a stenotrophomonas maltophilia multilocus sequence typing
TRANSCRIPT
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A Stenotrophomonas maltophilia Multilocus Sequence Typing Scheme 4
for Inferring Population Structure 5
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8
Sabine Kaiser,1,2
Klaus Biehler,1 Daniel Jonas
1,* 9
10
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Department of Environmental Health Sciences, University Medical Centre Freiburg 1 and 13
Institute of Microbiology, Faculty of Biology, University of Freiburg, Freiburg, Germany 2 14
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* Corresponding author: Dr. Daniel Jonas, Institute of Environmental Medicine and Hospital 17
Epidemiology at the University Medical Centre Freiburg, Breisacher Str. 115 b, 79106 18
Freiburg, Germany; fon: +49 761 270 8273; fax: +49 761 270 8203; e-mail: 19
21
Word count for the body of the text: 5479 22
Abbreviated title: MLST for S. maltophilia population structure analyses 23
Potential conflicts of interest. All authors report no conflicts of interest relevant to this 24
article. 25
Copyright © 2009, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.J. Bacteriol. doi:10.1128/JB.00892-08 JB Accepts, published online ahead of print on 27 February 2009
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ABSTRACT 26
27
Stenotrophomonas maltophilia is an opportunistic, highly resistant and, ubiquitous pathogen. 28
Strains have been assigned to genogroups using Amplified Fragment Length Polymorphism 29
(AFLP). Hence, isolates of environmental and clinical origin predominate in different groups. 30
An MLST scheme was developed using a highly diverse selection of 70 strains of various 31
ecological origins from seven countries on all continents including strains of the 10 32
previously defined genogroups. Sequence data were assigned to 54 sequence types (ST) based 33
on seven loci. Indices of association for all isolates and clinical isolates of IA = 2.498 and 34
2.562 indicated a significant linkage disequilibrium, as well as high congruence of tree 35
topologies from different loci. Potential recombination events were detected in one-sixth of 36
all ST, Calculation of the mean divergence between and within predicted clusters confirmed 37
previously defined groups and revealed five additional groups. Consideration of the different 38
ecological origins showed that 18 out of 31 respiratory tract isolates, including 12 out of 19 39
isolates from cystic fibrosis (CF) patients, belonged to genogroup 6. In contrast, 16 invasive 40
strains isolated from blood cultures were distributed among nine different genogroups. Three 41
genogroups contained isolates of strictly environmental origin that also featured high 42
sequence distances to other genogroups, including the S. maltophilia type strain. 43
Using this MLST scheme, isolates can be assigned to the genogroups of this species in order 44
to further scrutinize the population structure of this species and to unravel the uneven 45
distribution of environmental and clinical isolates, obtained from infected, colonised or CF 46
patients. 47
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INTRODUCTION 48
Stenotrophomonas maltophilia is ubiquitous in nature. It has, for instance, been isolated from 49
the rhizosphere of various plants and animals (14;25;35). Due to its tolerance against 50
cadmium and its ability to degrade xenobiotic compounds, it has been proposed for 51
remediation of contaminated ground (9;37). Increasingly, it is being isolated from 52
immunosuppressed individuals, intensive care and cystic fibrosis (CF) patients, and is 53
resistant to many antimicrobial agents (16;17;69). However, the role of this opportunistic 54
pathogen as an innocent bystander or causative agent often remains unclear (28) and little is 55
known about its virulence factors (31;48). 56
Recently, novel Stenotrophomonas species were described: Stenotrophomonas nitritireducens 57
sp. nov. (22), Stenotrophomonas acidaminiphila (3), Stenotrophomonas rhizophila (73) and 58
Stenotrophomonas africana sp. nov. (19). However, the latter is a synonym of S. maltophilia 59
(10). 60
Using amplified fragment length polymorphism (AFLP) fingerprinting and DNA-DNA 61
hybridizations, remarkable diversity has been shown to exist among S. maltophilia isolates 62
recovered from both the environment and human clinical samples. This species can be 63
subdivided into 10 AFLP genomic groups (33) that comprise to varying extents both clinical 64
and environmental isolates. Similarly, different genomic groups of the genus 65
Stenotrophomonas can be distinguished using restriction fragment length polymorphisms 66
(RFLP) in the gyrB gene (11). Surprisingly, 36 out of 40 CF isolates are grouped in just two 67
clusters. However, no such differences were seen in other investigations using PFGE after 68
DraI digestion, molecular typing by BOX PCR or temperature-gradient gel electrophoresis of 69
16S rRNA PCR fragments (7). Later DNA sequence analyses of the 16S rRNA revealed three 70
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clusters, with grouping of the strains according to their sources of isolation and signature 71
sequences in the region V1, which distinguishes clinical from environmental isolates (44). 72
The objective of this study was to develop an MLST scheme on the basis of a diverse strain 73
collection comprising of isolates from different ecological origins, continents and DNA-74
hybridization groups (33). We then employed this scheme to start initial analyses of the 75
population structure of this species. 76
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MATERIALS AND METHODS 77
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Stenotrophomonas spp. culture collection. Sixty-seven different S. maltophilia isolates from 79
five different collections were selected with the aim as far as possible to cover the full genetic 80
breadth of this species with only a limited number of analyzed strains (Table 1). Apart from 81
S. maltophilia ATCC 13637T (named 886_pat), type strains of three other species were 82
included - S. africana ATCC 700475T, S. nitritireducens ATCC BAA 12
T and 83
S. acidaminiphila ATCC 700916T. The strains were designated with a number and a suffix to 84
indicate species other than S. maltophilia, e.g. S. africana (afri), S. nitritireducens (nitri) and 85
S. acidaminiphila (acid) and origin e.g. patient (pat), conjunctivitis (conj), sputum (sputum), 86
tracheal secretion (ts), respiratory tract specimen from cystic fibrosis patients (CF), blood 87
culture (bc), pus, cerebro-spinal fluid (CSF), outbreak (out) in intensive care units (ICU), 88
hospital environment (hosp.env) and environmental origin unrelated to a health care setting 89
(env). 90
First, 12 clinical strains were received from five different hospitals participating in the 91
German project Surveillance of Antimicrobial Use and Antimicrobial Resistance in Intensive 92
Care Units (SARI). Ten of these were pairs of isolates that had been isolated during different 93
outbreaks lasting for at least 77 to 308 days, and in each case had identical Amplified 94
Fragment Length Polymorphism (AFLP) (data not shown) (64). 95
Second, 19 strains were isolated from epidemiologically non-associated cystic fibrosis 96
patients in England (n = 13) and Germany (n = 6), and were obtained from Dr. T. Pitt, 97
Laboratory of Hospital Infection, Health Protection Agency, Colindale, London, GB and from 98
Dr. Hogardt at the German Reference Center for Cystic Fibrosis, Max von Pettenkofer-99
Institute, Munich. 100
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Third, 13 strains were obtained from the Belgian Co-ordinated Collections of Microorganisms 101
(BCCM), Ghent University, including the type strains of the four species and one 102
representative from each of the 10 genogroups (LMG No. 958, 10853, 10871, 10873, 10874, 103
10879, 10991, 11089, 11108, 11114), as defined by L. Hauben et al. (33). 104
Fourth, 14 strains were provided by Dr. N. Foster, The University of Western Australia, 105
Crawley, as a collection with different gyrB RFLP analyzed as described (23). 106
Finally, 12 isolates of strictly environmental origin were obtained from Dr. G. Berg, 107
Department of Environmental Biotechnology at the Graz University of Technology, Graz, 108
Austria. These stemmed either from the rhizosphere of plants or from the sea and had no 109
apparent anthropogenic origin. 110
In addition, data from the K279a and R551-3 genome sequencing projects were included for 111
the purpose of sequence analysis in silico. These sequence data were produced by the 112
Stenotrophomonas maltophilia Sequencing Group at the Sanger Institute (12) and can be 113
obtained at ftp://ftp.sanger.ac.uk/pub/pathogens/sma/ (Dec 10 2004) and from the US 114
