Mario Andrea Marchisio

Ph.D   Associate Professor

Phone: +8615846331344

Email: marchisio@hit.edu.cn

Research Area: Synthetic Biology

Mario Andrea Marchisio got a Master’s Degree in Physics at the University of Eastern Piedmont (Alessandria, Italy) in 1999 and a PhD in Physics at the University of Trento (Italy) in 2002. He worked for four years at CILEA computing center close to Milan (Italy) where he got involved in national and international projects in Bioinformatics. In 2007 he joined,as a Post Doc, the Computational Systems Biology group at the ETH Zurich (Switzerland) where he worked for six years,first in computational and then in experimental Synthetic Biology. Since September 2013 he is Associate Professor at the HIT-School of Life Science and Technology.

 Research description

Synthetic Biology is a fairly new discipline often referred to as “engineering of life”. The main idea is to rationally re-design cell components (DNA, mRNA, signaling or metabolic pathways) in such a way that the host organism performs new functions, different from its natural ones.  To this aim Synthetic Biology requires mathematical modeling, computer simulations, and wet-lab experiments.

The Synthetic Biology lab research follows two main directions:

1)     Biosensing device implementation in yeast cells.Biosensors are genetic circuits that return an output (e.g. fluorescence) in response to the presence of some particular chemicals around the cells. They can find application in diagnostics, cure of diseases, and environmental care. As in electronics, biosensors are digital circuits i.e. their inputs and output take only two possible values: 0 and 1 corresponding to small and high chemical concentrations or fluorescence levels. In biology, digital behavior is achieved via transcription and translation control mechanisms and requires the engineering and characterizationof regulated promoters and mRNA.

2)     Computational design and modeling of gene circuits.  Starting point is the software “Parts & Pools” that makes use of ProMoT—forthe visual,modular design of gene circuits—and BioNetGen, for the rule-based modeling of eukaryotic cells. “Parts & Pools” is going to be expanded with new features in order to achieve predictive models for the biosensors that will be constructed in our lab and other synthetic gene networks to be hosted both in prokaryotic and eukaryotic cells. 

Publications

1)     Parts & Pools: a frameworkfor modular design ofsyntheticgenecircuits, M. A. Marchisio, Frontiers Bioeng. Biotech., doi:10/3389/fbioe.2014.00042

2)      In silico design and in vivo implementationofyeastgene Boolean gates, M. A. Marchisio, J. Biol. Eng., 8:6  (2014), doi:10.1186/1754-1611-8-6.

3)     Modular, rule-based modeling for the design of eukaryotic synthetic gene circuits, M.A. Marchisio, M. Colaiacovo, E. Whitehead, and J. Stelling. BMC Systems Biology 7, 42 (2013)

4)     Synthetic biosensing systems, M.A. Marchisio and F. Rudolf ,Int. J. Of Biochemistry and Cell Biology, 43(3),310-319 (2011), doi: 10.1016/j.biocel.2010.11.012

5)     Automatic Design of Digital Synthetic Gene Circuits, M.A. Marchisio and J. Stelling,PLoS Comp. Biol. 7(2) (2011),doi: 10.1371/journal.pcbi.1001083

6)     Computational Design Tools for Synthetic Biology,M.A. Marchisio and J. Stelling, Curr. Op. Biotech.20, 479-485 (2009), doi:10.1016/j.copbio.2009.08.007

7)     Synthetic gene network computational design, M.A. Marchisio and J. Stelling, Proc. IEEE International Symposium on Circuits and Systems (ISCAS 2009), 309-312

8)     Computational design of synthetic gene circuits with composable parts, M.A. Marchisio and J. Stelling, Bioinformatics24(17),1903-1910 (2008), doi:10.1093/bioinformatics/btn330.

Book Chapters

1.      Modular design of synthetic gene circuits with biological Parts and Pools, M.A. Marchisio, Methods in Molecular Biology Vol. 1244: Computational Methods in Synthetic Biology. Edited by Marchisio M.A., Springer-Verlag (in press).

2.      Simplified computational design of syntheticgene digital circuits, M.A. Marchisio and J. Stelling, A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems(pp. 257-272). Edited by V. Kulkarniet al., Springer-Verlag (2014)

3.      In silico implementation of synthetic gene networks, M.A Marchisio, Methods in Molecular Biology Vol. 813 (3-21): Synthetic Gene Networks. Edited by W. Weber and M. Fussenegger, Springler-Verlag (2012)

4.      Synthetic Biology: Dynamic Modeling and Construction of Cell Systems, T.T. Marquez-Lago and M.A. Marchisio, Process Systems Engineering. Vol. 7 (493-544): Dynamic Process Modeling. Edited by E.N. Pistikopouloset al., WILEY-VCH (2010).