Synthetic mammalian signaling circuits for robust cell population control.

In multicellular organisms, cells actively sense and control their own population density. Synthetic mammalian quorum-sensing circuits could provide insight into principles of population control and extend cell therapies. However, a key challenge is reducing their inherent sensitivity to "cheater" mutations that evade control. Here, we repurposed the plant hormone auxin to enable orthogonal mammalian cell-cell communication and quorum sensing. We designed a paradoxical population control circuit, termed "Paradaux," in which auxin stimulates and inhibits net cell growth at different concentrations. This circuit limited population size over extended timescales of up to 42 days of continuous culture. By contrast, when operating in a non-paradoxical regime, population control became more susceptible to mutational escape. These results establish auxin as a versatile "private" communication system and demonstrate that paradoxical circuit architectures can provide robust population control.

Lightness constancy in reality, in virtual reality, and on flat-panel displays.

Virtual reality (VR) displays are being used in an increasingly wide range of applications. However, previous work shows that viewers often perceive scene properties very differently in real and virtual environments and so realistic perception of virtual stimuli should always be a carefully tested conclusion, not an assumption. One important property for realistic scene perception is surface color. To evaluate how well virtual platforms support realistic perception of achromatic surface color, we assessed lightness constancy in a physical apparatus with real lights and surfaces, in a commercial VR headset, and on a traditional flat-panel display. We found that lightness constancy was good in all three environments, though significantly better in the real environment than on the flat-panel display. We also found that variability across observers was significantly greater in VR and on the flat-panel display than in the physical environment. We conclude that these discrepancies should be taken into account in applications where realistic perception is critical but also that in many cases VR can be used as a flexible alternative to flat-panel displays and a reasonable proxy for real environments.

MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1-4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. METHODS: Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. RESULTS: We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. CONCLUSIONS: When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.

BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts.

Biochemical interactions in systems and synthetic biology are often modeled with chemical reaction networks (CRNs). CRNs provide a principled modeling environment capable of expressing a huge range of biochemical processes. In this paper, we present a software toolbox, written in Python, that compiles high-level design specifications represented using a modular library of biochemical parts, mechanisms, and contexts to CRN implementations. This compilation process offers four advantages. First, the building of the actual CRN representation is automatic and outputs Systems Biology Markup Language (SBML) models compatible with numerous simulators. Second, a library of modular biochemical components allows for different architectures and implementations of biochemical circuits to be represented succinctly with design choices propagated throughout the underlying CRN automatically. This prevents the often occurring mismatch between high-level designs and model dynamics. Third, high-level design specification can be embedded into diverse biomolecular environments, such as cell-free extracts and in vivo milieus. Finally, our software toolbox has a parameter database, which allows users to rapidly prototype large models using very few parameters which can be customized later. By using BioCRNpyler, users ranging from expert modelers to novice script-writers can easily build, manage, and explore sophisticated biochemical models using diverse biochemical implementations, environments, and modeling assumptions.

Silver nanoparticles - laser induced graphene (Ag NPs - LIG) hybrid electrodes for sensitive electrochemical-surface enhanced Raman spectroscopy (EC-SERS) detection.

This paper presents a novel approach for the fabrication of low cost Electrochemical-Surface Enhanced Raman Scattering (EC-SERS) sensing platforms. Laser Induced Graphene (LIG) electrodes were readily fabricated by direct laser writing of polyimide tapes and functionalized with silver nanoparticles (Ag NPs) to obtain hybrid Ag NPs - LIG electrodes suitable for EC-SERS analysis. Detection was achieved by coupling a handheld potentiostat with a Raman spectrograph, enabling measurement of SERS spectra of target analytes generated during voltage sweeps in the 0.0 to -1.0 V interval range. The sensing capabilities of the fabricated system were first tested with model molecule 4-aminobenzenethiol (4-ABT). Following sensitive detection of 4-ABT, EC-SERS analysis of food contaminant melamine in milk and antibiotic difloxacin hydrochloride (DIF) in river water was demonstrated, achieving sensitive detection of both analytes without pre-treatment steps. The easiness of fabrication, versatility of design, rapid analysis time and potential miniaturization of the system make Ag NPs - LIG electrodes suitable for a large range of in situ applications in the field of food monitoring and for environmental analysis.

