Systems Metabolic Engineering of Bacillus subtilis for High-Level Riboflavin Production via Dynamic Regulation and CRISPRi Screening

Abstract

Riboflavin is the precursor of flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), and is widely used in food, feed, and pharmaceutical industries. However, riboflavin production by microbial fermentation in Bacillus subtilis is still limited by the complex multilayered regulation of riboflavin biosynthesis. In this study, we systematically engineered B. subtilis to improve riboflavin production. First, the riboflavin biosynthetic pathway was strengthened by relieving FMN-mediated feedback inhibition, replacing the native promoter of the rib operon, and optimizing ribA copy number, which increased the riboflavin titer to 2144.6 mg/L. Next, the supply of the precursors ribulose-5-phosphate (Ru5P) and guanosine triphosphate (GTP) was enhanced by reinforcing the pentose phosphate and purine pathways, and competing branch pathways were dynamically regulated using an FMN-responsive switch. In particular, dynamic regulation of purA and pgi further increased the titer by 31.4% to 4.6 g/L. Finally, guided by the genome-scale metabolic model etiBsu1209, we combined target prediction with CRISPRi library screening and identified co-repression of ilvD and guaC as an effective strategy, increasing the titer to 6.6 g/L. After further optimization of cultivation conditions, the final strain produced 8.4 g/L riboflavin in shake flasks and 20.2 g/L in a 5 L bioreactor. These results provide an effective strategy for riboflavin overproduction in B. subtilis and for engineering complex metabolic pathways.

Graphical abstract

Keywords

Bacillus subtilis / Systems metabolic engineering / CRISPRi screening / Dynamic regulation / Genome-scale model

Highlight

	● FMN feedback inhibition was relieved and ribA copy number optimized.
	● Dynamic regulation of branch pathways via RFN element redirected flux.
	● Genome-scale model-guided CRISPRi screening identified ilvD and guaC.

1 Introduction

Riboflavin, also known as vitamin B₂, is a water-soluble vitamin widely used in feed additives and dietary supplements [1]. It can be converted into flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), two essential cofactors involved in a wide range of cellular redox reactions [2]. While plants and microorganisms can synthesize riboflavin de novo, animals lack this capability and therefore depend on dietary intake [3]. In addition to its nutritional value, riboflavin has recently attracted increasing attention because of its potential roles in the treatment of neurological disorders and cancer [4,5]. Riboflavin can be produced by chemical synthesis, semi-synthesis, or microbial cultivation. Among these approaches, microbial production has largely replaced traditional chemical synthesis because of its economic and environmental advantages [6]. To date, several microbial hosts have been engineered for riboflavin production, including B. subtilis [7], Ashbya gossypii [8], and Corynebacterium ammoniagenes [9]. Among these, B. subtilis is one of the most important industrial producers owing to its generally recognized as safe (GRAS) status, simple nutritional requirements, and ease of downstream processing.

In B. subtilis, riboflavin biosynthesis is a highly coordinated process involving more than 30 enzymes and is closely connected to four major metabolic pathways: the Embden-Meyerhof-Parnas (EMP) pathway, the pentose phosphate pathway (PPP), the purine metabolism pathway, and the riboflavin synthesis pathway [10] (Fig. 1). Ru5P and GTP, derived mainly from the PPP and purine metabolism, respectively, serve as the two direct precursors for riboflavin biosynthesis. Consequently, numerous studies have focused on enhancing precursor supply and elevating riboflavin operon (rib operon) transcriptional levels. Significant progress has been made in enhancing the supply of precursors. For instance, overexpression of the zwf gene driven by a xylose-inducible promoter increased the concentration of the precursor Ru5P nearly 4-fold [11]. Similarly, by constructing a regulatable intergenic library to coordinate expression of zwf, ywlF, and ribA genes, intracellular Ru5P levels were significantly elevated, ultimately boosting riboflavin titer by 64.35% [12]. To improve GTP supply, overexpression of deoD and hprT genes in the purine salvage pathways increased the GTP concentration and elevated the riboflavin titer by 19.29% [13]. Additionally, other strategies such as mutagenesis [14], high-throughput screening [15], and omics analysis [16,17] are also widely applied to the biosynthesis of riboflavin. Despite these advances, the biosynthetic capability for riboflavin in B. subtilis still faces key limitations. These include the unclear genetic background of mutagenic strains, which limits further metabolic engineering modifications, as well as an imbalance between cell growth and product synthesis, coupled with a lack of tools for discovering new targets.

In this study, we first enhanced the transcriptional levels of genes involved in the riboflavin synthesis pathway through promoter engineering and copy number optimization. Subsequently, modular engineering strategies such as feedback regulation disengagement and key gene overexpression increased the supply of the dual precursors Ru5P and GTP. Next, we investigated the regulatory role of the FMN riboswitch (also termed RFN element, located in the 5’-UTR of the ribD gene) in modulating downstream gene expression. This riboswitch indirectly responds to changes in riboflavin levels. By utilizing the RFN element to regulate branch genes in the riboflavin synthesis pathway, we further concentrated the carbon flux. Finally, using the etiBsu1209 metabolic network model, we predicted potential targets within the riboflavin synthesis pathway and constructed a gene knockdown library to screen for the optimal combinations. Using this integrated strategy, the final strain produced 8.4 g/L riboflavin in shake flasks and 20.2 g/L in fed-batch cultivation in a 5 L bioreactor.

2 Materials and Methods

2.1 Strains and plasmids

The strains used in this study are listed in Table 1. Strain B. subtilis G600 was derived from B. subtilis 168 constructed in our laboratory. The plasmids used in this study are listed in Table 2. Plasmid construction was performed in Escherichia coli DH5α using a seamless cloning kit (Sangon Biotech, Shanghai, China) according to the manufacturer’s instructions. All recombinant B. subtilis strains were transformed using a previously reported method [18]. Plasmids were extracted using a plasmid extraction kit from Sangon Biotech (Shanghai, China) and subsequently sequenced at GENEWIZ (Suzhou, China).

