A Stenotrophomonas maltophilia Multilocus Sequence Typing ...

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A Stenotrophomonas maltophilia Multilocus Sequence Typing Scheme 4

for Inferring Population Structure 5

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Sabine Kaiser,1,2

Klaus Biehler,1 Daniel Jonas

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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

[email protected] 20

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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

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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

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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

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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

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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

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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

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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

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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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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


887_sputum S. maltophilia 15 10, 29, 21, 21, 32, 32, 10 #3 b)

BE sputum 1989


Continued on following page 730

731


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TABLE 1 — Continued 1 732


group

Hospital center or


isolation



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



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


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


734


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group

Hospital center or


isolation

396_ts_out S. maltophilia 25 1, 1, 3, 6, 8, 7, 8 #6 Harlachingen, DE tracheal secretion 07.01.02




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




737


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group

Hospital center or


isolation






886_pat S. maltophilia 14 17, 23, 23, 16, 26, 5, 6 #6 b)

US throat swab 1958


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



FR wheat, rhizosphere 1980


740



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group

Hospital center or


isolation




938_env S. maltophilia 49 39, 40, 48, 4, 41, 44, 35 #8 DE potato rhizosphere NA


JP rice plant 1963




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


743


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group

Hospital center or


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


746


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group

Hospital center or


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


757


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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

765


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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

773


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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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A Stenotrophomonas maltophilia Multilocus Sequence Typing ...

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