Unlocking the Synthetic Potential of Yarrowia lipolytica: Innovating Gene Expression Tools

ABSTRACT

Yarrowia lipolytica, with its robust lipid metabolism capabilities, efficient secretion system and generally recognised as safe (GRAS) status, has become a highly promising microbial chassis in synthetic biology. However, compared with model microorganisms such as Saccharomyces cerevisiae , the underdevelopment of gene expression tools in Y. lipolytica has become a critical bottleneck, limiting its industrial application. Currently, its core tools face two critical challenges: promoters with limited dynamic regulatory capacity, leading to metabolic flux imbalance; and gene editing systems plagued by low efficiency and poor multiplex compatibility. This opinion article focuses on these two pivotal directions to dissect their technical bottlenecks and propose innovative solutions: constructing dynamic transcriptional regulatory modules through machine learning guided design and synthetic biology approaches and developing orthogonal CRISPR systems and multiplex editing platforms.

As an important industrial microbial chassis, the development of gene expression tools for Yarrowia lipolytica is of great significance for advancing its industrial application process. This opinion article highlights the recent developments in promoter engineering and gene editing systems, current challenges and future prospects.

1. Promoter Engineering

1.1. Natural Promoter Mining and Optimization

The metabolic engineering of Y. lipolytica is currently highly dependent on the development of natural promoters, including constitutive and inducible promoters. Constitutive promoters such as P_TEF, P_EXP and P_GPD have been extensively studied, with their strengths quantified through fluorescent or luciferase‐based reporter systems (Blazeck et al. 2011; Liu, Cui, et al. 2022; Kang et al. 2025). However, promoter strength is significantly influenced by genetic background and cultivation conditions and the existing promoters remain insufficient. Inducible promoters dynamically regulate gene expression through specific signals, such as P_XPR2 (peptone‐inducible), P_POX2/P_POX5 (oleic acid‐inducible), P_ICL1 (ethanol‐inducible), P_ALK1 (alkane‐inducible) and P_EYK1 (erythritol‐inducible) (Davidow et al. 1987; Sassi et al. 2016; Juretzek et al. 2000; Trassaert et al. 2017; Xiong and Chen 2020). These promoters enable dynamic regulation of metabolic flux, but their induction conditions require precise optimization (Peng et al. 2015). Despite progress, the diversity of both promoter types remains limited, particularly due to the lack of high‐strength and flexibly regulated inducible systems. Future efforts should focus on expanding the promoter toolbox through genome mining and cross‐condition characterisation to support the optimization of complex metabolic pathways and synthetic biology applications.

1.2. Rational Design of Synthetic Promoters

Research on the rational design of synthetic promoters in Y. lipolytica has focused on two key directions: structural optimization and dynamic regulation. At the structural level, core promoter engineering focuses on the precise modulation of TATA box configuration, transcription start site (TSS) spacing and nucleotide composition, revealing the decisive role of key sequences in transcriptional efficiency. Replacing or engineering the TATA box can increase promoter activity by two to fivefold (Zhao et al. 2021; Shabbir Hussain et al. 2016). Through systematic optimization of the 30 bp core promoter motif between the TATA box and the TSS, it was demonstrated that T‐rich elements and high T content significantly enhance promoter strength. The optimal design achieved a 5.5‐fold increase in lycopene conversion efficiency and β‐carotene production reaching 7.4 mg/g DCW (Liu et al. 2020). Hybrid promoter engineering achieves functional programmability through modular recombination of core promoter with upstream activating sequence (UAS). For instance, the tandem integration of 12 UAS_TEF copies elevated promoter strength by 4.5‐fold compared to native versions (Blazeck et al. 2013). The incorporation of dynamic‐responsive UAS elements enabled the construction of high‐efficiency regulatory systems inducible by oleic acid or copper ions. The copper‐inducible promoter exhibiting a 30‐fold increase in activity compared to uninduced conditions (Xiong and Chen 2020; Shabbir Hussain et al. 2017). Explorations of functional compatibility in cross‐species UAS elements and the construction of UAS tandem libraries further expanded design flexibility. For example, a promoter library containing 1–32 copies of UAS1B demonstrated a dynamic range exceeding 400‐fold, showcasing its broad‐spectrum regulatory capacity for gene expression intensity (Blazeck et al. 2011).

