Literature DB >> 30793535

Genome and transcriptome analysis of Bacillus velezensis BS-37, an efficient surfactin producer from glycerol, in response to d-/l-leucine.

Dayuan Zhou1, Fangxiang Hu1, Junzhang Lin2, Weidong Wang2, Shuang Li1,3.   

Abstract

Surfactin is one of the most widely studied biosurfactants due to its many potential applications in different fields. In the present study, Bacillus velezensis BS-37, initially identified as a strain of Bacillus subtilis, was used to efficiently produce surfactin with the addition of glycerol, an inexpensive by-product of biodiesel production. After 36 hr of growth in glycerol medium, the total surfactin concentration reached more than 1,000 mg/L, which was two times higher than that in sucrose medium. Moreover, the addition of l- and d-Leu to the culture medium had opposite effects on surfactin production by BS-37. While surfactin production increased significantly to nearly 2,000 mg/L with the addition of 10 mM l-Leu, it was dramatically reduced to about 250 mg/L with the addition of 10 mM d-Leu. To systemically elucidate the mechanisms influencing the efficiency of this biosynthesis process, we sequenced the genome of BS-37 and analyzed changes of the transcriptome in glycerol medium in response to d-/l-leucine. The RPKM analysis of the transcriptome of BS-37 showed that the transcription levels of genes encoding modular surfactin synthase, the glycerol utilization pathway, and branched-chain amino acid (BCAA) synthesis pathways were all at a relatively high level, which may offered an explanation why this strain can efficiently use glycerol to produce surfactin with a high yield. Neither l-Leu nor d-Leu had a significant effect on the expression of genes in these pathways, indicating that l-Leu plays an important role as a precursor or substrate involved in surfactin production, while d-Leu appears to act as a competitive inhibitor. The results of the present study provide new insights into the synthesis of surfactin and ways of its regulation, and enrich the genomic and transcriptomic resources available for the construction of high-producing strains.
© 2019 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Entities:  

Keywords:  biofilm; genome; leucine; surfactin; transcriptome

Mesh:

Substances:

Year:  2019        PMID: 30793535      PMCID: PMC6692528          DOI: 10.1002/mbo3.794

Source DB:  PubMed          Journal:  Microbiologyopen        ISSN: 2045-8827            Impact factor:   3.139


INTRODUCTION

Biosurfactants, for their excellent surface activity, temperature tolerance, and biodegradability, have received great attention in the past decade. However, apart from a few biosurfactants such as sophorolipids, rhamnolipids, and mannosyl erythritol lipids (Chen, Juang, & Wei, 2015; Desai & Banat, 1997), their industrial application is largely restricted. Surfactin, a lipopeptide biosurfactant produced by Bacillus strains, is one of the most surface‐active biosurfactants, and it has potential applications in medicine, agriculture, and microbial enhanced oil recovery (MEOR) (Ashish & Debnath, 2018; Paraszkiewicz et al., 2017; Rodrigues, Banat, Teixeira, & Oliveira, 2006). However, due to its high production cost, its industrial applications are still underdeveloped. Therefore, improving its yield and reducing its production cost will be of great significance. Most of the efficient surfactin producers reported to date prefer sucrose as the carbon source (Jiao et al., 2017; Yan, Wu, & Xu, 2017). By contrast, glycerol, which is a by‐product of biodiesel production, is a widely available and inexpensive source of carbon, making its conversion into value‐added products of great interest (Clomburg & Gonzalez, 2013; Faria et al., 2011). Thus, producing surfactin efficiently utilizing glycerol as carbon source can not only reduce the production cost, but also solve the problem of glycerol valorization in the production of biodiesel. Surfactin is synthesized via a complex mechanism catalyzed by a nonribosomal peptide synthetase (NRPS), which is encoded by the srfA operon (srfAA, srfAB, srfAC, srfAD) (Nakano et al., 1991). These enzymes preferentially use amino acid and fatty acid residues present in the cytoplasm of the cell as substrates. The hydrophobic tail of surfactin is a β‐hydroxylated fatty acid chain with different lengths and isoforms, and the hydrophilic head is a circular heptapeptide containing l‐glutamic (l‐Glu), l‐aspartic (l‐Asp), l‐valine (l‐Val), l‐leucine (l‐Leu), and dleucine (dLeu) (Seydlova & Svobodova, 2008; Yang, Li, Li, Yu, & Shen, 2015). Therefore, amino acids and fatty acids are of great importance for the synthesis of surfactin, regardless of the synthetic mechanism or structural characteristics of the surfactin subtype. Liu, Yang, Yang, Ye, & Mu, 2012 reported that the addition of different amino acids to the cultures had a significant influence on the proportion of surfactin variants with different fatty acids. The peptide moiety contains two l‐Leu and two dLeu residues (Figure 1), and the content of Leu in cells is crucial for the synthesis of surfactin (Etchegaray et al., 2017). Moreover, the research of Coutte et al. indicated that leucine overproduction significantly improved the production of surfactin in recombinant Bacillus subtilis 168 derivatives (Coutte et al., 2015).
Figure 1

Schematic representation of surfactin (Coutte et al., 2015)

Schematic representation of surfactin (Coutte et al., 2015) In this study, Bacillus velezensis BS‐37 was found to efficiently produce surfactin at a very high level with the addition of glycerol. Interestingly, the addition of l‐ and dLeu to the culture medium as nitrogen source had opposite effects on surfactin production by BS‐37. To better understand the strain BS‐37 and the effects of d‐/l‐Leu on surfactin synthesis, genome sequencing in combination with global transcriptome analysis was employed. The transcription levels of genes related to surfactin biosynthesis, including the modular surfactin synthetase, glycerol utilization pathway, branched‐chain amino acid (BCAA) synthesis pathways, and the branched fatty acid (FA) metabolic pathway, were further studied. These results will hopefully provide a theoretical basis for later genetic manipulation of B. velezensis BS‐37.

