In-cell western assay as a high-throughput approach for Chlamydia trachomatis quantification and susceptibility testing to antimicrobials

Simone Filardo; Marisa Di Pietro; Patrizio Pasqualetti; Martina Manera; Fabiana Diaco; Rosa Sessa

doi:10.1371/journal.pone.0251075

Abstract

Chlamydia trachomatis, the leading cause of bacterial sexually transmitted diseases in developed countries, with around 127 million new cases per year, is mainly responsible for urethritis and cervicitis in women, and urethritis and epididymitis in men. Most C. trachomatis infections remain asymptomatic (>50%) and, hence, untreated, leading to severe reproductive complications in both women and men, like infertility. Therefore, the detection of C. trachomatis as well as the antimicrobial susceptibility testing becomes a priority, and, along the years, several methods have been recommended, like cell culture and direct immunofluorescence (DFA) on cell cultures. Herein, we described the application of In-Cell Western assay (ICW) via Odyssey CLx as a fast, more accessible, and high-throughput platform for the quantification of C. trachomatis and the screening of anti-chlamydial drugs. As a first step, we set up a standard curve by infecting cell monolayers with 2-fold serial dilutions of C. trachomatis Elementary Body (EB) suspension. Then, different unknown C. trachomatis EB suspensions were quantified and the chlamydial susceptibility testing to erythromycin was performed, using the DFA as comparison. Our results showed a very high concordance between these two assays, as evidenced by the enumeration of chlamydial IFUs as well as the determination of erythromycin Minimum Inhibitory Concentration (MIC). In conclusion, the ICW assay may be a promising candidate as an accurate and accessible methodology for C. trachomatis antimicrobial susceptibility testing.

Citation: Filardo S, Di Pietro M, Pasqualetti P, Manera M, Diaco F, Sessa R (2021) In-cell western assay as a high-throughput approach for Chlamydia trachomatis quantification and susceptibility testing to antimicrobials. PLoS ONE 16(5): e0251075. https://doi.org/10.1371/journal.pone.0251075

Editor: Bipul R. Acharya, University of Virginia School of Medicine, UNITED STATES

Received: December 22, 2020; Accepted: April 19, 2021; Published: May 11, 2021

Copyright: © 2021 Filardo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: This study was supported by a grant from Regione Lazio "Progetto Lazio Innova - DSPMI-INN" to Prof. Rosa Sessa. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Chlamydia trachomatis is the leading infectious cause of blindness among world’s poorest people, and, in developed countries, it is one of the major bacterial sexually transmitted pathogens with approximately 127 million new infections per year [1, 2]. In women, C. trachomatis manifests as cervicitis and salpingitis while, in men, it is mainly responsible for urethritis [3–5]. Furthermore, it can be transmitted to infants following the direct contact with infective cervical secretions during delivery, resulting in neonatal conjunctivitis and pneumonitis [5].

A major concern with C. trachomatis is that most urogenital infections are asymptomatic (>50%) and, hence, undetected, and untreated, leading to long-term complications including pelvic inflammatory disease, ectopic pregnancy, and infertility in women as well as epididymitis and proctitis in men [5, 6].

C. trachomatis, an obligate intracellular bacterium, has an intriguing and unique biphasic developmental cycle alternating between the extracellular, infectious elementary body (EB) and the intracellular, noninfectious, reticulate body (RB) [3, 7, 8]. The developmental cycle begins when EBs attach and enter the host cell by endocytosis. Once inside the host cell, EBs are internalized and confined to a vacuole termed inclusion, through a process requiring the secretion of several proteins including Type-III secretion system effector proteins [7, 9]. Within the inclusion, EBs then differentiate to RBs, which replicate by binary fission within 24 hours post-infection and, as the inclusion expands, RBs begin to transition back to EBs in an asynchronous process [7, 9]. At the end of the developmental cycle, the inclusion occupies most of the host cell’s cytoplasm and, after approximately 48 hours, the EBs are finally released from the host cell mainly by lysis [7, 10].

Given the impact of asymptomatic chlamydial infections on the development of long-term complications as well as the absence of effective vaccines, the detection of C. trachomatis as well as antimicrobial susceptibility testing becomes a priority, since, in the last decade, several clinical treatment failures to first-line antibiotics have been reported [11, 12].

During the years, several methods have been used for assaying C. trachomatis genital infections, such as cell culture and direct immunofluorescence assay (DFA), as well as real-time quantitative polymerase chain reaction (PCR) [13–15]. The latter is currently recommended for its high sensitivity (>90%), specificity (≥99%) and short turnaround times [13]. However, one of the main disadvantages of nucleic acid amplification tests is that the target DNA is amplified without discriminating between DNA originating from viable or non-viable C. trachomatis [13, 14]. Importantly, PCR assay is not utilized, to date, for antimicrobial susceptibility testing [16], although its potential application in this field appears promising [17, 18].

Cell culture has been considered, for a long time, the “gold standard” for its high specificity (100%) as well as the ability of isolating Chlamydial clinical strains, essential for the detection of C. trachomatis antimicrobial resistance [19]. However, the peculiar intracellular growth of C. trachomatis, characterized by a long incubation time, and the visualization of chlamydial inclusions across cell monolayers via fluorescence microscopy, have limited its routine use in clinical laboratories [20]. Indeed, the enumeration of chlamydial inclusions is time-consuming, especially when the analysis of multiple samples is performed, as in antimicrobial susceptibility testing. Further issue of microscopic counting is the extensive operator’s technical skill required, especially when cell monolayers are infected with high load of C. trachomatis and, hence, a defined and randomized number of microscopic fields must be selected [21]. Therefore, the microscopic counting of chlamydial inclusions is surely influenced by investigator’s bias, further compromising the reliability of findings.

To overcome such issues, a novel and fast approach, that utilizes near-infrared laser-based scanning, namely the In-Cell Western assay (ICW), has been proposed for viruses and intracellular bacteria, including C. trachomatis [22]. The ICW assay is a cell-based technique for intracellular protein detection and has been largely exploited for the quantitative analysis of cellular signaling pathways due to its high accuracy and reproducibility [23].

Herein, we described the application of ICW assay as a high-throughput platform for the quantification of C. trachomatis, fundamental for screening anti-chlamydial drugs. On this regard, the feasibility of ICW assay for the evaluation of chlamydial susceptibility to erythromycin has been investigated.

