Effect of glucose on poly-γ-glutamic acid metabolism in Bacillus licheniformis
- Wencheng Yu†1, 2,
- Zhen Chen†1, 2,
- Hong Ye1, 2,
- Peize Liu1, 2,
- Zhipeng Li3,
- Yuanpeng Wang1, 2,
- Qingbiao Li1, 2,
- Shan Yan4,
- Chuan-jian Zhong4 and
- Ning He1, 2Email author
© The Author(s) 2017
Received: 6 September 2016
Accepted: 28 January 2017
Published: 8 February 2017
Poly-gamma-glutamic acid (γ-PGA) is a promising macromolecule with potential as a replacement for chemosynthetic polymers. γ-PGA can be produced by many microorganisms, including Bacillus species. Bacillus licheniformis CGMCC2876 secretes γ-PGA when using glycerol and trisodium citrate as its optimal carbon sources and secretes polysaccharides when using glucose as the sole carbon source. To better understand the metabolic mechanism underlying the secretion of polymeric substances, SWATH was applied to investigate the effect of glucose on the production of polysaccharides and γ-PGA at the proteome level.
The addition of glucose at 5 or 10 g/L of glucose decreased the γ-PGA concentration by 31.54 or 61.62%, respectively, whereas the polysaccharide concentration increased from 5.2 to 43.47%. Several proteins playing related roles in γ-PGA and polysaccharide synthesis were identified using the SWATH acquisition LC–MS/MS method. CcpA and CcpN co-enhanced glycolysis and suppressed carbon flux into the TCA cycle, consequently slowing glutamic acid synthesis. On the other hand, CcpN cut off the carbon flux from glycerol metabolism and further reduced γ-PGA production. CcpA activated a series of operons (glm and epsA-O) to reallocate the carbon flux to polysaccharide synthesis when glucose was present. The production of γ-PGA was influenced by NrgB, which converted the major nitrogen metabolic flux between NH4 + and glutamate.
The mechanism by which B. licheniformis regulates two macromolecules was proposed for the first time in this paper. This genetic information will facilitate the engineering of bacteria for practicable strategies for the fermentation of γ-PGA and polysaccharides for diverse applications.
KeywordsGlucose γ-PGA Polysaccharide Carbon control protein B. licheniformis
Poly-gamma-glutamic acid (γ-PGA) is a type of polyamide composed of single glutamic acids joined via γ-amide linkages between the glutamate γ-carboxyl and α-amino groups . γ-PGA is a natural macromolecular polymer that is biodegradable, edible and non-toxic. Thus, γ-PGA and its derivatives have been applied in diverse fields, particularly as flocculants in water treatment and algal collection [2–4].
The selection of carbon sources for γ-PGA production is strain-dependent. Glucose and glycerol were both reported to favor γ-PGA production in most strains . Importantly, glucose plays different roles in different γ-PGA-producing strains. Bacillus licheniformis ATCC9945a converts glucose to α-ketoglutarate via glycolysis and the TCA cycle, followed by the production of glutamic acid to synthesize γ-PGA. Moreover, glucose is reported to be a better carbon source than glycerol for the growth of B. licheniformis ATCC9945a . For Bacillus subtilis NX-2, glucose is primarily utilized as an energy source for cell growth during γ-PGA biosynthesis, whereas glutamate in the medium is the main precursor for γ-PGA formation . In contrast, using glycerol as the sole carbon source, Bacillus amyloliquefaciens C06 produces γ-PGA containing polysaccharides as by-products . Some genetic information regarding the effect of glucose on γ-PGA synthesis has been reported. Msadek et al. demonstrated that the presence of glucose in the medium resulted in a decline in γ-PGA production because glucose suppressed the transcription of degQ, which activated the CapABC operon [9, 10].
Metabolic engineering has sought to improve γ-PGA production. In a B. amyloliquefaciens M306 mutant obtained by Liu et al. the γ-PGA yield increased from 3.2 to 6.8 g/L through the down-regulation of epsD and yqxM expression . A study from Feng et al. demonstrated that the epsA-O deletion in B. amyloliquefaciens NK-1 contributed to a significant improvement in γ-PGA production (5.12 g/L), which represented a 63.2% increase compared to the wild-type strain; moreover, the γ-PGA purity improved from 76.8 to 80.4% . These results indicate the existence of an unknown competition mechanism between the synthesis of γ-PGA and polysaccharides. Thus, the metabolic regulation system in these strains may control the synthesis of both extracellular polymeric substances in response to environmental changes.
