Open Access

Comparative genomic and transcriptomic analysis revealed genetic characteristics related to solvent formation and xylose utilization in Clostridium acetobutylicum EA 2018

BMC Genomics201112:93

DOI: 10.1186/1471-2164-12-93

Received: 5 August 2010

Accepted: 2 February 2011

Published: 2 February 2011

Abstract

Background

Clostridium acetobutylicum, a gram-positive and spore-forming anaerobe, is a major strain for the fermentative production of acetone, butanol and ethanol. But a previously isolated hyper-butanol producing strain C. acetobutylicum EA 2018 does not produce spores and has greater capability of solvent production, especially for butanol, than the type strain C. acetobutylicum ATCC 824.

Results

Complete genome of C. acetobutylicum EA 2018 was sequenced using Roche 454 pyrosequencing. Genomic comparison with ATCC 824 identified many variations which may contribute to the hyper-butanol producing characteristics in the EA 2018 strain, including a total of 46 deletion sites and 26 insertion sites. In addition, transcriptomic profiling of gene expression in EA 2018 relative to that of ATCC824 revealed expression-level changes of several key genes related to solvent formation. For example, spo0A and adhEII have higher expression level, and most of the acid formation related genes have lower expression level in EA 2018. Interestingly, the results also showed that the variation in CEA_G2622 (CAC2613 in ATCC 824), a putative transcriptional regulator involved in xylose utilization, might accelerate utilization of substrate xylose.

Conclusions

Comparative analysis of C. acetobutylicum hyper-butanol producing strain EA 2018 and type strain ATCC 824 at both genomic and transcriptomic levels, for the first time, provides molecular-level understanding of non-sporulation, higher solvent production and enhanced xylose utilization in the mutant EA 2018. The information could be valuable for further genetic modification of C. acetobutylicum for more effective butanol production.

Background

High oil prices, growing concerns over national security and climate change are driving investment and innovation in the renewable alternative fuels [1, 2]. Among various potentially alternatives, butanol has been proposed as an excellent substitute or supplement for gasoline, and has been demonstrated to work in some vehicles designed for use with gasoline without any engine modification [1]. In addition to manufacture from petroleum through chemical refinery process, industry production of butanol is typically through a so-called ABE fermentation process employing gram-positive, spore forming and anaerobic organism Clostridium acetobutylicum[2]. C. acetobutylicum is capable of producing a mixture of acetone (A), butanol (B) and ethanol (E) from a variety of carbohydrate substrates such as starch [3]. According to an estimate in 2008, butanol accounted for a 7-8.4 billon US dollar market worldwide and has a projected market expansion of 3% per year in the near future [4].

Significant efforts have been spent on physiological and genetic characterization of solvent-producing C. acetobutylicum in the past decades [58], and tools for genetic manipulation of C. acetobutylicum were also developed [911]. In 2001, the whole genome of well studied C. acetobutylicum ATCC 824 was sequenced, revealing a 3.94 Mb chromosome which encodes 3740 open reading frames (ORF), and a 192 Kb megaplasmid which encodes 178 ORFs [12]. Afterwards, a series of studies employing global approaches have been performed [1316], and the genome-scale metabolic model of C. acetobutylicum was also constructed [1719]. These efforts have improved the understanding of regulatory and metabolic networks of this industry significant species.

However, most of the C. acetobutylicum strains are not optimized systems for butanol production because their spore-forming life cycle decreases the efficiency of industrial fermentation, and the ABE fermentation process also creates a number of by-products, such as H2, acetic, lactic and propionic acids, acetone, isopropanol and ethanol [20]. As a result, the butanol yield is difficult to control and a significant amount of energy is wasted in these by-products. Moreover, it also increases the cost of downstream butanol purification. To address these issues, various modification approaches, such as mutagenesis by chemical or radiation agents, and genetic engineering, have been performed to improve the butanol production [10, 21]. Our laboratory has previously obtained a high butanol producing strain, C. acetobutylicum EA 2018, through butanol resistance screening of N-methyl-N-nitro-N-nitrosoguanidine (NTG) treated Clostridium strain isolated from soil [22]. Preliminary results in a 100-ton continuous fermenter showed that butanol ratio and starch conversion rates of EA 2018 strain were 10% and 5% higher than those reported in recent literature [23]. To explore the genetic difference between EA 2018 and ATCC 824, in this study, the C. acetobutylicum EA 2018 genome was sequenced using Roche 454 pyrosequencing together with traditional Sanger sequencing. In addition, comparative genomic and transcriptomic analyses of EA 2018 and ATCC 824 were also performed. The study, for the first time, provides a molecular-level understanding of higher solvent production, enhanced xylose utilization and non-sporulation in the mutant EA 2018. The information could be valuable for further genetic modification of C. acetobutylicum for more effective butanol production.

Results and Discussion

Characterization of isolate EA 2018

The original solvent producing strain was isolated by our laboratory previously [22]. After several rounds of mutagenesis using NTG (N-methyl-N'-nitro-N-nitrosoguanidine), we obtained a hyper butanol-producing strain designated as EA 2018. This strain was later identified as Clostridium acetobutylicum by the China Center for Type Culture Collection (CCTCC) and was kept in CCTCC under the preservation No. CCTCC M_94061. In this work, the 16S rDNA of C. acetobutylicum EA 2018 was cloned and sequenced. The 1399 bp 16S rDNA sequence of C. acetobutylicum EA 2018 was 100% identical to that of the type strain C. acetobutylicum ATCC 824 (Accession number NC_003030 for ATCC 824 genome sequence) [12]. Furthermore, the sol operon involved in butanol production was also cloned from C. acetobutylicum EA 2018 and sequenced, the comparative analysis showed that the sol operon of C. acetobutylicum EA 2018 was also 100% identical to that of C. acetobutylicum ATCC 824 (Accession number NC_001988 for ATCC 824 mega-plasmid sequence) [24]. The analysis demonstrated that EA 2018 and ATCC 824 belong to the same species.

Fermentation experiments were performed to compare the solvent production patterns of C. acetobutylicum EA 2018 and ATCC 824. EA 2018 exhibited higher solvent formation capacity than ATCC 824 strain in either 6% (w/v) glucose or xylose media (Figure 1A, B). After 48 h fermentation, 8.3 g/L glucose remained in the EA 2018 culture, while 16.5 g/L glucose still remained in the ATCC 824 culture after 72 h fermentation (Figure 1A). After 96 h fermentation, 23.6 g/L xylose was present in the EA 2018 culture, while 35.7 g/L xylose was still remained in the ATCC 824 culture (Figure 1B). In most C. acetobutylicum strains, solvent formation is always coupled with initiation of sporulation [10]. However, after fermentation of 72 h, there was no spore found in EA 2018 cultures, while significant spores were found in ATCC 824. With its higher solvent production and non-spore forming characteristics, EA 2018 strain could be an excellent strain for industrial application.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig1_HTML.jpg
Figure 1

Solvent and acid production, sugar utilization of C. acetobutylicum EA 2018 versus C. acetobutylicum ATCC 824 in P2 medium contained with 6% glucose (A) and 6% xylose (B).

