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

Project Abstract

CRISPR-based metabolic pathway engineering offers a transformative approach to enhance the biosynthesis of high-value bioproducts in Saccharomyces cerevisiae by enabling precise, multiplexed, and programmable modifications to native and heterologous pathways. This study presents a systematic optimization of CRISPR tools and strategies to elevate the yield, titer, and productivity of a targeted bioproduct through coordinated modulation of key enzymatic steps, cofactor balance, and flux distribution. We combined CRISPR interference and activation (CRISPRi/a) to downregulate competing pathways while upregulating rate-limiting enzymes, integrated CRISPR-mediated promoter and terminator engineering to fine-tune gene expression, and employed multiplexed guide RNA libraries to explore combinatorial gene sets in a high-throughput fashion. A robust computational pipeline was developed to predict flux redirection and identify synergistic gene targets, followed by iterative experimental validation in a lab-scale bioreactor under optimized fermentation conditions. To address metabolic burden and plasmid stability, we implemented genome-integrated CRISPR constructs with inducible systems and used chromosomal integration to reduce copy-number variability. Additionally, we engineered feedback-resistant variants and employed dynamic regulation strategies to match pathway activity with cellular growth phases, thereby mitigating toxicity and enhancing overall production. Quantitative omics (transcriptomics, proteomics, and metabolomics) and flux analyses were conducted to map the rewired network, revealing how targeted perturbations rebalanced NAD(P)H/NAD(P)? pools, precursor pools, and energy status to support sustained biosynthesis. The study reports a multi-criteria optimization outcome a substantial increase in bioproduct titer and yield, reduced byproduct formation, and improved process robustness across pH and temperature fluctuations. We further demonstrate the scalability potential by validating the optimized strain in fed-batch fermentation with consistent performance metrics over multiple cycles. Critical challenges addressed include off-target effects, metabolic burden, and regulatory circuit stability, which were mitigated through guide RNA design optimization, compact regulatory elements, and CRISPR-based sensory modules responsive to intracellular metabolite levels. The findings elucidate the interplay between promoter strength, gene copy number, and pathway bottlenecks, providing a generalizable framework for CRISPR-driven pathway optimization in yeast and other microbial hosts. This work lays the groundwork for rapid, precise strain development for sustainable production of diverse bioproducts, offering a blueprint for translating CRISPR-based engineering from proof-of-concept to industrially relevant workflows.

Project Overview

What This Project Is About

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The project looks at using CRISPR tools to fine-tune the metabolism of yeast (Saccharomyces cerevisiae) so it makes more of a specific useful product. It combines genetics editing with everyday lab tests to see how changes in the cell’s internal pathways affect production efficiency.

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The Problem It Addresses

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Industrial microbes often struggle to make large amounts of a desired product. Yeast has complex metabolic networks, and small changes can have big, unpredictable effects. This project seeks a clearer, safer way to direct these networks to boost yield without harming cell health.

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Objectives of the Project

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1. Identify a key metabolic step to enhance for higher product output.
2. Design CRISPR-based edits to adjust that step in yeast.
3. Test edited strains for growth and production under controlled conditions.
4. Measure product levels and cell health to assess trade-offs.
5. Analyze data to determine the most effective edits.

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What You Will Do Step by Step

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1) Review basic yeast metabolism and CRISPR concepts. 2) Select target genes to modify. 3) Create simple edit plans and introduce edits in yeast. 4) Grow edited strains and monitor growth curves. 5) Measure product concentration using standard assays. 6) Compare edited vs. non-edited strains. 7) Analyze results with basic statistics to draw conclusions. 8) Discuss practical implications and limitations.

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Expected Outcome

Anticipated result is a set of yeast strains with improved production of the chosen bioproduct and a clearer understanding of how specific pathway tweaks influence yield and cell health. The findings could guide safer, more efficient strain design for industrial bioprocesses.