Materials & methods

Cell line and culture conditions

McCoy cell line (ATCC^® CRL-1696^™, US) was cultured in Dulbecco’s Modified Eagle Medium (DMEM, Corning^™, US) supplemented with 10% (v/v) foetal calf serum (FCS) (complete medium), at 37°C in humidified atmosphere with 5% CO₂.

C. trachomatis propagation and titration

C. trachomatis serovar D UW3 (ATCC^© VR-885^™, US) was propagated in McCoy cells as previously described [24]. Briefly, confluent cell monolayers grown in 25 cm² flasks (6x10⁶ cells/well), were infected with chlamydial EBs by centrifugation at 754 x g for 30 min and harvested by scraping after 36 hours of incubation. The suspension containing Chlamydial EBs was, then, added to equal volumes of 4X Sucrose Phosphate (4SP) buffer and stored at −80°C.

For C. trachomatis titration, confluent cell monolayers, grown on coverslips in 24-well plates (1x10⁵ cells/well), were infected with 10-fold serial dilutions of C. trachomatis EB suspension by centrifugation at 754xg for 30 min, then washed 3x with PBS and added with complete medium. After 36-hours of incubation at 37°C and 5% CO₂, infected cell monolayers were washed 3x with PBS and, then, fixed in 96% ice cold methanol for 10 min at -20°C. Chlamydial inclusions were stained by using DFA via a fluorescein isothiocyanate (FITC)-conjugated anti-Chlamydia lipopolysaccharide (LPS) antibody kit (Oxoid, US), following the manufacturer’s instructions. Inclusions were visualized and counted by using a Leica DM5000B fluorescence microscope (Leica, US) at 400× magnification.

C. trachomatis quantification via In-cell Western assay

In order to quantify C. trachomatis by ICW assay we used species-specific chlamydial major outer membrane protein (MOMP) infrared-immunodetection to visualise chlamydial inclusions in cell monolayers. First, we set-up a standard curve by infecting, above described, confluent cell monolayers, grown on two different 96-well cell-culture microplates (1x10⁴ cells/well) (standard polystyrene tissue culture treated gamma-sterilised microplates, Orange Scientific, US and optically clear flat well bottom polystyrene tissue culture treated microplates, Corning^®, US), with two-fold serial dilutions of C. trachomatis EB (stock concentration of 4.37x10⁷ EB/mL), from MOI from 1 to 1/2⁹. Then, three unknown chlamydial cell suspensions were diluted 4 times at a ratio of 1:10, 1:100, 1:500 and 1:1000, and used to infect cell monolayers as above described. After 36 hours post infection, infected cell monolayers were washed 3x with PBS and then, fixed in 4% paraformaldehyde (PFA) for 10 min at room temperature and investigated by ICW assay.

At the same time, confluent cell monolayers, grown on coverslips in 24-well cell culture microplates (1x10⁵ cells/well) were infected under the same experimental conditions above described. After 36 hours post infection, infected cell monolayers were washed 3x with PBS and then, fixed with ice cold 96% methanol and analysed by DFA assay.

Anti-chlamydial drug screening via In-cell Western assay

Confluent cell monolayers grown on either standard microplates or optically clear bottom microplates (1x10⁴ cells/well), were infected with C. trachomatis at a MOI of 1.0, as above described. Then, infected cells were treated with two-fold serial dilutions of erythromycin (Sigma-Aldrich, US) (from 1 to 1/2⁹) and incubated at 37°C in humidified atmosphere with 5% CO₂. After 36 hours post infection, treated and untreated cell monolayers were washed 3x with PBS and, then, fixed in 4% PFA and analysed by ICW assay.

At the same time, confluent cell monolayers grown on coverslips in 24-well cell culture microplates (1x10⁵ cells/well), were infected and treated with erythromycin as above described. After 36 hours post infection, treated and untreated cell monolayers were washed 3x with PBS and, then, fixed with ice cold 96% methanol and analysed by DFA assay.

The Minimum Inhibitory Concentration (MIC) was determined by DFA assay and it was defined as the concentration of antibiotic that was one twofold dilution higher than the transition point (MIC_TP) as described by Suchland et al., 2003 [19].

Odyssey CLx in-cell western assay

Cell monolayers were stained with a primary mouse monoclonal antibody against species-specific MOMP (Mab6ciii, The Chlamydia Biobank, UK, Cat. No. #CT602) (1:1000 dilution) combined with a secondary goat anti-mouse infrared (IR) Dye 680RD antibody (Licor Biosciences, US) (1:2000 dilution), as previously described [22]. Briefly, following permeabilization with 0.1% triton X-100 in PBS for 8 min at Room Temperature (RT), cell monolayers were incubated with Odyssey Blocking Buffer for 30 min at RT. Then, cell monolayers were incubated with the primary antibody, diluted in Odyssey Blocking Buffer, for 1 hour at RT and washed 3x with PBS containing 0.1% Tween-20. The IR conjugated secondary antibody was then added and cell monolayers were incubated for 1 hour at RT, followed by three final washes with PBS containing 0.1% Tween-20. Multiwell microplates were then analysed on a laser scanner Odyssey CLx near-infrared imaging system (Licor Biosciences, US) at IR 700nm. The Odyssey system was set at 21μm resolution, high scan quality and auto-intensity mode, and images as well as Absolute Units (A.U.) values from each well were acquired using the Licor Image Studio Software (version 3.1). Recorded A.U. values were then exported into Excel (Microsoft, US, version 2010) and uninfected cell monolayers were used for subtracting unspecific and/or background fluorescent signals.

Direct immunofluorescence assay

Cell monolayers were stained with FITC-conjugated anti-Chlamydia LPS antibody (Oxoid, US), following the manufacturer’s instructions. Briefly, infected McCoy cell monolayers, grown on coverslip in 24-well cell culture plates and fixed with ice cold 96% methanol, were layered with 35μL of FITC-conjugated mouse monoclonal antibody anti-Chlamydia LPS. After 30 min incubation at 37°C, coverslips were washed 3x with PBS, dried at RT and applied on microscope slides (Thermofisher, US). The number of C. trachomatis IFU/well was determined by counting all microscopic fields using a fluorescence Leica DM5000B microscope (Leica) at 400× magnification [25].

Statistical analysis

All data are reported as mean ± standard deviation (SD) of at least four replicates from three independent experiments. For each analysis, data distribution was previously assessed and, since usually the clear departures form gaussianity (also test by means of Shapiro-Wilks procedure) were due to right skewness, log-transformation was applied. The correlation and the relationship between absorbance values and fixed concentration (standards) of C. trachomatis were estimated according to a linear regression model, after verifying that nonsignificant improvement was provided by higher-order models.

