DNA as a universal substrate for chemical kinetics

Molecular programming aims to systematically engineer molecular and chemical systems of autonomous function and ever-increasing complexity. A key goal is to develop embedded control circuitry within a chemical system to direct molecular events. Here we show that systems of DNA molecules can be constructed that closely approximate the dynamic behavior of arbitrary systems of coupled chemical reactions. By using strand displacement reactions as a primitive, we construct reaction cascades with effectively unimolecular and bimolecular kinetics. Our construction allows individual reactions to be coupled in arbitrary ways such that reactants can participate in multiple reactions simultaneously, reproducing the desired dynamical properties. Thus arbitrary systems of chemical equations can be compiled into real chemical systems. We illustrate our method on the Lotka–Volterra oscillator, a limit-cycle oscillator, a chaotic system, and systems implementing feedback digital logic and algorithmic behavior

Deterministic and stochastic descriptions of gene expression dynamics

A key goal of systems biology is the predictive mathematical description of gene regulatory circuits. Different approaches are used such as deterministic and stochastic models, models that describe cell growth and division explicitly or implicitly etc. Here we consider simple systems of unregulated (constitutive) gene expression and compare different mathematical descriptions systematically to obtain insight into the errors that are introduced by various common approximations such as describing cell growth and division by an effective protein degradation term. In particular, we show that the population average of protein content of a cell exhibits a subtle dependence on the dynamics of growth and division, the specific model for volume growth and the age structure of the population. Nevertheless, the error made by models with implicit cell growth and division is quite small. Furthermore, we compare various models that are partially stochastic to investigate the impact of different sources of (intrinsic) noise. This comparison indicates that different sources of noise (protein synthesis, partitioning in cell division) contribute comparable amounts of noise if protein synthesis is not or only weakly bursty. If protein synthesis is very bursty, the burstiness is the dominant noise source, independent of other details of the model. Finally, we discuss two sources of extrinsic noise: cell-to-cell variations in protein content due to cells being at different stages in the division cycles, which we show to be small (for the protein concentration and, surprisingly, also for the protein copy number per cell) and fluctuations in the growth rate, which can have a significant impact.Comment: 23 pages, 5 figures; Journal of Statistical physics (2012

Complex and unexpected dynamics in simple genetic regulatory networks

Peer reviewedPublisher PD

CRISPR transcriptional repression devices and layered circuits in mammalian cells

A key obstacle to creating sophisticated genetic circuits has been the lack of scalable device libraries. Here we present a modular transcriptional repression architecture based on clustered regularly interspaced palindromic repeats (CRISPR) system and examine approaches for regulated expression of guide RNAs in human cells. Subsequently we demonstrate that CRISPR regulatory devices can be layered to create functional cascaded circuits, which provide a valuable toolbox for engineering purposes.National Institutes of Health (U.S.) (Grant 5R01CA155320-04)National Institutes of Health (U.S.) (Grant P50 GM098792)Korea (South). Ministry of Science, Information and Communication Technolgy. Intelligent Synthetic Biology Center of Global Frontier Project (2013M3A6A8073557

Genetically encoded sender-receiver system in 3D mammalian cell culture

Engineering spatial patterning in mammalian cells, employing entirely genetically encoded components, requires solving several problems. These include how to code secreted activator or inhibitor molecules and how to send concentration-dependent signals to neighboring cells, to control gene expression. The Madin-Darby Canine Kidney (MDCK) cell line is a potential engineering scaffold as it forms hollow spheres (cysts) in 3D culture and tubulates in response to extracellular hepatocyte growth factor (HGF). We first aimed to graft a synthetic patterning system onto single developing MDCK cysts. We therefore developed a new localized transfection method to engineer distinct sender and receiver regions. A stable reporter line enabled reversible EGFP activation by HGF and modulation by a secreted repressor (a truncated HGF variant, NK4). By expanding the scale to wide fields of cysts, we generated morphogen diffusion gradients, controlling reporter gene expression. Together, these components provide a toolkit for engineering cell-cell communication networks in 3D cell culture.Facultad de Ciencias Exacta

Multi-objective optimization of genome-scale metabolic models: the case of ethanol production

