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BMC Genomics

Open Access

Comparative genomics of Fructobacillus spp. and Leuconostoc spp. reveals niche-specific evolution of Fructobacillus spp.

  • Akihito Endo1Email author,
  • Yasuhiro Tanizawa2, 3,
  • Naoto Tanaka4,
  • Shintaro Maeno1,
  • Himanshu Kumar5,
  • Yuh Shiwa6,
  • Sanae Okada4,
  • Hirofumi Yoshikawa6, 7,
  • Leon Dicks8,
  • Junichi Nakagawa1 and
  • Masanori Arita3, 9
Contributed equally
BMC Genomics201516:1117

https://doi.org/10.1186/s12864-015-2339-x

Received: 22 August 2015

Accepted: 22 December 2015

Published: 29 December 2015

Abstract

Background

Fructobacillus spp. in fructose-rich niches belong to the family Leuconostocaceae. They were originally classified as Leuconostoc spp., but were later grouped into a novel genus, Fructobacillus, based on their phylogenetic position, morphology and specific biochemical characteristics. The unique characters, so called fructophilic characteristics, had not been reported in the group of lactic acid bacteria, suggesting unique evolution at the genome level. Here we studied four draft genome sequences of Fructobacillus spp. and compared their metabolic properties against those of Leuconostoc spp.

Results

Fructobacillus species possess significantly less protein coding sequences in their small genomes. The number of genes was significantly smaller in carbohydrate transport and metabolism. Several other metabolic pathways, including TCA cycle, ubiquinone and other terpenoid-quinone biosynthesis and phosphotransferase systems, were characterized as discriminative pathways between the two genera. The adhE gene for bifunctional acetaldehyde/alcohol dehydrogenase, and genes for subunits of the pyruvate dehydrogenase complex were absent in Fructobacillus spp. The two genera also show different levels of GC contents, which are mainly due to the different GC contents at the third codon position.

Conclusion

The present genome characteristics in Fructobacillus spp. suggest reductive evolution that took place to adapt to specific niches.

Keywords

Fructobacillus Leuconostoc Comparative genomicsFructophilic lactic acid bacteriaNiche-specific evolutionMetabolism

Background

Lactic acid bacteria (LAB) are found in a variety of environments, including dairy products, fermented food or silage, and gastrointestinal tracts of animals. Their broad habitats exhibit different stress conditions and nutrients, forcing the microbe to develop specific physiological and biochemical characteristics, such as proteolytic and lipolytic activities to obtain nutrients from milk [1], tolerance to phytoalexins in plants [2], or tolerance to bile salts to survive in the gastrointestinal tracts [3]. Fructobacillus spp. in the family Leuconostocaceae are found in fructose-rich environments such as flowers, (fermented) fruits, or bee guts, and are characterized as fructophilic lactic acid bacteria (FLAB) [46].

The genus Fructobacillus is comprised of five species: Fructobacillus fructosus (type species), F. durionis, F. ficulneus, F. pseudoficulneus and F. tropaeoli [6, 7]. Four of the five species formerly belonged to the genus Leuconostoc, but were later reclassified as members of a novel genus, Fructobacillus, based on their phylogenetic position, morphology, and biochemical characteristics [8]. Fructobacillus is distinguished from Leuconostoc by the preference for fructose over glucose as the carbon source and the need for an electron acceptor (e.g. pyruvate or oxygen) during glucose assimilation. Fructobacillus is further differentiated from Leuconostoc by the production of acetic acid instead of ethanol when glucose is metabolized. We previously compared these microorganisms with special attention to the activities of alcohol and acetaldehyde dehydrogenases; Fructobacillus lacks the bifunctional acetaldehyde/alcohol dehydrogenase gene (adhE) [9] and its enzyme activities. They are the only obligately heterofermentative LAB without adhE to date, suggesting that niche-specific evolution occurred at the genome level. Recent comparative genomic studies also revealed niche-specific evolution of several LAB, including vaginal lactobacilli and strains used as dairy starter cultures [1012].

This is the first study to compare the metabolic properties of the draft genome sequences of four Fructobacillus spp. with those of Leuconostoc spp., with a special focus on fructose-rich niches. Results obtained confirm the general trend of reductive evolution, especially metabolic simplification based on sugar availability.

Methods

Bacterial strains and DNA isolation

Fructobacillus fructosus NRIC 1058T, F. ficulneus JCM 12225T, F. pseudoficulneus DSM 15468T and F. tropaeoli F214-1T were cultured in FYP broth (l−1: 10 g D-fructose, 10 g yeast extract, 5 g polypeptone, 2 g sodium acetate, 0.5 g Tween 80, 0.2 g MgSO4 . 7H2O, 0.01 g MnSO4 . 4H2O, 0.01 g FeSO4 . 7H2O, 0.01 g NaCl; pH 6.8) at 30 °C for 24 h. Genomic DNA was isolated by the method of a combination of phenol/chloroform and glass beads as described previously [13].

Draft genome sequencing and de novo assembly

Whole-genome sequencing was conducted by Illumina Genome Analyzer II system, with insert length of about 500 bp. Total 6,060,140, 1,904,646, 2,474,758 and 13,680,640 reads with average lengths of 60 to 91 bp were obtained from F. fructosus NRIC 1058T, F. ficulneus JCM 12225T, F. pseudoficulneus DSM 15468T and F. tropaeoli F214-1T, respectively. De novo assembly using the Velvet Assembler for short reads with parameters optimized by the VelvetOptimizer (Version 1.2.10) [14] resulted in 57, 28, 15 and 101 contigs each (Length: 1,489,862, 1,552,198, 1,413,733 and 1,686,944 bp; N50: 89,458, 226,528, 283,981 and 226,443 bp). The k-mer sizes for the strains were 81, 45, 51, 63 bp each. The genome was annotated using the Microbial Genome Annotation Pipeline (MiGAP) [15] with manual verification. In the pipeline, protein coding sequences (CDSs) were predicted by MetaGeneAnnotator 1.0 [16], tRNAs were predicted by tRNAscan-SE 1.23 [17], rRNAs were predicted by RNAmmer 1.2 [18], and functional annotation was finally performed based on homology searches against the RefSeq, TrEMBL, and Clusters of Orthologous Groups (COG) protein databases.

