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CcpA mutants influence selective carbon source utilization by changing interactions with target genes in Bacillus licheniformis

Abstract

The gram-positive bacterium Bacillus licheniformis exhibits obvious selective utilization on carbon sources. This process is mainly governed by the global regulator catabolite control protein A (CcpA), which can recognize and bind to multiple target genes that are widely distributed in metabolic pathways. Although the DNA-binding domain of CcpA has been predicted, the influence of key amino acids on target gene recognition and binding has yet to be uncovered. In this study, the impact of Lys31, Ile42 and Leu56 on in vitro protein–DNA interactions and in vivo carbon source selective utilization was investigated. The results showed that alanine substitution of Lys31 and Ile42, located within the 3rd helices of the DNA-binding domain, significantly weakened the binding strength between CcpA and target genes. These mutations also lead to alleviated repression of xylose utilization in the presence of glucose. On the other hand, the Leu56Arg mutant in the 4th helices exhibited enhanced binding affinity compared with that of the wild-type one. When this mutant was used to replace the native one in B. licheniformis cells, the selective utilization of glucose over xylose increased. This study provides a new strategy for understanding the relationship between the function and structure of regulatory proteins. This study also used a new strategy was used to regulate carbon source utilization beyond CCR engineering.

Introduction

Microorganisms have evolved a myriad of strategies to adapt to complex environments. In firmicutes, the regulation of carbon resource utilization is mainly governed by the global regulator catabolite control protein A (CcpA), a LacI-GalR family protein [1]. As this regulator can have direct or indirect effects on multiple genes involved in both catabolism and anabolism, its specific functions and action mechanisms have attracted increasing attention in the recent years. For example, the domains of CcpA in Bacillus subtilis and Bacillus megaterium have been characterized [2, 3]. Researchers have suggested that bacterial CcpA contains two domains: a DNA-binding domain and a core domain [4, 5]. The DNA-binding domain is mainly responsible for the recognition of nucleic acids, and the core domain is mainly responsible for cofactor HPr (histidine-containing protein) or Crh (Carbon flux regulating HPr) binding [6, 7]. With the increasing availability of “multi-omics” information, CcpA was found to have a widely distributed binding site [8]. However, the relationship between the structure and function of CcpA, especially the influence of key amino acids on target gene recognition and binding, is still unclear. The carbon metabolism regulatory networks centered on CcpA can only be fully comprehended by considering its structural context.

The current understanding of the regulatory function of CcpA in gram-positive bacteria is mainly based on research conducted in Bacillus subtilis and Bacillus megaterium, in which the function of CcpA has been appraised by examining the effects of amino acid substitutions [2, 3, 6]. In B. megaterium, was amino acid mutations were used to research the regulatory effect of CcpA on growth and catabolite repression. Mutations of Glu77, Ile227, Asp275, Met282, and Thr306 show glucose-independent regulation [2]. In both studies, the chosen amino acids are mainly located in the core domain and are highly conserved.

Bacillus licheniformis, a gram-positive bacterium with great application potential, is not only used for a wide range of applications in the field of fermentation but also as a platform for exogenous gene expression [9,10,11]. In the field of fermentation, the unique advantages of B. licheniformis (a moderate growth rate and sufficient protein folding activity [12]) allow for its use in the production of bacitracin [13], poly-γ-glutamic acid [14], amylase [15], and alkaline protease [16], among others. However, in industrial fermentation, the presence of a preferred carbon source, such as glucose, inhibits the utilization of a nonpreferred carbon source until the preferred carbon source has been exhausted [17]. This phenomenon is called carbon catabolite repression (CCR), of which glucose-lactose diauxie in Escherichia coli is a classic example [18]. CCR, one of the most widespread mechanisms by which microbes adapt to a changing environment, takes advantage of protein synthesis [19]. Generally, the major determining factor in the microbial growth rate is the selection of a preferred carbon source [18]. In addition, the presence of a preferred carbon source will also cause other metabolic changes beyond CCR [20]. In the past few years, CCR engineering for carbon source utilization has been widely discussed in the scientific community. Many cre sites have been mined and utilized in the recent years, such as those in xylose operator and mannose [12, 33]. Other types of cre sites, such as novel dual-cre in Clostridium acetobutylicum were mined as well [39]. All results suggest that CCR engineering for carbon source utilization is a useful strategy and that the cre site was widely distributed in microorganisms. On the other hand, the distribution of the cre site creates some limitations for CCR engineering for carbon source utilization.

Xylose can be utilized by B. licheniformis and other microorganisms [21, 22]. Xylose is one of the major components of biomass, which is a readily available, abundant, inexpensive, and renewable resource [23, 24]. The main hydrolytic products of lignocellulosic biomass include not only xylose, but also glucose. [25, 26]. Therefore, the utilization of xylose is repressed because of the existence of glucose under the regulation of CcpA [27].

This study shows that some amino acid mutations in the DNA-binding domain can influence the binding ability of CcpA, thus causing changes to its regulatory function in B. licheniformis. The utilization of xylose was repressed by the binding of CcpA with nucleic acid at its binding sites. The effect of amino acid mutations in the DNA-binding domain of CcpA on xylose utilization was investigated. These findings may help explain how CcpA regulates the utilization of xylose in B. licheniformis and open new possibilities for the collaborative utilization of the preferred carbon source and xylose.

Materials and methods

Bacterial strains and culture conditions

Table 1 lists the bacterial strains and plasmids that were used or generated during this study.

Table 1 Strains and plasmids used in this study

All experiments were performed with three replicates. B. licheniformis CA is a gene knockout expression host lacking the gene that expresses the global regulatory protein CcpA. This strain was designed to explore the influence of CcpA and CcpA mutants. The osmotic medium and agents used for protoplast transformation were prepared according to Waschkau et al. and included SMMP medium, SSM buffer, no.416 medium, and sugar [28]. E. coli was grown at 37 °C at 200 rpm in Luria–Bertani (LB) medium containing 10 g/L tryptone, 5 g/L yeast extract and 10 g/L NaCl. Bacillus was grown at 37 °C and 250 rpm in LB. TB medium containing 30 g/L xylose and 30 g/L glucose was prepared and used to evaluate the effect of CcpA protein mutants on xylose consumption. Ampicillin (100 μg/mL), kanamycin (30 μg/mL), or tetracycline (20 μg/mL) was added to the medium when E. coli and Bacillus were cultivated. The fermentation medium was divided into 250 mL shake flasks, where each flask contained 30 mL of medium, and was shaken at 250 rpm. Samples were taken every three hours to determine the OD600 and glucose and xylose content.