MATERIALS AND METHODS

Bacterial strains and growth conditions

Bacillus velezensis BS‐37 is a mutant derivative of strain 723, which was isolated from petroleum‐contaminated soil from the Shengli Oil Field, China (Zhu, Xu, Jiang, Huang, & Li, 2014). It was cultivated in 250‐ml flasks containing 50 ml of minimal medium (0.2% NH4NO3, 1% KH2PO4•3H2O, 0.02% MgSO4•7H2O, 0.002% FeSO4•7H2O) supplied with 2% glycerol (MMG) or 2% sucrose (MMS). Different concentrations (0–20 mM) of dLeu or l‐Leu were added into MMG medium, and a group without added amino acids served as the negative control. The pH of all media was adjusted to 7.5 with 5 M HCl or 5 M NaOH. Sterilization was conducted at 121°C for 20 min. The cultures were incubated at 37°C and 200 rpm. At various time‐points, the cell density was measured by measuring the OD600 using a spectrometer.

Surfactin production assay

The surfactin production was quantified according to a published HPLC method (Zhu et al., 2014). Briefly, 1 ml samples were extracted from the shake flasks, and a cell‐free supernatant was obtained by centrifugation at 10,000 g for 10 min. An aliquot comprising 300 µl of the supernatant was withdrawn, diluted fivefold with methanol, and shaken for 1 min. Then, the precipitate of samples was removed through centrifugation for 2 hr at 10,000 g under 4°C. Subsequently, the supernatant needed to be further filtered by a 0.22 μm nylon membrane remove impurities. The final sample was analyzed by HPLC on a U‐3000 system (Thermo Fisher Scientific, USA) equipped with a Synchronis C18 column (4.6 × 250 mm, 5 μm; Thermo Fisher Scientific) and a UV detector (Thermo Fisher Scientific). The analytes were detected at 214 nm, using 90% (v/v) methanol, 10% (v/v) water, and 0.05% trifluoroacetic acid as mobile phase with a flow rate of 0.8 ml/min. The authentic surfactin (98%) reference standard was purchased from Sigma‐Aldrich, USA. The proportions of surfactin isoforms were analyzed by comparing the peak areas observed by HPLC to the sum of areas of all surfactin peaks.

Genome sequencing and annotation

Before sequencing, the BS‐37 cells needed to be harvested through centrifugation for 5 min at 10,000 g and 4°C after cultivated for 24 hr. The isolation of genomic DNA was carried out using a Rapid Bacterial Genomic DNA Isolation Kit (GENEWIZ, China). Whole‐genome sequencing was performed using a Pacific Biosciences (PacBio, China) RSII single molecule real‐time (SMRT) sequencing technique with a 20‐kb SMARTbellTM template library. The circular chromosome was assembled by the obtained reads with the SMRT Analysis 2.3.0 software. Then, the complete genome of B. velezensis BS‐37 was upload to the NCBI database under the GenBank accession number CP023414. The prodigal software was used to assign coding genes from bacteria (Hyatt et al., 2010). Gene annotation of B. velezensisBS‐37 was performed using the National Center for Biotechnology Information (NCBI) database in conjunction with Diamond (Buchfink, Xie, & Huson, 2015). Subsequently, the functions of genes were annotated using the GO database (http://www.geneontology.org/), and the pathways were annotated using the KEGG database (http://www.genome.ad.jp/kegg/). The proteins encoded by the annotated genes were classified based on phylogeny using the COG database (http://www.ncbi.nlm.nih.gov/COG/).

RNA isolation, library construction, and Illumina sequencing

For RNA extraction, the cells of BS‐37 for 12 hr were harvested by centrifugation at 8,000 g for 5 min at 4°C, at the period of the fermentation when the production rate was the highest. The resulting pellets were immediately frozen in liquid nitrogen. Total RNA was isolated using the Trizol Reagent (Invitrogen Life Technologies, USA), according to the manufacturer's instructions. Quality and integrity were determined using a NanoDrop spectrophotometer (Thermo Scientific) and a Bioanalyzer 2100 system (Agilent, USA). To remove rRNA, the Ribo‐Zero rRNA removal kit (Illumina, San Diego, CA, USA) was employed. The synthesis of first‐strand cDNA was performed by random oligonucleotides and SuperScript III. Subsequently, polymerase I and RNase H were used to synthesize the second‐strand cDNA. The conversion of remaining overhangs to blunt ends was conducted by polymerase. The hybridization was performed after the adenylation of the 3′ ends of the DNA fragments and the combination with Illumina PE adapter oligonucleotides. To select the preferred cDNA fragments length of 300 bp, the library fragments were purified using the AMPure XP system (Beckman Coulter, Beverly, CA, USA). Illumina PCR Primer Cocktail in a 15 cycle PCR was used to selectively enrich the DNA fragments with ligated adaptor molecules on both ends. Besides, purification and quantification of products were conducted by AMPure XP system (Beckman Coulter) and Agilent high sensitivity DNA assay on a Bioanalyzer 2100 system (Agilent), respectively. Finally, the resulting library was sequenced on a NextSeq 500 platform (Illumina) by Shanghai Personal Biotechnology Co. Ltd.