Overview of C. acetobutylicum EA 2018 genome

For better understanding of the genetic basis of improved butanol producing characteristics in EA 2018, the whole genome of EA 2018 was sequenced. The genome has a circular chromosome consisting of 3,940,230 bp with an average G+C content of 30.93% and a circular megaplasmid of 191,996 bp with an average G+C content of 30.91%. The genome finishing procedures were listed in Additional file 1, 2, 3. A total of 3923 protein coding sequence (CDS) including 3,746 in chromosome and 176 in megaplasmid were indentified in the EA 2018 genome, representing 86.8% of the genome and 83.8% of the megaplasmid, respectively. The functional classification of all EA 2018 genes was listed in Table 1. There are 11 copies of rDNA operons and a total of 75 tRNA genes scattered over the EA 2018 genome. Genomic comparison with type strain ATCC 824 revealed the highly conserved gene content and gene order between these two strains. The base numbering start point of EA 2018 were chosen as the same site in ATCC 824 (Figure 2).
Table 1

Function Classification of EA 2018 genes

Function

Numbers in plasmid

Numbers in genome

Function

Numbers in plasmid

Numbers in genome

Energy production and conversion

12

121

Cell envelope biogenesis, outer membrane

10

182

Cell division and chromosome partitioning

3

38

Cell motility and secretion

1

92

Amino acid transport and metabolism

1

212

Posttranslational modification, protein turnover, chaperones

2

78

Nucleotide transport and metabolism

1

73

Inorganic ion transport and metabolism

6

93

Carbohydrate transport and metabolism

22

221

Secondary metabolites biosynthesis, transport and catabolism

3

27

Coenzyme metabolism

1

110

General function prediction only

16

321

Lipid metabolism

6

76

Function unknown

5

258

translation,ribosomal structure and biogenesis

0

159

Signal transduction mechanisms

4

126

transcription

22

243

Intracellular trafficking and secretion

0

14

DNA replication, recombination and repair

5

137

Defense mechanisms

5

106

   

Not in this system

55

1059

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig2_HTML.jpg
Figure 2

Atlas of the chromosome and the megaplasmid of C. acetobutylicum EA 2018 and its comparison with C. acetobutylicum ATCC 824. Moving inside, each concentric circle represents genomic data for C. acetobutylicum EA 2018 and its comparison with C. acetobutylicum ATCC 824. For chromosome atlas, the outer circle illustrates predicted coding sequences on the plus and minus strands, respectively, colored by functional categories according to COG classification. The 2nd circle represents EA 2018 variation genes compared with ATCC 824. The 3rd circle displays IS elements in EA 2018. The 4th circle shows rDNA genes in EA 2018, distinguished by plus strand (gold) and minus strand (red). The 5th circle shows tRNA genes in EA 2018, distinguished by plus strand (pink) and minus strand (blue). The 6th circle represent GC content, red for GC content above average and blue for GC content below average. The 7th circle (innermost) represents GC skew (G-C)/(G+C) calculated using a 100 kb window. For megaplasmid atlas, the outer circle illustrates predicted coding sequences on the plus and minus strands, respectively, colored by functional categories according to COG classification. 2nd circle represents EA 2018 variation genes compared with ATCC 824. 3th circle represent GC content, red for GC content above average and blue for GC content below average. The 4th circle (innermost) represents GC skew (G-C)/(G+C) calculated using a 100 kb window.

Comparative genomic analysis of EA 2018 and ATCC 824

The size of the EA 2018 chromosome is 650 bp smaller than that of ATCC 824, and the size of the EA 2018 megaplasmid is 4 bp smaller than that of ATCC 824. Compared with ATCC 824, a total of 46 deletion sites and 26 insertion sites were found across the EA 2018 genome, including 1 deletion site in the megaplasmid (Additional file 4). Among them, 55 sites are single nucleotide indel (i.e. insertion or deletion), and only 7 indel sites are larger than 100 bp. The largest insertion is 1768 bp in 1276337-1278091 which is located within a hypothetical protein gene (CEA_G1125, corresponding to CAC1113 in ATCC 824), while the largest deletion is 1812 bp in 1112030-1112031 which is located within a predicted member protein gene (CEA_G0978, corresponding to CAC0966 in ATCC 824). Apart from those indels, 440 single nucleotide variations (SNVs) were identified between the two chromosomes, and 11 SNVs were identified between the megaplasmid of EA 2018 and ATCC 824 (Additional file 5). The 523 variations (including 72 indels and 451 SNVs) affected a total of 229 protein encoding genes (including 10 genes in megaplasmid) and 38 predicted promoters (including 1 in megaplasmid) in the EA 2018 genome. Excluding the synonymous substitution, a total of 189 proteins had amino acids changes, while 47 of those proteins were with similar amino acid variations (Additional file 6). The 38 genes with their putative promoters affected were listed in Additional file 7. In Table 2 and 3, variations within putative promoters and genes related to solvent formation, xylose utilization, and spore formation (i.e. three key aspects related to enhanced butanol production in EA 2018) were listed.
Table 2

EA 2018 gene variations associated with key phenotypes

Gene locus in EA 2018

Gene locus in ATCC 824

Gene variation sites in EA 2018

Gene variation sites in ATCC 824

Protein variation sites in EA 2018

Protein variation sites in ATCC 824

Product name

Solvent formation related genes

CEA_G1048

CAC1036

899(T)

899(C)

300(V)

300(A)

Pyruvate kinase

CEA_G1755

CAC1742

391(A)

391(G)

131(N)

131(D)

phosphotransacetylase

CEA_G2463

CAC2449

256(A)

256(G)

86(S)

86(G)

Predicted flavoprotein

CEA_G2485

CAC2471

439(A)

438-439(-)

147-150(R,L,P,I)

147-150 (G,C,L,Stop codon)

Transcriptional regulator, TetR/AcrR family

CEA_G2556

CAC2543

241-249 (G,T,A,G, A,T,C,A,T)

240-241(---)

81-83(V,D,H)

80-81(---)

Electron-transferring flavoprotein large subunit

CEA_G2806

CAC2798

286(A)

286(G)

96(M)

96(V)

NADH:flavin oxidoreductase

CEA_P0058

CA_P0059

754(A)

754(C)

252(N)

252(H)

Alcohol dehydrogenase

CEA_P0077

CA_P0078

91(A)

91(G)

31(T)

31(A)

acetyl-CoA acetyltransferase

CEA_P0140

CA_P0141

566(T)

566(C)

189(I)

189(T)

Periplasmic hydrogenase small subunit, dehydrogenase

Substrate utilization related genes

CEA_G0239

CAC0234

1072(T)

1072(C)

358(Stop codon)

358(Q)

