8.4 Case studies in metabolic pathway optimization
2 min read•july 25, 2024
Metabolic pathway optimization has revolutionized industrial production of valuable compounds. From antimalarial drugs to biofuels, engineered microbes now churn out a wide range of products more efficiently and sustainably than traditional methods.
Success in this field hinges on careful host selection, smart engineering strategies, and process fine-tuning. As the field evolves, new tools like AI and are pushing the boundaries of what's possible, expanding our ability to create useful molecules.
Industrial Applications of Metabolic Pathway Optimization
Examples of metabolic pathway optimization
Top images from around the web for Examples of metabolic pathway optimization
Frontiers | Yeast-Based Biosynthesis of Natural Products From Xylose View original
Is this image relevant?
CH391L/S14/Artemisinin - SynBioCyc View original
Is this image relevant?
Frontiers | Integrated transcriptome and metabolome analysis revealed that flavonoids enhanced ... View original
Is this image relevant?
Frontiers | Yeast-Based Biosynthesis of Natural Products From Xylose View original
Is this image relevant?
CH391L/S14/Artemisinin - SynBioCyc View original
Is this image relevant?
1 of 3
Top images from around the web for Examples of metabolic pathway optimization
Frontiers | Yeast-Based Biosynthesis of Natural Products From Xylose View original
Is this image relevant?
CH391L/S14/Artemisinin - SynBioCyc View original
Is this image relevant?
Frontiers | Integrated transcriptome and metabolome analysis revealed that flavonoids enhanced ... View original
Is this image relevant?
Frontiers | Yeast-Based Biosynthesis of Natural Products From Xylose View original
Is this image relevant?
CH391L/S14/Artemisinin - SynBioCyc View original
Is this image relevant?
1 of 3
- in yeast engineered to produce later converted to artemisinin, an antimalarial drug crucial for treating malaria in developing countries
- in engineered pathway for conversion of glucose to 1,3-propanediol used as a monomer for polyester production in textiles and plastics industries
- advanced in E. coli and fatty acid-derived biofuels in as renewable alternatives to fossil fuels
- optimized in and in E. coli for food and feed additives
- in microorganisms achieved production of and other flavonoids in E. coli and S. cerevisiae for nutraceuticals and pharmaceuticals
Success factors in pathway engineering
- considered genetic tractability, metabolic capacity, growth requirements, and scalability (S. cerevisiae, E. coli)
- Pathway engineering strategies employed , for improved activity or specificity, to reduce bottlenecks, and
- Process optimization fine-tuned fermentation conditions (pH, temperature, aeration), substrate feeding strategies, and product extraction and purification methods
- Regulatory considerations addressed transcriptional regulation, and redirection, and
- Integration of utilized omics data analysis (, , ) and for comprehensive pathway understanding
Applications of case study lessons
- Transferable strategies developed for easier optimization, synthetic biology tools (CRISPR-Cas9) for precise genetic modifications, and dynamic pathway regulation using biosensors
- Areas for improvement focused on enhancing product yields and titers, reducing byproduct formation, and improving and robustness
- Emerging technologies explored for rapid prototyping, artificial intelligence for pathway design and optimization, and genome synthesis and minimal genome approaches
- Scale-up considerations addressed challenges in transitioning from lab to industrial scale and developing continuous fermentation processes
- Expanding the repertoire of host organisms explored with unique metabolic capabilities and for direct CO2 utilization
- Integration with other fields combined metabolic engineering with materials science for novel biomaterials and interfaced engineered pathways with chemical catalysis for hybrid processes
Key Terms to Review (37)
1,3-propanediol production: 1,3-Propanediol production refers to the biotechnological process of synthesizing 1,3-propanediol, a valuable chemical building block used in various applications such as plastics, cosmetics, and antifreeze. This production is often achieved through metabolic engineering techniques that optimize microbial pathways, enabling organisms like bacteria to convert renewable substrates into this compound efficiently.
Amino acid production: Amino acid production refers to the biochemical processes involved in synthesizing amino acids, which are the building blocks of proteins. This production can occur through various metabolic pathways, and optimizing these pathways can enhance yields and efficiency. The ability to balance metabolic flux is crucial in maximizing amino acid production, as it ensures that precursor molecules are effectively utilized to produce the desired amino acids.