Direct-write formation of integrated bottom contacts to laser-induced graphene-like carbon.

We report a simple, scalable two-step method for direct-write laser fabrication of 3D, porous graphene-like carbon electrodes from polyimide films with integrated contact plugs to underlying metal layers (Au or Ni). Irradiation at high average CO2laser power (30 W) and low scan speed (∼18 mm s)-1leads to formation of 'keyhole' contact plugs through local ablation of polyimide (initial thickness 17µm) and graphitization of the plug perimeter wall. Top-surface laser-induced graphene (LIG) electrodes are then formed and connected to the plug by raster patterning at lower laser power (3.7 W) and higher scan speed (200 mm s)-1. Sheet resistance data (71 ± 15 Ω sq.)-1indicates formation of high-quality surface LIG, consistent with Raman data which yield sharp first- and second-order peaks. We have also demonstrated that high-quality LIG requires a minimum initial polyimide thickness. Capacitance data measured between surface LIG electrodes and the buried metal film indicate a polyimide layer of thickness ∼7µm remaining following laser processing. By contrast, laser graphitization of polyimide of initial thickness ∼8µm yielded devices with large sheet resistance (>1 kΩ sq.)-1. Raman data also indicated significant disorder. Plug contact resistance values were calculated from analysis of transfer line measurement data for single- and multi-plug test structures. Contacts to buried nickel layers yielded lower plug resistances (1-plug: 158 ± 7 Ω , 4-plug: 31 ± 14 Ω) compared to contacts to buried gold (1-plug: 346 ± 37 Ω , 4-plug: 52 ± 3 Ω). Further reductions are expected for multi-plug structures with increased areal density. Proof-of-concept mm-scale LIG electrochemical devices with local contact plugs yielded rapid electron transfer kinetics (rate constantk0 âˆ¼ 0.017 cm s-1), comparable to values measured for exposed Au films (k0 âˆ¼0.023 cm s)-1. Our results highlight the potential for integration of LIG-based sensor electrodes with semiconductor or roll-to-roll manufacturing.

Luminance calibration of virtual reality displays in Unity.

Virtual reality (VR) displays are an increasingly popular medium for experiments on visual perception. This presents the challenge of showing precisely controlled stimuli on devices that were not primarily designed for research. Here we describe methods for controlling stimulus luminance in VR experiments created in Unity using the Built-in Render Pipeline. We discuss the Gamma/Linear setting, measuring luminance in a VR headset, and using color grading in Unity's Post-Processing Stack to make stimulus luminance proportional to achromatic RGB value. We provide MATLAB code that uses luminance measurements from a VR headset to generate the lookup table that Unity requires for linearizing luminance. We emphasize that when creating experiments in this complex environment, it is important to experiment with the rendering process to confirm that stimuli are displayed as expected. We show results of several such tests and provide code as a starting point for readers who wish to run further tests related to their own research.

The safety of asthma medications during pregnancy and lactation: Clinical management and research priorities.

Asthma is one of the most common underlying diseases in women of reproductive age that can lead to potentially serious medical problems during pregnancy and lactation. A group of key stakeholders across multiple relevant disciplines was invited to take part in an effort to prioritize, strategize, and mobilize action steps to fill important gaps in knowledge regarding asthma medication safety in pregnancy and lactation. The stakeholders identified substantial gaps in the literature on the safety of asthma medications used during pregnancy and lactation and prioritized strategies to fill those gaps. Short-term action steps included linking data from existing complementary study designs (US and international claims data, single drug pregnancy registries, case-control studies, and coordinated systematic data systems). Long-term action steps included creating an asthma disease registry, incorporating the disease registry into electronic health record systems, and coordinating care across disciplines. The stakeholders also prioritized establishing new infrastructures/collaborations to perform research in pregnant and lactating women and to include patient perspectives throughout the process. To address the evidence gaps, and aid in populating product labels with data that inform clinical decision making, the consortium developed a plan to systematically obtain necessary data in the most efficient and timely manner.

