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1 Centre d'Etudes du Bouchet (CEB), BP3, 91710 Vert le Petit, France
2 Écologie Microbienne, UMR 5557 CNRS, Bât. 741, Université Claude Bernard Lyon I, 69622 Villeurbanne cedex, France
3 Centre de Recherches du Service de Santé des Armées, BP87, 38702 La Tronche cedex, France
Correspondence
Vincent Ramisse
vramisse{at}ceb.etca.fr
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Published online ahead of print on 19 September 2002 as DOI 10.1099/ijs.0.02483-0.
The EMBL/GenBank accession number for the 16S rRNA gene sequence of CEB 01056 is AJ491304.
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), comprises 29 validly published species at the time of writing. It includes soil and rhizosphere bacteria, as well as plant and human pathogens (Gilligan, 1995). Among them are several species of particular interest in clinical microbiology. A review on Burkholderia taxonomy is available (Coenye et al., 2001c).
Burkholderia pseudomallei, the causative agent of melioidosis in humans, is a natural saprophytic micro-organism present in soils and stagnant waters in tropical regions (Dance, 2002). The ability of this species to invade and survive within free-living amoebae might affect its environmental survival and subsequent human exposure (Inglis et al., 2000). Melioidosis is transmitted by contact with contaminated soil or water through skin wounds, ingestion or inhalation (Benenson, 1995). Burkholderia mallei is responsible for glanders, a highly communicable disease of horses that is transmissible to humans (Benenson, 1995). This disease no longer occurs in the Western hemisphere, except for sporadic occupational cases (Srinivasan et al., 2001). Both B. pseudomallei and B. mallei are potential biological warfare and terrorism agents that necessitate efforts for preparedness, including rapid and accurate diagnostics (Rotz et al., 2002).
A major outcome of recent taxonomic studies of this genus has been the division of the Burkholderia cepacia complex into at least nine discrete genomic species, genomovars I–IX (Coenye et al., 2001a, b; Vandamme et al., 1997, 2000, 2002) that inhabit major environmental reservoirs but are frequently involved in nosocomial infections in patients with cystic fibrosis (CF) and other vulnerable individuals (Heath et al., 2002; Speert et al., 2002). B. cepacia complex infections contribute significantly to morbidity and mortality in CF patients. By 18 years of age, 80 % of patients harbour Pseudomonas aeruginosa and 3·5 % harbour B. cepacia (Rajan & Saiman, 2002). A study of 905 isolates from the B. cepacia complex recovered from 447 CF patients in Canada confirmed the prevalence of B. cepacia genomovar III (80 %), Burkholderia multivorans (formerly genomovar II) (10 %) and other genomovars of the B. cepacia complex or other Burkholderia species (9 %) (Speert et al., 2002). On the other hand, B. cepacia genomovar III is a common plant-associated bacterium (Balandreau et al., 2001). Moreover, human-pathogenic strains may not necessarily be distinct from environmental strains (LiPuma et al., 2002). There is some evidence that the health risks associated with infection are dependent on the nature of the genomovar, so the ability to differentiate genomovars is important for clinical microbiologists (Brisse et al., 2000; Henry et al., 2001; Mahenthiralingam et al., 2000). The accurate diagnosis of Burkholderia isolates is a challenge for the prevention and control of microbial infection caused by opportunistic pathogens. Moreover, the agricultural use of B. cepacia as a biopesticide for protecting crops against fungal diseases and as a bioremediation agent for decontamination of remanent pesticides is the subject of controversy (Holmes et al., 1998; Jones et al., 2001). The risks of the biotechnological uses of the B. cepacia complex and the ecology of the bacteria have been reviewed by Parke & Gurian-Sherman (2001).
Commercial bacterial identification systems are not always able to determine the genomovar status, nor accurately confirm the identification of B. cepacia isolates while differentiating them from closely related species. We have also observed ambiguous identification of some isolates of B. mallei and B. pseudomallei, thus rendering PCR- or antibody-based procedures valuable to confirm species identification (Bauernfeind et al., 1998; Steinmetz et al., 1999). A combination of phenotypic and molecular tests are recommended for differentiation among the genomovars of the B. cepacia complex (Henry et al., 2001). Nucleotide sequence variation within 16S rDNA is not sufficient to enable all genomovars to be discriminated by RFLP (Segonds et al., 1999). Nucleotide sequence analysis of the orthologous single-copy gene recA provides a means of identifying the current genomovars and newly delineated species within the B. cepacia complex (Mahenthiralingam et al., 2000), but single-locus-based identification schemes are risky because of the prevalence of lateral transfer (Mougel et al., 2002; Ochman et al., 2000).