In our previous studies, B. licheniformis CGMCC2876 was observed to produce extracellular polysaccharides when using glucose as the sole carbon source [13, 14], whereas poly-γ-glutamic acid (γ-PGA) was secreted when trisodium citrate and glycerol were used as the carbon sources . Both of the extracellular polymeric substances exhibited high flocculating activities. Polymers with different components and molecular weights are required for different purposes, and controlling the components and molecular weights has fundamental and practical importance for commercial development [16, 17]. To better understand the metabolic mechanism underlying the section of extracellular polymeric substances, we investigated the effect of glucose on the production of polysaccharides and γ-PGA at the proteome level. Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) acquisition LC–MS/MS was used to analyze the differentially expressed proteins in B. licheniformis cultured under different conditions. Finally, we proposed a mechanism for regulating the metabolism of these two macromolecules in B. licheniformis.
Results and discussion
Bacillus licheniformis cell growth in culture media with different glucose concentrations
Effect of glucose on B. licheniformis fermentation products
The production and range of molecular mass of the fermentation products
Crude extract (g/L)
17.988 ± 1.24
14.82 ± 1.69
0.94 ± 0.25
82.41 ± 7.39
5.2 ± 0.55
1.38 × 106 ~ 2.04 × 107
γ-PGA + 5 g
19.968 ± 1.57
11.27 ± 1.16
0.89 ± 0.46
56.42 ± 3.18
4.45 ± 0.79
4.25 × 104; 4.57 × 104
5.38 × 104; 6.38 × 105
γ-PGA + 10 g
19.44 ± 1.03
6.15 ± 0.85
8.45 ± 1.02
31.63 ± 4.33
43.47 ± 6.81
2.57 ×104; 3.36 × 104
5.39 × 105~ 1.58 × 106
Effect of glucose on the molecular mass of the fermentation products
The molecular masses of the fermentation products are shown in Fig. 2b. In the γ-PGA medium, γ-PGA was detected with an average mass ranging from 1.38 × 106 to 2.04 × 107 Da. With the addition of glucose at 5 g/L, the average masses were calculated to be 4.25 × 104, 4.57 × 104, 5.38 × 104 and 6.38 × 104 Da. However, with the addition of glucose at 10 g/L, broad molecular mass distributions were observed in peak I, ranging from 5.39 × 105 to 1.58 × 106 Da, whereas peaks II and III showed relatively low molecular masses of 2.57 × 104 and 3.36 × 104 Da, respectively (Table 1). The γ-PGA hydrolase PgdS was directly responsible for γ-PGA degradation to regulate the molecular mass . Further results showed that pgdS mRNA expression was up-regulated in the medium containing glucose, indicating that the addition of glucose enhanced the expression of γ-PGA hydrolase PgdS to decrease the molecular mass of γ-PGA (Additional file 1).
The flocculating activity of bioflocculants is closely related to both their constituents and their molecular mass . Under normal circumstances, γ-PGA shows higher flocculating activity than polysaccharides at the same concentration, and the flocculating activity increases with increasing of molecular mass. In the γ-PGA medium supplemented with glucose at 10 g/L, the flocculating activity of the culture was decreased by 70% due to the 43.47% decrease in γ-PGA concentration and to the presence of smaller molecules than those secreted from γ-PGA medium (Fig. 1).
Effect of glucose on the B. licheniformis metabolic pathway
The activities of several enzymes involved in glycolysis increased with the addition of glucose compared with γ-PGA medium (Fig. 3a). However, the levels of these proteins decreased in the cell proteome when glucose was exhausted. Similar proteomic results were observed for B. licheniformis DSM 13, indicating that the expression of glycolytic proteins decreased under glucose-limiting conditions . Some microbes can utilize the EMP pathway to synthesize glutamic acid as the precursor for γ-PGA synthesis [26, 27]. Similar to the findings reported in B. subtilis NX-2 , the glycolytic pathway substrates were supplied for cell growth, and the monomers were provided for polysaccharide biosynthesis (Fig. 3b).
As illustrated in Fig. 3a, glycerol metabolism was markedly inhibited by the addition of glucose, while glycerol was used as a preferred carbon source in γ-PGA synthesis, which was consistent with the reports of some other studies [6, 15, 28, 29].
