AAC Accepts, published online ahead of print on 4 November 2013 Antimicrob. Agents Chemother. doi:10.1128/AAC.01400-13 Copyright © 2013, American Society for Microbiology. All Rights Reserved.

1 2

Application of DNA chip scanning technology for the automatic detection of Chlamydia trachomatis and Chlamydia pneumoniae inclusions

3 4

Running title: Chlamydia inclusion detection system ChlamyCount

5 6 7

Anita Bogdanov1*, Valeria Endrész2*, Szabolcs Urbán3, Ildikó Lantos2, Judit Deák1, Katalin Burián2, Kamil Önder4, Ferhan Ayaydin5, Péter Balázs3, Dezs P. Virok1#

8 9

1, Institute of Clinical Microbiology, University of Szeged, Szeged, Hungary Address:

10

H-6725 Szeged Semmelweis str. 6.

11

2, Institute of Medical Microbiology and Immunobiology, University of Szeged,

12

Szeged, Hungary Address: H-6720 Szeged, Dóm sqr. 10.

13

3, Department of Image Processing and Computer Graphics, Institute of Informatics,

14

University of Szeged, Szeged, Hungary H-6720, Szeged, Árpád sqr. 2.

15

4, Department of Dermatology, Paracelsus Medical University, Salzburg, Austria

16

Address: 5020 Salzburg, Strubergasse 21.

17

5, Cellular Imaging Laboratory, Biological Research Center, Hungarian Academy of

18

Sciences, Hungary Address: H-6726 Szeged, Temesvári krt. 62.

19 20

*: these authors contributed equally

21

#: corresponding author

22

email of the corresponding author: [email protected]

23 24

1

25

Abstract

26 27

Chlamydiae are obligate intracellular bacteria that propagate in the inclusion, a

28

specific niche inside the host cell. The standard method for counting chlamydiae is

29

the immunofluorescent staining and manual counting of chlamydial inclusions. High

30

or medium throughput estimation of the reduction in chlamydia inclusions should be

31

the basis of testing antichlamydial compounds and other drugs that positively or

32

negatively influence chlamydial growth, yet low-throughput manual counting is the

33

common approach. To overcome the time-consuming and subjective manual

34

counting we developed an automatic inclusion counting system based on a

35

commercially available DNA chip scanner. Fluorescently labeled inclusions are

36

detected by the scanner, and the image is processed by ChlamyCount, a custom

37

plugin of the ImageJ software environment. ChlamyCount was able to measure the

38

inclusion counts over a one log dynamic range with high correlation to the theoretical

39

counts. ChlamyCount was capable of accurately determining the minimum inhibitory

40

concentration of the novel antimicrobial compound PCC00213 and the already

41

known antichlamydial antibiotics moxifloxacin and tetracycline. ChlamyCount was

42

also able to measure the chlamydial growth altering effect of drugs that influence

43

host-bacterium

44

cycloheximide. ChlamyCount is an easily adaptable system for testing antichlamydial

45

antimicrobials and other compounds that influence Chlamydia-host interactions.

interaction

such

as

interferon-gamma,

DEAE-dextran

and

46

2

47

Introduction

48 49

Chlamydia pneumoniae (C. pneumoniae) and various C. trachomatis serovars

50

are involved in medically important human diseases. C. pneumoniae is a frequent

51

source of community acquired pneumonia and is suspected of participating in the

52

pathogenesis of chronic diseases such as asthma and atherosclerosis (1, 2). C.

53

trachomatis serovars A-C are involved in trachoma pathogenesis; D-K serovars

54

induce pelvic inflammatory diseases (PID), infertility and reactive arthritis, while LGV

55

serovars are the pathogens that cause lymphogranuloma venereum, an STD with

56

systemic manifestations. The antibiotic therapy of chlamydia infections includes

57

tetracyclines and macrolides (3-5). While the antibiotic therapy is effective in the

58

majority of the cases, tetracycline and azithromycin resistance was reported (6, 7).

