Subhayu Basu

Synthetic biology: new engineering rules for an emerging discipline

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

A synthetic multicellular system for programmed pattern formation.

Pattern formation is a hallmark of coordinated cell behaviour in both single and multicellular organisms. It typically involves cell–cell communication and intracellular signal processing. Here we show a synthetic multicellular system in which genetically engineered ‘receiver’ cells are programmed to form ring-like patterns of differentiation based on chemical gradients of an acyl-homoserine lactone (AHL) signal that is synthesized by ‘sender’ cells. In receiver cells, ‘band-detect’ gene networks respond to user-defined ranges of AHL concentrations. By fusing different fluorescent proteins as outputs of network variants, an initially undifferentiated ‘lawn’ of receivers is engineered to form a bullseye pattern around a sender colony. Other patterns, such as ellipses and clovers, are achieved by placing senders in different configurations. Experimental and theoretical analyses reveal which kinetic parameters most significantly affect ring development over time. Construction and study of such synthetic multicellular systems can improve our quantitative understanding of naturally occurring developmental processes and may foster applications in tissue engineering, biomaterial fabrication and biosensing.

Genetic circuit building blocks for cellular computation, communications, and signal processing

In this paper, we review an emerging engineering discipline to programcell behaviors by embedding synthetic gene networks that performcomputation, communications, and signal processing. To accomplishthis goal, we begin with a genetic component library and a biocircuitdesign methodology for assembling these components into compoundcircuits. The main challenge in biocircuit design lies in selectingwell-matched genetic components that when coupled, reliably producethe desired behavior. We use simulation tools to guide circuitdesign, a process that consists of selecting the appropriatecomponents and genetically modifying existing components until thedesired behavior is achieved. In addition to such rational design, wealso employ directed evolution to optimize genetic circuitbehavior. Building on Natures fundamental principle of evolution,this unique process directs cells to mutate their own DNA until theyfind gene network configurations that exhibit the desired systemcharacteristics. The integration of all the above capabilities infuture synthetic gene networks will enable cells to performsophisticated digital and analog computation, both asindividual entities and as part of larger cell communities. Thisengineering discipline and its associated tools will advance thecapabilities of genetic engineering, and allow us to harness cells fora myriad of applications not previously achievable.

Parameter estimation for two synthetic gene networks: a case study

In this paper, we use two synthetic gene networks, a transcriptional cascade and a pulse generating network, to study the efficacy of a simple statistical parameter fitting algorithm. The fitting was performed on experimental data and computer-generated data (to test how well the algorithm works under ideal conditions with perfect information). Most of the experimental parameter estimations yielded tight ranges of kinetic values for both gene networks. However, the results using simulated data indicate that the algorithm was able to provide better parameter estimates for the pulse generating network than for the transcriptional cascade. This is likely a result of the larger amount of time-series data available for the pulse generator and its greater level of phenotypical complexity, leading to tighter constraints for optimization. The variation in the magnitudes of the standard deviations between parameter estimates may give an indication of system sensitivity to specific kinetic rate constants. In the future, we also plan to verify the experimental results by constructing network variants and attempting to predict behaviors using values obtained in this study.

Engineering signal processing in cells: Towards molecular concentration band detection

We seek to couple protein-ligand interactions with synthetic gene networks in order to equip cells with the ability to process internal and environmental information in novel ways. In this paper, we propose and analyze a new genetic signal processing circuit that can be configured to detect various chemical concentration ranges of ligand molecules. These molecules freely diffuse from the environment into the cell. The circuit detects acyl-homoserine lactone ligand molecules, determines if the molecular concentration falls within two prespecified thresholds, and reports the outcome with a fluorescent protein. In the analysis of the circuit and the description of preliminary experimental results, we demonstrate how to adjust the concentration band thresholds by altering the kinetic properties of specific genetic elements, such as ribosome binding site efficiencies or dna-binding protein affinities to their operators.

An Integrated Approach to Testing Embedded Cores and Interconnects Using Test Access Mechanism (TAM) Switch

The present paper introduces a new strategy for testing embedded cores using Test Access Mechanism (TAM) switches. An algorithm has been proposed for testing the cores using the TAM switch architecture. In addition, a scheme for testing the interconnections between cores in parallel is also presented. Experiments have been carried out on several synthetic SOC benchmarks. Results show significant optimization of area overhead as well as test time.

Engineering Signal Processing in Cells: Towards Molecular Concentration Band Detection

We seek to couple protein-ligand interactions with synthetic gene networks in order to equip cells with the ability to process internal and environmental information in novel ways. In this paper, we propose and analyze a new genetic signal processing circuit that can be configured to detect various chemical concentration ranges of ligand molecules. These molecules freely diffuse from the environment into the cell. The circuit detects acyl-homoserine lactone ligand molecules, determines if the molecular concentration falls within two prespecified thresholds, and reports the outcome with a fluorescent protein. In the analysis of the circuit and the description of preliminary experimental results, we demonstrate how to adjust the concentration band thresholds by altering the kinetic properties of specific genetic elements, such as ribosome binding site efficiencies or dna-binding protein affinities to their operators.

Dynamic control in a coordinated multi-cellular maze solving system

Control system theory provides convenient tools and concepts for describing and analyzing complex cell functions. In this paper we demonstrate the use of control theory to forward-engineer a complex synthetic gene network constructed from several modular components. Specifically, we present the design and simulation of a synthetic multi-cellular maze-solving system. Here, bacterial cells are programmed to use artificial cell-to-cell communication and regulatory feedback in order to illuminate the correct path in a user-defined maze of cells arranged on a surface. Simulations were used to analyze the systems spatiotemporal dynamics and sensitivity to various kinetic parameters. Experiments with Escherichia coli were carried out to characterize the diffusion properties of artificial cell-to-cell communication based on bacterial quorum sensing systems. The rational design process and simulation tools employed in this study provide an example for future engineering of complex synthetic gene networks comprising multiple control system motifs.

Reformatting test patterns for testing embedded core based system using test access mechanism (TAM) switch [SoC]

In this paper, a new algorithm for reformatting the test vector of system on chip (SOC) with test access mechanism (TAM) has been proposed. Exhaustive experimentation has been conducted by employing random reformatted test vectors for a variety of SOCs, constructed with the ISCAS sequential benchmark circuits. For a limited number of input pins, which have been provided for testing the SOC, the proposed algorithm drastically reduces the test-time as well as the hardware.