PID Control of Biochemical Reaction Networks

Principles of feedback control have been shown to naturally arise in biological systems and successfully applied to build synthetic circuits. In this work we consider Biochemical Reaction Networks (CRNs) as a paradigm for modelling biochemical systems and provide the first implementation of a derivative component in CRNs. That is, given an input signal represented by the concentration level of some species, we build a CRN that produces as output the concentration of two species whose difference is the derivative of the input signal. By relying on this component, we present a CRN implementation of a feedback control loop with Proportional-Integral-Derivative (PID) controller and apply the resulting control architecture to regulate the protein expression in a microRNA regulated gene expression model.Comment: 8 Pages, 4 figures, Submitted to CDC 201

PID control of biochemical reaction networks

Principles of feedback control have been shown to naturally arise in biological systems and have been applied with success to build synthetic circuits. Here, we present an implementation of a proportional–integral–derivative (PID) controller as a chemical reaction network with mass-action kinetics. This makes the controller synthesizable in vitro using DNA strand displacement technology, owing to its demonstrated capability of realizing arbitrary reaction-network designs as interacting DNA molecules. Previous related work has studied biological PID architectures using linearizations of nonlinear dynamics arising in both the controller components and in the plant. In this article, we present a proof of correctness of our nonlinear design in closed loop using arguments from singular perturbation theory. As an application to show the effectiveness of our controller, we provide numerical simulations on a genetic model to perform PID feedback control of protein expression

Differential protein expression during growth on model and commercial mixtures of naphthenic acids in Pseudomonas fluorescens Pf‐5

Naphthenic acids (NAs) are carboxylic acids with the formula (CnH2n+ZO2) and are among the most toxic, persistent constituents of oil sands process-affected waters (OSPW), produced during oil sands extraction. Currently, the proteins and mechanisms involved in NA biodegradation are unknown. Using LC-MS/MS shotgun proteomics, we identified proteins overexpressed during the growth of Pseudomonas fluorescens Pf-5 on a model NA (4′-n-butylphenyl)-4-butanoic acid (n-BPBA) and commercial NA mixture (Acros). By day 11, >95% of n-BPBA was degraded. With Acros, a 17% reduction in intensity occurred with 10–18 carbon compounds of the Z family −2 to −14 (major NA species in this mixture). A total of 554 proteins (n-BPBA) and 631 proteins (Acros) were overexpressed during growth on NAs, including several transporters (e.g., ABC transporters), suggesting a cellular protective response from NA toxicity. Several proteins associated with fatty acid, lipid, and amino acid metabolism were also overexpressed, including acyl-CoA dehydrogenase and acyl-CoA thioesterase II, which catalyze part of the fatty acid beta-oxidation pathway. Indeed, multiple enzymes involved in the fatty acid oxidation pathway were upregulated. Given the presumed structural similarity between alkyl-carboxylic acid side chains and fatty acids, we postulate that P. fluorescens Pf-5 was using existing fatty acid catabolic pathways (among others) during NA degradation

5. Is the Current Copyright Framework fit for Purpose in Relation to Writing, Reading, and Publishing in the Digital Age?

The regulatory framework controlling the publication, copying and distribution of content evolved in a technological and commercial environment very different to the digital landscape in which we now find ourselves. Our copyright laws were shaped in an age when IP was published in physical form, copying cost money and distribution was far from free. In that context it made practical sense to restrict the right to copy in order to protect the livelihoods of authors and publishers, who had to m..

Arcadia Seminars: March 2011

The Arcadia Programme has been generously funded by a Grant from the Arcadia Fund http://www.arcadiafund.org.uk