Artemisinic acid: Artemisinic acid is a sesquiterpene compound derived from the plant Artemisia annua, known for its anti-malarial properties. It serves as a precursor in the biosynthetic pathway leading to artemisinin, a crucial drug used to treat malaria, and its optimization has significant implications in metabolic engineering and synthetic biology.
Artemisinin production: Artemisinin production refers to the biosynthesis of artemisinin, a potent anti-malarial compound derived from the plant Artemisia annua, commonly known as sweet wormwood. This process is significant in synthetic biology and metabolic engineering as it exemplifies the manipulation of metabolic pathways to produce valuable pharmaceuticals, showcasing the principles and goals of creating sustainable bioproduction methods, addressing historical challenges in malaria treatment, and optimizing metabolic pathways for enhanced yields.
Artificial intelligence in pathway design: Artificial intelligence in pathway design refers to the application of machine learning and computational algorithms to optimize and create biological pathways for metabolic engineering. By analyzing vast datasets and predicting interactions within biological systems, AI can significantly enhance the efficiency and speed of pathway design, ultimately improving the production of desired compounds.
Biofuel production: Biofuel production refers to the process of generating fuels from biological materials, such as plant biomass, algae, or waste products. This renewable energy source plays a significant role in reducing dependence on fossil fuels and mitigating environmental impacts, connecting to advancements in metabolic engineering and synthetic biology for optimizing production pathways.
Cell-free systems: Cell-free systems are biological environments where cellular machinery is isolated from the cell itself, allowing for the production of biomolecules without the need for living cells. This approach enables scientists to manipulate and engineer biochemical pathways more efficiently, facilitating the integration of biosensors and optimizing metabolic pathways. By utilizing cell-free systems, researchers can streamline the testing and development of synthetic circuits and metabolic engineering applications.
Cofactor Regeneration Systems: Cofactor regeneration systems are biochemical processes that restore depleted cofactors, such as NADH or NADPH, during metabolic reactions. These systems are crucial for maintaining the efficiency of enzymatic reactions in metabolic pathways by recycling cofactors that would otherwise be consumed, allowing for continuous operation of pathways involved in synthetic biology and metabolic engineering.
Corynebacterium glutamicum: Corynebacterium glutamicum is a Gram-positive bacterium widely used in industrial biotechnology for the production of amino acids, particularly L-glutamate and L-lysine. It serves as a model organism for metabolic engineering and synthetic biology, enabling researchers to optimize metabolic pathways for enhanced production yields and efficiency.
CRISPR-Cas9 Gene Editing: CRISPR-Cas9 is a revolutionary gene-editing technology that allows scientists to precisely modify DNA sequences in living organisms. This system utilizes a guide RNA to target specific sequences of DNA and the Cas9 protein to create double-strand breaks, enabling the addition, deletion, or alteration of genetic material. Its high efficiency and precision make it a valuable tool in metabolic pathway optimization.
Cyanobacteria: Cyanobacteria, also known as blue-green algae, are a group of photosynthetic bacteria found in a variety of environments, including freshwater, marine, and terrestrial ecosystems. They are important for their role in oxygen production and nitrogen fixation, making them crucial players in nutrient cycling and ecosystem health.
E. coli: Escherichia coli, commonly known as e. coli, is a versatile bacterium found in the intestines of humans and animals, playing a critical role in gut health and digestion. Its importance extends to synthetic biology and metabolic engineering, where it serves as a key model organism for studying metabolic pathways and engineering biological processes due to its well-characterized genetics and rapid growth rates.
Engineered photosynthetic organisms: Engineered photosynthetic organisms are modified living systems that have been genetically altered to enhance their ability to convert sunlight into energy and produce valuable compounds through photosynthesis. These organisms can be bacteria, algae, or plants that have undergone metabolic pathway optimization to improve productivity, sustainability, and the efficiency of biotechnological applications.
Enzyme engineering: Enzyme engineering is the process of designing and modifying enzymes to improve their properties or functions for specific applications. This includes enhancing enzyme stability, specificity, and activity through various techniques, such as directed evolution and rational design. By tailoring enzymes to meet particular needs, this approach plays a crucial role in optimizing metabolic pathways and synthesizing valuable biomaterials.