Mapping reads to the reference genome and normalized gene expression

After removing out rRNA reads, sequencing adapters, short‐fragment reads, and other low‐quality reads, the sequencing raw reads were preprocessed. The remaining clear reads were mapped to the reference genome of BS‐37 using Bowtie 2 software based on the local alignment algorithm (Langmead & Salzberg, 2012). By calculating the RPKM value (reads per kilobase per million mapped reads), the expression levels and the gene length were normalized to the library (Frazee et al., 2015). DESeq software was used to quantify all transcripts with differential expression (Wang, Feng, Wang, Wang, & Zhang, 2010). Correcting the consequence of multiple hypothesis testing was operated by FDR (False Discovery Rate) control.

Reconstruction of the KEGG pathway map

The assignment of functional annotation descriptions was conducted by BLASTP (Altschul et al., 1998) in conjunction with the KEGG database (E‐value cutoff of 1E‐10). Subsequently, the KEGG map was manually redrawn using Adobe Illustrator CC 2014 (Adobe Systems, USA). The expressed genes which involved in the biosynthesis of surfactin were generated as heat maps with the GraphPad Prism 7 (GraphPad Software, Inc., La Jolla, CA, USA).

RESULTS AND DISCUSSION

Genomic analysis of the strain BS‐37

The optimal carbon source for strain BS‐37 was found to be glycerol, and its fermentation products contained more than 50% of the desirable surfactin isoform C15(Liu, Lin, Wang, Huang, & Li, 2015; Yi et al., 2017). In order to investigate the genomic organization of the metabolic pathways responsible for glycerol utilization and biosynthesis of surfactin, the complete genome of strain BS‐37 was sequenced. This strain was initially incorrectly identified as a B. subtilis. Subsequently, it was demonstrated by complete genome sequencing that this is a strain of B. velezensis. The principal features of the BS‐37 genome are shown in Figure 2. The 4,013,888‐bp long BS‐37 genome is composed of a circular chromosome with an average GC content of 46.46%. The chromosome contains 3,846 CDS, 90 rRNA and 86 tRNA genes (Table 1). Among the CDS, 3,395 (88.27%) were classified into 21 “cluster of orthologous groups” (COG) functional categories. The functions of most genes were associated with important transcription and metabolism pathways, such as amino acid, carbohydrate, inorganic ion and energy production and conversion pathways (Table 2).
Figure 2

Circular representation of the Bacillus velezensis BS‐37 genome. The circular map consists of five circles. From the outmost circle inwards, each circle contains information about the genome regarding the G + C ratio, reverse CDS, forward CDS, rRNA/tRNA, and long segment repeats, respectively

Table 1

Features of the Bacillus velezensis BS‐37 genome

FeatureValue
Chromosome number1
Genome size (bp)4,013,888
GC content (%)46.46
Protein coding genes (CDS)3,846
rRNA90
tRNA86
ncRNA91
Table 2

Distribution of COG functional categories in the complete genome sequence of Bacillus velezensis BS‐37

COG codeDescriptionGene number
FNucleotide transport and metabolism81
EAmino acid transport and metabolism344
QBiosynthesis, transport and catabolism of secondary metabolites110
ILipid transport and metabolism115
BChromatin structure and dynamics1
KTranscription281
LReplication, recombination, and repair132
SFunction unknown314
GCarbohydrate transport and metabolism265
RGeneral function prediction only446
HCoenzyme transport and metabolism132
JTranslation, ribosomal structure, and biogenesis162
UIntracellular trafficking, secretion, and vesicular transport46
DCell cycle control, cell division, chromosome partitioning35
CEnergy production and conversion181
TSignal transduction mechanisms151
OPosttranslational modification, protein turnover, chaperones97
MCell wall/membrane/envelope biogenesis192
NCell motility56
PInorganic ion transport and metabolism195
VDefense mechanisms59
Total3,395
Circular representation of the Bacillus velezensis BS‐37 genome. The circular map consists of five circles. From the outmost circle inwards, each circle contains information about the genome regarding the G + C ratio, reverse CDS, forward CDS, rRNA/tRNA, and long segment repeats, respectively Features of the Bacillus velezensis BS‐37 genome Distribution of COG functional categories in the complete genome sequence of Bacillus velezensis BS‐37 The putative key genes of glycerol and sucrose metabolism in BS‐37 were identified by whole‐genome analysis (Figure 3). The amino acid sequences encoded by these genes were arranged in comparison with those of B. subtilis 168 and MT45. In sucrose metabolism, five key enzymes catalyzing the steps from sucrose to glyceraldehyde‐3‐phosphate were compared, revealing that sucrose transport, hydrolysis, and fructokinase are represented by different isozymes. In fact, there were large differences between strain 168 and BS‐37, with SacA, SacP, and GmuE having sequence similarities at the protein level of <80%. By contrast, the similarity with MT45 was higher than 90% in all cases. In glycerol metabolism, three key proteins were compared between 168 and MT45, and their protein sequence similarity reached over 90% (Table 3).
Figure 3

Key genes of the pathways channeling sucrose and glycerol into the glycolytic pathway of Bacillus sp.

Table 3

Analysis of amino acid identity of the putative key genes for glycerol and sucrose metabolism

FunctionGene nameGene ID168MT45
(BS‐37)Identity (%)
Sucrose metabolism sacP a 1_0012/1_351579/8294/99
sacA a 1_3054/1_351677/7890/91
gmuE a 1_2644/1_345367/6892/95
fbaA 1_36129999
pfkA 1_05439799
Glycerol metabolism glpF 1_23448796
glpK 1_23439297
glpD 1_23429098

Isozymes with different coding genes.

Key genes of the pathways channeling sucrose and glycerol into the glycolytic pathway of Bacillus sp. Analysis of amino acid identity of the putative key genes for glycerol and sucrose metabolism Isozymes with different coding genes.