TCA cycle is an essential part of γ-PGA synthetic pathways and produces a precursor (α-ketoglutaric acid) for glutamate synthesis [22, 30]. However, a large amount of pyruvic acid from glycolysis is degraded via the Krebs cycle. In the medium containing glucose at 5 g/L, the levels of SucA and SdhC decreased by 3.59- and 2.01-fold, respectively (Additional file 3) after the glucose was exhausted. The same results revealed that the decrease in SucA and SdhC was beneficial for both the accumulation of α-ketoglutaric acid and the increase in glutamate for producing γ-PGA . Thus, glycerol metabolism was changed to glycolysis when glucose was added to the medium as a co-carbon source.
We observed that the γ-PGA synthetic enzyme system (CapABC) markedly decreased during the exponential growth phase (OD600 = 1.0) when glucose was added (Fig. 3a). Tannler et al. reported that glucose repressed a series of secondary catabolic proteins via carbon control protein N (CcpN) . The cap operon might be regulated by CcpN. In the medium containing glucose at 5 g/L, CapABC content in the cells mildly increased as glucose was exhausted, then returned to the same level as that in the cells cultured in γ-PGA medium. However, in the 10 g/L glucose medium, CapABC was repressed during the entire fermentation process.
Interestingly, GltA and RocG, which are both involved in γ-PGA biosynthesis, were up-regulated with the addition of glucose. GltA is a major regulatory link between carbon and amino acid metabolism. The lack of the gltAB operon limits B. subtilis growth on glucose/ammonium media . However, RocG catalyzes the reaction (glutamate + NAD+→α-ketoglutarate + NH3 + NADH), which provides rapidly metabolizable carbon- or nitrogen-containing compounds for biosynthesis .
Several intracellular enzymes (GlmS, GlmM, GlmU, EpsE, EpsF, EpsH, EpsO, ManA, PgcA and GtaB) that participate in polysaccharide synthesis  were more abundant in the medium containing 10 g/L glucose than in γ-PGA medium (Fig. 3a). The expression of the epsA-O operon was maintained at a high level during polysaccharide synthesis. The bacterial cells were stimulated to activate a series of operons to synthesize polysaccharides, resulting in the diversion of the carbon flux from γ-PGA synthesis to polysaccharides.
Stress response proteins
Proteomics changes in related regulatory proteins
As shown in Table 2, CcpN increased sharply in the early growth phase when glucose was added. When glucose was exhausted, CcpN decreased to the level observed in the cells in γ-PGA medium. CcpN in B. subtilis has been characterized as a repressor of two gluconeogenic genes (gapB/pckA, and glpFK/glpD) that are involved in glycerol metabolism [32, 36]. When the glucose were consumed in the 5 g/L glucose medium, CcpN decreased to the level detected in the bacterial cells cultured in γ-PGA medium. CcpN remarkably altered the distribution of carbon fluxes in B. licheniformis CGMCC2876 by rerouting the main carbon fluxes from glycerol metabolism to glycolysis.
As shown in Fig. 3c, NrgB relayed information on the ammonium availability to downstream regulatory factors and activated GlnA and GlnG, which are involved in glutamate metabolism . NrgB was strongly repressed during the exponential growth phase when glucose was added. Concomitant with the fermentation process, NrgB content in the proteome of the cells in the medium supplemented with 5 g/L glucose increased to the same level as that detected in the cells in γ-PGA medium, whereas NrgB levels were always low in the medium containing 10 g/L glucose. However, glutamine is an optimal nitrogen source for B. licheniformis growth. When glutamine was exhausted, alternative nitrogen sources such as ammonium were utilized . In γ-PGA medium, NrgB facilitated ammonium utilization and activated GlnA and GlnG to promote glutamine synthesis, which was beneficial for γ-PGA synthesis. When glucose was added to the medium, the down-regulation of NrgB resulted in the use of glutamine as a nitrogen source and promoted cell growth. These results suggested that NrgB was a positive regulator of ammonium utilization and rerouted the main nitrogen flux from glutamine to ammonium.