Genomic data of Fructobacillus durionis and Leuconostoc spp.

Draft genome sequence of Fructobacillus durionis DSM 19113T was obtained from the JGI Genome Portal (http://genome.jgi.doe.gov/) [19] and annotated using MiGAP in the same way as other Fructobacillus spp. Annotated genome sequences for nine of the twelve Leuconostoc species were obtained from the GenBank or RefSeq databases at NCBI. Of Leuconostoc spp., genomic data of Leuconostoc holzapfelii, Leuconostoc miyukkimchii and Leuconostoc palmae were not available at the time of analysis (December 2014) and were not included in the present study. When multiple strains were available for a single species, the most complete one was chosen. GenBank accession numbers of the strains used are listed in Table 1.
Table 1

General genome characteristics of the strains analyzed

Strains

Genome statusa

Source

INSD/SRA accession no.

Size

No. of CDS

%G + C

GC3

Completenessc

Contaminationc

Fructobacillus fructosus NRIC 1058T

D

Flower

BBXR01000000

1.49

1437

44.6

46.4

93.62

0

Fructobacillus durionis DSM 19113T

D

Fermented fruit

JGIb

1.33

1221

44.7

47.4

94.98

0.57

Fructobacillus ficulneus JCM 12225T

D

Fig

BBXQ01000000

1.55

1397

43.9

44.6

92.79

0.48

Fructobacillus pseudoficulneus DSM 15468T

D

Fig

BBXS01000000

1.41

1312

44.5

45.9

95.14

0.48

Fructobacillus tropaeoli F214-1T

D

Flower

BBXT01000000

1.69

1572

44.2

45.7

94.98

0.24

Leuconostoc mesenteroides ATCC 8293T

C

Fermenting olives

CP000414-15

2.08

2045

37.7

30.1

100

0

Leuconostoc carnosum JB16

C

Kimchi

CP003851-55

1.77

1696

37.1

27.9

99.04

0.6

Leuconostoc citreum KM20

C

Kimchi

DQ489736-40

1.90

1849

38.9

31.3

99.52

0

Leuconostoc fallax KCTC 3537T

D

Sauerkraut

AEIZ01000000

1.64

1882

37.5

29.2

97.30

1.16

Leuconostoc gelidum JB7

C

Kimchi

CP003839

1.89

1818

36.7

27.6

99.04

0.24

Leuconostoc inhae KCTC 3774T

D

Kimchi

AEMJ01000000

2.30

2790

36.4

28.6

95.59

5.38

Leuconostoc kimchii IMSNU 11154T

C

Kimchi

CP001753-58

2.10

2097

37.9

30.1

99.52

0

Leuconostoc lactis KACC 91922

D

Kimchi

JMEA01000000

1.69

2076

43.4

41.1

99.04

0.57

Leuconostoc pseudomesenteroides 1159

D

Cheese starter

JAUI01000000

2.04

1634

39.0

32.5

99.04

0.16

aGenome status: D, draft genome sequence; C, complete genome sequence

bObtained from Integrated Microbial Genomes (IMG) database at the Department of Energy Joint Genome Institute (http://genome.jgi.doe.gov/)

cDetermined by CheckM

Quality assessment of the genomic data

The completeness and contamination of the genomic data were assessed by CheckM (Version 1.0.4) [20], which inspects the existence of gene markers specific to the Leuconostocaceae family, a superordinate taxon of Fructobacillus and Leuconostoc.

Comparative genome analysis and statistical analysis

To estimate the size of conserved genes, all protein sequences were grouped into orthologous clusters by GET_HOMOLOGUES software (version 1.3) based on the all-against-all bidirectional BLAST alignment and the MCL graph-based algorithm [21]. The conserved genes are defined as gene clusters that are present in all analyzed genomes (please note the difference from the definition of specific genes). The rarefaction curves for conserved and total genes were drawn by 100-time iterations of adding genomes one by one in a random order. From this analysis, two genomes (L. fallax and L. inhae) were excluded to avoid underestimation of the size of conserved genes, since they contained many frameshifted genes, probably due to the high error rate at homopolymer sites of Roche 454 sequencing technology.

For functional comparison of the gene contents between Fructobacillus spp. and Leuconostoc spp., CDS predicted in each strain were assigned to Cluster of Orthologous Groups (COG) functional classification using the COGNITOR software [22]. Metabolic pathway in each strain was also predicted using KEGG Automatic Annotation Server (KAAS) by assigning KEGG Orthology (KO) numbers to each predicted CDS [23]. The numbers of genes assigned to each COG functional category were summarized as a table (Table 2). In the present study, Fructobacillus-specific genes were defined as those conserved in four or more Fructobacillus spp. (out of five) and in two or less Leuconostoc spp. (out of nine). Leuconostoc-specific genes were defined as those conserved in seven or more Leuconostoc spp. and one or less Fructobacillus spp.
Table 2

Gene content profiles obtained for Fructobacillus spp. and Leuconostoc spp.

