the hiatal hernia, and partial gastrectomy and gastropexy. Post-surgical biopsy findings showed focal mucosal necrosis and ulceration, focal foveolar hyperplasia, edematous changes, and overall congestion in the submucosal tissue. She was discharged five days later with no complications or recurrence of symptoms.