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Development and Validation of a Harmonized TaqMan-Based Triplex Real-Time RT-PCR Protocol for the Quantitative Detection of Normalized Gene Expression Profiles of Seven Porcine Cytokines

  • Anja Petrov,

    Affiliation Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Insel Riems, Greifswald, Germany

  • Martin Beer,

    Affiliation Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Insel Riems, Greifswald, Germany

  • Sandra Blome

    sandra.blome@fli.bund.de

    Affiliation Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Insel Riems, Greifswald, Germany

Development and Validation of a Harmonized TaqMan-Based Triplex Real-Time RT-PCR Protocol for the Quantitative Detection of Normalized Gene Expression Profiles of Seven Porcine Cytokines

  • Anja Petrov, 
  • Martin Beer, 
  • Sandra Blome
PLOS
x

Abstract

Dysregulation of cytokine responses plays a major role in the pathogenesis of severe and life-threatening infectious diseases like septicemia or viral hemorrhagic fevers. In pigs, diseases like African and classical swine fever are known to show exaggerated cytokine releases. To study these responses and their impact on disease severity and outcome in detail, reliable, highly specific and sensitive methods are needed. For cytokine research on the molecular level, real-time RT-PCRs have been proven to be suitable. Yet, the currently available and most commonly used SYBR Green I assays or heterogeneous gel-based RT-PCRs for swine show a significant lack of specificity and sensitivity. The latter is however absolutely essential for an accurate quantification of rare cytokine transcripts as well as for detection of small changes in gene expressions. For this reason, a harmonized TaqMan-based triplex real-time RT-PCR protocol for the quantitative detection of normalized gene expression profiles of seven porcine cytokines was designed and validated within the presented study. Cytokines were chosen to represent different immunological pathways and targets known to be involved in the pathogenesis of the above mentioned porcine diseases, namely interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, tumor necrosis factor (TNF)-α and interferon (IFN)-α. Beta-Actin and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as reference genes for normalization. For absolute quantification a synthetic standard plasmid was constructed comprising all target cytokines and reference genes within a single molecule allowing the generation of positive control RNA. The standard as well as positive RNAs from samples, and additionally more than 400 clinical samples, which were collected from animal trials, were included in the validation process to assess analytical sensitivity and applicability under routine conditions. The resulting assay allows the reliable assessment of gene expression profiles and provides a broad applicability to any kind of immunological research in swine.

Introduction

Cytokines are important mediators that orchestrate cellular functions including inflammatory responses and innate immune reactions. However, excessive activation of the innate immune system in response to pathogens can lead to pathological inflammatory consequences [1], and dysregulation of cytokine responses plays a major role in the pathogenesis of severe and life-threatening infectious diseases including viral haemorrhagic fevers [2]. Another example is the “cytokine storm” that is held responsible for the exceptionally high morbidity and mortality in human highly pathogenic influenza virus infections [3]. Hence, cytokine profiles, especially when targeting a set of cytokines expressed within a certain microenvironment [4], [5], can provide important insights into the development of infectious diseases, which are characterised by an immune pathogenesis such as classical swine fever (CSF), a severe porcine infection that can be accompanied by haemorrhagic lesions. For CSF, a cytokine dysregulation is suspected to be decisive for clinical severity [6]. Similar responses are known for African swine fever (ASF) [7], a disease that recently gained importance through its introduction into several Eastern European countries [8], [9].

Cytokines can be targeted at various levels, from assessment of cellular expression profiles using mRNA detection by RT-PCR, to measurement of intracellular proteins by fluorescence-activated cell sorter staining and quantification of secreted cytokine proteins by the use of bioassays, enzyme-linked immunosorbent assays, radioactive immunosorbent assays, and microarrays [10]. For pathogenesis studies, a combination of expression and protein detection methodologies is usually advisable. However, assessment of expression profiles in pigs is so far severely hampered by the lack of fully validated and reliable diagnostic tools. While several PCR systems for porcine cytokine detection were developed during the last years, most of them either comprised non-standardised heterologous conventional RT-PCR systems [11][13] or were performed using intercalating fluorescent dyes such as SYBR-Green I [14][18]. However, these techniques have clear disadvantages compared to TaqMan based PCRs particularly with regard to the lack of sensitivity and specificity which are however essential for the accurate quantification of rare cytokine transcripts and the detection of small changes in gene expression.

With the pig as target species, the presented study reports on the design and validation of a harmonized approach for specific detection of cytokine gene expression profiles in swine. Cytokines were chosen to represent different reaction pattern of the immune system (Th1 and Th2 responses), and mediators that are known to be involved in the pathogenesis of important porcine infections such as CSF. To this means, a harmonized multiplexed one-step TaqMan 5' nuclease [19] protocol for specific detection and quantification of seven cytokines, namely interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, tumor necrosis factor (TNF)-α and interferon (IFN)-α, was designed and validated. Two reference genes were included to allow reliable normalization.