Department of Energy Joint Genome Institute http://www.jgi.doe.gov/. 115
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Culture of isolates and preparation of DNA. Bacterial strains were maintained at –70°C in 117
defibrinated horse blood and cultured on 5% columbia sheep blood agar. Species 118
identification was confirmed biochemically by use of api®20 NE or VITEK classic (both 119
bioMérieux, Nürtingen, Germany) and 5’-end sequencing of the 16S rRNA gene of all strictly 120
environmental isolates (56). Purified DNA was prepared by means of the Qiagen Blood Kit 121
(Qiagen, Hilden, Germany). 122
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Locus selection. Several potential loci were identified using markers already successfully 124
employed in MLST schemes developed for other species such as Pseudomonas aeruginosa, 125
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Pseudomonas syringae, Burkholderia pseudomallei, Burkholderia cepacia and Acinteobacter 126
baumannii (5;6;13;27;61). The available sequence data were used for BLAST analysis with 127
data from the K279a genome sequencing project (2). These sequence data were produced by 128
the Stenotrophomonas maltophilia Sequencing Group at the Sanger Institute (12). 129
The entire putative coding sequences of the housekeeping genes were identified by use of the 130
Artemis genome viewer and annotation tool (58). The seven genes finally selected for use 131
with the MLST scheme were atpD, gapA, guaA, mutM, nuoD, ppsA, and recA. 132
133
Amplification and sequencing of loci. Using the primer3 software tool (57), PCR primers 134
were designed for the loci based on different regions of the putative coding sequences, which, 135
as work progressed, revealed themselves to be comparatively conserved. The primer 136
sequences are shown in Table 2. Practical annealing temperatures of primer pairs were 137
determined on a gradient cycler (FlexCycler, Analytik Jena, Jena, Germany). They were used 138
both for sequencing and amplification. 139
The PCR conditions were as follows: initial activation of the Taq-DNA-Polymerase (Ampli 140
Taq Gold, Applied Biosystems, Darmstadt, Germany) for 9 min at 95°C, followed by 30 141
cycles of 20 sec denaturation at 94°C, annealing for 1 min at the appropriate annealing 142
temperature (Tann) and extension for 50 sec at 72°C (Table 2). The program ended with a 5 143
min fill in step at 72°C. Two separately generated amplicons for forward and reverse 144
sequencing were purified from unincorporated nucleotides using Exonuclease I / Phosphatase 145
(USB, Staufen, Germany) according to the manufacturer’s protocol. The purified template 146
was quantified by using the Nanodrop ND-1000 spectral photometer (Peqlab Biotechnologie 147
GmbH, Erlangen, Germany). The sequencing reaction was performed with 20 ng DNA and 148
the BigDye Terminator Ready Reaction Mix (v1.1, Applied Biosystems). Cycle sequencing 149
with standard conditions was used for primers with Tann >60°C. In the case of lower Tann, 150
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denaturation for 10 sec at 96°C was followed by annealing at Tann for 10 sec and subsequent 151
elongation for 4 min at 60°C. Unincorporated dye terminators were removed by precipitation 152
with absolute ethanol. The air dried reaction product was resuspended in 20 µl of Hi-Di 153
formamide and loaded, separated and detected on an ABI PRISM 310 genetic analyzer using 154
POP-6 polymer and a 61 cm genetic analysis capillary (Applied Biosystems). 155
156
Allele and ST assignment. The sequencing files were assembled from the resultant 157
chromatograms with the Staden suite (version 1.7.0) of computer programs (66;67). The 158
database can be accessed at http://pubmlst.org/smaltophilia/. 159
160
Nucleotide sequence accession numbers. The GenBank accession numbers for the 161
sequences reported in this study are: for atpD, EU983582-EU983651; for gapA, EU983652-162
EU983721; for guaA, EU983722-EU983791; for mutM, EU983792-EU983861; for nuoD, 163
EU983862-EU983931; for ppsA, EU983932-EU984001; for recA, EU984002-EU984071. 164
165
Phylogenetic analysis. For statistical analysis of allele profiles and sequence data, START2 166
was employed to calculate GC-content, frequencies of alleles, number of variable sites and 167
dN/dS-value (34). The index of association (IA) was calculated (43) and significance was 168
proven by an observed variance greater than the maximum variance in 1,000 random trials 169
(p < 0.001) (http://linux.mlst.net/link_dis/index.htm). 170
BURST analysis was done with the tool provided at the pubmlst site mentioned above with a 171
group definition of profile match at four loci to any other member of the group. 172
Cluster analysis by the Neighbor-Joining (NJ) method with HKY85 model of DNA 173
substitution and 200 bootstrap replications was done employing PAUP 4.0 b 10 (68). The 174
value of similarity was calculated as one minus the corresponding distance-value. For proof of 175
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separate sequence similarity clusters, the k-parameter was calculated as described (8), which 176
is the ratio of the between-group divergence to the mean of the within-group divergence 177
levels (52). A ratio above 2 indicates that the groups can be considered to be separate 178
sequence similarity clusters (8). 179
The tree-presentation of phylogenetic data was obtained with TreeView 1.6.6 (50) with the 180
corresponding sequence data of Xanthomonas campestris pathovar campestris Xcc 8004 181
[GenBank accession number CP000050] for rooting as an outgroup (55). 182
Pearson correlations of DNA HKY85 distance matrices were tested for significance by use of 183
the Mantel’s test implemented in PopTools version 3.0.6 (http://www.cse.csiro.au/poptools) 184
according to a described algorithm (38). 185
The test of congruence was performed to compare the topology of the Neighbour-Joining 186
trees from different loci as described (20;59). They were constructed by use of the HKY85 187
model of DNA substitution, implemented in PAUP (21;32). Trees were optimized for 188
transition to transversion ratio (Ts/Tv), alpha parameter and branch-lengths. For each gene, 189
the log likelihood score (-ln L) and the log likelihood differences (∆-ln L) between the 190
corresponding values of the remaining six other loci were computed after optimization of 191
values for Ts/Tv, alpha parameter and branch-lengths. Two-hundred random trees were 192
computed for each gene and optimized again as described above. The ∆-ln L between the 193
random trees and the NJ tree of each gene were calculated. Trees revealing ∆-ln L above the 194
2nd
lowest value of the 200 random trees, i.e. within the 99th
percentile, were considered to be 195
non-congruent. 196
Horizontal gene transfer (HGT) was investigated by use of multiple approaches to limit the 197
risk of identifying false recombination events or overlooking the occurrence of true 198
recombinations (53;54). Calculation of recombination tests was performed with the 199
RDP3Beta26 program (41) by applying the following algorithms: RDP (39), GENECONV 200
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(49), Chimera (54), MaxChi (42), BootScan (40), and SiScan (26). The concatenated data 201
(atpD - gapA - guaA - mutM - nuoD - ppsA - recA) of all ST were imported into RDP in fasta 202
format. The following settings were used for all of the methods: (i) sequences were linear, (ii) 203
sequences in the alignment were screened in triplets, and (iii) statistical significance was set 204
to P = 0.001 with Bonferroni correction for multiple comparisons. In Geneconv, the 205
parameter GSCALE was set to 1. In MaxChi and Chimaera, a sliding window was used, and 206
the number of permutations was 1,000. Only recombination events detected by more than two 207
methods were considered further. 208
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RESULTS 209
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Delineation of Stenotrophomonas spp. Analysis of the HKY85 corrected distance-matrix for 211
the concatenated sequences from all seven loci revealed an average similarity (expressed as 212
percentage of 1 – distance-value) of 95.9% (± 0.03% S.E.) for all S. maltophilia strains. The 213
average similarity for the S. africana type strain in comparison to all S. maltophilia strains 214
was higher at 96.3% (± 0.21% S.E.). In contrast, comparison of all S. maltophilia strains with 215
the S. nitritireducens type strain and the S. acidaminiphila type strain revealed a lower 216
similarity of 89.9% (± 0.06%) and 89.7% (± 0.05%). Thus, in all subsequent analyses the 217
S. africana strain was considered to be a member of the S. maltophilia species. 218
219
Allelic variation in S. maltophilia. Sequence data analysis of all 70 S. maltophilia strains 220
