Integrating transcriptional and metabolite profiles to direct the engineering of lovastatin-producing fungal strains

Abstract

We describe a method to decipher the complex inter-relationships between metabolite production trends and gene expression events, and show how information gleaned from such studies can be applied to yield improved production strains. Genomic fragment microarrays were constructed for the Aspergillus terreus genome, and transcriptional profiles were generated from strains engineered to produce varying amounts of the medically significant natural product lovastatin. Metabolite detection methods were employed to quantify the polyketide-derived secondary metabolites lovastatin and (+)-geodin in broths from fermentations of the same strains. Association analysis of the resulting transcriptional and metabolic data sets provides mechanistic insight into the genetic and physiological control of lovastatin and (+)-geodin biosynthesis, and identifies novel components involved in the production of (+)-geodin, as well as other secondary metabolites. Furthermore, this analysis identifies specific tools, including promoters for reporter-based selection systems, that we employed to improve lovastatin production by A. terreus.

System Response of Metabolic Networks in Chlamydomonas reinhardtii to Total Available Ammonium

“…Advances in molecular profiling technologies such as microarray-based transcriptomics and mass spectrometrybased proteomics enable studies of the cellular responses to stress conditions on different molecular levels (17)(18)(19)(20)(21)(22). However, alterations in gene expression may not translate to alterations in proteins abundances.…”

Engineering Complex Phenotypes in Industrial Strains

“…The generation of this mapping provides new insights to identify both local and global targets of metabolic engineering. In one example integration of transcriptional and metabolic profiles through association analysis enabled engineering a fungal strain with 2-fold improvement in lovastatin titers (1). In this approach, a genomic fragment microarray for Aspergillus terreus consisting of 21,000 elements was used to generate the transcriptional profiles for a set of 21 strains that were producing either more or less of the desired metabolite, lovastatin.…”

“…However, recent successful commercial applications of bioprocesses are feasible as a result of the availability of engineered biocatalysts that not only do novel chemistry but also are optimized for economical performance at large scale. The capability for manipulating the biocatalyst to express desired complex traits (phenotypes) in industrial settings is possible as a result of the integration of the tools of "classical" and "modern" strain engineering approaches (1)(2)(3)(4)(5)(6)(7)(8) and the remarkable resilience of microbial cells to such non-natural interventions. Examples of common industrially relevant traits include higher rates of reaction, increase in yields on substrate, tolerance to products and inhibitors, and adaptability to process environments that differ significantly from natural habitats.…”

Reverse biological engineering of hrdB to enhance the production of avermectins in an industrial strain of Streptomyces avermitilis

“…Reverse engineering an organism with a desirable property is carried out by identifying the genetic basis of the property and then directly engineering the key genes, the aim of which is to rapidly gain insight into the complex mechanisms controlling microbial metabolism. Reverse engineering has successfully improved the yield of lovastatin in Aspergillus terreus by association analysis of transcriptional and metabolite profiling data to elucidate the key genetic components and physiological traits that impact the production of lovastatin (11). This approach can be utilized to elucidate the interrelationships between physiological traits and more efficiently direct the engineering of target compound-producing strains to synthesize high yields of these natural products.…”