59

Discovery of novel antimicrobial compounds for treatment and possible

60

chemoprevention is a medically important research task. High-throughput testing of

61

potentially antichlamydial compounds is hampered by the small size and obligate

62

intracellular propagation of the bacterium. After infecting the host cell, the chlamydia

63

propagates in a distinct cellular space called an inclusion. Since, at a low multiplicity

64

of infection, one chlamydia can form one inclusion, the original chlamydia count is

65

indirectly measured by labeling and manual microscopy counting of inclusions. To

66

circumvent the labor-intensive and subjective manual counting, we designed a

67

relatively low-cost, easy-to-use system that automatically counts chlamydial

68

inclusions. The system consists of a commercial DNA chip scanner and custom-

69

made image analysis software. DNA chip and microarray scanners are widely used

70

devices for the high resolution scanning of glass slides that contain a large number of

71

DNA probes that bind fluorescently labeled cDNAs or DNAs. We applied this system

72

to detect fluorescently labeled chlamydial inclusions in host cells propagated in a 16-

73

well chamber slide. We designed ChlamyCount, a custom ImageJ plugin for the

74

completely automatic detection of fluorescently labeled chlamydia inclusions on the

75

scanned image. ImageJ is a Java-based, platform-independent, freely available

76

image analysis software package (8). ImageJ can be specifically tailored to a given

77

application using user-made plugins. The image processing with ChlamyCount is

78

almost fully automatic, including the extraction of the areas of the 16 wells, the

79

automatic detection of inclusions in each well, dissecting and individually counting

80

inclusions and automatic reporting. 3

81

ChlamyCount was used to determine the minimum inhibitory concentration

82

(MIC) of the known antichlamydial antibiotics tetracycline and moxifloxacin and the

83

novel antimicrobial compound PCC00213. ChlamyCount was also used to measure

84

the effect of compounds that indirectly influence the chlamydial growth cycle such as

85

interferon-gamma (IFN-γ), DEAE-dextran and cycloheximide. The ChlamyCount

86

ImageJ

87

szeged.hu/ipcg/projects/medical.html.

plugin

is

available

for

non-commercial

use

at

http://www.inf.u-

88 89

Materials and Methods

90 91

Chlamydial strains. Two Chlamydia species were used in this study: C. trachomatis

92

(serovar D, UW-3/CX reference strain and serovar L2, strain VR-577, ATCC) and C.

93

pneumoniae (CWL029, ATCC). Chlamydia strains were propagated and partially

94

purified according to methods described previously with modifications (9, 10). Briefly,

95

DEAE-dextran (45 mg/ml in Hank’s balanced salt solution, HBSS) treated McCoy

96

cells were infected with C. trachomatis serovar D, and after a 2-day incubation in a

97

culture medium (MEM with Earle salts supplemented with 10% heat-inactivated fetal

98

bovine serum (FBS), 0,5% glucose, 2 mmol/l L-glutamine, 1x non-essential amino

99

acids, 8 mmol/l HEPES, 25 µg/ml gentamicin) in the presence of 1 µg/ml

100

cycloheximide, the infected cell layers were washed with PBS, frozen and covered

101

with 50 µl/cm2 sucrose-phosphate-glutamic acid buffer (SPG). After 2 freeze-thaw

102

cycles the cells were collected and separated from the cell debris by a 10 min, 800 g

103

centrifugation. C. trachomatis serovar L2 and C. pneumoniae were cultured in HEp2

104

cells and partially purified and concentrated by 30000 g centrifugation as described

105

previously (11).The pelleted EBs were re-suspended in SPG. Stocks of chlamydial

106

EBs were aliquoted and stored in SPG until use at -80 °C. The titer of the infectious

107

EBs was determined by inoculation of serial dilutions of the EB preparation onto

108

McCoy (C. trachomatis) or HEp-2 (C. pneumoniae) monolayers grown on 13mm

109

diameter cover slips. Inoculated cells were centrifuged for 1 h at 800 g, and after 24 h

110

(C. trachomatis) or 48 h (C. pneumoniae) culture in cycloheximide containing growth

111

medium, the cells were fixed with acetone and stained with monoclonal anti-

112

Chlamydia LPS antibody (AbD Serotec, Oxford, UK) and FITC-labeled anti-mouse

113

IgG (Sigma-Aldrich, St. Louis, MO, USA). The number of cells containing chlamydial

4

114

inclusions was counted under a UV microscope, and the titer was expressed as

115

IFU/ml.

116 117

Culture of chlamydiae on a chamber slide. Chamber slides with 16 wells (Lab-Tek

118

Chamber Slide System) consisting of a removable, plastic chamber attached to a

119

specially treated standard glass slide were used to culture host cells for infection with

120

the Chlamydia strains. The slides were treated with 0.01% poly-L-lysine at room

121

temperature (RT) for 15 minutes in order to optimize cell attachment. McCoy cells

122

were transferred into the wells of the chamber slides at a density of 3x104 cells/well in

123

100 µl of culture medium (see above). The slides were incubated for 1 hour at room

124

temperature in order to reduce the edge effect (12, 13), then overnight at 37 °C under

125

5% CO2 atmosphere to obtain a 90% confluent cell layer. For C. trachomatis serovar

126

D infection, the wells were washed with 200 µl/well of Hank’s balanced salt solution

127

(HBSS), then a 1% DEAE-dextran solution (80 µl/well) was added to all wells and

128

were incubated for 15 minutes, RT. After removal of the DEAE-dextran solution, the

129

cells were infected at 1 multiplicity of infection (MOI, 1 IFU/cell) in each well or with

130

serial 2-fold dilutions of stock in SPG starting with 1 IFU/cell. SPG was measured into

131

similarly treated control wells. The chamber slides were incubated at room

132

temperature in a vertical shaker (180 rpm) for 2 hours. The slides infected with C.