2.2 Medium

Luria-Bertani (LB) medium (g/L): yeast extract 5, tryptone 10, sodium chloride 10. Shake flask medium (g/L): glucose 90, peptone 12, yeast extract 12, urea 6, glycerol 5, monopotassium phosphate 9.55, dipotassium phosphate 2.5, magnesium sulfate 3. LB with glucose (LBG) medium (g/L): glucose 20, yeast extract 5, tryptone 10, sodium chloride 10. Fed-batch cultivation medium (g/L): glucose 90, peptone 20, yeast extract 20, urea 10, glycerol 5, monopotassium phosphate 9.55, dipotassium phosphate 2.5, magnesium sulfate 3. Feed medium (g/L): glucose 600, yeast extract 30. The culture medium was sterilized at 115 °C for 30 min. Antibiotics were used at the following concentrations (μg/mL): kanamycin, 50; bleomycin, 20; ampicillin, 100; spectinomycin, 100; chloramphenicol, 5. All chemicals were purchased from Sinopharm Group (Shanghai, China).

2.3 Markerless genetic modification using the Cre/lox system

Markerless gene integration was performed using a previously reported strategy [19]. To achieve target gene overexpression via copy number increase, the upstream and downstream flanking sequences (1000 bp each) of the genomic integration site, the target gene, and promoter were amplified from B. subtilis. These four fragments were assembled with the lox71-zeo-lox66 cassette (from plasmid p7Z6) via triple-fusion polymerase chain reaction (PCR). The purified assembly product was used to transform competent B. subtilis cells. For marker excision, the temperature-sensitive Cre-expressing plasmid pDG148 was introduced into the validated recombinant strain. This step facilitates recombination between the lox71 and lox66 sites, leading to the removal of the resistance marker. Subsequently, the cells were incubated at 50 °C for 12 h to cure the intracellular pDG148 plasmid.

The knockout strategy followed a procedure similar to that used for gene overexpression. Briefly, the upstream and downstream flanking sequences (1000 bp each) of the target gene were amplified and assembled with the lox71-zeo-lox66 cassette via triple-fusion PCR.

To achieve dynamic regulation of the target gene using the RFN element, three fragments—comprising the upstream and downstream flanking sequences (1000 bp each), and the RFN element sequence were amplified. These fragments were assembled with the lox71-zeo-lox66 cassette via triple-fusion PCR. The purified assembly product was then used to transform competent B. subtilis cells.

2.4 Gene editing operations performed using the CRISPR/Cpf1 system

Site-directed point mutations were introduced into the genome using a dual-plasmid CRISPR/Cpf1 system, as previously described [20]. The system comprises pHT-XCR6, which encodes the Cpf1 nuclease under a xylose-inducible promoter, and pcrF19NM2, which harbors the crRNA expression cassette and a homologous recombination repair template. All crRNAs were designed using the CRISPR-DT web server, with the protospacer adjacent motif (PAM) strictly restricted to TTV (V = A, G, or C) [21].

For genetic manipulation, competent cells were thawed on ice from −80 °C storage. A total of 1000 ng of pHT-XCR6 plasmid DNA was added to 500 μL of the competent cell suspension, followed by incubation at 37 °C with shaking at 220 r/min for 2 h. Transformants were selected on LB agar supplemented with 5 μg/mL chloramphenicol and verified by colony PCR. Positive colonies were subsequently used to prepare fresh competent cells for the second transformation. The pcrF19NM2 plasmid series was introduced into the pHT-XCR6-harboring strain and incubated at 37 °C for 2 h. Cells were then harvested by centrifugation at 4000 × g for 2 min and resuspended in 500 μL of LB medium containing 5 μg/mL chloramphenicol, 10 μg/mL kanamycin, and 3% (w/v) xylose to induce editing. Cultures were incubated at 30 °C with shaking at 220 r/min for 12 h. The cell suspension was concentrated to 150 μL by centrifugation, plated onto LB agar containing the same antibiotics and 3% (w/v) xylose, and incubated at 30 °C. Successfully edited clones were confirmed via colony PCR. Finally, plasmid curing was achieved by cultivating verified strains in LB medium supplemented with 0.1‰ (w/v) SDS at 37 °C and 220 r/min for 12 h.

2.5 Key target gene prediction via metabolic network model

The metabolic network model etiBsu1209 was used to predict key target genes [22]. This model integrates multi-omics data including genomic, transcriptomic, proteomic, and metabolic flux information, incorporating gene expression constraints and biosynthetic pathway simulations beyond traditional flux balance analysis (FBA). Based on reported riboflavin production conditions, the model was configured with glucose and glycerol as mixed carbon sources, with substrate uptake rates ranging from 0 to 1 mmol·gDW⁻¹·h⁻¹. Subsequently, the OptKnock algorithm was applied within the etiBsu1209 framework for genome-wide gene knockout simulations, identifying candidate targets that enhance product synthesis without compromising growth.

2.6 Screening for optimal gene inhibition combinations using 96-well plates

Single colonies were selected from solid medium plates and transferred into 96-well plates (Corning Inc., Corning, NY, USA) containing 150 μL of LBG medium. The 96-well plates were subsequently cultured at 37 °C with shaking at 800 r/min. The riboflavin fluorescence (excitation 473 nm; emission 520 nm), and the optical density at 600 nm (OD_{600 nm}) were measured using a microplate Multi-Mode Reader (Cytation 3; BioTek Instruments, Inc., Winooski, VT, USA) directly [23]. To calculate the relative fluorescence intensity, background absorbance from the medium (OD_bg) and background fluorescence from non-producing strains (FP_bg) were subtracted and the following equation was applied:

(1){\left(\frac{FP}{OD}\right)}_{\text{corrected}}=\frac{FP–{FP}_{\text{bg}}}{OD–{OD}_{\text{bg}}}

Where FP and OD represent the fluorescence intensity and optical density, respectively; FP_bg and OD_bg denote the background fluorescence from non-producing strains and background absorbance from the medium, respectively.

