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1 1 1 2 FLOW CYTOMETRY ANALYSIS USING SYSMEX UF1000I CHARACTERIZE UROPATHOGENS BASED ON 3 BACTERIAL-, LEUKOCYTE- AND ERYTHROCYTE COUNTS IN URINE SPECIMEN AMONG PATIENTS WITH 4 URINARY TRACT INFECTION 5 6 7 8 Tor Monsen 1 # , , Patrik Ryden 2,3 9 1 Department of Medical Microbiology, Umeå University, Sweden . 2 Department Mathematics 10 and Mathematical Statistics, Umeå University, University, Sweden. 3 Computational Life 11 science Cluster (CLiC), Umeå University, University, Sweden. 12 13 14 15 16 # Corresponding author. 17 Tor Monsen, MD, PhD, associate professor, Department of Clinical Microbiology Umeå 18 University Hospital, and University of Umeå, SE-90185 Umeå, Sweden; 19 E-mail: [email protected] 20 21 22 23 Short running headline: Flow cytometry, leukocyte, erythrocyte, uropathogens 24 25 JCM Accepts, published online ahead of print on 3 December 2014 J. Clin. Microbiol. doi:10.1128/JCM.01974-14 Copyright © 2014, American Society for Microbiology. All Rights Reserved. on January 28, 2020 by guest http://jcm.asm.org/ Downloaded from

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Page 1: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

1 1

1

2

FLOW CYTOMETRY ANALYSIS USING SYSMEX UF1000I CHARACTERIZE UROPATHOGENS BASED ON 3

BACTERIAL-, LEUKOCYTE- AND ERYTHROCYTE COUNTS IN URINE SPECIMEN AMONG PATIENTS WITH 4

URINARY TRACT INFECTION 5

6

7

8

Tor Monsen1#

,, Patrik Ryden

2,3 9

1Department of Medical Microbiology, Umeå University, Sweden

. 2Department Mathematics 10

and Mathematical Statistics, Umeå University, University, Sweden. 3Computational Life 11

science Cluster (CLiC), Umeå University, University, Sweden. 12

13

14

15

16

# Corresponding author. 17

Tor Monsen, MD, PhD, associate professor, Department of Clinical Microbiology Umeå 18

University Hospital, and University of Umeå, SE-90185 Umeå, Sweden; 19

E-mail: [email protected] 20

21

22

23

Short running headline: Flow cytometry, leukocyte, erythrocyte, uropathogens 24

25

JCM Accepts, published online ahead of print on 3 December 2014J. Clin. Microbiol. doi:10.1128/JCM.01974-14Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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26

Abstract 27

Urinary tract infections (UTIs) are the second most common bacterial infection. Urine culture is 28

gold standard for diagnosis but new techniques such as flow cytometry analysis (FCA) have 29

been introduced. 30

The aim of the present study was to evaluate FCA characteristics regarding bacteriuria, 31

leukocyteuria and erythrocyturia in relation to cultured uropathogens in specimens among 32

patients with suspected UTI We also wanted to evaluate whether the FCA characteristics can 33

identify uropathogens prior to culture. 34

From a prospective study, 1,587 consecutive urine specimens underwent FCA prior to culture 35

during January and February 2012. In- and outpatients (79.6% and 19.4%, respectively) were 36

included of whom women represented 67.5%. In total 620 specimens yielded growth of which 37

Escherichia coli represented 65%, Enterococci 8%, Klebsiella 7% and Staphylococci 5%. 38

For uropathogens the outcome of FCA was compared against the results for specimens with E. 39

coli and those with negative culture. E. coli had high bacterial- (median 17,914 /µL), leukocyte- 40

(348/µL) and erythrocyte counts (23/µL). With the exception of Klebsiella spp., the majorities of 41

uropathogens had considerable or significantly lower bacterial counts than E. coli. High 42

leukocyte counts were found in specimens with Staphylococcus aureus, Proteus mirabilis, 43

Pseudomonas aeruginosa and streptococci. For the three latter species and also Staphylococcus 44

saprophyticus elevated erythrocyte counts were found. 45

In essence, FCA adds new information of the bacterial-, leukocyte- and erythrocyte counts in 46

urine specimens for different uropathogens. Based on FCA characteristics, uropathogen can 47

be classified and identified prior to culture. E. coli and Klebsiella spp. have similar FCA 48

characteristics. 49

50

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Introduction 51

Urinary tract infections (UTIs) are caused by pathogenic microorganisms in the urinary tract 52

causing an inflammatory response with presence of red- and white blood cells in the urine. The 53

inflammatory response and clinical manifestations depends on the etiologic organism, the 54

severity of the infection and the immune status of the patient (1). 55

Urinary tract infections (UTIs) are the second most common bacterial infection and are 56

associated with high morbidity and costs. The annual incidence is estimated to more than 175 57

million UTI episodes worldwide. In US, UTI account annually for more than 7 million physician 58

visits, more than 1 million emergency department visits and more than 100,000 hospitalizations 59