133

trachomatis serovar L2 with MOI ranging from 1 IFU/cell to 1:64 IFU/cell in SPG were

134

incubated at 35 °C under 5% CO2 for 2 hours without DEAE-dextran pretreatment.

135

For C. pneumoniae infection the DEAE-dextran treatment was used, or the slides

136

were centrifuged with C. pneumoniae stock with MOI ranging from 1:8 to 1:512, 400

137

g, 60 minutes at RT. After infection, the EB containing inoculums in the wells were

138

replaced with a culture medium containing 1 µg/ml cycloheximide. The slides were

139

incubated at 37 °C under 5% CO2 for 24 or 48 hours after infection with C.

140

trachomatis D and L2 or C. pneumoniae, respectively, and the cells were fixed for

141

immunofluorescence staining.

142

Moxifloxacin (Avelox,

143

Inhibition of chlamydial growth with antibiotics and IFN-

144

Bayer Pharma AG) diluted in a culture medium and tetracycline hydrochloride powder

145

(Sigma-Aldrich) dissolved in distilled water were used. The concentration range of

146

0.25-0.004 µg/ml for moxifloxacin and of 0.04-0.0006 µg/ml for tetracycline with 2-fold

5

147

dilutions were tested. The stock solution of antibacterial drug candidate PCC00213

148

(10 mg/ml) was prepared in DMSO, and was diluted 2-fold in DMSO until 0.156

149

mg/ml. Cycloheximide containing culture medium was prepared by a 100-fold dilution

150

of the DMSO-diluted compound, resulting in a series of concentration ranging from

151

100 to 1.56 µg/ml with 1% DMSO content. After infection of McCoy cells with C.

152

trachomatis D (MOI 1), the culture medium with cycloheximide was supplemented

153

with the serial 2-fold dilutions of the respective antibiotics and was added to duplicate

154

wells. Control infected wells were cultured without adding any antibiotics; for

155

PCC00213, 1% DMSO containing medium was added to the control wells. Murine

156

IFN-γ (Peprotech, Rocky Hill, NJ, USA) was reconstituted according to the

157

manufacturers’ instructions and the 20 000 U/ml stock solution was stored at -80 °C

158

until use. On the day before infection, the established cell layers were treated with

159

serial twofold dilutions of murine IFN-γ over the concentration range of 100-0.046

160

IU/ml. As a control, human IFN-γ (Peprotech, Rocky Hill, NJ, USA) was also added

161

over a concentration range of 100 IU/ml-1.5 IU/ml. After the infection procedure, IFN-

162

γ diluted in a cycloheximide-free medium was added at the same concentration as

163

that used for the pretreatment of cells before infection.

164 165

Immunofluorescent labeling and scanning. Cells in chamber slides infected with

166

C. pneumoniae and C. trachomatis were evaluated by immunofluorescent staining.

167

After removing the culture medium from the slides, the cells were washed twice with

168

PBS (200 µl/well). Then the chamber structure was detached from the slides and the

169

cells were fixed with pre-cooled 100% acetone for 10 min at -20 °C. Alexa-647-

170

labeled anti-chlamydia LPS antibody (AbD Serotec, Oxford, UK) diluted 1:200 was

171

used for the detection of chlamydial inclusions. After incubation for 1 h at 37 °C, the

172

cells were washed three times with PBS for 7 minutes each and finally with distillated

173

water. Fluorescence signals were analyzed with an Axon GenePix Personal 4100A

174

DNA-chip scanner and GenePix Pro 6.1 software (Molecular Devices, Sunnyvale,

175

CA, USA) using the Cy5 channel and a 5 µm resolution.

176 177 178

6

179

Image Processing. The scanned images were about 50-60 MB single-image 16-bit

180

.tiff files with an intensity dynamic range of four orders of magnitude. The images

181

were processed by ChlamyCount in two phases: preprocessing and analysis. In the

182

preprocessing phase, after loading the image, the contrast was enhanced by

183

performing the “Histogram normalization” method of ImageJ. After, the regions of

184

interests (ROI) containing the 16-well areas of the scanned image were cropped. The

185

cropping scheme was specifically designed for the 16-well Lab-Tek Chamber Slide

186

System. In the subsequent steps, the image of each well was processed

187

independently. To reduce noise effects, pixels of the ROI below a predefined

188

threshold were eliminated using the ImageJ threshold operation. The default intensity

189

threshold was set to 15.000, which value had been empirically determined.

