Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

Joao G.R. Cardoso, Kristian Jensen, Christian Lieven, Anne Sofie Lærke Hansen, Svetlana Galkina, Moritz Beber, Emre Özdemir, Markus J. Herrgård, Henning Redestig, Nikolaus Sonnenschein*

*Corresponding author for this work

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Abstract

Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, for the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio.
Original languageEnglish
JournalA C S Synthetic Biology
Volume7
Issue number4
Pages (from-to)1163-1166
ISSN2161-5063
DOIs
Publication statusPublished - 2018

Bibliographical note

This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium,
provided the author and source are cited.

Keywords

  • Metabolic engineering
  • Genome-scale metabolic models
  • Heterologous pathway predictions
  • Computer-aided design
  • Software
  • Python

Projects

DD-DeCaF: Bioinformatics Services for Data-Driven Design of Cell Factories and Communities

Herrgard, M., Sonnenschein, N., Kutuzova, S., Redestig, N. H., Beber, M. E., Dannaher, D., Lopez Benito, A., Kaafarani, A., Lieven, C., Lohmann, R., Rasmussen, B. K., Kjiproski, D. & Beck Knudsen, E.

Horizon 2020

01/03/201629/02/2020

Project: Research

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