SynBioFromLeukipposInstitute

Paris, June 11-12, 2012

Gilles Charvin (IGMBC, France): Continuous monitoring of the transition to replicative senescence in single yeast cells,

Hidde de Jong (INRIA, France): Local and global regulators of the dynamic adaptation of gene expression in bacteria,

Diego di Bernardo (Tigem, Italy): Modelling and control of gene networks: from yeast to mammals,

In yeast, we describe the development and application of a method to control at will the dynamic behavior of a gene network in a growing population cells. We designed and implemented an integrated platform based on a microfluidic device, a time-lapse microscopy apparatus, and a set of actuated syringes, all controlled by a computer. We tested the platform to force yeast cells to express a desired time-varying amount of a reporter gene, part of a complex gene network, over thousands of minutes, by automatically switching the type of sugar administered to the cells, its concentration and its duration. In mammalian cells, we used a modified microfludics platform to characterise the dynamical properties and robustness to noise of a circuit we synthetically engineered in mammalian cells. The circuit mimics a common motif found in transcriptional regulation, consisting of a transcription factor regulating its own transcription (Positive Feedback Loop) as well as, transcription of a microRNA against itself (Negative Feedback Loop).

Alfonso Jaramillo (ISSB, France): Engineering transcriptional and post-transcriptional circuits with targeted behavior in E. coli,

The design and implementation of small synthetic genetic circuits for cell reprogramming is propelling the emerging field of Synthetic Biology. We will describe our recent results on the engineering of small synthetic circuits and their characterization in E. coli. We will show our recent results on the design of circuits made of either RNA or transcription factors. In the first case, we will describe the first fully automated design methodology and experimental validation of synthetic RNA interaction circuits in living cells. We tested our methodology in E. coli by designing several positive riboregulators with diverse structures and interaction models. The designed sequences exhibit very low similarity to any known non-coding RNA sequence. Our riboregulatory devices can work independently and in combination with transcription regulation to create complex logic circuits. In the second case, we describe the construction and characterisation in E. coli of minimal gene networks with oscillatory behaviour. We use microfluidic techniques to track the single-cell dynamics for several days. We have also engineered two coupled oscillators in a single cell. Coupling of two oscillators is known in physics to generate a number of interesting dynamical behaviours. The resulting function could represent a simple super-position of the dynamical behaviour or it could lock into several possible characteristic frequencies, or even it could have several characteristic properties, depending on the conditions of the experiment. To analyse these effects in vivo we designed and constructed several genetic parts that allow us characterizing the dynamical behaviour of coupled oscillator systems in bacteria.

Eric Klavins (U. Washington, USA): Toward engineered multi-cell behaviors,

A combination of internal logic, control of growth and division, and cell-cell communication must coordinate the behaviors of a growing organism so that it differentiates correctly in time and space, in spite of environmental perturbations, and intrinsic or extrinsic noise. Although several formalisms have been defined to describe development, the relationship between high level programs and the possible biochemical implementation of those programs in micro-organisms is tenuous. Said differently, it is unknown whether the basic mechanisms available to the synthetic biologist are sufficient to implement the pattern formation algorithms defined at higher levels. In my talk I will describe (1) our progress toward a framework for engineering multi-celled behaviors based on formal methods; (2) several pattern formation algorithms that may be simple enough to implement in cells; (3) experimental results with yeast and E. coli in which we demonstrate modules that control state, transduce signals, or use noise to implement aspects of the multi-cellular control systems systems we envisage.

Heinz Koeppl (ETHZ, Switzerland)Optimal perturbations for the identification of stochastic reaction dynamics,

Identification of stochastic reaction dynamics inside the cell is hampered by the low- dimensional readouts available with todays measurement technology. Moreover, such processes are poorly excited by standard experimental protocols, making identification even more ill-posed. Recent technological advances provide means to design and apply complex extra-cellular stimuli. Based on an information-theoretic framework we provide novel Monte Carlo sampling techniques to determine optimal temporal excitations profiles for such processes. These optimal control policies should aid in alleviating the ill-posedness in identification but moreover provide new means to control cell environments for synthetic biology. We give a new result for the controlled birth-death process, present numerical results for a simple model of regulated gene expression and discuss the experimental challenges.