Materials and Methods

1. Selection of primers and probes

Primers and probes for seven porcine cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IFN-α, TNF-α) and two reference genes (β-Actin, GAPDH) were either selected from previous studies [20][25] or designed using “Primer-BLAST” (NCBI GenBank). Sequences and corresponding references are shown in table 1. For corresponding alignments Mega 5- and BioEdit software (IBIS Biosciences Carlsbad, USA) were utilized. For all cytokines, probes were labeled with 6-Carboxyfluorecein (FAM), the β-Actin probe with hexachloro-6-carboxyfluorescein (HEX) and the GAPDH probe with Texas Red (TR). The synthesis of oligonucleotides was carried out by biomers.net (Ulm, Germany).

2. In vitro generation of positive control RNA

2.1. Generation of peripheral blood mononuclear cells (PBMCs).

Approximately 50 ml of porcine EDTA blood were overlayed with the equal amount of lymphocyte separation medium LSM 1077 (PAA Laboratories GmBH, Pasching, Austria) and a density gradient centrifugation at 580 g for 40 min at 20°C without brake was performed. The leucocyte phase was collected and washed with 0.8 mM EDTA solubilized in phosphate buffered saline (PBS-) for removal of separation medium. Thereafter, the remaining erythrocytes were removed through lysis with buffered ammonium chloride solution (containing 153 mM NH4Cl, 10 mM KHCO3, 1 mM EDTA to 1 l (pH 7.4)). To this means, the threefold volume of lysis buffer was added and incubated at 4°C for 15 min. The resulting PBMC suspension was washed with PBS- and cultured in DMEM medium containing 10% fetal bovine serum, 20 mM HEPES including penicillin-streptomycin (“Anti-Anti (100X)”), Antibiotic-Antimycotic from GIBCO by Life Technologies, Carlsbad, California, USA) at approximately 107 cells/ml. After 16 h of incubation at 37°C in a 5% CO2 atmosphere, non-adherent cells where removed through washing with sterile pre-warmed PBS- , and the cleaned PBMC cell suspension was incubated for one to three days for maturation under the same culture conditions until exposure to different cytokine-stimulators.

2.2. In-vitro stimulation of cytokines.

Different mitogens and antigens were used for stimulation of the desired cytokines as previously described [26][29]. Details are depicted in table 2. The stimulating agents were obtained from Sigma (Sigma-Aldrich, St. Louis, Missouri, USA). After a maturation time for PBMCs of one to three days, stimulators were utilized at the following concentrations: Lipopolysaccharide (LPS) 20 µg/ml, all other stimulating agents (Peptidoglycan, PGN; Concanavalin A, ConA; phytohaemagglutinin; PHA; pokeweed mitogen, PWM) 5 µg/ml. Along with the stimulating agents, cells were incubated for approximately 18 h at 37°C with 5% CO2 in 6-well plates until the expected cytokine expression optimum was reached. For RNA extraction, cells were harvested and subjected to RNA extraction using the methods described below.

3. RNA isolation

RNA extraction of different sample matrices was performed using Trizol Reagent (Life Technologies) in combination with the automated MagAttract Virus Mini M48 Kit (QIAGEN GmbH, Hilden, Germany) on the King Fisher 96 Flex instrument (Thermo Scientific) as previously described [30].

4. Analyses of expression stability of reference genes

Confirmatory analyses of stable expressions of β-Actin and GAPDH comprised the following tests. Firstly, in vivo generated PBMCs (see section 2.2.1) were exposed to different stimulating agents (see section 2.2.2 and table 2) while several wells were left untreated by incubating them only with cell culture media each time. PBMC RNA was extracted in different time intervals after stimulation (after 1, 12, 18, 24, 36, 48 and 60 hours) and RT-qPCRs targeting β-Actin and GAPDH were performed comparing the quantification cycle (Cq)-values of stimulated and untreated PBMC RNA. Secondly, RNA from EDTA blood derived from pigs infected with the highly virulent CSFV-strain “Koslov” were used in RT-qPCR. Cq-values of β-Actin and GAPDH were detected prior to infection and compared to measurements at different time intervals after infection.