2.7 Shake flask cultivation

A glycerol stock stored at −80 °C was thawed on ice and streaked onto an LB agar plate. After incubation at 37 °C for 12−14 h, a single colony was used to inoculate 2 mL of LB medium in a 14 mL tube to prepare the seed culture. The seed culture was grown at 37 °C with shaking at 220 r/min to the mid-log phase. Subsequently, 5% (v/v) of the seed culture was transferred to a 250 mL conical flask containing 20 mL of shake flask medium. Incubate at 37 °C and 220 r/min until the riboflavin titer ceases to increase, indicating the end of cultivation. Measure the OD_{600 nm} of the cultivation broth every 12 h by taking 0.5 mL samples.

2.8 Fed batch cultivation in 5 L bioreactor

A 75 mL seed culture was grown in LBG medium in a 500 mL baffled shake flask at 220 r/min and 41 °C for 12 h. This seed culture was then used to inoculate into a 5 L bioreactor (Shanghai Dibiol Engineering Co., Ltd., Shanghai, China) containing 1.5 L of fed-batch cultivation medium. Throughout the cultivation, the pH was maintained at 7.0 by automatic addition of 25% (v/v) hydrochloric acid and 50% (v/v) ammonia solution. The dissolved oxygen (DO) level was maintained at 30% by adjusting the agitation speed. The temperature and glucose concentration were controlled at 41 °C and 30.0 g/L, respectively.

2.9 Quantitative reverse transcription PCR (qRT-PCR)

B. subtilis strains were cultivated in shake flasks as described previously. At the indicated time points, cells were harvested, and the cell walls were lysed using lysozyme from Solarbio (Beijing, China). Total RNA was extracted from each strain using the RNA extraction kit from TaKaRa (Beijing, China). Subsequently, the extracted RNA was reverse-transcribed into complementary DNA (cDNA) using the PrimeScript RT reagent kit from TaKaRa (Beijing, China). The synthesized cDNA served as the template for the following real-time quantitative polymerase chain reaction.

qRT-PCR was performed using the SYBR Premix Ex Taq™ Ⅱ Reagent Kit from TaKaRa (Beijing, China). Amplification and fluorescence signal detection were conducted on the LightCycler^® 480 Ⅱ real-time quantitative PCR instrument from Roche Applied Science (Mannheim, Germany). The housekeeping gene rpoA (encoding RNA polymerase α subunit) served as the standard reference. The relative transcription levels of target genes were calculated using the 2^−ΔΔCt method.

2.10 Analytical methods

2.10.1 Cell density determination

Cell growth was monitored by measuring the OD_{600 nm}. Cultivation samples were appropriately diluted with deionized water to ensure readings fell within the linear range (0.2–0.8) of the instrument. Measurements were performed using a UV mini-1240 spectrophotometer (Shimadzu Corp., Kyoto, Japan).

2.10.2 Residual glucose analysis

The concentration of residual glucose in the cultivation broth was determined enzymatically. Samples were appropriately diluted with deionized water to ensure concentrations fell within the linear range of the analyzer. Measurements were performed using a glucose-glutamate analyzer (SBA-40E; Shandong Academy of Sciences Institute of Biology, Shandong, China) following the manufacturer’s instructions.

2.10.3 Riboflavin quantification

For riboflavin determination, an appropriate volume of cultivation broth was diluted with 0.01 mol/L NaOH and centrifuged at 12,000 × g for 5 min to remove cells. The supernatant was further diluted with 0.1 mol/L zinc acetate-sodium acetate buffer (pH 4.42) to maintain absorbance values within the linear range (0.2 to 0.8). Absorbance was measured at 444 nm (OD_{444 nm}) using a UV mini-1240 spectrophotometer (Shimadzu Corp., Kyoto, Japan) [24]. The riboflavin concentration was calculated using the following validated standard equation:

(2)Y=\frac{\left(O{D}_{444\mathrm{n}\mathrm{m}}-0.0203\right)\times DF}{0.0163}\left(R^2=0.9997\right)

Where Y is the concentration of riboflavin (mg/L), and DF is the dilution factor.

2.10.4 Quantification of intracellular ATP

Intracellular ATP content was determined using the ATP Content Detection Kit (Solarbio, BC0300, Beijing, China). The strains were streaked onto agar plates, incubated at 37 °C for 12 h, and then inoculated into LBG medium. When the culture reached an OD_{600 nm} of approximately 1.0, 2 mL of broth was collected and centrifuged at 10,000 × g for 10 min at 4 °C to obtain the cell pellet. The pellet was resuspended in 1 mL of ice-cold extraction buffer and subjected to ultrasonic disruption in an ice bath. ATP was then extracted from the bacteria strictly according to the manufacturer’s instructions and measured with a UV spectrophotometer; the entire procedure was performed on ice [25].

2.11 Statistical analysis

All experiments were independently performed at least three times, and the results were expressed as the mean ± standard deviation (SD).

3 Results

3.1 Optimizing riboflavin operon expression to enhance riboflavin production

In B. subtilis, the expression of the rib operon is under the negative control of FMN. FMN, the downstream product of riboflavin catalyzed by riboflavin kinase RibC (Fig. 2A), binds to the FMN riboswitch located in the 5’-untranslated region of the rib operon mRNA, leading to premature transcription termination [26]. Since complete deletion of the ribC gene causes cell death, we aimed to partially reduce its catalytic activity to relieve feedback inhibition. In our previous work [24], we employed base editors to mutate the ribC gene, the guanine riboswitch and the FMN riboswitch, generating a strain S12 capable of accumulating riboflavin and identifying a feedback-resistant mutation ribC^{F191S/I192T/I195T} (Fig. 2B). However, due to off-target effects of the base editors, the genome of S12 carried multiple undesired point mutations and the growth was significantly inhibited. Therefore, this study employed a CRISPR-mediated genome editing strategy to introduce the intended targeted substitutions, thereby eliminating off-target metabolic burden. By precisely integrating the ribC^{F191S/I192T/I195T} mutations into B. subtilis G600, we constructed strain BSF01, which possesses a well-defined genetic background. We subsequently integrated the mutant to disrupt the structure of the FMN riboswitch, generating strain BSF02. This resulted in a 1.49-fold increase in riboflavin titer, reaching a titer of 264.9 mg/L (Fig. 2C). This indicates that by reducing the conversion of riboflavin to FMN and releasing the inhibition of the FMN riboswitch, the expression of the rib operon can be effectively enhanced, resulting in increased riboflavin titer.