PTS system, fructoso-specific IIBC component

CEA_G1333

CAC1319

5(T)

5(C)

2(I)

2(T)

Glycerol uptake facilitator protein, GLPF

CEA_G1472

CAC1456

974(T)

974(A)

325(M)

325(K)

Sugar-binding periplasmic protein

CEA_G2622

CAC2613

270(T)

270(G)

90(C)

90(W)

Transcriptional regulators of NagC/XylR family

CEA_G2919

CAC2912

97(A)

97(C)

33(T)

33(P)

Sugar-binding periplasmic protein

CEA_P0052

CA_P0053

317(C)

317(T)

106(P)

106(L)

Xylanase, glycosyl hydrolase family 10

Sporulation related genes

CEA_G0080

CAC0080

1160(A)

1159-1160(-)

387-392(N,I,Q,D,L,Stop codon)

387-391(I,Y,K,I,Y,K)

Histidine kinase-like ATPase

CEA_G0656

CAC0644

1226(T)

1226(G)

409(V)

409(G)

Spore germination protein gerKA

CEA_G0710

CAC0699

416(C)

416(T)

139(T)

139(I)

Spore photoproduct lyase, splB

CEA_G2066

CAC2052

688(A)

687-688(-)

230-248 (18 amino acid)

230-238 (7 amino acid and a Stop Codon)

DNA-dependent RNA polymerase sigma subunit

CEA_G3736

CAC3729

374(T)

374(C)

125(L)

125(P)

Stage 0 sporulation J, ParB family of DNA-binding proteins

CEA_P0016

CA_P0017

11,245(G,A)

11,245(T,C)

4,82(E,G)

4,82(A,V)

Spore germination protein, GRKB

CEA_P0019

CA_P0020

1120(C)

1120(T)

407(A)

407(V)

Spore germination protein, GRKA

CEA_P0021

CA_P0022

-151(T)

104(C)

1(---)

1-85(85 amino acids insertion)

Spore germination protein, GRKB

Numbers in gene or protein variation sites lines indicated the variation sites in genes; the letters in bracket means the corresponding variation bases or amino acid; the symbol "-" means deletion in genes; the symbol "---" means consecutive deletion in genes; "No" means no amino acid variation; "Stop codon" means this site is mutated to stop codon.

Table 3

EA 2018 putative promoter variations related to key phenotypes

Gene locus in EA 2018

Gene locus in ATCC 824

Gene variation sites in EA 2018

Gene variation sites in ATCC 824

Product Name

Solvent formation related genes

CEA_G0028

CAC0028

-12(T)

-12(C)

Hydrogen dehydrogenase

CEA_P0034

CA_P0035

-84(T)

-84(C)

Aldehyde-alcohol dehydrogenase, ADHEII

Substrate utilization related genes

CEA_G3043

CAC3037

-80(T)

-80(C)

Catabolite control protein, LacI family transcriptional regulator

CEA_G3455

CAC3451

-84(T)

-84(G)

Sugar/Na+(H+) simporter

CEA_G1086

CAC1075

-56(T)

-56(G)

Beta-glucosidase family protein

CEA_G1365

CAC1351

-97(T)

-97(C)

Periplasmic sugar-binding protein

Sporulation related genes

CEA_G1634

CAC1620

-136(T)

-136(G)

Small acid-soluble spore protein

CEA_G3742

CAC3735

-(8-7)(-)

-7(C)

Predicted RNA-binding protein Jag, SpoIIIJ-associated

Numbers in gene or protein variation sites lines indicated the variation sites in genes; the letters in bracket means the corresponding variation bases or amino acid; the symbol "-" means deletion in genes.

Comparative transcriptomic analysis of EA 2018 and ATCC 824

To further explore the molecular mechanism of enhanced butanol production in the EA 2018 strain, DNA microarray of C. acetobutylicum were manufactured and used for a comparative analysis between EA 2018 and ATCC 824. The complete set of DNA array data was available in Additional file 8. Microarray analysis showed that a total of 2215 genes were differentially regulated at transcriptional level in at least 1 cultivation time point. Among them, differentially regulated genes related to some important metabolic pathways were listed in Table 4. And some putative promoter variation genes such as adhEII were found with differential expression level in the EA 2018 strain (Table 5). The detailed comparative analysis of transcriptomic data, along with genomic data (i.e. variation gene sequence) and biochemical phenotypes will be provided below from three key aspects related to enhanced butanol production (i.e. solvent formation, xylose utilization, and spore formation).
Table 4

List of differentially regulated genes in key functional groups.

Gene locus in EA 2018

Gene locus in ATCC 824

9 h (Log2Ratio 2018/824)

13 h (Log2Ratio 2018/824)

17 h (Log2Ratio 2018/824)

21 h (Log2Ratio 2018/824)

24 h (Log2Ratio 2018/824)

30 h (Log2Ratio 2018/824)

Product Name

Carbohydrate transportant and metabolism

     

CEA_G0343

CA_C0332

-2.97436

-3.22501

-2.37758

-2.08064

-2.57556

-1.49158

Beta-mannanase

CEA_G0501

CA_C0490

2.331505

2.410311

2.244172

2.361906

2.703307

2.474026

sugar kinase, N-terminal region - uncharacterized protein

CEA_G0552

CA_C0539

-3.20909

-3.00324

-2.93013

-2.29917

-3.34939

-3.01922

ChW repeat-containing mannanase ManB

CEA_G0553

CA_C0540

-3.097

-3.03398

-2.7227

-2.28306

-3.3665

-2.72934

ChW repeat-containing mannanase ManB

CEA_G1677

CA_C1664

1.744408

2.013214

2.53088

1.134795

1.816259

2.062687

glycogen phosphorylase

CEA_G2012

CA_C1997

3.052977

3.503142

3.004392

2.8712

2.075025

1.372718

glycosyltransferase

CEA_G2022

CA_C2007

3.179932

3.308867

2.812136

2.509044

1.656072

1.958591

glycosyltransferase

CEA_G2528

CA_C2514

2.588809

2.748177

3.625871

4.329215

2.708288

1.042021

Beta galactosidase

CEA_G2815

CA_C2807

2.40568

2.124155

2.476058

2.653992

2.808752

1.737289

endo-1,3(4)-beta-glucanase family protein 16

CEA_G2818

CA_C2810

1.835243

2.287891

2.800041

3.929157

3.739976

4.256289

glucoamylase family protein

CEA_G3051

CA_C3045

-2.41601

-2.05151

-2.19775

-2.37262

-2.3321

-2.16444

PHP family hydrolase

CEA_G3060

CA_C3054

-3.63818

-4.38617

-4.64833

-5.02922

-5.12371

-3.50751

phosphoheptose isomerase

CEA_G3426

CA_C3422

-1.07396

-2.79221

-3.22016

-2.15086

-2.69786

-1.37931

sugar:proton symporter (xylulose)