Transcriptomic changes in selected genes
1.00 ± 0.13
1.28 ± 0.11
3.36 ± 0.07
0.41 ± 0.06
0.06 ± 0.01
2.09 ± 0.23
0.10 ± 0.04
0.04 ± 0.01
1.09 ± 0.17
1.00 ± 0.21
2.46 ± 0.19
4.68 ± 0.78
1.02 ± 0.15
1.27 ± 0.28
2.02 ± 0.37
1.69 ± 0.21
0.92 ± 0.11
1.93 ± 0.40
1.00 ± 0.17
0.42 ± 0.05
0.08 ± 0.004
0.16 ± 0.03
0.86 ± 0.21
0.10 ± 0.02
0.21 ± 0.05
0.28 ± 0.03
0.12 ± 0.01
1.00 ± 0.18
0.52 ± 0.09
0.48 ± 0.07
0.11 ± 0.03
0.07 ± 0.01
0.29 ± 0.04
0.05 ± 0.007
0.04 ± 0.01
0.03 ± 0.005
1.00 ± 0.19
1.66 ± 0.23
1.17 ± 0.19
0.67 ± 0.08
0.46 ± 0.11
0.99 ± 0.24
0.89 ± 0.17
0.33 ± 0.05
0.44 ± 0.08
1.00 ± 0.09
1.06 ± 0.04
0.83 ± 0.39
5.26 ± 0.57
2.59 ± 0.31
3.78 ± 0.86
0.36 ± 0.06
2.87 ± 0.33
2.71 ± 0.37
1.00 ± 0.12
0.24 ± 0.07
0.17 ± 0.02
0.37 ± 0.08
0.46 ± 0.09
0.15 ± 0.01
0.06 ± 0.007
0.07 ± 0.004
0.29 ± 0.03
1.00 ± 0.07
0.13 ± 0.006
0.17 ± 0.02
0.14 ± 0.03
0.56 ± 0.02
0.05 ± 0.003
0.02 ± 0.001
0.03 ± 0.007
0.09 ± 0.01
1.00 ± 0.07
0.29 ± 0.03
0.23 ± 0.01
0.03 ± 0.001
0.65 ± 0.04
0.11 ± 0.01
0.02 ± 0.005
0.01 ± 0.001
0.01 ± 0.002
In this study, we demonstrated the effect of glucose on fermentation products through qualitative and quantitative analyses for the first time. The γ-PGA concentration decreased by 31.54 and 61.62% when the culture medium was supplemented with glucose at 5 and 10 g/L, respectively. However, the polysaccharide concentration rose sharply from 5.2 to 43.47% with the addition of glucose at 10 g/L. The SWATH-MS method was used to clarify bacterial metabolic regulation at the protein level, resulting in the detection of 969 intracellular proteins. Carbon control proteins (CcpA and CcpN) redistributed the carbon flux from γ-PGA to polysaccharide production in the presence of glucose. Simultaneously, the regulatory protein NrgB converted the major nitrogen metabolic flux from NH4 + to glutamate. Overall, the central metabolic turnover processes of two different extracellular polymeric substances in B. licheniformis CGMCC2876 were elucidated and provided an effective fermentation strategy for regulating the production of polysaccharides and γ-PGA. Our results offer different molecular weights for diverse applications through the regulation of the ratio of the carbon source in the culture. Moreover, the regulatory mechanism provides meaningful biological information for the metabolic engineering of B. licheniformis for enhanced flocculate production.
Strain and media
The B. licheniformis CGMCC2876 used in this study was isolated by our laboratory .
The pre-culture medium consisted of the following components (g/L): glucose, 10; urea, 0.5; MgSO4, 0.2; KH2PO4, 0.1; K2HPO4, 0.1; NaCl, 0.1 and yeast extract, 0.5 (pH 7.2). The γ-PGA production medium contained the following components (g/L): trisodium citrate, 20; glycerol, 20; NH4Cl, 9; sodium glutamate, 10; MgSO4, 0.5; and K2HPO4, 0.5 (pH 7.2). A total of 5 or 10 g/L of glucose was added to the γ-PGA production medium.
The cells were first maintained in an Erlenmeyer flask containing pre-culture medium at 37 °C at 200 rpm for 17 h and then transferred (at a 4% inoculum ratio) into a 250 mL Erlenmeyer flask with 50 mL of γ-PGA production medium (containing 5, 10 g/L, or no glucose) for γ-PGA production.