COVID-19 fosters social accountability in medical education.

The COVID-19 pandemic has highlighted embedded inequities and fragmentation in our health systems. Traditionally, structural issues with health professional education perpetuate these. COVID-19 has highlighted inequities, but may also be a disruptor, allowing positive responses and system redesign. Examples from health professional schools in high and low- and middle-income countries illustrate pro-equity interventions of current relevance. We recommend that health professional schools and planners consider educational redesign to produce a health workforce well equipped to respond to pandemics and meet future need.

Guidelines for designing the antithetic feedback motif.

Integral feedback control is commonly used in mechanical and electrical systems to achieve zero steady-state error following an external disturbance. Equivalently, in biological systems, a property known as robust perfect adaptation guarantees robustness to environmental perturbations and return to the pre-disturbance state. Previously, Briat et al proposed a biomolecular design for integral feedback control (robust perfect adaptation) called the antithetic feedback motif. The antithetic feedback controller uses the sequestration binding reaction of two biochemical species to record the integral of the error between the current and the desired output of the network it controls. The antithetic feedback motif has been successfully built using synthetic components in vivo in Escherichia coli and Saccharomyces cerevisiae cells. However, these previous synthetic implementations of antithetic feedback have not produced perfect integral feedback control due to the degradation and dilution of the two controller species. Furthermore, previous theoretical results have cautioned that integral control can only be achieved under stability conditions that not all antithetic feedback motifs necessarily fulfill. In this paper, we study how to design antithetic feedback motifs that simultaneously achieve good stability and small steady-state error properties, even as the controller species are degraded and diluted. We provide simple tuning guidelines to achieve flexible and practical synthetic biological implementations of antithetic feedback control. We use several tools and metrics from control theory to design antithetic feedback networks, paving the path for the systematic design of synthetic biological controllers.

Number Adaptation Can Be Dissociated From Density Adaptation.

Rapidly judging the number of objects in a scene is an important perceptual ability. Recent debates have centered on whether number perception is accomplished by dedicated mechanisms and, in particular, on whether number-adaptation aftereffects reflect adaptation of number per se or adaptation of related stimulus properties, such as density. Here, we report an adaptation experiment (N = 8) for which the predictions of number and density theories are diametrically opposed. We found that when a reference stimulus has higher density than an adaptation stimulus but contains fewer elements, adaptation reduces the perceived number of elements in the reference stimulus. This is consistent with number adaptation and inconsistent with density adaptation. Thus, number-adaptation aftereffects are more than a by-product of density adaptation: When density and number are dissociated, adaptation effects are in the direction predicted by adaptation to number, not density.

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local patterns of lighting and reflectance, and infers globally optimal interpretations of stimulus images. Like human observers, the model exhibits partial lightness constancy, codetermination, contrast, glow, and articulation effects. It also arrives at human-like interpretations of strong lightness illusions that have challenged previous models. The model's assumptions are reasonable and generic, including, for example, that lighting intensity spans a much wider range than surface reflectance and that shadow boundaries tend to be straighter than reflectance edges. Thus, a probabilistic model based on simple assumptions about lighting and reflectance gives a good computational account of lightness perception over a wide range of conditions. This work also shows how graphical models can be extended to develop more powerful models of constancy that incorporate features such color and depth.

A method for cost-effective and rapid characterization of engineered T7-based transcription factors by cell-free protein synthesis reveals insights into the regulation of T7 RNA polymerase-driven expression.