The biomass and surfactin production from glycerol and sucrose

Many previously characterized bacteria, such as B. subtilis 168 and Bacillus amyloliquefaciens MT45, can utilize sucrose to produce surfactin with high efficiency, but few of these can efficiently use glycerol (Amani, Haghighi, & Keshtkar, 2013; Biniarz, Coutte, Gancel, & Lukaszewicz, 2018; Zhu, Zhang, Chen, Cai, & Lin, 2016). It is therefore notable that BS‐37 shows the opposite substrate preference. The results revealed that up to 1,000 mg/L of surfactin could be accumulated after 36 hr of fermentation in minimal medium with glycerol (MMG). By contrast, the yield only reached about 350 mg/L in minimal medium with sucrose (MMS; Figure 4a). In addition, this strain reached an OD600 of 3.5 in MMG, which was twice higher than in MMS (Figure 4b). These results indicate that BS‐37 prefers glycerol over sucrose in terms of both growth and efficient surfactin production. Notably, the pH was constant during the 60 hr of cultivation.
Figure 4

Surfactin production and cell growth in MMG and MMS media. (a) Surfactin production curve. (b) Cell growth curve

Surfactin production and cell growth in MMG and MMS media. (a) Surfactin production curve. (b) Cell growth curve

Effects of supplementing d‐ and l‐Leu on surfactin production

To investigate the influence of d‐/l‐Leu on the growth of BS‐37 and the yield of surfactin, a preliminary study of the addition of d‐/l‐Leu at a series of concentrations was conducted. All the production and biomass data were collected after 36 hr of fermentation. With the increase in d‐/l‐Leu concentration, surfactin production showed great differences. The surfactin yield improved with increasing concentrations of l‐Leu, and with the supplementation of 10 mM l‐Leu reached a maximum of about 2,000 mg/L, twice that of the control (Figure 5a). Adding l‐Leu increased the percentage of the surfactin fatty acid chain length variants iso‐C13 and iso‐C15 (Figure 5b), as had already been reported (Liu, Yang, Yang, Ye, & Mu, 2012). However, the addition of dLeu unexpectedly inhibited the production of surfactin. With the increase in dLeu concentration, the surfactin yield gradually decreased, reaching a low titer of 250 mg/L with the supplementation of 10 mM dLeu (Figure 5c). Interestingly, it was found that the inhibitory effects of 10 mM dLeu on surfactin accumulation can be relieved by adding 5 mM l‐Leu, and the surfactin titer was restored to 1,000 mg/L. The surfactin titer could even be increased to 1,600 mg/L by adding 10 mM l‐Leu on the basis of 10 mM dLeu (Figure 5d).
Figure 5

Cell growth and surfactin production of BS‐37 supplemented with d‐/l‐Leu. (a) Biomass and surfactin production in cultures with l‐Leu. (b) The proportion of surfactin variants (c) Biomass and surfactin production in cultures with d‐Leu. (d) Surfactin production in 10 mM d‐Leu medium with l‐Leu supplementation. (e) Surfactin production time course. (f) Cell growth time course

Cell growth and surfactin production of BS‐37 supplemented with d‐/l‐Leu. (a) Biomass and surfactin production in cultures with l‐Leu. (b) The proportion of surfactin variants (c) Biomass and surfactin production in cultures with dLeu. (d) Surfactin production in 10 mM dLeu medium with l‐Leu supplementation. (e) Surfactin production time course. (f) Cell growth time course

The transcriptome analysis effects of adding d‐ or l‐Leu

To reveal the transcriptomic correlates of the overproduction, we performed a transcriptome analysis based on RNA sequencing of BS‐37 under supplementation of 10 mM d‐/l‐Leu and control cultures. Samples were taken during the growth stage with the highest biomass increase and accumulation of surfactin (24 hr; Figure 5e,f). Three samples of each group were extracted and sequenced, generating over ten million reads for each sample with cleans ratios >85%. The sequence data are summarized in Table 4. Each sample had over 98% clean reads that could be matched to the reference genome, which indicated that the transcriptome data can provide sufficient support for further analysis.
Table 4

Summary of RNA‐seq and the reads mapped to the genome of BS‐37

SampleRaw readsTotal mapped reads%Uniquely mapped reads%Multiple mapped reads%
Control‐129,367,78228,813,15599.128,056,16497.37756,9912.63
Control‐231,758,85831,113,27098.5630,363,81197.59749,4592.41
Control‐332,117,85430,982,81997.1330,113,51797.19869,3022.81
10 mM l‐Leu‐129,297,62028,659,07298.6427,950,16497.53708,9082.47
10 mM l‐Leu‐231,467,44230,777,60498.5629,808,42596.85969,1793.15
10 mM l‐Leu‐336,099,21435,392,25498.7334,347,74597.051,044,5092.95
10 mM d‐Leu‐134,050,43233,515,34899.1931,973,11295.41,542,2364.6
10 mM d‐Leu‐233,131,25432,420,66498.4831,692,34997.75728,3152.25
10 mM d‐Leu‐332,684,20432,126,77199.1331,176,49497.04950,2772.96
Summary of RNA‐seq and the reads mapped to the genome of BS‐37 Differentially expressed genes (DEGs) in response to l‐/dLeu are listed in Table 5. Compared with the control, five genes were upregulated and seven genes were downregulated when adding 10 Mm l‐Leu; When 10 mM dLeu was added, 17 genes were upregulated and 25 were downregulated. Interestingly, the expression level of the azlBCD operon (encoding genes azlB, azlC, and azlD), which is responsible for the transport of leucine, had little difference between control and l‐/dLeu. Sporulation can be induced in B. subtilis by starvation of carbon, nitrogen, and phosphorus. In this study, four genes involved in sporulation (cotV, cotX, rpsR, and cgeB) were found to be downregulated after adding dLeu. Furthermore, the key genes related to amino acid and purine metabolism, such as argD, argB, purC, pyrB, pyrR, and guaC, were upregulated in the cultures with dLeu. These products provide the energy required for cell proliferation, offering an explanation for the higher biomass in the presence of dLeu compared to the control in the early stages (Table 6).
Table 5