The rib operon houses the five key riboflavin synthesis enzymes (ribA, ribD, ribT, ribH, ribE). We replaced the weak native promoter of the rib operon with three strong promoters: the endogenous B. subtilis promoters P_veg and P₅₆₆, and the synthetic strong promoter P_SPL-L8 [27], generating the engineered strains BSF03 (P_veg), BSF04 (P₅₆₆), and BSF05 (P_SPL-L8), respectively (Fig. 2D). This genetic modification increased riboflavin titer by 43.9%, 42.5%, and 128.4%, respectively, reaching 381.3 mg/L, 377.5 mg/L, and 605.2 mg/L (Fig. 2E). Among them, the P_SPL-L8 promoter had the strongest activity. Next, we further increased the rib operon copy number driven by the P_SPL-L8 promoter to construct the strain BSF06. Shake flask cultivation showed that the riboflavin titer increased by 46.8%, reaching 888.6 mg/L, while the maximum OD_600nm value decreased by 5.9%. Because the ribA gene represents the most critical rate-limiting step in the riboflavin synthesis pathway [28], we integrated a separate ribA gene into the glmS site, constructing strain BSF07. The results showed that overexpression of the ribA gene alone significantly increased the titer by 1.22-fold, reaching 1348.5 mg/L, which was superior to the integration of the complete rib operon. This indicates that under the current engineered strain background, the transcriptional levels of the other four genes (ribD, ribE, ribH, ribT) are not major rate-limiting factors. We further integrated a second copy of the ribA gene, driven by the P_SPL-L8 promoter, at the sscB site of BSF07, generating strain BSF08. Compared with the parental strain BSF07, the riboflavin titer increased by 59.0%, reaching 2144.6 mg/L. However, integrating a third ribA copy resulted in a 19.4% decrease in titer and impaired strain growth, with a 25.5% reduction in maximum OD_{600 nm}. To exclude site effects, a third ribA copy was inserted at the yqiG site in BSF08, generating strain BSF10. Nevertheless, its titer remained significantly lower than BSF08, accompanied by severe growth inhibition (Fig. 2F).

To elucidate the mechanisms underlying copy-number-dependent titer reduction, we measured ribA gene transcriptional levels in strains with different copy numbers using qRT-PCR. The qRT-PCR analysis revealed that ribA expression in the BSF08 strain was 2.5-fold higher than in the BSF07 strain, while ribA expression in BSF09 and BSF10 increased only by 1.89-fold and 1.74-fold, respectively (Fig. 2G). This indicates that further increasing ribA copies in strain BSF08 fails to elevate ribA gene expression. We infer that multiple gene copies driven by the high-strength P_SPL-L8 promoter cause uncontrolled flux through the riboflavin pathway, leading to the accumulation of highly reactive GTP-derived intermediates (e.g., DARPP). In the absence of upstream feedback regulation, these electrophilic compounds likely induce metabolite damage and trigger cellular stress, thereby inhibiting host growth and ultimately limiting riboflavin synthesis [29,30]. To further assess the roles of other genes, engineered strains BSF11, BSF12, BSF13, and BSF14 were constructed by overexpressing ribD, ribE, ribT, and ribH, respectively, in the BSF08 strain. Unfortunately, these manipulations failed to enhance the riboflavin titer. This indicates that these genes are not rate-limiting steps in the riboflavin synthesis pathway in BSF08 (Fig. S1).

3.2 Enhancing supply of precursor Ru5P and GTP

Riboflavin biosynthesis requires two key precursors, Ru5P and GTP, and GTP synthesis also depends on Ru5P (Fig. 3A). The precursor Ru5P primarily originates from the PPP. Glucose-6-phosphate dehydrogenase, encoded by zwf, is one of the key enzymes in the oxidative branch of the PPP. Its function is to convert glucose-6-phosphate into 6-phosphogluconate while simultaneously reducing NADP⁺ to NADPH. We first inserted the zwf gene into the fhuD locus under the control of the P_veg promoter to construct the engineered strain BSF15. Shake flask cultivation showed that the riboflavin titer of strain BSF15 increased by 12.1% to 2.4 g/L. We next overexpressed the pgl and gndA genes in the BSF15 strain to direct more flux toward Ru5P, obtaining strains BSF16 and BSF17. Unfortunately, overexpressing these two genes did not increase riboflavin titer and significantly impaired growth, reducing the maximum OD_{600 nm} by 41.0% and 38.6%, respectively (Fig. 3B). We hypothesize that this may result from the enhanced PPP flux competing with the EMP pathway for glucose, thereby reducing the EMP pathway flux and subsequently limiting energy metabolism and biomass accumulation.

GTP biosynthesis begins with Ru5P, which is converted to 5-phosphoribosyl-1-pyrophosphate (PRPP) through catalysis by YwlF and Prs, followed by the generation of GTP via the purine synthesis pathway. In B. subtilis, transcription of the pur operon is negatively regulated by a guanine riboswitch (located in the 5’-UTR of the purE gene), where the binding of guanine prematurely terminates transcription (Fig. 3C). In our previous work, we disrupted the structure of this riboswitch to achieve riboflavin accumulation (Fig. 3D). Therefore, we introduced point mutations (pur-5’-UTR^mut) to disrupt the guanine riboswitch structure into the BSF15 strain, generating strain BSF18. This restored the strain’s growth, with a 29.1% increase in maximum OD_{600 nm} and an 8.3% increase in riboflavin titer.

