Jody Dascalu |May 12, 2025
Fermentation is a core platform in industrial biotechnology, used to convert renewable feedstocks into valuable products through microbial metabolism. This approach supports the production of biofuels, pharmaceuticals, enzymes, organic acids and specialty chemicals. It offers several advantages over traditional chemical synthesis, including lower operational costs, greater sustainability and improved scalability. The effectiveness of fermentation depends on multiple factors, including the choice of microbial host, the tuning of growth conditions, and the integration of process monitoring and control technologies. Recent innovations across these areas are enhancing performance, increasing yields and expanding the range of viable applications.
Enhancing yield through genetic modifications
As fermentation processes become more complex, microbial strains must be adapted to meet stricter performance requirements. Modern genome editing tools have made this possible by allowing precise control over genetic functions. CRISPR/Cas systems are widely used in microbial engineering because they allow for efficient, targeted modifications. By using a guide RNA and a Cas protein, researchers can remove unwanted pathways, introduce new genes or regulate existing ones to improve output and reduce waste.
Fermentation vats. Antoine Taveneaux/CC BY-SA 3.0
Cas9 is currently the most common system, but newer variants such as Cas12 and Cas13 are expanding the range of editing strategies. Cas12 enables edits at multiple locations and may support more accurate gene insertion through homology-directed repair. Cas13, which targets RNA instead of DNA, allows for temporary control over gene expression without making permanent genomic changes. These systems help optimize microbial performance under conditions such as osmotic stress, variable pH and nutrient limitations.
In addition to direct editing, CRISPR-based tools are also used to regulate gene activity. CRISPRi and CRISPRa, which silence or activate genes without modifying DNA, are useful for adjusting metabolic balance and controlling pathway activity. These tools allow for more precise tuning of cellular function, especially in cases where minor changes in expression can significantly impact productivity.
To guide strain modifications, researchers now use single-cell omics and computational models to analyze how genetic changes affect metabolism. Machine learning algorithms assist in identifying performance-limiting genes and predicting the outcomes of specific edits. This approach helps prioritize targets and improves the overall efficiency of strain development.
Integrated process control and monitoring
Alongside genetic improvements, modern fermentation also relies on advanced process control to maintain consistent performance. Inline sensors are used to track key variables such as pH, oxygen levels, nutrient availability and product concentration in real time. These inputs are processed by automated control systems that adjust environmental conditions, including agitation speed, airflow and feed rate, to keep microbial cultures in an optimal state.
Predictive tools based on machine learning are now used to anticipate fluctuations before they affect production. Engineers use these tools to analyze sensor data and historical records, allowing for early intervention when trends suggest a drop in performance. One example is digital twin simulation, where a virtual model of the fermentation system is used to test different strategies and refine process parameters without interrupting ongoing operations.
Closed-loop control systems apply adjustments quickly and consistently, reducing the chance of operator error and supporting reproducible results across multiple batches. These systems work especially well with single-use bioreactors, which simplify cleaning and setup while minimizing contamination risks. Modular hardware designs also allow facilities to scale production up or down as needed. Together, these technologies support flexible, high-throughput fermentation processes that can meet changing industrial demands.
Industrial applications
Dan Palraz/CC BY-SA 4.0
Fermentation is widely applied across multiple sectors to produce pharmaceuticals, biofuels, organic acids, amino acids and industrial enzymes. Engineered microbial strains allow for more efficient conversion of renewable substrates, such as glucose or glycerol, into target products. Applications now increasingly involve microbes tailored for specific outputs through genome editing, transcriptional control and pathway optimization. These capabilities support high-yield production of compounds like lactic acid, ethanol, and recombinant proteins at commercial scale.
The adoption of integrated process control and modular bioreactor systems further improves consistency, scalability and cost-effectiveness. Fermentation processes are also becoming more sustainable by using waste-derived feedstocks and applying closed-loop control systems that reduce material losses and resource consumption. In many cases, byproducts are recovered or repurposed to add value to the overall process. Together, these developments position microbial fermentation as a key platform for modern biomanufacturing.
Future perspectives
Advances in microbial engineering and bioprocess automation are expected to expand the capabilities of fermentation even further. Current research focuses on constructing highly specialized strains, sometimes referred to as microbial chassis, that are designed for specific classes of products. These strains can be modified using CRISPR-based systems, omics data and machine learning-guided design to improve efficiency, reduce side reactions and operate under more extreme process conditions.
At the process level, continuous fermentation and real-time monitoring are likely to become standard for high-volume production. These systems improve productivity while enabling faster response to process deviations. As these technologies mature, regulatory frameworks will need to evolve to address safety, traceability and quality control for genetically modified production strains. Continued coordination between strain development and process engineering will be essential to fully realize the potential of next-generation fermentation platforms in industrial applications.
To further accelerate strain development, researchers are integrating genome editing with high-throughput screening technologies. One promising approach combines microfluidic devices with directed evolution. These systems generate thousands of microbial variants by introducing small genetic changes, then culture and test them in parallel under controlled conditions. This allows for rapid evaluation of traits such as growth rate, product formation or stress resistance across large populations. Automated imaging and analysis identify top-performing variants for further optimization. By capturing beneficial mutations that might otherwise go unnoticed, this method supports the development of industrial strains that are both productive and robust under real-world fermentation conditions. It also reduces development timelines by replacing trial-and-error testing with data-rich, scalable experimentation. This integration of genetic design with rapid screening is becoming a critical step in modern strain engineering workflows.