Homology modeling of B. licheniformis CcpA and homology comparison

To explore the effect of CcpA on xylose utilization in B. licheniformis, a homology model of CcpA from B. licheniformis was generated using the SWISS-MODEL server [29]. The server input, which was downloaded from NCBI, was the amino acid sequence of CcpA. The amino acids of CcpA from B. licheniformis showed high identity (78.55%) with the model in the server. The homology of CcpA from B. licheniformis and other closely related bacilli were compared with DNAMAN (https://www.lynnon.com/dnaman.html). All the sequences were downloaded from NCBI.

CcpA site-directed mutagenesis

The mutated sites and primers used are shown in Table 2. PCR site-directed mutagenesis was used for mutants [30]. Each PCR sample contained 50 nM of each primer (Sangon Biotech, Shanghai, China), 50 mL of Phanta Max DNA polymerase (Vazyme Biotech, Nanjing, China), and 50 ng of template DNA (recombinant plasmid pET28aPA). All the PCR products were purified and digested with DpnI, followed by transformation into BL21 (DE3). The positive bacteria were cultured in LB medium containing 30 μg/mL kanamycin overnight at 37 °C. Then, the plasmids were extracted and sequenced, and the correct mutant was selected.

Table 2 Primers used to construct recombinant plasmids

Expression and purification of mutant proteins

Recombinant BL21 (DE3) bacteria were cultivated in a 250-mL flask containing 30 mL of fermentation medium. First, recombinant BL21 cultures were grown in LB broth on a shaker at 37 °C. Then, 3% seed cultures were inoculated into 30 mL fermentation medium. IPTG was added to a final concentration of 0.1 mM as an inducer when the OD600 of the culture had reached approximately 0.6. Then, the shake flask was transferred to 30 °C [31, 32]. After 12 h, the bacteria were collected and ultrasonically broken. The target protein was purified with a Mag-Beads His-tag protein purification kit (Sangon Biotech, Shanghai, China). The purified protein was detected by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) (10% gel) using Li’s methods [33].

Screening of mutant proteins

Bacillus licheniformis CcpA and mutant CcpA proteins were expressed and purified using the aforementioned methods. Fluorescence polarization immunoassay (FPIA) and electrophoretic mobility shift assay (EMSA) were used to screen and identify the ability of CcpA mutant proteins to bind cre sites. The 5′ terminal fluorescently (FAM) labeled probe dsDNA used in the FPIA experiment was obtained by PCR using the B. licheniformis genome as a template and CreF/CreR as primers, as shown in Table 2. Before testing with a multifunctional enzyme marker (BioTek Instruments, Winooski, VT), 100 nM of the fluorescently labeled probe dsDNA was incubated for 20 min at room temperature with 60 μg of mutant CcpA protein in binding buffer (60μL) consisting of 25 mM Tris–HCl, 3 mM NaCl, 3 mM MgCl2, and 0.1 mM DTT using methods outlined by Xu et al. [34]. Then, the total volume was added to 100 μL buffer using a multi-detector enzyme labeling instrument (BioTek, USA) to measure excitation and absorption at 485 nm and 528 nm. The DNA probes used in the EMSA were amplified by PCR with CreF1/CreR using the B. licheniformis genome as a template, and the 3' DNA probe was labeled with biotin. Before electrophoresis, 30 ng of DNA probe was incubated at room temperature with 3 μg of mutant CcpA protein in a binding buffer (chemiluminescent EMSA kit, GS009, Beyotime, Shanghai, China). All of these steps were conducted as indicated in the kit instructions. Bio-Rad Mini-Protean III electrophoresis apparatus and Bio-Red Mini Trans-Blot (Bio-Rad, California, USA) were used in this study.

Construction of ccpA gene knockout mutants and expression of CcpA mutants

The original genes of ccpA were knocked out to eliminate the effect on the evaluation of CcpA mutation. The bacteria and plasmids are shown in Table 1. The medium and reagents for B. licheniformis and E. coli were based on the methods outlined by Li [35]. E. coli and B. licheniformis were cultured in LB medium. The recombination plasmids TC and TCFKFC were used to construct gene knockout cassettes. Then, the gene knockout cassette was enzyme digested by KpnI and XhoI. Then, the knockout cassette was linked with plasmid pT. Lastly, the recombination plasmid pTCFKFC was transformed into B. licheniformis using the methods put forth by Li, while the next steps followed Wang’s methods [33, 36]. The ccpA gene was inactivated by an insertional inactivation via double-crossover homologous recombination (Fig. 4A).

The ccpA expression plasmids were constructed based on the pHY300-PLK vector with the primers listed in Table 2. All molecular experiments were performed using standard molecular cloning protocols. Promoter P43 was amplified with the primers listed in Table 2. The sequence of CcpA mutants was amplified by the primers listed in Table 2 using pETPAK31A, pETPAI42A, and pETPAL56R as templates. Then ccpA mutant genes were ligated to P43, after which the recombinant plasmids were individually transformed into ccpA-defective B. licheniformis strains by electro-transformation and cultured overnight at 37 °C in a solid medium containing 20 μg/mL tetracycline. The plasmids were extracted and sequenced to ensure the correct transformants.

Carbon source consumption measurements

Strains harboring different mutants were individually inoculated into LB medium containing tetracycline and cultured at 37 ℃, 250 rpm overnight. Then, the cultures were inoculated at OD600 = 0.15 into fresh 30 mL TB medium supplemented with glucose (30 g/L) and xylose (30 g/L). Samples of the CcpA-defective strains overexpressing the CcpA mutant were collected at different points in time (6 h, 9 h, 12 h, 15 h, 18 h, and 21 h) for assessment. One milliliter of each sample was centrifuged at 12,000 rpm for 10 min, and an equal volume of 10% trichloroacetic acid was added to the supernatant to remove impurities. Carbon source consumption were assessed by HPLC (Thermo Fisher Scientific, Shanghai, China) with a Polyamino HILIC (Dikma, Beijing, China) chromatographic column according to the manufacturer’s specifications [37, 38].