Wendell Lim (UCSF, USA): Learning to program cell signaling,

Ariel Lindner (INSERM, France),

John Lygeros (ETHZ, Switzerland): In silico control of gene expression in yeast,

Feedback mechanisms are at the heart of many cell functions, including genetic regulation. Engineering such mechanisms synthetically has proved to be a challenging task, however. This is partly due to the difficulties associated with making the process robust against cell-to-cell variability, cross-talk and antagonism from other cell functions, etc. Here we show how the performance of synthetic biological circuits can be improved by the addition of an external feedback loop, closed over the computer. We demonstrate this in silico feedback concept by using it to robustly regulate the expression of a gene in yeast, exploiting a light source and a light-sensitive transcription factor as a control input and flow cytometry measurements of protein concentration to close the loop. The in silico controller is based on Model Predictive Control and a Kalman filter to estimate unmeasured states.

Brian Munsky (LANL, USA): Using spatial and temporal fluctuations to identify predictive quantitative models of gene regulatory pathways,

Despite vast amounts of biochemical information, it remains difficult to quantitatively capture (let alone understand or predict) the spatiotemporal responses of signal transduction and gene regulatory pathways. In this talk, I will discuss recent results to integrate single-molecule and single-cell experiments with simple spatial stochastic analyses, with the resulting goal of identifying and validating quantitatively predictive models of transcriptional dynamics. I will use a couple simple computational studies to show how different fluctuations over time, over space, and from cell-to-cell each contain unique and useful information that helps improve the identification procedure. I will illustrate our integrated experimental and computational identification approach on a stress response pathway in yeast as well as on a host-pathogen interaction in mammalian cells. In each case study, I will show how we can generate large numbers of different model structures and use parameter estimation and uncertainty quantification analyses to determine the best model with the greatest predictive capability. I will discuss how these models yield new insight into biological dynamics, illustrate how these models can be used to predict the transcriptional responses in new conditions, and comment on the use of such models to help optimize or control gene regulatory behaviors.

Guy-Bart Stan (Imperial college, UK): Taking a systems control approach in biology,

In this talk I will give an overview of some of the research activities in my group, the "Control Engineering Synthetic Biology" group at Imperial College London. In particular, I will cover two lines of research (if time allows): (a) exogenous data-based optimal control of synthetic gene circuits, and (b) endogenous control of metabolic pathways through the design of enzymatic gene regulation networks.
(a) The use of traditional model-based optimal control methods to intervene on poorly characterised or unknown biological systems has so far met limited success. This is mostly due to the high level of model uncertainty and very limited knowledge on the biological systems to be controlled, rendering quite hard the a priori identification of a dynamical model. Taking a different approach to the problem, this talk will present research results pertaining to the inference of (close-to) optimal feedback control strategies directly from input-output measurements of biological systems (natural or synthetic), i.e., without the need for identifying a mathematical model of the system's dynamics a priori. To illustrate the methodology, we will show simulation results obtained by running a recently proposed batch-mode reinforcement learning algorithm, known as fitted Q iteration, on numerically generated data containing noise and outliers. The examples discussed include inference of optimal control strategies for two Synthetic Biology genetic constructs: the toggle switch and the generalised repressilator.
(b) Among Synthetic Biology's most prominent applications is the manipulation of bacterial metabolism for producing high-value chemicals in diverse sectors such as energy, biomedicine and food technology. In this project we are developing foundational tools for the analysis and design of synthetic biodevices that regulate bacterial metabolism according to pre-defined objectives. The genetic controllers act by adjusting enzyme transcription in response to changes in the metabolites of interest. When choosing a particular controller, we need to design its "wiring", choose its logic, and fine-tune its parameters. The wiring specifies which metabolites control which enzymes, whereas the logic defines whether gene transcription is activated or repressed. The controller parameters are typically the strength of the promoters and ribosomal binding sites. Because these controllers are intracellular, they have a great potential for applications where cellular behaviour needs to be controlled without real-time human intervention.

