Zdrav Vestn 2008; 77: 547–52 547 Research article/Raziskovalni prispevek MOLECULAR IDENTIFICATION OF SEVERAL CLINICALLY IMPORTANT BACTERIA INCLUDING ENTEROBACTERIA BY PARTIAL 16S RIBOSOMAL RNA GENE SEQUENCE COMPARISON MOLEKULARNA IDENTIFIKACIJA KLINIČNO POMEMBNIH BAKTERIJ, VKLJUČNO ENTEROBAKTERIJ S PRIMERJAVO DELNEGA NUKLEOTIDNEGA ZAPOREDJA GENA ZA 16S RIBOSOMSKO RNK Janez Šimenc,1, 2 Andrej Golle,3 Uroš Potočnik,1, 2 1 Center za humano molekularno genetiko in farmakogenomiko, Medicinska fakulteta, Univerza v Mariboru, Slomškov trg 15, 2000 Maribor 2 Fakulteta za zdravstvene vede, Univerza v Mariboru, Žitna ulica 15, 2000 Maribor 3 Zavod za zdravstveno varstvo Maribor, Prvomajska ulica 1, 2000 Maribor Abstract Background Methods Results Conclusions Key words The correct identification of bacterial isolates is paramount for the correct diagnosis and treatment of patients. The standard approach for bacterial identification relies on pheno-typic tests, which are often time-consuming and unreliable when identifying atypical strains. We instead hypothesized a molecular approach; fast and reliable identification could be achieved by comparing a 16S ribosomal RNA gene sequence with publicly available sequences. In the present study, DNA from seventeen bacterial species was extracted and amplified by PCR, and then a partial 16S ribosomal RNA gene sequence was obtained and compared with sequences deposited in public DNA sequence databases; EMBL/GeneBank/DDBJ and RDP-II. Bacterial species, belonging to several families; Coriobacteriaceae, Bacteroidaceae, Clostri-diaceae, Staphylococcaceae, as well as three out of nine Enterobacteriaceae were specifically identified by partial 16S ribosomal RNA gene sequence to the species level. For six other species of enteric bacteria specific identification of species failed, since the results of genotypic identification yielded several species. We conclude identification of bacteria with partial 16S ribosomal RNA gene sequence is an efficient complement to phenotypic identification, except for enteric bacteria. molecular identification; bacteria; 16S rDNA sequences Izvleček Za učinkovito diagnostiko bakterijskih okužb in zdravljenje je potrebna hitra in natančna identifikacija bakterije. Običajen postopek je fenotipska identifikacija, ki je pogosto zahtevna in nenatančna za atipične izolate. V naši študiji smo predpostavili, da je možno identificirati bakterije s primerjavo delnih nukleotidnih zaporedij genov, ki kodirajo 16S ribosomsko RNK s primerjavo z nukleotidnimi zaporedji v javno dostopnih podatkovnih bazah za zaporedja DNK: EMBL, GenBank, DDBJ in RDP-II. Še posebej nas je zanimala možnost identifikacije enterobakterij, saj mnogi avtorji navajajo, da te skupine bakterij ni Corresponding author / Avtor za dopisovanje: Asist. mag. Janez Šimenc, univ. dipl. mikrobiol., Magdalenski trg 5, 2000 Maribor, Slovenia, tel/fax +386 2 330 5876 / +386 2 330 5861, e-mail: janez.simenc@uni-mb.si 548 Zdrav Vestn 2008; 77 moč ločiti na osnovi zaporedij genov 16S ribosomske RNK. Za izvedbo študije smo pridobili 15 tipskih sevov in dva klinična izolata iz zbirke Zavoda za zdravstveno varstvo Maribor, katerih rutinska fenotipska identifikacija je težavna. Iz bakterij smo izolirali DNK ter z verižno reakcijo s polimerazo (PCR) pomnožili variabilen odsek gena za 16S ribosomsko RNK. Pridelke PCR smo očistili in poslali na sekveniranje s prednjim začetnim oligonukleotidom v podjetje Macrogen, Koreja (www.macrogen.com). Pridobljena nukleo-tidna zaporedja DNK smo nato z dvema iskalnima algoritmoma; BLAST, v bazah GeneBank/EMBL/DDBJ, ter z algoritmom Sequence match v bazi RDP-II primerjali z vloženimi nukleotidnimi zaporedji, za morebitno identifikacijo vrste. Specifično smo uspeli identificirati vrste: Staphylococcus epidermidis, Bacteroides fragilis, Clostridium per-fringens, Peptostreptococcus anaerobius, Eggerthella lenta, Enterobacter cloacae, Yersinia enterocolitica, Proteus mirabilis, Streptococcus pyogenes, Enterococcus faecalis. Medtem ko Escherichia coli, Serratia marcescens, Shigella flexneri, Klebsiella pneumoniae, Citro-bacter freundii nismo uspeli nedvoumno identificirati, čeprav je klinično nujno. Vendar menimo, da je opisan genotipski pristop za identifikacijo vrste bakterije učinkovito dopolnilo fenotipski