CEA_P0052

CA_P0053

2.477697

2.868013

3.649329

3.695172

3.721454

5.987476

xylanase

CEA_P0053

CA_P0054

4.25084

2.735168

2.447001

3.424303

3.598697

5.185082

xylanase/chitin deacetylase family protein

CEA_P0065

CA_P0066

3.062167

1.145145

2.159875

4.902259

3.81378

2.953822

mannose-specific phosphotransferase system component IIAB

CEA_P0066

CA_P0067

2.925021

1.579742

2.174524

4.883877

3.683632

2.826095

mannose/fructose-specific phosphotransferase system component IIC

CEA_P0067

CA_P0068

3.006142

1.74298

2.611356

4.717371

3.502957

2.456002

mannose-specific phosphotransferase system component IID

CEA_P0115

CA_P0116

1.777221

2.342324

2.902238

3.126694

3.321994

5.378643

xylanase

Amino acid transport and metabolism

     

CEA_G0180

CA_C0176

2.56498

2.063235

2.36635

2.08086

3.251555

3.705152

oligopeptide-binding protein, periplasmic component

CEA_G0327

CA_C0316

-4.09229

6.429377

7.957548

6.881528

4.185199

2.037144

ornithine carbomoyltransferase

CEA_G0390

CA_C0380

-4.23921

5.06975

5.365591

5.142555

3.394778

2.099342

periplasmic amino acid-binding protein

CEA_G0984

CA_C0973

-4.67305

6.390879

8.78089

7.141168

3.889621

2.522783

argininosuccinate synthase

CEA_G0985

CA_C0974

-4.03279

6.033303

8.738086

7.66813

4.662246

3.462605

argininosuccinate lyase

CEA_G2392

CA_C2377

-4.81354

-4.50847

-4.89131

-5.25303

-5.6598

-6.94396

oligopeptide ABC-type transporter, periplasmic binding component (frameshift)

CEA_G2403

CA_C2388

-3.653

6.58659

9.490741

7.214547

3.839977

1.277684

acetylornithine aminotransferase

CEA_G2405

CA_C2390

-4.029

7.044851

9.332151

8.593887

5.225523

1.729156

N-acetyl-gamma-glutamyl-phosphate reductase

CEA_G2406

CA_C2391

-3.63924

6.659273

9.430206

8.041522

4.889782

1.658329

bifunctional ornithine acetyltransferase/N-acetylglutamate synthase protein

CEA_G2531

CA_C2517

2.601974

2.875402

3.244092

4.199853

5.407919

5.659197

extracellular neutral metalloprotease, NPRE

CEA_G3059

CA_C3053

-3.80847

-4.46351

-4.85998

-5.20027

-5.64176

-4.16398

histidinol phosphatase related enzyme

CEA_G3625

CA_C3618

-2.33371

4.975742

4.579403

4.356899

3.79613

1.400104

ABC-type polar amino acid transport system, ATPase component

CEA_G3626

CA_C3619

-2.49499

4.94909

4.797836

4.831871

4.227636

1.349231

amino acid ABC transporter permease

CEA_G3627

CA_C3620

-2.79225

4.869307

2.77014

4.039679

3.923914

1.658129

amino acid ABC transporter periplasmic-binding protein

CEA_G3629

CA_C3622

3.744723

1.616914

-1.60643

-2.30924

-3.70552

-4.20925

benzoyl-CoA reductase/2-hydroxyglutaryl-CoA dehydratase

CEA_G3648

CA_C3641

3.877563

5.273677

6.532841

7.05381

6.150331

2.645978

oligopeptide ABC transporter, ATPase component

CEA_G3649

CA_C3642

3.862767

5.064748

6.213521

7.100308

6.123778

2.328286

oligopeptide ABC transporter, ATPase component

CEA_G3651

CA_C3644

3.540737

4.731217

4.796332

6.751584

6.151055

3.301733

oligopeptide ABC transporter, permease component

Lipid transport and metabolism

      

CEA_P0077

CA_P0078

-1.03663

-2.39938

-2.90422

-5.61457

-6.37659

-6.669

acetyl-CoA acetyltransferase

CEA_G0500

CA_C0489

2.843362

2.727643

3.104514

2.258672

2.789674

2.994569

4'-phosphopantetheinyl transferase

CEA_G2024

CA_C2009

3.02793

3.412819

2.753976

2.880761

2.465438

1.317947

3-hydroxyacyl-CoA dehydrogenase

CEA_G2027

CA_C2012

3.139119

3.519089

2.760385

2.466674

1.747722

1.295802

enoyl-CoA hydratase

CEA_G2023

CA_C2008

3.21547

3.393795

2.65468

2.624962

1.849978

1.696553

3-oxoacyl-(acyl-carrier-protein) synthase

CEA_G0825

CA_C0814

3.447389

2.690101

3.341654

3.492821

2.738719

2.617536

3-oxoacyl-

CEA_G3630

CA_C3623

3.78405

1.698615

-1.62094

-2.13197

-3.66189

-4.47732

2-hydroxyglutaryl-CoA dehydratase activator

Coenzyme transport and metabolism

      

CEA_G2539

CA_C2526

-5.80423

-4.29934

-2.18936

-3.20732

-2.04208

-2.09088

6-pyruvoyl-tetrahydropterin synthase related protein

CEA_G0110

CA_C0109

-1.93293

-1.10289

-4.51818

-4.22606

-3.40598

-5.95312

sulfate adenylyltransferase subunit 2

CEA_G2240

CA_C2226

1.175604

1.630568

1.933437

3.44313

4.132037

3.011011

branched-chain amino acid aminotransferase

CEA_G2817

CA_C2809

1.909506

2.362089

1.59545

3.297164

2.183049

1.029092

HD superfamily hydrolase

CEA_G2037

CA_C2022

2.45013

1.945668

2.521958

2.427533

2.187431

3.238565

molybdopterin biosynthesis protein MoaB

CEA_G3633

CA_C3626

2.627562

1.339719

-1.38437

-2.32524

-3.57634

-5.06491

GTP cyclohydrolase I

CEA_G2036

CA_C2021

2.849463

2.144804

2.666979

4.297463

3.319713

3.863173

molybdopterin biosynthesis protein MoeA

CEA_G2009

CA_C1994

3.136184

3.75827

3.408469

2.84809

1.881193

1.268359

molybdopterin biosynthesis protein MoaB

CEA_G2035

CA_C2020

3.146626

3.515592

5.182665

4.677354

4.692789

4.012931

molybdopterin biosynthesis protein MoeA

CEA_G3631

CA_C3624

3.416604

1.490697

-1.38827

-2.23319

-3.83641

-6.15768

6-pyruvoyl-tetrahydropterin synthase

Signal transduction

       