In the realm of dynamic regulatory system, researchers aim to overcome the limitations of traditional induction systems by integrating native and exogenous transcription factors (TFs). TFs specifically recognise promoter sequences through their DNA‐binding domains and recruit transcriptional machinery via their activation domains. While native regulatory mechanisms are inherently compatible with host metabolic networks, they often introduce metabolic burdens and genetic instability in heterologous product synthesis. To address this, researchers developed artificial regulatory systems with enhanced orthogonality (Wu et al. 2016). These systems employ exogenous TFs or reconstituted functional modules to decouple synthetic pathways from endogenous host networks (Naseri et al. 2017; Zhu et al. 2022; Dossani et al. 2018). Prokaryotic transcription factor‐based biosensors exhibit cross‐species compatibility. For instance, the prokaryotic FdeR‐FdeO system achieved naringenin‐sensitive regulation in Y. lipolytica, while maintaining production stability over 324 generations (Lv et al. 2020). A xylose‐inducible biosensor, integrating the Escherichia coli activator XylR, the xylO operator and the VPR‐H activation domain, dynamically matches xylose concentrations to optimise metabolic flux (Wei et al. 2020). Innovations in light‐controlled systems further expand non‐chemical induction approaches: a green light‐responsive system combining CarH with VPR‐HSF1 boosted coumaric acid and naringenin production by 2‐fold and 2.6‐fold, respectively (Zhang et al. 2021), while the blue light‐inducible EL222‐VP16 system exhibited approximately 130‐fold fluorescence enhancement following illumination (Wang et al. 2022). However, such systems remain constrained by equipment costs and scalability challenges, necessitating the development of more cost‐effective metabolite‐responsive elements. Although temperature‐inducible systems have yet to achieve breakthroughs in Y. lipolytica, their inherent compatibility with fermentation parameters provides a promising direction for future designs (Gou et al. 2024; Lu et al. 2024). Current research is advancing toward multifactorial orthogonal regulatory networks, which combine light‐controlled, chemically inducible and temperature‐responsive modules to establish the independent control capabilities required for complex metabolic engineering. However, limited by the scarcity of orthogonal transcription factors and insufficient component resources, the dynamic range and robustness of such systems still require optimization.

2. Gene Editing

2.1. Episomal Plasmid and Genomic Integration Systems

Y. lipolytica lacks native episomal plasmids. To address this limitation, researchers developed artificial plasmids based on chromosomal ARS/CEN sequences, but these faced genetic instability (Fournier et al. 1993). Subsequent identification of a 516‐bp mtORI sequence enabled efficient autonomous replication and stable expression of circular plasmids (Cui, Zheng, Jiang, et al. 2021), while promoter‐engineered CEN plasmids achieved an 80% increase in gene expression (Vernis et al. 1997). In multigene assembly, early one‐step integration (21% efficiency) was replaced by modular Golden Gate assembly technology, which standardised vector libraries to boost β‐carotene pathway assembly efficiency to 67%–90% (Celinska et al. 2017). Derived toolkits enabled single‐step assembly of three transcriptional units, successfully constructing xylose utilisation and violacein biosynthesis pathways (the latter fine‐tuned by differential promoter strengths) (Larroude et al. 2019; Tong et al. 2021). Additionally, the YaliBricks system and the CRISPR/Cas9‐based EasyCloneYALI toolkit (editing efficiency > 80%) expanded regulatory element libraries and provided precision editing capabilities, significantly enhancing the efficiency and stability of engineered complex metabolic pathways (Wong et al. 2017; Holkenbrink et al. 2018).

Genome editing provides higher efficacy than episomal plasmid systems for genetic manipulation in Y. lipolytica. Targeted genomic integration relies on the host's double strand break (DSB) repair mechanisms, which primarily include two distinct pathways: homologous recombination (HR) and non‐homologous end joining (NHEJ) (Bai et al. 2021; Lieber 2010). HR, as a precise repair mechanism, enables targeted integration of exogenous DNA via homology arms. However, the extremely low HR efficiency in Y. lipolytica severely limits its application. Studies have shown that disrupting core genes in the NHEJ pathway (e.g., Ku70) significantly enhances HR efficiency (Verbeke et al. 2013). In contrast, NHEJ, the dominant DNA repair mechanism in Y. lipolytica, offers unique advantages for random integration due to its high efficiency and independence from homologous sequences. It has been widely utilised for constructing modular expression libraries, optimising metabolic pathways and screening mutant libraries (Cui et al. 2019; Liu, Liu, et al. 2022). However, NHEJ‐mediated integration has notable limitations: random insertions may disrupt essential genes, require selection markers for screening and exhibit low targeted integration efficiency.