Feedback inhibition mitigation: Feedback inhibition mitigation refers to strategies employed to alleviate the negative impacts of feedback inhibition in metabolic pathways, allowing for enhanced production of desired metabolites. This process is crucial in optimizing metabolic pathways by balancing enzyme activities and substrate availability, ultimately improving yields in biotechnological applications. By addressing feedback inhibition, engineered pathways can achieve higher efficiency and productivity.
Fermentation optimization: Fermentation optimization refers to the process of improving the conditions and parameters under which fermentation occurs to enhance the yield and efficiency of desired products. This includes tweaking factors like temperature, pH, nutrient concentrations, and microbial strains to achieve maximum output of metabolites, such as alcohol, organic acids, or biofuels. The goal is to ensure that the fermentation process is not only productive but also cost-effective and sustainable.
Flavonoid biosynthesis: Flavonoid biosynthesis refers to the biochemical pathways that produce flavonoids, a diverse group of polyphenolic compounds found in plants. These compounds are important for plant coloration, UV protection, and as antioxidants, playing vital roles in plant physiology and human health. Understanding the metabolic pathways involved in flavonoid production is essential for optimizing their synthesis in plants and microbial systems.
Gene overexpression: Gene overexpression is the process of artificially increasing the expression level of a specific gene within an organism, leading to an enhanced production of its corresponding protein. This technique is often employed in synthetic biology and metabolic engineering to optimize metabolic pathways for increased yield or efficiency, facilitating advancements in areas such as biofuel production, pharmaceuticals, and industrial biotechnology.
Genome synthesis: Genome synthesis is the process of artificially constructing a complete genome from scratch or modifying an existing one, using techniques such as chemical synthesis and assembly of DNA fragments. This technology allows scientists to create novel organisms with specific traits by designing and building genetic sequences tailored to desired functions, impacting areas like metabolic engineering and synthetic biology.
Genome-scale metabolic modeling: Genome-scale metabolic modeling is a computational approach that allows researchers to simulate and analyze the metabolic networks of organisms at a genome level. This modeling integrates genomic, transcriptomic, and proteomic data to provide insights into cellular metabolism, helping to identify key pathways and optimize metabolic processes for various applications.
Host Organism Selection: Host organism selection is the process of choosing an appropriate organism to act as a platform for expressing and optimizing metabolic pathways. The selection is crucial as it directly impacts the efficiency and yield of the desired products from engineered pathways. This process involves evaluating various factors, such as growth characteristics, genetic tractability, and the ability to tolerate and produce specific metabolites.
Isobutanol production: Isobutanol production refers to the biological or chemical processes used to generate isobutanol, an alcohol with potential applications as a biofuel and solvent. The production of isobutanol typically involves the optimization of metabolic pathways in microorganisms, allowing for enhanced yields and efficiency in its synthesis, which is crucial for sustainable energy solutions.
L-lysine production: l-lysine production refers to the biotechnological processes used to synthesize l-lysine, an essential amino acid vital for protein synthesis in both humans and animals. It is mainly produced through fermentation methods involving specific strains of bacteria or yeast that are genetically engineered or optimized to enhance yield and efficiency. The optimization of metabolic pathways plays a critical role in increasing the production rates of l-lysine, addressing global demands in the food and feed industries.
L-threonine overproduction: l-threonine overproduction refers to the enhanced biosynthesis of the amino acid l-threonine in microorganisms, particularly in bacterial strains such as Escherichia coli. This process is significant in metabolic engineering, as it allows for the efficient production of l-threonine, which has applications in animal feed and pharmaceuticals. By optimizing metabolic pathways, researchers can achieve high yields and improved growth rates in engineered strains, making it an important case study in the field.
Metabolic Flux Analysis: Metabolic flux analysis (MFA) is a quantitative method used to analyze the flow of metabolites through metabolic networks, allowing researchers to understand the dynamics of metabolic pathways in cells. It integrates experimental measurements of metabolite concentrations and fluxes to provide insights into cellular metabolism, which is crucial for optimizing metabolic pathways, enhancing bioproduction, and engineering organisms for specific purposes.
Metabolomics: Metabolomics is the comprehensive study of metabolites within a biological system, involving the identification and quantification of small molecules present in cells, tissues, or organisms. This field helps to understand metabolic processes and interactions, providing insights into how these metabolites influence biological functions and overall health. It plays a crucial role in optimizing metabolic pathways, integrating omics data for better modeling, analyzing fluxes in metabolic networks, and reconstructing complex metabolic systems.