The T7 bacteriophage RNA polymerase (T7 RNAP) serves as a model for understanding RNA synthesis, as a tool for protein expression, and as an actuator for synthetic gene circuit design in bacterial cells and cell-free extract. T7 RNAP is an attractive tool for orthogonal protein expression in bacteria owing to its compact single subunit structure and orthogonal promoter specificity. Understanding the mechanisms underlying T7 RNAP regulation is important to the design of engineered T7-based transcription factors, which can be used in gene circuit design. To explore regulatory mechanisms for T7 RNAP-driven expression, we developed a rapid and cost-effective method to characterize engineered T7-based transcription factors using cell-free protein synthesis and an acoustic liquid handler. Using this method, we investigated the effects of the tetracycline operator's proximity to the T7 promoter on the regulation of T7 RNAP-driven expression. Our results reveal a mechanism for regulation that functions by interfering with the transition of T7 RNAP from initiation to elongation and validates the use of the method described here to engineer future T7-based transcription factors.

Shape from shading under inconsistent illumination.

People are able to perceive the 3D shape of illuminated surfaces using image shading cues. Theories about how we accomplish this often assume that the human visual system estimates a single lighting direction and interprets shading cues in accord with that estimate. In natural scenes, however, lighting can be much more complex than this, with multiple nearby light sources. Here we show that the human visual system can successfully judge 3D surface shape even when the lighting direction varies from place to place over a surface, provided the scale at which these lighting changes occur is similar to, or larger than, the size of the shape features being judged. Furthermore, we show that despite being able to accommodate rapid changes in lighting direction when judging shape, observers are generally unable to detect these changes. We conclude that, rather than relying on a single estimated illumination direction, the human visual system can accommodate illumination that varies substantially and rapidly across a surface.

On-chip membrane protein cell-free expression enables development of a direct binding assay: A curious case of potassium channel KcsA-Kv1.3.

Despite the significant role integral membrane proteins (IMPs) play in the drug discovery process, it remains extremely challenging to express, purify, and in vitro stabilize them for detailed biophysical analyses. Cell-free transcription-translation systems have emerged as a promising alternative for producing complex proteins, but they are still not a viable option for expressing IMPs due to improper post-translational folding of these proteins. We have studied key factors influencing in vitro folding of cell-free-expressed IMPs, particularly oligomeric proteins (i.e., ion channels). Using a chimeric ion channel, KcsA-Kv1.3 (K-K), as a model IMP, we have investigated several physiochemical determinants including artificial bilayer environments (i.e., lipid, detergent) for K-K in vitro stabilization. We observed that fusion of a 'superfolder' green fluorescent protein (sfGFP) to K-K as a protein expression reporter not only improves the protein yield, but surprisingly facilitates the K-K tetramer formation, probably by enhancing the solubility of monomeric K-K. Additionally, anionic lipids (i.e., DMPG) were found to be essential for the correct folding of cell-free-expressed monomeric K-K into tetramer, underscoring the importance of lipid-protein interaction in maintaining structural-functional integrity of ion channels. We further developed methods to integrate cell-free-expressed IMPs directly onto a biosensor chip. We employed a solid-supported lipid bilayer onto the surface plasmon resonance (SPR) chip to insert nascent K-K in a membrane. In a different approach, an anti-GFP-functionalized surface was used to capture in situ expressed K-K via its sfGFP tag. Interestingly, only the K-K-functionalized capture surface prepared by the latter strategy was able to interact with K-K's small binding partners. This generalizable approach can be further extended to other membrane proteins for developing direct binding assays involving small ligands.

Population diversification in a yeast metabolic program promotes anticipation of environmental shifts.