5. Construction of synthetic standard RNA

A synthetic gene comprising all target cytokines and reference genes (see figure 1) was constructed and synthesized by GeneArt Gene Synthesis (Life Technologies). The Kanamycin-resistant gene was transformed in corresponding resistant bacteria after permeabilization. The bacteria plasmid was purified with QIAfilter Plasmid Maxi Kit (Qiagen, Venlo, Netherlands) and the nucleic acid concentration was determined with a NanoDrop 2000c Spectrophotometer (PEQLAB Biotechnologie GmbH, Polling, Austria). To verify the transformation process the plasmid was sequenced using the Big Dye Terminator v1.1 Cycle sequencing Kit (Applied Biosystems). Nucleotide sequences were read with an automatic sequencer (3130 Genetic Analyzer, Applied Biosystems) and analyzed using the Genetics Computer Group software version 11.1 (Accelrys Inc., San Diego, USA). Thereafter, the DNA-plasmid was used for synthesis of heterologous RNA. It was cleaved at the attached NOD1-restriction site with NOD1 enzyme (New England Biolabs, Ipswitch, Massachusetts, USA) and linearized DNA strands were filtrated and eluted by using QIAquick Nucleotide Removal Kit (Qiagen). The obtained DNA was in vitro transcribed using T7 RNA Polymerase (Promega Corporation, Madison, USA). Subsequently, the DNA matrix was removed through DNase I digestion (RQ1 RNase-Free DNase, Promega). The gained RNA was visualized by 1% agarose gel electrophoresis. RNeasy Mini Kit (Qiagen) was utilized in combination with Trizol Reagent (Life Technologies) and DNA digestion (with RNase-Free DNase Set (Qiagen)) for a final RNA cleanup. Finally, RNA concentration was determined using the NanoDrop spectrophotometer (Peqlab) and the concentration was set to 2×109 copies/µl. A 10-fold standard dilution series was generated in RNA-safe buffer (50 ng/µl of carrier polyA-RNA, 0.05% Tween-20, 0.05% sodium azided in RNase-free water). Dilutions from 2×101 to 2×106 copies/µl were employed for subsequent RT-qPCRs.

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Figure 1. Composition of the synthetic standard gene comprising all target cytokines (IL-2, IL-4, IL-8, TNF-α, IFN-α, IL-6, IL-1β) and internal reference genes (β-Actin, GAPDH, HPRT (Hypoxanthin-Guanin-Phosphoribosyltransferase), starting with the T7-promotor sequence and concluding with the NOD1 restriction site as initial point for linearization and transformation to RNA.

Each target cytokine was included with a nucleotide overhang of approximately 50 base pairs (bp) prior to forward primer sequence. In total, the synthetic standard gene comprises 1464 bp.

https://doi.org/10.1371/journal.pone.0108910.g001

6. RT-qPCR

Prior to implementation in RT-qPCR systems, 10-fold dilution series of each in-vitro generated positive control RNA and the synthetic standard RNA were amplified in conventional RT-PCR, visualized in 3% agarose gel electrophoresis and verified by sequencing. Sequence data were obtained from the NCBI GenBank and corresponding alignments were carried out with Mega 5- and BioEdit software (IBIS Biosciences Carlsbad, USA).

In a first step, single-tube assays were designed for each cytokine or reference gene as basis for the subsequent development of the triplex RT-qPCR protocol using the AgPath-ID One-Step RT-PCR reagents (Ambion-Applied Biosystems, Thermo Fisher Scientific by Life technologies) for simultaneous detection of one target cytokine and two reference genes.

Subsequently, tests for the reduction of the total mastermix reaction volume from 25 µl to 12.5 µl were carried out. Thereby, the mastermix for a single reaction comprised 0.25 µl RNase-free water, 6.25 µl 2× RT- PCR Buffer, 0.5 µl of 25× RT- PCR Enzyme Mix, 1 µl FAM-labelled cytokine-primer-probe mix, 1 µl of each reference gen-primer-probe mix and finally 2.5 µl of template RNA.

All RT-qPCRs were performed with a Bio-Rad CFX 96 Real-Time Detection Systems (Bio-Rad, Hercules, CA, USA). Protocols for all cytokine RT-qPCRs were adjusted to the same thermal profile: reverse transcription at 45°C for 10 min, followed by PCR activation for 10 min at 95°C and 45 cycles including denaturation phase at 95°C for 15 sec, annealing at 57°C for 20 sec and elongation for 30 sec at 72°C. Data were collected during the annealing phase.

Oligonucleotide concentrations were optimized through checkerboard titrations. Furthermore, confirmatory tests for the absence of residual DNA in isolated RNA samples were performed by deployment of the one- and two-step RT-qPCR chemistry from Promega. For that purpose, RNA samples were tested using both systems under the same conditions while the two-step assay was carried out without adding the enzyme for reverse transcription.

Moreover, reproducibility of all assays was tested using the standard RNA in triplicates and deviations of Cq-value were determined.

In addition, 402samples gathered from pigs infected or vaccinated with CSFV (leucocyte samples) and infected with ASFV (EDTA blood samples) during several animal trials carried out at the Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Insel Riems, Germany (sample repository) were tested in all seven triplex RT-qPCRs (see table 3). In the experimental studies involving live animals, all applicable animal welfare regulations, including EU Directive 2010/63/EC and institutional guidelines, were taken into consideration. The animal experiments were approved by the competent German authority (Landesamt für Landwirtschaft, Lebensmittelsicherheit und Fischerei Mecklenburg-Vorpommern) under reference numbers 7221.3-1.1-015/12 and 7221.3-1.1-018/12.