(2, 3). 60

In outpatients UTI belong to the most frequent bacterial infections and antibiotics given for 61

treatment represent approximately 15% of all antibiotics prescribed to human in US, to an 62

estimated annual cost of > US $1 billion (3). In addition, the indirect annual cost is estimated to 63

approximately $1.6 billion (4). 64

Bacteria in urine can be classified in primary-, secondary-, tertiary- or doubtful uropathogens 65

according to their pathogen capacity, frequency of appearance or association with contamination 66

of urine specimens (5). E. coli is the most prevalent uropathogen and is responsible for 67

approximately 80% of lower UTI while S. saprophyticus, Klebsiella and Proteus spp. and other 68

uropathogens are less prevalent (6, 7, 8, 9, 10, 11), ECDC surveillance data 2012 69

(http://www.ecdc.europa.eu/en/publications/publications/annual-epidemiological-report-70

2012.pdf). E. coli is a more common cause of community- than nosocomial UTI (12, 13). 71

Urine culture is gold standard for diagnosis of UTI but culture is laborious, moderate costly 72

with a turnaround time of 24 to 48 hours. Recently fully automated and cost-effective diagnostic 73

instruments as flow cytometry analysis (FCA) have been introduced to improve the efficiency of 74

handling urine specimens. FCA makes it possible to rule out urine specimens which contain 75

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significant numbers of bacteria from those who do not. 76

The first generation automated FCA instrument, Sysmex UF50 (Medical Electronics, Kobe, 77

Japan) showed variable results but the next generation the Sysmex UF-500i and UF-1000i, have 78

improved sensitivity, specificity and a separate measurement channel for detection of bacteria 79

(14, 15, 16, 17, 18). In urine specimens, FCA identifies and enumerates bacteria, leukocytes, 80

erythrocytes and other cells. Culture negative specimens are identified and ruled out before 81

culture is performed which reduce the turnaround time, workload and cost (14, 15, 16). 82

However, the instrument has not been evaluated to predict identification of uropathogens prior to 83

urine culture. 84

The aim of the present study was to examine the FCA characteristics as bacterial-, 85

leukocyte- and erythrocyte counts associated with different uropathogens in urine specimens 86

among patients with suspected UTI. Moreover to evaluate whether the causative uropathogen 87

could be predicted in urine specimens prior to urine culture based on its FCA characteristics. 88

89

90

Material and Methods 91

Collection of Urine Specimens 92

During January and February 2012, 1,587 urine specimens from in- and outpatients were 93

collected in non-preservative tubes, stored and transported at <6ºC to the Department of 94

Clinical Microbiology Laboratory at University Hospital of Umeå for analysis. Specimens 95

were cultured within 3 hours after arrival to the laboratory and all specimens were from the 96

county of Västerbotten, Sweden. 97

98

Urinalysis 99

Prior to culture the urine specimens were analysed with flow cytometry (UF-1000i, Sysmex, 100

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TOA medical Electronics, Kobe, Japan). Specimens arrived after 4 PM were analysed and 101

stored at +60C until culture was performed the next morning. The instrument was supported 102

by the software version of 00-15. 103

In summary, the flow cytometry instrument aspirates urine which is split in two volumes in the 104

instrument prior to a fluorescent dyes staining. In the first volume, the sediment stain, 105

polymethine stains nucleic acid in the cells and in the second volume only nucleic acids in 106

bacteria are stained. After staining the specimen is delivered to the flow cell for particle analysis 107

by use of a red semiconductor laser. Particles are characterized according to impedance, 108

scattering and fluorescence light from forward- and side scatter lights. The forward scatter 109

provides information on particle size and the sides scatter information on the internal complexity 110

and the surface. In addition, fluorescence intensity provides information on the nucleic acid 111

content of each particle. 112

Particle concentration of counted bacteria, leukocytes and erythrocytes in urine specimens were 113

denoted U-bacteria, U-leucocytes and U-erythrocytes. 114

115

Culture and bacterial identification 116

Quantitative urine culture was performed by inoculation with a 10 µL calibrated plastic loop 117

(Sarstedt, Nurnbrecht, Germany) on cystine-lactose electrolyte-deficient (CLED) agar 118

(Acumedia Manufacturers, Inc. Baltimore, Maryland, USA). Agar plates were incubated in air 119

at 35° C for 18 to 20 h before counting of colony forming units (CFU/mL). 120

Species identification was performed as previously described (6). Briefly, Gram-negative and 121

Gram-positive uropathogens were identified by BrillianceTM

UTI agar (Oxoid Ltd, 122

Basingstoke, UK). Gram-negative bacteria were identified further with biochemical tests; 123

ornitine-, inositol and Triple sugar iron-test as described (19). Acinetobacter spp. were also 124

identified by species specific growth on CHROMagarTM

Acinetobacter (Chromagar, Paris, 125

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France). 126

Gram-positive bacteria were identified by catalase reaction. Staphylococci were identified 127

with species specific growth on CHROMagarTM

. In addition S. aureus was identified by its 128

DNAse activity. S. saprophyticus was identified by novobiocin susceptibility and coagulase 129

negative staphylococci other than S. saprophyticus were denoted “CoNS”. Enterococci and 130

streptococci were identified by esculin, agglutination to type specific serum (Streptex, Murex 131