To assess differences between means, a General Linear Model was applied, specifying each time the dependent variable as well as the sources of variation (between-measures factors). When appropriate, the interaction between factors was reported and interpreted. Whenever a significant factor was found, Bonferroni procedure was applied to pairwise comparisons to control alpha-inflation.

The threshold of statistically significance was set at 0.05.

Results

Set-up and optimization of the ICW assay

Preliminary experiments were performed to determine the appropriate primary antibody as well as the optimal concentrations for the primary and the secondary antibodies, yielding the best signal to noise ratio. McCoy cell monolayers were infected with C. trachomatis at an MOI of 1 and incubated for 36 hours. Hence, infected cell monolayers were fixed, permeabilized and stained with three different 2-fold serial dilutions (1:500, 1:1000, 1:2000) of the primary antibody anti-C. trachomatis LPS or anti-C. trachomatis MOMP, routinely used in the IFU counting, as well as of the secondary antibody anti-mouse (IRDye 680RD). Background signals were obtained from uninfected cells, treated as previously described. Results showed that the combination of the primary antibody against C. trachomatis MOMP at 1: 1000 dilution factor, with the secondary antibody at 1:2000 dilution factor, provided the highest signal to noise ratio (3.54 as compared to a ratio of <3 in all the other combinations, Table 1) and, therefore, was chosen for further experiments.

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Table 1. Optimization of the concentrations for the primary and secondary antibodies.

https://doi.org/10.1371/journal.pone.0251075.t001

Other experiments were performed to determine the time point after infection. McCoy cell monolayers were infected with C. trachomatis at an MOI of 1 and incubated for 2, 24, 36 or 48 hours. Hence, infected cell monolayers were fixed and processed for ICW assay. Results showed the highest absorbance values at 36 hours (3.76x10⁶ ± 2.24x10⁵ A.U.) as compared to values found at 2 hours (2.1x10⁴ ± 4.03x10³), 24 hours (3.06x10⁶ ± 9.8x10⁴ A.U.) and 48 hours (3.08x10⁶ ± 7.95x10⁴ A.U.), representing immature inclusions at 24 hours post infection and cell lysis at 48 hours post infection. At 2 hours post infection, the absorbance values (2.1x10⁴ ± 4.03x10³) were similar to those of uninfected cells (2.2x10⁴ ± 9.7x10²).

Lastly, further experiments were carried out to determine the appropriate MOI to be used in anti-chlamydial drug screening. In particular, McCoy cell monolayers were infected with C. trachomatis at MOIs of 0.5, 1.0, 2.0, 5.0 and 10.0 and incubated for 36 hours. Hence, infected cell monolayers were fixed and processed for ICW assay. As reported in Table 2, the results showed that signals were maximum when high MOIs were used. Indeed, absorbance values observed at MOI of 2.0, 5.0 and 10.0 were 1.54x10⁸ ± 3.14x10⁶ A.U., 1.60x10⁸ ± 6.03x10⁶ A.U., 1.53x10⁸ ± 2.74x10⁶ A.U., respectively, showing the inability of the ICW assay to discriminate these different MOI. Therefore, to evaluate the applicability of ICW for C. trachomatis antimicrobial susceptibility testing, we used the MOI of 1.0 since it possessed the higher signal to noise ratio as compared to MOI of 0.5 (1.47 and 1.04, respectively).

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Table 2. Determination of the appropriate C. trachomatis MOI to be used in anti-chlamydial drug screening.

https://doi.org/10.1371/journal.pone.0251075.t002

Lastly, in order to investigate the stability of the IRdye 680RD, we scanned the same microplates after 1 month of -20°C storage, showing no statistically significant variation of absorbance values in either optically clear bottom or standard microplates (p = 0.11 and p = 0.9, respectively, S1 Fig).

Quantification of C. trachomatis IFUs via ICW

In order to evaluate the performance of ICW assay in the quantification of C. trachomatis via Odyssey CLx, we used as comparison the DFA assay on cell cultures, the traditional method employed for determining chlamydial titer. Specifically, we first set-up a standard curve of C. trachomatis IFU via ICW in relation to the enumeration of chlamydial inclusions determined via DFA (Fig 1). To this aim, cell monolayers were infected with known quantities of chlamydial EBs, from 2x10⁵ to 39 EBs/well (MOI from 1 to 1/2⁹, respectively), fixed, stained and scanned at 36h via Odyssey CLx (Fig 1A). Similar experiments were also performed on cell monolayers grown on 24-well plates and analysed via DFA. Subsequently, C. trachomatis titer (IFU/mL) was determined in different unknown chlamydial EB suspensions by using both methodologies. Lastly, the performance of ICW assay in the quantification of C. trachomatis was evaluated in two different microplates, standard and with optically clear well bottom.

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Fig 1. Standard curves of C. trachomatis IFUs via ICW assay in optically clear bottom and standard microplates, related to the enumeration of chlamydial IFUs by DFA assay.

ICW assay: confluent McCoy cell monolayers, grown on either 96-well standard polystyrene or optically clear bottom cell culture microplates, were infected with two-fold serial dilutions of C. trachomatis EB suspension, from MOI of 1.0 to 1/2⁹ IFUs/cell. After 36 hours post infection, infected cell monolayers were fixed in 4% PFA, permeabilized by 0.1% triton x-100 in PBS, stained and scanned via Odyssey CLx as described in Materials and Methods. DFA: confluent McCoy cell monolayers, grown on coverslips in 24-well cell culture microplates, were infected as above described. After 36 hours post infection, infected cell monolayers were fixed in 96% ice cold methanol, stained and visualized via fluorescence microscopy (400X magnification) as described in Materials and Methods. (A) Representative infrared scan images of Chlamydia-infected cells on standard polystyrene cell-culture or optically clear bottom microplates from at least three independent experiments; (B) Signal to noise ratio of Chlamydia-infected cells in either standard polystyrene cell-culture or optically clear bottom microplates; Standard curves of C. trachomatis IFUs via ICW in optically clear bottom and standard microplates, calculated from near-infrared absorbance data with background (C) or no-background (D) subtraction, related to the enumeration of chlamydial IFU via DFA; Linear regression models of standard curves by the ICW assay after log-transformation on (E) standard polystyrene cell-culture microplates or (F) optically clear bottom microplates. **, p < 0.001; *, p < 0.05.