The expression level of CcpA mutants

To verify that the CcpA mutants did not change the expression level of ccpA and thus affect the utilization of xylose, strains harboring different mutants were individually inoculated into LB medium containing tetracycline and cultured overnight at 37 ℃, 250 rpm. Then, the cultures were inoculated into a fresh 30 mL TB medium at OD600 = 0.15. The negative control was strains harboring ccpA. The expression levels of the ccpA mutants were determined using real-time quantitative PCR (RT-qPCR). Samples were collected at 8 h, and the cells were harvested after isolation. Complete RNA was extracted with the Simply Ptotal RNA extraction kit (Bioflux, Beijing, China) and quantified with a Quawell Q5000 ultraviolet − visible spectrophotometer (Quawell Technology, San Jose, CA). cDNA was prepared using the PrimeScript RT reagent kit (Vazyme Biotech, Nanjing, China) and was used as a template for real‑time PCR analysis with ChamQ™ Universal SYBR qPCR Master Mix (Vazyme Biotech, Nanjing, China) and the primers qccpA-F/qccpA-R. The internal reference gene was rpsE [21]. The relative transcript strength was calculated using the 2−ΔΔCt method [33]. Translation levels of CcpA mutants were measured by the ratio of the CcpA mutant bands. Recombinant CcpA mutants were cultured with TB medium suppled 30 g/L glucose and 30 g/L xylose. The strains were collected after 24 h. The strains were washed twice with PB buffer, and then resuspended in PB buffer containing 10 g/L lysozyme. The bacterial solutions were incubated for 1 h at 37 °C and lysed via sonication on ice and then centrifuged at 12,000 rpm for 10 min. 20 µg of total protein per sample was loaded onto a gel.

Results

Homology modeling of B. licheniformis CcpA and sequence alignment analysis

Diversified cre sites and changes in these sites can effectively influence the binding ability of CcpA. These changes influence the regulation of metabolism by CcpA [39, 40]. To explore whether changes in the amino acids of the CcpA protein would also affect the function of CcpA, a homology model of CcpA was built by SWISS-MODEL (Fig. 1A). The obtained model of CcpA in B. licheniformis showed high homology (87.01%) with the model (1ZVV) used. Verify3D showed that at least 80% of the amino acids were scored [41]. In addition, ERRAT showed that the quality factor was 95.5 [42]. These results indicate that the modeled structures of CcpA can be used for subsequent analyses. The model shows that the DNA-binding domain of B. licheniformis CcpA contains four α-helices. In previous studies, Arg22 and Leu56 at the 2nd and 4th α-helix were shown to play an important role CcpA interaction with cre sites [43]. To further analyze the key amino acids, the model of CcpA was used to docking with cre sites. Residues within 5A were marked and the side chain was shown in Fig. 1A. To further confirm the key amino acids that can influence the regulation of CcpA, CcpA from seven closely related Bacillus species was analyzed. Identical and similar amino acids in the DNA-binding domain were marked in blue, and conserved amino acids were marked in red (Fig. 1C).

Fig. 1
figure1

Selection of the key amino acids in the CcpA DNA-binding domain. A Structure of the whole CcpA and the docking of CcpA with cre site. The side chain of the active site was marked in finguer. Active sites selected were marked in yellow. B The location of amino acids selected in DNA-binding domain. The amino acids selected and side chain were marked in yellow. C The location of amino acids in other Bacillus. The conserved amino acid in different strains were marked in red. The amino acids selected were marked with a red box. The accession numbers used for the acid sequence analysis were WP_010789522.1 (B. atrophaeus), WP_025909479.1 (B. flexus), WP_014458003.1 (B. megaterium), EEK71284.1 (B. mycoides), WP_061409141.1 (B. pumilus), and WP_003229285.1 (B. subtilis168)

The structures of CcpA subunits are flexible, and the structure of CcpA changes to fit nucleic acids for binding. The main change in CcpA when it binds nucleic acids is a change in the angle between different α-helices of the DNA-binding domain [43]. In B. subtilis, the mutations of Asn49 and Asn50, which are next to the hinge helix, were likely to directly or indirectly affect DNA binding [44]. These amino acids were located at one end of the 4th helix. The key amino acids that cause this change in the angle between different α-helices may be located at both ends of the α-helix. Alignment of the amino acid sequences of Bacillus, Val23, Thr33, Lys36 and Lys59 were strictly conserved in the DNA-binding domain. These amino acids were located at the middle and end of helices. According to previous studies, essential residues are important for the stability and activity of CcpA [43]. Hence, the amino acid in DNA-binding domain plays an import role in recognition and binding. The amino acids near conservation may also affect the function of CcpA. Based on the above information, the amino acids Ile6, Va9, Glu12, Met17, Arg22, Val24, Lys31, Lys37, Ile42, Asn50, Arg54, Leu56, and Ser58 were chosen as target positions for further examination. They are mainly located at either end of the α-helix or near the conserved region, as shown in Fig. 1B.

Site-directed mutagenesis, expression, and purification of the B. licheniformis CcpA protein

Based on the above analysis, the putative amino acids within the α-helix were replaced by site-directed mutagenesis. In a previous study, an alanine scanning peptide library was used to estimate the specific amino acids that were correlated with stability and function [45]. To test the function of amino acids, some residues were replaced with alanine using site-directed mutagenesis. Schumacher MA confirmed that Leu56 identifies the conserved domain of cre during binding with nucleic acids [43]. The characteristics of Leu were opposite those of Arg. Leu56 was mutated to Arg. The sequencing results show that all the mutations were in agreement with the sequences shown in Table 2. Therefore, 13 CcpA mutants were obtained. All mutant proteins were expressed and purified in host BL21 bacteria using the pET28a vector, and 35–67 mg of each purified protein was obtained. The mutant proteins migrated at their expected size as judged by SDS-PAGE (Fig. 2).

