Article
Biochemical Research Methods
Kate E. Dray, Joseph J. Muldoon, Niall M. Mangan, Neda Bagheri, Joshua N. Leonard
Summary: Mathematical modeling is crucial for understanding and designing synthetic biological systems. However, the model development process is complex and nonintuitive, requiring iteration and comparison with experimental data. To address these challenges, we introduce the GAMES workflow, which combines automated and human-in-the-loop processes. This workflow enables biologists to more easily build and analyze models for various applications.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Lorenzo Olivi, Mareike Berger, Ramon N. P. Creyghton, Nicola De Franceschi, Cees Dekker, Bela M. Mulder, Nico J. Claassens, Pieter Rein ten Wolde, John van der Oost
Summary: Recent developments in synthetic biology may bring the generation of a synthetic cell within reach, with a key feature being a functional cell cycle. While progress has been made in establishing individual machineries, integrating and controlling them in a synthetic cell cycle is still a challenge to be addressed. This Perspective discusses potential paths towards achieving an integrated synthetic cell cycle.
NATURE COMMUNICATIONS
(2021)
News Item
Multidisciplinary Sciences
Philip Ball
Summary: A pair of studies highlight ethical and legal concerns surrounding the status of lab-grown human embryo models.
Article
Engineering, Electrical & Electronic
Andrew Lezia, Arianna Miano, Jeff Hasty
Summary: The design and construction of synthetic gene circuits have made significant progress, with applications in medicine, biosensing, and industrial chemical production. The focus has shifted from isolated circuits to complex systems, and design methods now include detailed models of host genome interaction with synthetic gene circuits.
PROCEEDINGS OF THE IEEE
(2022)
Article
Engineering, Electrical & Electronic
Joshua Adam Bull, Helen Mary Byrne
Summary: This article introduces the significant increase in understanding cancer biology over the past 25 years and the role of mathematical modeling in unraveling complex processes, testing hypotheses, and improving cancer treatment. The article emphasizes the collaboration between mathematical modelers and cancer scientists, as well as the integration of modeling with experimental and clinical studies for disease diagnosis and personalized treatment improvement.
PROCEEDINGS OF THE IEEE
(2022)
Article
Biochemical Research Methods
Nadia Taou, Michael Lones
Summary: This study introduces a method using synthetic regulatory networks to control and respond to the dynamics of a cell's native regulatory network, with the structure and parameters of the synthetic network optimized using Boolean networks and an evolutionary algorithm. Results show that controllers are effective in driving the target system to specified steady states, with scalability demonstrated for larger controlled networks through experiments with random Boolean networks.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Arjun Khakhar
Summary: Lichens have a rich history of scientific exploration, but modern biological techniques have been underutilized in their research. This has limited our understanding of unique lichen phenomena and their underlying mechanisms. Creating synthetic lichen from tractable microbes offers a solution to these challenges and opens up possibilities for sustainable biotechnology.
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
(2023)
Review
Cell Biology
Michael Cotner, Sarah Meng, Tyler Jost, Andrea Gardner, Carolina De Santiago, Amy Brock
Summary: Physiological processes rely on the control of cell proliferation, and mathematical modeling provides new insights into the complex regulation of cell proliferation dynamics. This review examines experimental approaches for measuring cell proliferation dynamics in vitro and discusses the integration of wet-laboratory studies with mathematical modeling to aid interpretation and prediction of cell behaviors, especially in the context of cancer.
AMERICAN JOURNAL OF PHYSIOLOGY-CELL PHYSIOLOGY
(2023)
Review
Microbiology
Icvara Barbier, Hadiastri Kusumawardhani, Yolanda Schaerli
Summary: Spatial pattern formation is an important feature of biological systems, and advances in synthetic biology have allowed us to engineer microbial populations to display sophisticated spatial patterns. This review discusses recent experimental advances in engineering microbial patterns, classifying them based on input signals and biological processes. The applications of microbial pattern formation are highlighted, and the challenges and potential future directions are discussed.
CURRENT OPINION IN MICROBIOLOGY
(2022)
Review
Plant Sciences
Elif Gediz Kocaoglan, Dhanya Radhakrishnan, Naomi Nakayama
Summary: Plant morphology and anatomy greatly impact agricultural yield. Genetic engineering has allowed for precise engineering of plant development, but with unpredictable outcomes. Synthetic biology approaches offer the potential for improved plant growth and development, creating climate-resilient agriculture.