https://doi.org/10.1371/journal.pone.0251075.g001

According to general linear model with signal to noise ratio (log-transformed) as dependent variable, microplate type (optically clear vs. standard microplate) and dilution (from 1 to 1/2⁹) as between-units factors, both main effects [microplate type: F(1,58) = 253.88, p<0.001 and dilution: F(9,58) = 78.29, p<0.001] as well as microplate type*dilution interaction [F(9,58) = 5.37, p<0.001] resulted significant. These findings are represented in Fig 1B, where the signal to noise ratio of ICW assay in both microplates decreased with decreasing MOI, and it was generally higher in the optically clear bottom microplates as compared to the standard microplates. Specifically, signal-to-noise ratio was higher at each dilution level (Bonferroni adjusted p-values <0.05, consistently) even if differences between microplate type varied across dilution levels, as indicated by the significant interaction.

However, an increased sensitivity of ICW assay was not observed when optically clear bottom microplates were used. In fact, as shown in Fig 1C and 1D, the limits of detection, expressed as MOI, were 1/2⁵ and 1/2⁴, in the standard and optically clear bottom microplates, respectively; the ICW assay was also able to discriminate differences in MOI up to 1.0 in both microplates. After the appropriate log-transformation to make additive originally multiplicative variables, linear correlation between instrument readings and fixed standards was higher for standard microplates (r = 0.91, Fig 1E) than for optically clear bottom microplates (r = 0.76, Fig 1F). By contrast, DFA assay showed a sensitivity up to MOI 1/2⁹, as evidenced in Fig 1C and 1D.

When the number of chlamydial EB was estimated in the samples with unknown C. trachomatis concentrations, according to the relationship derived from the above regression models (ANOVA with log(ICW) as dependent variable and method (ICW in standard or optically clear microplates, and DFA) and samples (1, 2, 3) as between-measures factors), method resulted significant [F(2, 88) = 6.26; p = 0.003], without any evidence of dependence on samples [F(4, 88) = 0.31; p = 0.972]. As shown in Table 3 and in Fig 2, ICW measures (IFU/mL) were lower in standard microplates than in optically clear microplates (Bonferroni adjusted p = 0.008). ICW measures in standard microplates were also lower than DFA values (IFU/mL) (p = 0.031). On the other hand, no significant difference was observed between the ICW measures in optically clear microplates and DFA values (p = 1.000).

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Fig 2. Quantification of C. trachomatis IFUs (IFU/mL) in samples with unknown chlamydial concentration via In-cell western and DFA assays.

Bars represent mean values of log-transformed measures and error bars correspond to 95% confidence intervals (CI). The left panel shows the marginal means across the three samples and Bonferroni adjusted p-values for each of the three pairwise comparisons. The right panel shows the means (and 95% CI) for each sample (post-hoc comparisons are not reported since no evidence of Method*Sample interaction was found (p>0.80)).

https://doi.org/10.1371/journal.pone.0251075.g002

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Table 3. Quantification of C. trachomatis IFUs (IFU/mL) in samples with unknown chlamydial concentration via In-cell western and DFA assays.

https://doi.org/10.1371/journal.pone.0251075.t003

C. trachomatis susceptibility to erythromycin via ICW assay

In order to evaluate the performance of ICW assay as a novel approach for screening anti-chlamydial drugs, erythromycin, one of the antibiotics recommended for treating C. trachomatis infections [26], was chosen and DFA assay was used as comparison. Specifically, the susceptibility of C. trachomatis to erythromycin was investigated via ICW and DFA assays by challenging Chlamydia-infected cell monolayers on either standard or optically clear bottom microplates with twofold serial dilutions of erythromycin (from 1 μg/mL to 1/2⁹ μg/mL).

As evidenced in Fig 3, the ICW as well as the DFA assays were able to determine the MIC; via DFA assay, the MIC_TP was 1/2⁵ and, hence, the MIC value was 1/2⁴ μg/mL. The ICW assay detected the same MIC value as the DFA assay, at 1/2⁴ μg/mL. Furthermore, no differences in the MIC value were observed when the ICW assay was used on either standard or optically clear-bottom microplates.

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Fig 3. Susceptibility of C. trachomatis to erythromycin by ICW and DFA assays.

Confluent McCoy cell monolayers, grown in either 96-well cell culture microplates or on coverslips in 24 well cell culture microplates, were infected with C. trachomatis EBs at a MOI of 1.0. Subsequently, cell monolayers were challenged with two-fold serial dilutions of erythromycin (from 1.0 μg/mL to 0.0019 μg/mL) and, then, incubated for 36 hours at 37°C and 5% CO₂. 96-well microplates were then fixed in 4% PFA, permeabilized by 0.1% triton x-100 in PBS and analysed via Odyssey CLx, whereas 24-well microplates were fixed with 96% ice cold methanol and analysed via fluorescence microscopy. (A) Near-infrared absorbance data via ICW and chlamydial IFU via DFA in relation to erythromycin concentrations; (B) Immunohistological staining of infected cell monolayers treated with the erythromycin concentrations corresponding at MIC (0.063 μg/mL) and MIC_TP (0.0019 μg/mL) and untreated cells.

https://doi.org/10.1371/journal.pone.0251075.g003

Discussion

The findings of our study show that the ICW assay can represent a simple, affordable, and fast alternative to DFA assay on cell-cultures for either the quantification of chlamydial inclusions or the susceptibility testing to anti-chlamydial agents. In particular, the ICW assay possesses high accuracy, as evidenced by the low dispersion of the standard curve for chlamydial quantification observed in our study. Furthermore, a very high concordance between ICW and DFA assay was observed in the enumeration of chlamydial IFUs as well as the determination of erythromycin MIC. Also, ICW assay significantly reduce the analysis duration (approximately 3 hours) as compared to the DFA assay, that requires from one to several days in relation to the number of samples analysed. Lastly, the performance of the ICW assay is not significantly influenced by the type of microplate used. This is an important aspect for reducing the overall cost of the analysis, since the optically clear bottom microplates are particularly expensive.

Historically, the well-established approaches, such as DFA on cell-cultures, have been adopted for the quantification of C. trachomatis EBs and the testing of chlamydial susceptibility to antibiotics [16, 19, 20]. However, DFA assay rely on investigator’s experience in identifying chlamydial EBs, and the number of samples assayed per day is limited, making it not very time-efficient [20]. As a consequence, the DFA on cell cultures is not routinely employed in all laboratories and require dedicated facilities and trained professionals.