 

F. fructosus NRIC 1058T

F. durionis DSM 19113T

F. ficulneus JCM 12225T

F. pseudoficulneus DSM 15468T

F. tropaeoli F214-1T

L. mesenteroides ATCC 8293T

L. carnosum JB16

L. citreum KM20

L. fallax KCTC 3537T

L. gelidum JB7

L. inhae KCTC 3774T

L. kimchii IMSNU 11154T

L. lactis KACC 91922

L. pseudomesenteroides 1159

[C] Energy production and conversion

40

34

41

36

43

69

49

66

39

67

50

68

56

61

[D] Cell cycle control, cell division, chromosome partitioning

35

36

41

37

43

37

33

40

24

33

23

45

30

38

[E] Amino acid transport and metabolism

112

106

159

137

160

192

152

129

110

136

116

179

139

152

[F] Nucleotide transport and metabolism

64

61

77

74

73

91

88

85

71

88

78

97

82

100

[G] Carbohydrate transport and metabolism

61

61

69

63

74

168

123

155

80

172

138

156

120

162

[H] Coenzyme transport and metabolism

51

49

54

49

64

91

73

80

52

72

64

98

78

78

[I] Lipid transport and metabolism

40

43

44

43

51

62

56

71

40

71

59

64

58

57

[J] Translation, ribosomal structure and biogenesis

180

175

188

180

190

193

191

185

162

193

166

198

186

191

[K] Transcription

93

84

89

87

115

133

128

129

93

150

132

153

100

151

[L] Replication, recombination and repair

110

86

97

86

115

110

100

105

57

92

95

119

96

125

[M] Cell wall/membrane/envelope biogenesis

84

77

73

74

84

110

92

105

81

98

75

102

93

94

[N] Cell motility

10

7

6

4

11

11

12

14

7

12

5

17

13

12

[O] Posttranslational modification, protein turnover, chaperones

46

37

47

40

49

63

59

59

39

54

44

67

46

58

[P] Inorganic ion transport and metabolism

49

48

51

54

54

81

70

77

46

61

56

83

63

70

[Q] Secondary metabolites biosynthesis, transport and catabolism

10

7

12

9

12

18

10

13

10

11

12

11

15

15

[R] General function prediction only

67

55

78

67

85

99

83

87

64

89

77

103

79

95

[S] Function unknown

111

100

90

94

114

133

109

122

95

116

108

124

107

118

[T] Signal transduction mechanisms

31

27

36

29

36

60

49

55

46

48

44

60

51

58

[U] Intracellular trafficking, secretion, and vesicular transport

15

12

11

15

24

12

15

11

12

15

10

14

14

12

[V] Defense mechanisms

34

23

37

37

26

35

37

35

24

47

43

52

35

59

[X] Mobilome: prophages, transposons

44

12

26

9

33

27

21

42

18

12

51

43

38

58

The Mann–Whitney U test was applied to compare genome features and gene contents of Fructobacillus spp. and Leuconostoc spp. The p value of 0.05 was considered statistically significant. Statistical analysis was performed using IBM SPSS Statistics for Windows (Version 21.0. Armonk, NY: IBM Corp.).

Phylogenetic analysis

Orthologous clusters that were conserved among all Fructobacillus spp., all Leuconostoc spp. and Lactobacillus delbrueckii subsp. bulgaricus ATCC 11842 (as the outgroup) were determined by GET_HOMOLOGUES as described above. For phylogenetic reconstruction, 233 orthologs that appeared exactly once in each genome were selected. The amino acid sequences within each cluster were aligned using MUSCLE (version 3.8.31) [24]. Poorly-aligned or divergent regions were trimmed using Gblocks [25], and conserved regions were then concatenated using FASconCAT-G [26]. A partitioned maximum likelihood analysis was performed to construct the phylogenetic tree with RAxML (version 8.1.22) [27] using the best-fit evolutionary models predicted for each alignment by ProtTest [28]. The number of bootstrapping was 1,000 replicates.

Polysaccharides production and reaction to oxygen

Polysaccharides production from sucrose were determined by the methods as described previously [29]. Briefly, the strains were inoculated on agar medium containing sucrose as sole carbon source and incubated aerobically at 30 °C for 48 h.

To study reaction to oxygen on growth, the cells were streaked onto GYP agar [8], which contained D-glucose as the sole carbon source, and cultured under anaerobic and aerobic conditions at 30 °C for 48 h as described previously [4]. The anaerobic conditions were provided by means of a gas generating kit (AnaeroPack, Mitsubishi Gas Chemical, Japan). These studies were conducted for the type strains of five Fructobacillus species, Leuconostoc mesenteroides subsp. mesenteroides NRIC 1541T, Leuconostoc citreum NRIC 1776T and Leuconostoc fallax NRIC 0210T.

Data deposition

Annotated draft genome sequences of F. fructosus NRIC 1058T, F. ficulneus JCM 12225T, F. pseudoficulneus DSM 15468T and F. tropaeoli F214-1T were deposited to the DDBJ/EMBL/GenBank International Nucleotide Sequence Database with accession numbers BBXR01000000, BBXQ01000000, BBXS01000000 and BBXT01000000, respectively. Unassembled raw sequence data were also deposited to the database with accession number DRA004155. The phylogenetic tree and associated data matrix for Fig. 6 are available at TreeBASE (Accession URL: http://purl.org/phylo/treebase/phylows/study/TB2:S18090).

Results and discussion

General genome features of Fructobacillus spp. and Leuconostoc spp.