Modular pathway design: Modular pathway design refers to the strategy of constructing metabolic pathways in a flexible, interchangeable manner, allowing for the systematic optimization and assembly of biological functions. This approach promotes the use of defined modules, or parts, that can be combined to achieve desired metabolic outputs while simplifying the engineering process. By treating pathways as modules, scientists can more efficiently manipulate and enhance metabolic networks for improved production of desired compounds.
Naringenin: Naringenin is a flavanone, a type of flavonoid, primarily found in citrus fruits like grapefruits and oranges. This compound is known for its antioxidant properties and potential health benefits, including anti-inflammatory and anti-cancer effects. Its significance also extends to metabolic engineering, where it serves as a valuable building block in the optimization of metabolic pathways for producing various compounds.
Non-model organisms: Non-model organisms are species that have not been extensively studied or characterized in laboratory settings, making them less understood than model organisms like E. coli or yeast. These organisms can possess unique metabolic pathways and genetic traits that offer valuable insights into biological processes and can be optimized for various applications, such as bioproduction or environmental sustainability. Their study is becoming increasingly relevant in fields like metabolic engineering and systems biology.
Pathway Balancing: Pathway balancing is the process of optimizing the flow of metabolites through a metabolic pathway to ensure that the production rates of desired products are maximized while minimizing by-product formation. This involves adjusting enzyme activities, substrate concentrations, and cofactor availability to achieve an efficient and effective biochemical reaction network. Achieving proper balance can significantly enhance the yield and efficiency of engineered pathways in synthetic biology applications.
Product Yield Enhancement: Product yield enhancement refers to the strategies and techniques used to increase the amount of desired product produced from a biological system, typically involving metabolic engineering and pathway optimization. This concept is crucial for improving the efficiency of bioprocesses, allowing for more effective conversion of substrates into target products. By optimizing metabolic pathways, researchers aim to maximize the yield of specific compounds, which can have significant implications in various fields such as pharmaceuticals, biofuels, and biotechnology.
Proteomics: Proteomics is the large-scale study of proteins, particularly their structures and functions. It plays a critical role in understanding cellular processes and metabolic pathways by providing insights into protein expression, interactions, and modifications. This information is crucial when optimizing metabolic pathways, integrating omics data into models, and applying metabolic flux analysis to better predict and manipulate biological systems.
Saccharomyces cerevisiae: Saccharomyces cerevisiae is a species of yeast commonly known as baker's or brewer's yeast, widely used in baking, brewing, and scientific research. This organism is a powerful model organism for studying cellular processes and metabolic pathways due to its well-characterized genetics and ease of manipulation, making it a cornerstone in various applications like biofuel production, protein synthesis, and biomaterial creation.
Strain stability: Strain stability refers to the ability of a microbial strain to maintain its genetic and phenotypic characteristics over time, especially during fermentation processes or industrial applications. This stability is crucial in metabolic engineering, as it ensures consistent performance in producing desired metabolites and prevents loss of engineered traits that can occur due to genetic drift, mutations, or environmental stressors.
Systems biology approaches: Systems biology approaches are integrated strategies that focus on understanding complex biological systems through the analysis of interactions within cellular networks and pathways. By leveraging computational modeling, data analysis, and experimental validation, these approaches help in deciphering the intricate relationships between genes, proteins, and metabolic pathways. This understanding is crucial for optimizing metabolic processes, as it enables researchers to manipulate and enhance pathways for desired outcomes.
Titer: Titer is a measure of the concentration of a substance in a solution, typically referring to the amount of a specific molecule, such as proteins or metabolites, present in a culture or sample. In metabolic engineering, determining the titer is crucial for evaluating the efficiency of engineered pathways and assessing product yields. Understanding titer helps researchers optimize metabolic processes and informs decisions related to scaling up production in biotechnological applications.
Transcriptomics: Transcriptomics is the study of the complete set of RNA transcripts produced by the genome at any given time, providing insights into gene expression patterns and cellular responses. This field helps researchers understand how genes are regulated and how their expression varies under different conditions, contributing to advances in areas like metabolic engineering and pathway optimization.