190

Nevertheless, depending on the used fluorescent antibody and scanner type, the

191

image intensity may change; hence the user can manually adjust the inclusion

192

intensity and area thresholds. In a further noise-reduction step, a greyscale

193

morphological opening (a morphological erosion followed by a dilation) was applied,

194

using the minimum and maximum filters of ImageJ on a 3x3 window.

195

In the analysis phase, the images of each well were processed independently. First,

196

a binarized copy of the result of the preprocessing phase was produced. Then, the

197

ImageJ Analyze Particles function was called to encounter and outline the particles

198

(potential inclusion or inclusions) in the well. Since confluent inclusions of various

199

shapes could occur, no size or circularity constraints were set during the process. In

200

the next step, the median area of the particles was computed, and particles having

201

an area greater than the calculated median area were further processed. If the

202

perimeter of the particle was less than 500 pixels, then the particle was decomposed

203

by Voronoi-tesselation using the local greyscale minima as seeds, and the Euclidean-

204

distance. However, no splitting was performed if the perimeter of the particle was

205

greater than 500 pixels, because those regions were likely to represent areas of

206

potentially aspecific labeling of the background and/or host cells. Setting a higher

207

intensity threshold in the preprocessing step could reduce the occurrence of such

208

areas. After the splitting step, the ImageJ Analyze Particles function was again called

209

to identify the final number of particles and to find their boundaries, which were

210

highlighted in red on the original greyscale image. Finally, the result of the analysis

211

was reported in .txt, .xls, and .pdf files. The .pdf file contains the numerical results

212

and the processed images of the 16 areas. It should be noted, that for easier visibility 7

213

of the inclusions on the small scale Figures, the images of the 16 areas were further

214

contrast enhanced using the duotone feature of the PhotoFiltre image processing

215

software.

216 217

Confocal Microscopy and Imaging. Confocal laser scanning microscopy was

218

performed using Olympus FV1000 confocal laser scanning microscope (Olympus Life

219

Science Europe GmbH, Hamburg, Germany). Microscope configuration was the

220

following: objective lenses: UPLSAPO 10x (NA:0.4) UPLSAPO 20x (NA:0.75),

221

LUMPLFL 40x (NA:0.8); sampling speed: 4 or 8 µs/pixel; line averaging: 2x; confocal

222

aperture: 200 µm; image dimension: 512x512 pixels; scanning mode: sequential

223

unidirectional; excitation: 633 nm HeNe laser; laser transmissivity: 45%, AlexaFluor

224

647 was detected between 645-745 nm. Transmitted light images were also captured

225

and paired with each fluorescence image using 633 nm laser. Using a 10x objective,

226

16 successive images were captured to encompass the full diameter of each well of

227

the 16-well chamber slide. Images were stitched together to make an image strip of

228

512x8192 pixels using "import image sequence" and "make montage" functions of

229

ImageJ software. Infected cells were identified and manually scored on these

230

composite images. Since the area of the image strip is 12.2 times smaller than the

231

area of the whole well, to estimate the approximate total number of inclusions/well

232

the counted inclusions were multiplied by 12.2. For close-up analyses, microscopy

233

slides

234

(SouthernBiotech, Birmingham, AL, USA) and 40x immersion objective was used to

235

capture images.

were

mounted

with

Fluoromount-G

antifade

mounting

solution

236 237 238

Results

239 240

ChlamyCount software. McCoy epithelial cells grown on a 16-well chamber slide

241

were used for chlamydial infection. Depending on the chlamydial strain, we removed

242

the chamber 24 or 48 hours post infection (p.i.), fixed the host cells and stained the

243

chlamydial inclusions with the Cy5 analogue Alexa-647-labeled anti-chlamydial LPS

244

antibody. The stained inclusions were scanned with a commercially available Axon

245

GenePix 4100 DNA chip scanner. The scanner is capable of scanning Cy3 or Cy5 8

246

labeled spots on a regular microscope glass slide with a maximum resolution of 5

247

µm, which is comparable to the size of a chlamydial inclusion (Fig 1A-D). The

248

scanned image is processed by the ChlamyCount software. The thresholds for the

249

minimum intensity and size of the inclusion are adjustable by the user, otherwise

250

preset threshold values are applied (Fig. 2A). The two threshold values are the only

251

parameters that can be adjusted by the user; all the subsequent steps are automatic.