Recently, other alternative approaches have been suggested for improving or automating C. trachomatis quantification or susceptibility testing. In particular, genetically modified C. trachomatis strains expressing Green Fluorescent Protein (GFP), in-silico analysis of ImmunoSpot data or modified plaque-forming assays [27–31] have been proposed. However, these approaches have not gained a lot of traction in the scientific community since, for example, the engineering of GFP-producing C. trachomatis is challenging and time-consuming [27–31], the ImmunoSpot imaging system shows a low resolving power, underestimating chlamydial quantification [30], and the plaque assay lack accuracy and reproducibility [31].

Differently, the ICW assay possesses numerous advantages. First, ICW assay removes the investigator’s bias associated with the subjective microscopic examination of DFA assay, increasing, thus, the accuracy of results. Second, the ICW assay shows the potential to greatly increase the throughput of the analysis for its ability to scan up to 384-well microplates, allowing the simultaneous testing of several anti-chlamydial agents. Lastly, the ICW possesses further advantages as compared to the other methodologies based on the same test principle, like the horseradish peroxidase (HRP) based ELISA assay. The ICW assay, indeed, improve the reliability of C. trachomatis inclusion enumeration via the quantification of cell monolayer integrity, since it is able to acquire two different signals simultaneously by using fluorescent molecules emitting at different wavelength, differently from the HRP-ELISA. Also, the ICW assay can be stored at -20°C up to a month, making it possible to revisit the results of the assay at a later time, whereas HRP-ELISA must be read in the first 15 minutes after the addition of the stop solution. Nevertheless, HRP-ELISA is a well-known methodology in clinical laboratories and has been used for antimicrobial susceptibility testing towards non-bacterial pathogens [32, 33].

Overall, the ICW assay may be a promising candidate as an accurate and accessible methodology for C. trachomatis antimicrobial susceptibility testing, since it can be completely automated and, hence, within reach of all laboratories.

Supporting information

S1 Fig. Stability of IRdye 680RD after 1 month of storage at -20°C.

Absorbance values (AU) in relation to C. trachomatis MOI determined by Odyssey CLx in optically clear bottom and standard microplates scanned at day O and after 1 month of storage at -20°C.

https://doi.org/10.1371/journal.pone.0251075.s001

(TIF)

S1 File.

https://doi.org/10.1371/journal.pone.0251075.s002

(XLSX)

