User:Olivier Borkowski
Contact Info
- Olivier Borkowski, Paris, France
- email: olivier.borkowski[at]inrae.fr
- scholar: https://scholar.google.com/citations?hl=en&user=YV-nMcUAAAAJ
- twitter: @O_Borkowski (https://twitter.com/O_Borkowski)
- https://sites.google.com/view/olivierborkowski
Current lab
- Tenured Research Scientist (CRCN) INRAE, Université Paris-Saclay, AgroParisTech (Paris area, France)
Past lab experiences
- Drew Endy Lab, Stanford University, USA (https://engineering.stanford.edu/people/drew-endy)
- Tom Ellis Lab, Imperial College London, UK (https://www.tomellislab.com/)
- Jean-Loup Faulon Lab, INRAE & Genopole, France (https://www.jfaulon.com/)
- Inbio - Grégory Batt Lab, Institut Pasteur Paris / Inria, France (https://research.pasteur.fr/en/team/inbio/)
Education
- 2013, PhD, Université de Paris
- 2008, MS/Engineer degree, Graduate School of Life Sciences of Toulouse (ENSAT)
Research interests
- Molecular Biology
- Cell-free synthetic biology
- Resource competition
- Transcription/Translation processes
- Feedback control system
- Bacteria, Yeast
- and more (or less)
Publications
- Borkowski O, Goelzer A, Schaffer M, Calabre M, Mäder U, Aymerich S, Jules M, and Fromion V. Translation elicits a growth rate-dependent, genome-wide, differential protein production in Bacillus subtilis. Mol Syst Biol. 2016 May 17;12(5):870. DOI:10.15252/msb.20156608 |
- Borkowski O, Gilbert C, and Ellis T. SYNTHETIC BIOLOGY. On the record with E. coli DNA. Science. 2016 Jul 29;353(6298):444-5. DOI:10.1126/science.aah4438 |
- Borkowski O, Ceroni F, Stan GB, and Ellis T. Overloaded and stressed: whole-cell considerations for bacterial synthetic biology. Curr Opin Microbiol. 2016 Oct;33:123-130. DOI:10.1016/j.mib.2016.07.009 |
- Ceroni F, Boo A, Furini S, Gorochowski TE, Borkowski O, Ladak YN, Awan AR, Gilbert C, Stan GB, and Ellis T. Burden-driven feedback control of gene expression. Nat Methods. 2018 May;15(5):387-393. DOI:10.1038/nmeth.4635 |
- Borkowski O, Bricio C, Murgiano M, Rothschild-Mancinelli B, Stan GB, and Ellis T. Cell-free prediction of protein expression costs for growing cells. Nat Commun. 2018 Apr 13;9(1):1457. DOI:10.1038/s41467-018-03970-x |
- Koch M, Faulon JL, and Borkowski O. Models for Cell-Free Synthetic Biology: Make Prototyping Easier, Better, and Faster. Front Bioeng Biotechnol. 2018;6:182. DOI:10.3389/fbioe.2018.00182 |
- Koch M, Pandi A, Borkowski O, Batista AC, and Faulon JL. Custom-made transcriptional biosensors for metabolic engineering. Curr Opin Biotechnol. 2019 Oct;59:78-84. DOI:10.1016/j.copbio.2019.02.016 |
- Pandi A, Grigoras I, Borkowski O, and Faulon JL. Optimizing Cell-Free Biosensors to Monitor Enzymatic Production. ACS Synth Biol. 2019 Aug 16;8(8):1952-1957. DOI:10.1021/acssynbio.9b00160 |
- Borkowski O, Koch M, Zettor A, Pandi A, Batista AC, Soudier P, and Faulon JL. Large scale active-learning-guided exploration for in vitro protein production optimization. Nat Commun. 2020 Apr 20;11(1):1872. DOI:10.1038/s41467-020-15798-5 |
-
Borkowski O, Drew E, Subsoontorn P. Hands-free control of heterologous gene expression in batch cultures (https://doi.org/10.1101/150375)
-
Synthetic Biology at the Hand of Cell-Free Systems (https://doi.org/10.1007/978-981-15-0081-7_16)
-
Advances and applications of cell-free systems for metabolic production (https://doi.org/10.1016/B978-0-12-821477-0.00008-8)
-
Nature Research Bioengineering Community: Active learning leads to highly efficient predictions in cell-free systems (https://bioengineeringcommunity.nature.com/users/382588-olivier-borkowski/posts/66375-active-learning-leads-to-highly-efficient-predictions-in-cell-free-systems)
-
EuSynBioS: Optimization of cell-free biosensors for synthetic biology (https://www.eusynbios.org/blog/2019/9/2/optimization-of-cell-free-biosensors-for-synthetic-biology)
Useful links
