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Frontiers of Chemical Science and Engineering

ISSN 2095-0179

ISSN 2095-0187(Online)

CN 11-5981/TQ

Postal Subscription Code 80-969

2018 Impact Factor: 2.809

Front. Chem. Sci. Eng.    2022, Vol. 16 Issue (12) : 1751-1760    https://doi.org/10.1007/s11705-022-2211-x
RESEARCH ARTICLE
Genomic and metabolomic analysis of Bacillus licheniformis with enhanced poly-γ-glutamic acid production through atmospheric and room temperature plasma mutagenesis
Xiaoyu Wei1, Lijie Yang1, Haiyan Wang1, Zhen Chen3, Yiyuan Xu1, Yue Weng1, Mingfeng Cao1, Qingbiao Li2(), Ning He1()
1. Department of Chemical and Biochemical Engineering, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
2. College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
3. College of Life Science, Xinyang Normal University, Xinyang 464000, China
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Abstract

Poly-γ-glutamic acid is an extracellular polymeric substance with various applications owing to its valuable properties of biodegradability, flocculating activity, water solubility, and nontoxicity. However, the ability of natural strains to produce poly-γ-glutamic acid is low. Atmospheric and room temperature plasma was applied in this study to conduct mutation breeding of Bacillus licheniformis CGMCC 2876, and a mutant strain M32 with an 11% increase in poly-γ-glutamic acid was obtained. Genome resequencing analysis identified 7 nonsynonymous mutations of ppsC encoding lipopeptide synthetase associated with poly-γ-glutamic acid metabolic pathways. From molecular docking, more binding sites and higher binding energy were speculated between the mutated plipastatin synthase subunit C and glutamate, which might contribute to the higher poly-γ-glutamic acid production. Moreover, the metabolic mechanism analysis revealed that the upregulated amino acids of M32 provided substrates for glutamate and promoted the conversion between L- and D-glutamate acids. In addition, the glycolytic pathway is enhanced, leading to a better capacity for using glucose. The maximum poly-γ-glutamic acid yield of 14.08 g·L–1 was finally reached with 30 g·L–1 glutamate.