252

If the user adjusts the intensity and/or area thresholds, the effect of the adjustment

253

can immediately be seen by a magnified quarter of the uppermost and lowest left-

254

hand side wells (Fig. 2B). In the next step, ChlamyCount automatically crops the 16

255

areas containing the host cells from the complete image. For each area,

256

ChlamyCount processes the images as follows: i, the pixels with low intensity values

257

are likely noise, thus they are eliminated by thresholding the image with an intensity

258

and area threshold value ii, regions having an area greater than the median of the

259

area of all regions (the suspected size of a single inclusion) are split by finding the

260

local maxima in the regions and then assigning each point to the same closest

261

maximum to form smaller regions and iii, the identified particles are encountered and

262

their boundaries are determined. It is worth to note that the splitting of high intensity

263

areas is not complete, larger high intensity areas likely to contain multiple infected

264

cells without clear boundaries among them are regarded as one particle (inclusion).

265

On the other hand this effect can be observed both at higher and lower MOIs,

266

therefore the correlation of detected particles with the theoretical inclusion count

267

remains. After the image analysis, ChlamyCount provides a detailed .txt, .xls output

268

of the 16 areas with the inclusion counts, total areas above the threshold and if

269

confluent high intensity areas were detected and could not be dissect to individual

270

inclusions by the software the area/median area ratio is also provided. Median area

271

size is suspected to be the area of an individual inclusion when the MOI is not high

272

i.e. equal or below 1. The third output file is a .pdf file, with the above mentioned

273

numerical results and the processed images of the 16 areas (Fig. 2C). A typical

274

scanning time is about 10 minutes and the image analysis time is about 1-5 minutes.

275 276

Measuring the dynamic range of detection of C. trachomatis serovar D, C.

277

trachomatis serovar L2 and C. pneumoniae. The ChlamyCount system was tested

278

on McCoy cells infected with a 1:2 dilution series of C. trachomatis serovar D, C.

279

trachomatis serovar L2 and C. pneumoniae. The C. trachomatis serovar D infection 9

280

was performed using the DEAE-dextran method; the C. trachomatis serovar L2 were

281

performed without DEAE-dextran; and the C. pneumoniae infections were performed

282

by centrifugation (400 g, 60 minutes, RT). Since both C. trachomatis serovars have a

283

faster developmental cycle, the inclusion counting was performed 24 h p.i., while for

284

C. pneumoniae 48 h p.i. Initially the highest MOI was 8, but between 8 and 1 MOI the

285

infected areas were highly confluent and ChlamyCount could not dissect these areas

286

efficiently. For further experiments the starting MOI was either 1 (C. trachomatis

287

serovars D and L2) or 1:8 (C. pneumoniae) and 6 additional 1:2 dilutions were

288

performed in duplicates. The last two wells contained uninfected McCoy cells (Fig.

289

3A-C). With all three Chlamydia species we could measure a high correlation (R2

290

0.94-0.98) between the measured Chlamydia inclusion count (in the report: particle

291

count) and the theoretical inclusion count calculated from the 1:2 dilution curve. The

292

other two calculated values, namely the total area above the intensity threshold and

293

the area/median area ratios, also highly correlated to the calculated theoretical

294

values. When no centrifugation was used for infection (C. trachomatis serovar D and

295

L2), the inclusion counts were closely followed the theoretical inclusion counts

296

between MOI 1 and MOI 1:8-1:16 resulting in an approximately 1 log dynamic range

297

of the ChlamyCount system. The detected inclusion counts did not change

298

substantially after MOI 1:16, marking the lower threshold of detection. The

299

centrifugation was more efficient and permitted us to use lower MOIs for C.

300

pneumoniae infection (Fig. 3C), however we experienced leakage in about 25-30% of

301

the chambers, hence this infection method was not used for other experiments.

302 303

Measuring the MIC of moxifloxacin, tetracycline and the novel antichlamydial

304

compound PCC00213 on C. trachomatis serovar D growth. We tested whether

305

ChlamyCount was capable of determining the MIC of the known antichlamydial

306

antibiotics moxifloxacin and tetracycline. The C. trachomatis serovar D moxifloxacin

307

MIC was characterized before as 0.03-0.05 µg/ml (14-16). We performed C.

308

trachomatis serovar D infections (MOI 1) in the presence of moxifloxacin with a

309

concentration ranging from 0.25 µg/ml to 0.04 µg/ml. Our experiments showed (Fig.