revealed 54 STs (Table 1). Comparison of isolates from five different outbreaks showed the 221
stability of the allelic profile over at least 77 to 308 days (Table 1). It should be noted that 222
outbreak-isolates from two ICUs located in different German states belonged to the same ST 223
29. In the following analysis, data from all five subsequent outbreak-isolates were omitted. 224
Analysis of the data of the 54 STs revealed that the number of allele types ranged from 38 for 225
mutM to 53 for guaA (Table 3). There were considerable percentages of variable sites ranging 226
from 11.9% for atpD to 37.0% for mutM. The Simpson’s index of diversity was always ≥ 227
0.971, which is indicative of a highly discriminatory typing method. The low dn/ds ratios 228
indicate the absence of a strong positive selection pressure at these loci and the suitability of 229
these loci for population genetic studies. 230
231
Linkage disequilibrium. In order to assess the clonality of S. maltophilia, the index of 232
association (IA) was calculated for different groups of isolates. This measure was significantly 233
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different from zero, which indicates a linkage disequilibrium, if all 65 strains were considered 234
or all 48 clinical isolates (Table 4). The IA differed from zero in regard of all 54 STs, all 41 235
STs of clinical isolates or all 17 environmental isolates, but did not reach statistical 236
significance in these analyses, because the maximum variance in 1,000 random trials 237
exceeded the observed variance. 238
239
Congruence of the different loci. In order to compare the sequence similarities in all seven 240
loci, HKY85 matrices were calculated and compared by Pearson correlation (Table S1 in the 241
supplemental material). Randomization of pair wise correlated matrices employing the 242
Mantel’s test revealed significant correlation coefficients in all cases, i.e. above the 95.50% 243
percentile of 1,000 permutations, except for the comparison mutM - guaA. In all possible 244
combinations, the mutM matrix displayed the lowest correlation coefficients followed by 245
values of the guaA matrix. The only exception was ppsA, which had the second lowest 246
coefficient when correlating with nuoD. This is one indication of marked differences in the 247
topology of the mutM and guaA trees compared with the five other loci. Trees of the seven 248
loci of all 54 ST can be depicted (Figure S1 in the supplemental material). 249
To test for congruence using the maximum likelihood approach, an Unweighted Pair Group 250
Method with Arithmetic mean (UPGMA) dendrogram was constructed using allelic profiles 251
and was subsequently truncated at a linkage distance of 0.55, so that 49 lineages were 252
included. A single strain was selected at random to obtain a set of isolates distinctly related to 253
each other. Trees revealing log likelihood differences below the 3rd
lowest value of the 200 254
random trees, i.e. not within the 99th
percentile, were considered as congruent. This applied to 255
the majority of the loci except for the guaA tree when comparing with mutM sequences and 256
vice versa (Table S2 in the supplemental material). 257
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HGT detection. The output of the HGT analyses performed using the RDP3 package is 259
summarized in Table S3 of the supplemental material. The occurrence of a potential HGT 260
event was accepted only if validated by at least three distinct methods and sustained by strong 261
statistical support. This approach revealed four events, involving nine out of 54 ST. Three 262
gene fragments (guaA, mutM, nuoD) concatenated in MLST profiles were affected by HGT 263
events. In two HGTs events, breakpoints were located within a single locus, in two other 264
events breakpoints were limited to pairs of genes arranged consecutively. Recombinant ST 265
were found in strains belonging to the environmental groups #5, #8, #9 and #10. An analysis 266
of alleles involved in single HGT events revealed mut-4 involved in all six ST involved in the 267
event 1 and 4. 268
269
Genogroups in S. maltophilia. The Based Upon Related Sequence Types (BURST) analysis 270
for clonal complexes revealed three groups of Triple Locus Variants (TLV) comprising (i) ST 271
17 and 30 belonging to genomic group #7, (ii) ST 1, 26 and 27 belonging to genomic group 272
#6, and (iii) ST 2 and 43 also belonging to genomic group #6. All the strains of these STs 273
were of clinical origin. 274
The Neighbor-Joining tree presentation was chosen (Figure 1) for cluster analysis of all 70 275
S. maltophilia strains.. The 10 different genogroups defined by Hauben et al. (33) could be 276
delineated on the basis of all seven loci. We were able to use the same numbering of 277
genogroups by inclusion of strains which had already been assigned in that previous study. 278
Additional groups were indicated with letters. None of the other isolates investigated grouped 279
together with strain 888_env, formerly assigned to AFLP genogroup 10. Sequence divergence 280
between different genogroups and calculated k-parameters are depicted in Table S4 and S5 in 281
the supplemental material. On average, sequence divergence between different genogroups 282
was as high as 0.048 (S.E. ± 0.002) with the highest values ranking in the order of genogroups 283
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#8, A, #9 and 5. All the groups could be separated by a significant ratio of the between-group 284
divergence to the mean of the within-group divergence above 2, except when comparing 285
genogroup #2 with #3 – 6, B, D and E. Moreover, five additional groups became apparent, 286
which we designated with letters. S. africana belonged to group #4, along with four other 287
S. maltophilia strains. Two isolates, 470_bc and 639_CF could not be assigned to any 288
genogroup. 289
Twenty-two (44%) out of 50 clinical isolates originating from patients in seven German cities 290
and four other countries were clustered in group #6, which consisted of clinical isolates only. 291
Twelve (63%) out of 19 strains isolated from epidemiologically non-associated cystic fibrosis 292
patients also belonged to this group. Clinical invasive isolates originating from blood cultures 293
or CSF were distributed more evenly among nine genogroups, with just three (18.7%) out of 294
19 strains belonging to genogroup #6. The three hospital environment strains were found in 295
three different groups (#2, D and E), which also included clinical strains. Three genogroups, 296
though containing a limited number of isolates, exclusively comprised of strains of 297
environmental origin: genogroups #5 (n = 4), #8 (n = 6) and #9 (n = 3). 298
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DISCUSSION 299
In the past decades, there have been several changes in the taxonomy of Stenotrophomonas 300
spp. (51). At present, this genus comprises of nine species, five of which, S. dokdonensis, 301
S. humi, S. koreensis, S. rhizophila and S. terrae, were not available for the study presented 302
here. The delineation of S. africana from S. maltophilia has been on debate (10;19). This 303
work also confirms that S. africana is a synonym for S. maltophilia. 304
S. maltophilia can be isolated from a wide variety of environments and geographical regions, 305
and may occupy various niches such as soil, rhizosphere, water and food (17). S. maltophilia 306
has emerged in many hospitals as an important nosocomial pathogen, especially in 307
immunocompromised patients (63). Although this species was previously considered to have 308
limited pathogenicity, reports indicate that infection with the organism is associated with 309
significant morbidity and mortality, particularly in severely compromised patients (46). Yet, 310
the clinical importance of this opportunistic pathogen as a mere colonizer or infectious agent 311
often remains unresolved. There is an ongoing debate about the role of this species in later 312
stages of cystic fibrosis. At any rate, isolation of S. maltophilia in CF patients tends to be 313
associated with more advanced disease (15;28;30). Treatment of S. maltophilia infection is 314
also complicated by its inherent resistance to many broad-spectrum agents, including 315
carbapenems, which to a considerable extent are mediated by multidrug efflux pumps (1) and 316
broad spectrum beta-lactamases (4). The emerging resistance against 317
trimethoprim/sulfametoxazole, which is one of the few remaining treatment options, is of 318
major concern (69). Currently, little is known about the virulence factors of S. maltophilia, 319
such as factors for adherence to plastics, an extracellular protease and a phage encoded zonula 320
occludens like toxin (31;47;72). More recently, a diffusible signal factor (DSF) has been 321