JOURNAL OF EXPERIMENTAL BOTANY
(2023)
Article
Engineering, Electrical & Electronic
Robyn P. Araujo, Sean T. Vittadello, Michael P. H. Stumpf
Summary: Innovations in synthetic biology currently rely on trial and error, domain expertise, and ingenuity, but rational design engineering methods may offer a more efficient approach. Mathematical models of cellular systems are necessary to determine if they can meet intended target behavior. Complementary approaches such as algebraic methods and Bayesian design approaches can help identify general principles and choose models with the highest probability of fulfilling design objectives.
PROCEEDINGS OF THE IEEE
(2022)
Article
Multidisciplinary Sciences
Andras Gyorgy, Amor Menezes, Murat Arcak
Summary: The authors develop a genetic optimizer based on common synthetic biology parts to ensure optimal and robust cellular performance in diverse contexts. By presenting the blueprint of a genetic feedback module, they propose a method to dynamically fine-tune and optimize cellular performance. The optimizer can be easily implemented and integrated with existing pathways and biosensors.
NATURE COMMUNICATIONS
(2023)
Article
Biotechnology & Applied Microbiology
Viviana Nguyen, Pu Xue, Yifei Li, Huimin Zhao, Ting Lu
Summary: This study uses a combination of experimentation and mathematical modeling to investigate the growth optimization mediated by signaling in Saccharomyces cerevisiae. The results show that cAMP-mediated control plays a crucial role in achieving maximal or nearly maximal steady-state growth under different conditions. The study also reveals the dynamic adaptation of yeast cells through tuning cAMP levels and the involvement of other regulatory systems in growth maximization.
METABOLIC ENGINEERING
(2023)
Review
Engineering, Chemical
Jiansheng Chen, Haibin Zuo, Qingguo Xue, Jingsong Wang
Summary: This study reviews the progress in the research of burden distribution in blast furnaces, including charging measurements, physical model experiments, mathematical models for macroscopic burden distribution, and particle behavior simulations. The advantages, disadvantages, and applicable conditions of these approaches are analyzed, aiming to provide a comprehensive understanding of blast furnace charging and guidance for future technical developments.
Article
Plant Sciences
Orio Basallo, Lucia Perez, Abel Lucido, Albert Sorribas, Alberto Marin-Saguino, Ester Vilaprinyo, Laura Perez-Fons, Alfonso Albacete, Cristina Martinez-Andujar, Paul D. Fraser, Paul Christou, Teresa Capell, Rui Alves
Summary: Many valuable chemicals in various industries rely on the biosynthesis of IPP/DMAPP, which plants produce through two distinct pathways. Developing plants for high value terpenoid production is a biotechnological goal, but redirecting IPP/DMAPP to produce non-cognate metabolites poses challenges. This study aims to understand and predict the effects of increasing IPP/DMAPP production in plants through modeling.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Automation & Control Systems
Yang Zheng, Aivar Sootla, Antonis Papachristodoulou
Summary: This article introduces a new notion of block factor-width-two matrices and builds a new hierarchy of inner and outer approximations of the cone of positive semidefinite matrices. This improves the inner-approximation of the PSD cone. In the context of SOS optimization, this leads to a block extension of the scaled diagonally dominant sum-of-squares polynomials. Numerical experiments confirm the theoretical findings.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Jared Miller, Yang Zheng, Mario Sznaier, Antonis Papachristodoulou
Summary: This paper presents a concept of decomposed structured subsets to approximate an SDP with structured subsets after an equivalent conversion. The lower/upper bounds found by approximation after conversion become tighter than the bounds obtained by approximating the original SDP directly.
Article
Automation & Control Systems
Giorgio Valmorbida, Antonis Papachristodoulou
Summary: This article presents strategies for the state-feedback control law design of nonlinear control laws with saturating inputs. The input constraints are handled by considering a generalized local sector inequality, allowing the study of nonsymmetric saturation bounds. A numerical formulation based on solving Lyapunov inequalities with sum-of-squares programming is presented for polynomial systems.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Han Shu, Xuan Zhang, Na Li, Antonis Papachristodoulou
Summary: This article presents a control reconfiguration approach to improve the performance of two classes of dynamical systems. The approach involves a three-step procedure of reverse-engineering, forward-engineering, and comparing dynamics to redesign and improve the given system. Internet congestion control and distributed proportional-integral control are used as applications to showcase the effectiveness of the proposed approach.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Han Wang, Kostas Margellos, Antonis Papachristodoulou
Summary: This paper introduces a novel Time-Triggered Dimension Reduction Algorithm (TTDRA) for solving the task assignment problem. The algorithm accelerates computational speed by convexifying the constraints and cost function. Numerical simulations verify the optimality and computational efficiency of the algorithm.