310

4A), that C. trachomatis could grow until 0.015 µg/ml moxifloxacin concentration, but

311

was inhibited at a concentration of 0.031 µg/ml resulting in a MIC value of 0.031

312

µg/ml. Tetracyclines are first-choice antibiotics for chlamydial infections (5). The 10

313

tetracycline and doxycycline MICs for C. trachomatis serovar D was previously

314

characterized as 0.03-0.15 µg/ml (14, 17, 18). We performed C. trachomatis serovar

315

D infections (MOI 1) in the presence of tetracycline with a concentration ranging from

316

0.04 µg/ml to 0.0006 µg/ml. Our experiments revealed (Fig. 4B) that C. trachomatis

317

could grow until 0.01 µg/ml tetracycline concentration, but was inhibited at a

318

concentration of 0.02 µg/ml resulting in a MIC value of 0.02 µg/ml. We also used

319

ChlamyCount to determine the MIC of the novel antichlamydial compound

320

PCC00213. As Figure 4C shows, C. trachomatis could grow until 3.1 µg/ml

321

concentration of PCC00213 but was inhibited at a concentration of 6.2 µg/ml,

322

resulting in a MIC value of 6.2 µg/ml. We have to note that the parallel MTT-based

323

host cell viability assays showed that the antichlamydial effect of PCC00213 was

324

partially due to the inhibition of host cell metabolism (data not shown). Parallel to the

325

ChlamyCount based MIC determination we investigated the same slides with

326

fluorescent microscopy and determined the inclusion counts in each chambers. As

327

Figure 4A-C shows, the absolute inclusion counts were generally higher when we

328

applied ChlamyCount, but there was a high correlation between the two inclusion

329

counts (R2 0.94-0.98) (Fig. 4D). Importantly, the MIC values determined by the

330

ChlamyCount and manual methods were identical for all the three tested compounds.

331 332

Measuring the effect of IFN-γ on C. trachomatis serovar D and DEAE-dextran

333

and cycloheximide on C. trachomatis serovar D and on C. pneumoniae growth.

334

The inhibitory activity of IFN-γ on chlamydial growth in human host cells via the

335

degradation of host tryptophan pool is a well known phenomenon (19). Byrne et al.

336

found that IFN-γ had a concentration dependent inhibitory activity on C. psittaci

337

growth in the human uroepithelial cell line T24, resulting an approximately 10-fold

338

reduction of direct inclusion counts at 20 ng/ml IFN-γ concentration. We performed C.

339

trachomatis infection (MOI 1) of McCoy murine fibroblastoid cells in the presence of

340

murine and human IFN-γ. Despite the fact that the host species, cell line and

341

chlamydial species were different, our experiments showed comparable extent of

342

inhibition albeit at lower murine IFN-γ concentration: inhibition of chlamydial

343

propagation was concentration dependent and the maximum inhibition was

344

approximately 3.8 fold at a concentration of 1.5 IU/ml (approximately 0.07 ng/ml) or

345

higher murine IFN-γ concentration (Fig. 5A-B). The control human IFN-γ did not show 11

346

any inhibitory effect even at a concentration of 100 IU/ml (Fig. 5A). It was an early

347

observation that the pretreatment of host cells with DEAE-dextran or treatment with

348

cycloheximide could increase the number of chlamydial inclusions and the

349

recoverable IFU (9, 20-22). We applied ChlamyCount to detect these effects during

350

C. trachomatis serovar D and C. pneumoniae infection. We pretreated HeLa cells

351

with DEAE-dextran (1% DEAE-dextran, 15 minutes, RT) and/or applied 1 µg/ml

352

cycloheximide during the infection and compared the direct inclusion counts to the

353

untreated cells. Our results showed partially different effects of these drugs on the

354

growth of the two Chlamydia species (Fig. 5C-D). For C. trachomatis serovar D the

355

application of DEAE-dextran showed only marginal effect, but the cycloheximide

356

treatment largely independently of the presence of DEAE-dextran increased the

357

direct inclusion count 1.9-2.2 fold. For C. pneumoniae the application of dextran or

358

cycloheximide alone increased the direct inclusion count 2.4-3.3 fold respectively, but

359

the co-addition of the two drugs did not show a further growth promoting effect.