Genes of Bacillus velezensis BS‐37 differentially expressed in response to l‐/d‐Leu

GeneEncoding proteinFold change ratio q‐value (%)
Upregulated (expressed in response to d‐Leu)
argD Acetylornithine aminotransferase2.260.04
argB Acetylglutamate kinase2.420.02
argG Argininosuccinate synthase2.540.04
pyrC Dihydroorotase2.150.04
pyrB Aspartate carbamoyltransferase2.260.04
pyrR Bifunctional pyrimidine regulatory protein PyrR uracil phosphoribosyltransferase2.060.02
guaC GMP reductase2.560.02
rutR TetR family transcriptional regulator2.080.04
carA Carbamoyl phosphate synthase small subunit2.570.03
lepB Signal peptidase2.000.04
dsbB 2‐oxoglutarate dehydrogenase2.460.03
plT Inorganic phosphate transporter2.010.00
mccB Cystathionine gamma‐synthase2.610.01
opuC Glycine betaine/carnitine/choline‐binding protein2.220.04
yxlA Hypothetical protein3.450.00
yxlD Putative protein2.780.02
yxwF Hypothetical protein2.780.03
Downregulated (expressed in response to d‐Leu)
cgeB Spore maturation protein CgeB0.040.04
cotV Spore coat protein0.370.01
cotX Spore coat protein0.420.02
rpsR Sporulation protein YjcZ0.250.00
bioW 6‐carboxyhexanoate‐CoA ligase0.330.01
bioA Adenosylmethionine‐8‐amino‐7‐oxononanoate aminotransferase0.220.00
bioF 8‐amino‐7‐oxononanoate synthase0.140.00
bioD Dethiobiotin synthetase0.140.00
bioB Biotin synthase0.210.00
bioI Cytochrome P4500.210.00
liaI Protein iaI0.310.01
liaH Phage shock protein A homolog0.330.01
fadD Acyl‐CoA synthetase0.450.04
atoB Acetyl‐CoA acetyltransferase0.430.03
gerE LuxR family transcriptional regulator0.340.01
ywlT Hypothetical protein0.370.03
ywhV Membrane protein0.150.00
ywgA Hypothetical protein0.140.03
ylmF Uncharacterized protein0.350.01
ysrdE Uncharacterized protein0.190.00
ylxF Putative oxidoreductase0.400.03
yrzF Uncharacterized protein0.160.00
ywqH Hypothetical protein0.020.02
ysdB Hypothetical protein0.010.01
yitR Hypothetical protein0.140.00
Upregulated (expressed in response to l‐Leu)
pgsC Poly‐gamma‐glutamate biosynthesis protein3.250.02
yxgK Hypothetical protein2.740.02
yxgC Hypothetical protein2.130.03
yxgB Hypothetical protein2.260.05
yxgM Hypothetical protein2.610.02
Downregulated (expressed in response to l‐Leu)
bioA Adenosylmethionine‐8‐amino‐7‐oxononanoate aminotransferase0.400.01
bioF 8‐amino‐7‐oxononanoate synthase0.410.02
bioD Dethiobiotin synthetase0.340.01
bioB Biotin synthase0.410.02
bioI Cytochrome P4500.380.00
clpE ATP‐dependent Clp protease ATP‐binding protein0.490.04
yxgH Uncharacterized protein0.480.03
Table 6

Detail information on genes involved in the surfactin synthesis pathway and their expression levels

