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Generalized Schemes for High-Throughput Manipulation of the Desulfovibrio vulgaris Genome
Author(s) -
Swapnil R. Chhabra,
Gareth Butland,
Dwayne A. Elias,
JohnMarc Chandonia,
O.-Y. Fok,
Thomas R. Juba,
Alaka Gorur,
S. Allen,
C. M. Leung,
Kimberly L. Keller,
Sonia A. Reveco,
Grant M. Zane,
Elizabeth S. Semkiw,
Ramadevi Prathapam,
B. Gold,
Michael Singer,
Mario Ouellet,
E. D. Szakal,
Danielle M. Jorgens,
Morgan N. Price,
H. Ewa Witkowska,
Harry R. Beller,
Adam P. Arkin,
Terry C. Hazen,
Mark D. Biggin,
Manfred Auer,
Judy D. Wall,
Jay D. Keasling
Publication year - 2011
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.05495-11
Subject(s) - desulfovibrio vulgaris , computational biology , biology , synthetic biology , genome , gene , genome engineering , genome editing , genetics , bacteria
The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA "parts" to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

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