Optimization of a CRISPR-based metabolic pathway engineering in Saccharomyces cerevisiae for enhanced biosynthesis of a high-value bioproduct

Project Abstract

Optimization of a CRISPR-based metabolic pathway engineering in Saccharomyces cerevisiae for enhanced biosynthesis of a high-value bioproduct presents a systematic approach to reprogram yeast metabolism for superior production metrics. We report a multi-layered framework that integrates precise CRISPR-Cas9 mediated genome and pathway edits with dynamic regulation strategies to maximize flux toward the target metabolite while maintaining cellular health and viability. The study begins with a comprehensive metabolic reconstruction of S. cerevisiae tailored to the biosynthetic route of the bioproduct, identifying bottlenecks, competing pathways, and cofactor imbalances. High-throughput CRISPR perturbation screens are employed to validate gene targets implicated in flux redirection, cofactor balance (NADPH/NADH), and precursor supply, followed by multiplexed genome engineering to install and optimize a synthetic operon, regulatory elements, and feedback-resistant enzyme variants. A programmable CRISPR interference/activation (CRISPRi/a) layer is implemented to fine-tune expression dynamics in response to real-time metabolic readouts, enabling adaptive control of pathway flux under batch and fed-batch fermentation conditions. The project also introduces a modular scaffold for pathway assembly that facilitates rapid iteration of enzyme ordering, copy number variation, and partitioning across subcellular compartments to minimize metabolic burden and toxic intermediate accumulation. Advanced omics and flux analysis, including transcriptomics, proteomics, metabolomics, and 13C-labeling studies, are integrated to quantify intracellular flux distributions and to calibrate a kinetically informed genome-scale model. A data-driven optimization pipeline leverages machine learning to predict beneficial edits and to simulate perturbation effects prior to laboratory implementation, reducing experimental cycles and improving hit rates. Biosecurity and biosafety considerations are embedded throughout, with containment strategies, genetic safeguards, and in silico risk assessments guiding design choices. The engineered yeast strain is evaluated for production titer, yield, and productivity across defined media and scales, with emphasis on robustness to process variables such as pH, temperature, and feed strategy. Downstream processing compatibility and product purity are assessed to ensure industrial feasibility, including potential byproduct minimization and streamlined purification workflows. The study demonstrates a synergistic gain in biosynthetic output achieved through coordinated CRISPR-based genome editing, dynamic regulation, and systems-level optimization. Sensitivity analyses reveal key leverage points and reveal trade-offs between growth and product synthesis, informing scalable implementation. The findings contribute to a generalizable workflow for CRISPR-enabled metabolic pathway optimization in yeast, with implications for the production of high-value bioproducts that require precise control of flux and regulatory balance, offering a blueprint for translating bench-scale innovations into economically viable biomanufacturing processes.

Project Overview

What This Project Is About

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The project explores how a gene-editing tool called CRISPR can be used to fine-tune the tiny biological factory inside baker’s yeast (Saccharomyces cerevisiae) to produce more of a valuable product. It focuses on selecting target genes, adjusting their activity, and balancing the cell’s resources to boost production without harming the yeast.

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The Problem It Addresses

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Many useful bioproducts are made in yeast, but natural production is often limited by inefficient pathways and competing cell processes. This project aims to overcome these bottlenecks by precisely editing the metabolic steps, improving yield, reliability, and scalability for industrial use.

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Objectives of the Project

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1. Identify key metabolic steps that limit production of the target bioproduct.
2. Design CRISPR-based edits to upregulate or downregulate specific genes in yeast pathways.
3. Assess how edits affect product yield and cell health.
4. Develop a simple protocol to screen engineered strains for the best performance.
5. Evaluate the stability of production over multiple growth cycles.

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What You Will Do Step by Step

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1. Review basic yeast metabolism and CRISPR concepts.
2. Choose the target pathway and design CRISPR edits with minimal off-target effects.
3. Create edited yeast strains in a lab setting.
4. Grow strains and measure product yield and growth metrics.
5. Analyze data to compare engineered vs. control strains.
6. Optimize conditions to maximize production.
7. Document methods, results, and potential improvements.

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Expected Outcome

Engineered yeast strains with higher production of the chosen bioproduct and a clear set of steps for reproducibility, along with practical insights into balancing production and cell health for future scale-up.