Draft genome sequences of four Fructobacillus spp. were determined by the Illumina Genome Analyzer II system. The sequence coverage of F. fructosus NRIC 1058T, F. ficulneus JCM 12225T, F. pseudoficulneus DSM 15468T and F. tropaeoli F214-1T were 329-, 55-, 90-, and 513-fold, respectively. Genome sequences of nine Leuconostoc spp. and Fructobacillus durionis were obtained from public databases (see Methods). The genome features of the strains used in the present study are summarized in Table 1. The genome sizes of Fructobacillus ranged from 1.33 to 1.69 Mbp (median ± SD, 1.49 ± 0.30 Mbp) and are significantly smaller than those of Leuconostoc (p < 0.001), 1.69 to 2.30 Mbp (median ± SD, 1.94 ± 0.21) (Fig. 1a). Accordingly, Fructobacillus strains contain significantly smaller numbers of CDSs than Leuconostoc strains (median ± SD, 1387 ± 132 vs 1980 ± 323, p < 0.001) (Fig. 1b). The DNA G + C contents of both species are also significantly different (p < 0.001): median ± SD is 44.4 % ± 0.30 % in Fructobacillus and 38.1 % ± 2.05 % in Leuconostoc (Fig. 1c). The difference in G + C contents is caused by the composition at the third codon (GC3): 46.0 % ± 1.02 % in Fructobacillus and 30.9 % ± 4.12 % in Leuconostoc. The low GC3 value in Leuconostoc spp. shows a good contrast with the high GC3 value in Lactobacillus delbrueckii subsp. bulgaricus [11]. In L. delbrueckii subsp. bulgaricus, the changes in GC3 are attributed to ongoing evolution [11], and similar selection pressure might be responsible here. Overall, these distinct genomic features strongly support the reclassification of Fructobacillus spp. from the genus Leuconostoc.
Fig. 1

Genome sizes (a), number of CDSs (b) and GC contents (c) in Fructobacillus spp. and Leuconostoc spp. The line in the box represents the median, with lower line in the 25 % border and the upper line the 75 % border. The end of the upper vertical line represents the maximum data value, outliers not considered. The end of the lower vertical line represents the lowest value, outliers not considered. The separate dots indicate outliers

Since most of the genomes analyzed in this study were in draft status, quality assessment of the genomes was conducted using CheckM. The average completeness values for Fructobacillus and Leuconostoc genomes were 94.3 and 98.7 %, respectively (Table 1). Except for the genome of L. inhae, which exhibited the contamination value of 5.4 %, all genomes satisfied the criteria required to be considered a near-complete genome with low contamination (≥90 % completeness value and ≤ 5 % contamination value) [20]. The lower completeness values for Fructobacillus genomes might be attributable to insufficiency of the reference gene markers used by CheckM, for which the genomic data of Fructobacillus spp. were not reflected at the time of writing this paper (December 2014), rather than the lower quality of these genomes. In addition, the lower completeness may indicate specific gene losses in the genus Fructobacillus since the closer investigation of CheckM results showed that seven gene markers were consistently absent among five Fructobacillus genomes while on average, 14.6 markers were absent out of 463 Leuconostocaceae-specific gene markers.

Conserved genes in Fructobacillus spp. and Leuconostoc spp.

The numbers of conserved genes in the nine genomes of Leuconostoc and five genomes of Fructobacillus were estimated as 1,026 and 862, respectively. They account for 52 % and 62 % of average CDS numbers of each genus (Fig. 2a). The difference in the average CDS numbers reflects their genomic history including ecological differences between the two genera. A previous study also reported 1162 conserved genes in three genomes of Leuconostoc species [30]. The smaller number and the higher ratio of fully conserved genes in Fructobacillus spp. is probably due to a less complex and consistent habitat with specific sugars only, such as fructose. It is a major carbohydrate found in habitats of Fructobacillus spp., e.g. flowers, fruits and associated insects. On the other hand, Leuconostoc spp., that are usually seen in wide variety of habitats, including gut of animals, dairy products, plant surfaces, or fermented foods and soils, possess a larger number of conserved genes. Figure 2b shows the distribution of gene clusters in two genera. The frontmost peak (721 gene clusters) represents conserved genes that are shared by both Leuconostoc and Fructobacillus spp. Genus-specific conserved genes are indicated as leftmost and right peaks in Fig. 2b. The leftmost peak (159 gene clusters) represents genes that are present in all Leuconostoc genomes, but absent in all Fructobacillus genomes, and the right peak (24 gene clusters) represents vice versa. The much smaller peak of the right compared to that of the left indicates that Fructobacillus spp. have lost more genes or have acquired less genes than Leuconostoc spp. during diversification after they separated into two groups. In addition, the number of gene clusters located near the center of the figure was small, which indicates that the exchange of genes between the two genera is not frequent and that they share distinct gene pools. This supports the validity of the classification of Fructobacillus as a distinct genus [8].
Fig. 2

Conserved genes and pan-genome of Fructobacillus and Leuconostoc. a Estimation of the numbers of conserved genes and pan-genome for Fructobacillus (blue) and Leuconostoc (orange). Solid lines represent conserved genes and dashed lines represent pan-genomes as a function of the number of genomes added. The medium of 100 random permutations of the genome order is presented. b Distribution of gene clusters present in Fructobacillus and Leuconostoc. Horizontal axes represent the numbers of genomes in each genus. Vertical axes show the numbers of gene clusters present in the given number of genomes

Comparison of gene contents between Fructobacillus spp. and Leuconostoc spp.

The identified genes were associated with COG functional categories by COGNITOR software at the NCBI. The sizes of COG-class for each strain are summarized in Table 2, and for each genus in Additional file 1: Figure S1. In addition, ratio of genes assigned in each COG category against the total number of genes in all COGs were determined for each genus and shown in Fig. 3. Fructobacillus spp. have less genes for carbohydrate transport and metabolism compared to Leuconostoc spp. (Class G in Fig. 3 and Additional file 1: Figure S1): Class G ranked 9th largest in Fructobacillus whereas it ranked 3rd in Leuconostoc. Similarly, the number of genes in Class C (energy production and conversion) was significantly less in Fructobacillus spp. than in Leuconostoc spp., suggesting that energy systems in Fructobacillus spp. are much simpler than those in Leuconostoc spp. The smaller number of CDS and conserved genes in Fructobacillus spp. could have resulted from metabolic reduction caused by scarce availability of carbohydrates other than fructose.
Fig. 3

Comparison of ratio (%) of gene content profiles obtained for the genera Fructobacillus and Leuconostoc. The Mann–Whitney U test was done to compare Fructobacillus spp. and Leuconostoc spp., and significant differences (P < 0.05) are denoted with an asterisk (*)

When compared based on the ratio of genes (Fig. 3), Class D (cell cycle, cell division and chromosome partitioning), Class J (translation, ribosomal structure and biogenesis), Class L (replication, recombination and repair) and Class U (intracellular trafficking, secretion and vesicular transport) were overrepresented in Fructobacillus spp. than in Leuconostoc spp. However, the numbers of genes classified in the four classes were comparable between the two genera (Additional file 1: Figure S1). The conservation of genes in these classes against the genome reduction may indicate that their functions are essential for re-production, and the class names roughly correspond to housekeeping mechanisms.

