Turing Patterning in Stratified Domains

Reaction-diffusion processes across layered media arise in several scientific domains such as pattern-forming E. coli on agar substrates, epidermal-mesenchymal coupling in development, and symmetry-breaking in cell polarisation. We develop a modelling framework for bi-layer reaction-diffusion systems and relate it to a range of existing models. We derive conditions for diffusion-driven instability of a spatially homogeneous equilibrium analogous to the classical conditions for a Turing instability in the simplest nontrivial setting where one domain has a standard reaction-diffusion system, and the other permits only diffusion. Due to the transverse coupling between these two regions, standard techniques for computing eigenfunctions of the Laplacian cannot be applied, and so we propose an alternative method to compute the dispersion relation directly. We compare instability conditions with full numerical simulations to demonstrate impacts of the geometry and coupling parameters on patterning, and explore various experimentally-relevant asymptotic regimes. In the regime where the first domain is suitably thin, we recover a simple modulation of the standard Turing conditions, and find that often the broad impact of the diffusion-only domain is to reduce the ability of the system to form patterns. We also demonstrate complex impacts of this coupling on pattern formation. For instance, we exhibit non-monotonicity of pattern-forming instabilities with respect to geometric and coupling parameters, and highlight an instability from a nontrivial interaction between kinetics in one domain and diffusion in the other. These results are valuable for informing design choices in applications such as synthetic engineering of Turing patterns, but also for understanding the role of stratified media in modulating pattern-forming processes in developmental biology and beyond.Comment: 25 pages, 7 figure

Interpretation of morphogen gradients by a synthetic bistable circuit.

During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations

Orthogonal intercellular signaling for programmed spatial behavior.

Bidirectional intercellular signaling is an essential feature of multicellular organisms, and the engineering of complex biological systems will require multiple pathways for intercellular signaling with minimal crosstalk. Natural quorum-sensing systems provide components for cell communication, but their use is often constrained by signal crosstalk. We have established new orthogonal systems for cell-cell communication using acyl homoserine lactone signaling systems. Quantitative measurements in contexts of differing receiver protein expression allowed us to separate different types of crosstalk between 3-oxo-C6- and 3-oxo-C12-homoserine lactones, cognate receiver proteins, and DNA promoters. Mutating promoter sequences minimized interactions with heterologous receiver proteins. We used experimental data to parameterize a computational model for signal crosstalk and to estimate the effect of receiver protein levels on signal crosstalk. We used this model to predict optimal expression levels for receiver proteins, to create an effective two-channel cell communication device. Establishment of a novel spatial assay allowed measurement of interactions between geometrically constrained cell populations via these diffusible signals. We built relay devices capable of long-range signal propagation mediated by cycles of signal induction, communication and response by discrete cell populations. This work demonstrates the ability to systematically reduce crosstalk within intercellular signaling systems and to use these systems to engineer complex spatiotemporal patterning in cell populations.PKG acknowledges support from the John Templeton Foundation Grant ID#15619: “Mind, Mechanism and Mathematics: Turing Centenary Research Project”. JH acknowledges Biotechnology and Biological Sciences Research Council and Engineering and Physical Sciences Research Council (RG72490), and FF acknowledges support from CONICYT‐PAI/Concurso Nacional de Apoyo al Retorno de Investigadores/as desde el Extranjero Folio 82130027. We would like to thank J. Ajioka and O. Yarkoni for use of equipment and advice. We would like to thank P.J. Steiner for early discussions about this work

Scheduling nab-paclitaxel combined with gemcitabine as first-line treatment for metastatic pancreatic adenocarcinoma