described which is assumed to control the expression of virulence and antimicrobial resistance 322
as a cell-cell signaling factor by use of a two-component regulatory system (24). 323
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Genotyping methods have been used successfully in the molecular epidemiology of 324
S. maltophilia. Many typing approaches have revealed that this species is of high 325
genodiversity. Genotyping of isolates from hospitalized cystic fibrosis and non- cystic fibrosis 326
patients by pulsed-field gel electrophoresis (PFGE) or RAPD-PCR revealed a high diversity 327
with changes in the strains consecutively isolated from CF patients (18;36;70;71). Even a 328
Multilocus Enzyme Electrophoresis scheme (MLEE) has been proposed for investigations of 329
hospital epidemiology (62). However, this scheme could not be used here, partly because it is 330
based on markers such as peptidases or elastases, which can not be assumed to be neutral for 331
selection, while other markers we could not retrieve unambiguously from the genome 332
sequence databases. 333
There have been several attempts to delineate the genetic groups of related strains. 334
S. maltophilia could be subdivided into three clusters by use of 16S rDNA sequences 335
signatures in the V1 (positions 73-97) and V6 domain (positions 451 – 482) (44). A 336
comparative investigation of clinical isolates revealed six 16S rRNA groups based on variable 337
positions in the positions 41 – 109, and four so called phylogenetic groups based on the 338
smeD - smeT intergenic sequences (29). This region is assumed to be involved in regulation of 339
the smeDEF multidrug efflux pump genes (60). The most extensive work was done by 340
Hauben et al., where a highly diverse strain collection of different origins was delineated into 341
10 genomic groups by use of AFLP: The results were in part confirmed by 16S rDNA 342
sequencing and DNA – DNA hybridization experiments (33). However, 18 out of 107 343
investigated strains were non-groupable. In a different approach, nine different genomic 344
groups of the genus Stenotrophomonas could be distinguished, on the basis of restriction 345
fragment length polymorphisms (RFLP) in the gyrB gene (11). Surprisingly, 36 out of 40 346
isolates from CF patients were grouped in just two clusters, group B and group C. In 347
summary, on the basis of RFLP, there is increasing evidence of the existence of particular 348
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subgroups of different ecological origin and clinical importance within this bacterial species 349
(11;33). However, the impact of few recombination events can be sufficient to obliterate the 350
phylogenetic signal in the gene trees of many species (20). Thus, for future investigation of 351
isolates, this study aimed to develop an MLST scheme to cluster different genotypes in 352
phylogenetically meaningful groups. 353
The scheme was developed on the basis of a restricted set of carefully selected strains. This 354
diverse strain collection included strains from 10 previously defined genogroups, type strains, 355
and 17 isolates of non-anthropogenic origin. Also, for the purpose of sequence analysis, data 356
were included from two genome sequencing projects of strains K279a and R551-3; despite 357
changes in the latter sequence data being conceivable before final publication. However, 358
grouping of the environmental isolate R551-3 together with other environmental isolates in 359
genogroup #5 allowed use of these preliminary data to appear plausible, although allelic types 360
were unique in the dataset of all 7 loci investigated so far. 361
Despite the fact that the number of isolates investigated is still limited, analysis of the 362
individual loci revealed high diversity, reflected by a high number of allele types and variable 363
sites, as well as by a Simpson’s index of diversity of at least 0.971 in all seven sequences. 364
However, one should bear in mind that the strains had already been selected from different 365
collections on the basis of maximum diversity available to us. Furthermore, it is possible that 366
RFLP-based methods, like AFLP or PFGE, which in contrast to MLST or SNP analysis of 367
core genome genes also cover the entire accessory genome, give greater insight into 368
epidemiological associations or pathoadaptive processes by gain or loss of genomic islands 369
and virulence factors, as has for instance been described for the recombinant species of 370
P. aeruginosa (45). 371
Finally, the low dn/ds ratios indicate the absence of a strong positive selection pressure at the 372
chosen loci and their suitability for population genetic studies. 373
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Another distinct feature is the apparent difference in the tree topology of the different loci. 374
Whereas most had a congruent topology, mutM and guaA differed, as demonstrated by the 375
low correlation coefficient of the computed distance matrices. Such variations have been 376
described within the genome of a species, for instance in Haemophilus influencae (20). 377
In a first approach, we attempted to identify clonal complexes (CC) with the established 378
BURST algorithm. Despite the restricted and highly diverse strain collection, on a relaxed 379
definition of at least four identical loci we could already identify three complexes, two of 380
them originating within the genogroup #6, which included the largest number of isolates. 381
These findings were also supported by the neighbouring phylogenetic tree-presentation 382
(Figure 1) of those genogroup #7 strains (889 conjunctivis, 909 bc) as well as #6 strains (645 383
CF, 673 CF and 441 ts out, 681 CF, K279a). 384
There were three indications for clonality in this species. First, we found a high and 385
significant Pearson correlation between the distance matrices calculated in the different loci 386
except for mutM and guaA. One conceivable reason for this might be the high number of 387
variable sites in both loci. However, two other loci with a similarly high number of variable 388
sites (recA and ppsA) revealed high correlation coefficients. This fact constrains the argument 389
of a low correlation due to a high number of SNP, at least as it being the only reason. Of note, 390
mutM and guaA were the most frequently affected loci in RDP-analyses. 391
Second, for various subsets, calculation of the IA revealed values different from zero, which 392
tested significant in regard of all 65 copy-strain-cleared isolates and all 48 clinical isolates. 393
The significant IA of all 65 isolates in comparison to a non- significant IA of all 54 ST could be 394
in line with a clonal epidemic population structure. Consideration of all 41 ST of the clinical 395
isolates resulted in an IA of 1.216. However, this was not significant in contrast to the IA of all 396
48 clinical isolates, because the observed variance was smaller than the maximal trial 397
variance. This observation could also be in accordance with a clonal epidemic population 398
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structure with the successful genomic group #6 or due to a number of tested strains simply too 399
small to reach statistical significance. The absence of significant evidence for a linkage 400
disequilibrium in the 17 isolates of environmental origin with an IA of 2.911 can simply be 401
due to the low number of isolates tested. 402
Finally, the statistical test of congruence using the maximum likelihood approach, which in 403
contrast to BURST analysis does not require a large MLST dataset, pointed toward a clonal 404
population structure, again with the exception of both loci mutM and guaA. 405
However, based on today’s species definition of S. maltophilia, there are conceivable 406
limitations to the high overall linkage disequilibrium calculated in this study, particularly in 407
consideration of the extensive sequence divergence of different genogroups, e.g. #5, #8 and 408
#9 (Table S4 of the supplemental material). Future studies could delineate further species 409
within the boundaries of the species designated as belonging to S. maltophilia today. In this 410
case, fixed differences between these new species and a low inter-species recombination rate 411
could prove to be the reason for an apparently high overall linkage disequilibrium of what is 412
considered to be S. maltophilia today. However, it should be noted that we were also able to 413
show a significant high IA for the clinical isolates including genogroup #6 with the species 414
defining type strain and other less distantly related genogroups. 415
Furthermore, data were scrutinized for putative recombination events by employing different 416
detection algorithms in the RDP suite. Our analyses identified four independent events of 417
