Genome-scale analysis of anti-metabolite directed strain engineering.
Classic strain engineering methods have previously been limited by the low-throughput of conventional sequencing technology. Here, we applied a new genomics technology, scalar analysis of library enrichments (SCALEs), to measure >3 million Escherichia coli genomic library clone enrichment patterns resulting from growth selections employing three aspartic-acid anti-metabolites. Our objective was to assess the extent to which access to genome-scale enrichment patterns would provide strain-engineering insights not reasonably accessible through the use of conventional sequencing. We determined that the SCALEs method identified a surprisingly large range of anti-metabolite tolerance regions (423, 865, or 909 regions for each of the three anti-metabolites) when compared to the number of regions (1-3 regions) indicated by conventional sequencing. Genome-scale methods uniquely enable the calculation of clone fitness values by providing concentration data for all clones within a genomic library before and after a period of selection. We observed that clone fitness values differ substantially from clone concentration values and that this is due to differences in overall clone fitness distributions for each selection. Finally, we show that many of the clones of highest fitness overlapped across all selections, suggesting that inhibition of aspartate metabolism, as opposed to specific inhibited enzymes, dominated each selection. Our follow up studies confirmed our observed growth phenotypes and showed that intracellular amino-acid levels were also altered in several of the identified clones. These results demonstrate that genome-scale methods, such as SCALEs, can be used to dramatically improve understanding of classic strain engineering approaches.
Bonomo
Jeanne
J
Department of Chemical and Biological Engineering, University of Colorado, UCB 424 Boulder, CO 80309, USA.
Lynch
Michael D
MD
Warnecke
Tanya
T
Price
James V
JV
Gill
Ryan T
RT
D000409:Alanine / Q000031:analogs & derivatives / Q000494:pharmacology; D000465:Algorithms; D000963:Antimetabolites / Q000494:pharmacology*; D001216:Asparagine / Q000031:analogs & derivatives / Q000494:pharmacology; D001224:Aspartic Acid / Q000031:analogs & derivatives / Q000037:antagonists & inhibitors / Q000494:pharmacology; D003001:Cloning, Molecular; D020451:Contig Mapping; D004926:Escherichia coli / Q000187:drug effects* / Q000254:growth & development*; D020869:Gene Expression Profiling; D005787:Gene Frequency; D005818:Genetic Engineering / Q000379:methods; D016680:Genome, Bacterial; D015698:Genomic Library; D023281:Genomics / Q000379:methods; D007763:Lac Operon; D016254:Mutagenesis, Insertional; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D010957:Plasmids; D012641:Selection, Genetic
D000963:Antimetabolites; C011274:3-hydroxyaspartic acid; C024848:beta-aspartylhydroxamic acid; C000082:alanosine; D001224:Aspartic Acid; D001216:Asparagine; D000409:Alanine