Fig. 2
figure2

The mutation and purification of CcpA. A The purification of CcpA mutants. CcpA mutants were purified and then detected using SDS-PAGE. The expected band size was 36.7 kDa, consistent with the expected size of CcpA mutants

The binding ability of CcpA to cre sites changed due to the amino acid mutation

Previous studies have demonstrated that CcpA can directly and indirectly regulate the transcription of several essential genes by binding to cre sites [46]. Therefore, the ability of CcpA mutants to bind cre sites was first evaluated in vitro. The proteins and DNA were mixed and subjected to fluorescence polarization (FPIA) and electrophoretic mobility shift assays (EMSA), the results of which are shown in Fig. 3. Figure 3A was the result of fluorescence polarization between CcpA mutants and probe. It is clear from the experimental results that the fluorescence polarization of Lys31Ala, Ile42Ala and Leu56Arg were significantly shifted when compared with that of other mutants. Leu56Arg has a higher affinity for binding with the cre site than the negative control (wild-type CcpA). In contrast, Lys31Ala and Ile42Ala have a lower affinity for binding to the cre site than the negative control. To verify the above results, the binding of CcpA mutants to the cre site was examined using electrophoretic mobility shift assays (EMSAs) (Fig. 3B). As expected, a substantial DNA-binding shift was observed in the Leu56Arg compared with the negative control. However, no obvious DNA-binding shift was detected for Lys31Ala and Ile42Ala. In addition, the binding ability of CcpA mutants was also confirmed by the structural information. The side chain of Ala was much smaller than Lys and Ile. Therefore, Lys31Ala and Ile42Ala have the less sterically hindered positions. CcpA mutants release from target sites easier. However, the side chain of Arg was larger than Leu. Hence, Leu56Arg has the bigger sterically hindered positions. CcpA mutants have more difficulty releasing from target sites (Fig. 4). Together, these results verified that the amino acids chosen in the DNA-binding domain play an important role in cre recognition.

Fig. 3
figure3

Evaluation of nucleic acids binding ability between different CcpA mutants. All experiments were performed in triplicate. A Screening the CcpA mutants using FPIA. “I” is defined as the difference in polarization value between the mutant and the wild-type CcpA. B and C EMSAs of wild-type CcpA and CcpA mutants selected in (A) binding to the probe containing the canonical cre site. The final concentration of 5’ labeled DNA probe used was 30 ng, and 0 to 0.6 nm CcpA mutants were used. Wild-type protein was included as control. ***P < 0.001, **P < 0.01, *P < 0.05

Fig. 4
figure4

Structural information of mutants. The side chain of amino acids that affects binding ability in this study and was marked red (left). The structural information of the mutants corresponding to the original CcpA was listed on the right

Construction of ccpA mutants

A CcpA knock out mutant was initially constructed to investigate the effect of this protein on carbon source utilization and to provide a clear background for engineered CcpA proteins. This result was confirmed by diagnostic PCR and subsequent sequencing. The schematic of CcpA knockout strategy was shown in Fig. 5A. The ccpA deletion cassette exhibited a 2384 bp fragment in nucleic acid electrophoresis, as shown in Fig. 5B. Finally, the fragment of ccpA range of N-terminus from 255 to 891 bp was knock out. The relative expression intensity of the ccpA gene was also documented at different times (Fig. 5C). Quantitative RT-PCR analyses of the levels of ccpA in the cells cultured for 4 h, 8 h and 12 h were performed. The ccpA expression levels in the ccpA deletion strain were 1.6%, 0.4%, and 4.4% of that in the wild-type strain. The origin ccpA was knocked out successful through the homologous recombination strategy.

Fig. 5
figure5

Verification of ccpA gene knockout. A The schematic of the ccpA knockout strategy. ccpA-L and ccpA-R were left and right homologous arms. The origin ccpA was replaced by Kan (kanamycin resistance gene (CP054551.1)) during homeologous recombination. B PCR products were used to verify that the ccpA was replaced with a foreign gene. The edited ccpA gene will have three bands (Lanes 4, 5, 6 (1283 bp, 1825 bp, and 2384 bp)). Unsuccessfully edited ccpA genes have two bands (Lanes 1, 2, 3). The sizes of the DNA markers are labeled on the left. C The expression ratio of ccpA. The expression ratio is the expression of wild-type ccpA divided by the ccpA mutant expression. ***P < 0.001, **P < 0.01, *P < 0.05

The effect of CcpA mutants on glucose/xylose selective utilization

The repression of xylose utilization by glucose has been demonstrated in Bacillus strains, as shown in Fig. 6. Generally, CcpA binds cre sites in the presence of glucose, after which the expression of a xylose utilization gene is repressed [6, 21, 33]. In the above studies, it was demonstrated that a CcpA mutant has the ability to bind cre sites differed from that of wild-type CcpA (Fig. 6D). The mutant genes of ccpA were then expressed in B. licheniformis CA, influencing carbon source selective utilization. Recombinant Bacterial were cultured in TB medium supplied with xylose and glucose. The xylose consumption rate was used as an index. As expected, CcpA mutants, with diversified affinities to cre sites, exhibited significant differences in selective utilization between glucose and xylose (Fig. 7). The average specific consumption rate of xylose in the control (wild-type ccpA was expressed in B. licheniformis CA) was approximately 0.25 ± 0.1 g/ (L.OD600) in the presence of glucose. The results showed that the average specific rate of xylose consumption in the presence of the preferred carbon source was clearly higher in Lys31Ala and Ile42Ala CcpA than in the control group in the presence of glucose. As shown in Fig. 7E, the average specific consumption rates of xylose Lys31Ala in and Ile42Ala are approximately 1.5 ± 0.3 g/ (L.OD600) and 1.2 ± 0.02 g/ (L.OD600) at 21 h, respectively. The xylose consumption rate for Lys31Ala in and Ile42Ala increased by 5- and 3.8-fold relative to that of the wild type. In contrast, the average specific rate of xylose consumption of the Leu56Arg mutant decreased significantly. The average specific consumption rate of xylose is approximately 0.04 ± 0.003 g/ (L.OD600) in the presence of glucose. The xylose consumption rate for Leu56Arg decreased by 5.25-fold. Moreover, the ratio of glucose to xylose utilization was clearly different in strains expressing mutant CcpA. The ratio of glucose to xylose utilization was approximately 15 in the negative control group, but approximately fourfold lower in the strains expressing Lys31Ala and Ile42Ala CcpA. The ratio of glucose to xylose utilization was over 30-fold higher than that of the negative control in the strain expressing Leu56Arg CcpA. Furthermore, the biomass of strains that overexpressed the CcpA mutants was different from that of the strain expressing wild-type CcpA (Fig. 7D).