HGT involving one-sixth of all analyzed ST profiles. Interestingly, these all involved isolates 418
of genogroups #5, #8, #9 and #10 with a high DNA sequence distance to the species defining 419
type strain ATCC 13637T (886_pat) in genogroup #6. These findings were corrobated by at 420
least four independent methods for detection of the HGT. Therefore, it seems rather unlikely 421
that the occurrence of true recombinations was misidentified or overlooked. Nevertheless, 422
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future investigations of considerably larger numbers of ST might drastically improve the 423
statistical power of detection by the suite of methods applied here (53;54). 424
In the end, we were able to confirm previously described genogroups and identify new ones. 425
It is important to note that genogroups defined on the base of DNA-similarities can comprise 426
strains with entirely different allelic profiles, which already change by introduction of one 427
SNP in each loci with a remaining sequence similarity of >99 %. For instance, both 428
genogroup #6 strains 325 and 396 differed in 31 SNPs out of 3591 nucleotides, which varied 429
from one SNP in gapA to 11 in the guaA locus. Despite entirely different allelic profiles both 430
strains have a sequence similarity of 99.14%. This MLST scheme provides some further 431
evidence that the distribution of isolates from the non-anthropogenic environment, like the 432
rhizosphere or water apparently differs from that of humans. Like previously described 433
genogroups (33) containing isolates of predominantly (>75%) or entirely clinical origin (#2, 434
#6 and #7) or of environmental origin (#5, #8 and #9), the study presented here also found the 435
same genogroups comprising of exclusively isolates of the corresponding different ecological 436
origins. This is reminiscent of niche separation of different ecotypes. Yet, to some extent, the 437
small number of isolates (<10) assigned to the particular genogroups is a clear limitation of 438
both studies. In addition, this MLST scheme confirmed a genetical relatedness among the 439
majority of genotypes found in isolates from CF patients (11). In this previous study based on 440
a gyrB RFLP, 90% of all the 40 CF isolates were grouped in just two clusters. However, the 441
delineation in the study appeared to be rather fuzzy, because group B corresponded to the 442
AFLP groups 1 and 3, and group C included the AFLP groups 2, 4, 6, and 7, as well as the 443
type strains of S. maltophilia, S. africana and S. rhizophilia. More precisely, our study 444
assigned 12 out of 19 isolates from epidemiological non-associated CF-patients to genogroup 445
#6. The remaining CF isolates belonged to five other genogroups and one could not be 446
assigned to any of the groups. Of note, genogroups #6 included further respiratory tract 447
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isolates from three different hospital outbreaks and the S. maltophilia type strain 448
ATCC 13637T. In contrast, this typing scheme could not provide evidence for particularly 449
virulent, i.e. invasive genogroups. Sixteen isolates from blood cultures or CSF isolates were 450
found among eight genogroups. One might speculate that these strains gave raise to invasive 451
infections, due mainly to the impaired immune response of the host and thus without need for 452
particular virulence factors in the pathogen. The association of genogroup #6 isolates with 453
respiratory tract specimens and CF or ICU patients may lead to the hypothesis that these 454
strains are particularly adapted to colonization of this environment or to interacting as a 455
specialist with particular microbial consortia prevailing in this ecological niche. Similarly, 4 456
out of 10 respiratory tract isolates and 2 out of 3 CF isolates have previously been described 457
as belonging to AFLP genogroup #6 (33). 458
We noticed a high average sequence divergence between different genogroups of 0.048 459
(± 0.016 SD) in the range from 0.026 – 0.088 on calculation of k-parameters to assess the 460
significance of genogroups identified in the tree presentation. Based on published 16S rDNA 461
sequence data, the percentage of sequence similarities ranged from 91.6% to 99% (mean, 462
96.5%) (33), which is partly below the species definition that usually proposes a 16S rDNA 463
sequence similarity >97% (65). However, in the absence of characteristic phenotypes and 464
relatively high intergroup DNA – DNA hybridisation values, the authors refrained from 465
terming the genogroups as separate species. 466
In conclusion, this MLST scheme for S. maltophilia presents a discriminatory typing method 467
with stable markers appropriate for studying the population structure. Based on DNA 468
similarities, S. africana belongs to the species S. maltophilia. MLST data confirmed the 469
existence of previously defined genogroups and identified an additional five new genogroups. 470
Thus, this work provides a sequence database and a method for assigning further isolates to 471
already defined or new genogroups and for refining population structure analyses. Initial data 472
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analyses for inferring population structure provide additional evidence for a clonal rather than 473
a recombinant structure. However, to corroborate these findings a greater number isolates 474
must be investigated with this newly established scheme, especially those belonging to the 475
environmental genogroups, which are apparently just distantly related to the S. maltophilia 476
type strain. The predominance of clinical isolates, particularly in genogroup #6 requires 477
further elucidation, as does the strict environmental origin of isolates in genogroups #5, #8 to 478
#10. Further taxonomic studies are required to assess whether or not S. maltophilia must be 479
separated into several distinct species. 480
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ACKNOWLEDGEMENTS 481
This study was part of a diploma thesis (S.K.). The authors would like to thank Dr. S. Brisse, 482
Institut Pasteur, Paris and Dr. P. Graumann, Institute of Microbiology, University of Freiburg 483
for helpful comments and Deborah Lawrie-Blum for assisting with the preparation of the 484
manuscript. The authors are also grateful to their colleagues and the German SARI study 485
group for providing isolates. 486
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REFERENCES 487
1. Alonso, A. and J. L. Martinez. 2000. Cloning and characterization of SmeDEF, a 488
novel multidrug efflux pump from Stenotrophomonas maltophilia. Antimicrob.Agents 489
Chemother. 44:3079-3086. 490
2. Altschul, S. F., T. L. Madden, A. A. Schaffer, J. Zhang, Z. Zhang, W. Miller, and 491
D. J. Lipman. 1997. Gapped BLAST and PSI-BLAST: a new generation of protein 492
database search programs. Nucleic Acids Res 25:3389-3402. 493
3. Assih, E. A., A. S. Ouattara, S. Thierry, J. L. Cayol, M. Labat, and H. Macarie. 494
2002. Stenotrophomonas acidaminiphila sp. nov., a strictly aerobic bacterium isolated 495
from an upflow anaerobic sludge blanket (UASB) reactor. Int.J.Syst.Evol.Microbiol. 496
52:559-568. 497
4. Avison, M. B., C. S. Higgins, C. J. von Heldreich, P. M. Bennett, and T. R. Walsh. 498
2001. Plasmid location and molecular heterogeneity of the L1 and L2 beta-lactamase 499
genes of Stenotrophomonas maltophilia. Antimicrob Agents Chemother 45:413-419. 500
5. Baldwin, A., E. Mahenthiralingam, K. M. Thickett, D. Honeybourne, M. C. 501
Maiden, J. R. Govan, D. P. Speert, J. J. LiPuma, P. Vandamme, and C. G. 502
Dowson. 2005. Multilocus sequence typing scheme that provides both species and 503
strain differentiation for the Burkholderia cepacia complex. J.Clin.Microbiol. 504
43:4665-4673. 505
6. Bartual, S. G., H. Seifert, C. Hippler, M. A. Luzon, H. Wisplinghoff, and F. 506
Rodriguez-Valera. 2005. Development of a multilocus sequence typing scheme for 507
characterization of clinical isolates of Acinetobacter baumannii. J.Clin.Microbiol. 508
43:4382-4390. 509
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
25
7. Berg, G., N. Roskot, and K. Smalla. 1999. Genotypic and phenotypic relationships 510
between clinical and environmental isolates of Stenotrophomonas maltophilia. 511
J.Clin.Microbiol. 37:3594-3600. 512
8. Brisse, S. and J. Verhoef. 2001. Phylogenetic diversity of Klebsiella pneumoniae and 513
Klebsiella oxytoca clinical isolates revealed by randomly amplified polymorphic 514
DNA, gyrA and parC genes sequencing and automated ribotyping. 515
Int.J.Syst.Evol.Microbiol. 51:915-924. 516
9. Chien, C. C., C. W. Hung, and C. T. Han. 2007. Removal of cadmium ions during 517
stationary growth phase by an extremely cadmium-resistant strain of 518
Stenotrophomonas sp. Environ.Toxicol.Chem. 26:664-668. 519
