ABSTRACT
Our limited ability to predict genotype-phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype-phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli We designed over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This approach sets a framework for forward investigation of complex multigenic phenotypes.
Subject(s)
Escherichia coli/metabolism , Lysine/metabolism , Metabolic Networks and Pathways , Mutation , CRISPR-Cas Systems , Escherichia coli/genetics , Escherichia coli Proteins/genetics , Escherichia coli Proteins/metabolism , Gene Library , PhenotypeABSTRACT
Methods for importing heterologous genes into genetically tractable hosts are among the most desired tools of synthetic biology. Easy plug-and-play construction methods to rapidly test genes and pathways stably in the host genome would expedite synthetic biology and metabolic engineering applications. Here, we describe a CRISPR-based strategy that allows highly efficient, single step integration of large pathways in Escherichia coli. This strategy allows high efficiency integration in a broad range of homology arm sizes and genomic positions, with efficiencies ranging from 70 to 100% in 7 distinct loci. To demonstrate the large size capability, we integrated a 10 kb construct to implement isobutanol production in a single day. The ability to efficiently integrate entire metabolic pathways in a rapid and markerless manner will facilitate testing and engineering of novel pathways using the E. coli genome as a stable testing platform.
Subject(s)
Escherichia coli/genetics , Escherichia coli/metabolism , Metabolic Engineering/methods , Bacterial Proteins/genetics , Butanols/metabolism , CRISPR-Associated Protein 9 , Clustered Regularly Interspaced Short Palindromic Repeats , Endonucleases/genetics , Escherichia coli Proteins/genetics , Genetic Engineering/methods , Genome, Bacterial , Green Fluorescent Proteins/genetics , Green Fluorescent Proteins/metabolism , Metabolic Networks and Pathways , MutS DNA Mismatch-Binding Protein/genetics , Mutation , RNA, Guide, Kinetoplastida , Reproducibility of ResultsABSTRACT
Since the 1970s technological advancements in the fields of synthetic biology and metabolic engineering have led to a dramatic reduction in both time and cost required for generating genomic mutations in a variety of organisms. The union of genomic editing machinery, DNA inkjet printers, and bioinformatics algorithms allows engineers to design a library of thousands of unique oligos as well as build and test these designs on a â¼2 months time-scale and at a cost of roughly â¼0.3 cents per base pair. The implications of these capabilities for a variety of fields are far-reaching, with potential impacts in defense, agricultural, human health, and environmental research. The explosion of synthetic biology applications over the past two decades have led many to draw parallels between biological engineering and the computer sciences. In this review, we highlight some important parallels between these fields and emphasize the importance of engineering design strategies.
