Genome-scale analysis of anti-metabolite directed strain engineering

Wiring cell growth to product formation

Microbial cell factories offer new and sustainable production routes for high-value chemicals. However, identification of high producers within a library of clones remains a challenge. When product formation is coupled to growth, millions of metabolic variants can be effectively interrogated by growth selection, dramatically increasing the throughput of strain evaluation. While growth-coupled selections for cell factories have a long history of success based on metabolite auxotrophies and toxic antimetabolites, such methods are generally restricted to molecules native to their host metabolism. New synthetic biology tools offer the opportunity to rewire cellular metabolism to depend on specific and non-native products for growth.

Biosensor-Enabled Directed Evolution to Improve Muconic Acid Production in Saccharomyces cerevisiae

Muconic acid is a valuable platform chemical with potential applications in the production of polymers such as nylon and polyethylene terephthalate (PET). The conjugate base, muconate, has been previously biosynthesized in the bacterial host Escherichia coli. Likewise, previous significant pathway engineering lead to the first reported instance of rationally engineered production of muconic acid in the yeast Saccharomyces cerevisiae. To further increase muconic acid production in this host, a combined adaptive laboratory evolution (ALE) strategy and rational metabolic engineering is employed. To this end, a biosensor module that responds to the endogenous aromatic amino acid (AAA) as a surrogate for pathway flux is adapted. Following two rounds of ALE coupled with an anti-metabolite feeding strategy, the strains with improved AAA pathway flux is isolated. Next, it is demonstrated that this increased flux can be redirected into the composite muconic acid pathway with a threefold increase in the total titer of the composite pathway compared to our previously engineered strain. Finally, a truncation of the penta-functional ARO1 protein is complemented and overexpress an endogenous aromatic decarboxylase to establish a final strain capable of producing 0.5 g L^-1 muconic acid in shake flasks and 2.1 g L^-1 in a fed-batch bioreactor with a yield of 12.9 mg muconic acid/g glucose at the rate of 9.0 mg h^-1 . This value represents the highest titer of muconic acid reported to date in S. cerevisiae, in addition to the highest reported titer of a shikimate pathway derivative in this host.

Genome-wide mapping of furfural tolerance genes in Escherichia coli

Advances in genomics have improved the ability to map complex genotype-to-phenotype relationships, like those required for engineering chemical tolerance. Here, we have applied the multiSCale Analysis of Library Enrichments (SCALEs; Lynch et al. (2007) Nat. Method.) approach to map, in parallel, the effect of increased dosage for >10(5) different fragments of the Escherichia coli genome onto furfural tolerance (furfural is a key toxin of lignocellulosic hydrolysate). Only 268 of >4,000 E. coli genes (∼ 6%) were enriched after growth selections in the presence of furfural. Several of the enriched genes were cloned and tested individually for their effect on furfural tolerance. Overexpression of thyA, lpcA, or groESL individually increased growth in the presence of furfural. Overexpression of lpcA, but not groESL or thyA, resulted in increased furfural reduction rate, a previously identified mechanism underlying furfural tolerance. We additionally show that plasmid-based expression of functional LpcA or GroESL is required to confer furfural tolerance. This study identifies new furfural tolerant genes, which can be applied in future strain design efforts focused on the production of fuels and chemicals from lignocellulosic hydrolysate.

Strategies for the multiplex mapping of genes to traits

Rewiring and optimization of metabolic networks to enable the production of commercially valuable chemicals is a central goal of metabolic engineering. This prospect is challenged by the complexity of metabolic networks, lack of complete knowledge of gene function(s), and the vast combinatorial genotype space that is available for exploration and optimization. Various approaches have thus been developed to aid in the efficient identification of genes that contribute to a variety of different phenotypes, allowing more rapid design and engineering of traits desired for industrial applications. This review will highlight recent technologies that have enhanced capabilities to map genotype-phenotype relationships on a genome wide scale and emphasize how such approaches enable more efficient design and engineering of complex phenotypes.

