Article history:Received 11 January 2011Received in revised form 25 March 2011Accepted 6 April 2011Available online 13 April 2011
Keywords:Acetobacteraceae16S rRNA geneTaxonomy
The 16S–23S gene internal transcribed spacer sequence of sixty-four strains belonging to different acetic acidbacteria genera were analyzed, and phylogenetic trees were generated for each genera. The topologies of thedifferent trees were in accordance with the 16S rRNA gene trees, although the similarity percentages obtainedbetween the species was shown to be much lower. These values suggest the usefulness of including the 16S–23S gene internal transcribed spacer region as a part of the polyphasic approach required for the furtherclassification of acetic acid bacteria. Furthermore, the region could be a good target for primer and probedesign. It has also been validated for use in the identification of unknown samples of this bacterial group fromwine vinegar and fruit condiments.
Acetic acid bacteria (AAB) are Gram negative, coccoid to rodshaped, obligate aerobic bacteria that are well known for their abilityto incompletely oxidize a wide range of sugars or alcohols leading tothe accumulation of organic acids as end products (De Ley et al., 1984;Sievers and Swings, 2005; Swings et al., 1992). Acetic acid is one of themain by-products of the AAB oxidation of ethanol, and it is found inmany foods as a consequence of the presence and activity of thesebacteria (González et al., 2005). AAB arewidespread in nature becauseof their capability to survive and grow in both neutral and acidicmedia and the variety of substrates that they can use (De Ley et al.,1984). These characteristics allow AAB to be involved in the desiredfermentation of certain foods (cocoa products, vinegar, nata de coco,and beer) and the spoilage of others (wine, beer, and ciders). Thesebacteria are also involved in the production of chemicals with a higheconomical value, such as vitamin C, and the production of bacterialcellulose (Kersters et al., 2006). They have also been isolated fromtropical fruits and flowers and, more recently, have been found ashuman pathogens (Greenberg et al., 2006) and as commensal bacteriain Drosophila melanogaster (Roh et al., 2008).
The application of novel techniques to study and classifymicroorganisms has brought new insight into AAB taxonomy(Cleenwerck and De Vos, 2008). AAB are currently classified into 12genera (Acetobacter, Gluconobacter, Gluconacetobacter, Granulibacter,
Asaia, Kozakia, Neoasaia, Swaminatania, Saccharibacter, Acidomonas,Tanticharoenia, and Ameyamaea) in the family Acetobacteraceae as abranch of the acidophilic bacteria in the α-subdivision of theProteobacteria.
The identification of AAB isolates has been difficult to achieve(Cleenwerck and De Vos, 2008; Greenberg et al., 2006; Kersters et al.,2006; Moore et al., 2002), but it is of great importance for the propercontrol of the food processes where they are involved, both as spoilersas well as main producing agents. AAB identification at the specieslevel has traditionally been performed by phenotypic tests. Thedrawbacks of phenotypic tests, however, have led to the developmentand application of molecular techniques to complement them(Cleenwerck and De Vos, 2008).
The 16S–23S rRNA gene internal transcribed spacer (ITS) isregarded as having a higher discriminatory power than the 16SrRNA gene because it exhibits more polymorphisms. Although the 16SrRNA gene sequence has been previously used for the identification ofAAB in taxonomic studies, it can give ambiguous results because of thesimilarity in sequence among closely related species (Cleenwerck andDe Vos, 2008). The 16S–23S rRNA gene ITS sequences have alreadybeen successfully used to classify and identify AAB, albeit with alimited number of genera and species (González et al., 2005; Gulloet al., 2006; Ruiz et al., 2000, Sievers et al., 1996, Trcek, 2005; Trcekand Teuber, 2002). These sequences have been also used as part oftaxonomic approaches for the description of new AAB species(Cleenwerck et al., 2009, Malimas et al., 2009, Tanasupawat et al.,2004, Yukphan et al., 2005). The aim of the present study is to test theusefulness of the 16S–23S rRNA gene ITS for the classification andidentification of AAB strains at the species level. Considering thatnowadays sequencing is relatively cheap, this type of analysis can bealso proposed for routine analysis in ecological and industrial studies.