To understand gene contents involved in metabolic/biosynthesis pathways in more detail, ortholog assignment and pathway mapping against the KEGG Pathway Database were performed using the KAAS system. The number of mapped genes was significantly less for Fructobacillus spp. as compared to Leuconostoc spp. (Table 3). Firstly, Fructobacillus spp. lack respiration genes. Whereas oxygen is known to enhance their growth [8], the strains have lost genes for the TCA cycle, and keep only one gene for ubiquinone and other terpenoid-quinone biosynthesis (Table 3). Presumably they do not perform respiration and use oxygen only as an electron acceptor. This characteristic is not applicable to certain Leuconostoc species: L. gelidum subsp. gasicomitatum [31], formerly classified as L. gasicomitatum [32], has been reported to conduct respiration in the presence of heme and oxygen [33].
Table 3

Discriminative pathways between Fructobacillus spp. and Leuconostoc spp.

 

Fructobacillus spp.

Leuconostoc spp.

 
 

Mean (SD)a

Mean (SD)

p

Glycolysis (map00010)

12.2 (0.84)

19.5 (1.72)

0.001

TCA cycle (map00020)

0

4.2 (0.79)

 

Pentose and glucuronate interconversions (map00040)

3.2 (1.64)

7.9 (2.80)

0.008

Fructose and mannose metabolism (map00051)

2.8 (0.84)

9.4 (2.12)

0.001

Galactose metabolism (map00052)

5.8 (0.84)

11.6 (2.72)

0.003

Ubiquinone and other terpenoid-quinone biosynthesis (map00130)

1 (0)

7.6 (0.97)

0.001

Oxidative phosphorylation (map00190)

9.2 (0.45)

12.7 (1.57)

0.001

Valine, leucine and isoleucine degradation (map00280)

2 (0)

4.4 (0.84)

0.001

Starch and sucrose metabolism (map00500)

6.4 (1.52)

12.9 (2.28)

0.001

Amino sugar and nucleotide sugar metabolism (map00520)

11.2 (0.45)

19.5 (2.17)

0.001

Pyruvate metabolism (map00620)

12 (1)

19.8 (1.99)

0.001

Carbon metabolism (map01200)

30.6 (3.21)

37.4 (3.20)

0.005

ABC transporters (map02010)

33.8 (3.11)

50.6 (8.34)

0.003

Phosphotransferase system (map02060)

1 (0)

13 (3.13)

0.03

Map numbers shown in parenthesis correspond to the numbers in KEGG

aThe values indicate means and standard deviations of number of genes used for the pathways

Secondly, Fructobacillus spp. lack pentose and glucuronate interconversions (Table 3). They lost genes for pentose metabolism, unlike other obligately heterofermentative LAB that usually metabolize pentoses [34]. They do not metabolize mannose, galactose, starch, sucrose, amino sugars or nucleotide sugars, either [7, 8]. Moreover, the species possess none or at most one enzyme gene for the phosphotransferase systems (PTS), significantly less than the number of respective genes in Leuconostoc spp. (13 ± 3.13, average ± SD). This validates the observation that Leuconostoc spp. metabolize various carbohydrates whereas Fructobacillus spp. do not [8] (Fig. 4.) However, the genome-based prediction does not always coincide with observed metabolism: Fructobacillus species do not metabolize ribose [8], against its metabolic prediction (Fig. 4). The discrepancy is due to an absence of ATP-dependent ribose transporter. On the other hand, some Leuconostoc spp. have the transporter and metabolize ribose.
Fig. 4

Predicted sugar metabolic pathways in Fructobacillus spp. and Leuconostoc spp. The orange and blue lines represent the pathways exist in Leuconostoc spp. and Fructobacillus spp., respectively. The bold lines represent conserved genes among each genus (core) and the narrow lines represent dispensable genes that are exist in some but not all species in each genus. The dotted lines represent electron flow

Thirdly, Fructobacillus spp. have more genes encoding phenylalanine, tyrosine and tryptophan biosynthesis compared to Leuconostoc spp. (Table 3), although this difference is statistically not significant (p = 0.165). The difference is mainly due to presence/absence of tryptophan metabolism, and the production of indole and chorismate. This is important to wine lactobacilli [35]. The reason of the sporadic conservation of indole biosynthesis in Fructobacillus remains unknown.

Comparison of genus-specific genes

To further investigate their differences, we defined genes as Fructobacillus-specific when they are conserved in four or more Fructobacillus species (out of five) and two or less in the nine Leuconostoc species. On the other hand, genes are Leuconostoc-specific when they are possessed by seven or more Leuconostoc species (out of nine) and zero or one in the five Fructobacillus species. According to this definition, 16 genes were identified as Fructobacillus-specific and 114 as Leuconostoc-specific (Additional file 2: Table S1). These numbers are smaller than the numbers of fully conserved genes in each genus (24 for Fructobacillus and 159 for Leuconostoc), because we defined genus-specific genes after mapping them to the KEGG Orthology (KO) database; genes without any KO entry were excluded from the analysis.