Biotech Ltd. Dartford, England) and species specific growth on UTI-Brilliance agar. In 132

addition diagnosis of Streptococcus agalactiae (GBS) was supported by species specific 133

growth on chromagar (StrepB, Bio-Rad, Marns-la-Conquetta, France). 134

135

Inclusion criteria 136

Urine specimens yielding growth of >108 CFU/L of an identified pathogen were included 137

irrespectively of presence of UTI symptoms. Urine specimens yielding growth of 106

to 107 138

CFU/L of were included if reported presence UTI symptoms and/or laboratory tests indicating 139

UTI (nitrite test positive and/or moderate to high leukocyturia). Among these, specimens with 140

one pathogen were included as well as those with mixed flora containing a single dominating 141

pathogen (bacterial count at least 10 times higher than any other species which was judged as 142

the uropathogen and identified (6). Specimens with less than 106 CFU/L were classified as 143

negative cultures. Specimens from patients with urinary catheter, mixed flora without a 144

dominating uropathogen, pregnant women and specimens that lacked clinical information of 145

UTI were excluded. 146

147

Statistical analysis 148

All presented values are median values if not otherwise stated. Differences between 149

proportions were analyzed using the proportion z-test, Wilcoxon's rank sum test was used to 150

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compare differences between groups, and Spearman’s rank correlation was used to study the 151

dependencies between variables. The two-sided alternative hypothesis was used for all tests 152

and p-values < 0.05 were considered as significant. Importantly, we did not correct the p-153

values for multiple testing. We performed 220 tests looking at differences between 154

photogenes, negative controls and the dominating species E. coli, and 83 of those tests 155

resulted in a p-value < 0.05. The expected number of false positives is at most 11 (under the 156

extreme assumption that the null hypothesis is true for all tests) and a conservatively estimate 157

of the false discovery rate is 13.3%. If we assume that the null hypothesis is true for half of 158

the considered tests then an upper limit of the false discovery rate is 6.6%. In addition 108 159

direct comparisons between the photogenes were made and for those tests we presented the 160

observed p-values as well as the locally adjusted p-values obtained using Bonferroni 161

correction. For some bacteria/groups of bacteria the numbers of isolates were rather few and 162

the corresponding tests had relatively weak power. As a consequence, the observed p-values 163

were judge taking the sample size and the observed effect size into account. The uropathogens 164

were clustered using hierarchical clustering (using average linkage) based on the Manhattan 165

distance between the standardized U-bacterial-, U-leukocyte- and U-erythrocyte counts. The 166

R-package PVclust (20) was used to identify robust clusters in the observed dendrogram. All 167

statistical analyses were conducted using R version 2.9.1 (R Development Core Team, 2009). 168

169

170

Results 171

A total of 1,587 consecutive urine specimens from patients with suspected UTI were eligible 172

for urine culture and flow cytometer analysis. Of these 772 were excluded due to specimens 173

from urine catheters (125), mixed flora without a dominating pathogen (608), pregnancy 174

(128) and those without clinical information (5). The remaining 823 specimens were included 175

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of whom 620 were culture positive and 203 culture negative. The majority (67.5%, p < 0.001) 176

of specimens originated from women. The mean age for men and women was 61.9 (standard 177

deviation 20.8) and 59.9 (standard deviation 25.5) years, respectively. Outpatients represented 178

79.6% and inpatients 19.4%. Of the included specimens 54.4% yielded growth of > 108 179

CFU/L, 17.3% had 107-10

8 CFU/L, 4.4% had 10

6-10

7 and 24.9% were culture negative. 180

The dominating species was E. coli 64.5%, followed by Enterococcus spp. 8.2%, Klebsiella 181

spp. 7.2% and Staphylococcus spp. 5.0% (Table 1). 182

Among culture positive, 91% of specimens had 108, 7% had 10

7, 2% had 10

6 CFU/L of which 183

mixed flora was found in 17%, 53% and 0% of these specimens, respectively. Among patients 184

with 108 and <10

8 CFU/L, E. coli represented 65.6 and 63.4% of the uropathogens, 185

respectively. The distributions of uropathogens other than E. coli were also similar in both 186

groups. 187

Overall, specimens with gram-negative bacteria were associated with significantly (p <0.001) 188

higher U-bacterial counts (median 16,777/µL) compared with gram-positive bacteria 189