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For that purpose, we have used 64 strains representing the main AABgenera. To the best of our knowledge, this is the first attempt that asimilar study has been performedwith almost all the available speciesdescribed to date.
2. Materials and methods
2.1. Strains and growth conditions
A total of 64 AAB strains were used in this study (Table 1). Typestrains were obtained from the BCCM/LMG Bacteria Collection and theResearch Collection of the Laboratory of Microbiology (LM-UGent) orfrom the German Collection of Microorganisms and Cell Cultures(DSMZ) and were grown according to the provider's specifications.The wild samples were isolated from wine, vinegar and strawberryfood condiment elaborated in our experimental facilities (Mas delsFrares, URV, Tarragona, Spain). Theywere cultured in glucosemedium(5% glucose: 1% yeast extract) at 28 °C under aerobic conditions. Thewild isolates were B4, A1, A5, Fi4, Fi6, Fh5 and Fe1; these strains havebeen tentatively identified by 16S rRNA gene analysis. Some of thesequences were retrieved from EMBL as indicated in Table 1.
2.2. DNA preparation
The total DNA from the strains was extracted using the CTABmethod (Cetyltrimethylammonium bromide) as described by Ausubelet al. (1992) and modified as in Jara et al. (2008).
Table 1List of AAB species and strains used in this study.
2.3. 16S–23S rRNA gene ITS amplification and sequencing
Primers used for amplification and sequencing and the amplificationconditions of the 16S–23S rRNAgene ITSwere as described byRuiz et al.(2000). Gene amplicons were purified and sequenced byMacrogen Inc.facilities (Seoul, South Korea) using an ABI3730 XL automatic DNAsequencer. The sequenceswere deposited in theGenBankdatabasewiththe accession numbers (FR716473–FR716502) as indicated in Table 1.
2.4. Phylogenetic analysis
Sequences were assembled manually and subjected to BLASTanalysis (Altschul et al., 1997) tofindsimilarities to sequences depositedat GenBank. As Gr. bethesdensis appeared to be very different from theother AAB, it was used as an outgroupwhen creating phylogenies usingCLUSTALW (Thompson et al., 1994). Alignments weremodifiedmanu-ally, and the phylogenetic and evolutionary analyses were conductedusing MEGA version 4 software (Tamura et al., 2007). The phylogenetictrees were constructed based on the neighbor joining method (Saitouand Nei, 1987). The analyses of the evolutionary divergence betweensequences were conducted using the Kimura 2-parameter method inMEGA version 4 (Kimura, 1980; Tamura et al., 2007).
3. Results and discussion
The nucleotide sequences of the 16S–23S rRNA gene ITSs of themain genera of AAB have been determined. The phylogenetic
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relationships of the different genera have been constructed usingneighbor joining trees on the basis of the alignments of the sequencesand compared to the 16S rRNA gene tree.
The Acetobacter genus tree (comprising 16 species) was found tohave the same topology as the 16S rRNA gene tree (Fig. 1), indicatingthe presence of two subclusters (groups I and II). The grouping of thisgenus was supported by bootstrap values higher than 90% (in 1000trials) in most of the branches. The exception was the branching ofgroup II, which had a bootstrap value of 60%.
Sequence similarities between Acetobacter species for the 16S–23SrRNA gene ITS ranged between 58.4% (A. syzigii/A. nitrogenifigens) and97.7% (A. cerevisiae/A. malorum). Those values are lower than the onesfound in the 16S rRNA gene which range between 96.4 and 99.9%(Cleenwerck and De Vos, 2008). Group II contained A. lovaniensis,A. syzigii, A. pasteurianus, A. perxoydans and A. pomorum. Thesimilarities among this subgroup were below 85%, except betweenA. syzigii and A. lovaniensis where we found a similarity of 94.6% andA. pasteurianus and A. pomorum where the similarities wereapproximately 97%. Group I, containing the remaining 11 speciesshowed sequence similarity between species of approximately 65%.The closest related species in this group were A. cerevisiae, A. malorumand A. orleaniensis, where similarities between 97.7 and 92.3% wereobtained. The percent similarities found using the ITS sequences aremuch lower than the ones derived from the 16S rRNA gene, allowingfor a better phylogenetic classification of wild isolates. This isdemonstrated by using the ITS to classify strains A1 and A5 asA. cerevisiae and B4 as a A. malorum obtained from the production ofvinegar and food condiments from strawberry. We were unable toclassify these isolates by using only the 16S rRNA gene sequences
A. ce
A. ce
A. ce
A. m
A m
A.