Keywords ARTP mutagenesis      Bacillus licheniformis      poly-γ-glutamic acid      metabolomics     
Corresponding Author(s): Qingbiao Li,Ning He   
Online First Date: 28 September 2022    Issue Date: 19 December 2022
 Cite this article:   
Xiaoyu Wei,Lijie Yang,Haiyan Wang, et al. Genomic and metabolomic analysis of Bacillus licheniformis with enhanced poly-γ-glutamic acid production through atmospheric and room temperature plasma mutagenesis[J]. Front. Chem. Sci. Eng., 2022, 16(12): 1751-1760.
 URL:  
https://academic.hep.com.cn/fcse/EN/10.1007/s11705-022-2211-x
https://academic.hep.com.cn/fcse/EN/Y2022/V16/I12/1751
Fig.1  ARTP mutagenesis and characteristics of screened B. licheniformis. (a) Growth curve of B. licheniformis CGMCC 2876; (b) Effects of ARTP treatment time on the mortality rate of B. licheniformis; (c) Analysis of the crude γ-PGA yield of ARTP-mutated strains; (d) γ-PGA production and flocculating activity of the rescreened strains; (e) The stability of the mutant M32.
Characters CGMCC 2876 M32
Crude yield/(g?L–1) 9.36 ± 0.24 13.6 ± 0.26
γ-PGA/(g?L–1) 6.01 ± 0.34 6.68 ± 0.35
Total sugar/(g?L–1) 0.35 ± 0.02 0.35 ± 0.04
Protein/(g?L–1) 0.15 ± 0.05 0.15 ± 0.05
Other components/(g?L–1) 4.33 ± 0.12 6.42 ± 0.15
Tab.1  Productions and compositions of extracellular polymers produced by B. licheniformis CGMCC 2876 and the mutant M32
Gene Definition Amino acid change
ppsC_1 Plipastatin synthase subunit C Phe1266Phe
ppsA_1 Plipastatin synthase subunit A Arg29Ser
ppsC Plipastatin synthase subunit C Arg1092Cys, Val1250Met, Ala915Met, Tyr963Tyr, Ala1117Ser, Tyr926His, Ala931Tyr, Gln4652His
rnja Ribonuclease J1 Leu477Thr
grsA Gramicidin S synthase 1 Pro20Ala, Ala26Ser
lgrB Antiholin-like protein Asp4656Gln, His154Arg, Thr4661Ala, Arg4651Arg, Asp4658His, Gly160Glu, Thr4661Ala, Ser4647Ile
Tab.2  SNPs analysis of M32
Fig.2  The molecular simulation docking of PpsC and (a) glutamate, (b) valine and (c) alanine before and after ARTP mutagenesis in B. licheniformis CGMCC 2876 (up) and the mutant M32 (down).
Strain Substrate Score/ (kcal?mol–1) Bound amino acid
B. licheniformis CGMCC 2876 Glu –15.3 Asp1886, Arg1976, Arg1975
Val –14.9 Arg1883, Asp1868
Ala –15.2 Asp1868, Tyr1880, Arg1883
M32 Glu –18.2 Asp1868, Lys1972, Arg1883
Val –11.5 Arg1883, Asp1868
Ala –11.1 Asp1868, Lys1972
Tab.3  The PpsC docking score and the key amino acids combined with the ligands in B. licheniformis CGMCC 2876 and the mutant M32
Fig.3  Comparative metabonomic analysis of B. licheniformis CGMCC 2876 and the mutant M32. (a) The PCA score plot and (b) OPLS-DA score plot were obtained between B. licheniformis CGMCC 2876 and M32. (c) Heatmap of 60 differential metabolites for normalized concentrations. The normalized abundance values are indicated from blue (increase) to red (decrease).
Fig.4  The intracellular metabolites and key genes in the γ-PGA synthetic pathways in B. licheniformis CGMCC 2876 and the mutant M32. The number represents the multiple of the M32 mutant compared to the wild-type strain.
Fig.5  Gene expression in the γ-PGA synthesis and glycolysis pathways of B. licheniformis CGMCC 2876 and the mutant M32.
Fig.6  Effects of sodium glutamate supplementation on γ-PGA yields of B. licheniformis CGMCC 2876 and the mutant M32. The single asterisks indicate significant differences in each group (P < 0.05).
Gene Primer sequence (5’ to 3’)
q-crr-F TCAAGCCGCATCCACC
q-crr-R AAGTTCTCCAATAAAATCTCCC
q-pyk-F CAGCCGCTTTTTCAAGGGAC
q-pyk-R CAGCCGCTTTTTCAAGGGAC
q-pdh-F CTCTTGTCATTGGTGCGGGA
q-pdh-R CATTCTCATAGCGGTGGCCT
q-pgi-F CTTTCGGCAGCACATTG
q-pgi-R GTCGCCCACCATACCAT
q-glpk-F GCGTGCCTAAACCTACAAA
q-glpk-R CGTGATGGGCTGAGAATG
q-gapB-F ACGCTGGAGACGATTGC
q-gapB-R CCACGGAAGAAGTTTAGGG
q-capA-F CCATTTGCGAAGGAGTTT
q-capA-R GCTGACGAAGCAGGAGAA
q-capB-F GAATTGTCTGCGACGATGACT
q-capB-R GATGGGACCGACTTTGGAT
q-capC-F AGCGTAATCGTTAATCCCTGTC
q-capC-R CGGTGATGCCGTTTGAGA
q-glnA-F AGTCATGGTCAAAGCCCTCG
q-glnA-R CTCCCAAGGGTGGACTTGTG
q-gltA-F GGCAACAAAGTGTATCC
q-gltA-R TCGGTGAGGCTCCAGTG
q-gltB-F AGCGTCGTCCAGTTCGG
q-gltB-R CGCCTCTTCATAAGCATAGT
q-pdgS-R AGACATCTTGAGGGTGCG
q-pdgS-R TCCGTTTGATTTTGTGCTG
q-ccpN-F CCTGTTTGCCGATGCTG
q-ccpN-R CGCGGGTCGGTTATTTC
q-ccpA-F CGAGCCGTAAAGGAACA
q-ccpA-R GCTTGCCATTTGAGGAA
q-16S-F CAGATTTGTGGGATTGGCTTAG
q-16S-R CGTGTCGTGAGATGTTGGGT
  Primers used in qRT-PCR in this experiment
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[1] Chenggang Qiu, Alei Zhang, Sha Tao, Kang Li, Kequan Chen, Pingkai Ouyang. Combination of ARTP mutagenesis and color-mediated high-throughput screening to enhance 1-naphthol yield from microbial oxidation of naphthalene in aqueous system[J]. Front. Chem. Sci. Eng., 2020, 14(5): 793-801.
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