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Table 3. Samples from different animal trials (n = 402) used for assay validation.

https://doi.org/10.1371/journal.pone.0108910.t003

Results

1. Confirmation of identity and stable expression of reference genes

Identity of all cytokines and reference genes could be confirmed by alignments with sequences available through NCBI GenBank. No indications for possible cross-reactions were observed. Absence of residual DNA in extracted RNA samples was proven by tests for no-reverse transcription (RT) as described in section 2.6.

RT-qPCRs conducted for the assessment of β-Actin- and GAPDH as reference targets (see section 2.4) revealed no coherent changes in expression levels after different stimulation or infection and thus, suitability for gene expression normalization was confirmed.

2. Sensitivity

For first assessment of analytical sensitivity, a 10-fold dilution series of the positive control RNA derived from the synthetic plasmid was employed for testing each cytokine and reference gene. The resulting standard curves from all single tube assays are shown in figure S1, starting from 2×107 copies/µl as highest standard to 2×101 copies/µl as lowest. Corresponding Cq-values and efficiencies for all assays are listed in table S1. The last employed standard dilution of to 2×101 copies/µl could be detected by each assay except for β-Actin which showed a detection limit of 2×102 copies/µl. Cq-values of standard RNA dilutions ranged between 15 for the highest standard and 35 for the lowest (see table S1).

Sensitivity was further analyzed by testing in vitro-generated positive RNA in 10-fold dilutions from 10−1 to 10−7. The measured Cq-values as well as limits of detections are shown in table S1 ranging from a dilution of 10−3 (for IL-6 and IFN-α) to more than 10−7 for IL-8.

Finally, the applicability of all assays for routine pig samples (EDTA blood and white blood cells) could be demonstrated by testing a total number of 402 samples from pigs infected with different CSFV strains, ASFV “Armenia08”or from CSFV vaccinated pigs. Exemplary results for normalized TNF-α and IL-8 expression (ΔΔCq) after infection of two different pig breeds with the highly virulent CSF virus strain “Koslov” are depicted in figures 2 and 3, respectively. Additionally, detailed information comprising the results of all seven triplex assays including Cq values and corresponding normalized gene expressions are provided in table S5. To link gene expression with protein detection, exemplary results are depicted in figure S2.

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Figure 2. Detection of normalized TNF-α gene expression (ΔΔCq) in leukocyte samples from CSFV infected pigs.

Samples were obtained from two different pig breeds at days 0, 2, 4, and 7 post infection (dpi). Results are given as mean values: in total from all animals (TNF-α overall mean) and separately for each breed (Mean Breed 1, Mean Breed 2). Bars indicate standard deviations.

https://doi.org/10.1371/journal.pone.0108910.g002

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Figure 3. Detection of normalized IL-8 gene expression (ΔΔCq) in leukocyte samples from CSFV infected pigs.

Samples were obtained from two different pig breeds at days 0, 2, 4, and 7 post infection (dpi). Results are given as mean values: in total from all animals (IL-8 overall mean) and separately for each breed (Mean Breed 1, Mean Breed 2). Bars indicate standard deviations.

https://doi.org/10.1371/journal.pone.0108910.g003

3. Implementation of seven cytokine triplex RT-qPCR assays

In order to detect one cytokine and two reference genes simultaneously a triplex protocol was developed (as described in section 2.6). Checkerboard titrations of all primers and probes revealed the following optimal and harmonized concentrations: for all cytokines the harmonized protocols uses 10 pmol primers, 2.5 pmol probe, and for reference genes 2.5 pmol primers, 1.25 pmol probe.

A comparison between single and triplex assays was performed for each cytokine by using the standard RNA and in vitro-generated positive RNA in 10-fold dilutions. The comparative results are presented in table S2.

The analyses revealed variations of Cq-values between single and multiplex assays of less than 2 Cq-values in all cases apart from two exceptions, in which higher deviations were found within the last dilution steps of positive RNA (IFN-α, IL-1β). Each single and triplex assay was able to detect the lowest deployed standard (see table S2). Furthermore, losses of end fluorescence levels (End RFUs) did not obviously influence final results (see figure 4).

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Figure 4. Comparative amplifications of 10-fold diluted standard RNA ranging from 2×102 to 2×107 copies/µl of single target and multiplex assays of all target cytokines (FAM).

The vertical axis demonstrate fluorescence levels (relative fluorescence units, RFU), the horizontal axis shows the number of cycles. Comparative illustrations of end fluorescence levels of standard curves are shown illustrating higher end fluorescences in single target compared triplex assays in which target cytokines were detected simultaneously with β-Actin (HEX) and GAPDH (TR).

https://doi.org/10.1371/journal.pone.0108910.g004

All validation experiments of the triplex RT-qPCR protocol were performed with a total mastermix reaction volume of 12.5 µl including 2.5 µl RNA-template. Comparative analyses of full (25 µl) and halved (12.5 µl) approaches revealed no notable differences of Cq-values, detected genome copies and fluorescence levels (RFUs) as shown in table S3. Cq-losses higher than 3 were only observed in some of the lowermost dilution steps within the standard- and positive RNA 10-fold dilution series. For example, the lowest standard of 2×101 copies/µl revealed Cq-losses in assays targeting IL-2, IL-8 and IL-1β (FAM) or by targeting β-Actin (HEX) in the IFN-α triplex assay and GAPDH (TR) in the IL-2, TNF-α and IFN-α triplex assays respectively. Apart from that, no notable differences of Cq-values or absolute quantities were measured. End fluorescence levels revealed differences between approximately 500 to maximum deviations of 3000 (see table S3).