Interestingly the adh gene coding alcohol dehydrogenase [EC:1.1.1.1] was characterized as Fructobacillus-specific whereas adhE gene coding bifunctional acetaldehyde/alcohol dehydrogenase [EC1.2.1.10 1.1.1.1] was characterized as Leuconostoc-specific. There was no alternative acetaldehyde dehydrogenase gene in Fructobacillus. These results are consistent with our previous study reporting the lack of adhE gene and acetaldehyde dehydrogenase activity in Fructobacillus spp. [9] and their obligately heterofermentative nature with no ethanol production [6, 8]. No production of ethanol is due to an absence of acetaldehyde dehydrogenase activity, but it conflicts with the NAD/NADH recycling. Therefore, there must be a different electron acceptor in glucose metabolism [4, 6, 9].

NAD(P)H dehydrogenase gene was found as Fructobacillus-specific (Additional file 2: Table S1). This is the only gene used for the quinone pool in Fructobacillus spp., suggesting that the gene does not contribute to respiration. Rather, it is used for oxidation of NAD(P)H under the presence of oxygen. This helps to keep the NAD(P)/NAD(P)H balance, since their sugar metabolism produces imbalance in NAD(P)/NAD(P)H cycling as described above. Indeed, Fructobacillus spp. can be easily differentiated from Leuconostoc spp. based on the reaction to oxygen [8]. In our validation study, Fructobacillus spp. grew well under aerobic conditions but poorly so under anaerobic conditions on GYP medium (Fig. 5). Presence of oxygen had smaller impacts on growth of Leuconostoc spp., but they generated larger colonies under anaerobic conditions than under aerobic conditions.
Fig. 5

Growth of L. mesenteroides NRIC 1541T and F. fructosus NRIC 1058T on GYP agar medium under aerobic and anaerobic conditions after incubation for 2 days. L. mesenteoides NRIC 1541T, a and c; F. fructosus NRIC 1058T, b and d

Genes for subunits of the pyruvate dehydrogenase complex were undetected in the genomes of Fructobacillus, but were found in Leuconostoc. Fructobacillus also lack TCA cycle genes. This suggests that, in Fructobacillus, pyruvate produced from the phosphoketolase pathway is not dispatched to the TCA cycle but metabolized to lactate by lactate dehydrogenase. The lack of pyruvate dehydrogenase complex was also reported in Lactobacillus kunkeei [35], which is also a member of FLAB found in fructose-rich environment [4, 36].

The levansucrase gene was also characterized as Fructobacillus-specific (Additional file 2: Table S1). The enzyme has been known to work for production of oligosaccharides in LAB [36, 37] and for biofilm production in other bacteria [38]. However, production of polysaccharides was unobserved in Fructobacillus spp. when cultured with sucrose. The reason for this discrepancy is yet unknown. Incompetence of sucrose metabolism, including no dextran production, in Fructobacillus spp. has been reported [7, 8], and systems to metabolize sucrose, e.g. genes for sucrose-specific PTS, sucrose phosphorylase and dextransucrase, were not detected in their genomes. On the other hand, L. citreum NRIC 1776T and L. mesenteroides NRIC 1541T produced polysaccharides, possibly dextran. Production of dextran from sucrose in the genus Leuconostoc is strain/species dependent [39], and dextransucrase gene was identified in six Leuconostoc genomes (out of nine) in this study. A number of genes coding peptidases and amino acids transport/synthesis/metabolism were also found as Leuconostoc-specific genes (Additional file 2: Table S1), suggesting that Leuconostoc spp. can survive various environments with different amino acid compositions. Several PTS related genes and genes for teichoic acid transport were also characterized as Leuconostoc-specific. LAB cells usually contain two distinct types of teichoic acid, which are wall teichoic acid and lipoteichoic acid. The identified genes are involved in biosynthesis of wall teichoic acid in Bacillus subtilis [40]. Few studies have been reported for wall teichoic acid in Leuconostoc spp. and none in Fructobacillus spp.

Phylogenetic analysis

To confirm the phylogenetic relationship between Fructobacillus spp. and Leuconostoc spp., a phylogenetic tree was produced based on concatenated sequences of 233 orthologous genes which were conserved as a single copy within the tested strains. The tree showed a clear separation of the two genera (Fig. 6), indicating that Fructobacillus spp. have distinct phylogenetic position from Leuconostoc spp. This agrees well with the previous reports using 16S rRNA gene or house-keeping genes [7, 8].
Fig. 6

Phlylogenetic tree of Fructobacillus spp. and Leuconostoc spp. based on the multiple alignments of the 233 conserved genes. The partitioned maximum-likelihood tree constructed using the best-fit evolutionary model clearly separated Fructobacillus spp. from Leuconostoc spp. The values on the branches are bootstrap support from 1000 rapid bootstrapping replicates. Lactobacillus delbrueckii subsp. bulgaricus ATCC 11842 was used as an out group

Conclusion

Genome-based analysis on conserved genes and metabolic characteristics clearly indicated the distinction between Fructobacillus spp. and Leuconostoc spp. Fructobacillus spp. possess smaller numbers of CDS in smaller genomes compared to Leuconostoc spp. This is mainly due to the absence of carbohydrate metabolic systems. Similar genomic characteristics have been reported for L. kunkeei [41], a member of FLAB found in fructose-rich environment. Since they are known as poor sugar fermenter in the group of LAB and always inhabit in fructose-rich niches, the characteristics could have resulted from an adaptation to their extreme environments. Niche-specific evolution, usually genome reduction, has been reported for dairy and vaginal LAB [1012], and the present study reconfirms such niche-specific evolution in FLAB. These findings would be valuable to know a link of diverse physiological and biochemical characteristics in LAB and environmental factors in their habitats.