2.2. CRISPR Gene Editing System

In early studies, Schwartz et al. (2016) developed a high‐efficiency editing system by codon‐optimising the Cas9 gene, fusing it with a nuclear localization signal and driving its expression under the control of the strong hybrid promoter UAS1B8‐TEF. Through optimization of sgRNA expression using the SCR1’‐tRNA (Gly) promoter, they achieved markerless homologous recombination efficiency of up to 64%, and this efficiency further increased to 100% in NHEJ‐deficient strains (Schwartz et al. 2016). In subsequent studies, researchers employed the P_TEF‐intron hybrid promoter to drive Cas9 expression, flanking sgRNA cassettes with self‐cleaving hammerhead ribozyme and hepatitis delta virus ribozymes. Through a single‐plasmid triple‐sgRNA design, they achieved simultaneous knockout of three target genes with approximately 19% efficiency (Gao et al. 2016). An orthogonal T7 polymerase‐based sgRNA expression system was developed. This system consists of a T7 polymerase with SV40 nuclear localization tag driven by a strong constitutive promoter and a T7 phi9 promoter driving the guide RNA expression. Independent of host RNA processing machinery, it supports universal applications across diverse yeast species (Morse et al. 2018). By employing a red fluorescent protein reporter system, both the potential toxicity of Cas9 overexpression and the critical role of sgRNA expression levels in indel formation were revealed. When single‐stranded DNA oligonucleotides were transiently supplied, a 16% targeted genomic integration efficiency was achieved (Borsenberger et al. 2018). A CRISPR‐Cas9‐based markerless integration system, utilising a dual‐plasmid strategy, demonstrated 48%–69% heterologous sequence integration efficiency across five non‐essential genomic loci in Y. lipolytica and was successfully applied for the efficient assembly of the lycopene biosynthesis pathway (Schwartz et al. 2017). Gao et al. developed a dual‐sgRNA strategy that enabled 3.5 kb gene excision via NHEJ with 14%–33% efficiency. When combined with HR or homology‐mediated end joining (HMEJ), exogenous sequence integration efficiency rose to 37%, while the gene‐empty carrier rate decreased from 15% to 7%, marking the first application of HMEJ technology in microorganisms (Gao et al. 2018). Concurrently, our team created a homology arm‐free CRISPR/NHEJ‐based integration tool, streamlining the traditional HR‐dependent workflow (Cui, Zheng, Zhang, et al. 2021). Subsequently, we integrated NHEJ with fluorescence‐activated cell sorting to construct a green fluorescent protein (GFP)‐based random expression library. By screening high‐expression strains, we identified novel loci exhibiting both high integration efficiency and robust heterologous gene expression (Liu, Cui, et al. 2022). CRISPR‐Cas12/Cpf1 is a novel gene‐editing tool that utilises a single‐stranded RNA guide to recognise TTTN sequences (PAM), making it particularly suitable for editing high‐GC genomes. In Y. lipolytica, this system achieves high‐efficiency editing, with dual‐target efficiency reaching 75%–83% and triple‐target efficiency at 41.7% (Yang et al. 2020). Base editors, created by fusing deactivated Cas9 (dCas9) or nickase Cas9 (nCas9) with cytidine deaminase, enable precise editing at specific loci. For example, the base editor engineered by Bae et al. in Y. lipolytica achieved 94% single‐gene and 34% double‐gene disruption efficiency (Bae et al. 2020). Additionally, CRISPR systems enable gene expression regulation: CRISPRi suppresses transcription by blocking RNA polymerase via dCas9 or dCpf1 (Misa and Schwartz 2021; Zhang et al. 2018), while CRISPRa upregulates gene expression by coupling dCas9 with transcriptional activation domains (Schwartz et al. 2018). Studies have shown that CRISPRi technology can suppress chromosomally integrated GFP by expressing dCpf1 or dCas9, with repression efficiencies of 78% for dCpf1 and 89% for dCas9 (Zhang et al. 2018). A dual CRISPR‐STAR system, utilising orthogonal scaffold RNAs (scRNAs), significantly enhanced fatty alcohol production in Y. lipolytica by simultaneously activating the fatty acyl‐CoA reductase gene (FAR) and repressing the peroxisome biogenesis‐related gene (PEX10) (Chen et al. 2025). While CRISPR technologies and their derivatives in Y. lipolytica have progressed from foundational tool development to functional applications, challenges remain in improving editing efficiency, specificity and dynamic regulation capabilities (Figure 1).