CEA_G0078

CA_C0078

-4.99228

-8.71284

-9.43594

-9.21854

-9.14927

-7.97564

putative accessory gene regulator protein

CEA_G3328

CA_C3325

-1.00804

-2.85267

-4.3502

-5.19446

-4.39209

-5.05262

periplasmic amino acid binding protein

CEA_G0921

CA_C0909

-2.84748

-1.88833

-1.93256

-1.50557

-2.64087

-2.89144

methyl-accepting chemotaxis protein

CEA_G2085

CA_C2071

2.455498

2.263411

2.413649

1.803983

2.20351

2.550339

Spo0A protein

CEA_G2422

CA_C2407

3.784844

1.475039

1.927948

1.823945

2.526403

2.502499

CheY-like domain-containing protein

CEA_G0448

CA_C0437

2.192653

1.378372

2.665966

1.827148

2.252286

2.342264

sensory transduction histidine kinase

CEA_G3025

CA_C3019

-2.65448

3.491201

3.449102

2.735229

1.336433

1.266833

sensory transduction protein

CEA_G0296

CA_C0289

1.792323

1.978035

2.438903

2.751395

3.435751

3.052853

response regulator

CEA_G2782

CA_C2774

1.625932

1.895382

3.060796

2.846554

2.092881

1.726376

methyl-accepting chemotaxis protein

CEA_G0334

CA_C0323

3.362504

2.662176

2.652177

3.222052

4.952742

2.037345

sensory transduction histidine kinase

CEA_G3627

CA_C3620

-2.79225

4.869307

2.77014

4.039679

3.923914

1.658129

amino acid ABC transporter periplasmic-binding protein

CEA_G0390

CA_C0380

-4.23921

5.06975

5.365591

5.142555

3.394778

2.099342

periplasmic amino acid-binding protein

Energy production and convertion

      

CEA_G1083

CA_C1072

3.271648

3.230747

4.254617

2.59071

2.723209

3.766376

Fe-S oxidoreductase

CEA_G2012

CA_C1997

3.052977

3.503142

3.004392

2.8712

2.075025

1.372718

glycosyltransferase

CEA_G2015

CA_C2000

2.963078

3.638083

2.745804

2.983214

2.587284

2.204476

indolepyruvate oxidoreductase subunit beta

CEA_G2016

CA_C2001

2.832561

3.688549

3.007107

3.355002

2.718563

2.206461

indolepyruvate ferredoxin oxidoreductase, subunit

CEA_G2022

CA_C2007

3.179932

3.308867

2.812136

2.509044

1.656072

1.958591

glycosyltransferase

CEA_G2025

CA_C2010

3.282342

3.533526

2.84142

3.003615

2.50221

2.005231

Fe-S oxidoreductase

CEA_G2555

CA_C2542

8.22595

5.876659

5.423124

5.135223

4.224852

4.280766

FAD/FMN-containing dehydrogenase

CEA_G2556

CA_C2543

8.451735

6.100494

5.401602

5.24343

4.426238

3.987954

electron-transferring flavoprotein large subunit

CEA_G2557

CA_C2544

7.904188

6.040402

4.848558

4.578106

4.214698

3.969443

electron-transferring flavoprotein small subunit

CEA_G3411

CA_C3408

-2.71993

-3.64684

-4.53359

-4.7967

-4.89809

-4.45863

NADH oxidase

Cell mobility

        

CEA_G0921

CA_C0909

-2.84748

-1.88833

-1.93256

-1.50557

-2.64087

-2.89144

methyl-accepting chemotaxis protein

CEA_G3572

CA_C3565

1.783589

1.966743

1.626123

1.303128

1.522492

1.56009

cell adhesion domain-containing protein

CEA_G3091

CA_C3085

1.669031

1.879947

1.641572

3.329325

2.811493

2.558158

TPR repeat-containing cell adhesion protein

CEA_G3092

CA_C3086

1.689695

1.7646

1.823344

3.167841

2.629106

2.423856

cell adhesion domain-containing protein

CEA_G2782

CA_C2774

1.625932

1.895382

3.060796

2.846554

2.092881

1.726376

methyl-accepting chemotaxis protein

CEA_P0159

CA_P0160

2.878477

3.739495

3.515178

3.50976

3.19802

3.547315

cell-adhesion domain-containing protein

Table 5

DNA and transcriptional variations of putative promoter variations between EA 2018 and ATCC 824

Gene locus in EA 2018

Gene locus in ATCC 824

Gene varition site in 2018

Gene varition site in 824

9 h (Log2Ratio 2018/824)

13 h (Log2Ratio 2018/824)

17 h (Log2Ratio 2018/824)

21 h (Log2Ratio 2018/824)

24 h (Log2Ratio 2018/824)

30 h (Log2Ratio 2018/824)

Product Name

CEA_G0334

CA_C0323

-96(A)

-(97-96)(-)

3.362504

2.662176

2.652177

3.222052

4.952742

2.037345

Sensory transduction histidine kinase

CEA_G0390

CA_C0380

-135,-131(A,A)

-135,-131(T,T)

-4.23921

5.06975

5.365591

5.142555

3.394778

2.099342

Periplasmic amino acid-binding protein

CEA_G2504

CA_C2490

-(13-12),-53(-,T)

-12,-(54-53)(C,-)

-2.39555

-3.35613

-3.80832

-2.2032

-2.7562

-1.10185

Xre family DNA-binding domain and TPR repeats containing protein

CEA_G3701

CA_C3694

-43(T)

-43(C)

4.045439

3.430925

3.859781

3.69948

4.131629

3.75554

TPR-repeat-containing protein

CEA_P0034

CA_P0035

-84(T)

-84(C)

3.331902

5.740285

6.007483

8.056546

6.576379

7.664691

Aldehyde-alcohol dehydrogenase, AdhEII

Changes in expression of adhEII, spo0A and hydrogenase gene may contribute to enhanced solvent formation in EA 2018

Comparative genomic analysis identified a set of solvent-relevant genes with variations within their coding sequences (Table 2). And most of which were SNV variations, such as genes encoding phosphotransacetylase and acetyl-CoA acetyltransferase. In addition, comparative genomics analysis also identified some variations up-stream of solvent-relevant genes (Table 3), which could potentially affect expression level of these genes. For example, a SNV site was found 84 bases upstream of the start codon of the AdhEII encoded gene CEA_P0034 (CA_P0035 in ATCC 824), under the s 1 transcription start point [25]. Consistent with the variations at genomic level, we also found that transcription level of solvents formation genes, such as adhEII were highly expressed in EA 2018 relative to ATCC 824(Table 5 and Figure 3).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig3_HTML.jpg
Figure 3

Expression profiles of variation genes involved in sporulation related two-component system and solvent formation pathway of C. acetobutylicum EA 2018 versus ATCC 824.