Ethanol is among the largest fermentation product used worldwide, accounting for more than 90% of all biofuel produced in the last decade. However current production methods of ethanol are unable to meet the requirements of increasing global demand, because of low yields on glucose sources. In this work, we present an in silico multi-objective optimization and analyses of eight genome-scale metabolic networks for the overproduction of ethanol within the engineered cell. We introduce MOME (multi-objective metabolic engineering) algorithm, that models both gene knockouts and enzymes up and down regulation using the Redirector framework. In a multi-step approach, MOME tackles the multi-objective optimization of biomass and ethanol production in the engineered strain; and performs genetic design and clustering analyses on the optimization results. We find in silico E. coli Pareto optimal strains with a knockout cost of 14 characterized by an ethanol production up to 19.74mmolgDW−1h−1 (+832.88% with respect to wild-type) and biomass production of 0.02h−1 (−98.06% ). The analyses on E. coli highlighted a single knockout strategy producing 16.49mmolgDW−1h−1 (+679.29% ) ethanol, with biomass equals to 0.23h−1 (−77.45% ). We also discuss results obtained by applying MOME to metabolic models of: (i) S. aureus; (ii) S. enterica; (iii) Y. pestis; (iv) S. cerevisiae; (v) C. reinhardtii; (vi) Y. lipolytica. We finally present a set of simulations in which constrains over essential genes and minimum allowable biomass were included. A bound over the maximum allowable biomass was also added, along with other settings representing rich media compositions. In the same conditions the maximum improvement in ethanol production is +195.24%

A Guide to Simple and Informative Binding Assays

The aim of binding assays is to measure interactions between two molecules, such as a protein binding another protein, a small molecule, or a nucleic acid. Hard work is required to prepare reagents, but flaws in the design of many binding experiments limit the information obtained. In particular many experiments fail to measure the affinity of the reactants for each other. This essay describes simple methods to get the most out of valuable reagents in binding experiments

Kernel Architecture of the Genetic Circuitry of the Arabidopsis Circadian System

A wide range of organisms features molecular machines, circadian clocks, which generate endogenous oscillations with ~24 h periodicity and thereby synchronize biological processes to diurnal environmental fluctuations. Recently, it has become clear that plants harbor more complex gene regulatory circuits within the core circadian clocks than other organisms, inspiring a fundamental question: are all these regulatory interactions between clock genes equally crucial for the establishment and maintenance of circadian rhythms? Our mechanistic simulation for Arabidopsis thaliana demonstrates that at least half of the total regulatory interactions must be present to express the circadian molecular profiles observed in wild-type plants. A set of those essential interactions is called herein a kernel of the circadian system. The kernel structure unbiasedly reveals four interlocked negative feedback loops contributing to circadian rhythms, and three feedback loops among them drive the autonomous oscillation itself. Strikingly, the kernel structure, as well as the whole clock circuitry, is overwhelmingly composed of inhibitory, rather than activating, interactions between genes. We found that this tendency underlies plant circadian molecular profiles which often exhibit sharply-shaped, cuspidate waveforms. Through the generation of these cuspidate profiles, inhibitory interactions may facilitate the global coordination of temporally-distant clock events that are markedly peaked at very specific times of day. Our systematic approach resulting in experimentally-testable predictions provides insights into a design principle of biological clockwork, with implications for synthetic biology.Comment: Supplementary material is available at the journal websit

DAAM is required for thin filament formation and Sarcomerogenesis during muscle development in Drosophila.

During muscle development, myosin and actin containing filaments assemble into the highly organized sarcomeric structure critical for muscle function. Although sarcomerogenesis clearly involves the de novo formation of actin filaments, this process remained poorly understood. Here we show that mouse and Drosophila members of the DAAM formin family are sarcomere-associated actin assembly factors enriched at the Z-disc and M-band. Analysis of dDAAM mutants revealed a pivotal role in myofibrillogenesis of larval somatic muscles, indirect flight muscles and the heart. We found that loss of dDAAM function results in multiple defects in sarcomere development including thin and thick filament disorganization, Z-disc and M-band formation, and a near complete absence of the myofibrillar lattice. Collectively, our data suggest that dDAAM is required for the initial assembly of thin filaments, and subsequently it promotes filament elongation by assembling short actin polymers that anneal to the pointed end of the growing filaments, and by antagonizing the capping protein Tropomodulin

Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.National Institutes of Health (U.S.) (Grant # 7R01GM74712-5)United States. Defense Advanced Research Projects Agency (contract HR0011-10-C-0168)National Science Foundation (U.S.) (NSF CAREER award 0968682)BBN Technologie