identifikaciji, še posebno pri identifikaciji atipičnih izolatov. Ključne besede molekularna identifikacija; nukleotidno zaporedje; bakterije Introduction Accurate identification of bacterial isolates is essential task for clinical microbiology laboratories. Currently, standard methods for bacterial identification rely on phenotypic methods. However, for many fastidious bacteria, phenotypic identification is not only difficult and time consuming, but the identification of species is difficult due to the phenotypic variability among strains belonging to the same species. In these situations, a molecular approach, based on DNA sequence analysis, could achieve identification.1 Two PCR-based approaches are widely used for molecular bacterial identification: the first targets species or group specific genes,2 while the second approach uses PCR amplification of ribosomal genes by broad range primers for bacteria detection and require a second post-PCR processing step for identification.3 Ribosomal genes are ubiquitous, multicopy genes, in evolutionary sense operating as molecular chronometers, hence reflecting bacterial phylogenetic related-ness.4 The 16S ribosomal RNA gene has been proposed as most suitable for use in phylogenetic studies.5 Partial sequences of 16S ribosomal RNA gene should be sufficient for the identification of species when compared with some longer, closely related sequence. In contrast, the entire 16S ribosomal RNA gene sequence is required for new species identification.6, 7 Due to extensive use of 16S ribosomal gene sequences for phylogenetic studies, public domain databases have been established for sequences deposition and com-parison.8, 9 Indeed, comparisons between partial 16S ribosomal RNA gene sequences and sequences deposited in public domain DNA databases has proven an efficient complement to phenotypic methods, i.e. for gram-positive rods,10 for identification of aerobic catalase-negative, gram-positive cocci,11 for non fermenting gram negative bacteria,12 for enteric bacteria, limited results have been reported.13 The aim of this study was to assess the feasibility of the amplification of partial 16S ribosomal RNA gene by a single broad range primer pair, and subsequent sequencing of PCR products for bacterial species identification. We were particularly interested in enteric bacteria identification. Material and methods Bacterial species and DNA isolation As listed in Table 1, fifteen bacterial quality control type strains were obtained from the American type culture collection (ATTC); Escherichia coli, Bactero-ides fragilis, Clostridium perfringens, Peptostreptococ-cus anaerobius, Eggerthella lenta, Salmonella Typhi-murium, Shigella flexneri, Enterobacter cloacae, Ser-ratia marcescens, Citrobacter freundi, Yersinia entero-colitica, Proteus mirabilis, Streptococcus pyogenes, Klebsiella pneumoniae, Enterococcus faecalis and two clinical isolates (Prevotella spp., and Staphylococcus epidermidis were obtained from clinical microbiology laboratory for this study. DNA was extracted and purified from colonies with tissue modified following the Qiamp DNA mini kit procedure (Qiagen): a colony was picked up from a plate, suspended in 180 µl of ATL buffer and incubated with 20 µl of pro-teinase K (1 mg/ml) for 35 minutes at 56 °C, without lizocyme or other cell wall degrading enzymes. Tissue protocol was then followed. PCR and sequencing Extracted DNA was used as a template for 20 µl PCR reactions. PCR was performed with 2U of Taq poly-merase (Fermentas), 2.5 mM MgCl2, 1X PCR buffer with ammonium sulphate, 0.4 mM of each deoxynu-cleoside triphosphate, deionizied and autoclaved water, 0.5 µM of each primer f-968: 5‘-AACGCGAA-GAACCTTAC-3‘ and r-1401: 5‘-CGGTGTGTACAAGAC-CC-3‘.14 The reaction was performed in a thermocy-cler (Biometra) as follows: 3 min at 95 °C, 35 cycles of 40 s at 94 °C, 40 s at 56 °C, 40 s at 72 °C, and 3 min at 72 °C. PCR products of about 430 nucleotides were observed by agarose (1.5 %) gel electrophoresis. Ampli- Šimenc J, Golle A, Potočnik U. Molecular identification of several clinically important bacteria 549 Table 1. Bacterial strains used for this study, source, and molecular identification results with highest similarity score with compared sequences. Razpr. 