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The Variability of the Order Burkholderiales Representatives in the Healthcare Units

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Hindawi Publishing Corporation BioMed Research International Volume 2015, Article ID 680210, 9 pages http://dx.doi.org/10.1155/2015/680210 Research Article The Variability of the Order Burkholderiales Representatives in the Healthcare Units Olga L. Voronina,1 Marina S. Kunda,1 Natalia N. Ryzhova,1 Ekaterina I. Aksenova,1 Andrey N. Semenov,1 Anna V. Lasareva,2 Elena L. Amelina,3 Alexandr G. Chuchalin,3 Vladimir G. Lunin,1 and Alexandr L. Gintsburg1 1 N.F. Gamaleya Federal Research Center for Epidemiology and Microbiology, Ministry of Health of Russia, Gamaleya Street 18, 123098 Moscow, Russia 2Federal State Budgetary Institution “Scientific Centre of Children Health” RAMS, 119991 Moscow, Russia 3Research Institute of Pulmonology FMBA of Russia, 105077 Moscow, Russia Correspondence should be addressed to Olga L. Voronina; [email protected] Received 12 September 2014; Accepted 1 December 2014 Academic Editor: Vassily Lyubetsky Copyright © 2015 Olga L. Voronina et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background and Aim. The order Burkholderiales became more abundant in the healthcare units since the late 1970s; it is especially dangerous for intensive care unit patients and patients with chronic lung diseases. The goal of this investigation was to reveal the real variability of the order Burkholderiales representatives and to estimate their phylogenetic relationships. Methods. 16S rDNA and genes of the Burkholderia cenocepacia complex (Bcc) Multi Locus Sequence Typing (MLST) scheme were used for the bacteria detection. Results. A huge diversity of genome size and organization was revealed in the order Burkholderiales that may prove the adaptability of this taxon’s representatives. The following variability of the Burkholderiales in Russian healthcare units hasbeen revealed: Burkholderiaceae (Burkholderia, Pandoraea,andLautropia), Alcaligenaceae (Achromobacter), and Comamonadaceae (Variovorax). The Burkholderia genus was the most diverse and was represented by 5 species and 16 sequence types (ST). ST709 and 728 were transmissible and often encountered in cystic fibrosis patients and in hospitals. A. xylosoxidans was estimated by 15 genotypes. The strains of first and second ones were the most numerous. Conclusions. Phylogenetic position of the genus Lautropia with smaller genome is ambiguous. The Bcc MLST scheme is applicable for all Burkholderiales representatives for resolving the epidemiological problems. 1. Introduction intensive care unit patients and patients with chronic lung diseases, particularly cystic fibrosis [3]. The taxonomy of this The antibiotic era resulted in the cardinal changes in the bacteria group has been developing since the 1980s and they spectrum of the microorganisms, causing the healthcare- were subdivided into different genera between 1981 and 2000 associated infections. Well-known bacterial pathogen Staphy- [4–8]. lococcus aureus was crowded by Pseudomonas aeruginosa The infusion of nucleic acid sequencing technology in [1]; then both were pressed by other Proteobacteria. The microbiology allowed Woese to start solving the bacterial resistome of these bacteria has been enriched over the years phylogeny problem [9]. Proteobacteria, the most abundant of the nosocomial circulation, but most of them kept sensitive and diverse bacterial phyla, were subdivided into classes to at least one antibiotic. on the base of the 16S rRNA gene sequences. First of all, The situation was complicated by the appearance of the 8–12 nucleotide signature sequences whose characteristic is order Burkholderiales bacteria after the late 1970s [2]. These unique to the species of Beta- and Gammaproteobacteria bacteria are the common inhabitants of soil and water. They were identified (AAAAACCUUACC for Betaproteobacteria; can be the plants’ pathogens and have natural resistance AAACUCAAAUG for Gammaproteobacteria) [10, 11]. So to common antibiotics. They are especially dangerous for the taxon Pseudomonas, according to Woese, was actually 2 BioMed Research International acollectionofatleastfiveseparategroupsofbacteria[9]. It 2.7. Nucleotide Sequence Polymorphism. The numbers of was subdivided into several genera, one of which was genus nucleotide/amino acid differences per site between concate- Burkholderia [5]. Later a new genus Ralstonia was separated nated sequences of 17 Bcc STs were obtained by pairwise from Burkholderia [7]. Lautropia [6]and Pandoraea [8]have distance calculation. Analyses were conducted in MEGA 4.0 appeared in the last few years. However the diversity, clinical [19]. andepidemiologicalsignificanceofthesetaxabacterianeeds Percent