SWATH acquisition LC–MS/MS method analysis
For the preparation of cytoplasm proteins, the bacteria were harvested by centrifugation (12,000×g, 15 min, 4 °C) at three sampling times (early, middle and late). The early sampling time was during exponential growth, when OD600 = 1.0. The middle sampling time was 1 h after glucose was exhausted in the γ-PGA production medium supplemented with 5 g/L glucose. The late sampling time was at the end of fermentation. The pellets were washed with TE buffer (10 mM Tris and 1 mM EDTA, pH 7.5) and then resuspended in TE buffer . The resuspended cells were disrupted twice at 25 kpsi at 4 °C using a homogenizer (One Shot Model, Constant Systems, UK). The cell debris was removed by centrifugation at 14,000×g for 15 min at 4 °C. SWATH acquisition LC–MS/MS was performed using an Eksigent nanoLC-ultra system coupled with a Triple-TOF5600 Mass Spectrometer (ABSCIEX, Canada). Details of the parameters and data analysis for SWATH were reported by Yu et al. .
Concomitant with the protein extraction, RNA was immediately extracted from the samples during exponential growth (OD600 = 1.0), 1 h after glucose was exhausted in the γ-PGA production medium supplemented with 5 g/L glucose, and at the end of fermentation using the MiniBEST Universal RNA Extraction Kit (TaKaRa, Japan). The isolated RNA was quantified using a Spectrophotometer Q6000 (Quawell, USA). A high capacity cDNA reverse transcription kit (Applied Biosystems, USA) and a TransStart Top Green qPCR SuperMix Kit (TransGen Biotech, China) were used for reverse transcription and real-time PCR, respectively. The real-time PCR analysis was performed using a StepOne Real-Time PCR System (Applied Biosystems, USA). Reactions without the cDNA template were used as the negative controls, and γ-PGA medium without glucose was used as the reference in the calculations.
Purification of fermentation products
After 24 h of fermentation, the culture broths were centrifuged at 10,000×g for 15 min to remove the cells. Three volumes of ethanol were added to the supernatant to precipitate the crude products. Then, the crude products were dissolved using distilled water and dialyzed (molecular weight cut-off of 7000 Da) in distilled water overnight. Finally, the sample was lyophilized to obtain the purified products .
Qualitative and quantitative analyses of the fermentation products
The total sugar content of the purified products was determined by the phenol–sulfuric acid method using glucose as the standard solution . The total protein content was measured by the Bradford method using a protein assay kit (Bio-Rad, USA).
To measure the γ-PGA content, the purified products were dissolved in 6 M HCl to hydrolyze the γ-PGA. The mixtures were maintained at 110 °C for 12 h. The hydrolysates were neutralized and metered volumetrically and then characterized by HPLC for qualitative and quantitative analysis. The HPLC analysis was performed on an Agilent 1200 HPLC system using an Agilent HC-C18 (25 cm × 4.6 mm) column and a UV detector (210 nm). The mobile phase consisted of 10 mM KH2PO4 (pH 2.5) and methanol (5%, v/v) at a flow rate of 0.5 mL/min. Pure sodium glutamate was used as the standard compound .
Determination of the molecular masses of the fermentation products
Molecular mass was evaluated by high-performance gel permeation chromatography (HPGPC) coupled with refractive index (RI) detection using a TSK G4000PWxl column (Tosoh, Japan). The mobile phase was NaN3 (0.01%) at a flow rate of 0.5 mL/min. The column temperature and pressure were maintained at 30 °C and 1.3 MPa, respectively. A dextran T series (Pharmacia, Sweden) was used as the standard compound for the molecular mass determination .
sequential window acquisition of all theoretical fragment-ion spectra
tricarboxylic acid cycle
WCY, ZC, NH, CJZ, YPW and QBL designed the experiments. WCY, ZC and HY preformed the experiments. WCY, ZC and NH analyzed the results. WCY, ZC, NH and SY wrote the manuscript which was reviewed and approved by all authors. All authors read and approved the final manuscript.
This work was financially supported by the National Key Research and Development Plan (2016YFD0400205), National Natural Science Foundation of China (51378444, 21676221), the University of Science and Technology in Fujian Province in the cooperative major project (2015H6004) and Xiamen Southern Oceanographic Center (15GYY024NF03). We also gratefully acknowledge the Analysis and Testing Center, School of Life Sciences, Xiamen University and the Fujian Provincial Scientific and Technological Innovation Platform of China (2014H2006) for their technical support and AJE for language polishing work.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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