Biosynthetic Gene Cluster Screening for Low-Yield Metabolites
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Solution Overview
Problem
Existing technologies face challenges in efficiently harnessing the biosynthetic potential of microbial genomes for secondary metabolites due to low yields, limited supply, complex structures, and difficulty in structural modifications, leading to a decline in the discovery of new secondary metabolites for medical applications.
Innovation Solution
A method for identifying and expressing gene clusters in host cells, particularly using yeast cells modified for increased sporulation frequency and mitochondrial stability, to produce small molecules that modulate target proteins, involving the introduction of gene clusters into vectors and host cells, and utilizing homologous recombination for controlled expression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional approaches are used to harness biosynthetic gene clusters, then the structural diversity of secondary metabolites is preserved, but the yield and supply are extremely low
Solution Approach 1:
The patent segments the biosynthetic process by separating the gene cluster identification and expression steps. It uses bioinformatics tools to identify candidate gene clusters from genomic data, then expresses them in heterologous host organisms. This segmentation allows systematic screening of multiple gene clusters without being limited by the low natural production capacity of individual organisms.
Solution Approach 2:
The patent introduces heterologous host organisms as intermediaries to express the biosynthetic gene clusters. These host organisms serve as mediators that can be optimized for high-yield production while maintaining the ability to produce diverse secondary metabolites. The intermediary hosts bridge the gap between gene cluster identification and practical production.
2Reliability
If secondary metabolites are used for drug discovery, then clinically valuable compounds are obtained, but the complex structures pose difficulty for structural modifications
Solution Approach 1:
The patent enables dynamic exploration of chemical space by allowing modular manipulation of expressed gene clusters. Researchers can systematically modify gene sequences, promoter regions, and expression conditions to generate analogs and derivatives. This dynamic approach transforms the static, complex natural structures into modifiable systems that can be optimized for both clinical value and manufacturability.
3Adaptability or versatility
If more biosynthetic gene clusters are screened, then the diversity of secondary metabolites increases, but the time and resources required for identification and expression increase
Solution Approach 1:
The patent performs preliminary bioinformatics analysis to predict and prioritize candidate gene clusters before experimental expression. By using computational tools to screen genomic databases and identify promising gene clusters based on sequence homology and structural predictions, the method pre-filters the vast number of possible clusters, reducing the experimental workload and time required for actual expression and screening.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the production of secondary metabolites that can modulate target proteins, overcoming yield and supply limitations, and enabling the discovery of novel compounds with structural diversity for medical applications.
Implementation Method 1
introducing the polynucleotides into a host cell that includes machinery for homologous recombination, wherein the host cell assembles the expression vector via homologous recombination that occurs in the flanking regions of the second plurality of polynucleotides
Data Source
AI summary
Methods for identifying biosynthetic gene clusters that include genes for producing compounds that interact with specific target proteins are disclosed. Some methods relate to bioinformatics methods for identifying and/or prioritizing biosynthetic gene clusters. Related systems, components, and tools for the identification and expression of such gene clusters are also disclosed.