GeneEncoding proteinRPKMExpression intensity
glpF Glycerol uptake facilitator protein268.05M
glpK Glycerol kinase292.79M
glpD Glycerol‐3‐phosphate dehydrogenase3,913.68H
gapA Glyceraldehyde 3‐phosphate dehydrogenase822.98H
gapA1 Glyceraldehyde 3‐phosphate dehydrogenase360.78H
pgK Phosphoglycerate kinase1,263.41H
pgmB Beta‐phosphoglucomutase19.01L
enO Enolase829.03H
pyK Pyruvate‐kinase741.43H
pdhA Pyruvate dehydrogenase E1 component alpha subunit35.57L
PdhA1 Pyruvate dehydrogenase E1 component alpha subunit48.42L
pdhB Pyruvate dehydrogenase E1 component beta subunit134.22M
pdhB1 Pyruvate dehydrogenase E1 component beta subunit42.10L
pdhC Pyruvate dehydrogenase E2 component88.81L
pdhC1 Pyruvate dehydrogenase E2 component559.59H
gltA Citrate synthase41.75L
gltA1 Citrate synthase1,275.28H
gltA2 Citrate synthase142.42M
acO Aconitate hydratase596.77H
icD Isocitrate dehydrogenase655.60H
sucA α‐oxoglutarate dehydrogenase E1 component694.23H
sucB α‐oxoglutarate dehydrogenase E2 component416.95M
sucD Succinyl‐CoA synthetase alpha subunit665.10H
sucC Succinyl‐CoA synthetase beta subunit138.34M
frd1 Succinate dehydrogenase40.65L
frd2 Succinate dehydrogenase721.62H
frd3 Succinate dehydrogenase1,212.02H
fumC Fumarate hydratase213.36M
mdH Malate dehydrogenase1,383.80H
accB Acetyl‐CoA carboxylase biotin carboxyl carrier protein11.19L
accC Acetyl‐CoA carboxylase, biotin carboxylase subunit32.80L
accA Acetyl‐CoA carboxylase carboxyl transferase subunit alpha93.49L
accD Acetyl‐CoA carboxylase carboxyl transferase subunit alpha176.19M
fabD Acyl‐carrier‐protein S‐malonyltransferase88.63L
acpP Acyl carrier protein473.00M
acpP1 Acyl carrier protein134.37M
fabF 3‐oxoacyl‐acyl‐carrier‐protein synthase II113.46M
fabH 3‐oxoacyl‐acyl‐carrier‐protein synthase III162.73M
fabH1 3‐oxoacyl‐acyl‐carrier‐protein synthase III83.42L
fabG 3‐oxoacyl‐acyl‐carrier protein reductase165.28M
fabG1 3‐oxoacyl‐acyl‐carrier protein reductase60.93L
fabG2 3‐oxoacyl‐acyl‐carrier protein reductase67.52L
fabG3 3‐oxoacyl‐acyl‐carrier protein reductase142.31M
fabG4 3‐oxoacyl‐acyl‐carrier protein reductase46.28L
fabG5 3‐oxoacyl‐acyl‐carrier protein reductase168.87M
fabZ 3‐hydroxyacyl‐acyl‐carrier‐protein dehydratase188.72M
fabZ1 3‐hydroxyacyl‐acyl‐carrier‐protein dehydratase65.54L
fabI Enoyl‐acyl‐carrier protein reductase I151.65M
fabL Enoyl‐acyl‐carrier protein reductase III100.02M
ilvB Acetolactate synthase large subunit480.96M
ilvH Acetolactate synthase small subunit121.19M
ilvB1 Acetolactate synthase I/II/III large subunit1844.90H
ilvC Ketol‐acid reductoisomerase732.24H
ilvD Dihydroxy‐acid dehydratase149.41M
leuA 2‐isopropylmalate synthase729.44H
leuB 3‐isopropylmalate dehydrogenase695.53H
leuC (R)‐2‐methylmalate dehydratase large subunit1,120.36H
leuD (R)‐2‐methylmalate dehydratase small subunit129.54M
AspB Aspartate aminotransferase1910.50H
yhdR Aspartate aminotransferase874.50H
ilvE Branched‐chain amino acid aminotransferase263.97M
ilvE‐1 Branched‐chain amino acid aminotransferase215.51M
pdhD Dihydrolipoamide dehydrogenase74.71L
bkdA1 Pyruvate dehydrogenase E1 component alpha subunit74.46L
bkdA2 Pyruvate dehydrogenase E1 component beta subunit63.71L
bkdB Pyruvate dehydrogenase E2 component132.29M
srfAD External thioesterase TEII3,396.47H
srfAC Surfactin family lipopeptide synthetase C3,883.08H
srfAB Surfactin family lipopeptide synthetase B3,831.80H
srfAA Surfactin family lipopeptide synthetase A3,090.12H
sfp 4′‐phosphopantetheinyl transferase171.40M

H: high expression (RPKM ≥ 500); L: low expression (RPKM < 100); M: medium expression (100 ≤ RPKM < 500).

Genes of Bacillus velezensis BS‐37 differentially expressed in response to l‐/dLeu Detail information on genes involved in the surfactin synthesis pathway and their expression levels H: high expression (RPKM ≥ 500); L: low expression (RPKM < 100); M: medium expression (100 ≤ RPKM < 500).

Construction of the KEGG pathway map for surfactin biosynthesis

In order to better understand the biosynthesis of surfactin in glycerol medium, we reconstructed the whole metabolic pathway of surfactin synthesis using the transcriptome of BS‐37 grown on glycerol. The transcripts with different levels were summarized into a heat map and subsequently displayed as a metabolic pathway map (Figure 6). The depth of the color in the map represents the strength of gene transcription according to the ranking of all the gene transcriptional intensities in the cells, represented by RPKM (Table 6). The transcripts were assessed according to their transcription levels and classified into high expression (RPKM ≥ 500), medium expression (100 ≤ RPKM < 500), and low expression (RPKM < 100) groups. According to the function, all modules were divided into glycolysis metabolism module, tricarboxylic acid cycle module, branched‐chain amino acid metabolism module, branched fatty acid biosynthesis module, and modular enzymatic synthesis of surfactin module.
Figure 6

Metabolic map of the pathways responsible for surfactin biosynthesis. The metabolic network was constructed based on KEGG pathway analysis. Five modules were partitioned according to their functions. 1, 2, 3, 4, and 5, respectively, represent different metabolic modules: 1, glycolysis metabolism module; 2, branched‐chain amino acid metabolism module; 3, tricarboxylic acid cycle module; 4, branched‐chain fatty acid biosynthesis module; and 5, modular enzymatic synthesis of surfactin module. Transcriptional levels of the relevant genes in BS‐37 are show next to the pathway as a heat map, based on the ranking of expression intensity (RPKM) in the whole genome. The color of each square represents the strength of gene transcription. The transcription level (RPKM) of glpD is defined as 100%, corresponding to pure red. The expression intensity of other genes was calculated as the ratio of their respective transcription levels (RPKM) to that of glpD. The culture condition is MMG medium without d/l‐leu. The expression is the ratio of the gene to glpD. In the paper, these have been defined