(2,271/µL). 190

We found significant correlations between: the concentration of uropathogens (bacteria/µL) 191

and U-leukocyte counts (Spearman’s rho = 0.26, p < 0.001), the concentration of U-bacteria- 192

and U-erythrocyte counts (Spearman’s rho = 0.15, p < 0.001) as U-leukocyte counts and U-193

erythrocyte counts (Spearman’s rho = 0.51, p < 0.001) (Figure 1 D-E). The outcomes of 194

bacterial-, leukocyte- and erythrocyte counts (particles/µL) for groups- or individual 195

uropathogens were compared against the FCA characteristics for E. coli as well as specimens 196

with negative culture (Table 1 and Figure 1-3). 197

Specimens with E. coli had high U-bacterial- (17,914/µl), U-leukocyte- (348/µL) and U-198

erythrocyte counts (23/µL) compared with culture negative specimens (33, 7 and 9/µL, 199

respectively), (Table 1). 200

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Among gram-negatives, urine specimens with Klebsiella spp. were associated with higher U-201

bacterial counts (24,240/µL, p=0.46) but lower U-leukocyte (160/µL, p < 0.05) and U-202

erythrocyte- (18/µL, p=0.67) counts than those with E. coli. Among Klebsiella, K. oxytoca 203

was associated with higher U-leukocyte counts than K. pneumoniae (351 vs 153/µL) but both 204

species had similar U-erythrocyte counts (16 and 17/µL, respectively), (Table 1). 205

In comparison, specimens with Citrobacter spp. (9 isolates) have significant lower U-206

erythrocyte counts (6/µL, p<0.05) and lower U-bacterial counts (8,405/µL, p=0.27) and U-207

leukocyte counts (144/µL, p=0.09) than E. coli. The 12 isolates of P. mirabilis had 208

significantly lower U-bacterial counts (1,956/µL, p < 0.05), higher U-leukocyte- (903/µL, p 209

0.48) and U-erythrocyte counts (52/µL, p 0.15) than E. coli. In contrast, P. vulgaris had 210

despite high U-bacteria counts (13,107/µL), low U-leukocyte- (79/µL) and high U-211

erythrocyte counts (197/µL). Of the 12 Pseudomonas isolates, 11 represented P. aeruginosa 212

which had significantly lower U-bacterial- (6,888/µL, p < 0.05), higher U-leukocyte counts 213

(1,278/µL, p=0.08) and significantly higher U-erythrocyte counts (73/µL, p < 0.05) than E. 214

coli (Table 1). 215

Among gram-positive bacteria, staphylococci were the second most common genus after 216

enterococci (31 isolates vs. 51). Staphylococci had significantly lower U-bacterial counts 217

(3,392/µL, p < 0.05) and higher U-leukocyte counts (466 /µL, p <0.05) - and U-erythrocyte 218

counts (24/µL, p=0.53) than E. coli. 219

Enterococci (E. faecalis and E. faecium, 42 and 9 isolates, respectively) were associated with 220

significantly lower bacterial counts (2,103/µL, p <0.05) than E. coli and E. faecalis had higher 221

U-leukocyte counts than E. faecium (200 vs. 34/µL, p 0.45). Alpha-haemolytic streptococci 222

and GBS were both associated with low leukocyte counts (64 and 36/µL, respectively) and 223

low erythrocyte counts (19 and 19/µL, respectively). However GBS had low bacterial counts 224

(272/µL). 225

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The relation between the most common uropathogens are summarised in a 3-dimensional plot 226

of the outcome of FCA (U-leukocyte-, U-erythrocyte- and U-bacterial counts) (Figure 2) and 227

relation between uropathogens is presented in the dendrogram (Figure 3). According to these 228

findings uropathogens could be classified into four groups (I-IV, Figure 3). The first group 229

consists of E. coli, K. pneumoniae and K. oxytoca, the second of P. aeruginosa, P. mirabilis, S. 230

aureus and the third of Citrobacter spp. Finally the fourth group consists of Alpha- 231

Streptococci, CoNS, E. faecalis, E. faecium, Morganella morganii, Enterobacter spp., GBS 232

and Citrobacter that cluster together with the culture negative specimens. 233

234

235

Discussion 236

In this study we evaluated the presence of leukocyte- and erythrocyturia for different 237

uropathogens among patients with suspected UTI measured by FCA analysis. In addition the 238

FCA results for different uropathogen were compared with E. coli, the most prevalent 239

uropathogen and to the culture negative specimens. 240

The distribution of uropathogens in the present study was consistent with previous reports 241

(6, 21). However, S. saprophyticus represented only <1% of the uropathogens but a similar 242

prevalence has been reported by others (22). The low prevalence of S. saprophyticus in the 243

present study is explained by the high mean age (59.9 year) of the included women and that 244

the study was performed during the winter season. In addition elderly are more likely to have 245

asymptomatic bacteriuria, altered sense of UTI symptoms and probably also a weakened 246

immune response (23), factors that differs from younger adults and may influence the 247

conclusions of the present study to an overall population of patients with UTI. Gram-positive 248

bacteria were often associated with lower bacterial counts than gram-negative bacteria 249

presumably because the former often form aggregates (staphylococci) or chains (streptococci) 250

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(24). The bacterial counts of aggregated bacteria may be underestimated by the instrument 251

and incorrectly reported with lower counts in contrast to gram-negative bacteria which are 252

present in the urine as single planktonic bacteria. In other studies, the urinalysis instrument 253

has been shown to correlate well to manual microscopy (25). 254

Bacterial-, leukocyte- and erythrocyte counts differ among gram-negative uropathogens. 255

Citrobacter were associated with nearly lack of erythrocyturia (<10 erythrocytes/µL) 256

indicating that Citrobacter are less: invasive, virulent or immunostimulating compared with 257

other uropathogens. In contrast, high erythrocyte counts were observed for P. vulgaris 258