The determination of the DNA–DNA relatedness of the whole genome remains an irreplaceable step in the delineation of bacterial species (Stackebrandt et al., 2002; Wayne et al., 1987). Nevertheless, there is a strong tendency to replace it because DNA–DNA reassociation experiments are not easily carried out, even though numerous methods with simplified and more reproducible steps have been described (Johnson, 1991). Moreover, the polyphasic taxonomic approach fulfils taxonomists' requirements by studying a wide range of genotypic and phenotypic information, but makes the identification procedure more complex (Rosselló-Mora & Amann, 2001; Vandamme et al., 1996). Developments in the field of high-density DNA arrays show great promise for bacterial systematics (Stackebrandt et al., 2002), but there is no routinely available application at present. As it is not easy for any laboratory to invest the efforts required to ensure a polyphasic approach for bacterial identification, and considering that species definition should still be based on determination of DNA–DNA relatedness, we felt the necessity to return to this approach but in a more simple manner. Here, we report a prospective work concerning a simplified way to implement species delineation, based on whole genomic DNA–DNA hybridization using DNA macro-arrays. This paper describes the method and its evaluation with previously characterized strains of the genus Burkholderia.
DNA macro-arrays were constructed from DNA extracted, as described by Yabuuchi et al. (1992), from reference strains of the Burkholderia species listed in Table 1. Burkholderia sp. CEB 01056, isolated in Centre d'Etudes du Bouchet (CEB) as a laboratory contaminant, was included in the study in an attempt to clarify its identification. The almost-complete 16S rDNA sequence (GenBank no. AJ491304) suggests that this isolate is closely related to the members of the B. cepacia complex, with similarity values ranging from 98·6 to 99·7 %. Staphylococcus epidermidis (an environmental isolate, CEB 01074) was used as an outgroup. A DNA macro-array consisted of a 18x18 mm square of positively charged nylon transfer membrane Hybond-N+ (Amersham Biosciences) onto which 15 different alkali-denaturated genomic DNAs (250 ng DNA in 10 µl 200 mM NaOH, 30 µM bromophenol blue per dot) and a blank (all reagents but no DNA) were spotted using the Hydra-96 Microdispenser coupled to its vacuum manifold (Robbins Scientific). Dots were 2 mm in diameter. Macro-arrays were produced in 10 batches, each consisting of 24 membranes (240 macro-arrays in total). Genomic DNA (100 ng) from all the strains listed (Table 1) was labelled, in a final volume of 20 µl, using 370 kBq [
-32P]dCTP (110 TBq mmol-1; Amersham Biosciences) and the Random Primed DNA Labeling kit (Roche Diagnostics), according to the manufacturer's instructions. Unincorporated nucleotides were removed by Sephadex G-50 filtration with the Multiscreen separation system MAHV-N45 (Amersham Biosciences) according to the manufacturer's instructions. Based on the observed mean of the incorporation rate (>50 %) and on the rate of DNA recovery after filtration (>65 %), the procedure routinely gives >65 ng labelled DNA with a specific activity of 2 MBq µg-1. Individual hybridization chambers consisted of 1·8 ml Nunc CryoTube vials (Nalge Nunc International) into which a DNA macro-array was introduced and allowed to pre-hybridize for 2 h at 65 °C under agitation (8 rotations min-1) with 500 µl Rapid-hyb buffer (Amersham Biosciences) before introduction of the purified probe (20 µl) and overnight hybridization under the same conditions. Free labelled DNA was removed by successive washing steps at 65 °C with 2x SSC, 0·1 % SDS then 0·1x SSC, 0·1 % SDS washing buffer (Amresco). DNA macro-arrays were scanned at 100 µm resolution using the Molecular Imager system GS-525 (Bio-Rad). For each DNA macro-array hybridized with a given labelled DNA, DNA–DNA relatedness was expressed as the hybridization signal ratio (R) between the maximum-intensity signal of each individual spot (Sx) and the total signal from the 16 spots (
S1–S16) and expressed as a percentage. All data in the text are R values. Standardized data were calculated using the formula Rstd=100(Sx-Smin)/(Smax-Smin), where Smin and Smax are respectively the minimum and maximum signal observed for an individual spot among all the spots present on the DNA macro-array. To avoid any confusion between classical DNA–DNA hybridization format (which is a true pairwise comparison where only two different DNAs are involved) and multiple DNA–DNA hybridization format on macro-arrays, we deliberately made the choice to display R, not Rstd. The usefulness of displaying one of these two parameters is discussed below. DNA macro-array hybridizations were repeated 4–10 times for a given labelled DNA. Values of Spearman's correlation coefficient (r) were calculated to find relationships between hybridization patterns of macro-arrays. Microsoft Excel software was used for statistical calculations.