Fig. 6
figure6

Model of xylose utilization and repression by glucose in B. licheniformis. A In the absence of xylose, the activity of XylA and XylB responsible for xylose utilization was repressed by XylR. B In the presence of xylose, the expression of XylA and XylB was activated. C In the presence of xylose and glucose, glucose activates CcpA binds with cre sites. The expression of XylA and XylB was repressed. D A previous study by the same researchers has demonstrated that the binding ability of CcpA mutants with cre sites have changed. These changes of CcpA may affect the xylose utilization at the presence of glucose

Fig. 7
figure7

Sugar consumption and biomass of overexpressed CcpA mutant strains in fermenting glucose and xylose mixture (approximate 30 g/L glucose and 30 g/L xylose). All experiments were performed in triplicate. AC Sugar consumption of overexpressed CcpA mutation strains in fermenting glucose and xylose mixture. D Biomass of overexpressed CcpA mutation strains in fermenting glucose and xylose mixture. E Xylose average specific consumption rate of overexpressed CcpA mutation strains in fermenting glucose and xylose mixture after being cultured for 21 h. The formula for calculating the xylose average specific consumption rate was xylose consumption divided by OD 600. F The expression level of ccpA mutants fermenting in a glucose and xylose mixture. G Intracellular SDS-PAGE of B. licheniformis CA, which contains different CcpA mutants. A, Intracellular SDS-PAGE of B. licheniformis CA, which contains Lys 31 Ala. B, Intracellular SDS-PAGE of B. licheniformis CA, which contains Ile 42 Ala. C, Intracellular SDS-PAGE of B. licheniformis CA, which contains Leu 56 Arg. D, Intracellular SDS-PAGE of B. licheniformis CA, which contains origin CcpA. E, Intracellular SDS-PAGE of B. licheniformis CA. H The proportion of CcpA mutants intracellular of B. licheniformis CA expressing different mutants. ***P < 0.001, **P < 0.01, *P < 0.05

To confirm that these differences in xylose and glucose utilization were caused by the mutation of CcpA rather than the expression level, CcpA mutant expression levels were determined. Transcriptional strength and the translational levels were detected, as shown in Fig. 7F–H. The transcriptional level was detected by qPCR. When compared with wild-type CcpA, the relative values of transcription strength of CcpA mutants were not significantly different. In addition, the ratio of the CcpA mutants and wild-type CcpA bands were calculated as shown in Fig. 7H. This result demonstrates that CcpA mutation did not change the CcpA expression level. These findings demonstrate that the Lys31Ala, Ile42Ala, and Ile56Ala CcpA mutants affect the ability of CcpA to bind cre sites, leading to the utilization of xylose.

Discussion

A lot of the coding capacity in the species of Bacillus is dedicated to carbohydrate uptake and metabolism, though the specific amount depends on species and functional gene assignment [47]. These estimates are in close association with the well-documented ability of Bacillus to utilize a diverse array of carbohydrates [48]. The LacI family regulator is representative of a class of carbohydrate metabolism-related transcription factors, of which CcpA is the most studied [43]. Approximately 60 residues of the DNA-binding domain are present in its N-terminus. Other domains of CcpA are mainly responsible for recognition with cofactors such as HPr and Crh [49]. As synthetic biological science continues to advance, CCR engineering for carbon source utilization in Bacillus has received much attention become the subject of much scientific attention. Glucose and xylose consumptions were simultaneously achieved by CCR engineering in Clostridium acetobutylicum [57]. On the other hand, CcpA was the regulator of cre sites. Many metabolic pathways were regulated by CcpA. Therefore, CcpA protein engineering maybe another useful strategy for carbon source utilization.

In the previous studies, the function of CcpA was affected by amino acid substitutions, the mutation of Val302 in Clostridium acetobutylicum, and changes in the priority of xylose and glucose [6]. However, these mutants have mainly focused on sites within the cofactor-binding domain [2, 6, 44] or those highly conserved amino acids within the DNA-binding domain [2, 43]. The present study experimentally validated the effect on regulatory functions of CcpA of multiple sites within the DNA-binding domains. It appears that alanine substitution of Lys31 and Ile42, located within the 3rd helix of the DNA-binding domain, lead to alleviated repression of xylose utilization in the presence of glucose. In addition, the Leu56Arg mutant in the 4th helix exhibited an increased selective utilization of glucose over xylose. These results suggest that changes in microstructure around these domains also contribute to modified regulatory functions of CcpA. This information is useful for the engineering of other LacI family regulators.

Three CcpA mutants with different binding abilities were found with rapid in vitro screening guided by homology modeling. According to available reports, the main reason for xylose utilization repression in the presence of glucose is the binding of CcpA with cre sites and the repressed expression of XylA and XylB [48]. It is important to note that the recognition of CcpA by cre sites is structure dependent. The substructure of CcpA is flexible. The relative distances between different substructures will change as CcpA is combined between cre sites and cofactors [43]. In this study, when the mutants were expressed in B. licheniformis CA, the rate of xylose utilization differed distinctly. These differences were mainly attributed to a difference in binding abilities, which was supported by in vitro characterization. The mutation sites selected were distributed in different substructures of the DNA-binding domain, which had implications for the flexibility of the substructure. Previous studies demonstrated that electrostatic interactions between proteins and DNA, as well as steric hindrance, affect the binding of DNA and protein [50, 51]. In this study, steric hindrance was lower in the side chain of Lys31Ala and Ile42Ala. Therefore, the bond between CcpA mutants and cre sites was much weaker. In comparison, the steric hindrance of Leu56Arg was significantly larger. Therefore, Leu56Arg had a higher binding capacity. These results proved that in vitro interaction between the regulator and the target genes could offer credible evidence and be helpful for engineering regulatory proteins.