Finally, reproducibility was tested as described in section 2.6 and could be confirmed by showing no notable differences in Cq-values between the standard RNA triplicates in all assays (see table S4). Cytokine Cq-deviations were below 1 in the majority of cases which corresponds to a less than with a less than 3-fold deviation. In general, variation was mainly observed in higher dilutions (lowest target concentrations, see table S4).

Discussion

Cytokines are powerful mediators of the immune system and have a key role in the selection of immunological pathways and link innate and adaptive immune responses. To date, many basic immune pathological mechanisms e.g. for haemorrhagic diseases like CSF and ASF have not been clearly defined showing the need for reliable detection tools in order to characterize beneficial or detrimental reaction patterns. The selection of target cytokines for this study pursued the objective of covering a preferably wide range of immunological events in swine. While IL-2 can be regarded as indicator for the Th1 pathway, IL-4 is indicative for the Th2 response respectively [31]. The endogenous pyrogen TNF-α is of great importance as it can provoke shock symptoms upon systemically release. Yet, it also has beneficial abilities through a local restrictive effect after infection [31]. Especially in the context of CSF pathogenesis, it has been proven one of the most crucial cytokines [32]. In this context, inclusion of the TNF-α induced proinflammatory cytokines IL-1β and IL-6 seems reasonable for their potential of acting either pyrogenic or activating monocytes and natural killer cells [31]. In contrast, IL-8 which can be produced e.g. by T-helper cells can be indicative for the Th2 pathway possessing the abilities of attracting neutrophil granulocytes, lymphocytes and of contributing to angiogenesis [31]. An IL-8 dysregulation is suspected to be involved in CSF development [20]. Finally, as an effective mediator of antiviral resistance, IFN-α is particularly involved in important mechanisms of innate immunity [33] and was therefore included in the established assay. Taken together, the selected cytokines represent valuable immunological markers by giving information about complex immunological responses.

Among the most suitable techniques for molecular cytokine research is the highly sensitive one-step RT-qPCR system [34] which allows quantitative analyses as well as multiplexing. As already stated by Huggett et al., the enhanced specificity of TaqMan-based real-time assays is greatly advantageous for immunological research since many cytokines appear in such low abundances that detection of their mRNA by real-time RT-PCR represents the only method which is sensitive enough for reliably measuring their expression in vivo [24], [35]. So far, gel-based PCR systems have been applied widely for cytokine detection [11], [13] despite their disadvantage of being not truly quantitative and often leading to an underestimation of total mRNA levels because of common depletion of reagents during the reaction [36]. Consequently, PCR products are not proportional to the amount of initial target when visualised on a gel [37]. The most widely used SYBR-Green I assays [38][42] have the disadvantages of potentially generating primer-dimers, the indiscriminately binding to all double-stranded DNA which might lead to a formation of secondary structures, and to a possibly limiting primer-concentration as well as to an overestimation of target-DNA [43]. To overcome these problems and to add specificity, a fluorogenic probe based approach was chosen in the presented study. The probe detection system in TaqMan PCRs make those assays clearly advantageous in comparison to SYBR Green and conventional PCR methods as they provide a high level of target specificity [19]. Specificity is particularly difficult to prove in immunological assays as truly negative biological samples are difficult to obtain (e.g. stress reactions or previous pathogen contact). However, “negative” control samples were involved in the establish procedure either originating from in vitro generated PMBCs or from pigs of untreated control groups. To prove the “diagnostic” performance of the established assay more than 400 samples were collected during several animal trials including CSFV vaccination and infection as well as ASFV infection and were tested in all seven triplex assays. However, due to the above mentioned reasons, comparative evaluations of true “positive” and “negative” pigs concerning specific cytokine gene expressions was problematic. During the development procedure, the “Assay validation pathway” [44] was implemented as far as for this purpose possible by detecting analytical performance characteristics. The assessment of repeatability revealed a high level of agreement between triplicates of synthetic standard RNA by showing only minor deviations while increased variations were exclusively found in dilution steps with lowest concentrations as shown in table S4. Furthermore, limits of detections were assessed for determining the analytical sensitivity for each, single-target test (see table S1), comparative analyses between single target and multiplex assays (see table S2) as well as the comparison between a full mastermix reaction volume of 25 µl and a halved volume of 12.5 µl (see table S3). Indeed detection limits partly showed decreases in triplex assays compared to single target PCRs and also in the halve approach compared to the full, but these were measured in negligible amounts or exclusively within the least dilutions of the standard RNA or biological control RNA. Thereby, it could be proven that RT-qPCR chemistry as well as the sample volume could be successfully halved making the assay much more cost-effective and that simultaneous detection of one target cytokine and two reference genes is possible which allows an accurate determination of gene expression profiles by normalization. Another advantage of inclusion of two reference genes is to control varying amounts of input RNA used in the reverse transcription step [34]. This is particularly useful regarding the high variability of biological sample material. Different stimulation and infection experiments were successfully conducted for further confirmation of stable β-Actin and GAPDH expressions [45] despite this was already shown by preliminary studies [46].

