Experimental and computational methods to highlight behavioural variations in TonB-dependent transporter expression in Pseudomonas aeruginosa versus siderophore concentration.

Iron is a key nutrient for bacterial growth. The source can be either heme or siderophore-Fe complexes. Siderophores are small molecules synthesized by bacteria to scavenge iron from the bacterial environment. The pathogen Pseudomonas aeruginosa can express at least 15 different iron uptake pathways and all but one involve a TonB-dependent transporter (TBDT) for the uptake of iron across the outer membrane. Little is known about how bacteria modulate and adapt the expression of their different iron import pathways according to their environment. Here, we have developed fluorescent reporters between the promoter region of genes encoding a TBDT and the fluorescent reporter mCherry. With these constructs, we can follow the expression of TBDTs under different growth conditions. Mathematical modelling of the data obtained showed the transcription and expression of the gene encoding the TBDT PfeA to have a sigmoidal shape, whereas it was logarithmic for the TBDT gene foxA. Maximum transcription for pfeA was reached in the presence of 3 µM enterobactin, the siderophore recognized by PfeA, whereas the maximum was not reached for foxA with 100 µM nocardamine, the siderophore of FoxA.

Calibration Methods for Time-to-Digital Converters.

In this paper, two of the most common calibration methods of synchronous TDCs, which are the bin-by-bin calibration and the average-bin-width calibration, are first presented and compared. Then, an innovative new robust calibration method for asynchronous TDCs is proposed and evaluated. Simulation results showed that: (i) For a synchronous TDC, the bin-by-bin calibration, applied to a histogram, does not improve the TDC's differential non-linearity (DNL); nevertheless, it improves its Integral Non-Linearity (INL), whereas the average-bin-width calibration significantly improves both the DNL and the INL. (ii) For an asynchronous TDC, the DNL can be improved up to 10 times by applying the bin-by-bin calibration, whereas the proposed method is almost independent of the non-linearity of the TDC and can improve the DNL up to 100 times. The simulation results were confirmed by experiments carried out using real TDCs implemented on a Cyclone V SoC-FPGA. For an asynchronous TDC, the proposed calibration method is 10 times better than the bin-by-bin method in terms of the DNL improvement.

Analytic modelling of passive microfluidic mixers.

This paper deals with a new analytical model for microfluidic passive mixers. Two common approaches already exist for such a purpose. On the one hand, the resolution of the advection-diffusion-reaction equation (ADRE) is the first one and the closest to physics. However, ADRE is a partial differential equation that requires finite element simulations. On the other hand, analytical models based on the analogy between microfluidics and electronics have already been established. However, they rely on the assumption of homogeneous fluids, which means that the mixer is supposed to be long enough to obtain a perfect mixture at the output. In this paper, we derive an analytical model from the ADRE under several assumptions. Then we integrate these equations within the electronic-equivalent models. The resulting models computed the relationship between pressure and flow rate in the microfluidic circuit but also takes the concentration gradients that can appear in the direction perpendicular to the channel into account. The model is compared with the finite element simulation performed with COMSOL Multiphysics in several study cases. We estimate that the global error introduced by our model compared to the finite element simulation is less than 5% in every use case. In counterparts, the cost in terms of computational resources is drastically reduced. The analytical model can be implemented in a large range of modelling and simulation languages, including SPICE and hardware description language such as Verilog-AMS. This feature is very interesting in the context of the in silico prototyping of large-scale microfluidic devices or multi-physics devices involving microfluidic circuits, e.g. lab-on-chips.

Towards Tracking of Deep Brain Stimulation Electrodes Using an Integrated Magnetometer.

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

Feasibility and reliability of sequential logic with gene regulatory networks.

Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called state machines. For such a circuit, outputs depend both on inputs and the current state of the system. Although it is still possible to design such circuits by analogy with digital electronics, some particularities of biology make the task trickier. The impact of two of them, namely the stochasticity of biological processes and the inhomogeneity in the response of regulation mechanisms, are assessed in this paper. Numerical simulations performed in two use cases point out high risks of malfunctions even for designed GRNs functional from a theoretical point of view. Several solutions to improve reliability of such systems are also discussed.

A Label-Free Optical Detection of Pathogens in Isopropanol as a First Step towards Real-Time Infection Prevention.

The detection of pathogens is a major public health issue. Every year, thousands of people die because of nosocomial infections. It is therefore important to be able to detect possible outbreaks as early as possible, especially in the hospital environment. Various pathogen detection techniques have already been demonstrated. However, most of them require expensive and specific equipment, and/or complex protocols, which, most of the time, involve biochemical reaction and labelling steps. In this paper, a new method that combines microscopic imaging and machine learning is described. The main benefits of this approach are to be low-cost, label-free and easy to integrate in any suitable medical device, such as hand hygiene dispensers. The suitability of this pathogen detection method is validated using four bacteria, both in PBS (Phosphate Buffered Saline) and in isopropanol. In particular, we demonstrated an efficient pathogenic detection that is sensible to changes in the composition of a mixture of pathogens, even in alcohol-based solutions.

Efficient Modeling and Simulation of Space-Dependent Biological Systems.