The purine repressor PurR, encoded by the purR gene, inhibits transcription of multiple genes involved in purine synthesis, transport, and metabolism [31]. Therefore, we knocked out the purR gene to construct strain BSF19, attempting to further release feedback regulation of the purine synthesis pathway. However, the growth and riboflavin titer showed no significant changes. This indicates that the purR gene is not functioning. Previous studies have shown that PurR acts as a transcriptional repressor by binding to the purBox to inhibit the pur operon. High intracellular concentrations of PRPP can bind to PurR, inducing a conformational change that releases PurR from purBox, thereby derepressing the purine biosynthesis pathway [31]. Therefore, we speculate that PRPP may be accumulating intracellularly. The amidophosphoribosyl transferase encoded by the purF gene is subject to feedback regulation by downstream purine nucleotides, representing a critical rate-limiting step in the de novo purine biosynthesis pathway. Therefore, we released feedback inhibition by overexpressing the purF gene mutants purF^{D293V/K316Q/S400W}, generating strain BSF20, which significantly increased riboflavin titer by 19.2%, reaching 3.1 g/L. We further overexpressed prs and ywlF to construct strains BSF21 and BSF22, redirecting metabolic flux from the PPP toward the purine pathway. Shake-flask cultivation revealed that prs overexpression severely impaired strain growth, reducing the maximum OD_{600 nm} by 22.1% and riboflavin titer by 19.3%. Conversely, ywlF overexpression further increased the riboflavin titer by 12.9%, reaching 3.5 g/L (Fig. 3E). This phenotypic divergence may be attributed to differences in the catalytic mechanisms and thermodynamic properties of Prs and ywlF. Prs catalyzes an ATP-dependent phosphotransferase reaction (R5P + ATP → PRPP + AMP). Although this reaction thermodynamically drives PRPP synthesis, it simultaneously depletes the R5P pool and consumes intracellular ATP, thereby causing precursor shortage in the non-oxidative branch of the PPP and inducing energy stress. In contrast, ywlF encodes a reversible isomerase that catalyzes the thermodynamically neutral interconversion between R5P and Ru5P without ATP consumption, only modestly adjusting carbon flux distribution. To verify this hypothesis, we measured intracellular ATP levels. The results showed that BSF21 exhibited an ATP content of 3.5 μmol/10⁹ cells, representing a 23.9% decrease compared to BSF20 (4.6 μmol/10⁹ cells), whereas the ATP content of BSF22 (5.4 μmol/10⁹ cells) increased by 17.3% relative to BSF20. These results confirm that the growth inhibition caused by prs overexpression is primarily attributable to decreased ATP levels (Fig. 3F).

3.3 Dynamically modulating branch pathways using RFN element

In B. subtilis, the riboflavin synthesis pathway is long and involves numerous branching metabolic pathways (Fig. 4A). Since these pathways and their metabolites play indispensable roles in various physiological processes, direct knockout of related genes would severely impair the normal growth and metabolism of the bacterial cells [32]. To address this issue, we tried to construct a switch to dynamically regulate these branch pathways.

The RFN element serves as a natural sensor that represses downstream gene expression via transcriptional attenuation upon binding to FMN [33]. Given that intracellular FMN levels correlate positively with riboflavin concentrations, we repurposed the RFN element for the dynamic regulation of competing pathways. By incorporating the RFN element, we can achieve a metabolic state-dependent downregulation: as riboflavin (and subsequently FMN) accumulates, the expression of these competing genes is gradually suppressed, thereby redirecting metabolic flux toward riboflavin synthesis without compromising cell viability.

To verify the dynamic regulatory capacity of the RFN element on downstream gene expression, we targeted the purA gene, whose attenuated expression promotes precursor inosine monophosphate (IMP) accumulation and its subsequent conversion to GTP, thereby increasing riboflavin precursor supply and enhancing riboflavin production [16]. To ensure the integrity of the RFN element, we designed primers to amplify the first structural gene of the rib operon, specifically the 300 bp DNA sequence upstream of this gene, as the RFN element (Fig. 4B). Subsequently, the RFN element was integrated upstream of the structural gene of purA to construct strain BSF23. Shake flask cultivation showed that the riboflavin titer of strain BSF23 increased by 8.5%, reaching 3.8 g/L (Fig. 4C). The changes in purA gene expression at 12, 24, and 36 h during shake flask cultivation were measured by qRT-PCR, using strain BSF22 as the control. qRT-PCR results showed that at the early cultivation stage (12 h), purA gene expression in strain BSF23 decreased by only 20.0%, while at 36 h, it decreased by 61.1% (Fig. 4D). This confirms that the RFN element indeed indirectly responds to riboflavin concentration dynamics to regulate gene expression. Growth curves in shaking flasks also indicate that strain growth was largely unaffected in the early phase. After 48 h, as FMN accumulated, the RFN element’s inhibitory effect on gene expression gradually intensified, subsequently impacting strain growth (Fig. 4E).

Based on the successful application of the RFN element in regulating purA expression, we further employed it to regulate other branch pathway genes. We selected pgi from the EMP pathway, tkt and rpe from the PPP, hisZ and hisG (both located in the his operon) from the histidine pathway, and yfkN from the purine pathway as target genes. The RFN element was integrated into their promoter regions to construct strains BSF24, BSF25, BSF26, BSF27 and BSF28. Shake flask cultivation showed that after weakening the pgi gene in the EMP pathway, the riboflavin titer reached 4.6 g/L, representing a 21.0% increase (Fig. 4F). Weakening the rpe and tkt gene in the PPP led to decreased riboflavin titer, suggesting that regulating the non-oxidative branch of the PPP may require more precise methods. Regulation of the his operon (competing for PRPP) and the nucleotidase gene yfkN (degrading adenosine monophosphate (AMP) and guanosine monophosphate (GMP) using the RFN element did not increase riboflavin titer, indicating that these branch pathways are not critical bottlenecks in the engineered strain.

The pyrE gene, which competes with the purine pathway for PRPP, is located at the terminus of the pyr operon. To disrupt this competitive flux while avoiding polar effects on upstream genes, we specifically knocked out pyrE, thereby generating strain BSF29. Although this modification increased the riboflavin titer by 7.8% to 4.1 g/L, it caused severe growth defects and hindered subsequent genetic manipulation of the strain. This growth defect is hypothesized to result from impaired pyrimidine synthesis. However, exogenous uridine monophosphate (UMP) supplementation failed to alleviate it, and the underlying mechanism requires further investigation. For these reasons, strain BSF29 was not selected as the chassis strain for further development.

3.4 Identifying key targets for riboflavin production using the etiBsu1209 model

Due to the complexity of the riboflavin synthesis pathway, traditional single-gene modification strategies often fail to achieve linear increases in titer due to compensatory regulation or flux redistribution, sometimes even resulting in negative synergistic effects. Therefore, systematically identifying key rate-limiting nodes in riboflavin synthesis and selecting non-intuitive genetic intervention targets with positive gain effects has become a core challenge for further breakthroughs in titer bottlenecks.

