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Anné J, Vrancken K, Van Mellaert L, Van Impe J, Bernaerts K. Protein secretion biotechnology in Gram-positive bacteria with special emphasis on Streptomyces lividans. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2014; 1843:1750-61. [PMID: 24412306 DOI: 10.1016/j.bbamcr.2013.12.023] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2013] [Revised: 12/26/2013] [Accepted: 12/31/2013] [Indexed: 02/07/2023]
Abstract
Proteins secreted by Gram-positive bacteria are released into the culture medium with the obvious benefit that they usually retain their native conformation. This property makes these host cells potentially interesting for the production of recombinant proteins, as one can take full profit of established protocols for the purification of active proteins. Several state-of-the-art strategies to increase the yield of the secreted proteins will be discussed, using Streptomyces lividans as an example and compared with approaches used in some other host cells. It will be shown that approaches such as increasing expression and translation levels, choice of secretion pathway and modulation of proteins thereof, avoiding stress responses by changing expression levels of specific (stress) proteins, can be helpful to boost production yield. In addition, the potential of multi-omics approaches as a tool to understand the genetic background and metabolic fluxes in the host cell and to seek for new targets for strain and protein secretion improvement is discussed. It will be shown that S. lividans, along with other Gram-positive host cells, certainly plays a role as a production host for recombinant proteins in an economically viable way. This article is part of a Special Issue entitled: Protein trafficking and secretion in bacteria. Guest Editors: Anastassios Economou and Ross Dalbey.
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Affiliation(s)
- Jozef Anné
- Rega Institute for Medical Research, Katholieke Universiteit Leuven, Laboratory of Molecular Bacteriology, Herestraat 49, box 1037, B-3000 Leuven, Belgium.
| | - Kristof Vrancken
- Rega Institute for Medical Research, Katholieke Universiteit Leuven, Laboratory of Molecular Bacteriology, Herestraat 49, box 1037, B-3000 Leuven, Belgium.
| | - Lieve Van Mellaert
- Rega Institute for Medical Research, Katholieke Universiteit Leuven, Laboratory of Molecular Bacteriology, Herestraat 49, box 1037, B-3000 Leuven, Belgium.
| | - Jan Van Impe
- Chemical and Biochemical Process Technology and Control Section (BioTeC), Department of Chemical Engineering, KU Leuven, Willem de Croylaan 46 box 2423, B-3001 Leuven, Belgium.
| | - Kristel Bernaerts
- Chemical and Biochemical Process Technology and Control Section (BioTeC), Department of Chemical Engineering, KU Leuven, Willem de Croylaan 46 box 2423, B-3001 Leuven, Belgium.
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Guimaraes JC, Rocha M, Arkin AP, Cambray G. D-Tailor: automated analysis and design of DNA sequences. ACTA ACUST UNITED AC 2014; 30:1087-1094. [PMID: 24398007 PMCID: PMC3982154 DOI: 10.1093/bioinformatics/btt742] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2013] [Accepted: 12/17/2013] [Indexed: 11/30/2022]
Abstract
Motivation: Current advances in DNA synthesis, cloning and sequencing technologies afford high-throughput implementation of artificial sequences into living cells. However, flexible computational tools for multi-objective sequence design are lacking, limiting the potential of these technologies. Results: We developed DNA-Tailor (D-Tailor), a fully extendable software framework, for property-based design of synthetic DNA sequences. D-Tailor permits the seamless integration of multiple sequence analysis tools into a generic Monte Carlo simulation that evolves sequences toward any combination of rationally defined properties. As proof of principle, we show that D-Tailor is capable of designing sequence libraries comprising all possible combinations among three different sequence properties influencing translation efficiency in Escherichia coli. The capacity to design artificial sequences that systematically sample any given parameter space should support the implementation of more rigorous experimental designs. Availability: Source code is available for download at https://sourceforge.net/projects/dtailor/ Contact:aparkin@lbl.gov or cambray.guillaume@gmail.com Supplementary information:Supplementary data are available at Bioinformatics online (D-Tailor Tutorial).
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Affiliation(s)
- Joao C Guimaraes
- Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Miguel Rocha
- Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Adam P Arkin
- Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Guillaume Cambray
- Department of Bioengineering, California Institute for Quantitative Biosciences, University of California, Berkeley, CA, 94720, USA, Computer Science and Technology Center, School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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Gaspar P, Moura G, Santos MAS, Oliveira JL. mRNA secondary structure optimization using a correlated stem-loop prediction. Nucleic Acids Res 2013; 41:e73. [PMID: 23325845 PMCID: PMC3616703 DOI: 10.1093/nar/gks1473] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Secondary structure of messenger RNA plays an important role in the bio-synthesis of proteins. Its negative impact on translation can reduce the yield of protein by slowing or blocking the initiation and movement of ribosomes along the mRNA, becoming a major factor in the regulation of gene expression. Several algorithms can predict the formation of secondary structures by calculating the minimum free energy of RNA sequences, or perform the inverse process of obtaining an RNA sequence for a given structure. However, there is still no approach to redesign an mRNA to achieve minimal secondary structure without affecting the amino acid sequence. Here we present the first strategy to optimize mRNA secondary structures, to increase (or decrease) the minimum free energy of a nucleotide sequence, without changing its resulting polypeptide, in a time-efficient manner, through a simplistic approximation to hairpin formation. Our data show that this approach can efficiently increase the minimum free energy by >40%, strongly reducing the strength of secondary structures. Applications of this technique range from multi-objective optimization of genes by controlling minimum free energy together with CAI and other gene expression variables, to optimization of secondary structures at the genomic level.
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Affiliation(s)
- Paulo Gaspar
- DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
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