Abstract: Background: Nab-paclitaxel plus gemcitabine (nabP+gemcitabine) offers modest survival gains for patients with metastatic pancreatic ductal adenocarcinoma (PDAC). Sequential scheduling of nabP+gemcitabine in a PDAC mouse model improved efficacy; this hypothesis was tested in a clinical trial. Methods: Patients with previously untreated metastatic PDAC were randomised to receive nabP+gemcitabine administered either concomitantly on the same day, or sequentially, with gemcitabine administered 24 h after nabP. The primary outcome measure was progression-free survival (PFS). Secondary outcome measures were objective response rate (ORR), overall survival (OS), safety, quality of life (QoL) and predictive biomarkers. Results: In total, 71 patients received sequential (SEQ) and 75 concomitant (CON) treatment. Six-month PFS was 46% with SEQ and 32% with CON scheduling. Median PFS (5.6 versus 4.0 months, hazard ratio [HR] 0.67, 95% confidence interval [95% CI] 0.47–0.95, p = 0.022) and ORR (52% versus 31%, p = 0.023) favoured the SEQ arm; median OS was 10.2 versus 8.2 months (HR 0.93, 95% CI 0.65–1.33, p = 0.70). CTCAE Grade ≥3 neutropaenia incidence doubled with SEQ therapy but was not detrimental to QoL. Strongly positive tumour epithelial cytidine deaminase (CDA) expression favoured benefit from SEQ therapy (PFS HR 0.31, 95% CI 0.13–0.70). Conclusions: SEQ delivery of nabP+gemcitabine improved PFS and ORR, with manageable toxicity, but did not significantly improve OS. Clinical trial registration: ISRCTN71070888; ClinialTrials.gov (NCT03529175)

On Chemical Reaction Network Design by a Nested Evolution Algorithm

International audienceOne goal of synthetic biology is to implement useful functions with biochemical reactions, either by reprogramming living cells or programming artificial vesicles. In this perspective, we consider Chemical Reaction Networks (CRN) as a programming language, and investigate the CRN program synthesis problem. Recent work has shown that CRN interpreted by differential equations are Turing-complete and can be seen as analog computers where the molecular concentrations play the role of information carriers. Any real function that is computable by a Turing machine in arbitrary precision can thus be computed by a CRN over a finite set of molecular species. The proof of this result gives a numerical method to generate a finite CRN for implementing a real function presented as the solution of a Polynomial Initial Values Problem (PIVP). In this paper, we study an alternative method based on artificial evolution to build a CRN that approximates a real function given on finite sets of input values. We present a nested search algorithm that evolves the structure of the CRN and optimizes the kinetic parameters at each generation. We evaluate this algorithm on the Heaviside and Cosine functions both as functions of time and functions of input molecular species. We then compare the CRN obtained by artificial evolution both to the CRN generated by the numerical method from a PIVP definition of the function, and to the natural CRN found in the BioModels repository for switches and oscillators

Interpretation of morphogen gradients by a synthetic bistable circuit.

During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations

Rhythmic regulation of Ca2+ signalling networks

The circadian clock is the internal timekeeper of plants. This clock regulates most aspects of plant physiology providing considerable competitive advantage. We are investigating the role for oscillations in the cytosolic free Ca2+ concentration ([Ca2+]cyt) in the circadian control of cellular physiology. We have previously demonstrated that circadian oscillations of [Ca2+]cyt encode photoperiodic information but the precise role of circadian [Ca2+]cyt oscillations remain obscure. We have been taking a systems wide approach to determine the origin and function of circadian oscillations of [Ca2+]cyt. Using pharmacology, bioinformatics and biochemical tools we have new evidence that oscillations of [Ca2+]cyt are generated by the small signalling intermediate, cADPR. Positioning the oscillations of [Ca2+]cyt with respect to the molecular oscillator using reverse genetics indicates that [Ca2+]cyt is an output of the clock. Using a whole genome transcriptional profile we have identified over 1800 circadian-regulated transcripts, many of which encode for Ca2+ signalling elements. The function of circadian-regulated transcripts encoding signalling components is being investigated by reverse genetic screens with automated imaging. Using our extensive data sets describing the circadian regulation of [Ca2+]cyt in different backgrounds and conditions we have constructed a mathematical model. This is being validated using mutant analysis and refined by introducing complexity to the model. Our data and models suggest that [Ca2+]cyt acts an output of the clock that regulates diverse aspects of physiology and has the potential to form a feedback loop with the molecular components of the oscillator