Notes

Abbreviations

CDS: 

protein coding sequences

COG: 

Clusters of Orthologous Groups

FLAB: 

fructophilic lactic acid bacteria

KO: 

KEGG Orthology

LAB: 

lactic acid bacteria

Declarations

Acknowledgment

This study was supported by MEXT-Supported Program for the Strategic Research Foundation at Private Universities 2013–2017 (S1311017) and Collaborative Research Program (A1) No.50 (2015) from National Institute of Genetics (NIG). Computational analysis was performed in part on the NIG supercomputer at ROIS. The sequence data of F. durionis DSM 19113T was produced by the US Department of Energy Joint Genome Institute (http://www.jgi.doe.gov/) in collaboration with the user community.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture
(2)
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo
(3)
Center for Information Biology, National Institute of Genetics
(4)
NODAI Culture Collection Centre, Tokyo University of Agriculture
(5)
Functional Foods Forum, University of Turku
(6)
Genome Research Center, NODAI Research Institute, Tokyo University of Agriculture
(7)
Department of Bioscience, Tokyo University of Agriculture
(8)
Department of Microbiology, University of Stellenbosch
(9)
RIKEN Center for Sustainable Resource Science

References

  1. Slattery L, O'Callaghan J, Fitzgerald GF, Beresford T, Ross RP. Invited review: Lactobacillus helveticus--a thermophilic dairy starter related to gut bacteria. In: J Dairy Sci. vol. 93. American Dairy Science Association, United States: Elsevier Inc; 2010. p. 4435–54.Google Scholar
  2. Nomura M, Kobayashi M, Narita T, Kimoto-Nira H, Okamoto T. Phenotypic and molecular characterization of Lactococcus lactis from milk and plants. In: J Appl Microbiol. vol. 101. England: Wiley Online Library; 2006. p. 396–405.Google Scholar
  3. Hammes W, Hertel C. The genera Lactobacillus and Carnobacterium. In: Dworkin M, Falkow S, Rosenberg E, Schleifer K-H, editors. The Prokaryotes. US: Springer; 2006. p. 320–403.View ArticleGoogle Scholar
  4. Endo A, Futagawa-Endo Y, Dicks LM. Isolation and characterization of fructophilic lactic acid bacteria from fructose-rich niches. In: Syst Appl Microbiol. vol. 32. Germany: Elsevier; 2009. p. 593–600.Google Scholar
  5. Endo A, Salminen S. Honeybees and beehives are rich sources for fructophilic lactic acid bacteria. Syst Appl Microbiol. 2013;36(6):444–8.PubMedView ArticleGoogle Scholar
  6. Endo A, Dicks LMT. The genus Fructobacillus. In: Holzapfel W, Wood B, editors. Lactic Acid Bacteria; Biodiversity and Taxonomy. UK: Wiley Blackwell; 2014. p. 381–90.View ArticleGoogle Scholar
  7. Endo A, Irisawa T, Futagawa-Endo Y, Sonomoto K, Itoh K, Takano K, et al. Fructobacillus tropaeoli sp. nov., a fructophilic lactic acid bacterium isolated from a flower. In: Int J Syst Evol Microbiol. vol. 61. England: Microbiology Society; 2011. p. 898–902.Google Scholar
  8. Endo A, Okada S. Reclassification of the genus Leuconostoc and proposals of Fructobacillus fructosus gen. nov., comb. nov., Fructobacillus durionis comb. nov., Fructobacillus ficulneus comb. nov. and Fructobacillus pseudoficulneus comb. nov. In: Int J Syst Evol Microbiol. vol. 58. England: Microbiology Society; 2008. p. 2195–205.Google Scholar
  9. Endo A, Tanaka N, Oikawa Y, Okada S, Dicks L. Fructophilic characteristics of Fructobacillus spp. may be due to the absence of an alcohol/acetaldehyde dehydrogenase gene (adhE). Curr Microbiol. 2014;68(4):531–5.PubMedView ArticleGoogle Scholar
  10. Mendes-Soares H, Suzuki H, Hickey RJ, Forney LJ. Comparative functional genomics of Lactobacillus spp. reveals possible mechanisms for specialization of vaginal lactobacilli to their environment. J Bacteriol. 2014;196(7):1458–70.PubMedPubMed CentralView ArticleGoogle Scholar
  11. van de Guchte M, Penaud S, Grimaldi C, Barbe V, Bryson K, Nicolas P, et al. The complete genome sequence of Lactobacillus bulgaricus reveals extensive and ongoing reductive evolution. In: Proc Natl Acad Sci U S A. vol. 103. United States: National Academy of Sciences of the United States of America; 2006. p. 9274–79.Google Scholar
  12. Hols P, Hancy F, Fontaine L, Grossiord B, Prozzi D, Leblond-Bourget N, et al. New insights in the molecular biology and physiology of Streptococcus thermophilus revealed by comparative genomics. In: FEMS Microbiol Rev. vol. 29. Netherlands: Wiley Online Library; 2005. p. 435–63.Google Scholar
  13. Endo A, Okada S. Monitoring the lactic acid bacterial diversity during shochu fermentation by PCR-denaturing gradient gel electrophoresis. In: J Biosci Bioeng. vol. 99. Japan: Elsevier; 2005. p. 216–21.Google Scholar
  14. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18(5):821–9.PubMedPubMed CentralView ArticleGoogle Scholar
  15. Sugawara H, Ohyama A, Mori H, Kurokawa K. Microbial genome annotation pipeline (MiGAP) for diverse users. In: Proceedings of the 20th International Conference on Genome Informatics. World Scientific Publishing Company: Pacifico Yokohama, Japan; 2009. p. S–001–001–002.Google Scholar
  16. Noguchi H, Taniguchi T, Itoh T. MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes. DNA Res. 2008;15(6):387–96.PubMedPubMed CentralView ArticleGoogle Scholar
  17. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25(5):955–64.PubMedPubMed CentralView ArticleGoogle Scholar
