A genomics approach to improve the analysis and design of strain selections.

Strain engineering has been traditionally centered on the use of mutation, selection, and screening to develop improved strains. Although mutational and screening methods are well-characterized, selection remains poorly understood. We hypothesized that we could use a genome-wide method for assessing laboratory selections to design selections with enhanced sensitivity (true positives) and specificity (true negatives) towards a single desired phenotype. To test this hypothesis, we first applied multi-SCale Analysis of Library Enrichments (SCALEs) to identify genes conferring increased fitness in continuous flow selections with increasing levels of 3-hydroxypropionic acid (3-HP). We found that this selection not only enriched for 3-HP tolerance phenotypes but also for wall adherence phenotypes (41% false positives). Using this genome-wide data, we designed a serial-batch selection with a decreasing 3-HP gradient. Further examination by ROC analysis confirmed that the serial-batch approach resulted in significantly increased sensitivity (46%) and specificity (10%) for our desired phenotype (3-HP tolerance).

[1]  W. Stemmer Rapid evolution of a protein in vitro by DNA shuffling , 1994, Nature.

[2]  R. Kolter,et al.  Evolution of microbial diversity during prolonged starvation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[3]  J. Shendure,et al.  Selection analyses of insertional mutants using subgenic-resolution arrays , 2001, Nature Biotechnology.

[4]  Elizabeth A. Winzeler,et al.  Genomic profiling of drug sensitivities via induced haploinsufficiency , 1999, Nature Genetics.

[5]  T. Wood,et al.  Motility influences biofilm architecture in Escherichia coli , 2006, Applied Microbiology and Biotechnology.

[6]  G. Stephanopoulos,et al.  Genome-wide screening for trait conferring genes using DNA microarrays , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[7]  G. Stephanopoulos,et al.  Global transcription machinery engineering: a new approach for improving cellular phenotype. , 2007, Metabolic engineering.

[8]  R. Lenski,et al.  The population genetics of ecological specialization in evolving Escherichia coli populations , 2000, Nature.

[9]  Felix Naef,et al.  Solving the riddle of the bright mismatches: labeling and effective binding in oligonucleotide arrays. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Anu Raghunathan,et al.  Comparative genome sequencing of Escherichia coli allows observation of bacterial evolution on a laboratory timescale , 2006, Nature Genetics.

[11]  N. Sandoval,et al.  Parallel mapping of genotypes to phenotypes contributing to overall biological fitness. , 2008, Metabolic engineering.

[12]  Ryan T Gill,et al.  SCALEs: multiscale analysis of library enrichment , 2007, Nature Methods.

[13]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[14]  F. Neidhardt,et al.  Culture Medium for Enterobacteria , 1974, Journal of bacteriology.

[15]  Ryan T Gill,et al.  Genome-scale analysis of anti-metabolite directed strain engineering. , 2008, Metabolic engineering.

[16]  J. Gottschal,et al.  Growth kinetics and competition — some contemporary comments , 2004, Antonie van Leeuwenhoek.

[17]  F. Srienc,et al.  The cytostat: A new way to study cell physiology in a precisely defined environment. , 2006, Journal of biotechnology.

[18]  S. Vollenweider,et al.  3-Hydroxypropionaldehyde: applications and perspectives of biotechnological production , 2004, Applied Microbiology and Biotechnology.

[19]  Richard E. Lenski,et al.  Long-Term Experimental Evolution in Escherichia coli. II. Changes in Life-History Traits During Adaptation to a Seasonal Environment , 1994, The American Naturalist.

[20]  R. Lenski,et al.  Microbial genetics: Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation , 2003, Nature Reviews Genetics.

[21]  Ronald W. Davis,et al.  Quantitative phenotypic analysis of yeast deletion mutants using a highly parallel molecular bar–coding strategy , 1996, Nature Genetics.

[22]  U. Römling,et al.  GGDEF and EAL domains inversely regulate cyclic di‐GMP levels and transition from sessility to motility , 2004, Molecular microbiology.

[23]  Ronald W. Davis,et al.  Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. , 1999, Science.

[24]  Johnathan E. Holladay,et al.  Top Value Added Chemicals From Biomass. Volume 1 - Results of Screening for Potential Candidates From Sugars and Synthesis Gas , 2004 .

[25]  J. Sambrook,et al.  Molecular Cloning: A Laboratory Manual , 2001 .

[26]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[27]  D. Dykhuizen,et al.  Predicted fitness changes along an environmental gradient , 1994, Evolutionary Ecology.

[28]  W. Stemmer,et al.  DNA shuffling of a family of genes from diverse species accelerates directed evolution , 1998, Nature.