(197/µL) and S. saprophyticus (154/µL). Whether the high erythrocyte count is an effect of 259

invasiveness or inflammatory response to an uropathogen or both, is unclear. However, both 260

these species are urease producers a property which has been reported as an important 261

bacterial virulence factor, essential for colonization and associated with gastric peptic ulcers 262

in man (26). For Pseudomonas and P. mirabilis we found high erythrocyte- and leukocyte 263

counts despite low bacterial counts. Virulence factors as exotoxins and at least four different 264

proteases have been reported in Pseudomonas that may cause bleeding and tissue necrosis 265

(27, 28). 266

However, specimens with high bacterial counts were associated with a high leukocyte and 267

erythrocyte counts (Figure 1 D-E) indicating that the bacterial load is of importance for the 268

inflammatory response of leukocytes and erythrocytes in urine during UTI. 269

Finally, U-leukocyte and U-erythrocyte counts for the most common uropathogen species 270

were plotted and presented in a 3 dimensional figure (Figure 2). As can be seen, E. coli and K. 271

pneumoniae/oxytoca have similar characteristics in the present study. However E. coli is by 272

far a more common cause of UTI and has virulence factors of importance that are not 273

measured by FCA (29). Despite this the FCA characteristics of the uropathogens differs from 274

the present Swedish classification in primary-, secondary- and doubtful uropathogens (5). In 275

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particular urine specimens with S. saprophyticus show lower U-leukocyte counts compared to 276

those with P. aeruginosa, S. aureus and P. mirabilis although S. saprophyticus is classified as 277

a primary UTI pathogen. 278

The fourth group of uropathogens represented by GBS, E. faecalis, Enterobacter spp. and M. 279

morganii is associated with low leukocyte and erythrocyte counts similar to what was seen in 280

culture negative specimens. 281

Urinalysis with automated FCA has four diagnostic potentials. First, the ability to separate 282

gram-negative- from gram-positive bacteria based on bacterial counts (30, 31). Secondly, to 283

predict bacterial species (e.g Citrobacter) or groups of bacteria (e.g. E. coli / Klebsiella). Such 284

information can assist the clinician in deciding which antimicrobial (or not) that should be 285

initiated for treatment pending the outcome of urine culture. Thirdly, the quality of a urine 286

specimen could be examined by the numbers of epithelial cells present in the specimen. High 287

epithelial cell counts indicate suboptimal sampling which may affect the interpretation of 288

culture results. Fourthly, the outcome of FCA can guide laboratory staff to improve diagnosis 289

in culture negative specimens with high U-leukocyte counts. In the present study 24.9% of the 290

specimens were culture negative, despite clinical signs of UTI, which is in accordance to 291

other studies (6, 32, 33). Culture negative specimens may be due to suboptimal culture 292

conditions in particular for anaerobic bacteria. In the present study 203 specimens were 293

culture negative of whom 30 and 22 specimens had more than 100 or 200 U-leukocytes, 294

respectively. In these specimens, an expanded urine culture protocol compared with standard 295

protocols should have been applied for detection of fastidious bacteria. 296

The Sysmex UF-1000 instrument also measures additional results than bacterial-, leukocyte- and 297

erythrocyte counts. Adding other FCA results (e.g. squamous cells, conductivity, pH etc) into 298

consideration might improve characterization and diagnosis of uropathogens. Inclusion of 299

improved staining techniques (fluorophores) that identify the four most prevalent uropathogens 300

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would identify nearly 90% of the causative uropathogens. Further studies are warranted to 301

improve diagnosis uropathogens in urine specimens using FCA and to confirm the results from 302

the present study, especially as some of the bacteria are present in a low number. 303

The urine specimens analysed in this study does (probably) not represent specimens from an 304

average population but rather specimens from a selected population of patients who were 305

examined due to suspected UTI, pyelonephritis, failure of treatment or control after treatment. 306

Contrary, the results are representative for urine specimens that are examined in our 307

laboratory. 308

In essence, except ruling out culture negative urine specimens, FCA improves handling of 309

urine specimens and diagnosis of UTI. The outcome of FCA adds information of the numbers 310

of uropathogens and the leukocyte- and erythrocyte counts in urine specimens among patients 311

with suspected UTI. According to these FCA characteristics, uropathogens can be classified 312

into four classes of which Klebsiella and E. coli had similar characteristics. Specimens 313

containing Citrobacter were associated with nearly absence of erythrocyturia. Urine specimen 314

examined by FCA may predict the causative uropathogen by its FCA characteristics which 315

may have clinical implications in guiding the clinicians towards appropriate antimicrobial 316

treatment pending culture results. 317

318

319

ACKNOWLEDGMENTS 320

We acknowledge Tamara Matti, Department of Infectious Diseases, University Hospital of 321