10. Coenye, T., E. Vanlaere, E. Falsen, and P. Vandamme. 2004. Stenotrophomonas 520
africana Drancourt et al. 1997 is a later synonym of Stenotrophomonas maltophilia 521
(Hugh 1981) Palleroni and Bradbury 1993. Int.J.Syst.Evol.Microbiol. 54:1235-1237. 522
11. Coenye, T., E. Vanlaere, J. J. LiPuma, and P. Vandamme. 2004. Identification of 523
genomic groups in the genus Stenotrophomonas using gyrB RFLP analysis. FEMS 524
Immunol.Med.Microbiol. 40:181-185. 525
12. Crossman, L. C., V. C. Gould, J. M. Dow, G. S. Vernikos, A. Okazaki, M. 526
Sebaihia, D. Saunders, C. Arrowsmith, T. Carver, N. Peters, E. Adlem, A. 527
Kerhornou, A. Lord, L. Murphy, K. Seeger, R. Squares, S. Rutter, M. A. Quail, 528
M. A. Rajandream, D. Harris, C. Churcher, S. D. Bentley, J. Parkhill, N. R. 529
Thomson, and M. B. Avison. 2008. The complete genome, comparative and 530
functional analysis of Stenotrophomonas maltophilia reveals an organism heavily 531
shielded by drug resistance determinants. Genome Biol. 9:R74. 532
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
26
13. Curran, B., D. Jonas, H. Grundmann, T. Pitt, and C. G. Dowson. 2004. 533
Development of a Multilocus Sequence Typing Scheme for the Opportunistic 534
Pathogen Pseudomonas aeruginosa. J.Clin.Microbiol. 42:5644-5649. 535
14. Debette, J. and R. Blondeau. 1980. Presence of Pseudomonas maltophilia in the 536
rhizosphere of several cultivated plants. Can.J.Microbiol. 26:460-463. 537
15. Demko, C. A., R. C. Stern, and C. F. Doershuk. 1998. Stenotrophomonas 538
maltophilia in cystic fibrosis: incidence and prevalence. Pediatr.Pulmonol. 25:304-539
308. 540
16. Denton, M. 1997. Stenotrophomonas maltophilia: an emerging problem in cystic 541
fibrosis patients. Rev.Med.Microbiol 8:15-19. 542
17. Denton, M. and K. G. Kerr. 1998. Microbiological and clinical aspects of infection 543
associated with Stenotrophomonas maltophilia. Clin.Microbiol.Rev. 11:57-80. 544
18. Denton, M., N. J. Todd, K. G. Kerr, P. M. Hawkey, and J. M. Littlewood. 1998. 545
Molecular epidemiology of Stenotrophomonas maltophilia isolated from clinical 546
specimens from patients with cystic fibrosis and associated environmental samples. 547
J.Clin.Microbiol. 36:1953-1958. 548
19. Drancourt, M., C. Bollet, and D. Raoult. 1997. Stenotrophomonas africana sp. nov., 549
an opportunistic human pathogen in Africa. Int.J.Syst.Bacteriol. 47:160-163. 550
20. Feil, E. J., E. C. Holmes, D. E. Bessen, M. S. Chan, N. P. Day, M. C. Enright, R. 551
Goldstein, D. W. Hood, A. Kalia, C. E. Moore, J. Zhou, and B. G. Spratt. 2001. 552
Recombination within natural populations of pathogenic bacteria: short-term empirical 553
estimates and long-term phylogenetic consequences. Proc Natl Acad Sci U S A 554
98:182-187. 555
21. Felsenstein, J. 1981. Evolutionary trees from DNA sequences: a maximum likelihood 556
approach. J.Mol.Evol. 17:368-376. 557
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
27
22. Finkmann, W., K. Altendorf, E. Stackebrandt, and A. Lipski. 2000. 558
Characterization of N2O-producing Xanthomonas-like isolates from biofilters as 559
Stenotrophomonas nitritireducens sp. nov., Luteimonas mephitis gen. nov., sp. nov. 560
and Pseudoxanthomonas broegbernensis gen. nov., sp. nov. Int.J.Syst.Evol.Microbiol. 561
50 Pt 1:273-282. 562
23. Foster, N. F., A. J. Chang, T. V. Plant, and T. V. Riley. 2006. Evaluation of gyrB 563
RFLP analysis for the typing of clinical and environmental strains of 564
Stenotrophomonas maltophilia, abstr. P538, Abstr. 16th European Congress of 565
Clinical Microbiology and Infectious Diseases, Nice, France. 566
24. Fouhy, Y., K. Scanlon, K. Schouest, C. Spillane, L. Crossman, M. B. Avison, R. P. 567
Ryan, and J. M. Dow. 2007. Diffusible signal factor-dependent cell-cell signaling 568
and virulence in the nosocomial pathogen Stenotrophomonas maltophilia. J.Bacteriol. 569
189:4964-4968. 570
25. Furushita, M., A. Okamoto, T. Maeda, M. Ohta, and T. Shiba. 2005. Isolation of 571
multidrug-resistant Stenotrophomonas maltophilia from cultured yellowtail (Seriola 572
quinqueradiata) from a marine fish farm. Appl.Environ.Microbiol. 71:5598-5600. 573
26. Gibbs, M. J., J. S. Armstrong, and A. J. Gibbs. 2000. Sister-scanning: a Monte 574
Carlo procedure for assessing signals in recombinant sequences. Bioinformatics. 575
16:573-582. 576
27. Godoy, D., G. Randle, A. J. Simpson, D. M. Aanensen, T. L. Pitt, R. Kinoshita, 577
and B. G. Spratt. 2003. Multilocus sequence typing and evolutionary relationships 578
among the causative agents of melioidosis and glanders, Burkholderia pseudomallei 579
and Burkholderia mallei. J.Clin.Microbiol. 41:2068-2079. 580
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
28
28. Goss, C. H., K. Otto, M. L. Aitken, and G. D. Rubenfeld. 2002. Detecting 581
Stenotrophomonas maltophilia does not reduce survival of patients with cystic 582
fibrosis. Am.J.Respir.Crit Care Med. 166:356-361. 583
29. Gould, V. C., A. Okazaki, and M. B. Avison. 2006. Beta-lactam resistance and beta-584
lactamase expression in clinical Stenotrophomonas maltophilia isolates having defined 585
phylogenetic relationships. J Antimicrob Chemother 57:199-203. 586
30. Graff, G. R. and J. L. Burns. 2002. Factors affecting the incidence of 587
Stenotrophomonas maltophilia isolation in cystic fibrosis. Chest 121:1754-1760. 588
31. Hagemann, M., D. Hasse, and G. Berg. 2006. Detection of a phage genome carrying 589
a zonula occludens like toxin gene (zot) in clinical isolates of Stenotrophomonas 590
maltophilia. Arch.Microbiol. 185:449-458. 591
32. Hasegawa, M., H. Kishino, and T. Yano. 1985. Dating of the human-ape splitting by 592
a molecular clock of mitochondrial DNA. J.Mol.Evol. 22:160-174. 593
33. Hauben, L., L. Vauterin, E. R. Moore, B. Hoste, and J. Swings. 1999. Genomic 594
diversity of the genus Stenotrophomonas. Int.J.Syst.Bacteriol. 49 Pt 4:1749-1760. 595
34. Jolley, K. A., E. J. Feil, M. S. Chan, and M. C. Maiden. 2001. Sequence type 596
analysis and recombinational tests (START). Bioinformatics. 17:1230-1231. 597
35. Juhnke, M. E., D. E. Mathre, and D. C. Sands. 1987. Identification and 598
Characterization of Rhizosphere-Competent Bacteria of Wheat. 599
Appl.Environ.Microbiol. 53:2793-2799. 600
36. Krzewinski, J. W., C. D. Nguyen, J. M. Foster, and J. L. Burns. 2001. Use of 601
random amplified polymorphic DNA PCR to examine epidemiology of 602
Stenotrophomonas maltophilia and Achromobacter (Alcaligenes) xylosoxidans from 603
patients with cystic fibrosis. J.Clin.Microbiol. 39:3597-3602. 604
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
29
37. Lee, E. Y., Y. S. Jun, K. S. Cho, and H. W. Ryu. 2002. Degradation characteristics 605
of toluene, benzene, ethylbenzene, and xylene by Stenotrophomonas maltophilia T3-c. 606
J.Air Waste Manag.Assoc. 52:400-406. 607
38. Manly, B. F. J. 1991. Randomization and Monte Carlo methods in biology. Chapman 608
& Hall, London. 609
39. Martin, D. and E. Rybicki. 2000. RDP: detection of recombination amongst aligned 610
sequences. Bioinformatics. 16:562-563. 611
40. Martin, D. P., D. Posada, K. A. Crandall, and C. Williamson. 2005. A modified 612
bootscan algorithm for automated identification of recombinant sequences and 613
recombination breakpoints. AIDS Res.Hum.Retroviruses 21:98-102. 614
41. Martin, D. P., C. Williamson, and D. Posada. 2005. RDP2: recombination detection 615
and analysis from sequence alignments. Bioinformatics. 21:260-262. 616
42. Maynard-Smith, J. 1992. Analyzing the mosaic structure of genes. J.Mol.Evol. 617
34:126-129. 618
43. Maynard-Smith, J., N. H. Smith, M. O'Rourke, and B. G. Spratt. 1993. How 619
clonal are bacteria? Proc Natl Acad Sci U S A 90:4384-4388. 620
44. Minkwitz, A. and G. Berg. 2001. Comparison of antifungal activities and 16S 621
ribosomal DNA sequences of clinical and environmental isolates of 622
Stenotrophomonas maltophilia. J.Clin.Microbiol. 39:139-145. 623
45. Morales, G., L. Wiehlmann, P. Gudowius, C. Van Delden, B. Tummler, J. L. 624
Martinez, and F. Rojo. 2004. Structure of Pseudomonas aeruginosa Populations 625
Analyzed by Single Nucleotide Polymorphism and Pulsed-Field Gel Electrophoresis 626
Genotyping. J Bacteriol 186:4228-4237. 627
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
30
46. Morrison, A. J., Jr., K. K. Hoffmann, and R. P. Wenzel. 1986. Associated 628
mortality and clinical characteristics of nosocomial Pseudomonas maltophilia in a 629
university hospital. J.Clin.Microbiol. 24:52-55. 630
47. Oliveira-Garcia, D., M. Dall'Agnol, M. Rosales, A. C. Azzuz, N. Alcantara, M. B. 631
Martinez, and J. A. Giron. 2003. Fimbriae and adherence of Stenotrophomonas 632
maltophilia to epithelial cells and to abiotic surfaces. Cell Microbiol. 5:625-636. 633
48. Oliveira-Garcia, D., M. Dall'Agnol, M. Rosales, A. C. Azzuz, M. B. Martinez, and 634
J. A. Giron. 2002. Characterization of flagella produced by clinical strains of 635
