Introducing our Authors - American Chemical Society

Jun 7, 2016 - College London. Education. Postdoctoral positions at Imperial College. London (2009−2012), The Wellcome Trust Sanger Institute. (2006â...
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Introducing Our Authors pubs.acs.org/synthbio



CHRIS P. BARNES

Current Position. Associate Professor, Institute of Systems and Synthetic Biology, University of Evry-Vald’Essonne, France. I am responsible for the molecular biology wet laboratory of Prof. Jean-Loup Faulon’s research group. Education. Postdoctoral fellow, Institut des Sciences du Végétal, CNRS, Gif sur Yvette, France (2006−2010). Advisor: Dr. Bruno Gronenborn. Ph.D. Biochemistry, Ecole Polytechnique, Palaiseau, France (2005). Advisor: Dr. Pierre Plateau. Nonscientific Interests. Traveling, family life. My current research activities are oriented to metabolic engineering. This field of synthetic biology is facing a major issue that is the lack of enzymes able to catalyze reactions and thus create non-natural pathways. This paper addresses this topic and provides us with a rational computational new way and its experimental validation of finding novel enzymatic activities. I am also a faculty member of the University of Évry-Vald’Essonne where I teach courses in biochemistry, molecular biology, metabolic engineering, and synthetic biology. In addition, I am the deputy director of mSSB, master 2 in Systems and Synthetic Biology, and in charge of the practical courses in synthetic biology and rational protein design dispensed in this master. mSSB is one of the first and few master programs proposed in Europe teaching synthetic biology. (Read Grigoras’ article; DOI: 10.1021/acssynbio.5b00294).

Chris P. Barnes

Current Position. Lecturer/Assistant Professor, University College London. Education. Postdoctoral positions at Imperial College London (2009−2012), The Wellcome Trust Sanger Institute (2006−2009), and CERN/Imperial College London (2005− 2006). Ph.D. High Energy Physics, Imperial College London (2005). MSci Physics, Imperial College London (2001). Nonscientific Interests. Running, hiking, conservation, music. My research interests include the engineering of probiotic bacteria for the understanding of healthy host−microbiota interactions and novel therapeutic interventions. I’m interested in how we can engineer robustness into biological systems using strategies from traditional engineering disciplines and natural biological systems. In this issue, we report a new design and computational modeling framework for selecting gene networks that will perform their function robustly over a wide range of parameter values. We apply this approach to the example of genetic oscillators, which serve as a model for complex behavior and are of wide interest to the biological community. We find a number of novel oscillator designs that are expected to be more robust than those currently constructed. These methods can eventually be used to construct more robust and reliable clinical applications. (Read Barnes’ article; DOI: 10.1021/acssynbio.5b00179).





MIRIAM LEON

IOANA GRIGORAS Robert Stanley

Current Position. Ph.D. Candidate, Department of Cell and Developmental Biology, University College London, London, UK. Supervisor: Dr. Chris P Barnes. Education. MSc in Bioinformatics and Theoretical systems biology, Imperial College London (2012); BSc in Biology, Imperial College London (2011). Nonscientific Interests. I enjoy running, hiking, camping and most of all traveling. Special Issue: IWBDA 2015 Received: June 7, 2016 Ioana Grigoras

© 2016 American Chemical Society

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DOI: 10.1021/acssynbio.6b00164 ACS Synth. Biol. 2016, 5, 446−448

ACS Synthetic Biology



My work focuses on the design of robust synthetic genetic systems. A genetic system must behave reliably if it is to be used successfully in synthetic biology applications. The stochasticity of the cellular environment makes the functioning of such systems challenging, and can cause them to stop behaving as designed. I’ve developed Bayesian methodology to select the most robust designs for multistable stochastic systems. Currently I am working on robust versions of the genetic toggle switch, a system of mutually repressing transcription factors. This framework is a step closer to designing systems that behave predictably in order to use them for industrial or therapeutic applications. (Read Leon’s article; DOI: 10.1021/ acssynbio.5b00179).



Introducing Our Authors

NICHOLAS ROEHNER

Madeline Barr

RUBEN PEREZ-CARRASCO

Current Position. Postdoctoral researcher, Boston University and MIT-Broad Foundry. Advisor: Prof. Douglas Densmore. Education. Ph.D. in Bioengineering (2014), University of Utah; Advisor, Prof. Chris J. Myers. B.S. in Bioengineering (2010), University of Washington. Advisor: Prof. Suzie Pun. Nonscientific Interests. Board games, video games, running, and biking. My primary research interests are in languages, games, and simulation and their potential to support a hierarchy of abstraction for synthetic biology, such that experts with different specialties (such as modelers and builders of biological systems) can effectively communicate across disciplines and complement each other’s work. I believe that these concepts are critical to development of such a hierarchy, owing to their ability to relate concepts from biology and engineering and facilitate a mutual understanding between experts of their respective specialties. I am also interested in the statistical design of biological systems and the relationship between biological data and models of system behavior. (Read Roehner’s articles; DOI: 10.1021/acssynbio.5b00215 and DOI: 10.1021/ acssynbio.5b00232)

Ruben Perez-Carrasco

Current Position. Postdoctoral research associate, Department of Mathematics, University College London; Advisor: Prof. Karen M. Page. Education. Ph.D. Physics, Universitat de Barcelona (2013). Advisor: Prof. J.M. Sancho. M.Sc. Biophysics, Universitat de Barcelona (2008), B.Sc Physics Universitat de Barcelona (2007). Nonscientific Interests. Playing the clarinet and dancing swing music I am fascinated by stochastic processes and self-organization, and got the opportunity to study these during my degree in physics. During a brief stay working as a summer student in christallographic platform diffracting proteins, I became even more interested in the molecular biology of the cell where my favorite topics in physics collide. This led me to my Ph.D. where I studied the stochastic nature of energy transduction at a nanoscopic level in rotatory molecular motors such as the F0F1 ATP-syntase and the bacteria flagellar motor. After that I moved to London where I am focused on studying the dynamics of stochastic genetic networks, currently working with Prof. Karen Page and Dr. James Briscoe where the dynamics of such noisy systems can give rise to the precision necessary for the patterning of embryonic tissues such as the neural tube. (Read PerezCarrasco’s article; DOI: 10.1021/acssynbio.5b00179).



MAE L. WOODS

Mae L. Woods

Current Position. Research Associate at University College, London. Education. Postdoctoral institution: University College London. Advisor: Dr. Chris Barnes. Graduate institution 447

DOI: 10.1021/acssynbio.6b00164 ACS Synth. Biol. 2016, 5, 446−448

ACS Synthetic Biology

Introducing Our Authors

University College London. Undergraduate institution King’s College London. Nonscientific Interests. When I’m not in the lab, I play the french horn and piano. I also like to paint and run marathons. I enjoy watching the ballet and ice skating. I use experimental data to design and simulate mathematical models, from which the model can be used to interpret implicit properties of the system under study. However, there are some instances when theory can be applied to provide predictions in experimental design. This is the case in the article presented in this issue of ACS Synthetic Biology, where we combine theory on robustness and Bayesian model selection to determine new oscillator systems that could potentially be constructed. (Read Woods’ article; DOI: 10.1021/acssynbio.5b00179).

448

DOI: 10.1021/acssynbio.6b00164 ACS Synth. Biol. 2016, 5, 446−448