Spo0A is a central regulator of sporulation and solvent formation in C. acetobutylicum. Previous studies showed that C. acetobutylicum spo0A inactivation mutant stops producing spores and solvent, while over-expression of spo0A gene can enhance solvent production since 0A binding boxes have been identified in the promoter regions of solvent formation genes [26]. Therefore, it is speculative that the higher expression of spo0A could be one of the reasons for the higher butanol formation in EA 2018. Comparative transcriptomic analysis confirmed our speculation that higher transcriptional level of spo0A was found in EA 2018 (Table 4 and Figure 3). There were three ways for Spo0A to be phosphorylated (i.e. by a sensory kinase; through a novel phosphorylation system; by butyryl-P or acetyl-P) [27]. Using trans-membrane domain along with transcriptional analysis, four orphan kinases (CAC0437, CAC0323, CAC0903, and CAC2730) were identified as plausible kinases that might phosphorylate Spo0A in B. subtilis[27]. In our study, we also found that the transcriptional level of an orphan kinase CEA_G0344 (corresponding to CAC0323 in ATCC 824) was higher in EA 2018 (Figure 3), and the result is consistent well with the spo0A gene expression data.

During solvent fermentation process in C. acetobutylicum, a considerable amount of NADH was consumed by hydrogenase via reduced Fd (FeH2) to form hydrogen [28]. Previous reports showed that butanol production by C. acetobutylicum can be elevated by inhibiting hydrogen formation through adding viologen dyes or increasing hydrogen partial pressure [28], and knockdown of hupCBA cluster which encoded hydrogen uptake genes in C. saccharoperbutylacetonicum strain N1-4 decreased butanol formation (to 75.6% compared to the control strain) successfully [29]. Biochemical analysis showed that hydrogen formation in EA 2018 was nearly 29% lower than in ATCC 824 (Table 6). Interestingly, comparative genomic analysis also revealed SNVs in NiFe-hydrogenase coded gene CEA_P0140 (CA_P0141 in ATCC 824) and in the promoter of Fe-only hydrogenase coded gene CEA_G0028 (CAC 0028 in ATCC 824) (Table 2, 3). The variation site of CEA_G 0028 was located on the 12th base upstream of the start codon of hydA and altered the ribosome binding site (RBS) of this important gene (GGGAGG in ATCC 824 versus AGGAGG in EA 2018). In addition, the higher expression level of hydrogen uptake genes mbhs and mbhl were also revealed in EA 2018 (Figure 3). The result showed that hydrogen uptake could be an important factor for butanol formation, and increased expression level of hydrogen uptake gene mbhs and mbhl was closely correlated to the lower hydrogen formation in EA 2018, which can eventually help balance the NAD(P)H needed for higher production of butanol.
Table 6

Hydrogen production of C. acetobutylicum EA 2018 and C. acetobutylicum ATCC 824 in 6% glucose contained P2 medium

 

Fermentation

Time (h)

Glucose

consumed (mM)

Hydrogen

production (mM)

Hydrogen formation

ratio (mM/100

mM glucose)

EA 2018

72

260.6 ± 3.7

244.1 ± 1.3

93.9 ± 1.6

ATCC 824

72

239.4 ± 5.0

315.4 ± 0.5

131.7 ± 3.1

Using non-replicating plasmid pO1X, putative solvent formation repressor solR gene was inactivated in ATTC 824, and its fermentation experiment revealed that more solvent were produced in the solR inactivation mutant [5]. Although there are different speculations on the function of SolR [25], it has been confirmed that low expression of solR will enhance solvent formation [26]. Transcriptomic analysis revealed a lower expression level of solR, especially in the solventogenic phase in EA 2018, which might be related to hyper-butanol formation (Figure 3).

It has been suggested that the onset of solvent production is closely related to the accumulation of acid end products [30], and the addition of acetate and butyrate might result in a rapid induction of solventogenesis [31]. For example, it was reported that the concentration of undissociated butyric acid might play an important role in the induction of solventogenesis [32]. Transcriptomic analysis showed that expression of ack, pta, buk and ptb were all lower in EA 2018 than in ATCC 824 (Figure 3), consistent with the biochemical analysis (Figure 1). In addition, the results also suggested that the transition to the solventogenesis took place at a lower acetate and butyrate acid concentration in EA 2018 compared to ATCC 824.

Analysis of substrate utilization genes and inactivation of CAC2613 revealed genetic bases of better xylose utilization in EA 2018

Solvent production from agriculturally based lignocellulosic substrates (i.e. cellulose or hemicellulose) was studied previously and results showed that a large part of the lignocellulosic substrates were hydrolyzed into glucose and xylose [33]. Therefore, utilization of these substrates, especially xylose, can be important in determining the efficiency of solvent production. Comparative genomic analysis identified several mutations in the putative promoters and within the coding region of genes which might be involved in substrates utilization (Table 2, 3). Among them, three out of seven mutated genes encode sugar-binding periplasmic proteins. One interesting gene was CEA_G2622 (CAC2613 in ATCC 824), which encodes a transcriptional regulator of NagC/XylR family and the sequence variation could cause a putative W90C substitution. The gene is located on the upstream of xylB (xylulose kinase) gene (Figure 4A). Since most of the known xylR genes in other AT-rich gram-positive species such as B. subtillus and C. difficile were located upstream of xyl operon [34, 35], we speculated that this gene (CEA_G2622) may function similarly as xylR in EA 2018 (Figure 4B). Transcriptomic analysis showed that even in the glucose-based medium, the expression level of xylB was higher in EA 2018 (Figure 3). However, evidence is still needed to confirm the direct regulatory function of CEA_G2622 on xyl operon. To do so, we disrupted CAC2613 gene in C. acetobutylicum ATCC 824 (corresponding to CEA_G2622 in EA 2018) using Targetron system (Figure 4C). Batch fermentation showed that xylose utilization in CAC2613 disrupted mutant was faster than ATCC 824 (constant pH 5.0). In addition, the time of butanol formation and acids reassimilation in the mutant were 24 h earlier than ATCC 824 strain, although the final concentration of end products and xylose were nearly the same (Figure 4D). The similarities, in terms of the time of butanol formation and acid reassimilation, between EA 2018 and the CAC2613 disrupted ATCC 824 derived mutant, suggested that better xylose utilization in EA 2018 could be related to the mutation in CEA_G2622 (CAC2613 in ATCC 824).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig4_HTML.jpg
Figure 4

Inactivation of putative xylR CAC2613 in ATCC 824 leaded to faster xylose utilization in C. acetobutylicum. A: location of CAC2613 in C. acetobutylicum and xylR in different organisms; B: Alignment of CAC2613 and xylR in different organisms; C: CAC2613 inactivation in ATCC 824 using Targetron system; D: Accurate pH-controlled fermentation profile of mutant strain versus wild type in 6% xylose contained P2 medium.