To address these issues, this study conducted a systematic analysis of the riboflavin synthesis pathway using the genome-scale metabolic network model etiBsu1209 [22], aiming to predict potential rate-limiting steps and associated regulatory targets within the global metabolic context. Through constrained flux balance analysis (cFBA) combined with the minimization of metabolic adjustment (MOMA), the model predicted 34 candidate genes that could potentially enhance riboflavin titer via gene knockout. Furthermore, based on the relevance of these genes to central metabolism and riboflavin synthesis, 18 candidate genes were selected from the initial set of 34 predicted genes for validation (Fig. 5A). These include: (i) PP pathway genes rpe, tkt, tal; (ii) amino acid synthesis genes ilvD, yoaD, kbl, thrD, lysC, tdh; (iii) nucleotide metabolism genes pucG, cdd, yxlA, pucL, pdp, guaC; (iv) citric acid cycle genes citZ, citA, pycA.

Due to the low gene editing efficiency of strain BSF24, strain BSF15 was selected as the starting strain in this study. Knockouts were performed on these 18 genes to construct strains Q1–Q18 with specific strain genotypes listed in Table 1. Shake flask cultivation identified six beneficial knockout targets: ilvD and yoaD in the amino acid synthesis pathway; cdd, yxlA, and pucL in the purine pathway; and citA in the citric acid cycle. Riboflavin production was increased by the knockout of these genes, with titer improvements of 29.2%, 28.6%, 25.9%, 24.7%, 13.6%, and 10.9% (Fig. 5B). Subsequently, these target sites were combined for knockout, resulting in the construction of strain Q19–Q25. The specific strain genotypes are detailed in Table 1. However, shake flask cultivation showed that the riboflavin titer of the combinatorial knockout strains did not improve, and some knockout combinations exhibited a significant decrease in titer. This indicates that the effect of gene knockout combinations on titer enhancement is not simply additive.

3.5 Screening optimal target combinations based on CRISPRi inhibition libraries

To rapidly evaluate the combinatorial effects of model-predicted targets, we constructed a CRISPRi-mediated transcriptional repression library for high-throughput screening. Compared with gene knockout strategies, CRISPRi enables simultaneous transcriptional repression of multiple genes, thereby accelerating the validation of model-predicted gene targets. Additionally, this method allows tunable downregulation of growth-associated nodes while maintaining genomic integrity and viability, redirecting metabolic flux toward desired products. This library consists of two components: dCpf1 and the crRNA array. First, the pcrF19-dCpf1 plasmid was constructed to integrate dCpf1 into the B. subtilis genome, controlled by the promoter P_veg. The crRNA array plasmid was constructed using the Synthetic Oligos Mediated Assembly of crRNA Array (SOMACA) method, described in our previous work [20]. Construction of the crRNA array requires two rounds of PCR. First, a primary scaffold containing DR (Direct Repeat) sequences, crRNA sequences, and separator sequences is synthesized (Fig. 6A). Subsequently, through PCR amplification, different linker combinations and Eco31I restriction enzyme sites were added to both ends of the crRNA scaffold, forming a complete crRNA unit. Finally, all constructed complete crRNA sequences were assembled with the pcrF20NM plasmid backbone to generate a random crRNA array library (Fig. 6B).

To validate the accuracy and diversity of library construction, we first selected eight representative target genes—ilvD, pucL, yoaD, yxlA, cdd, rpe, tkt, and pdp—and designed crRNA sequences within their promoter regions. Subsequently, crRNA units with different linker combinations were constructed. Finally, all constructed fragments were pooled and assembled to generate the pcrF20NM plasmid library containing random triplet crRNA arrays. This library was then transformed into E. coli DH5α for library construction. Next, 15 monoclonal clones were randomly selected for Sanger sequencing analysis. Results showed that 86.6% of positive clones achieved correct insertion and arrangement of distinct crRNAs, with no significant preference or ligation bias observed, confirming the system’s efficient random combinatorial capability (Fig. 6C). This strategy was subsequently extended to all 18 predicted targets to construct a full-scale CRISPRi library. This library was transformed into the riboflavin-producing strain BSF15 for functional screening. After two rounds of screening—primary screening in 96-well plates followed by confirmatory screening in shake flasks—two strains (Strain 12 and Strain 23) were identified with significantly enhanced titers. Both strains achieved a riboflavin titer of 3.8 g/L, representing a 58.3% increase over the parental strain (Fig. 6D). Sequencing analysis of their crRNA arrays revealed identical combinations of guaC and ilvD crRNAs, indicating this pairing likely drives the phenotypic improvement. Subsequently, we extracted the plasmid and transformed it into the high-titer strain BSF24 to construct strain BSF30. Shake flask cultivation revealed a titer of 6.6 g/L, a 43.4% increase compared to BSF24 (Fig. 6E). Furthermore, the growth of strain BSF30 was not compromised (Fig. 6F). This result confirms the effectiveness of the dual-gene combination inhibition strategy.

In the metabolic network, guaC encodes GMP reductase, which catalyzes the conversion of GMP to IMP, while ilvD encodes dihydroxyacid dehydratase involved in branched-chain amino acid (BCAA) synthesis. Although ilvD has not been directly linked to riboflavin metabolism, its functional loss may enhance production through two putative mechanisms: Mechanism 1: sparing glutamate, a key nitrogen donor linked to purine metabolism; and Mechanism 2: redirecting NADPH, a cofactor shared by the BCAA and riboflavin pathways, toward riboflavin synthesis. Thus, the co-inhibition of guaC and ilvD likely improves riboflavin titer by alleviating nitrogen metabolic stress and reducing competition for reducing power.

3.6 Fed-batch cultivation in 5 L bioreactor

To optimize cultivation performance, we employed LBG medium as the seed culture medium and elevated the cultivation temperature from 37 °C to 41 °C (the optimal catalytic temperature for RibA). The final strain BSF30 achieved a riboflavin titer of 8.4 g/L with a yield of 0.093 g/g glucose (at 41 °C), representing a 27% increase compared to cultivation at 37 °C. Moreover, both the glucose consumption rate and the riboflavin productivity of the strain were significantly enhanced (Fig. 7A–7C).