Stenotrophomonas maltophilia. Emerg.Infect.Dis. 8:918-923. 636
49. Padidam, M., S. Sawyer, and C. M. Fauquet. 1999. Possible emergence of new 637
geminiviruses by frequent recombination. Virology 265:218-225. 638
50. Page, R. D. 1996. TreeView: an application to display phylogenetic trees on personal 639
computers. Comput.Appl.Biosci. 12:357-358. 640
51. Palleroni, N. J. and J. F. Bradbury. 1993. Stenotrophomonas, a new bacterial genus 641
for Xanthomonas maltophilia (Hugh 1980) Swings et al. 1983. Int.J.Syst.Bacteriol. 642
43:606-609. 643
52. Palys, T., L. K. Nakamura, and F. M. Cohan. 1997. Discovery and classification of 644
ecological diversity in the bacterial world: the role of DNA sequence data. 645
Int.J.Syst.Bacteriol. 47:1145-1156. 646
53. Posada, D. 2002. Evaluation of methods for detecting recombination from DNA 647
sequences: empirical data. Mol.Biol.Evol. 19:708-717. 648
54. Posada, D. and K. A. Crandall. 2001. Evaluation of methods for detecting 649
recombination from DNA sequences: computer simulations. 650
Proc.Natl.Acad.Sci.U.S.A 98:13757-13762. 651
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
31
55. Qian, W., Y. Jia, S. X. Ren, Y. Q. He, J. X. Feng, L. F. Lu, Q. Sun, G. Ying, D. J. 652
Tang, H. Tang, W. Wu, P. Hao, L. Wang, B. L. Jiang, S. Zeng, W. Y. Gu, G. Lu, 653
L. Rong, Y. Tian, Z. Yao, G. Fu, B. Chen, R. Fang, B. Qiang, Z. Chen, G. P. 654
Zhao, J. L. Tang, and C. He. 2005. Comparative and functional genomic analyses of 655
the pathogenicity of phytopathogen Xanthomonas campestris pv. campestris. Genome 656
Res. 15:757-767. 657
56. Relman, D. A., T. M. Schmidt, R. P. MacDermott, and S. Falkow. 1992. 658
Identification of the uncultured bacillus of Whipple's disease. N.Engl.J Med 327:293-659
301. 660
57. Rozen, S. and H. J. Skaletsky. 2000. Primer3 on the WWW for general users and for 661
biologist programmers., p. 365-386. In S. Krawetz and S. Misener (eds.), Methods in 662
Molecular Biology. Humana Press, Totowa, NJ. 663
58. Rutherford, K., J. Parkhill, J. Crook, T. Horsnell, P. Rice, M. A. Rajandream, 664
and B. Barrell. 2000. Artemis: sequence visualization and annotation. Bioinformatics. 665
16:944-945. 666
59. Salerno, A., A. Deletoile, M. Lefevre, I. Ciznar, K. Krovacek, P. Grimont, and S. 667
Brisse. 2007. Recombining population structure of Plesiomonas shigelloides 668
(Enterobacteriaceae) revealed by multilocus sequence typing. J.Bacteriol. 189:7808-669
7818. 670
60. Sanchez, P., A. Alonso, and J. L. Martinez. 2002. Cloning and characterization of 671
SmeT, a repressor of the Stenotrophomonas maltophilia multidrug efflux pump 672
SmeDEF. Antimicrob.Agents Chemother. 46:3386-3393. 673
61. Sarkar, S. F. and D. S. Guttman. 2004. Evolution of the core genome of 674
Pseudomonas syringae, a highly clonal, endemic plant pathogen. 675
Appl.Environ.Microbiol. 70:1999-2012. 676
on February 13, 2018 by guest
http://jb.asm.org/
Dow
nloaded from
32
62. Schable, B., M. E. Villarino, M. S. Favero, and J. M. Miller. 1991. Application of 677
multilocus enzyme electrophoresis to epidemiologic investigations of Xanthomonas 678
maltophilia. Infect.Control Hosp.Epidemiol. 12:163-167. 679
63. Senol, E. 2004. Stenotrophomonas maltophilia: the significance and role as a 680
nosocomial pathogen. J.Hosp.Infect. 57:1-7. 681
64. Speijer, H., P. H. Savelkoul, M. J. Bonten, E. E. Stobberingh, and J. H. Tjhie. 682
1999. Application of different genotyping methods for Pseudomonas aeruginosa in a 683
setting of endemicity in an intensive care unit. J.Clin.Microbiol. 37:3654-3661. 684
65. Stackebrandt, E. and B. M. Goebel. 1994. Taxonomic note: a place for DNA-DNA 685
reassociation and 16S rRNA sequence analysis in the present species definition in 686
bacteriology. Int.J.Syst.Bacteriol. 44:846-849. 687
66. Staden, R. 1996. The Staden sequence analysis package. Mol.Biotechnol. 5:233-241. 688
67. Staden, R., K. F. Beal, and J. K. Bonfield. 2000. The Staden package, 1998. 689
Methods Mol.Biol. 132:115-130. 690
68. Swofford, D. L. 1998. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other 691
Methods). Sinauer Associates, Sunderland, Massachusetts. 692
69. Toleman, M. A., P. M. Bennett, D. M. Bennett, R. N. Jones, and T. R. Walsh. 693
2007. Global emergence of trimethoprim/sulfamethoxazole resistance in 694
Stenotrophomonas maltophilia mediated by acquisition of sul genes. 695
Emerg.Infect.Dis. 13:559-565. 696
70. Valdezate, S., A. Vindel, L. Maiz, F. Baquero, H. Escobar, and R. Canton. 2001. 697
Persistence and variability of Stenotrophomonas maltophilia in cystic fibrosis patients, 698
Madrid, 1991-1998. Emerg.Infect.Dis. 7:113-122. 699
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71. Valdezate, S., A. Vindel, P. Martin-Davila, B. S. Del Saz, F. Baquero, and R. 700
Canton. 2004. High genetic diversity among Stenotrophomonas maltophilia strains 701
despite their originating at a single hospital. J.Clin.Microbiol. 42:693-699. 702
72. Windhorst, S., E. Frank, D. N. Georgieva, N. Genov, F. Buck, P. Borowski, and 703
W. Weber. 2002. The major extracellular protease of the nosocomial pathogen 704
Stenotrophomonas maltophilia: characterization of the protein and molecular cloning 705
of the gene. J.Biol.Chem. 277:11042-11049. 706
73. Wolf, A., A. Fritze, M. Hagemann, and G. Berg. 2002. Stenotrophomonas 707
rhizophila sp. nov., a novel plant-associated bacterium with antifungal properties. 708
Int.J.Syst.Evol.Microbiol. 52:1937-1944. 709
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FIGURE LEGENDS 710
711
FIG. 1. NJ-tree based on the concatenated data for all 7 loci of the 70 S. maltophilia strains. 712
The isolates originated from blood culture (bc), cystic fibrosis (CF), tracheal secretions from 713
outbreaks (ts_out), sputum, pus, conjunctivitis (conj), environmental specimens (env), 714
hospital environment (hosp env), patient (pat), and one cerebrospinal fluid isolate of 715
S. africana (afri_CSF). Cross hatches followed by a number indicate to already defined 716
genogroups, which could be numbered accordingly by inclusion of previously investigated 717
strains (33), shown in small rectangular boxes. Capital letter point to groups newly detected in 718
this work. Bootstrap values (200 random seeds) are given as percentages for the main 719
branches. The tree was rooted with the corresponding concatenate of X. campestris (55). 720
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TABLES 726
TABLE 1. Properties of Stenotrophomonas spp. strains ordered by their genomic groups. Allelic profile is given in the order atpD, gapA, guaA, 727
mutM, nuoD, ppsA, recA. Countries are given in the ISO 3166-1 alpha-2 code. 728
729
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
895_bc S. maltophilia 23 8, 20, 14, 25, 14, 17, 3 #1 b)
FR blood culture 1989
904_bc S. maltophilia 24 9, 21, 28, 26, 15, 18, 3 #1 Perth, AU blood culture 1999
929_env S. maltophilia 24 9, 21, 28, 26, 15, 18, 3 #1 DE rape rhizosphere NA
683_CF S. maltophilia 10 6, 18, 27, 18, 21, 9, 20 #2 GB cystic fibrosis 2006
892_pus S. maltophilia 20 16, 9, 32, 20, 20, 9, 18 #2 b)
BE abscess, leg 1983
918_hosp.env S. maltophilia 35 6, 19, 39, 19, 19, 33, 21 #2 Perth, AU hospital environment 2005
686_CF S. maltophilia 13 12, 27, 37, 23, 30, 29, 22 #3 GB cystic fibrosis 2006
887_sputum S. maltophilia 15 10, 29, 21, 21, 32, 32, 10 #3 b)
BE sputum 1989
914_bc S. maltophilia 32 11, 30, 15, 22, 33, 31, 10 #3 Perth, AU blood culture 1999
Continued on following page 730
731
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TABLE 1 — Continued 1 732
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
920_bc S. maltophilia 37 13, 28, 25, 24, 31, 30, 23 #3 Perth, AU blood culture 1999
682_CF S. maltophilia 9 22, 24, 20, 9, 4, 14, 2 #4 GB cystic fibrosis 2006
890_bc S. maltophilia 18 20, 25, 11, 17, 4, 2, 2 #4 US blood culture 1966
896_afri_CSF S. africana 54 44, 44, 53, 9, 46, 48, 39 #4 b)
CD cerebro-spinal fluid 1994
922_bc S. maltophilia 39 21, 26, 33, 9, 29, 2, 15 #4 Perth, AU blood culture 2002
930_env S. maltophilia 39 21, 26, 33, 9, 29, 2, 15 #4 DE rape rhizosphere NA
893_env S. maltophilia 21 31, 12, 26, 34, 34, 34, 28 #5 b)
FR chicory, rhizosphere 1977
940_env S. maltophilia 50 40, 41, 49, 38, 42, 41, 36 #5 NL dune rhizosphere NA
943_env S. maltophilia 50 40, 41, 49, 38, 42, 41, 36 #5 NL dune rhizosphere NA
R551_env a)
S. maltophilia 45 35, 36, 44, 37, 37, 39, 32 #5 US Populus trichocarpa NA
325_ts_out S. maltophilia 28 4, 3, 2, 5, 9, 6, 9 #6 Wismar, DE tracheal secretion 31.05.01
435_ts_out S. maltophilia 28 4, 3, 2, 5, 9, 6, 9 #6 Wismar, DE tracheal secretion 04.04.02
Continued on following page 733
734
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TABLE 1 — Continued 2 735
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
396_ts_out S. maltophilia 25 1, 1, 3, 6, 8, 7, 8 #6 Harlachingen, DE tracheal secretion 07.01.02