Over the past few years, the function of CcpA has been investigated extensively [52, 53]. Many studies have been performed [54, 55] to explore the relationship between structure and function of CcpA. For example, amino acids were mutated to explore the activation (alsS, ackA) and repression (xynP, gntR) regulated by CcpA in B. subtilis [3]. The preference for xylose utilization was affected by the amino acid mutation at position 302 of CcpA in Clostridium acetobutylicum [6]. In both studies, amino acids selected were located at the cofactor-binding domain. In this study, the preference of xylose was affected by the amino acid substitutions located in the 3rd and 4th helix in the DNA-binding domain, a subdomain that had remained generally unreported in previous studies. The results of this study show that this substructure may be a key domain for recognition and DNA binding. Furthermore, the “in vitro interaction–in vivo characterization” strategy used in this study to screen 13 CcpA mutants is quick and cost-effective as compared to in vivo screening [3, 6]. Although this study does not comprise a mutation library, this method can be easily applied to a large-scale mutagenesis screen.

In conclusion, three key amino acids, Lys31, Ile42 and Ile56, have been identified in the DNA-binding domain of CcpA. These amino acids affect xylose utilization rate in the presence of glucose in B. licheniformis. These changes in xylose utilization have potential uses in fermentation with lignocellulosic biomass. Moreover, because of the functional diversity of CcpA, many metabolic processes were regulated, including Biofilm formation and central metabolism [56]. These results are helpful for understanding how microorganisms can sense and adapt to changes in their environment. In addition, the strategy used in this study provides new insight for the engineering of regulatory proteins in B. licheniformis.

Availability of data and material

The datasets used or analysed during the current study are available by request from the corresponding author.

Code availability

Not applicable for that section.

References

  1. 1.

    Goerke B, Stuelke J. Is there any role for cAMP-CRP in carbon catabolite repression of the Escherichia coli lac operon? Reply from Gorke and Stulke. Nat Rev Microbiol. 2008;2008:6.

    Google Scholar 

  2. 2.

    Kuster-Schock E, Wagner A, Volker U, Hillen W. Mutations in catabolite control protein CcpA showing glucose-independent regulation in Bacillus megaterium. J Bacteriol. 1999;181:7634–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. 3.

    Sprehe M, Seidel G, Diel M, Hillen W. CcpA mutants with differential activities in Bacillus subtilis. J Mol Microbiol Biotechnol. 2007;12:96–105.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  4. 4.

    Schumacher MA, Choi KY, Zalkin H, Brennan RG. Crystal-structure of laci member, purr, bound to dna—minor-groove binding by alpha-helices. Science. 1994;266:763–70.

    CAS  PubMed  Article  Google Scholar 

  5. 5.

    Schumacher MA, Choi KY, Lu F, Zalkin H, Brennan RG. Mechanism of corepressor-mediated specific DNA-binding by the purine repressor. Cell. 1995;83:147–55.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  6. 6.

    Wu Y, Yang Y, Ren C, Yang C, Yang S, Gu Y, Jiang W. Molecular modulation of pleiotropic regulator CcpA for glucose and xylose coutilization by solvent-producing Clostridium acetobutylicum. Metab Eng. 2015;28:169–79.

    CAS  PubMed  Article  Google Scholar 

  7. 7.

    Landmann JJ, Busse RA, Latz J-H, Singh KD, Stuelke J, Goerke B. Crh, the paralogue of the phosphocarrier protein HPr, controls the methylglyoxal bypass of glycolysis in Bacillus subtilis. Mol Microbiol. 2011;82:770–87.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    Yang Y, Zhang L, Huang H, Yang C, Yang S, Gu Y, Jiang W. A flexible binding site architecture provides new insights into CcpA global regulation in gram-positive bacteria. MBio. 2017;2017:8.

    Google Scholar 

  9. 9.

    Li K, Cai D, Wang Z, He Z, Chen S. Development of an efficient genome editing tool in bacillus licheniformis using CRISPR-Cas9 nickase. Appl Environ Microbiol. 2018;2018:84.

    Google Scholar 

  10. 10.

    Silano V, Baviera JMB, Bolognesi C, Cocconcelli PS, Crebelli R, Gott DM, Grob K, Lambre C, Lampi E, Mengelers M, Mortensen A, Riviere G, Steffensen I-L, Tlustos C, Van Loveren H, Vernis L, Zorn H, Herman L, Andryszkiewicz M, Liu Y, Rainieri S, Chesson A, Enzy EPFCM. Safety evaluation of the food enzyme phospholipase C from the genetically modified Bacillus licheniformis strain NZYM-VR. EFSA J. 2020;2020:18.

    Google Scholar 

  11. 11.

    Pang C, Yin X, Zhang G, Liu S, Zhou J, Li J, Du G. Current progress and prospects of enzyme technologies in future foods. Syst Microbiol Biomanufact. 2020;1:24–32.

    Article  Google Scholar 

  12. 12.

    Xiao F, Li Y, Zhang Y, Wang H, Zhang L, Ding Z, Gu Z, Xu S, Shi G. Construction of a novel sugar alcohol-inducible expression system in Bacillus licheniformis. Appl Environ Microbiol. 2020;104:5409–25.

    CAS  Google Scholar 

  13. 13.

    Cai D, Zhu J, Zhu S, Lu Y, Zhang B, Lu K, Ma J, Ma X, Chen S. Metabolic engineering of main transcription factors in carbon, nitrogen, and phosphorus metabolisms for enhanced production of bacitracin in Bacillus licheniformis. ACS Synth Biol. 2019;8:866–75.

    CAS  PubMed  Article  Google Scholar 

  14. 14.

    Qiu Y, Wang Q, Zhu C, Yang Q, Zhou S, Xiang Z, Chen S. Deciphering metabolic responses of biosurfactant lichenysin on biosynthesis of poly–glutamic acid. Appl Microbiol Biotechnol. 2019;103:4003–15.

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Ikramul H, Ashraf H, Iqbal J, Qadeer MA. Production of alpha amylase by Bacillus licheniformis using an economical medium. Bioresour Technol. 2003;87:57–61.

    Article  Google Scholar 

  16. 16.

    Mabrouk SS, Hashem AM, El-Shayeb NMA, Ismail AMS, Abdel-Fattah AF. Optimization of alkaline protease productivity by Bacillus licheniformis ATCC 21415. Bioresour Technol. 1999;69:155–9.