We recently demonstrated the possibility to model and to simulate biological functions using hardware description languages (HDLs) and associated simulators traditionally used for microelectronics. Nevertheless, those languages are not suitable to model and simulate space-dependent systems described by partial differential equations. However, in more and more applications space- and time-dependent models are unavoidable. For this purpose, we investigated a new modeling approach to simulate molecular diffusion on a mesoscopic scale still based on HDL. Our work relies on previous investigations on an electrothermal simulation tool for integrated circuits, and analogies that can be drawn between electronics, thermodynamics, and biology. The tool is composed of four main parts: a simple but efficient mesher that divides space into parallelepipeds (or rectangles in 2D) of adaptable size, a set of interconnected biological models, a SPICE simulator that handles the model and Python scripts that interface the different tools. Simulation results obtained with our tool have been validated on simple cases for which an analytical solution exists and compared with experimental data gathered from literature. Compared with existing approaches, our simulator has three main advantages: a very simple algorithm providing a direct interface between the diffusion model and biological model of each cell, the use of a powerful and widely proven simulation core (SPICE) and the ability to interface biological models with other domains of physics, enabling the study of transdisciplinary systems.

Modeling and simulation of biological systems using SPICE language.

The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology).

[Application of microelectronics CAD tools to synthetic biology]. / Application à la biologie synthétique des méthodes et outils de CAO de la microélectronique.

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper.

GeNeDA: An Open-Source Workflow for Design Automation of Gene Regulatory Networks Inspired from Microelectronics.

The topic of this article is the development of an open-source automated design framework for synthetic biology, specifically for the design of artificial gene regulatory networks based on a digital approach. In opposition to other tools, GeNeDA is an open-source online software based on existing tools used in microelectronics that have proven their efficiency over the last 30 years. The complete framework is composed of a computation core directly adapted from an Electronic Design Automation tool, input and output interfaces, a library of elementary parts that can be achieved with gene regulatory networks, and an interface with an electrical circuit simulator. Each of these modules is an extension of microelectronics tools and concepts: ODIN II, ABC, the Verilog language, SPICE simulator, and SystemC-AMS. GeNeDA is first validated on a benchmark of several combinatorial circuits. The results highlight the importance of the part library. Then, this framework is used for the design of a sequential circuit including a biological state machine.

A general framework improving teaching ligand binding to a macromolecule.

The interaction of a ligand with a macromolecule has been modeled following different theories. The tenants of the induced fit model consider that upon ligand binding, the protein-ligand complex undergoes a conformational change. In contrast, the allosteric model assumes that only one among different coexisting conformers of a given protein is suitable to bind the ligand optimally. In the present paper, we propose a general framework to model the binding of ligands to a macromolecule. Such framework built on the binding polynomial allows opening new ways to teach in a unified manner ligand binding, enzymology and receptor binding in pharmacology. Moreover, we have developed simple software that allows building the binding polynomial from the schematic description of the biological system under study. Taking calmodulin as a canonical example, we show here that the proposed tool allows the easy retrieval of previously experimental and computational reports. This article is part of a Special Issue entitled: Calcium Signaling in Health and Disease. Guest Editors: Geert Bultynck, Jacques Haiech, Claus W. Heizmann, Joachim Krebs, and Marc Moreau.

Modeling biology with HDL languages: a first step toward a genetic design automation tool inspired from microelectronics.

Nowadays, synthetic biology is a hot research topic. Each day, progresses are made to improve the complexity of artificial biological functions in order to tend to complex biodevices and biosystems. Up to now, these systems are handmade by bioengineers, which require strong technical skills and leads to nonreusable development. Besides, scientific fields that share the same design approach, such as microelectronics, have already overcome several issues and designers succeed in building extremely complex systems with many evolved functions. On the other hand, in systems engineering and more specifically in microelectronics, the development of the domain has been promoted by both the improvement of technological processes and electronic design automation tools. The work presented in this paper paves the way for the adaptation of microelectronics design tools to synthetic biology. Considering the similarities and differences between the synthetic biology and microelectronics, the milestones of this adaptation are described. The first one concerns the modeling of biological mechanisms. To do so, a new formalism is proposed, based on an extension of the generalized Kirchhoff laws to biology. This way, a description of all biological mechanisms can be made with languages widely used in microelectronics. Our approach is therefore successfully validated on specific examples drawn from the literature.

A game-of-life like simulator for design-oriented modeling of BioBricks in synthetic biology.

This paper deals with the development of a new simulator that will be very helpful to establish new accurate and predictive design-oriented models for the BioBricks used in synthetic biology. The simulator uses the principle of the game-of-life: molecules can move on a grid and, at every iteration, binding and dissociation rules are applied when two molecules are on same node. The principle is elementary but it can highlight interesting biological phenomenon. Those can be modeled by mathematical equations to achieve design-oriented models. In this case, the simulator also helps to make to link between mathematical parameters and the microscopic parameters. A first version of the software has been implemented in MATLAB. It permits to retrieve very interesting results, such as the Hill's equation and the properties of Hill's coefficient.

Synthetic biology methodology and model refinement based on microelectronic modeling tools and languages.

In microelectronics, the design of new systems is based on a proven time-tested design flow. The goal of this paper is to determine to what extend this design flow can be adapted to biosystem design. The presented methodology is based on a top-down approach and consists of starting with a behavioral description of the system to progressively refine it to its final low-level system representation, composed of DNA parts. To preserve accuracy and simplicity, the design flow relies on refined models of biological mechanisms, which can be expressed by the hardware description languages and simulation tools traditionally used in microelectronics. A case study, the complete modeling of a priority encoder, is presented to demonstrate the effectiveness of the method.