A.i n
A. tropica
A.
A. or
A
A
1
100
100
99
97
61
60
100
64100
100
7390
89
0.05
Fig. 1. Neighbor-joining tree based on 16S–23S intergenic spacer sequences of the Acetobbranching points indicate the confidence limits estimated by bootstrap analysis based on 1parenthesis.
(results not shown). There is a two base-pair difference between thetype strains of these two species in the 16S rRNA gene sequence, andour isolates had one base pair match to each type strain in those twobase pairs. The discrimination power of this ITS could be an excellenttool to be included as a characteristic for identification of differentspecies of Acetobacter genus using a polyphasic approach.
The Gluconacetobacter genus tree was also divided in twosubclusters (groups I and II) (Fig. 2) as it shares the same topologyas the 16S rRNA, dnaK, groEL and rpoB trees (Cleenwerck et al., 2010).Using the ITS sequences, Ga. hanseniiwas placed in group II instead ofgroup I, where it was placed when using sequences of the above-mentioned other genes. The confidence of the grouping of this genuswas supported by high bootstrap values obtained for all the mainbranches (Fig. 2). Sequence similarities of the 16S–23S rRNA gene ITSswithin this genus ranged between 75.3 and 98.1%, which is muchlower than similarities between the 16S rRNA, dnaK, groEL or rpoBgenes. Within the species of group II, similarities obtained were above90%, except for Ga. diazotrophicus, which had sequence similarityvalues of approximately 80% when compared with other members ofthe group. This suggests lower phylogenetic divergence in this regionof the genome for group II compared to group I, which had similarityvalues below 90% in all species. In the case of the 16S rRNA gene, somespecies in group I have been reported with 100% similarity values(Dellaglio et al., 2005, Lisdiyanti et al., 2006), indicating that 16S–23SrRNA gene ITSs should be good regions for further classification andidentification and as a part of polyphasic approaches studies withinthis genus. We were able to confirm the identification of the vinegarstrain Fe1 as Ga. europaeus previously identified by 16S rRNA genesequencing. Furthermore, two more vinegar strains were identified as
revisiae A1
revisiae A5
revisiae LMG 1625T
alorum LMG 1746T
alorum B4
orleaniensis LMG 1583T
donesiensis LMG 19824T
lis LMG 1663T
cibinongensis LMG 21418T
ientalis LMG 21417T
A. oeni B7 (EU449494)
A. oeni B13T (449495)
A. nitrogenifigens LMG 23498T
A. estunensis LMG 1626T
A. aceti DSM 3508T (AJ007831)
A. aceti NBR 14858 (AB111902)
A. peroxydans LMG 1635T
. lovaniensis LMG 1579T
A. syzigii LMG 21419T
A. pomorum LMG 18849T (EU449498)
. pasteurianus LMG 1590 (205102)
A. pasteurianus IFO 3283 (AJ888877)
Gr. bethesdensis NIH 1T (340304)
100
00
I
II
acter genus. Granulibacter bethesdensis NIH 1T was used as an outgroup. Numbers at000 replicates. Accession numbers of the sequences retrieved from EMBL are shown in
Ga. europaeus DSM 6160T (X85406)
Ga. europaeus Fe.1
Ga. swingsii LMG 22125T
Ga.oboediens LMG 18849T
Ga. saccharivorans LMG 1582T
Ga. intermedius Fi.6
Ga. intermedius Fi.4
Ga. xylinus LMG 1515 T
Ga.nataicola LMG 1536T
Ga. hansenii LMG 1527T
Ga. hansenii Fh.5
Ga. liquefaciens LMG 1382T
Ga. sacchari LMG 19747T
Ga. diazotrophicus LMG 7603T
Ga. azotocaptans LMG 21311T
Ga. johannae LMG 13595T
Gr. bethesdensis NIH 1T (DQ340304)
100
100
10098
95
99
100
73
100
10080
54
98
0.05
I
II
Fig. 2. Neighbor-joining tree based on 16S–23S intergenic spacer sequences of the Gluconacetobacter genus. Granulibacter bethesdensis NIH 1T was used as an outgroup. Numbers atbranching points indicate the confidence limits estimated by bootstrap analysis based on 1000 replicates. Accession numbers of the sequences retrieved from EMBL are shown inparenthesis.