Umeå for support and registration of datasets and Dr. Kjell Leonardsson, Swedish University 322

of Agricultural Science, Umeå for the assistance in the presentation of Figure 2. The study 323

was financed by the University of Umeå, Sweden. 324

We declare no conflict of interest. 325

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326

References 327

1. Grover S, Srivastava A, Lee R, Tewari AK, Te AE. 2011. Role of inflammation in bladder 328

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2. Stamm WE, Hooton TM. 1993. Management of urinary tract infections in adults. N Engl 330

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2013. Healthcare-associated, community-acquired and hospital-acquired bacteraemic 359

urinary tract infections in hospitalized patients: a prospective multicentre cohort study in 360

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sensitivity of bacteria associated with community-acquired urinary tract infection in 387

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urinary tract infections in older people. Clinical Interventions in Aging 6:173-180 390

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long-lasting human diseases. Curr Protein Pept Sci. 13:789-806. 400

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particle analyzer UF-1000i screening for urinary tract infection in nonpregnant women. 411

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discrimination of Gram-positive and Gram-negative bacteria in liquid samples by using 414

NaOH-sodium dodecyl sulfate solution and flow cytometry. PLoS One. 7:e.0047093: 1-10. 415

32. Pappas PG. 1991. Laboratory in the diagnosis and management of urinary tract infections. 416

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Gai X, Wolfe AJ, Schreckenberger PC. 2014. Urine is not sterile: use of enhanced urine 419

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422

423

424

425

426

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Table 1 427

Bacteria-, leukocyte and erythrocyte counts (median values) in urine among patients with suspected urinary tract infection estimated by flow 428

cytometer analysis. 429

430

Group Bacteria Number Percentage

Positive

Cell counts – median value / µL

Bacterial cells WBCa RBC

b

ECc Escherichia coli

400 64.5 17,914 348 23

KCc

Klebsiella pneumoniae

Klebsiella oxytoca

Klebsiella ”other”

All Klebsiella spp.(Kd)

Enterobacter spp.

33

10

2

45

5

5.3

1.6

0.3

7.2

1.5

20,866

27,239

29,817

24,240

4,345

(+,+*)

(+,+)

(+,+*)

(-,+*)

(-,+*)

153

351

70

160

166

(-*,+*)

(+,+*)

(-,+)

(-*,+*)

(-*,+*)

16

17

55

18

30

(-,+)

(-,+)

(+,+)

(-,+*)

(+,+)

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19 19

Citrobacter spp.

Citrobacter freundi

Acinetobacter spp.

Pantoea spp.

Aggregated

9

1

1

1

62

0.2

0.2

0.2

0.2

10.0

8,405

15,220

163

7,143

15,346

(-,+*)

(-,+)

(-,+)

(-,+*)

(-,+*)

144

226

118

56

157

(-,+*)

(-,+)

(-,+)

(-,+)

(-*,+*)

9

7

24

15

17

(-*,+)

(-,-)

(+,+)

(-,+)

(-,+*)

PRc Proteus vulgaris

Proteus mirabilis

Morganella morganii

Providentia rettgeri

Aggregated

3

12

5

1

21

0.5

1.9

0.8

0.2

3.4

13,107

1,955

249

30,689

2,128

(-,+*)

(-*,+*)

(-*,+)

(+,+)

(-*,+*)

79

902

207

9

207

(-,+)

(+,+*)

(-,+*)

(-,+)

(-,+*)

197

52

19

8

38

(+,+)

(+,+*)

(-,+)

(-,-)

(+,+*)

PSc P. aeruginosa

Pseudomonas ”other”

Aggregated

11

1

12

1.8

0.2

1.9

6,888

3,467

5,177

(-*,+*)

(-,+)

(-*,+*)

1,278

294

1,175

(+,+*)

(-,+)

(+,+*)

73

12

62

(+*,+*)

(-,+)

(+*,+*)

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20 20

STc S. saprophyticus

d

S. aureuse

CoNS f

Aggregated

4

10

17

31

0.6

1.6

2.7

5.0

3,732

474

4,383

3,392

(-,+*)

(-*,+*)

(-*,+*)

(-*,+*)

200

936

462

466

(-,+)

(+,+*)

(+,+*)

(+,+*)

154

32

19

24

(+,+)

(+,+*)

(-,+*)

(+,+*)

ENc Enterococcus faecalis

Enterococcus faecium

Aggregated

42

9

51

6.8

1.5

8.2

2,623

1,116

2,103

(-*,+*)

(-*,+*)

(-*,+*)

200

34

120

(-*,+*)

(-,+*)

(-*,+*)

19

35

20

(-*,+*)

(+,+*)

(-,+*)

SRc Alpha-streptococci

Streptococci Group C

Streptococci Group A

Streptococci Group G

Gemella hemolysans

Aggregated

11

4

1

3

1

20

1.8

0.6

0.2

0.5

0.2

3.2

2,877

1,286

111

467

4,503

1,583

(-*,+*)

(-,+*)

(-,+)

(-,+*)

(-,+)

(-*,+*)

64

1,399

782

96

973

269

(-,+*)

(+,+*)

(+,+)

(-,+*)

(+,+)

(-,+*)

19

59

6

28

16

22

(-,+*)

(+,+)

(-,-)

(+,+)

(-,-)