Based on shake flask cultivation results, fed-batch cultivation of the recombinant strain BSF30 was performed in a 5 L bioreactor for riboflavin production. Riboflavin production began to increase rapidly after 20 h of cultivation. When the residual glucose concentration reached 30.0 g/L at 21 h, feeding with carbon sources was initiated to maintain it at that level. The maximum riboflavin titer of 20.2 g/L was achieved at 81 h, with a maximum OD_{600 nm} of 102 (Fig. 7D). Based on the total glucose consumed, the riboflavin yield coefficient reached 0.076 g/g glucose, quantitatively confirming the enhanced carbon flux redirection toward riboflavin biosynthesis. These results demonstrate that the engineered strain BSF30, obtained solely through rational modification, possesses excellent production performance, providing a solid foundation for further strain optimization and industrial-scale production.

4 Discussion

In this study, a systematic metabolic engineering strategy was employed to achieve efficient riboflavin synthesis in B. subtilis. The resulting engineered strain achieved a riboflavin titer of 8.4 g/L under shake flask cultivation conditions, the highest shake flask titer reported to date through rational design strategies alone, and 20.2 g/L riboflavin in a 5 L bioreactor via fed-batch cultivation.

Unlike previous studies that primarily focused on modifying a single pathway, this study simultaneously optimized rib operon expression, precursor supply, and branching metabolic fluxes, demonstrating the advantages of multi-target synergistic modification. The enhancement of the rib operon, particularly the ribA gene, significantly increased riboflavin titer, consistent with the conclusions of previous studies.

Overexpression of the synthetic pathway leads to insufficient precursor supply, thereby creating a new metabolic bottleneck. Therefore, we progressively enhanced the expression of six genes in the Ru5P and GTP precursor synthesis pathways. The co-overexpression of the zwf, ywlF, and purF genes significantly increased riboflavin titer. This indicates that optimizing carbon flux to redirect more toward the PPP and purine metabolic pathways can enhance the supply of both precursors. However, overexpression of the prs gene inhibited cell growth and reduced riboflavin titer. We speculate that this may be related to feedback inhibition of Prs and changes in the flux of the non-oxidative branch of the PPP. Future studies could fine-tune the transcriptional level of the prs gene or introduce prs mutants to lift feedback inhibition. Furthermore, our modifications were limited to the upstream purine pathway; subsequent experiments could explore the possibility of enhancing the downstream purine pathway [34].

While traditional knockout of branch pathway genes can redirect flux, it often leads to growth defects; in contrast, this study utilized the natural response of RFN elements to FMN to achieve metabolic state-dependent dynamic regulation of the purA and pgi genes, redirecting carbon flux toward riboflavin synthesis while maintaining early-stage bacterial growth, thereby providing a new approach to balancing growth and production. Future experiments could also introduce mutations in FMN to increase its regulatory range.

Notably, in prior single-gene knockout validations, deletion of guaC failed to enhance riboflavin production, whereas CRISPRi-mediated downregulation successfully improved the titer. This discrepancy indicates that although the etiBsu1209 model employs zero reaction flux (simulating complete knockout) as a mathematical constraint for target prediction, static gene knockout often fails to achieve the anticipated titer increase due to the disruption of basal metabolic homeostasis or the induction of global stress responses [35]. In contrast, CRISPRi-mediated partial repression effectively redirects target metabolic flux while preserving the residual enzymatic activity essential for maintaining basal cellular physiological functions. The successful identification of guaC demonstrates that the "model prediction–CRISPRi screening" workflow expands the dimensionality of metabolic target discovery and validates the efficiency and reliability of this strategy for engineering complex metabolic pathways. Furthermore, the discovery of ilvD (a branched-chain amino acid biosynthesis gene) as a non-intuitive genetic target underscores the indirect regulatory role of global metabolic networks in target product synthesis. Future work will focus on further expanding the coverage breadth of CRISPRi libraries, optimizing editing efficiency in industrial strains, and extending this paradigm to more diverse microbial cell factories and target metabolites to systematically validate its engineering universality.

5 Conclusions

In this study, we engineered B. subtilis through systematic metabolic engineering to achieve high-level riboflavin production. By optimizing the riboflavin operon, enhancing precursor supply, and utilizing the RFN element to dynamically regulate branching metabolic pathways, combined with the genome-scale model etiBsu1209 and CRISPRi screening technology, we identified guaC and ilvD as key targets. The strain, BSF30, produced 8.4 g/L of riboflavin in shake flask cultivation and 20.2 g/L in fed-batch cultivation, providing a reference for the further industrial production of riboflavin.

References

[1] Pinto J T, Zempleni J. Riboflavin. Advances in Nutrition, 2016, 7(5): 973–975

[2] Abbas C A, Sibirny A A. Genetic control of biosynthesis and transport of riboflavin and flavin nucleotides and construction of robust biotechnological producers. Microbiology and Molecular Biology Reviews, 2011, 75(2): 321–360

[3] You J J, Pan X W, Yang C. et al. Microbial production of riboflavin: biotechnological advances and perspectives. Metabolic Engineering, 2021, 68: 46–58

[4] Mosegaard S, Dipace G, Bross P. et al. Riboflavin deficiency—implications for general human health and inborn errors of metabolism. International Journal of Molecular Sciences, 2020, 21(11): 3847

[5] Qu R Z, Zhang Y, Kim B. et al. Microbial riboflavin inhibits ceramide synthase 3 to lower ceramide (d18:1/26:0) and delay colorectal cancer progression.. Cell Metabolism, 2025, 37(9): 1852–1869

[6] Liu Y, Zhang Q, Qi X X. et al. Metabolic engineering of Bacillus subtilis for riboflavin production: a review. Microorganisms, 2023, 11(1): 164

[7] Wang S J, Zhu Q Y, Liu C. et al. Engineering riboflavin-overproducing Bacillus subtilis via pathway gene overexpression. Synthetic and Systems Biotechnology, 2026, 11: 91–101