Previous study showed that ATCC 824 harbors extracellular and cell bound xylanase activities when grown under xylose or glucose-based media, and most of the putative xylanase encoded genes were located on the megaplasmid [36]. Two endoxylanase genes, thermostable xylanase 10A gene (CA_P0053 in ATCC 824 and CEA_P0052 in EA 2018) and xylanase 10B gene (CA_P0116 in ATCC 824 and CEA_P0115 in EA 2018) located on mega-plasmid were identified in EA 2018 [37]. In addition, transcriptomic analysis showed higher expression level of those two genes in EA 2018 (Figure 5). Xylan is the major component of hemicelluloses. The higher expression level of xylanase in EA 2018 could make it suitable for hemicellulosic fermentation, and could offer potential economic benefits in the future [1].
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig5_HTML.jpg
Figure 5

Expression profiles of substrate utilization related genes. Gene functions were shown below the expression profile. Red and green indicated higher or lower expression, respectively.

Among all putative promoter variations, there were 4 sites which may affect substrate utilization in EA 2018 (Table 3). Among them, CEA_G3043 (CAC3037 in ATCC 824) gene that encodes a catabolite control protein (CcpA) has a variation site located on 80 bp upstream of the start codon. CcpA play an important role in catabolite repression and inactivation of this gene will release catabolic repression in many gram-positive organisms [8, 38, 39]. However, no significant regulation was observed for the expression level of CcpA gene in EA 2018, and the potential effect of the variation in ccpA promoter region still needs further investigation.

agrC and sigma factor variations may involve in spore formation in EA 2018

Comparative genomic analysis identified several genes which may be accounted for difference in terms of spore formation (Table 2). Among these muted genes, CEA_G2066 (CAC2052 in ATCC 824) encodes a putative sigma factor. It has been known that the transcription of this gene was closely related to spore-formation in ATCC 824 [40]. CEA_G2066 has a single nucleotide (A) insertion site in 687-688th bases, which altered the C-terminal protein sequence. Transcriptomic analysis showed that the transcription level of CEA_G2066 and other 4 putative sporulation related sigma factors [40] was lower in EA 2018 at 21 h, 24 h and 30 h (Figure 6), which might contribute to non-sporulation property in EA 2018.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-93/MediaObjects/12864_2010_Article_3221_Fig6_HTML.jpg
Figure 6

Expression profiles of sporulation related genes. Gene functions were shown below the expression profile. Red and green indicated higher or lower expression, respectively.

Quarum sensing is related to some important characteristics of bacteria, such as sporulation, virulence, and biofilm formation [41]. In C. perfringens, the virulence gene was regulated by agr system, and agrBD knockout mutant did not express theta-toxin gene, and transcription of the alpha- and kappa-toxin genes was also significantly decreased in the mutant strain [42]. A two-component system gene, CEA_G0080 (CAC0080 in ATCC 824), encoding a histidine kinase-like ATPase (AgrC), has a single nucleotide (A) insertion site in 1159-1160th bases when compared with agrC gene in ATCC 824, which may truncate the protein encoding sequence. In addition, the expression level of agrB (CEA_G0078) was constantly lower in EA 2018 (Figure 3). Early studies suggested that deletion of any agr system genes could result in no spore formation in ATCC 824 [43]. Therefore, mutation in agrC gene and lower expression of agrB gene in EA 2018 might be responsible for to the non-sporulation property in EA 2018.

Conclusion

A hyper-butanol, non spore-forming C. acetobutylicum EA 2018 strain we isolated previously can produce 10% more butanol than the type strain C. acetobutylicum ATCC 824 [23]. To seek molecular basis of these characteristics in EA 2018 strain, we completed the genome sequencing of this strain using 454 GS FLX pyrosequceing and performed a detailed genomic comparison with a C. acetobutylicum type strain ATCC 824. Although EA 2018 was found more than 99.8% identical to ATCC 824, 72 indels (i.e. insertions and deletions) and 451 SNVs were identified, some of which may be related to the enhanced butanol production in EA 2018. In addition, we performed a comparative transcriptomic analysis of C. acetobutylicum EA 2018 and ATCC 824 using oligonucleotide microarrays. The results showed that increased expression of several key genes related to solvent formation, and decreased expression of the acid formation related genes may be related to the enhanced butanol production in EA 2018. Furthermore, the results also showed that the variation in CEA_G2622 (CAC2613 in ATCC 824), a putative transcriptional regulator involved in xylose utilization, may be able to accelerate utilization of substarte xylose. The comparisons of hyper-butanol EA 2018 and type strain ATCC 824 at both genomic and transcriptomic levels not only improved our understanding of the hyper butanol-producing, xylose utilization as well as non-spore formation properties in EA 2018 strain, but also provided some useful clues for the future genetic modification of C. acetobutylicum to produce solvents, especially butanol more effectively.

Methods

Bacteria strain and genome sequencing

C. acetobutylicum EA 2018 (CCTCC M 94061) used for this study [22] is deposited in China Center for Type Culture Collection (http://www.cctcc.org/). C. acetobutylicum ATCC 824 was the wild type strain we purchased from American Type Culture Collection (ATCC) [23]. The C. acetobutylicum EA 2018 was grown anaerobically (Thermo Electron Crop., San Jose, USA). Colonies picked from Clostridia growth medium (CGM) plate were inoculated into 5 ml liquid CGM and cultured at 37°C overnight [44], and then the cells were transferred into 100 ml CGM and incubated at 37°C for 16-20 h until they reach late-exponential phase. Cells collected were used for chromosomal DNA isolation as described previously [45]. Roche 454 GS FLX pyrosequencing was used to sequence the DNA. A total of 60.3 Megabases was generated, with an average read length of 200 bp. The GS FLX reads were assembled into a total of 198 contigs using a GS de novo assembler, among them, 157 contigs are larger than 500 bp. The gaps were closed by PCR procedure using the ATCC 824 genome sequence as reference. The large PCR products were sequenced via primer walking. The whole sequence was assembled by using the software phredPhrap (http://www.phrap.org) and was visualized by Consed [46]. The low-quality sequences were verified by PCR resequencing using ABI 3730 (Applied Biosystem Inc.). The sequence accuracy of the final genome was 99.9919%. All the variation between EA 2018 and ATCC 824 were verified by PCR resequencing using ABI 3730.

Genome annotation and bioinformatic analysis

CDSs were identified by combining the results of ZCURVE 1.0 [47] and Glimmer 3.2 (http://www.cbcb.umd.edu/software/glimmer). Transfer RNA genes were predicted by tRNAscan-SE [48]. Functional annotation of CDSs was performed through comparison with NCBI non-redundant protein database using BLASTP, followed by manual curation. Comparative genomic analysis was performed by using the Artemis Comparison Tool (ACT; http://www.sanger.ac.uk/resources/software/act/). The atlas of the genome is drawn by using GenomeViz1.1 [49].

Nucleotide sequence accession number

The annotated genome sequence has been deposited into GenBank under accession no. CP002118 (Chromosome) and no. CP002119 (Plasmid).