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Resolution
The strains chosen for this study represent a portion of the variety of the genus Burkholderia (Table 1
). To investigate the DNA–DNA relatedness of these strains, labelled DNA from each reference strain was hybridized individually to a DNA macro-array that allowed multiple nucleic acid hybridization. R values were calculated to express the proportion of the signal measured from a spot, compared to the total signal measured for the 16 spots (Table 1). The unique Rmax value measures the homologous DNA–DNA reassociation, and the 15 remaining R values measure heterologous DNA–DNA reassociations. Consequently, Rmax should decrease as the DNA–DNA relatedness among strains increases. As expected, Rmax ranged from 81·74 % (Burkholderia glathei ATCC 29195T) to 27·89 % (Burkholderia plantarii LMG 9035T) for homologous pairs of DNAs. The higher Rmax values observed for labelled DNA of Burkholderia caribensis LMG 18531T, Burkholderia gladioli ATCC 10248T and B. glathei ATCC 29195T (respectively 79·72, 75·77 and 81·74 %), coupled to the weakness of R values for heterologous DNA pairing, may denote that these strains are distinct. Conversely, labelled DNA of other species yielded low Rmax values (27·89–57·66 %), but non-negligible R values, as the probable result of cross-hybridization of the probe to multiple positions on the array. The B. mallei ATCC 23344T probe yielded an Rmax value of 30·43±8·29 % (at the position of B. mallei) and markedly lower, an R value of 18·60±6·75 % at the position of B. pseudomallei ATCC 23343T. Similarly, the probe for B. pseudomallei ATCC 23343T yielded an Rmax value of 36·70±10·26 % (at the position of B. pseudomallei) and markedly lower, an R value of 25·58±7·19 % at the position of B. mallei ATCC 23344T. It is known that B. mallei and B. pseudomallei are closely related, to the extent that published DNA–DNA relatedness values, obtained by the classical fluorimetric method in microdilution wells, are higher than 90 % (Yabuuchi et al., 1992). However, the distinction between these two species is justified, based on pathogenicity. Originally included in the study design, Burkholderia thailandensis ATCC 700388T was not available when the work started. It is reasonable to assume that labelled DNA from B. thailandensis ATCC 700388T would have hybridized strongly to itself, to a lower extent to B. mallei and B. pseudomallei, and to a non-negligible extent to the members of the B. cepacia complex.
The symmetry of R values between B. mallei and B. pseudomallei was further investigated by determining R values with labelled DNA from two additional strains of B. mallei and 12 strains of B. pseudomallei (Table 2). The hybridization patterns observed for the three different strains of B. mallei are homogeneous (r=0·9578) and consistent with that of B. mallei ATCC 23344T (n=10). The R values observed for positions of B. mallei ATCC 23344T and B. pseudomallei ATCC 23343T are not significantly different, but both differ significantly from R values observed at other positions (i.e. other Burkholderia species). The hybridization patterns observed for the 12 different strains of B. pseudomallei are more homogeneous (r=0·9781). Moreover, significant differences of R values are observed for positions of B. mallei ATCC 23344T and B. pseudomallei ATCC 23343T on the array. For labelled DNA from both B. mallei and B. pseudomallei, the hybridization profiles at the remaining positions were similar. The R values are high for B. cepacia genomovar I ATCC 25416T, B. cepacia genomovar III LMG 12614, B. multivorans LMG 13010T, Burkholderia pyrrocinia ATCC 15958T, Burkholderia stabilis LMG 14294T, Burkholderia vietnamiensis LMG10929T and Burkholderia sp. isolate CEB 01056, and low at other positions. One could have expected that these cross-hybridizations should have yielded reciprocal values (by a significant increase of R at positions of B. mallei and B. pseudomallei) when using labelled DNA from the species B. cepacia genomovar I ATCC 25416T, B. cepacia genomovar III LMG 12614, B. multivorans LMG 13010T, B. pyrrocinia ATCC 15958T, B. stabilis LMG 14294T, B. vietnamiensis LMG 10929T and Burkholderia sp. isolate CEB 01056. Curiously, this was not the case, thus generating asymmetrical sections of the matrix (Table 1). This was also observed for B. plantarii LMG 9035T. The genome of B. cepacia ATCC 25416T (Rodley et al., 1995) and that of Burkholderia fungorum LB400 (Joint Genome Institute, http://www.jgi.doe.gov), both estimated at 8·1 Mb, are markedly larger than those of B. pseudomallei clinical isolate K96943, estimated at 6·5 Mb (Songsivilai & Dharakul, 2000) and B. mallei ATCC 23344T, estimated at 6·0 Mb (The Institute for Genomic Research, http://www.tigr.org). The homologous hybridizing proportion of the larger genomes will thus be correspondingly smaller than that of the smaller genomes, and may result in non-reciprocity. Such non-symmetry of matrices has already been observed for classical DNA–DNA homology studies (Lisdiyanti et al., 2002; Takeuchi & Hatano, 1998).