1. Bakterijski sevi, uporabljeni v študiji, vir in rezultati molekularne identifikacije z najvišjo vrednostjo ujemanja primerjanih zaporedij. Isolate number Številka izolata Bacterial strain and phenotypic identification Bakterijski sev in fenotipska identifikacija Source Identification by Highest similarity sequence alignment score percentage with BLAST with BLAST algorithm in algorithm GeneBank, DDBJ, EMBL databases Vir Identifikacija s Najvišja vrednost primerjavo zaporedij ujemanja v skladu z BLAST z BLAST algoritmom v GeneBank, algoritmom DDBJ, EMBL bazah (v odstotkih) podatkov Identification by Highest S sequence value with alignment Sequence with Sequence match match algorithm algorithm in RDP database Identifikacija s pri- Najvišja S merjavo zaporedij v vrednost skladu z algoritmom pri algoritmu za primerjavo za primerjavo zaporedij v RDP- zaporedij bazi podatkov 1 Staphylococcus epidermidis Clinical isolate Klinični izolat Staphylococcus epidermidis 100 Staphylococcus epidermidis 1.00 2 Prevotella spp. Clinical isolate Klinični izolat Bacteroides fragilis 99 Bacteroides fragilis 0.44 3 Bacteroides fragilis ATCC 25285 Bacteroides fragilis 99 Bacteroides fragilis 0.981 4 Clostridium perfringens ATCC 13124 Clostridium perfringens 100 Clostridium perfringens 1.00 5 Peptostreptococcus anaerobius ATCC 27337 Peptostreptococcus anaerobius 100 Peptostreptococcus anaerobius 1.00 6 Eggerthella lenta ATCC 43055 Eggerthella lenta 100 Eggerthella lenta 0.995 Escherichia coli ATCC 25922 Escherichia coli, Shigella sonnei, Shigella flexneri, Shigella dysenteriae, Shigella boydii 99 Escherichia coli, Shigella flexneri, Shigella boydii, Shigella sonnei, Escherichia albertii, Escherichia fergusonii 0.966 Salmonella typhimurium ATCC 140028 Salmonella enterica sub. Enterica, ser. Paratyphi B, Paratyphi C 100 Salmonella entericaca sup. enterica, ser. Typhimurium 1.00 Shigella flexneri ATCC 12022 Shigella flexneri, Shigella boydii, Shigella sonnei, Shigella dysenteriae, Escherichia coli 100 Escherichia coli, Shigella boydii, Shigella flexneri, Shigella sonnei, Escherichia albertii, Escherichia fergusonii 1.00 10 Enterobacter cloacae ATCC 13047 Enterobacter cloacae, 100 Enterobacter cloacae 1.00 11 Serratia marcescens ATCC 13880 Serratia marcescens, Enterobacter aerogenes, Kluyvera cryocrescens 100 Serratia marcescens, Kluyvera cryocrescens 1.00 12 Citrobacter freundii ATCC 8090 Citrobacter freundii, Klebsiella oxytoca, Raoultella terrigena 100 Citrobacter freundii, Klebsiella oxytoca, 0.984 13 Yersinia enterocolitica ATCC 9610 Yersinia enterocolitica 100 Yersinia enterocolitica 0.995 14 Proteus mirabilis ATCC 43071 Proteus mirabilis 100 Proteus mirabilis 1.00 15 Streptococcus pyogenes ATCC 19615 Streptococcus pyogenes 100 Streptococcus pyogenes 0.971 16 Klebsiella pneumoniae ATCC 13883 Klebsiella pneumoniae, Klebsiella variicola, Klebsiella oxytoca 100 Klebsiella pneumoniae, Klebsiella variicola, Klebsiella oxytoca 1.00 17 Enterococcus faecalis ATCC 29212 Enterococcus faecalis, Enterococcus dispar, Lactobacillus plantarum 100 Enterococcus faecalis 0.955 cons were purified with the QIAquick PCR purification kit (Qiagen) according to manufacturer’s instructions and were sent for sequencing with forward primer f-968, and in cases of nucleotide ambiguity with reverse primer r-1401 to Macrogen, Inc. (www.macrogen.com). 16S ribosomal RNA gene sequence analysis Determined sequences were compared with sequences available in GeneBank, EMBL, and DDBJ data- bases using the BLAST algorithm,15 through the National center for biotechnology information server (www.ncbi.nlm.nih.gov) and with sequences available in Ribosomal database project (RDP-II) (http:// rdp.cme.msu.edu), release 9.59, by use of Sequence match algorithm.9 In order to assign isolate to a species, each derived sequence aligned by the BLAST algorithm, yielded at least 99 % similarity score with identified species in the BLAST search, and the highest S-ab value with identified species in the Sequence match search. 