References

1. Fenwick A. The global burden of neglected tropical diseases. Public Health. 2012;126(3):233–236. pmid:22325616
- View Article
- PubMed/NCBI
- Google Scholar
2. Report on global sexually transmitted infection surveillance, 2018. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO.
3. Di Pietro M, Filardo S, Romano S, Sessa R. Chlamydia trachomatis and Chlamydia pneumoniae Interaction with the Host: Latest Advances and Future Prospective. Microorganisms. 2019;7(5):140. pmid:31100923
- View Article
- PubMed/NCBI
- Google Scholar
4. Filardo S, Skilton RJ, O’Neill CE, Di Pietro M, Sessa R, Clarke IN. Growth kinetics of Chlamydia trachomatis in primary human Sertoli cells. Sci Rep. 2019;9(1):5847. pmid:30971744
- View Article
- PubMed/NCBI
- Google Scholar
5. O’Connell CM, Ferone ME. Chlamydia trachomatis Genital Infections. Microb Cell. 2016;3(9):390–403. pmid:28357377
- View Article
- PubMed/NCBI
- Google Scholar
6. Filardo S, Di Pietro M, Tranquilli G, Latino MA, Recine N, Porpora MG, et al. Selected Immunological Mediators and Cervical Microbial Signatures in Women with Chlamydia trachomatis Infection. mSystems. 2019;4(4):e00094–19. pmid:31164450
- View Article
- PubMed/NCBI
- Google Scholar
7. Chiarelli TJ, Grieshaber NA, Omsland A, Remien CH, Grieshaber SS. Single-Inclusion Kinetics of Chlamydia trachomatis Development. mSystems. 2020;5(5):e00689–20. pmid:33051378
- View Article
- PubMed/NCBI
- Google Scholar
8. Sessa R, Di Pietro M, Filardo S, Bressan A, Mastromarino P, Biasucci AV, et al. Lactobacilli-lactoferrin interplay in Chlamydia trachomatis infection. Pathog Dis. 2017;75(5). pmid:28505248
- View Article
- PubMed/NCBI
- Google Scholar
9. Soules KR, LaBrie SD, May BH, Hefty PS. Sigma 54-Regulated Transcription Is Associated with Membrane Reorganization and Type III Secretion Effectors during Conversion to Infectious Forms of Chlamydia trachomatis. mBio. 2020;11(5):e01725–20. pmid:32900805
- View Article
- PubMed/NCBI
- Google Scholar
10. Skilton RJ, Cutcliffen LT, Barlow D, Wang Y, Salim O, Lambden PR, et al. Penicillin induced persistence in Chlamydia trachomatis: high quality time lapse video analysis of the developmental cycle. PLoS One. 2009;4(11):e7723. pmid:19893744
- View Article
- PubMed/NCBI
- Google Scholar
11. Shao L, You C, Cao J, Jiang Y, Liu Y, Liu Q. High treatment failure rate is better explained by resistance gene detection than by minimum inhibitory concentration in patients with urogenital Chlamydia trachomatis infection. Int J Infect Dis. 2020;96:121–127. pmid:32173573
- View Article
- PubMed/NCBI
- Google Scholar
12. Mohammadzadeh F, Dolatian M, Jorjani M, Afrakhteh M, Majd HA, Abdi F, et al. Urogenital Chlamydia trachomatis treatment failure with azithromycin: A meta-analysis. Int J Reprod Biomed. 2019;17(9):603–620. pmid:31646255
- View Article
- PubMed/NCBI
- Google Scholar
13. Janssen KJ, Hoebe CJ, Dukers-Muijrers NH, Eppings L, Lucchesi M, Wolffs PF. Viability-PCR Shows That NAAT Detects a High Proportion of DNA from Non-Viable Chlamydia trachomatis. PLoS One. 2016;11(11):e0165920. pmid:27812208
- View Article
- PubMed/NCBI
- Google Scholar
14. Phillips S, Vodstrcil LA, Huston WM, Lawerence A, Timms P, Chen MY, et al. Detection of Chlamydia trachomatis mRNA using digital PCR as a more accurate marker of viable organism. Eur J Clin Microbiol Infect Dis. 2018;37(11):2117–2122. pmid:30109584
- View Article
- PubMed/NCBI
- Google Scholar
15. Shao L, Guo Y, Jiang Y, Liu Y, Wang M, You C, et al. Sensitivity of the Standard Chlamydia trachomatis Culture Method Is Improved After One Additional In Vitro Passage. J Clin Lab Anal. 2016;30(5):697–701. pmid:26987564
- View Article
- PubMed/NCBI
- Google Scholar
16. Mahmud NU, Hossain MA, Nahar K, Ahmed GS, Mahmud C, Paul SK, et al. Non-culture diagnosis of Chlamydia trachomatis genital infection in sexually active women. Mymensingh Med J. 2012;21(1):8–12. pmid:22314447
- View Article
- PubMed/NCBI
- Google Scholar
17. Pitt R, Alexander S, Ison C, Horner P, Hathorn E, Goold P, et al. Phenotypic antimicrobial susceptibility testing of Chlamydia trachomatis isolates from patients with persistent or successfully treated infections. J Antimicrob Chemother. 2018;73(3):680–686. pmid:29207004
- View Article
- PubMed/NCBI
- Google Scholar
18. Eszik I, Lantos I, Önder K, Somogyvári F, Burián K, Endrész V, et al. High dynamic range detection of Chlamydia trachomatis growth by direct quantitative PCR of the infected cells. J Microbiol Methods. 2016;120:15–22. pmid:26578244
- View Article
- PubMed/NCBI
- Google Scholar
19. Suchland RJ, Geisler WM, Stamm WE. Methodologies and cell lines used for antimicrobial susceptibility testing of Chlamydia spp. Antimicrob Agents Chemother. 2003;47(2):636–42. pmid:12543671
- View Article
- PubMed/NCBI
- Google Scholar
20. Jespersen DJ, Flatten KS, Jones MF, Smith TF. Prospective comparison of cell cultures and nucleic acid amplification tests for laboratory diagnosis of Chlamydia trachomatis Infections. J Clin Microbiol. 2005;43(10):5324–6. pmid:16208009
- View Article
- PubMed/NCBI
- Google Scholar
21. Janssen KJH, Dirks JAMC, Dukers-Muijrers NHTM, Hoebe CJPA, Wolffs PFG. Review of Chlamydia trachomatis viability methods: assessing the clinical diagnostic impact of NAAT positive results. Expert Rev Mol Diagn. 2018;18(8):739–747. pmid:29987959
- View Article
- PubMed/NCBI
- Google Scholar
22. Sarshar M, Scribano D, Tranquilli G, Di Pietro M, Filardo S, Zagaglia C, et al. A simple, fast and reliable scan-based technique as a novel approach to quantify intracellular bacteria. BMC Microbiol. 2019 Nov 12;19(1):252. pmid:31718545
- View Article
- PubMed/NCBI
- Google Scholar
23. Boveia V, Schutz-Geschwender A. Quantitative Analysis of Signal Transduction with In-Cell Western Immunofluorescence Assays. Methods Mol Biol. 2015;1314:115–30. pmid:26139260
- View Article
- PubMed/NCBI
- Google Scholar
24. Skilton RJ, Wang Y, O’Neill C, Filardo S, Marsh P, Bénard A, et al. The Chlamydia muridarum plasmid revisited: new insights into growth kinetics. Wellcome Open Res. 2018;3:25. pmid:29657985
- View Article
- PubMed/NCBI
- Google Scholar
25. Sessa R, Di Pietro M, De Santis F, Filardo S, Ragno R, Angiolella L. Effects of Mentha suaveolens essential oil on Chlamydia trachomatis. Biomed Res Int. 2015;2015:508071. pmid:25685793
- View Article
- PubMed/NCBI
- Google Scholar
26. World Health Organization. WHO guidelines for the treatment of Chlamydia trachomatis. World Health Organization. 2016.
27. Zhang Y, Xian Y, Gao L, Elaasar H, Wang Y, Tauhid L, et al. Novel Detection Strategy To Rapidly Evaluate the Efficacy of Antichlamydial Agents. Antimicrob Agents Chemother. 2017;61(2):e02202–16. pmid:27855081
- View Article
- PubMed/NCBI
- Google Scholar
28. Zuck M, Feng C, Hybiske K. Using Fluorescent Proteins to Visualize and Quantitate Chlamydia Vacuole Growth Dynamics in Living Cells. J Vis Exp. 2015;(104):51131. pmid:26484535
- View Article
- PubMed/NCBI
- Google Scholar
29. Vromman F, Laverrière M, Perrinet S, Dufour A, Subtil A. Quantitative monitoring of the Chlamydia trachomatis developmental cycle using GFP-expressing bacteria, microscopy and flow cytometry. PLoS One. 2014;9(6):e99197. pmid:24911516
- View Article
- PubMed/NCBI
- Google Scholar
30. Wang S, Indrawati L, Wooters M, Caro-Aguilar I, Field J, Kaufhold R, et al. A novel automated method for enumeration of Chlamydia trachomatis inclusion forming units. J Immunol Methods. 2007;324(1–2):84–91. pmid:17553519
- View Article
- PubMed/NCBI
- Google Scholar
31. Banhart S, Saied EM, Martini A, Koch S, Aeberhard L, Madela K, et al. Improved plaque assay identifies a novel anti-Chlamydia ceramide derivative with altered intracellular localization. Antimicrob Agents Chemother. 2014;58(9):5537–46. pmid:25001308
- View Article
- PubMed/NCBI
- Google Scholar
32. Spurgers KB, Hurt CR, Cohen JW, Eccelston LT, Lind CM, Lingappa VR, et al. Validation of a cell-based ELISA as a screening tool identifying anti-alphavirus small-molecule inhibitors. J Virol Methods. 2013;193(1):226–31. pmid:23764417
- View Article
- PubMed/NCBI
- Google Scholar
33. Conzelmann C, Gilg A, Groß R, Schütz D, Preising N, Ständker L, et al. An enzyme-based immunodetection assay to quantify SARS-CoV-2 infection. Antiviral Res. 2020;181:104882. pmid:32738255
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Fenwick A. The global burden of neglected tropical diseases. Public Health. 2012;126(3):233–236. pmid:22325616
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Report on global sexually transmitted infection surveillance, 2018. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO.