220 Á. González, A. Mas / International Journal of Food Microbiology 147 (2011) 217–222
Ga. intermedius (Fi6 and Fi4). Finally the Ga. hansenii strain Fh5isolated from wine vinegar was appropriately identified in its species.
The Gluconobacter tree could also be divided in two mainsubclusters according to a phylogenetic tree built with the 16S–23SrRNA gene ITS (Fig. 3): Group I, comprising G. oxydans, G. shpaericus,G. roseus, and G. albidus, and group II comprising G. cerinus,G. japonicus, G. frateurii and G. thailandicus. These groups match withthe 16S rRNAgene subclusters (Cleenwerck andDeVos, 2008; Yamada
G.
G.
G.
G.
G.
G
G
100
100
9998
100
68
58
0.05
Fig. 3. Neighbor-joining tree based on 16S–23S intergenic spacer sequences of the Gluconobranching points indicate the confidence limits estimated by bootstrap analysis based on 1parenthesis.
andYukphan, 2008).Wealso obtained the same results as Takahashi etal. (2006) who analyzed this genus with the 16S–23S rRNA gene ITS,except for G. cerinus, which they found was in a separate group,although it was close to the first subcluster. Similarity values foundbetween species in groups I and II were quite high when compared toother AAB genera. The 16S–23S rRNA gene ITS sequence similarityranged between 95.5 and 99.2%, with the latter value corresponding tothe similarity betweenG. frateurii andG. thailandicus. Between the two
oxydans LMG 1674 (GU205104)
oxydans NBRC 14819T (AB 163869)
oxydans B10 (EU449497)
sphaericus NBRC 12467T (AB163867)
roseus NBRC 3990T (AB163865)
. albidus NBRC 3250T (AB163828)
. albidus NBRC 3273 (AB163848)
G. cerinus IAM 1832 (AB111903)
G. cerinus NBRC 3267T (AB111899)
G. japonicus PHD-1 (AB540146)
G. japonicus RBY-1 (AB540145)
G. frateurii NBRC 16669 (AB163870)
G. thailandicus F142-1 (AB127942)
G. thailandicus F149-1T (AB127941)
Gr. bethesdensis NHI 1T (DQ340304)
100
9769
98
99
I
II
bacter genus. Granulibacter bethesdensis NIH 1T was used as an outgroup. Numbers at000 replicates. Accession numbers of the sequences retrieved from EMBL are shown in
As. krungthepensis BCC 15704 (AB231007)
As. krungthepensis BCC 15713 (AB231009)
As. siamensis BCC 15670 (AB231003)
As. siamensis BCC 15681 (AB231004)
As. bogorensis BCC 15696 (AB231005)
As. bogorensis BCC 15725 (AB231010)
Sw. salitolerans LMG 21291T (AB 220163)
Na. chiangmaiensis BCC 15763 (AB208550)
Ac. methanolica BCC 12263T (AB210135)
K. baliensis BCC 12275T (AB208554)
Sa. floricola JCM 12116T (AB210092)
Gr. bethesdensis NIH 1T (DQ340304)
68
81
100
100
92
96
98
0.05
Fig. 4. Neighbor-joining tree based on 16S–23S intergenic spacer sequences of Asaia, Neoasaia, Acidomonas, Kozakia, Swaminatania and Saccharibater genera. Granulibacterbethesdensis NIH 1T was used as an outgroup. Numbers at branching points indicate the confidence limits estimated by bootstrap analysis based on 1000 replicates. Accessionnumbers of the sequences retrieved from EMBL are shown in parenthesis.