First implementation of the assays in different animal trials (see examples in table S5) showed that the choice of sample matrices and sample handling (especially leukocyte preparation and freeze/thawing) had a strong impact on the detection of cytokine gene expression. While in vitro stimulations proved that the respective cytokine mRNAs were reliably detected (see results for positive RNAs), diagnostic samples often resulted in negative results (if normalized gene expression was assessed). In this context, further validation and optimization for sample transport (direct cooling), preparation (avoiding freeze/thawing) and extraction (direct sample suspension in Trizol or equivalents) is clearly needed.

Conclusions

A one-step TaqMan-based triplex RT-qPCR protocol was established and validated for the accurate and reliable detection and quantification of seven porcine cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, TNF-α, IFN-α) representing immunological markers by covering a broad range of host responses. These real-time assays were successfully harmonized by using a unique RT-qPCR protocol along with the same chemistry, temperature profile and synthetic standard resulting in a simple, cost-efficient, specific and highly sensitive assessment of normalized gene expression profiles. This novel and versatile tool will aid not only studies of swine fever pathogenesis but also swine immunology in general.

Supporting Information

Figure S1.

Amplifications of all single assays of 10-fold diluted standard RNA ranging from 2×101 to 2×107 copies/µl.

https://doi.org/10.1371/journal.pone.0108910.s001

(TIF)

Figure S2.

Exemplary comparison of gene expression and cytokine protein detection using ELISA systems (IL-6 and IL-8).

https://doi.org/10.1371/journal.pone.0108910.s002

(TIF)

Table S1.

RT-qPCR results of all single target assays.

https://doi.org/10.1371/journal.pone.0108910.s003

(DOC)

Table S2.

Comparison of single target and triplex RT-qPCR results.

https://doi.org/10.1371/journal.pone.0108910.s004

(DOC)

Table S3.

Comparison of RT-qPCRs between a total mastermix reaction volume of 25 µl and the halved volume of 12.5 µl.

https://doi.org/10.1371/journal.pone.0108910.s005

(DOC)

Table S4.

Assessment of reproducibility by the use of a synthetic standard RNA dilution series as triplicates.

https://doi.org/10.1371/journal.pone.0108910.s006

(DOC)

Acknowledgments

Our special thanks go to Christian Korthase for help and assistance throughout the project. Furthermore, we would like to thank the laboratory technicians involved, especially UIrike Kleinert and Kristin Trippler.

Author Contributions

Conceived and designed the experiments: AP MB SB. Performed the experiments: AP. Analyzed the data: AP MB SB. Contributed reagents/materials/analysis tools: AP MB SB. Wrote the paper: AP MB SB.