The modelling and synthesis of chemical reaction networks

Biochemical systems have been influenced, altered, and engineered to produce a myriad of complex behaviours that have far reaching consequences in the realization of computational models and in applications such as pharmaceuticals and cell networks. However, unlike producing desired behaviours in digital systems, the mechanics behind biochemical systems are complex and poorly understood. In particular, gaps in our understanding of the behaviour of cell mechanics or synthetic molecular systems have hindered the production of biochemical circuits that model or enact certain behaviours. This thesis addresses these issues by accepting the inherent uncertainty and unknowns within biochemical systems, and exploring ways to produce desired behaviours despite these difficulties. This is done through the use of deterministic and stochastic interpretations of Chemical Reaction Networks (CRNs) to describe these biochemical systems. The first part of this thesis considers parameter synthesis of CRNs. A novel sketching language for CRNs that allows for both discrete and continuous parameter declarations is proposed. Often it is not only the correctness of synthesized programs that is important, but also their optimality with respect to a given cost function. Based on a cost function given by the structure of a CRN, there is an attempt to reduce the cost in order to produce a CRN optimal for the given cost function. Synthesis of complex CRN behaviour without structural constraints is seen as intractable, and therefore Syntax-Guided Synthesis (SyGuS) is employed to constrain the search space and allow us to synthesize behaviour of non-linear Ordinary Differential Equations (ODEs). Algorithms and case studies aimed at finding an optimal CRN are provided. Satisfiability Modulo Theory (SMT-ODE) solvers are employed to solve parametric ODEs constructed from a combination of the Linear Noise Approximation dynamics and sketching language choice variables. In our tool, named CRNSketch, a generalization of the CRN synthesis problem to include non mass-action kinetics as well as arbitrary continuous functions as inputs to a CRN, is successfully demonstrated. Biologically motivated case studies are provided highlighting the need for the tool, as well as our parameter and structural synthesis methods in general. An evaluation is provided on the limitations and tractability of our parameter synthesis approach. The second part of this thesis addresses the problem of control of CRNs, because of the inherent unknowns in biochemical systems. Using a reference CRN which exhibits a desired continuous behaviour, the principles of Proportional-Integral-Derivative (PID) control are employed, in an attempt to control the behaviour of any arbitrary CRN. That is, given an input signal, represented by the concentration level of a species, a series of CRNs are constructed that in turn attempt to control the output concentration of an arbitrary CRN, such that the plant CRN exhibits the behaviour of the reference signal. A novel CRN implementation of a derivative component is provided, and proofs and simulation of its operation are given. This novel derivative component is used as a building block for a PID controller, enabling us to compare this with an existing PI controller, and show how negative feedback with a PID controller can be implemented in CRNs. The effectiveness of this architecture on a microRNA regulated gene expression example is demonstrated, where the time evolution of a protein is controlled by acting on the expression of mRNA and microRNA using a CRN reference signal provided by our synthesis method.</p

Usefulness of the NULL-PLEASE Score to predict 1 survival in out-of hospital cardiac arrest

© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.Purpose: Out-of-hospital cardiac arrest (OHCA) carries a very high mortality even after successful cardiopulmonary resuscitation. Currently, information given to relatives regarding prognosis following resuscitation is often emotive and subjective, and varies with clinician experience. We aimed to validate the NULL-PLEASE score to predict survival following OHCA. Methods: A multicentre cohort study was conducted, with retrospective and prospective validation in consecutive unselected patients presenting with OHCA. The NULL-PLEASE score was calculated by attributing points to the following variables: Non-shockable initial rhythm, Unwitnessed arrest, Long low-flow period, Long no-flow period, pH7.0 mmol/l, End-stage renal failure, Age ≥85 years, Still resuscitation and Extra cardiac cause. The primary outcome was in-hospital death. Results: We assessed 700 patients admitted with OHCA, of whom 47% survived to discharge. In 300 patients we performed a retrospective validation, followed by prospective validation in 400 patients. The NULL-PLEASE score was lower in patients who survived compared to those who died (0 [IQR 0-1] vs. 4 [IQR 2-4], p<0.0005) and strongly predictive of in-hospital death (c-statistic 0.874, 95% confidence interval [CI] 0.848-0.899). Patients with a score ≥3 had a 24-fold increased risk of death (OR 23.6; 95%CI 14.840-37.5, p<0.0005) compared to those with lower scores. A score ≥3 has a 91% positive predictive value for in-hospital death, whilst a score <3 predicts a 71% chance of survival. Conclusion: The easy-to-use NULL-PLEASE score predicts in-hospital mortality with high specificity and can help clinicians explain the prognosis to relatives in an easy-to-understand, objective fashion, to realistically prepare them for the future.Peer reviewe