(-,+*)

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21 21

GBc Streptococcus

agalactiae

20 3.2 272 (-*,+*) 36 (-*,+*)

19 (-,+*)

OTc Candida glabrata

Diptheroid rod

H. influenzae

Aggregated

1

1

1

3

0.2

0.2

0.2

0.5

518

18,266

2,263

2,263

(-,+)

(+,+)

(-,+)

(-,+*)

94

65

434

94

(-,+)

(-,+)

(+,+)

(-,+*)

4

40

108

40

(-,-)

(+,+)

(+,+)

(+,+)

NEc,g

Negative / No growth 195 NA 33 7 9

431

a WBC= white blood cells/ leukocytes;

b RBC= red blood cells/erythrocytes.

c denotes all uropathogens or group of uropathogens presented in the 432

right column. ddenote all Klebsiella species only (K);

e Staphylococcus saprophyticus;

f Staphylococcus aureus;

g Coagulase negative 433

staphylococci; f Negative control 434

“+” (“-“) indicates that the observed value is higher (lower) than the value observed for 435

E. coli / negative culture. * indicate that the corresponding p-value < 0.05. 436

437

438

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Figure 1 439

Bacterial- leukocyte and erythrocyte counts per microlitre (logarithmic scale with base 2) in 440

urine for uropathogens, groups of uropathogen and specimens with negative culture estimated 441

by flow cytometry analysis. 442

443

444

445

446

447

448

449

450

Figure A: log. bacterial counts vs. bacterial counts. Figure B: log. leukocyte counts vs. 451

bacterial counts. Figure C: log. erythrocyte counts vs. bacterial counts. Figure D: log. 452

leukocyte counts vs. bacterial counts. Figure E: log. erythrocyte counts vs. bacterial counts. 453

Figure F: log. erythrocyte counts vs. leukocyte counts /µl (logarithmic values) in urine. 454

EC = E. coli / lane 1 = E. coli (red colour in figure D-F); KC/2 = Klebsiella spp., Enterobacter 455

spp., Citrobacter spp., Acinetobacter spp., Pantoea spp. K = Klebsiella spp., PR/3 = Proteus 456

spp., Morganella spp. and Providentia rettgeri group; EN/4 = Enterococcus spp. group; PS/5 457

= Pseudomonas spp. group; ST/6 = Staphylococcus spp. group; SR/7 = Streptococci (A,C,G), 458

Alpha-haemolytic streptococci and Gemella hemolysans group; GB/8= Streptococci 459

agalactiae (GBS). NE/0 = specimens with negative culture (green colour, in figure D-F). 460

The median for E. coli and the negative culture are shown with solid and dashed lines (A-F) 461

respectively. 462

463

464

465

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Figure 2 466

Three dimensional plot of the median bacterial-, leukocyte- and erythrocyte counts per 467

microliter in urine estimated from flow cytometry analysis for different uropathogens among 468

patients with suspected urinary tract infection. 469

470

471

472

473

474

475

476

477

“Star” (in left lower corner) represents culture negative specimens. 478

Y-axis: RBC = erythrocyte blood cell counts/µl. X-axis: Bacterial counts/µl. Z-axis: WBC= 479

white blood cell counts/µl (leukocytes). Alpha-strep = alpha haemolytic streptococci 480

481

482

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Figure 3. 483

Dendrogram (hierarchical) presenting relationship between bacteria and bacterial clusters 484

based on bacteria-, leukocyte- and erythrocyte counts//µl (median values) for bacteria ≥5 in 485

numbers. 486

487

488

489

490

491

492

493

494

495

Dendrogram based on bacteria with ≥5 in numbers. * Presented order for au value (left) and 496

bp value (right). Clusters analysis on uropatogens (cluster I-IV). “High” au/bp values (%) 497

indicate robust clusters. 498

499

500

501

502

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log

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5 10 15

05

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1

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log Leukocy te counts

log

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thro

cyte

co

un

ts

0 2 4 6 8 10 12

05

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15

A B C

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Page 26: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

Escherichia coli

Pseudomoas aeruginosa

Klebsiella pneumoniaeKlebsiella oxytoca

Streptococcus Group C

Proteus mirabilisStaphylococcus aureus

Staphylococcus saprophyticus

Coagulase-negative staphylococci

Citrobacter spp.

Morganella morganii

GBS

Enterocuccus faecalisEnterobacter spp.

Enterocccus faecium

α-strept

RB

C

LK

C

Bacterial counts

Escherichia coli

Pseudomoas aeruginosa

Klebsiella pneumoniaeKlebsiella oxytoca

Streptococcus Group C

Proteus mirabilis

Staphylococcus aureusStaphylococcus saprophyticus

Coagulase-negative staphylococci

Citrobacter spp.

Morganella morganii

GBS

Enterocuccus faecalisEnterobacter spp.

Enterocccus faecium

α-strept

RB

C

WB

CBacterial counts

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Page 27: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

au / bp *

97 70

96 70 85 58

42 100

91 36 3

3 22

85 53

62 33

85 53

41

79 30

66 92

22

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Page 28: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

Table 1

Bacteria-, leukocyte and erythrocyte counts (median values) in urine among patients with suspected urinary tract infection estimated by flow

cytometer analysis.