EUROPEAN JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Elias August, Antonis Papachristodoulou
Summary: This paper presents a controller design method for nonlinear systems, achieving global asymptotic stability and a certain cost using sum of squares programming. Compared to previous approaches, the new method is less restrictive and requires less memory.
EUROPEAN JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Licio Romao, Kostas Margellos, Antonis Papachristodoulou
Summary: In this study, we propose a removal scheme with a less conservative bound on constraint violation probability. By extending the number of discarded scenarios, we improve the theoretical properties of the sampling-and-discarding scheme. Our results show that our feasibility guarantees outperform the standard approach, but also highlight the inherent property of introducing additional conservatism when the number of discarded scenarios is not an integer multiple of the decision space dimension.
Review
Biotechnology & Applied Microbiology
Miroslav Gasparek, Harrison Steel, Antonis Papachristodoulou
Summary: Living organisms produce a variety of metabolites that are of interest to the pharmaceutical industry due to their potential medicinal properties. Co-culturing producer species with specific inducer microbes is an effective method to activate silent gene clusters and produce secondary metabolites. However, the mechanisms and means of induction in co-cultures are not well understood, which limits the diversity and yield of valuable compounds. This review summarizes the known physiological mechanisms of secondary metabolite production in inducer-producer consortia and discusses approaches to optimize their discovery and production.
BIOTECHNOLOGY ADVANCES
(2023)
Article
Automation & Control Systems
Licio Romao, Antonis Papachristodoulou, Kostas Margellos
Summary: We revisit the sampling and discarding approach used for quantifying the probability of constraint violation in convex scenario programs. We propose a removal scheme that consists of a cascade of optimization problems, which leads to less conservative bounds for the probability of constraint violation compared to existing methods. We also provide evidence of the tightness of the proposed bound by characterizing a class of optimization problems that achieve the given upper bound. The improved performance of the proposed methodology is illustrated through an example involving a resource sharing linear program.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Proceedings Paper
Automation & Control Systems
Han Wang, Kostas Margellos, Antonis Papachristodoulou
Summary: This paper introduces the application of the control barrier function approach in the synthesis of safe controllers and proposes a method to explicitly synthesize a safe control law for nonlinear control-affine systems with limited control ability. By transforming the online quadratic programming problem into an offline parameterized optimization problem, considering states as parameters, a piece-wise Lipschitz continuous function as an explicit safe controller can be obtained.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Matthew Newton, Antonis Papachristodoulou
Summary: Neural networks have become increasingly popular in control feedback systems, but providing robustness guarantees is challenging. Current research focuses on addressing the sensitivity to adversarial inputs through computing outer-approximations of reachable sets and using a sparse polynomial optimization framework with Positivstellensatz. Our method shows tighter bounds and reasonable computational time compared to similar methods, and it can handle non-linear polynomial dynamics.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Matthew Newton, Antonis Papachristodoulou
Summary: This paper presents a method using a Sum of Squares programming framework to directly compute the stability of non-linear systems with neural network controllers. By proposing higher order candidate Lyapunov functions and constraint multipliers, the method is able to better capture the non-linear dynamics of the system and the neural network.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Article
Automation & Control Systems
Emmanouil Alexis, Luca Cardelli, Antonis Papachristodoulou
Summary: Here, a highly tunable PID bio-controller is introduced and its performance is compared to PI regulation using numerical simulations.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Multidisciplinary Sciences
Aivar Sootla, Nicolas Delalez, Emmanouil Alexis, Arthur Norman, Harrison Steel, George H. Wadhams, Antonis Papachristodoulou
Summary: We present a new design framework, called 'dichotomous feedback', for implementing negative feedback regulation in synthetic biology. This approach utilizes the existing fluxes in the process to be controlled and takes advantage of the process's architecture to design the control law. This mechanism of signal sequestration is commonly found in biological systems and is potentially easier to achieve compared to other methods. By linking the strength of signal sequestration to the process output, our feedback regulation mechanism shapes the signal response, reduces noise, and improves system robustness.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Microbiology
Carolin C. M. Schulte, Vinoy K. Ramachandran, Antonis Papachristodoulou, Philip S. Poole
Summary: This study reconstructed a genome-scale metabolic model for Rhizobium leguminosarum and integrated various experimental data sets to investigate the metabolic characteristics of rhizosphere bacteria, undifferentiated bacteria inside root nodules, and nitrogen-fixing bacteroids. These findings provide a framework for future experimental studies and help advance efforts to engineer novel symbioses with cereal crops for sustainable agriculture.