FIGURE 1.

Gene expression tools for Y. lipolytica. (A) Promoter engineering optimization. This involves both the mining and optimization of natural promoters, and the rational design of synthetic promoters. The promoter primarily consists of two functional elements—the upstream activating sequence (UAS) and the core promoter. Key components of these elements include the transcription factor binding sites (TFBSs) and the TATA box, respectively. Synthetic transcription factors typically combine a DNA‐binding domain (DBD) with activation domain (AD) to activate target genes. (B) Advances in gene editing tools. This section encompasses episomal expression systems, genomic integration systems utilising homologous recombination (HR) or non‐homologous end joining (NHEJ) mechanisms and CRISPR‐based genome editing systems.

3. Challenges and Prospects

Despite being widely recognised as a highly promising microbial chassis for industrial biotechnology (Duman‐Ozdamar et al. 2025; Lu et al. 2021), the limited availability of efficient gene expression tools in Y. lipolytica has constrained its broader industrial adoption. Native promoters exhibit limited regulatory capacity, genome editing relies on inefficient/random repair mechanisms (HR/NHEJ), CRISPR systems are hindered by host heterogeneity, sgRNA instability and Cas9 cytotoxicity, while multiplex editing struggles with vector payload overload and synergistic off‐target effects. These limitations collectively impede synthetic biology platform development and industrial‐scale applications.

3.1. Promoter Engineering: From Static Regulation to Dynamic Intelligent Design

Future research will prioritise engineering dynamically tunable and smart‐responsive synthetic promoters to overcome the functional limitations of traditional single‐purpose promoters. Leveraging machine learning to decode nonlinear relationships between conserved promoter motifs and expression intensity will enable the creation of synthetic promoter libraries with expanded dynamic ranges, such as graded‐intensity promoters and logic‐gated promoters. Third‐generation sequencing technologies will facilitate the mining of cryptic genomic regulatory elements, and combining high‐throughput functional validation with deep learning models will drive the design of non‐natural high‐performance variants, overcoming limitations inherent to native promoter libraries. Further integration of metabolite biosensors with orthogonal induction systems will advance self‐regulatory feedback networks, allowing real‐time adaptation of metabolic flux to dynamic fermentation conditions.

3.2. Gene Editing: Orthogonal Systems and Multi‐Gene Precision Control

Gene editing technologies will evolve toward orthogonalization, multiplexing and scarless precision. The development of CRISPR‐Cas9 variants optimised for Y. lipolytica, combined with self‐cleaving ribozymes or tRNA spacers, will enable single‐vector delivery of multiple sgRNAs, thereby circumventing vector overloading and off‐target effects. Prime Editing and Base Editing technologies will enable scarless editing and precise base substitution, addressing bottlenecks in synchronous multi‐locus editing. Genome‐wide screening will identify high‐expression, neutral integration sites, while machine learning prediction integrated with automated platforms will optimise sgRNA design and editing efficiency, reducing screening costs. Concurrently, the development of self‐selection systems tailored for industrial strains and the integration of CRISPR with synthetic biology tools will achieve multi‐locus precision integration and complex metabolic pathway assembly. These advances will deliver efficient, versatile and scalable editing solutions for biomanufacturing and synthetic biology.

4. Conclusion

Future advances will be achieved through integrated high‐throughput screening and deep learning to decode genetic element functions, enabling the establishment of standardised CRISPR‐promoter element libraries. By coupling genome reprogramming with metabolic regulation via automated design‐build‐test‐learn (DBTL) cycles, Y. lipolytica will be transformed into intelligent biofactories capable of autonomously sensing environmental cues and dynamically balancing metabolic fluxes. This systematic integration will propel synthetic biology toward CRISPR‐driven precision editing and fully automated directed evolution.

Author Contributions

Xiaoqin Liu: conceptualization, writing – original draft, writing – review and editing. Qingsheng Qi: conceptualization, supervision, writing – original draft, writing – review and editing, project administration.

Conflicts of Interest

The authors declare no conflicts of interest.

Liu, X. , and Qi Q.. 2025. “Unlocking the Synthetic Potential of Yarrowia lipolytica: Innovating Gene Expression Tools.” Microbial Biotechnology 18, no. 8: e70185. 10.1111/1751-7915.70185.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.