[8] Kurabayashi K, Enshasy H A E, Park E Y. et al. Increased production of riboflavin in Ashbya gossypii by endoplasmic reticulum stresses. Archives of Microbiology, 2025, 207(7): 167

[9] Koizumi S, Yonetani Y, Maruyama A. et al. Production of riboflavin by metabolically engineered Corynebacterium ammoniagenes. Applied Microbiology and Biotechnology, 2000, 53(6): 674–679

[10] Bacher A, Eberhardt S, Fischer M. et al. Biosynthesis of vitamin B₂ (riboflavin). Annual Review of Nutrition, 2000, 20: 153–167

[11] Duan Y X, Chen T, Chen X. et al. Overexpression of glucose-6-phosphate dehydrogenase enhances riboflavin production in Bacillus subtilis. Applied Microbiology and Biotechnology, 2010, 85(6): 1907–1914

[12] You J J, Du Y X, Pan X W. et al. Increased production of riboflavin by coordinated expression of multiple genes in operons in Bacillus subtilis. ACS Synthetic Biology, 2022, 11(5): 1801–1810

[13] Chen X, Yuan Y G, Wang X D. Enhancement of riboflavin production by an enhanced purine salvage pathway in Bacillus subtilis. Applied Biochemistry and Biotechnology, 2025, 197(7): 4807–4816

[14] Perkins J B, Sloma A, Hermann T. et al. Genetic engineering of Bacillus subtilis for the commercial production of riboflavin. Journal of Industrial Microbiology and Biotechnology, 1999, 22(1): 8–18

[15] Xu F, Liu C, Xia M M. et al. Characterization of a riboflavin-producing mutant of Bacillus subtilis isolated by droplet-based microfluidics screening. Microorganisms, 2023, 11(4): 1070

[16] Wang G L, Shi T, Chen T. et al. Integrated whole-genome and transcriptome sequence analysis reveals the genetic characteristics of a riboflavin-overproducing Bacillus subtilis. Metabolic Engineering, 2018, 48: 138–149

[17] You J J, Wang K, Zhang X L. et al. Enhancing riboflavin yield by elucidating the regulatory role of transcription factor YgzD in Bacillus subtilis. Systems Microbiology and Biomanufacturing, 2026, 6(1): 28

[18] Chen Q, Xu X H, Sun Z Y. et al. Metabolic engineering of Bacillus subtilis for de novo synthesis of 6’-sialyllactose. Systems Microbiology and Biomanufacturing, 2025, 5(1): 223–236

[19] Sun X, Bi X Y, Li G Y. et al. Combinatorial metabolic engineering of Bacillus subtilis for menaquinone-7 biosynthesis. Biotechnology and Bioengineering, 2024, 121(10): 3338–3350

[20] Wu Y K, Liu Y F, Lv X Q. et al. CAMERS-B: CRISPR/Cpf1 assisted multiple-genes editing and regulation system for Bacillus subtilis. Biotechnology and Bioengineering, 2020, 117(6): 1817–1825

[21] Zhu H X, Liang C. CRISPR-DT: designing gRNAs for the CRISPR-Cpf1 system with improved target efficiency and specificity. Bioinformatics, 2019, 35(16): 2783–2789

[22] Bi X Y, Cheng Y, Xu X H. et al. etiBsu1209: a comprehensive multiscale metabolic model for Bacillus subtilis. Biotechnology and Bioengineering, 2023, 120(6): 1623–1639

[23] Wu Y K, Chen T C, Liu Y F. et al. Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis. Nucleic Acids Research, 2020, 48(2): 996–1009

[24] Wu Y K, Li Y, Liu Y F. et al. Multiplexed in-situ mutagenesis driven by a dCas12a-based dual-function base editor. Nucleic Acids Research, 2024, 52(8): 4739–4755

[25] Beutler E, Mathai C K. A comparison of normal red cell ATP levels as measured by the firefly system and the hexokinase system. Blood, 1967, 30(3): 311–320

[26] Bera A K, Zhu J H, Zalkin H. et al. Functional dissection of the Bacillus subtilis pur operator site. Journal of Bacteriology, 2003, 185(14): 4099–4109

[27] Li Y, Wu Y K, Liu Y F. et al. A genetic toolkit for efficient production of secretory protein in Bacillus subtilis. Bioresource Technology, 2022, 363: 127885

[28] Hümbelin M, Griesser V, Keller T. et al. GTP cyclohydrolase II and 3, 4-dihydroxy-2-butanone 4-phosphate synthase are rate-limiting enzymes in riboflavin synthesis of an industrial Bacillus subtilis strain used for riboflavin production. Journal of Industrial Microbiology and Biotechnology, 1999, 22(1): 1–7

[29] Frelin O, Huang L L, Hasnain G. et al. A directed-overflow and damage-control N-glycosidase in riboflavin biosynthesis. Biochemical Journal, 2015, 466(1): 137–145

[30] Liu S, Sun D C. Recent advances in metabolic engineering of Escherichia coli for riboflavin biosynthesis. World Journal of Microbiology and Biotechnology, 2025, 41(10): 329

[31] Shi T, Wang Y C, Wang Z W. et al. Deregulation of purine pathway in Bacillus subtilis and its use in riboflavin biosynthesis. Microbial Cell Factories, 2014, 13(1): 101

[32] Lian J Z, Mishra S, Zhao H M. Recent advances in metabolic engineering of Saccharomyces cerevisiae: new tools and their applications. Metabolic Engineering, 2018, 50: 85–108

[33] García-Angulo V A. Overlapping riboflavin supply pathways in bacteria. Critical Reviews in Microbiology, 2017, 43(2): 196–209

[34] Liu C, Xia M M, Fang H. et al. De novo engineering riboflavin production Bacillus subtilis by overexpressing the downstream genes in the purine biosynthesis pathway. Microbial Cell Factories, 2024, 23(1): 159

[35] Tepper N, Shlomi T. Predicting metabolic engineering knockout strategies for chemical production: accounting for competing pathways. Bioinformatics, 2010, 26(4): 536–543

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The Author(s) 2026. This article is published by Higher Education Press.