7 8 9 550 Zdrav Vestn 2008; 77 Results and discussion In the present study, fifteen bacterial type strains were used and two clinical isolates were obtained from clinical microbiology laboratory (Table 1). DNA was then extracted and amplified between 968 and 1401 positions in the 16S ribosomal RNA gene (Escherichia coli reference numbering), giving 430 bp amplification product, and amplicons were purified and sequenced with f-968 forward primer and in case of ambiguous nucleotides with r-1401 reverse primer as well. Partial 16S ribosomal RNA gene sequences were obtained and checked, in order to ascertain whether identification of bacterial species would be possible through comparison with publicly available sequences with the BLAST algorithm in GeneBank/EMBL/DDBJ DNA databases, and with the Sequence match algorithm in the RDP-II database. It is noteworthy that one difficulty of the sequence comparison approach for new species identification is that there are no generally accepted guidelines for comparison of sequence similarity for 16S ribosomal RNA gene sequence based identification. However some recommendations have been made: based on theoretical predictions of divergence, a difference of entire 16S ribosomal gene or protein coding region sequence > 0.5 % has been suggested as indicative for a new species within known genus.16 In this study, only the variable region of 16S ribosomal RNA gene was amplified by f-968 and r-1401 primer pair,14 since greater heterogeneity has been displayed in this region among bacterial species, as compared with other variable regions of the gene.17 This region of 16S ribosomal RNA gene has been widely used for the profiling of diverse bowel bacterial communi-ties.18, 19 Ideally, we would expect this region of 16S ribosomal sequence to differentiate among bacterial species, and on the other hand, for it to be conserved enough, for clustering of bacterial isolates of the same species. In addition, identification problems may arise from interoperon ribosomal sequence heterogeneity, which may also contribute to differences.20 Since just a portion of variable 16S ribosomal RNA gene sequences was used for comparison, we expected only to identify existing species, while phylogenetic observations indicated new bacterial species were unlikely.6, 7 After the second step, the BLAST search, derived sequences were aligned with the Sequence match algorithm in the RDP-II database, which uses alignment information to calculate percent identity over all comparable positions and calculates binary association coefficient Sab21 in contrast to the BLAST algorithm, which reports only local identity over a fraction of sequence.9 Sequence match algorithm should enable more reliable species identification. Search results with the BLAST algorithm in GeneBank/EMBL/ DDBJ were able to specifically identify several enteric bacteria species: Yersinia enterocolitica, Proteus mirabilis, Enterobacter cloacae, and Salmonella enterica, although it was not identified as serovar Typhi-murium in the BLAST search results. The same results were obtained with Sequence match algorithm in the RDP-II search (Table 1). Shigellae were indiscernible from each other and from Escherichia coli. This observation was expected, since Escherichia coli and Shigella are considered phylogenetically as the same species.22 On the other hand, Escherichia coli isolate was specifically identified as Shigella or Escherichia coli with BLAST; however with the Sequence match algorithm two additional unclassified Escherichia species were identified (Table 1), indicating high intra-genus similarities of the Escheri-chia species, a phylogenetic property which is not clinically acceptable. However specific identification was not achieved for other enteric bacteria species. Klebsiella pneumoniae was not discerned from Kleb-siella variicola and Klebsiella oxytoca, just as with Escherichia, indicating close intra-genus homogeneity. For Serratia marcescens and Citrobacter freundii classification to genus level failed (Table 1). Citro-bacter freundii was not discerned from Klebsiella oxytoca and Raoultella terrigena. These observations are in accordance with phylogenetic observations, indicating that Klebsiella and Raoultella species are grouped with other representatives of Enterobac-teriaceae genera, including with Citrobacter freun-dii.23 Serratia marcescens was not discerned from Enterobacer aerogenes and Kluyvera cryocrescescens. This observation indicates the closer relationship between Serratia marcescens and Kluyvera cryocre-scescens, however further phylogenetic