  18. Lagesen K, Hallin P, Rodland EA, Staerfeldt HH, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007;35(9):3100–8.PubMedPubMed CentralView ArticleGoogle Scholar
  19. Kyrpides NC, Woyke T, Eisen JA, Garrity G, Lilburn TG, Beck BJ, et al. Genomic Encyclopedia of Type Strains, Phase I: The one thousand microbial genomes (KMG-I) project. Stand Genomic Sci. 2014;9(3):1278–84.PubMedPubMed CentralView ArticleGoogle Scholar
  20. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25(7):1043–55.PubMedPubMed CentralView ArticleGoogle Scholar
  21. Contreras-Moreira B, Vinuesa P. GET_HOMOLOGUES, a versatile software package for scalable and robust microbial pangenome analysis. Appl Environ Microbiol. 2013;79(24):7696–701.PubMedPubMed CentralView ArticleGoogle Scholar
  22. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28(1):33–6.PubMedPubMed CentralView ArticleGoogle Scholar
  23. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007;35(Web Server issue):W182–5.PubMedPubMed CentralView ArticleGoogle Scholar
  24. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.PubMedPubMed CentralView ArticleGoogle Scholar
  25. Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol. 2007;56(4):564–77.PubMedView ArticleGoogle Scholar
  26. Kuck P, Longo GC. FASconCAT-G: extensive functions for multiple sequence alignment preparations concerning phylogenetic studies. Front Zool. 2014;11(1):81.PubMedPubMed CentralView ArticleGoogle Scholar
  27. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3.PubMedPubMed CentralView ArticleGoogle Scholar
  28. Darriba D, Taboada GL, Doallo R, Posada D. ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics. 2011;27(8):1164–5.PubMedView ArticleGoogle Scholar
  29. Endo A, Okada S. Lactobacillus satsumensis sp. nov., isolated from mashes of shochu, a traditional Japanese distilled spirit made from fermented rice and other starchy materials. In: Int J Syst Evol Microbiol. vol. 55. England: Microbiology Society; 2005. p. 83–5.Google Scholar
  30. Lukjancenko O, Ussery DW, Wassenaar TM. Comparative genomics of Bifidobacterium, Lactobacillus and related probiotic genera. Microb Ecol. 2012;63(3):651–73.PubMedPubMed CentralView ArticleGoogle Scholar
  31. Rahkila R, De Bruyne K, Johansson P, Vandamme P, Bjorkroth J. Reclassification of Leuconostoc gasicomitatum as Leuconostoc gelidum subsp. gasicomitatum comb. nov., description of Leuconostoc gelidum subsp. aenigmaticum subsp. nov., designation of Leuconostoc gelidum subsp. gelidum subsp. nov. and emended description of Leuconostoc gelidum. Int J Syst Evol Microbiol. 2014;64(Pt 4):1290–5.PubMedView ArticleGoogle Scholar
  32. Bjorkroth KJ, Geisen R, Schillinger U, Weiss N, De Vos P, Holzapfel WH, et al. Characterization of Leuconostoc gasicomitatum sp. nov., associated with spoiled raw tomato-marinated broiler meat strips packaged under modified-atmosphere conditions. Appl Environ Microbiol. 2000;66(9):3764–72.PubMedPubMed CentralView ArticleGoogle Scholar
  33. Jaaskelainen E, Johansson P, Kostiainen O, Nieminen T, Schmidt G, Somervuo P, et al. Significance of heme-based respiration in meat spoilage caused by Leuconostoc gasicomitatum. Appl Environ Microbiol. 2013;79(4):1078–85.PubMedPubMed CentralView ArticleGoogle Scholar
  34. Björkroth J, Holzapfel W. Genera Leuconostoc, Oenococcus and Weissella. In: Dworkin M, Falkow S, Rosenberg E, Schleifer K-H, Stackebrandt E, editors. The Prokaryotes. US: Springer; 2006. p. 267–319.View ArticleGoogle Scholar
  35. Arevalo-Villena M, Bartowsky EJ, Capone D, Sefton MA. Production of indole by wine-associated microorganisms under oenological conditions. Food Microbiol. 2010;27(5):685–90.PubMedView ArticleGoogle Scholar
  36. Teixeira JS, McNeill V, Ganzle MG. Levansucrase and sucrose phoshorylase contribute to raffinose, stachyose, and verbascose metabolism by lactobacilli. Food Microbiol. 2012;31(2):278–84.PubMedView ArticleGoogle Scholar
  37. Tieking M, Ehrmann MA, Vogel RF, Ganzle MG. Molecular and functional characterization of a levansucrase from the sourdough isolate Lactobacillus sanfranciscensis TMW 1.392. Appl Microbiol Biotechnol. 2005;66(6):655–63.PubMedView ArticleGoogle Scholar
  38. Velazquez-Hernandez ML, Baizabal-Aguirre VM, Cruz-Vazquez F, Trejo-Contreras MJ, Fuentes-Ramirez LE, Bravo-Patino A, et al. Gluconacetobacter diazotrophicus levansucrase is involved in tolerance to NaCl, sucrose and desiccation, and in biofilm formation. Arch Microbiol. 2011;193(2):137–49.PubMedView ArticleGoogle Scholar
  39. Nieminen TT, Sade E, Endo A, Johansson P, Bjorkroth J. The family Leuconostocaceae. In: Eeae R, editor. The Prokaryotes – Firmicutes and Tenericutes. US: Springer; 2014. p. 215–40.Google Scholar
  40. Lazarevic V, Karamata D. The tagGH operon of Bacillus subtilis 168 encodes a two-component ABC transporter involved in the metabolism of two wall teichoic acids. Mol Microbiol. 1995;16(2):345–55.PubMedView ArticleGoogle Scholar
  41. Tamarit D, Ellegaard KM, Wikander J, Olofsson T, Vasquez A, Andersson SG. Functionally Structured Genomes in Lactobacillus kunkeei Colonizing the Honey Crop and Food Products of Honeybees and Stingless Bees. Genome Biol Evol. 2015;7(6):1455–73.PubMedPubMed CentralView ArticleGoogle Scholar

Copyright

© Endo et al. 2015

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