Delineating the strategies by which cells contend with combinatorial changing environments is crucial for understanding cellular regulatory organization. When presented with two carbon sources, microorganisms first consume the carbon substrate that supports the highest growth rate (e.g., glucose) and then switch to the secondary carbon source (e.g., galactose), a paradigm known as the Monod model. Sequential sugar utilization has been attributed to transcriptional repression of the secondary metabolic pathway, followed by activation of this pathway upon depletion of the preferred carbon source. In this work, we demonstrate that although Saccharomyces cerevisiae cells consume glucose before galactose, the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. This early activation reduces the time required for the population to transition between the two metabolic programs and provides a fitness advantage that might be crucial in competitive environments.

Classification images reveal decision variables and strategies in forced choice tasks.

Despite decades of research, there is still uncertainty about how people make simple decisions about perceptual stimuli. Most theories assume that perceptual decisions are based on decision variables, which are internal variables that encode task-relevant information. However, decision variables are usually considered to be theoretical constructs that cannot be measured directly, and this often makes it difficult to test theories of perceptual decision making. Here we show how to measure decision variables on individual trials, and we use these measurements to test theories of perceptual decision making more directly than has previously been possible. We measure classification images, which are estimates of templates that observers use to extract information from stimuli. We then calculate the dot product of these classification images with the stimuli to estimate observers' decision variables. Finally, we reconstruct each observer's "decision space," a map that shows the probability of the observer's responses for all values of the decision variables. We use this method to examine decision strategies in two-alternative forced choice (2AFC) tasks, for which there are several competing models. In one experiment, the resulting decision spaces support the difference model, a classic theory of 2AFC decisions. In a second experiment, we find unexpected decision spaces that are not predicted by standard models of 2AFC decisions, and that suggest intrinsic uncertainty or soft thresholding. These experiments give new evidence regarding observers' strategies in 2AFC tasks, and they show how measuring decision variables can answer long-standing questions about perceptual decision making.

What image features guide lightness perception?

Lightness constancy is the ability to perceive black and white surface colors under a wide range of lighting conditions. This fundamental visual ability is not well understood, and current theories differ greatly on what image features are important for lightness perception. Here we measured classification images for human observers and four models of lightness perception to determine which image regions influenced lightness judgments. The models were a high-pass-filter model, an oriented difference-of-Gaussians model, an anchoring model, and an atmospheric-link-function model. Human and model observers viewed three variants of the argyle illusion (Adelson, 1993) and judged which of two test patches appeared lighter. Classification images showed that human lightness judgments were based on local, anisotropic stimulus regions that were bounded by regions of uniform lighting. The atmospheric-link-function and anchoring models predicted the lightness illusion perceived by human observers, but the high-pass-filter and oriented-difference-of-Gaussians models did not. Furthermore, all four models produced classification images that were qualitatively different from those of human observers, meaning that the model lightness judgments were guided by different image regions than human lightness judgments. These experiments provide a new test of models of lightness perception, and show that human observers' lightness computations can be highly local, as in low-level models, and nevertheless depend strongly on lighting boundaries, as suggested by midlevel models.

Lightness matching and perceptual similarity.

Lightness constancy is the ability to perceive surface reflectance correctly despite substantial changes in lighting intensity. A classic view is that lightness constancy is the result of a "discounting" of lighting intensity, and this continues to be a prominent view today. Logvinenko and Maloney (2006) have proposed an alternative approach to understanding lightness constancy, in which observers do not make explicit estimates of reflectance, and lightness constancy is instead based on a perceptual similarity metric that depends on both the reflectance and the illuminance of surfaces viewed under different lighting conditions. Here we compare these two views using a novel, free-adjustment reflectance-matching task. We test whether observers can match reflectance in a task where they are free to adjust both the illuminance and the reflectance of the match stimulus over a wide range. We find that observers can match reflectance under these conditions, which supports the view that observers make explicit estimates of reflectance. We also compare performance in this free adjustment task using physical objects and computer-rendered images as stimuli. We find that lightness constancy is good in both cases, but with some evidence of a glow-related artifact with computer-rendered stimuli.