360 361 362

Discussion

363

We

364

designed

a low-cost,

medium-throughput

method

for the

rapid

365

enumeration of chlamydial inclusions. Chlamydial inclusions on a 16-well chamber

366

slide were labeled by a fluorescently labeled genus-specific antibody and scanned by

367

a commercial DNA chip scanner. In this detection system, the DNA chip scanner is

368

the most expensive component, however these scanners are easily available in core

369

facilities, and in many cases the new generation sequencing technology makes these

370

scanners infrequently used or redundant. Our technology reuses these scanners in a

371

novel role, when the high resolution images produced by these scanners are used to

372

visualize chlamydial inclusions. The images are processed either completely

373

automatically or after a short intensity and area threshold adjustments on a single

374

desktop computer with an average or low-average year 2013 hardware configuration

375

(Intel Core2 CPU [email protected] GHz, 2 GB RAM, ATI Radeon HD 3600 Series video

376

card).

377

The golden standard test of inclusion counting is the infection of host cells with

378

serial dilutions of Chlamydia and the subsequent counting of inclusions. Our method

379

was capable of counting the 1:2 dilutions of inclusions of three different chlamydial 12

380

species, with high correlation with the theoretical estimates. The system was capable

381

of measuring the inclusion counts over a 1 log range which was comparable or better

382

than the previously described other methods (12, 23-25). As with other methods, a

383

limitation of the ChlamyCount method at higher MOIs is the accurate dissection of the

384

high number of confluent or nearly confluent fluorescent areas originated from close

385

inclusions. Also, ChlamyCount detects a higher number of inclusions than the manual

386

counting by microscopy likely because the software is detecting smaller fluorescent

387

areas as inclusions. Therefore the current version of ChlamyCount may not be used

388

for absolute quantitation of inclusions. ChlamyCount was designed to measure the

389

effect of various treatments on chlamydial growth and for this task it is enough to

390

follow the changes in inclusion counts with high accuracy and is not necessary to

391

determine their absolute number.

392

Indeed, we could demonstrate that inclusion counts detected by ChlamyCount

393

and manual microscopy closely correlated and therefore could be applied for tasks

394

where the detection of changes in bacterial (inclusion) counts are important such as

395

MIC determination. We used ChlamyCount to determine the MIC of two well-

396

characterized but different action antichlamydial antibiotics, the ribosome inhibitor

397

tetracycline and the gyrase inhibitor moxifloxacin. In both cases ChlamyCount was

398

able to determine MIC values that were identical to the MIC values determined by

399

manual microscopy and also close to the previously described values. ChlamyCount

400

was also able to reproducibly determine the MIC value of the novel antichlamydial

401

compound PCC00213. Besides antibiotics, various chemicals can effect chlamydial

402

growth in a positive or negative manner. ChlamyCount was also able to determine

403

the previously described inhibitory effect of IFN-γ, and growth promoting effect of

404

DEAE-dextran and cycloheximide. Importantly, these data shows that ChlamyCount

405

can be used to quantitatively measure the fold changes in inclusion count between a

406

treated and control samples. This type of relative quantitation makes our method

407

applicable in chlamydia basic biology experiments, where the effect of a given

408

treatment should be quantitatively measured.

409

Considering the previously described methods, the rapid estimation of

410

chlamydial growth can be achieved via two approaches. The first approach uses

411

either a fluorimeter or spectrophotometer to measure the total intensity of Chlamydia

412

specific fluorescently labeled-antibody (26) or indirectly measure the Chlamydia

413

growth by measuring decreased host cell metabolism after chlamydia induced lysis 13

414

(25). These methods are rapid, inexpensive, but do not rely on counting the individual

415

inclusions, hence the aspecific antibody binding or aspecific change in host cell

416

metabolism cannot be excluded. The second approach mostly (12, 24) but not

417

exclusively (23) uses automatic microscopes to take a certain number of images/well,

418

followed by computer image analysis for the specific detection and enumeration of

419

inclusions. ChlamyCount relates to these methods. Compared to the recently

420

described automatic microscope-based inclusion counting method (12) our method

421

has certain advantages and disadvantages. The automatic microscope-based

422

method uses 96-well plates and obviously produces images with a higher resolution.

423

Since analyzing the images requires a significant computational power, the image

424

analysis is performed by a computer cluster with 16 processors. In contrast our

425

method has a lower throughput, but the analysis time is significantly shorter,

426

therefore the processing time of 96 samples (6x16-well chambers) is comparable for

427

at least the first 96 samples. ChlamyCount system set-up cost is generally lower, the

428

required computational support is significantly simpler. Albeit at lower resolution,

429

ChlamyCount also preserves a major advantage of the automatic microscope-based

430

methods; namely it provides topological information about the inclusions. Since DNA

431

chip scanners can scan at two different wavelengths, our method can potentially be

432

applied to provide colocalization information, e.g. allowing testing the effect of anti- or

433

pro-chlamydial proteins recombinantly expressed in the host cells.