    CAS  Article  Google Scholar 

  17. 17.

    Deutscher J, Francke C, Postma PW. How phosphotransferase system-related protein phosphorylation regulates carbohydrate metabolism in bacteria (vol 70, pg 939, 2006). Microbiol Mol Biol Rev. 2008;72:555–555.

    CAS  PubMed Central  Article  PubMed  Google Scholar 

  18. 18.

    Jankovic I, Bruecker R. Carbon catabolite repression of sucrose utilization in Staphylococcus xylosus: Catabolite control protein CcpA ensures glucose preference and autoregulatory limitation of sucrose utilization. J Mol Microbiol Biotechnol. 2007;12:114–20.

    CAS  PubMed  Article  Google Scholar 

  19. 19.

    Romero-Rodriguez A, Rocha D, Ruiz-Villafan B, Guzman-Trampe S, Maldonado-Carmona N, Vazquez-Hernandez M, Zelarayan A, Rodriguez-Sanoja R, Sanchez S. Carbon catabolite regulation in Streptomyces: new insights and lessons learned. World J Microbiol Biotechnol. 2017;2017:33.

    Google Scholar 

  20. 20.

    Blencke HM, Homuth G, Ludwig H, Mader U, Hecker M, Stulke J. Transcriptional profiling of gene expression in response to glucose in Bacillus subtilis: regulation of the central metabolic pathways. Metab Eng. 2003;5:133–49.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  21. 21.

    Li Y, Liu X, Zhang L, Ding Z, Xu S, Gu Z, Shi G. Transcriptional changes in the xylose operon in Bacillus licheniformis and their use in fermentation optimization. Int J Mol Sci. 2019;2019:20.

    Google Scholar 

  22. 22.

    Hohenschuh W, Hector RE, Chaplen F, Murthy GS. Using high-throughput data and dynamic flux balance modeling techniques to identify points of constraint in xylose utilization in Saccharomyces cerevisiae. Syst Microbiol Biomanuf. 2020;1:58–75.

    Article  Google Scholar 

  23. 23.

    Gu Y, Jiang Y, Yang S, Jiang W. Utilization of economical substrate-derived carbohydrates by solventogenic clostridia: pathway dissection, regulation and engineering. Curr Opin Biotechnol. 2014;29:124–31.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Promdonkoy P, Mhuantong W, Champreda V, Tanapongpipat S, Runguphan W. Improvement in d-xylose utilization and isobutanol production in S. cerevisiae by adaptive laboratory evolution and rational engineering. J Ind Microbiol Biotechnol. 2020;47:497–510.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25.

    Mosier N, Wyman C, Dale B, Elander R, Lee YY, Holtzapple M, Ladisch M. Features of promising technologies for pretreatment of lignocellulosic biomass. Bioresour Technol. 2005;96:673–86.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Dong J-J, Ma B-J, Liu Y-M, Li H, Gong L, Han R-Z, Xu G-C, Ni Y. Coproduction of xylose and biobutanol from corn stover via recycling of sulfuric acid pretreatment solution. Syst Microbiol Biomanuf. 2020;1:200–7.

    Article  Google Scholar 

  27. 27.

    Chen B, Wen J, Zhao X, Ding J, Qi G. Surfactin: a quorum-sensing signal molecule to relieve ccr in Bacillus amyloliquefaciens. Front Microbiol. 2020;2020:11.

    Google Scholar 

  28. 28.

    Waschkau B, Waldeck J, Wieland S, Eichstaedt R, Meinhardt F. Generation of readily transformable Bacillus licheniformis mutants. Appl Microbiol Biotechnol. 2008;78:181–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  29. 29.

    Schwede T, Kopp J, Guex N, Peitsch MC. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 2003;31:3381–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

    Soto-Nieves N, Puga I, Abe BT, Bandyopadhyay S, Baine I, Rao A, Macian F. Transcriptional complexes formed by NFAT dimers regulate the induction of T cell tolerance. J Exp Med. 2009;206:867–76.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Liu M, Ding Y, Chen H, Zhao Z, Liu H, Xian M, Zhao G. Improving the production of acetyl-CoA-derived chemicals in Escherichia coli BL21(DE3) through iclR and arcA deletion. BMC Microbiol. 2017;2017:17.

    Google Scholar 

  32. 32.

    Zhang S, Fang Y, Zhu L, Li H, Wang Z, Li Y, Wang X. Metabolic engineering of Escherichia coli for efficient ectoine production. Syst Microbiol Biomanuf. 2021;2021:1–15.

    Google Scholar 

  33. 33.

    Li Y, Jin K, Zhang L, Ding Z, Gu Z, Shi G. Development of an inducible secretory expression system in Bacillus licheniformis based on an engineered xylose operon. J Agric Food Chem. 2018;66:9456–64.

    CAS  PubMed  Article  Google Scholar 

  34. 34.

    Xu HQ, Zhang AH, Auclair C, Xi XG. Simultaneously monitoring DNA binding and helicase-catalyzed DNA unwinding by fluorescence polarization. Nucleic Acids Res. 2003;2013:31.

    Google Scholar 

  35. 35.

    Li Y, Wang H, Zhang L, Ding Z, Xu S, Gu Z, Shi G. Efficient genome editing in Bacillus licheniformis mediated by a conditional CRISPR/Cas9 system. Microorganisms. 2020;2020:8.

    Google Scholar 

  36. 36.

    Wang Y, Wang Z, Cao J, Guan Z, Lu X. FLP-FRT-Based method to obtain unmarked deletions of chu_3237 (poru) and large genomic fragments of Cytophaga hutchinsonii. Appl Environ Microbiol. 2014;80:6037–45.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  37. 37.

    Pan S, Tong T, Ye M, Chen X, Jin M. Determination of residual glyphosate and aminomethylphosphonic acid in wheat flour and oats samples by non-derivatization method based on ultra-performance liquid chromatography-high resolution mass spectrometry. Chin J Chromatogr. 2019;37:1321–30.

    CAS  Article  Google Scholar 

  38. 38.

    Ata O, Rebnegger C, Tatto NE, Valli M, Mairinger T, Hann S, Steiger MG, Calik P, Mattanovich D. A single Gal4-like transcription factor activates the Crabtree effect in Komagataella phaffii. Nat Commun. 2018;2018:9.