335_ts_out S. maltophilia 25 1, 1, 3, 6, 8, 7, 8 #6 Harlachingen, DE tracheal secretion 26.06.01
397_ts_out S. maltophilia 26 1, 1, 4, 1, 6, 4, 1 #6 Harlachingen, DE tracheal secretion 03.12.01
441_ts_out S. maltophilia 26 1, 1, 4, 1, 6, 4, 1 #6 Harlachingen, DE tracheal secretion 11.03.02
529_bc S. maltophilia 4 1, 4, 7, 7, 28, 19, 6 #6 Köpenick, DE blood culture 27.02.04
635_CF S. maltophilia 5 5, 22, 9, 4, 27, 5, 7 #6 Homburg, DE cystic fibrosis 2006
637_CF S. maltophilia 5 5, 22, 9, 4, 27, 5, 7 #6 Innsbruck, AU cystic fibrosis 2006
643_CF S. maltophilia 8 3, 4, 18, 3, 7, 20, 1 #6 Gaißach, DE cystic fibrosis 2006
645_CF S. maltophilia 43 1, 1, 42, 3, 28, 37, 6 #6 Bonn, DE cystic fibrosis 2006
651_CF S. maltophilia 44 1, 35, 43, 36, 7, 38, 6 #6 Stuttgart, DE cystic fibrosis 2006
673_CF S. maltophilia 2 1, 1, 12, 3, 28, 7, 1 #6 GB cystic fibrosis 2006
674_CF S. maltophilia 27 3, 1, 1, 3, 6, 4, 1 #6 GB cystic fibrosis 2006
Continued on following page 736
737
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TABLE 1 — Continued 3 738
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
675_CF S. maltophilia 5 5, 22, 9, 4, 27, 5, 7 #6 GB cystic fibrosis 2006
676_CF S. maltophilia 6 5, 4, 29, 4, 25, 21, 19 #6 GB cystic fibrosis 2006
677_CF S. maltophilia 1 1, 1, 1, 1, 1, 1, 1 #6 GB cystic fibrosis 2006
680_CF S. maltophilia 8 3, 4, 18, 3, 7, 20, 1 #6 GB cystic fibrosis 2006
681_CF S. maltophilia 27 3, 1, 1, 3, 6, 4, 1 #6 GB cystic fibrosis 2006
886_pat S. maltophilia 14 17, 23, 23, 16, 26, 5, 6 #6 b)
US throat swab 1958
913_bc S. maltophilia 31 3, 4, 24, 7, 7, 22, 7 #6 Perth, AU blood culture 2002
K279a_bc a)
S. maltophilia 1 1, 1, 1, 1, 1, 1, 1 #6 GB blood culture NA
889_conj S. maltophilia 17 18, 5, 34, 8, 5, 25, 4 #7 b)
BE conjunctivitis 1989
909_bc S. maltophilia 30 19, 5, 8, 8, 5, 26, 4 #7 Perth, AU blood culture 1999
894_env S. maltophilia 22 7, 7, 6, 11, 11, 11, 30 #8 b)
FR wheat, rhizosphere 1980
Continued on following page 739
740
TABLE 1 — Continued 4 741
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Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
928_env S. maltophilia 46 36, 37, 45, 4, 38, 42, 30 #8 DE rape rhizosphere NA
934_env S. maltophilia 47 37, 38, 46, 4, 39, 47, 33 #8 DE rape rhizosphere NA
936_env S. maltophilia 48 38, 39, 47, 4, 40, 43, 34 #8 DE rape rhizosphere NA
938_env S. maltophilia 49 39, 40, 48, 4, 41, 44, 35 #8 DE potato rhizosphere NA
891_env S. maltophilia 19 33, 31, 17, 32, 35, 35, 12 #9 b)
JP rice plant 1963
941_env S. maltophilia 51 41, 42, 50, 4, 43, 45, 37 #9 NL dune rhizosphere NA
942_env S. maltophilia 52 42, 43, 51, 4, 44, 46, 38 #9 NL dune rhizosphere NA
888_env S. maltophilia 16 32, 6, 38, 10, 10, 10, 29 #10 b)
US soil 1959
678_CF S. maltophilia 7 14, 32, 19, 12, 12, 12, 13 A GB cystic fibrosis 2006
685_CF S. maltophilia 12 15, 33, 31, 13, 13, 13, 14 A GB cystic fibrosis 2006
919_bc S. maltophilia 36 27, 13, 36, 27, 22, 16, 17 B Perth, AU blood culture 2001
944_env S. maltophilia 53 43, 13, 52, 27, 45, 40, 17 B DE Baltic Sea NA
945_env S. maltophilia 53 43, 13, 52, 27, 45, 40, 17 B DE Baltic Sea at Zingst NA
Continued on following page 742
743
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TABLE 1 — Continued 5 744
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
242_ts_out S. maltophilia 29 2, 2, 5, 2, 2, 3, 5 C Tübingen, DE tracheal secretion 02.11.00
290_ts_out S. maltophilia 29 2, 2, 5, 2, 2, 3, 5 C Tübingen, DE tracheal secretion 18.01.01
326_ts_out S. maltophilia 29 2, 2, 5, 2, 2, 3, 5 C Gera, DE tracheal secretion 14.05.01
372_ts_out S. maltophilia 29 2, 2, 5, 2, 2, 3, 5 C Gera, DE tracheal secretion 19.10.01
908_bc S. maltophilia 29 2, 2, 5, 2, 2, 3, 5 C Perth, AU blood culture 1999
684_CF S. maltophilia 11 25, 16, 16, 29, 3, 8, 11 D GB cystic fibrosis 2006
916_hosp.env S. maltophilia 33 24, 17, 40, 31, 16, 28, 24 D Perth, AU hospital environment 2005
923_bc S. maltophilia 40 26, 14, 13, 28, 3, 8, 11 D Perth, AU blood culture 2003
924_sputum S. maltophilia 41 23, 15, 35, 30, 17, 27, 25 D Perth, AU sputum 2001
917_bc S. maltophilia 34 30, 10, 10, 14, 23, 23, 26 E Perth, AU blood culture 2000
921_hosp.env S. maltophilia 38 29, 11, 22, 15, 24, 24, 27 E Perth, AU hospital environment 2005
470_bc S. maltophilia 3 28, 8, 30, 33, 18, 15, 16 - Gera, DE blood culture 22.09.02
Continued on following page 745
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TABLE 1 — Continued 6 747
Strain no. Species ST Allelic profile Genomic
group
Hospital center or
geographic source Isolation site Date of
isolation
639_CF S. maltophilia 42 34, 34, 41, 35, 36, 36, 31 - Munich, DE cystic fibrosis 2006
897_nitri S. nitritireducens 55 45, 45, 54, 39, 47, 49, 40 NA Osnabrück, DE laboratory-biofilter 1992
898_acid S. acidaminiphila 56 46, 46, 55, 40, 48, 50, 41 NA MX mud 1999
748
a) Sequence data taken from the US Department of Energy Joint Genome Institute http://www.jgi.doe.gov/ and from the Stenotrophomonas 749
maltophilia Sequencing Group ftp://ftp.sanger.ac.uk/pub/pathogens/sma/) at the Sanger Institute (12). 750
b) Strain had already been assigned to an identical number of genogroup as described previously (33). 751
752
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753
TABLE 2. Primers, annealing temperatures used for amplification and positions in the amplicons used for assignation to allelic types. 754
755
Primer Nucleotidesequence (5' → 3') Annealing-
Temperature (°C) a
Amplicon
size (bp)
Bp position in the
amplicon used for
sequence typing
atpD forw ATGAGTCAGGGCAAGATCGTTC 62°C 858 214 - 744
atpD rev TCCTGCAGGACGCCCATTTC
gapA forw TGGCAATCAAGGTTGGTATCAAC 62°C 800 120 - 677
gapA rev TTCGCTCTGTGCCTTCACTTC
guaA forw AACGAAGAAAAGCGCTGGTA (62°C) 704 70 - 621
guaA rev ACGGATGGCGGTAGACCAT
mutM forw AACTGCCCGAAGTCGAAAC 579 42 - 506
mutM rev (2r) GAGGATCTCCTTCACCGCATC 58°C (62°C)
mutM rev (4r) TTACCGGCCTCGCGCAG 52°C (48°C) 545 42 - 506
Continued on following page 756
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TABLE 2 — Continued 1 758
Primer Nucleotidesequence (5' → 3') Annealing-
Temperature (°C) a
Amplicon
size (bp)
Bp position in the
amplicon used for
sequence typing
nuoD forw TTCGCAACTACACCATGAAC 48°C 514 33 - 476
nuoD rev CAGCGCGACTCCTTGTACTT
ppsA forw CAAGGCGATCCGCATGGTGTATTC 62°C 635 65 - 559
ppsA rev CCTTCGTAGATGAA(A/G)CCGGT(A/G)TC
recA forw ATGGACGAGAACAAGAAGCGC 62°C 807 100 - 645
recA rev CCTGCAGGCCCATCGCC
759 a)
Changed temperatures in the presence of 1.3 M betaine. 760
761
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TABLE 3. Analysis of the seven loci in the S. maltophilia STs detected. 762
763
Locus Fragment
size (bp)
No. of
alleles
No. of
variable sites
% Variable
sites
% GC-
content dN/dS
Simpson’s
index of
Diversity
atpD 531 44 63 11.9 65.4 0.040 0.982
gapA 558 44 114 20.4 63.4 0.095 0.984
guaA 552 53 140 25.4 65.4 0.060 0.999
mutM 465 38 172 37.0 71.4 0.078 0.971
nuoD 444 46 85 19.1 63.6 0.017 0.993
ppsA 495 48 130 26.3 67.0 0.092 0.996
recA 546 39 137 25.1 65.1 0.047 0.983
764
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TABLE 4. Index of Association (IA) calculated for different groups of S. maltophilia. IA was 766
considered as significantly different from 0, indicating a disequilibrium if the observed 767
variance exceeded maximum variance in 1,000 random trials. 768
769
Analysed group a)
Observed
variance
Expected
variance IA
Max. trials
variance
Linkage
disequil.
65 isolates b)
0.498 0.142 2.498 0.447 significant
54 ST 0.177 0.090 0.971 0.480 not significant
48 clin. isolates b)
0.778 0.219 2.562 0.534 significant
41 ST of clin. isolates 0.304 0.137 1.216 0.589 not significant
17 env. isolates 0.795 0.203 2.911 1.850 not significant
15 ST of env. Isolates 0.130 0.132 -0.011 1.708 not significant
a) Clinical isolates (clin.) also included those from the hospital environment. Environmental 770
isolates (env.) only included those originating strictly outside of hospitals. 771
b) every second isolate from each of the five outbreaks was omitted. 772
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X campestris888 env
934 env
936 env938 env
894 env
928 env678 CF
685 CF893 envR551 env940 env943 env
891 env941 env942 env
470 bc
682 CF890 bc
896 africana CSF922 bc
930 env919 bc
944 env
945 env924 sputum
916 hosp env684 CF
923 bc892 pus683 CF
918 hosp env651 CF
325 ts out435 ts out
645 CF673 CF
529 bc
913 bc886 pat676 CF
635 CF
637 CF675 CF
397 ts out441 ts out674 CF681 CF
677 CFK279a bc
643 CF680 CF335 ts out
396 ts out889 conjunctivis
909 bc
917 bc921 hosp env
639 CF686 CF
920 bc887 sputum
914 bc895 bc
904 bc929 env
242 ts out290 ts out326 ts out372 ts out908 bc
concatenate(atpD, gapA, guaA, mutM,
nuoD, ppsA, recA)
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
96
96
97
77
100
100
100
100
100
100
100
100
100
100
100
100
100
C
#6
#7
#4
#2
A
#8
#9
#5
E
D
B
#3
#1
0.01
63
53
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