similarity and divergence coefficients of gltB gene in detailed study. Continuing the investigation of Bcc role in nucleotide/amino acid sequences among analyzed represen- nosocomial infections and using Multilocus Sequence Typing tatives of the Burkholderiales were performed by the use (MLST) as successful methodology in the epidemiology [12], of ClustalW2 [17], MEGA 6.0 [20], and MegAlign 5.05. we attempted to understand the variability of Burkholderiales For comparative sequence analysis and phylogenetic recon- in healthcare units. struction 10 extra gltB gene sequences of the Burkholderi- ales order representatives (Ralstonia solanacearum, Ralstonia 2. Materials and Methods pickettii, Acidovorax citrulli, Variovorax paradoxus, Bordetella bronchiseptica, Bordetella pertussis, and Lautropia mirabilis) 2.1. Materials. Biological samples used for sequencing data were retrieved from GenBank database (Table 3). The gltB are divided into two parts. The first part predominantly sequences of Pseudomonas aeruginosa have been used as represented by nosocomial strains and strains from cystic outgroup taxon (Table 3). fibrosis(CF)patientswasdescribedin[13] in detail. The second part contained some strains and mainly specimens of human sputum and aspirates from more than 300 CF 2.8. Phylogenetic Analysis. Phylogenetic analysis of Bcc was patients. performed based on allelic profile data of Bcc STs and translated concatenated sequences of seven MLST loci. Phy- 2.2. DNA Isolation. DNA for PCR analysis was extracted logenetic tree of analyzed representatives of Burkholderiales from the bacterial cultures as described previously [13]. DNA order was constructed by the use of gltB sequences. from sputum and aspirate was isolated according to the Analysis of profile data of Bcc STs was conducted using protocol of the Maxwell 16 Tissue DNA Purification Kit for the software packages SplitsTree21 [ ]. Maxwell MDX Instrument (Promega). The phylogenetic tree of 17 Bcc STs based on translated concatenated sequences of seven MLST loci was obtained 2.3. Species Identification. Identification of species was per- automatically by applying the neighbor-joining method [22]. formed by amplification and sequencing of 16S ribosomal The evolutionary distances between 17 Bcc STs were com- RNA gene (16S rDNA)fragmentwithprimers[14, 15]. puted using the -distance method [23]andwereevaluated through the units of the amino acid differences’ number per 2.4. MLST. For Multilocus Sequence Typing, a modified site. Evolutionary analyses were conducted in MEGA 6.0 scheme that allows differentiating 19 species of the Burkholde- [20]. Bootstrap analyses were performed with 500 replicates. ria cepacia complex (Bcc)wasused[16]. The scheme includes Phylogenetic tree of analyzed representatives of the the following targets for amplification: atpD,a chain of ATP Burkholderiales order was constructed by the use of synthase; gltB,alargesubunitofglutamatesynthase;gyrB,a neighborhood-joining, maximum likelihood, and maximum BsubunitofDNAgyrase;recA,recombinaseA;lepA,aGTP parsimony methods. binding protein; phaC,acetylCoAreductase;andtrpB,aB Genetic distances between microorganisms were evalu- subunitoftryptophanesynthase.ForDNAamplification,the ated by the use of Tamura 3-parameter model [24], which was following reagents were used: hot rescue DNA pol 5 units/ L, chosen as an optimal evolution distance model derived from PCR buffer 10x (N.F. Gamaleya Institute for Epidemiol- Modeltest based on the Akaike information criterion [25]. ogy and Microbiology MoH), dNTP5 mM (Medigen), and The evolutionary history was inferred by using the maximum primers (Evrogen). The modified amplification program was ∘ ∘ ∘ likelihood method based on the general time reversible the same for all targets: 95 C—10 min (95 C—30 s, 63 C— ∘ × ∘ model GTR+G. Initial trees for the heuristic search were 40 s, 72 C—1 min) 35, 72 C—5 min. obtained automatically by applying neighbor-joining and BioNJ algorithms to a matrix of pairwise distances estimated 2.5. PCR Products Sequencing. PCRproductsweresequenced by the use of the maximum composite likelihood approach according to the protocol of BigDye Terminator 3.1 Cycle andthenselectingthetopologywithsuperiorloglikelihood Sequencing kit for the Genetic Analyzer 3130 of Applied value. A discrete gamma distribution was used to model Biosystems/Hitachi. The electrophoretic DNA separation was evolutionary rate differences among sites (+G, parameter = performed in 50 cm capillaries with POP7 polymer. 0.8170). Maximum parsimony trees were constructed with 2.6. Nucleotide Sequence Analysis. Analysis of sequences and an algorithm implemented in MEGA 6.0. Bootstrap analyses alignment were made by the use of the program ClustalW2 were performed
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