Ron Weiss (MIT, USA): Integrated computational and experimental approach to engineering complex behavior in living systems,

Synthetic biology is revolutionizing how we conceptualize and approach the engineering of biological systems. Recent advances in the field are allowing us to expand beyond the construction and analysis of small gene networks towards the implementation of complex multicellular systems with a variety of applications. In this talk Ron Weiss will describe his integrated computational and experimental approach to engineering complex behavior in living systems ranging from bacteria to stem cells. In his research, he appropriates useful design principles from electrical engineering and other well established fields. These principles include abstraction, standardization, modularity, and computer aided design. But he also spends considerable effort towards understanding what makes synthetic biology different from all other existing engineering disciplines and discovering new design and construction rules that are effective for this unique discipline.
Weiss will briefly describe the implementation of genetic circuits with finely-tuned digital and analog behavior and the use of artificial cell-cell communication to coordinate the behavior of cell populations for programmed pattern formation. Recent results with implementing Turing patterns with engineering bacteria will be presented. Arguably the most significant contribution of synthetic biology will be in medical applications such as tissue engineering. He will discuss preliminary experimental results for obtaining precise spatiotemporal control over stem cell differentiation. For this purpose, he couples elements for gene regulation, cell fate determination, signal processing, and artificial cell-cell communication. He will conclude by discussing the design and preliminary results for creating an artificial tissue homeostasis system where genetically engineered stem cells maintain indefinitely a desired level of pancreatic beta cells despite attacks by the autoimmune response. The system, which relies on artificial cell-cell communication, various regulatory network motifs, and programmed differentiation into beta cells, may one day be useful for the treatment (or cure) of diabetes.

 

02-16-12 11am PST, Cynthia Collins from RPI to give virtual seminar.
02-02-12 Jared Toettcher from UCSF gave a talk at the synthetic biology seminar series.
12-14-11 NASA-Supported Student Team Wins at International Genetic Engineering Contest
8-18-11 James Carothers of UC Berkeley / JBEI spoke at NASA Ames
05-16-11 Craig Venter's Keynote Talk from our synthetic biology workshop is now on-line.
04-28-11 NASA Ames, job opening in synthetic biology.
11-19-10 Join our announcements mailing list
10-31-10 NASA Ames holds synthetic biology workshop

About the initiative
The synthetic biology initiative at NASA Ames is designed to harness biology in reliable, robust, engineered systems to support NASA’s exploration and science missions, to improve life on Earth, and to help shape NASA’s future. The initiative is also intended to contribute foundational tools to the synthetic biology community.

Biology on Earth readily demonstrates that life is an efficient user of resources around it, turning those resources into habitats, materials and forms that perform various functions. Synthetic biology in space represents a new challenge, the challenge of designing organisms to perform reliable functions that an astronaut may one day depend on. If the promise of an engineerable biology on Earth is within reach the initiative aims to develop applications for synthetic biology in space.

FEBS Letters,Authors:Markus Schmidt; Víctor de Lorenzo...

"The plausible release of deeply engineered or even entirely synthetic/artificial microorganisms raises the issue of their intentional (e.g. bioremediation) or accidental interaction with the Environment. Containment systems designed in the 1980s–1990s for limiting the spread of genetically engineered bacteria and their recombinant traits are still applicable to contemporary Synthetic Biology constructs. Yet, the ease of DNA synthesis and the uncertainty on how non-natural properties and strains could interplay with the existing biological word poses yet again the challenge of designing safe and efficacious firewalls to curtail possible interactions. Such barriers may include xeno-nucleic acids (XNAs) instead of DNA as information-bearing molecules, rewriting the genetic code to make it non-understandable by the existing gene expression machineries, and/or making growth dependent on xenobiotic chemicals."