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): 40·12 %<Rmax<57·66 %, 3·69 %<R<12·29 % within this subgroup (mean 7·06±2·31 %), R<2·52 % with other species (mean 0·99±0·65 %). All these type strains are fully differentiated. This does not prejudge about the differentiation of B. cepacia members other than those tested herein.
DNA homology values relevant to the strains used herein have been obtained previously (Achouak et al., 1999; Coenye et al., 1999; Vandamme et al., 1997; Viallard et al., 1998; Yabuuchi et al., 1992) based on three different techniques: nuclease S1 (NS1), microfluorimetry (MF) and spectrophotometry (SP) (Fig. 1). These data and current R values were plotted and a linear regression curve was then calculated (Fig. 1). The r2 value of 0·740 demonstrates a weak positive correlation between DNA homology measures obtained by two radically different approaches. The slope of the tendency curve is therefore greatly affected by the value of R at 100 % DNA–DNA relatedness, because Rmax values are directly lowered by the extent of cross-hybridization at other positions on the array. The use of the standardized ratio Rstd eliminates this bias, thus strengthening the correlation (r2=0·904). The correlation between the NS1, MF, SP and macro-array methods by comparing DNA similarity values for several DNA pairs remains to be assessed. Presently available data are rare but encouraging, and highlight the asymmetry mentioned above (Table 3). The qualitative (e.g. diversity of species) and quantitative (e.g. number of species) nature of the genetic material spotted on the array remains to be addressed, to determine how it affects R values.
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). The ongoing identification of virulence determinants by subtractive hybridization will provide new tools in specific detection of these two species (DeShazer et al., 2001). Proposition of B. thailandensis (Brett et al., 1998), formerly a Burkholderia pseudomallei-like species that is able to assimilate L-arabinose contrary to B. pseudomallei, has been reinforced by 16S rDNA sequence analysis of numerous Ara+ or Ara- clinical and environmental isolates (Dharakul et al., 1999). Differentiation of Burkholderia species, most particularly those belonging to the B. cepacia complex, has been intensively addressed in the last few years, and a combination of phenotypic and molecular tests such as recA PCR and 16S rDNA RFLP are recommended for differentiation among the genomovars; the reliability of these approaches has been reviewed recently (Speert et al., 2002). All these methods target different cellular constituents and are thus complementary; however, none of them consider the whole genome. Delineation of four Pseudomonas species by DNA–DNA hybridization, which uses hundreds of genome fragments of each species spotted onto DNA micro-arrays, offsets laborious cross-hybridization but needs tedious cloning and handling of genome fragments (Cho & Tiedje, 2001). The overall homology between two genomes remains an important feature in the identification process for atypical isolates or species never encountered before. The sequencing of complete genomes has opened the way for micro-arraying nearly all ORFs of a bacterium, and for future evaluation of whole-genome homology in a gene-by-gene manner (Dziejman et al., 2002; Schoolnik, 2002).
DNA–DNA hybridization using genomic DNA macro-arrays looks like an interesting tool at the species level, and should be thoroughly addressed at the subspecies level by investigating several clinical and environmental isolates. Low intraspecies DNA–DNA hybridization values (up to 54 %) have been reported in several members of the B. cepacia complex, especially for genomovars I and III (Vandamme et al., 1997). Moreover, comparison of data in Tables 1 and 2 suggests that R values (at the B. mallei and B. pseudomallei positions) tend to overlap more as the number of strains examined increases. This suggests a low clonality of the population structure that could be a result of ‘rampant interspecific recombination’ (Ochman et al., 2000).
DNA–DNA hybridization using genomic DNA macro-arrays is simple and constitutes a straightforward approach for species identification. Automation of arraying enables the production of large quantities of macro-arrays, and the most demanding efforts consist of preparing the reference DNA stocks from type strains and updating macro-arrays for their species content as novel species are described. Once available, these macro-arrays could be used to investigate the nature of numerous unknown labelled DNAs extracted from various sources. There are at least two potential applications in whole-genome-based bacterial identification, as an initial step preceding the use of more appropriate or targeted tests. The first is the species identification of a large number of strains isolated from clinical infection or recovered from natural environments. Identification and monitoring of bacteria by reverse sample genome probing (RSGP) has already been described, for example in soil (Léveillé et al., 2001; Shen et al., 1998). The second application concerns the monitoring of bacteria in the environment by RSGP and a possible way to analyse spatio-temporal variations in bacterial communities within a biotope. DNA–DNA hybridization using genomic DNA macro-array analysis may be modified to use non-radioactive labelling and thus become a high-throughput alternative for existing DNA–DNA hybridization methods.
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ACKNOWLEDGEMENTS |
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