Group Bacteria Number Percentage

Positive

Cell counts – median value / µL

Bacterial cells WBCa RBC

b

ECc Escherichia coli

400 64.5 17,914 348 23

KCc

Klebsiella pneumoniae

Klebsiella oxytoca

Klebsiella ”other”

All Klebsiella spp.(Kd)

Enterobacter spp.

33

10

2

45

5

5.3

1.6

0.3

7.2

1.5

20,866

27,239

29,817

24,240

4,345

(+,+*)

(+,+)

(+,+*)

(-,+*)

(-,+*)

153

351

70

160

166

(-*,+*)

(+,+*)

(-,+)

(-*,+*)

(-*,+*)

16

17

55

18

30

(-,+)

(-,+)

(+,+)

(-,+*)

(+,+)

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Page 29: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

Citrobacter spp.

Citrobacter freundi

Acinetobacter spp.

Pantoea spp.

Aggregated

9

1

1

1

62

0.2

0.2

0.2

0.2

10.0

8,405

15,220

163

7,143

15,346

(-,+*)

(-,+)

(-,+)

(-,+*)

(-,+*)

144

226

118

56

157

(-,+*)

(-,+)

(-,+)

(-,+)

(-*,+*)

9

7

24

15

17

(-*,+)

(-,-)

(+,+)

(-,+)

(-,+*)

PRc Proteus vulgaris

Proteus mirabilis

Morganella morganii

Providentia rettgeri

Aggregated

3

12

5

1

21

0.5

1.9

0.8

0.2

3.4

13,107

1,955

249

30,689

2,128

(-,+*)

(-*,+*)

(-*,+)

(+,+)

(-*,+*)

79

902

207

9

207

(-,+)

(+,+*)

(-,+*)

(-,+)

(-,+*)

197

52

19

8

38

(+,+)

(+,+*)

(-,+)

(-,-)

(+,+*)

PSc P. aeruginosa

Pseudomonas ”other”

Aggregated

11

1

12

1.8

0.2

1.9

6,888

3,467

5,177

(-*,+*)

(-,+)

(-*,+*)

1,278

294

1,175

(+,+*)

(-,+)

(+,+*)

73

12

62

(+*,+*)

(-,+)

(+*,+*)

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Page 30: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

STc S. saprophyticus

d

S. aureuse

CoNS f

Aggregated

4

10

17

31

0.6

1.6

2.7

5.0

3,732

474

4,383

3,392

(-,+*)

(-*,+*)

(-*,+*)

(-*,+*)

200

936

462

466

(-,+)

(+,+*)

(+,+*)

(+,+*)

154

32

19

24

(+,+)

(+,+*)

(-,+*)

(+,+*)

ENc Enterococcus faecalis

Enterococcus faecium

Aggregated

42

9

51

6.8

1.5

8.2

2,623

1,116

2,103

(-*,+*)

(-*,+*)

(-*,+*)

200

34

120

(-*,+*)

(-,+*)

(-*,+*)

19

35

20

(-*,+*)

(+,+*)

(-,+*)

SRc Alpha-streptococci

Streptococci Group C

Streptococci Group A

Streptococci Group G

Gemella hemolysans

Aggregated

11

4

1

3

1

20

1.8

0.6

0.2

0.5

0.2

3.2

2,877

1,286

111

467

4,503

1,583

(-*,+*)

(-,+*)

(-,+)

(-,+*)

(-,+)

(-*,+*)

64

1,399

782

96

973

269

(-,+*)

(+,+*)

(+,+)

(-,+*)

(+,+)

(-,+*)

19

59

6

28

16

22

(-,+*)

(+,+)

(-,-)

(+,+)

(-,-)

(-,+*)

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Page 31: JCM Accepts, published online ahead of print on 3 …...140 UTI (nitrit e test positive and/or moderate to high leukocyturia). Among these, s pecimens with 141 one pathogen were included

GBc Streptococcus

agalactiae

20 3.2 272 (-*,+*) 36 (-*,+*)

19 (-,+*)

OTc Candida glabrata

Diptheroid rod

H. influenzae

Aggregated

1

1

1

3

0.2

0.2

0.2

0.5

518

18,266

2,263

2,263

(-,+)

(+,+)

(-,+)

(-,+*)

94

65

434

94

(-,+)

(-,+)

(+,+)

(-,+*)

4

40

108

40

(-,-)

(+,+)

(+,+)

(+,+)

NEc,g

Negative / No growth 195 NA 33 7 9

a WBC= white blood cells/ leukocytes;

b RBC= red blood cells/erythrocytes.

c denotes all uropathogens or group of uropathogens presented in the

right column. ddenote all Klebsiella species only (K);

e Staphylococcus saprophyticus;

f Staphylococcus aureus;

g Coagulase negative

staphylococci; f Negative control

“+” (“-“) indicates that the observed value is higher (lower) than the value observed for

E. coli / negative culture. * indicate that the corresponding p-value < 0.05.

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