Oligonucleotide microarray experiments

Cells for RNA isolation were grown on P2 medium and collected at 9 h, 13 h, 17 h, 21 h, 24 h and 30 h by centrifugation at 4°C and 4500 × g for 10 min. Total RNA was extracted and purified by using Trizol (Invitrogen, Carlsbad, CA, USA) and RNeasy cleanup kit (Qiagen, Inc., Valencia, CA, USA) according to the manufacturer's protocol. The total RNA yield was quantified by spectrophotometric analysis (NanoDrop Technology, Cambridge, UK) and the quality was verified by gel electrophoresis. Agilent oligonucleotide microarrays technology was used for monochromic analysis, in which probes (size: 60 bp; three replicates for each ORF) from the two groups were labeled by incorporation of cyanine 3 (Cy3) (Agilent Technologies, Palo Alto, CA, USA). The experiment procedures and data normalization were performed using the methods described previously [50]. Average linkage hierarchical clustering was performed using Cluster 3.0, and gene clusters were visualized in Treeview [51].

Oligonucleotide microarray accession number

The Oligonucleotide microarray data has been deposited into GEO under accession no. GSE23071.

Gene disruption

Gene disruption in C. acetobutylicum ATCC 824 was performed as described previously [11]. The disruption procedures were shown in Additional file 9. The selected site for CAC2613 disruption was 532/533a, where the group II intron will insert into gene CAC2613 coding region between amino acid 532 and 533 sites in the antisense direction. The primers (CAC2613-532-533-IBS, CAC2613-532-533-EBS1d and CAC2613-532-533-EBS2), for retargeting the RNA portion of the intron for C. acetobutylicum CAC2613 gene disruption, are listed in Additional file 10. The 350 bp targetron fragment was obtained by PCR based on the plasmid pACD4K-C and protocol provided by the TargeTron™ Gene Knockout System Kit (Sigma-Aldrich, St Louis, MO, USA). The 350 bp PCR fragment was digested with Xho I and Bsr GI, and then inserted into pSY6 [11] digested with the same restriction enzymes, to generate the plasmid pSY6-2613. The plasmid pSY6-2613 was methylated in E. coli ER2275 (pANS1) first [52], and then electroporated into C. acetobutylicum ATCC 824. Cells were plated on CGM agar containing 50 μg/mL erythromycin and incubated at 37°C for about 2-3 days. The positive transformants containing the inserted intron were identified by colony PCR, using primers CAC2613-ID-fw and CAC2613-ID-rev (Additional file 10).

Fermentation conditions

Solvent production and sugar utilization of C. acetobutylicum ATCC 824 and C. acetobutylicum EA 2018 were determined when the cultures were grown on P2 medium [53]. 6% Glucose or xylose contained P2 solution I (840 ml) and KH2PO4 (0.5 g/L), K2HPO4 (0.5 g/L), CH3COONH4 (2.2 g/L) contained P2 solution II (100 ml) were boiled for 20 min, then cooled by flushing O2-free N2 gas, and autoclaved at 121°C for 15 min separately. After autoclaving, 100 ml P2 solution II, 10 ml filter-sterilized P2 medium stock solution III (MgSO4·7H2O, 20 g/L; MnSO4·H2O, 1 g/L; FeSO4·7H2O, 1 g/L; NaCl, 1 g/L) and 1 ml solution IV (Para-amino-benzoicacid, 0.1 g/L; thiamin, 0.1 g/L; biotin, 0.001 g/L) were added into P2 solution I. The stock solutions were filter sterilized through a 0.2 μm pore-size filter. An inoculum of 5% from a CGM grown culture was typically used. Batch fermentation was carried out in 250 ml sealed bottle with 100 ml medium. 1 ml samples were taken every 12 h and analyzed for solvent and sugar. Accurate pH-controlled fermentations were carried out in BioFlo 110 bioreactors with 1.5 L working volume (New Brunswick Scientific, Edison, NJ). The pH control was achieved by using 9% (w/v) aqueous ammonia. Anaerobic conditions of fermentors were maintained through aeration of filtered nitrogen.

Analytical methods

The surface morphology of C. acetobutylicum EA 2018 was studied using a JSM-6360 scanning electron microscope (JEOL Co. Ltd. Japan). Spore formation analysis was performed by growing the cells in P2 medium. After 48 h fermentation, cells were collected by centrifuging at 10,000 × g for 5 min, and stained with crystal violet for imaging analysis using a U-CTR30-2 microscope (Olympus Optical Co. Ltd. Japan). Butanol, acetone, ethanol, acetic acid and butyric acid were determined using a gas chromatograph (7890A, Agilent, Wilmington, DE, USA) equipped with a capillary column (Alltech EC™-WAX) and a flame ionization detector. The analysis was carried out under the following conditions: oven temperature, programmed from 80 to 140°C at a rate of 25°C/min; injector temperature, 200°C; detector temperature, 200°C; nitrogen (carrier gas) flow rate, 13 ml/min; hydrogen flow rate, 20 ml/min; air flow rate, 140 ml/min. Total solvent was defined as the sum of ABE. Isobutylalcohol and isobutyric acid were used as the internal standards for ABE and acid determination, respectively. Glucose and xylose were determined using a HPLC system (Model 1200, Agilent) equipped with a sugar-pak I column (Waters) and a refractive index detector. The analysis was carried out with water as mobile phase at a rate of 0.6 ml/min, and the column temperature was set up at 70°C. The composition of the gas produced (mainly H2 and CO2) was measured using the method described previously [54].

Abbreviations

ABE: 

Acetone-Butanol-Ethanol

ATCC: 

American Type Culture Collection

CCTCC: 

China Center for Type Culture Collection

ORF: 

Open Reading Frames

NTG: 

N-methyl-N-nitro-N-nitrosoguanidine

SNVs: 

Single Nucleotide Variations

RBS: 

Ribosome Binding Site

CcpA: 

Catabolite Control Protein A

CGM: 

Clostridia Growth Medium.

Declarations

Acknowledgements

This work was supported by National Basic Research Program of China (2007CB707803, 2011CBA00806), Knowledge Innovation Program of the Chinese Academy of Sciences (KSCX2-EW-G-1, KSCX2-EW-J-12), National Natural Science Foundation of China (31070075) and Key Program of Science and Technology Commission of Shanghai Municipality (08DZ1207100).

We thank Prof. Peter Duerre for providing the manipulation methods on Clostridium acetobutylicum. We thank Jun Chen, Huiqi He, Lijun Shao, Cong Ren, Yongqiang Zhu, Qiuping Hu, Yiwei Yang and Qing Tang for their kindly help on this project.

During the review process we realized there is a concern from one of the reviewers regarding the origin of EA 2018 used in this research due to its high genome sequence similarity with ATCC 824. Although all the historical records we know about indicated that this is an independently isolated strain [23], at this moment we would like to keep the discussion regarding its origin ongoing until further evidences emerge.

Authors’ Affiliations

(1)
Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences
(2)
Research Center of Industrial Biotechnology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences
(3)
Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai
(4)
Center for Ecogenomics, Biodesign Institute, Arizona State University

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