Evolutionary engineering of E. coli MG1655 for tolerance against isoprenol.

Adaptive laboratory evolution Butanol E. coli Isoprenol Terpenes Tolerance

Journal

Biotechnology for biofuels
ISSN: 1754-6834
Titre abrégé: Biotechnol Biofuels
Pays: England
ID NLM: 101316935

Informations de publication

Date de publication:
09 Nov 2020
Historique:
received: 10 03 2020
accepted: 24 10 2020
entrez: 9 12 2020
pubmed: 10 12 2020
medline: 10 12 2020
Statut: epublish

Résumé

Isoprenol is the basis for industrial flavor and vitamin synthesis and also a promising biofuel. Biotechnological production of isoprenol with E. coli is currently limited by the high toxicity of the final product. Adaptive laboratory evolution (ALE) is a promising method to address complex biological problems such as toxicity. Here we applied this method successfully to evolve E. coli towards higher tolerance against isoprenol, increasing growth at the half-maximal inhibitory concentration by 47%. Whole-genome re-sequencing of strains isolated from three replicate evolutions at seven time-points identified four major target genes for isoprenol tolerance: fabF, marC, yghB, and rob. We could show that knock-out of marC and expression of mutated Rob H(48) → frameshift increased tolerance against isoprenol and butanol. RNA-sequencing showed that the deletion identified upstream of yghB correlated with a strong overexpression of the gene. The knock-out of yghB demonstrated that it was essential for isoprenol tolerance. The mutated Rob protein and yghB deletion also lead to increased vanillin tolerance. Through ALE, novel targets for strain optimization in isoprenol production and also the production of other fuels, such as butanol, could be obtained. Their effectiveness could be shown through re-engineering. This paves the way for further optimization of E. coli for biofuel production.

Sections du résumé

BACKGROUND BACKGROUND
Isoprenol is the basis for industrial flavor and vitamin synthesis and also a promising biofuel. Biotechnological production of isoprenol with E. coli is currently limited by the high toxicity of the final product. Adaptive laboratory evolution (ALE) is a promising method to address complex biological problems such as toxicity.
RESULTS RESULTS
Here we applied this method successfully to evolve E. coli towards higher tolerance against isoprenol, increasing growth at the half-maximal inhibitory concentration by 47%. Whole-genome re-sequencing of strains isolated from three replicate evolutions at seven time-points identified four major target genes for isoprenol tolerance: fabF, marC, yghB, and rob. We could show that knock-out of marC and expression of mutated Rob H(48) → frameshift increased tolerance against isoprenol and butanol. RNA-sequencing showed that the deletion identified upstream of yghB correlated with a strong overexpression of the gene. The knock-out of yghB demonstrated that it was essential for isoprenol tolerance. The mutated Rob protein and yghB deletion also lead to increased vanillin tolerance.
CONCLUSION CONCLUSIONS
Through ALE, novel targets for strain optimization in isoprenol production and also the production of other fuels, such as butanol, could be obtained. Their effectiveness could be shown through re-engineering. This paves the way for further optimization of E. coli for biofuel production.

Identifiants

pubmed: 33292484
doi: 10.1186/s13068-020-01825-6
pii: 10.1186/s13068-020-01825-6
pmc: PMC7653855
doi:

Types de publication

Journal Article

Langues

eng

Pagination

183

Références

Bioinformatics. 2015 Jan 15;31(2):166-9
pubmed: 25260700
Bioinformatics. 2009 Jul 15;25(14):1754-60
pubmed: 19451168
J Mol Biol. 2009 May 8;388(3):415-30
pubmed: 19289129
Nat Biotechnol. 2013 Jan;31(1):46-53
pubmed: 23222703
Microb Cell Fact. 2013 Jul 01;12:64
pubmed: 23815749
J Bacteriol. 2012 Jan;194(2):303-6
pubmed: 22081388
Nat Prod Rep. 2015 Sep 23;32(10):1508-26
pubmed: 26216573
Bioinformatics. 2010 Jan 1;26(1):139-40
pubmed: 19910308
mSystems. 2019 Jun 11;4(4):
pubmed: 31186336
Cell. 2003 Sep 5;114(5):623-34
pubmed: 13678585
Mol Syst Biol. 2011 May 10;7:487
pubmed: 21556065
Appl Environ Microbiol. 2015 May 15;81(10):3316-25
pubmed: 25746998
Metab Eng. 2018 May;47:60-72
pubmed: 29530749
Nat Methods. 2009 May;6(5):343-5
pubmed: 19363495
Mol Syst Biol. 2010 Dec 21;6:449
pubmed: 21179021
Microb Cell Fact. 2014 Sep 12;13:135
pubmed: 25212876
Proc Natl Acad Sci U S A. 2012 Oct 9;109(41):16696-701
pubmed: 23010927
Mol Microbiol. 2003 Jun;48(6):1609-19
pubmed: 12791142
Microb Cell Fact. 2011 Mar 25;10:18
pubmed: 21435272
Mol Syst Biol. 2006;2:2006.0008
pubmed: 16738554
Biotechnol Biofuels. 2018 May 11;11:136
pubmed: 29760777
Appl Environ Microbiol. 1995 Jun;61(6):2302-7
pubmed: 7793951
Antimicrob Agents Chemother. 2014;58(2):923-30
pubmed: 24277026
Metab Eng. 2019 Dec;56:85-96
pubmed: 31499175
Biotechnol Bioeng. 2012 Oct;109(10):2513-22
pubmed: 22539043
Bioinformatics. 2012 Feb 1;28(3):433-5
pubmed: 22155869
J Bacteriol. 2002 Mar;184(5):1407-16
pubmed: 11844771
Extremophiles. 1998 Aug;2(3):239-48
pubmed: 9783171
Appl Microbiol Biotechnol. 2007 Feb;74(2):406-21
pubmed: 17273855
J Mol Biol. 2003 Oct 3;332(5):1015-24
pubmed: 14499605
Science. 2011 Jun 3;332(6034):1190-2
pubmed: 21636771
Appl Microbiol Biotechnol. 2007 Jan;73(5):980-90
pubmed: 17115212
PLoS One. 2008 Feb 06;3(2):e1573
pubmed: 18253509
Appl Environ Microbiol. 2010 Mar;76(6):1935-45
pubmed: 20118358
Genome Biol. 2010;11(10):R106
pubmed: 20979621
Antimicrob Agents Chemother. 2008 Jan;52(1):382-3
pubmed: 17954692
mBio. 2014 Nov 04;5(6):e01932
pubmed: 25370492
Microbiol Mol Biol Rev. 2010 Dec;74(4):570-88
pubmed: 21119018
Science. 2011 Jun 3;332(6034):1193-6
pubmed: 21636772
J Mol Biol. 2008 Jul 4;380(2):278-84
pubmed: 18514222
Bioinformatics. 2013 Jan 1;29(1):15-21
pubmed: 23104886
Int J Food Sci Nutr. 2019 Aug;70(5):595-602
pubmed: 30624146
BMC Mol Biol. 2009 Aug 07;10:79
pubmed: 19660145
Nat Struct Biol. 2000 May;7(5):424-30
pubmed: 10802742
J Struct Funct Genomics. 2009 Apr;10(2):157-63
pubmed: 19058030
J Bacteriol. 2008 Jul;190(13):4489-500
pubmed: 18456815

Auteurs

Heiko Babel (H)

Systems Biotechnology Group, Department of Solar Materials, Helmholtz Centre for Environmental Research-UFZ, Leipziger KUBUS, Permoserstrasse 15, 04318, Leipzig, Germany.
Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riß, Germany.

Jens O Krömer (JO)

Systems Biotechnology Group, Department of Solar Materials, Helmholtz Centre for Environmental Research-UFZ, Leipziger KUBUS, Permoserstrasse 15, 04318, Leipzig, Germany. jens.kroemer@ufz.de.

Classifications MeSH