References

  1. 1. Iwasaki A, Medzhitov R (2011) A new shield for a cytokine storm. Cell 146: 861–862.
  2. 2. Bray M (2005) Pathogenesis of viral hemorrhagic fever. Curr Opin Immunol 17: 399–403.
  3. 3. Tscherne DM, Garcia-Sastre A (2011) Virulence determinants of pandemic influenza viruses. The Journal of clinical investigation 121: 6–13.
  4. 4. O'Garra A, Murphy K (1994) Role of cytokines in determining T-lymphocyte function. Curr Opin Immunol 6: 458–466.
  5. 5. de Jager W, Bourcier K, Rijkers GT, Prakken BJ, Seyfert-Margolis V (2009) Prerequisites for cytokine measurements in clinical trials with multiplex immunoassays. BMC Immunol 10: 52.
  6. 6. Lange A, Blome S, Moennig V, Greiser-Wilke I (2011) [Pathogenesis of classical swine fever–similarities to viral haemorrhagic fevers: a review]. Berl Munch Tierarztl Wochenschr 124: 36–47.
  7. 7. Blome S, Gabriel C, Beer M (2013) Pathogenesis of African swine fever in domestic pigs and European wild boar. Virus Res 173: 122–130.
  8. 8. Costard S, Wieland B, de Glanville W, Jori F, Rowlands R, et al. (2009) African swine fever: how can global spread be prevented? Philosophical transactions of the Royal Society of London Series B, Biological sciences 364: 2683–2696.
  9. 9. Sanchez-Vizcaino JM, Mur L, Martinez-Lopez B (2013) African swine fever (ASF): five years around Europe. Veterinary microbiology 165: 45–50.
  10. 10. de Jager W, te Velthuis H, Prakken BJ, Kuis W, Rijkers GT (2003) Simultaneous detection of 15 human cytokines in a single sample of stimulated peripheral blood mononuclear cells. Clinical and diagnostic laboratory immunology 10: 133–139.
  11. 11. Choi C, Kwon D, Jung K, Ha Y, Lee YH, et al. (2006) Expression of inflammatory cytokines in pigs experimentally infected with Mycoplasma hyopneumoniae. J Comp Pathol 134: 40–46.
  12. 12. Segura M, Vanier G, Al-Numani D, Lacouture S, Olivier M, et al. (2006) Proinflammatory cytokine and chemokine modulation by Streptococcus suis in a whole-blood culture system. FEMS Immunol Med Microbiol 47: 92–106.
  13. 13. Techau ME, Johansen MV, Aasted B, Lind P, Ornbjerg N, et al. (2007) Cytokine mRNA profiles in pigs exposed prenatally and postnatally to Schistosoma japonicum. Vet Res 38: 25–36.
  14. 14. Shi KC, Guo X, Ge XN, Liu Q, Yang HC (2010) Cytokine mRNA expression profiles in peripheral blood mononuclear cells from piglets experimentally co-infected with porcine reproductive and respiratory syndrome virus and porcine circovirus type 2. Vet Microbiol 140: 155–160.
  15. 15. Razzuoli E, Villa R, Sossi E, Amadori M (2011) Reverse transcription real-time PCR for detection of porcine interferon alpha and beta genes. Scand J Immunol 74: 412–418.
  16. 16. Islam MA, Uddin MJ, Tholen E, Tesfaye D, Looft C, et al. (2012) Age-related changes in phagocytic activity and production of pro-inflammatory cytokines by lipopolysaccharide stimulated porcine alveolar macrophages. Cytokine 60: 707–717.
  17. 17. Charerntantanakul W, Yamkanchoo S, Kasinrerk W (2013) Plasmids expressing porcine interferon gamma up-regulate pro-inflammatory cytokine and co-stimulatory molecule expression which are suppressed by porcine reproductive and respiratory syndrome virus. Vet Immunol Immunopathol 153: 107–117.
  18. 18. Ferrari L, Martelli P, Saleri R, De Angelis E, Cavalli V, et al. (2013) Lymphocyte activation as cytokine gene expression and secretion is related to the porcine reproductive and respiratory syndrome virus (PRRSV) isolate after in vitro homologous and heterologous recall of peripheral blood mononuclear cells (PBMC) from pigs vaccinated and exposed to natural infection. Vet Immunol Immunopathol 151: 193–206.
  19. 19. Livak KJ, Flood SJ, Marmaro J, Giusti W, Deetz K (1995) Oligonucleotides with fluorescent dyes at opposite ends provide a quenched probe system useful for detecting PCR product and nucleic acid hybridization. PCR Methods Appl 4: 357–362.
  20. 20. Lange A (2010) In vitro and in vivo detemination of cytokine gene expression profiles after infection with Classical swine fever virus. Hannover: Gottfried Wilhelm Leibniz Universtität Hannover. pp.96.
  21. 21. Duvigneau JC, Hartl RT, Groiss S, Gemeiner M (2005) Quantitative simultaneous multiplex real-time PCR for the detection of porcine cytokines. J Immunol Methods 306: 16–27.
  22. 22. Yang XQ, Murani E, Ponsuksili S, Wimmers K (2012) Association of TLR4 polymorphism with cytokine expression level and pulmonary lesion score in pigs. Molecular Biology Reports 39 pp 7003–7009.
  23. 23. Toussaint JF, Sailleau C, Breard E, Zientara S, De Clercq K (2007) Bluetongue virus detection by two real-time RT-qPCRs targeting two different genomic segments. Journal of virological methods 140: 115–123.
  24. 24. Demissie A, Abebe M, Aseffa A, Rook G, Fletcher H, et al. (2004) Healthy individuals that control a latent infection with Mycobacterium tuberculosis express high levels of Th1 cytokines and the IL-4 antagonist IL-4delta2. J Immunol 172: 6938–6943.