[ref3] 3. Di Pietro M, Filardo S, Romano S, Sessa R. Chlamydia trachomatis and Chlamydia pneumoniae Interaction with the Host: Latest Advances and Future Prospective. Microorganisms. 2019;7(5):140. pmid:31100923
View Article
PubMed/NCBI
Google Scholar

[7] View Article

[8] PubMed/NCBI

[9] Google Scholar

[ref4] 4. Filardo S, Skilton RJ, O’Neill CE, Di Pietro M, Sessa R, Clarke IN. Growth kinetics of Chlamydia trachomatis in primary human Sertoli cells. Sci Rep. 2019;9(1):5847. pmid:30971744
View Article
PubMed/NCBI
Google Scholar

[11] View Article

[12] PubMed/NCBI

[13] Google Scholar

[ref5] 5. O’Connell CM, Ferone ME. Chlamydia trachomatis Genital Infections. Microb Cell. 2016;3(9):390–403. pmid:28357377
View Article
PubMed/NCBI
Google Scholar

[15] View Article

[16] PubMed/NCBI

[17] Google Scholar

[ref6] 6. Filardo S, Di Pietro M, Tranquilli G, Latino MA, Recine N, Porpora MG, et al. Selected Immunological Mediators and Cervical Microbial Signatures in Women with Chlamydia trachomatis Infection. mSystems. 2019;4(4):e00094–19. pmid:31164450
View Article
PubMed/NCBI
Google Scholar

[19] View Article

[20] PubMed/NCBI

[21] Google Scholar

[ref7] 7. Chiarelli TJ, Grieshaber NA, Omsland A, Remien CH, Grieshaber SS. Single-Inclusion Kinetics of Chlamydia trachomatis Development. mSystems. 2020;5(5):e00689–20. pmid:33051378
View Article
PubMed/NCBI
Google Scholar

[23] View Article

[24] PubMed/NCBI

[25] Google Scholar

[ref8] 8. Sessa R, Di Pietro M, Filardo S, Bressan A, Mastromarino P, Biasucci AV, et al. Lactobacilli-lactoferrin interplay in Chlamydia trachomatis infection. Pathog Dis. 2017;75(5). pmid:28505248
View Article
PubMed/NCBI
Google Scholar

[27] View Article

[28] PubMed/NCBI

[29] Google Scholar

[ref9] 9. Soules KR, LaBrie SD, May BH, Hefty PS. Sigma 54-Regulated Transcription Is Associated with Membrane Reorganization and Type III Secretion Effectors during Conversion to Infectious Forms of Chlamydia trachomatis. mBio. 2020;11(5):e01725–20. pmid:32900805
View Article
PubMed/NCBI
Google Scholar

[31] View Article

[32] PubMed/NCBI

[33] Google Scholar

[ref10] 10. Skilton RJ, Cutcliffen LT, Barlow D, Wang Y, Salim O, Lambden PR, et al. Penicillin induced persistence in Chlamydia trachomatis: high quality time lapse video analysis of the developmental cycle. PLoS One. 2009;4(11):e7723. pmid:19893744
View Article
PubMed/NCBI
Google Scholar

[35] View Article

[36] PubMed/NCBI

[37] Google Scholar

[ref11] 11. Shao L, You C, Cao J, Jiang Y, Liu Y, Liu Q. High treatment failure rate is better explained by resistance gene detection than by minimum inhibitory concentration in patients with urogenital Chlamydia trachomatis infection. Int J Infect Dis. 2020;96:121–127. pmid:32173573
View Article
PubMed/NCBI
Google Scholar

[39] View Article

[40] PubMed/NCBI

[41] Google Scholar

[ref12] 12. Mohammadzadeh F, Dolatian M, Jorjani M, Afrakhteh M, Majd HA, Abdi F, et al. Urogenital Chlamydia trachomatis treatment failure with azithromycin: A meta-analysis. Int J Reprod Biomed. 2019;17(9):603–620. pmid:31646255
View Article
PubMed/NCBI
Google Scholar

[43] View Article

[44] PubMed/NCBI

[45] Google Scholar

[ref13] 13. Janssen KJ, Hoebe CJ, Dukers-Muijrers NH, Eppings L, Lucchesi M, Wolffs PF. Viability-PCR Shows That NAAT Detects a High Proportion of DNA from Non-Viable Chlamydia trachomatis. PLoS One. 2016;11(11):e0165920. pmid:27812208
View Article
PubMed/NCBI
Google Scholar

[47] View Article

[48] PubMed/NCBI

[49] Google Scholar

[ref14] 14. Phillips S, Vodstrcil LA, Huston WM, Lawerence A, Timms P, Chen MY, et al. Detection of Chlamydia trachomatis mRNA using digital PCR as a more accurate marker of viable organism. Eur J Clin Microbiol Infect Dis. 2018;37(11):2117–2122. pmid:30109584
View Article
PubMed/NCBI
Google Scholar

[51] View Article

[52] PubMed/NCBI

[53] Google Scholar

[ref15] 15. Shao L, Guo Y, Jiang Y, Liu Y, Wang M, You C, et al. Sensitivity of the Standard Chlamydia trachomatis Culture Method Is Improved After One Additional In Vitro Passage. J Clin Lab Anal. 2016;30(5):697–701. pmid:26987564
View Article
PubMed/NCBI
Google Scholar

[55] View Article

[56] PubMed/NCBI

[57] Google Scholar

[ref16] 16. Mahmud NU, Hossain MA, Nahar K, Ahmed GS, Mahmud C, Paul SK, et al. Non-culture diagnosis of Chlamydia trachomatis genital infection in sexually active women. Mymensingh Med J. 2012;21(1):8–12. pmid:22314447
View Article
PubMed/NCBI
Google Scholar

[59] View Article

[60] PubMed/NCBI

[61] Google Scholar

[ref17] 17. Pitt R, Alexander S, Ison C, Horner P, Hathorn E, Goold P, et al. Phenotypic antimicrobial susceptibility testing of Chlamydia trachomatis isolates from patients with persistent or successfully treated infections. J Antimicrob Chemother. 2018;73(3):680–686. pmid:29207004
View Article
PubMed/NCBI
Google Scholar