    Google Scholar 

  39. 39.

    Zhang L, Liu Y, Yang Y, Jiang W, Gu Y. A novel dual-cre motif enables two-way autoregulation of CcpA in Clostridium acetobutylicum. Appl Environ Microbiol. 2018;2018:84.

    Google Scholar 

  40. 40.

    Marciniak BC, Pabijaniak M, de Jong A, Duhring R, Seidel G, Hillen W, Kuipers OP. High- and low-affinity cre boxes for CcpA binding in Bacillus subtilis revealed by genome-wide analysis. BMC Genomics. 2012;2012:13.

    Google Scholar 

  41. 41.

    Luthy R, Bowie JU, Eisenberg D. Assessment of protein models with 3-dimensional profiles. Nature. 1992;356:83–5.

    CAS  PubMed  Article  Google Scholar 

  42. 42.

    Colovos C, Yeates TO. Verification of protein structures-patterns of nonbonded atomic interactions. Protein Sci. 1993;2:1511–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Schumacher MA, Sprehe M, Bartholomae M, Hillen W, Brennan RG. Structures of carbon catabolite protein A-(HPr-Ser46-P) bound to diverse catabolite response element sites reveal the basis for high-affinity binding to degenerate DNA operators. Nucleic Acids Res. 2011;39:2931–42.

    CAS  PubMed  Article  Google Scholar 

  44. 44.

    Kuster E, Hilbich T, Dahl MK, Hillen W. Mutations in catabolite control protein CcpA separating growth effects from catabolite repression. J Bacteriol. 1999;181:4125–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Baskaran Y, Ang KC, Anekal PV, Chan WL, Grimes JM, Manser E, Robinson RC. An in cellulo-derived structure of PAK4 in complex with its inhibitor Inka1. Nat Commun. 2015;2015:6.

    Google Scholar 

  46. 46.

    Tojo S, Satomura T, Morisaki K, Deutscher J, Hirooka K, Fujita Y. Elaborate transcription regulation of the Bacillus subtilis ilv-leu operon involved in the biosynthesis of branched-chain amino acids through global regulators of CcpA, CodY and TnrA. Mol Microbiol. 2005;56:1560–73.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  47. 47.

    Fujita Y. Carbon catabolite control of the metabolic network in Bacillus subtilis. Biosci Biotechnol Biochem. 2009;73:245–59.

    CAS  PubMed  Article  Google Scholar 

  48. 48.

    Singh KD, Schmalisch MH, Stuelke J, Goerke B. Carbon catabolite repression in Bacillus subtilis: quantitative analysis of repression exerted by different carbon sources. J Bacteriol. 2008;190:7275–84.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Esteban CD, Mahr K, Monedero V, Hillen WG, Perez-Martinez G, Titgemeyer F. Complementation of a delta ccpA mutant of Lactobacillus casei with CcpA mutants affected in the DNA- and cofactor-binding domains. Microbiology. 2004;150:613–20.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50.

    Klaus T, Stalinska K, Czaplicki D, Mak P, Skupien-Rabian B, Kedracka-Krok S, Wiatrowska K, Bzowska M, Machula M, Bereta J. Mouse antibody of IgM class is prone to non-enzymatic cleavage between CH1 and CH2 domains. Sci Rep. 2018;2018:8.

    Google Scholar 

  51. 51.

    Habtemariam B, Anisimov VM, MacKerell AD Jr. Cooperative binding of DNA and CBFbeta to the runt domain of the CBFalpha studied via MD simulations. Nucleic Acids Res. 2005;33:4212–22.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Grand M, Riboulet-Bisson E, Deutscher J, Hartke A, Sauvageot N. Enterococcus faecalis maltodextrin gene regulation by combined action of maltose gene regulator MaIR and pleiotropic regulator CcpA. Appl Environ Microbiol. 2020;2020:86.

    Google Scholar 

  53. 53.

    Peng Q, Zhao X, Wen J, Huang M, Zhang J, Song F. Transcription in the acetoin catabolic pathway is regulated by AcoR and CcpA in Bacillus thuringiensis. Microbiol Res. 2020;2020:235.

    Google Scholar 

  54. 54.

    Zheng L, Chen Z, Itzek A, Herzberg MC, Kreth J. CcpA regulates biofilm formation and competence in Streptococcus gordonii. Mol Oral Microbiol. 2012;27:83–94.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Weme RDO, Seidel G, Kuipers OP. Probing the regulatory effects of specific mutations in three major binding domains of the pleiotropic regulator CcpA of Bacillus subtilis. Front Microbiol. 2015;2015:6.

    Google Scholar 

  56. 56.

    Sadykov MR, Hartmann T, Mattes TA, Hiatt M, Jann NJ, Zhu Y, Ledala N, Landmann R, Herrmann M, Rohde H, Bischoff M, Somerville GA. CcpA coordinates central metabolism and biofilm formation in Staphylococcus epidermidis. Microbiology. 2011;157:3458–68.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  57. 57.

    Bruder M, Moo-Young M, Chung DA, Chou CP. Elimination of carbon catabolite repression in Clostridium acetobutylicum a journey toward simultaneous use of xylose and glucose. Appl Microbiol Biotechnol. 2015;99:7579–88.

    CAS  PubMed  Article  Google Scholar 

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Funding

This work was supported by National Key Research & Development Program of China (2018YFA0900504, 2020YFA0907700 and 2018YFA0900300), the National Natural Foundation of China (31401674), the National First-Class Discipline Program of Light Industry Technology and Engineering (LITE2018-22), and the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions.

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YZ, YL, and GS designed the study, carried out the experiments, analyzed data, and wrote the paper. FX and HW carried out the experiments. LZ and ZD analyzed data. ZG and SX designed the study.

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Correspondence to Youran Li or Guiyang Shi.

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Zhang, Y., Li, Y., Xiao, F. et al. CcpA mutants influence selective carbon source utilization by changing interactions with target genes in Bacillus licheniformis. Syst Microbiol and Biomanuf (2021). https://doi.org/10.1007/s43393-021-00055-7

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Keywords

  • CcpA
  • Bacillus licheniformis
  • Mutagenesis
  • Xylose utilization