  25. 25. Bautista EM, Ferman GS, Gregg D, Brum MC, Grubman MJ, et al. (2005) Constitutive expression of alpha interferon by skin dendritic cells confers resistance to infection by foot-and-mouth disease virus. Journal of virology 79: 4838–4847.
  26. 26. Sorensen NS, Skovgaard K, Heegaard PM (2011) Porcine blood mononuclear cell cytokine responses to PAMP molecules: comparison of mRNA and protein production. Vet Immunol Immunopathol 139: 296–302.
  27. 27. Verfaillie T, Cox E, To LT, Vanrompay D, Bouchaut H, et al. (2001) Comparative analysis of porcine cytokine production by mRNA and protein detection. Vet Immunol Immunopathol 81: 97–112.
  28. 28. Charley B, Laverne S, Lavenant L (1990) Recombinant porcine interferon-gamma activates in vitro porcine adherent mononuclear cells to produce interleukin 1. Vet Immunol Immunopathol 25: 117–124.
  29. 29. Knoetig SM, McCullough KC, Summerfield A (2002) Lipopolysaccharide-induced impairment of classical swine fever virus infection in monocytic cells is sensitive to 2-aminopurine. Antiviral Res 53: 75–81.
  30. 30. Hoffmann B, Schulz C, Beer M (2013) First detection of Schmallenberg virus RNA in bovine semen, Germany, 2012. Vet Microbiol 167: 289–295.
  31. 31. PDTW J (1996) Zelluläre und molekulare Grundlagen der Immunologie. Bern: Universität Bern, Institut für Veterinär-Virologie. pp.183.
  32. 32. Lange A, Blome S, Moennig V, Greiser-Wilke I (2011) [Pathogenesis of classical swine fever–similarities to viral haemorrhagic fevers: a review]. Berliner und Munchener tierarztliche Wochenschrift 124: 36–47.
  33. 33. Stark GR, Kerr IM, Williams BR, Silverman RH, Schreiber RD (1998) How cells respond to interferons. Annu Rev Biochem 67: 227–264.
  34. 34. Huggett J, Dheda K, Bustin S, Zumla A (2005) Real-time RT-PCR normalisation; strategies and considerations. Genes Immun 6: 279–284.
  35. 35. Fletcher HA, Owiafe P, Jeffries D, Hill P, Rook GA, et al. (2004) Increased expression of mRNA encoding interleukin (IL)-4 and its splice variant IL-4delta2 in cells from contacts of Mycobacterium tuberculosis, in the absence of in vitro stimulation. Immunology 112: 669–673.
  36. 36. Santagati S, Garnier M, Carlo P, Violani E, Picotti GB, et al. (1997) Quantitation of low abundance mRNAs in glial cells using different polymerase chain reaction (PCR)-based methods. Brain Res Brain Res Protoc 1: 217–223.
  37. 37. Whelan JA, Russell NB, Whelan MA (2003) A method for the absolute quantification of cDNA using real-time PCR. J Immunol Methods 278: 261–269.
  38. 38. Kumar N, Raina OK, Nagar G, Prakash V, Jacob SS (2013) Th1 and Th2 cytokine gene expression in primary infection and vaccination against Fasciola gigantica in buffaloes by real-time PCR. Parasitol Res 112: 3561–3568.
  39. 39. Sanchez-Matamoros A, Kukielka D, De las Heras AI, Sanchez-Vizcaino JM (2013) Development and evaluation of a SYBR Green real-time RT-PCR assay for evaluation of cytokine gene expression in horse. Cytokine 61: 50–53.
  40. 40. Forlenza M, Kaiser T, Savelkoul HF, Wiegertjes GF (2012) The use of real-time quantitative PCR for the analysis of cytokine mRNA levels. Methods in molecular biology 820: 7–23.
  41. 41. Razzuoli E, Villa R, Sossi E, Amadori M (2011) Reverse transcription real-time PCR for detection of porcine interferon alpha and beta genes. Scandinavian journal of immunology 74: 412–418.
  42. 42. Espino AM, Rivera F (2010) Quantitation of cytokine mRNA by real-time RT-PCR during a vaccination trial in a rabbit model of fascioliasis. Veterinary parasitology 169: 82–92.
  43. 43. Vanysacker L, Denis C, Roels J, Verhaeghe K, Vankelecom IF (2014) Development and evaluation of a TaqMan duplex real-time PCR quantification method for reliable enumeration of Candidatus Microthrix. J Microbiol Methods 97: 6–14.
  44. 44. OIE (2013) Principles and methods of validation of diagnostic assays for infectious diseases. OIE Terrestrial Manual 2013.
  45. 45. Overbergh L, Valckx D, Waer M, Mathieu C (1999) Quantification of murine cytokine mRNAs using real time quantitative reverse transcriptase PCR. Cytokine 11: 305–312.
  46. 46. Facci MR, Auray G, Meurens F, Buchanan R, van Kessel J, et al. (2011) Stability of expression of reference genes in porcine peripheral blood mononuclear and dendritic cells. Vet Immunol Immunopathol 141: 11–15.
  47. 47. Yang XQ, Murani E, Ponsuksili S, Wimmers K (2012) Association of TLR4 polymorphism with cytokine expression level and pulmonary lesion score in pigs. Springer Science+Business Media BV 2012 39: 7003–7009.
  48. 48. Bautista EM, Ferman GS, Gregg D, Brum MC, Grubman MJ, et al. (2005) Constitutive expression of alpha interferon by skin dendritic cells confers resistance to infection by foot-and-mouth disease virus. J Virol 79: 4838–4847.
  49. 49. Toussaint JF, Sailleau C, Breard E, Zientara S, De Clercq K (2007) Bluetongue virus detection by two real-time RT-qPCRs targeting two different genomic segments. J Virol Methods 140: 115–123.