[63] View Article

[64] PubMed/NCBI

[65] Google Scholar

[ref18] 18. Eszik I, Lantos I, Önder K, Somogyvári F, Burián K, Endrész V, et al. High dynamic range detection of Chlamydia trachomatis growth by direct quantitative PCR of the infected cells. J Microbiol Methods. 2016;120:15–22. pmid:26578244
View Article
PubMed/NCBI
Google Scholar

[67] View Article

[68] PubMed/NCBI

[69] Google Scholar

[ref19] 19. Suchland RJ, Geisler WM, Stamm WE. Methodologies and cell lines used for antimicrobial susceptibility testing of Chlamydia spp. Antimicrob Agents Chemother. 2003;47(2):636–42. pmid:12543671
View Article
PubMed/NCBI
Google Scholar

[71] View Article

[72] PubMed/NCBI

[73] Google Scholar

[ref20] 20. Jespersen DJ, Flatten KS, Jones MF, Smith TF. Prospective comparison of cell cultures and nucleic acid amplification tests for laboratory diagnosis of Chlamydia trachomatis Infections. J Clin Microbiol. 2005;43(10):5324–6. pmid:16208009
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref21] 21. Janssen KJH, Dirks JAMC, Dukers-Muijrers NHTM, Hoebe CJPA, Wolffs PFG. Review of Chlamydia trachomatis viability methods: assessing the clinical diagnostic impact of NAAT positive results. Expert Rev Mol Diagn. 2018;18(8):739–747. pmid:29987959
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref22] 22. Sarshar M, Scribano D, Tranquilli G, Di Pietro M, Filardo S, Zagaglia C, et al. A simple, fast and reliable scan-based technique as a novel approach to quantify intracellular bacteria. BMC Microbiol. 2019 Nov 12;19(1):252. pmid:31718545
View Article
PubMed/NCBI
Google Scholar

[83] View Article

[84] PubMed/NCBI

[85] Google Scholar

[ref23] 23. Boveia V, Schutz-Geschwender A. Quantitative Analysis of Signal Transduction with In-Cell Western Immunofluorescence Assays. Methods Mol Biol. 2015;1314:115–30. pmid:26139260
View Article
PubMed/NCBI
Google Scholar

[87] View Article

[88] PubMed/NCBI

[89] Google Scholar

[ref24] 24. Skilton RJ, Wang Y, O’Neill C, Filardo S, Marsh P, Bénard A, et al. The Chlamydia muridarum plasmid revisited: new insights into growth kinetics. Wellcome Open Res. 2018;3:25. pmid:29657985
View Article
PubMed/NCBI
Google Scholar

[91] View Article

[92] PubMed/NCBI

[93] Google Scholar

[ref25] 25. Sessa R, Di Pietro M, De Santis F, Filardo S, Ragno R, Angiolella L. Effects of Mentha suaveolens essential oil on Chlamydia trachomatis. Biomed Res Int. 2015;2015:508071. pmid:25685793
View Article
PubMed/NCBI
Google Scholar

[95] View Article

[96] PubMed/NCBI

[97] Google Scholar

[ref26] 26. World Health Organization. WHO guidelines for the treatment of Chlamydia trachomatis. World Health Organization. 2016.

[ref27] 27. Zhang Y, Xian Y, Gao L, Elaasar H, Wang Y, Tauhid L, et al. Novel Detection Strategy To Rapidly Evaluate the Efficacy of Antichlamydial Agents. Antimicrob Agents Chemother. 2017;61(2):e02202–16. pmid:27855081
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref28] 28. Zuck M, Feng C, Hybiske K. Using Fluorescent Proteins to Visualize and Quantitate Chlamydia Vacuole Growth Dynamics in Living Cells. J Vis Exp. 2015;(104):51131. pmid:26484535
View Article
PubMed/NCBI
Google Scholar

[104] View Article

[105] PubMed/NCBI

[106] Google Scholar

[ref29] 29. Vromman F, Laverrière M, Perrinet S, Dufour A, Subtil A. Quantitative monitoring of the Chlamydia trachomatis developmental cycle using GFP-expressing bacteria, microscopy and flow cytometry. PLoS One. 2014;9(6):e99197. pmid:24911516
View Article
PubMed/NCBI
Google Scholar

[108] View Article

[109] PubMed/NCBI

[110] Google Scholar

[ref30] 30. Wang S, Indrawati L, Wooters M, Caro-Aguilar I, Field J, Kaufhold R, et al. A novel automated method for enumeration of Chlamydia trachomatis inclusion forming units. J Immunol Methods. 2007;324(1–2):84–91. pmid:17553519
View Article
PubMed/NCBI
Google Scholar

[112] View Article

[113] PubMed/NCBI

[114] Google Scholar

[ref31] 31. Banhart S, Saied EM, Martini A, Koch S, Aeberhard L, Madela K, et al. Improved plaque assay identifies a novel anti-Chlamydia ceramide derivative with altered intracellular localization. Antimicrob Agents Chemother. 2014;58(9):5537–46. pmid:25001308
View Article
PubMed/NCBI
Google Scholar

[116] View Article

[117] PubMed/NCBI

[118] Google Scholar

[ref32] 32. Spurgers KB, Hurt CR, Cohen JW, Eccelston LT, Lind CM, Lingappa VR, et al. Validation of a cell-based ELISA as a screening tool identifying anti-alphavirus small-molecule inhibitors. J Virol Methods. 2013;193(1):226–31. pmid:23764417
View Article
PubMed/NCBI
Google Scholar

[120] View Article

[121] PubMed/NCBI

[122] Google Scholar

[ref33] 33. Conzelmann C, Gilg A, Groß R, Schütz D, Preising N, Ständker L, et al. An enzyme-based immunodetection assay to quantify SARS-CoV-2 infection. Antiviral Res. 2020;181:104882. pmid:32738255
View Article
PubMed/NCBI
Google Scholar

[124] View Article

[125] PubMed/NCBI

[126] Google Scholar

Figures

Abstract

Introduction

Materials & methods

Cell line and culture conditions

C. trachomatis propagation and titration

C. trachomatis quantification via In-cell Western assay

Anti-chlamydial drug screening via In-cell Western assay

Odyssey CLx in-cell western assay

Direct immunofluorescence assay

Statistical analysis

Results

Set-up and optimization of the ICW assay

Quantification of C. trachomatis IFUs via ICW

C. trachomatis susceptibility to erythromycin via ICW assay

Discussion

Supporting information

S1 Fig. Stability of IRdye 680RD after 1 month of storage at -20°C.

S1 File.

References