434

In conclusion, we developed an easily useable, accurate system for measuring

435

the antichlamydial effect of known and novel antibiotics and for measuring the effect

436

of various compounds on Chlamydial growth. We think that ChlamyCount has the

437

potential to be further optimized, an extended dynamic range and absolute inclusion

438

number estimation could be achieved by applying new raw image processing

439

methods, and improved confluent area dissection algorithm, the goals we are

440

currently pursuing.

441

14

442

Acknowledgments

443

This work was supported by the ERA-NET ChlamyTrans grant (D.P. Virok), OTKA

444

National Research Fund grant PD 100442 (K. Burián), TÁMOP-4.2.2.A-11/1/KONV-

445

2012-0073 (P. Balázs) and TÁMOP-4.2.2.A-11-1-KONV-2012-0035.

446 447

Figure Legends

448

FIG. 1

449

Comparison of the images produced by a DNA chip scanner and confocal microscopy (A) C.

450

trachomatis serovar D infected McCoy cells grow in a 16-well plastic chamber attached to a

451

glass slide. After fixation chlamydial inclusions are fluorescently labeled and scanned by a

452

DNA chip scanner at 5 µM resolution. Scanned image of a well of the 16-well chamber slide.

453

(B) Magnified portion of the scanned image. (C) The same area visualized by fluorescent

454

confocal laser scanning microscopy. Bar=100µm. (D) Further magnification of the lower right

455

fluorescent structure reveals a single infected cell. Bar=10µm.

456 457

FIG. 2

458

ChlamyCount image adjustments and report. (A) Infected host cells are grown in a 16-well

459

chamber slide. Chlamydial inclusions are stained by direct immunofluorescence and scanned

460

by a DNA chip scanner. Before image analysis, the user can adjust the inclusion intensity

461

and area thresholds for detection. (B) The effect of the applied threshold changes on the

462

number and location of the detected inclusions can be readily checked by a magnified

463

quadrant of the left uppermost and lowest wells of the chamber. Based on the applied

464

thresholds ChlamyCount performs the image analysis. (C) ChlamyCount reports the

465

numerical data as a .txt, .xls and .pdf files. The .pdf file contains the numerical data as well

466

as the images of the 16 scanned areas.

467 468

FIG. 3

469

Detection of chlamydial inclusions. McCoy cells were infected with serially diluted (A) C.

470

trachomatis serovar D, (B) C. trachomatis serovar L2 and (C) C. pneumoniae. C.

471

pneumoniae infections were performed by centrifugation (400 g, 60 min, RT). Each infection

472

with a particular MOI was performed in parallel wells. MOIs are shown as simple fractions

473

instead of decimal numbers in order to follow the serial dilutions easier. The last two wells

474

were uninfected. The images of scanned and ChlamyCount processed wells and the

475

numerical data are shown for each species and serovar. For an easier comparison of

476

theoretical and measured inclusion counts, the first theoretical inclusion count was made the

15

477

same as the first measured inclusion count. Data are means +/- standard deviations of the

478

parallel wells.

479 480

FIG. 4

481

MIC estimation of known and novel antimicrobial compounds. McCoy cells were infected with

482

C. trachomatis serovar D (MOI 1) in the presence of various concentrations of (A)

483

moxifloxacin, (B) tetracycline and (C) PCC00213. Each infection with a particular antibiotics

484

concentration was performed using parallel wells. The inclusion counts were enumerated by

485

ChlamyCount and manual confocal microscopy on the same slide. The scanned and

486

ChlamyCount processed well images and the numerical data are shown. Data are means +/-

487

standard deviations for the parallel wells. (D) Correlation between the inclusion numbers

488

enumerated by ChlamyCount method and manual counting. Each data point represents the

489

inclusion number detected in a single well of the 16-well chamber slide.

490 491

FIG. 5

492

Measuring the effect of IFN- , DEAE-dextran and cycloheximide on the direct inclusion

493

counts of C. trachomatis serovar D and C. pneumoniae. McCoy cells were infected with C.

494

trachomatis serovar D (MOI 1) in the presence of various concentrations of (A) human and

495

(A, B) murine IFN- . HeLa cells were infected with (C) C. trachomatis serovar D (MOI 0.5)

496

and (D) C. pneumoniae (MOI 1) after pretreatment with 1% DEAE-dextran (15 minutes, RT)

497

and/or applied 1 µg/ml cycloheximide during the infection. Each infection with a particular

498

compound concentration was performed in two parallel wells. The scanned and

499

ChlamyCount processed well images and the numerical data are shown. Data are means +/-

500

standard deviations for the parallel wells. Student’s t-test was applied for statistical

501

comparison of the treated samples vs. the non treated. * P