Genome-wide identification of genes conferring energy related resistance to a synthetic antimicrobial peptide (Bac8c)

A fundamental issue in the design and development of antimicrobials is the lack of understanding of complex modes of action and how this complexity affects potential pathways for resistance evolution. Bac8c (RIWVIWRR-NH₂) is an 8 amino acid antimicrobial peptide (AMP) that has been shown to have enhanced activity against a range of pathogenic Gram-positive and Gram-negative bacteria, as well as yeast. We have previously demonstrated that Bac8c appears to interfere with multiple targets, at least in part through the disruption of cytoplasmic membrane related functions, and that resistance to this peptide does not easily develop using standard laboratory methods. Here, we applied a genomics approach, SCalar Analysis of Library Enrichement (SCALEs), to map the effect of gene overexpression onto Bac8c resistance in parallel for all genes and gene combinations (up to ∼ 10 adjacent genes) in the E. coli genome (a total of ∼ 500,000 individual clones were mapped). Our efforts identified an elaborate network of genes for which overexpression leads to low-level resistance to Bac8c (including biofilm formation, multi-drug transporters, etc). This data was analyzed to provide insights into the complex relationships between mechanisms of action and potential routes by which resistance to this synthetic AMP can develop.

Genome-scale identification and characterization of ethanol tolerance genes in Escherichia coli

The identification of relevant gene targets for engineering a desired trait is a key step in combinatorial strain engineering. Here, we applied the multi-Scalar Analysis of Library Enrichments (SCALEs) approach to map ethanol tolerance onto 1,000,000 genomic-library clones in Escherichia coli. We assigned fitness scores to each of the ∼4,300 genes in E. coli, and through follow-up confirmatory studies identified 9 novel genetic targets (12 genes total) that increase E. coli ethanol tolerance (up to 6-fold improved growth). These genetic targets are involved in the processes related to cell membrane composition, translation, serine biosynthesis, and transcription regulation. Transcriptional profiling of the ethanol stress response in 5 of these ethanol-tolerant clones revealed a total of 700 genes with significantly altered expression (mapped to 615 significantly enriched gene ontology terms) across all five clones, with similar overall changes in global gene expression between two clone clusters. All ethanol-tolerant clones analyzed shared 6% of the overexpressed genes and showed enrichment for transcription regulation-related GO terms. iTRAQ-based proteomic analysis of ethanol-tolerant strains identified upregulation of proteins related to ROS mitigation, fatty acid biosynthesis, and vitamin biosynthesis as compared to the parent strain's ethanol response. The approach we outline here will be useful for engineering a variety of other traits and further improvements in alcohol tolerance.

Biology by design: from top to bottom and back

Synthetic biology is a nascent technical discipline that seeks to enable the design and construction of novel biological systems to meet pressing societal needs. However, engineering biology still requires much trial and error because we lack effective approaches for connecting basic "parts" into higher-order networks that behave as predicted. Developing strategies for improving the performance and sophistication of our designs is informed by two overarching perspectives: "bottom-up" and "top-down" considerations. Using this framework, we describe a conceptual model for developing novel biological systems that function and interact with existing biological components in a predictable fashion. We discuss this model in the context of three topical areas: biochemical transformations, cellular devices and therapeutics, and approaches that expand the chemistry of life. Ten years after the construction of synthetic biology's first devices, the drive to look beyond what does exist to what can exist is ushering in an era of biology by design.

Increased mutation frequency in redox-impaired Escherichia coli due to RelA- and RpoS-mediated repression of DNA repair

Balancing of reducing equivalents is a fundamental issue in bacterial metabolism and metabolic engineering. Mutations in the key metabolic genes ldhA and pflB of Escherichia coli are known to stall anaerobic growth and fermentation due to a buildup of intracellular NADH. We observed that the rate of spontaneous mutation in E. coli BW25113 (DeltaldhA DeltapflB) was an order of magnitude higher than that in wild-type (WT) E. coli BW25113. We hypothesized that the increased mutation frequency was due to an increased NADH/NAD(+) ratio in this strain. Using several redox-impaired strains of E. coli and different redox conditions, we confirmed a significant correlation (P < 0.01) between intracellular-NADH/NAD(+) ratio and mutation frequency. To identify the genetic basis for this relationship, whole-genome transcriptional profiles were compared between BW25113 WT and BW25113 (DeltaldhA DeltapflB). This analysis revealed that the genes involved in DNA repair were expressed at significantly lower levels in BW25113 (DeltaldhA DeltapflB). Direct measurements of the extent of DNA repair in BW25113 (DeltaldhA DeltapflB) subjected to UV exposure confirmed that DNA repair was inhibited. To identify a direct link between DNA repair and intracellular-redox ratio, the stringent-response-regulatory gene relA and the global-stress-response-regulatory gene rpoS were deleted. In both cases, the mutation frequencies were restored to BW25113 WT levels.