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groups, similarity values were approximately 85%. Those values arequite similar to the ones observed by Takahashi et al. (2006) and lowerthan the similarities found with the 16S rRNA gene, which range from98.3 to 99.6%. These results suggest that the different species in theGluconobacter genus are closely related.
The tree obtained with the phylogenetic analysis of 16S–23S rRNAgene ITS sequences in the Asaia, Neoasaia, Acidomonas, Kozakia andSaccharibacter genera is represented in Fig. 4. In this analysis, weobserved a close phylogenetic relationship among the Asaia species.As with the 16S rRNA gene, there were very high similarity values inthe ITS region (from 96.3 to 98.2%), confirming that these species arephylogenetically very closely related. Between Asaia and other closelyrelated genera such as Neoasaia, Swaminatania and Kozakia, onlySwaminatania showed high similarity values with the Asaia species(above 93%). When compared to the rest of the genera, similarityvalues obtained were always below 65%.
According to the results obtained, we can confirm the higherdiscriminatory power of the 16S–23S rRNA gene ITS sequence analysiscompared to using the 16S rRNA gene itself. The low similarity valuesbetween isolates suggest this could be a good DNA region for specificprimer and/or probe design for identification and quantificationstudies. We found the same topology as in the 16S rRNA gene trees,suggesting that could be a good tool for further phylogenetic studiesamong AAB and a useful technique for more accurate classification ofspecies of AAB. Thus, even for taxonomic classification, this could bealso a good parameter to be considered in the polyphasic approachthat nowadays is required for good description of new species. In fact,we were able to identify three wild strains that could not bedifferentiated between A. cerevisiae and A. malorum by using 16S–23S rRNA gene ITS phylogenetic analysis. Two of them (A1 and A5)were identified as A. cerevisiaewhereas another (B4) was identified asA. malorum. We were unable to distinguish between those strainsusing the 16S rRNA gene due to their high sequence similarity.Additionally, other Gluconacetobacter isolates that were previouslyidentified by 16S rRNA gene sequence were also successfully classifiedusing the 16S–23S rRNA gene ITS phylogenetic analysis. Strains Fe1,Fh5 and Fi4 and 6, belonging to Ga. europaeus and Ga. hansenii andGa. intermedius respectively, were correctly classified according totheir phylogenetic relationships in the Gluconacetobacter genus(Fig. 2). Due to the high species polymorphism and the low cost ofsequencing, the phylogenetic analysis of the 16S–23S rRNA gene ITS
appears to be a promising tool for the identification of AAB spoilingand producing agents in the food industries, where a large number ofsamples should be analyzed for appropriate control.
We also found two highly conserved regions in all the sequences,coincident to tRNAIle and tRNAAla that were identical in all strainspreviously reported (Sievers et al., 1996, Trcek and Teuber, 2002).Distances between those conserved regions were variable, except inthe case of the Gluconobacter genus where the distance was 12 basepairs in all the sequences analyzed. Those two highly conservedregions could be ideal nucleotide sequences for primer design and forgenus differentiation.
4. Conclusion
In summary, using the 16S–23S rRNA gene ITS for phylogeneticanalysis can be a good tool for the AAB identification of naturalisolates and in food production as well as a complementary tool fortaxonomic identification. In the present study we have been able toconfirm that all the AAB species could be differentiated by thisphylogenetic analysis. Also, it should be considered as useful criteriain taxonomic polyphasic studies. Furthermore, the presence ofconserved sequences within this region provides good targets forthe design of primers and probes for identification or differentiation atthe species or genus level.
Acknowledgement
The present work has been financed by the project AGL2007-66417-C02-02/ALI from the Spanish Ministry of Education andScience.
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