analyses are needed for more decisive conclusions. The Entero-bacter genus is phylogenetically interwined with members of several other genera, and Enterobacter aerogenes may be more closely related to Serratia marcescens than to the other Enterobacter species.24 For enteric bacteria, the discriminatory power at species level of 16S ribosomal RNA gene sequences has been questioned, and it seems phenotypic approach yields higher level of discrimination.13 Other studies reported failures in the 16S ribosomal gene sequence based approach to differentiating enteric bacteria,1, 25 however in this study; we were able to delineate several enteric bacteria by partial 16S ribosomal RNA gene sequence comparison with publicly available sequences. But for clinical use, molecular approach should be at least as discriminative as phenotypic tests. Several other bacteria species, members of different phyla: Staphylococcus epidermidis, Clostridium perfringens, Bacteroides fragilis, Peptostreptococcus anaerobious, Eggerthella lenta, Streptococcus pyo-genes were identified specifically with BLAST algorithm, as well as with the Sequence match algorithm (Table 1). The amplified region of the 16S ribosomal RNA gene is diverse enough for discrimination of these species. In addition, clinical isolate number two, identified by phenotypic approach as Prevotella spp. (Table 1), was specifically identified as Bacteroides fragilis, which exemplifies the need for an improved routine identification scheme. However, this discrepancy is not unusual, since both genera, Prevotel-la and Bacteroides are phenotypically and genotypi-cally closely related, and previous phylogenetic analyses, based on 16S ribosomal gene sequence had Šimenc J, Golle A, Potočnik U. Molecular identification of several clinically important bacteria 551 shown that several Prevotella species fall in the genus Bacteroides.26 Peptostreptococcus anaerobius was specifically identified by the BLAST algorithm, as well as with the RDP-II search (Table 1). Isolate number six (Table 1), identified as Eggerthella lenta is bacterium belonging to the Coriobacteriaceae family, and has long been classified as Eubacterium lentum. Since the genus Eubacterium is phylogenetically and pheno-typically diverse, Eubacterium lentum has been reclassified as a type species of Eggerthella genus, named Eggerthella lenta on the basis of 16S ribosomal gene sequence analysis.27 Specific identification was observed for Streptococcus pyogenes identification with the BLAST algorithm, and with RDP-II search results, indicating that the section 16S ribosomal gene used for this study has sufficient discriminatory power. Although we were able to identify Streptococcus pyogenes specifically, use of the 16S ribosomal RNA gene sequence has been reported ambiguously for Streptococcus species iden-tification.28 On the contrary, nonspecific identification was observed with the BLAST algorithm for Entero-coccus faecalis, since it was additionally identified as Enterococcus dispar and Lactobacillus plantarum. However, the existence of Enterococcus dispar as a new species has been questioned, since it was identified only by partial 16S ribosomal RNA gene sequences of two strains.28 Searching in the RDP-II, led to the identification of Enterococcus faecalis as well as Lacto-bacillus plantarum. This observation indicates a close relationship, and may be explained by the horizontal gene transfer between these two species.29 We propose, for routine identification, that the query sequence should be compared with the BLAST algorithm in GenBank/EMBL/DDBJ databases and with the Sequence match algorithm in RDP-II database. In case of ambiguous identification with both algorithms, yielding several different species, we propose searching for the most similar type strains, which can enable identification by subsequent direct comparison of genetic regions and/or phenotypic characteristics. Molecular identification results should be correlated with phenotypic identification and interpreted together. In conclusion, in this study, we were able to identify several bacterial type strains, including three out of nine enteric bacteria, to the species level by only partial 16S ribosomal gene sequence. 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