Metabolic map of the pathways responsible for surfactin biosynthesis. The metabolic network was constructed based on KEGG pathway analysis. Five modules were partitioned according to their functions. 1, 2, 3, 4, and 5, respectively, represent different metabolic modules: 1, glycolysis metabolism module; 2, branched‐chain amino acid metabolism module; 3, tricarboxylic acid cycle module; 4, branched‐chain fatty acid biosynthesis module; and 5, modular enzymatic synthesis of surfactin module. Transcriptional levels of the relevant genes in BS‐37 are show next to the pathway as a heat map, based on the ranking of expression intensity (RPKM) in the whole genome. The color of each square represents the strength of gene transcription. The transcription level (RPKM) of glpD is defined as 100%, corresponding to pure red. The expression intensity of other genes was calculated as the ratio of their respective transcription levels (RPKM) to that of glpD. The culture condition is MMG medium without d/l‐leu. The expression is the ratio of the gene to glpD. In the paper, these have been defined Modules 1, 2, and 3 of the pathway correspond to glycerol utilization, the subsequent glycolysis pathway, and TCA cycle, which provide the basis for the metabolism of the cell. The genes involved in the utilization of glycerol, including glpF, glpK, and glpD, were relatively highly expressed (Holmberg, Beijer, Rutberg, & Rutberg, 1990). Particularly, the transcription level (RPKM) of glpD, encoding glycerol‐3‐phosphate dehydrogenase, which is the key enzyme in the glycolysis pathway when cells are grown on glycerol, reached 3,913.68, which puts it into the top 1% of all transcription levels. Most of the genes involved in glycolysis and the TCA cycle were also highly expressed to provide enough energy and carbon moieties for downstream metabolic pathways. These include pyruvate, oxaloacetate, and acetyl‐CoA, which can act as precursors participating in the biosynthesis of Val/Leu, Glu/Asp, and fatty acids, respectively. The metabolism of branched‐chain amino acids has a significant effect on the synthesis of surfactin, since three different branched‐chain amino acid components are found in the cyclopeptide ring of surfactin. Especially, the content of Leu in the cells determines the yield of surfactin, because the peptide moiety of surfactin contains four leucines. Module 2 encompasses the synthesis of amino acids in the peptide moiety, including Glu, Val, Ile, Leu, and Asp. Genes involved in the synthesis of Leu (leuA, leuB, leuC) were highly expressed, supplying abundant precursors for surfactin overproduction. The metabolism of intracellular fatty acids is divided into straight‐chain fatty acid synthesis and branched‐chain fatty acid synthesis. The precursor of straight‐chain fatty acids is acetyl‐CoA, while the precursors of branched‐chain fatty acids are catabolic products of l‐Val, l‐Leu, and l‐Ile (Kaneda, 1991). These are converted into three different branched‐chain CoAs by the action of aminotransferase (ilvE) and the branched‐chain amino acid dehydrogenase complex (BkdA, BkdB, PdhD). The branched‐chain CoAs (isobutyryl‐CoA, 3‐methylbutanoyl‐CoA and (S)‐2‐methylbutanoyl‐CoA) act as precursors for the biosynthesis of different branched‐chain fatty acids, which are another intrinsic component of surfactin, constituting the hydrophobic tail. The expression level of genes related to the degradation of branched‐chain amino acids and synthesis of branched‐chain fatty acids from module 4 was medium or low, implying a likely bottleneck of surfactin production in BS‐37. The biosynthesis of surfactin is mainly catalyzed by NRPS, which is composed of adenylation, condensation, and thiolation domains. The biosynthesis is started with the condensation of fatty acids and Glu (And & Marahiel, 2005). Both l‐ and dLeu are found in the peptide chain of surfactin. The SrfAA and SrfAB proteins have the “E” function, meaning the epimerization of l‐ to dLeu. We supposed that the adenylation (A) domains present in SrfAA, SrfAB, and SrfAC for the activation of Leu are highly specific for l‐Leu, while dLeu, a structural analogue of l‐Leu, can influence the surfactin synthesis activity through competitive inhibition of the adenylation (A) domains of the Leu module. This may explain why l‐Leu supplementation can improve the production of surfactin by providing substrate molecules, while dLeu sharply decreased it through competitive inhibition. Notably, the competitive inhibition effects of dLeu could be relieved by l‐Leu supplementation (Figure 3d). Furthermore, many studies on replacing the promoter of the srfAoperon to abrogate the effect of quorum sensing on the synthesis of surfactin have been reported (Jiao et al., 2017; Sun et al., 2009; Willenbacher et al., 2016). Unfortunately, the results of these attempts were far from satisfactory and did not lead to high surfactin yields, indicating that a complex regulatory network controls srfA expression, so that modifying the srfA operon is not a good choice (Jung et al., 2012). In module 5, the srfA operon (srfAA, srfAB, srfAC, srfAD) was expressed at a very high level in BS‐37, implying that the native surfactin synthase (SrfA) promoter of BS‐37 is a strong promoter (Guan et al., 2015).

CONCLUSIONS

Transcriptional profiling of B. velezensis BS‐37 grown in glycerol medium showed that the expression levels (RPKM) of genes related to surfactin synthesis, encompassing the modular surfactin synthase, glycerol utilization pathway, and branched‐chain amino acid (BCAA) synthesis pathway, were all at relatively high levels. Furthermore, adding d‐/l‐Leu to the cultures did not affect the expression of genes associated with these pathways and the competitive inhibition effects of dLeu could be relieved by l‐Leu supplementation, implying that l‐Leu improved surfactin production by acting solely as a precursor or substrate, while dLeu decreased the yield by acting as a competitive inhibitor. The high transcription levels of genes encoding modular surfactin synthase, the glycerol utilization pathway, and branched‐chain amino acid (BCAA) synthesis pathways can provide great support for the establishment of a B. velezensis cell factory for the production of surfactin with high yield and at low cost.

