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Understanding and controlling filamentous growth of fungal cell factories: novel tools and opportunities for targeted morphology engineering

Summary

Fungi are used in industry to produce medicines, chemicals, and enzymes in large fermentation tanks. However, the way these fungal cells grow and clump together greatly affects how much product they make, but scientists don’t yet fully understand or control this growth. This review discusses new tools like genetic engineering, computer modelling, and special imaging techniques that are helping researchers better understand and control fungal growth patterns to improve industrial production.

Background

Filamentous fungi are efficient producers of platform chemicals, proteins, enzymes and natural products in large-scale bioreactors. Fungal hyphae self-assemble into various macromorphologies (dispersed mycelia, clumps, pellets) that significantly impact bioprocess productivity but remain largely unpredictable and uncontrollable.

Objective

To review novel genomic, genetic, metabolic, imaging and modelling tools that provide insights into filamentous fungal growth and product formation. The paper discusses how these tools can enable rational morphology engineering and improved bioprocess control.

Results

Key advances include: development of genome editing and conditional gene expression systems; co-expression network approaches predicting functions for ~9600 proteins; subcellular and population-level mathematical models; X-ray micro-computed tomography for non-destructive 3D pellet reconstruction; and improved understanding of rheological properties and shear stress effects.

Conclusion

Despite recent advances, a universal model of fungal growth across scales does not yet exist. Future progress requires tight collaboration between experimenters and modellers to develop transferable tools for predicting and controlling optimal macromorphology for given products and strains.
  • Published in:Fungal Biology and Biotechnology,
  • Study Type:Review,
  • Source: 10.1186/s40694-021-00115-6, PMID: 34425914
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