CONFLICT OF INTEREST

None declared.

AUTHORS CONTRIBUTION

Dayuan Zhou performed the experiments and edited the primary version of the manuscript. Fangxiang Hu performed the experiments and edited the final version of the manuscript. Shuang Li was the project manager and internal reviewer. Dayuan Zhou and Fangxiang Hu contributed equally.

ETHICS STATEMENT

None required.
  25 in total

1.  Identification of lipopeptide isoforms by MALDI-TOF-MS/MS based on the simultaneous purification of iturin, fengycin, and surfactin by RP-HPLC.

Authors:  Huan Yang; Xu Li; Xue Li; Huimin Yu; Zhongyao Shen
Journal:  Anal Bioanal Chem       Date:  2015-02-10       Impact factor: 4.142

Review 2.  Microbial production of surfactants and their commercial potential.

Authors:  J D Desai; I M Banat
Journal:  Microbiol Mol Biol Rev       Date:  1997-03       Impact factor: 11.056

3.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2012-03-04       Impact factor: 28.547

4.  Effects of different amino acids in culture media on surfactin variants produced by Bacillus subtilis TD7.

Authors:  Jin-Feng Liu; Juan Yang; Shi-Zhong Yang; Ru-Qiang Ye; Bo-Zhong Mu
Journal:  Appl Biochem Biotechnol       Date:  2012-03-14       Impact factor: 2.926

5.  Production of Bacillus amyloliquefaciens OG and its metabolites in renewable media: valorisation for biodiesel production and p-xylene decontamination.

Authors:  Augusto Etchegaray; François Coutte; Gabrielle Chataigné; Max Béchet; Ramon H Z Dos Santos; Valérie Leclère; Philippe Jacques
Journal:  Can J Microbiol       Date:  2016-09-02       Impact factor: 2.419

Review 6.  Iso- and anteiso-fatty acids in bacteria: biosynthesis, function, and taxonomic significance.

Authors:  T Kaneda
Journal:  Microbiol Rev       Date:  1991-06

7.  Modeling leucine's metabolic pathway and knockout prediction improving the production of surfactin, a biosurfactant from Bacillus subtilis.

Authors:  François Coutte; Joachim Niehren; Debarun Dhali; Mathias John; Cristian Versari; Philippe Jacques
Journal:  Biotechnol J       Date:  2015-08       Impact factor: 4.677

8.  Enhancement of surfactin production of Bacillus subtilis fmbR by replacement of the native promoter with the Pspac promoter.

Authors:  Huigang Sun; Xiaomei Bie; Fengxia Lu; Yaping Lu; Yundailai Wu; Zhaoxin Lu
Journal:  Can J Microbiol       Date:  2009-08       Impact factor: 2.419

Review 9.  Anaerobic fermentation of glycerol: a platform for renewable fuels and chemicals.

Authors:  James M Clomburg; Ramon Gonzalez
Journal:  Trends Biotechnol       Date:  2012-11-21       Impact factor: 19.536

10.  High-throughput optimization of medium components and culture conditions for the efficient production of a lipopeptide pseudofactin by Pseudomonas fluorescens BD5.

Authors:  Piotr Biniarz; François Coutte; Frédérique Gancel; Marcin Łukaszewicz
Journal:  Microb Cell Fact       Date:  2018-08-04       Impact factor: 5.328

View more
  5 in total

1.  Genome and transcriptome analysis of Bacillus velezensis BS-37, an efficient surfactin producer from glycerol, in response to d-/l-leucine.

Authors:  Dayuan Zhou; Fangxiang Hu; Junzhang Lin; Weidong Wang; Shuang Li
Journal:  Microbiologyopen       Date:  2019-02-22       Impact factor: 3.139

2.  Genetic engineering of the precursor supply pathway for the overproduction of the nC14-surfactin isoform with promising MEOR applications.

Authors:  Fangxiang Hu; Weijie Cai; Junzhang Lin; Weidong Wang; Shuang Li
Journal:  Microb Cell Fact       Date:  2021-05-08       Impact factor: 5.328

3.  Sustainable Surfactin Production by Bacillus subtilis Using Crude Glycerol from Different Wastes.

Authors:  Tomasz Janek; Eduardo J Gudiña; Xymena Połomska; Piotr Biniarz; Dominika Jama; Lígia R Rodrigues; Waldemar Rymowicz; Zbigniew Lazar
Journal:  Molecules       Date:  2021-06-08       Impact factor: 4.411

4.  Molecular Network and Culture Media Variation Reveal a Complex Metabolic Profile in Pantoea cf. eucrina D2 Associated with an Acidified Marine Sponge.

Authors:  Giovanni Andrea Vitale; Martina Sciarretta; Chiara Cassiano; Carmine Buonocore; Carmen Festa; Valerio Mazzella; Laura Núñez Pons; Maria Valeria D'Auria; Donatella de Pascale
Journal:  Int J Mol Sci       Date:  2020-08-31       Impact factor: 5.923

5.  Comparative Genome Analysis Reveals Phylogenetic Identity of Bacillus velezensis HNA3 and Genomic Insights into Its Plant Growth Promotion and Biocontrol Effects.

Authors:  Doaa S Zaid; Shuyun Cai; Chang Hu; Ziqi Li; Youguo Li
Journal:  Microbiol Spectr       Date:  2022-02-02
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.