Name: development and validation of a quantitative pcr method for equid herpesvirus-2 diagnostics in respiratory fluids
Uploaded: 2016-03-17T15:00:00
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Description: Watch this Scientific Journal Video about Development and Validation of a Quantitative PCR Method for Equid Herpesvirus-2 Diagnostics in Respiratory Fluids at JoVE.com

The authors would like to thank Sophie Castagnet and Nadia Doubli-Bounoua for their technical support. This work received financial support from the General Council of Calvados and the agreement of Region Basse-Normandie and French Government (CPER 2007-2013; project R25 p3). The authors would like to thank the experts of the AFNOR group and particularly Jean-Philippe Buffereau and Eric Dubois.

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Principles and Methods of Validation of Diagnostic Assay for Infectious Diseases. , (2009).</li><li>Apaza, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+and+genogrouping+of+noroviruses+from+children's+stools+by+Taqman+One-step+RT-PCR.">Detection and genogrouping of noroviruses from children's stools by Taqman One-step RT-PCR.</a> J Vis.Exp. (65), e3232 (2012).</li><li>Lorenz, T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polymerase+chain+reaction:+basic+protocol+plus+troubleshooting+and+optimization+strategies.">Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.</a> J Vis.Exp. (63), e3998 (2012).</li><li>Sanger, F., Coulson, A. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+rapid+method+for+determining+sequences+in+DNA+by+primed+synthesis+with+DNA+polymerase.">A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase.</a> J Mol.Biol. 94 (3), 441-448 (1975).</li><li>Sanger, F., Nicklen, S., Coulson, A. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+sequencing+with+chain-terminating+inhibitors.">DNA sequencing with chain-terminating inhibitors.</a> Proc.Natl.Acad.Sci.U.S.A. 74 (12), 5463-5467 (1977).</li><li>NCBI. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> BLAST Homepage and Selected Search Pages. 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The authors declare that they have no competing financial interests.

Since the 2000s, real-time PCR has been replacing gold standard techniques (cell culture and bacteria culture methods) in an increasing number of laboratories. Implementation of the technique is relatively easy. However validation of laboratory methods is essential for molecular detection and quantification of pathogens to ensure accurate, repeatable and reliable data.
Since the extraction step is the primary source of loss of biological material, it may be considered the main source of error of quantification between one protocol and another. As such, the creation of a standard curve of DNA plasmid during qRT-PCR, mainly reported in the literature, indicates the viral genome load but does not take into account the extraction step.
Description of a de novo strategy for a whole method validation process in the AFNOR norm NF U47-600-2 represents a significant progress in this area. As illustrated in this paper for EHV-2 in horses, or by others in bees21, this necessitates clear differentiation between the development step and the validation step with characterization of the PCR and characterization of the whole method. One limitation in this interesting approach is that any change in the protocol will result in the obligation to revalidate the complete process which could be very costly. This limitation was also highlighted by the fact that the confines of quantification depend on the source from which the virus is extracted (e.g., respiratory fluids, organs, blood or urine). In fact, each matrix presents different specificities in their physico-chemistry characteristics and it is important to define independently each different matrix used for viral detection and quantification by qRT-PCR. Thus, the viral genome load of each biological sample can be quantified more precisely from the extraction. The characterization also takes into account the thermocycler model and when the use of a previously well-characterized method (e.g., the EHV-2 qPCR method described in this paper) necessitates a new type of machine in the parent laboratory or another laboratory, one must confirm the performance of that instrument. The confirmation of the performance of a qPCR assay is a prerequisite for all tests bring into a laboratory. This is normally achieved by analyzing a reference sample with known properties. Such a check is a prerequisite and considered mandatory as requested by the NF 47-600-1 AFNOR norm in order to validate the performance of the qPCR (LOD, LOQ efficiency) and the robustness of the whole method (LOD, LOQ). Not only during the development and characterization steps but also when used in research or for diagnostic purposes, the risk factors can be identified and well controlled to ensure standardization of the protocol. Of particular concern is adequate staff training, highly qualified personnel, quality control of the consumables used and their storage, control of the immediate environmental conditions and awareness of metrological conditions that may affect the performance of the scientific instruments involved in the assay. Use of reference samples for inter-laboratory comparisons could also help control the uncertainties. In this manner, comparison of data between laboratories may be facilitated. Indeed, inter-laboratory proficiency tests are essential to evaluate and confirm the reproducibility of the method.
Viral genome load results which are expressed in international units (IU) of the analyzed biological matrix (IU: copies/ml for fluids or copies/g for tissues) are easier to use in order to compare results between different laboratories. All the results above the LOQ are expressed as copies/ml and a result between the LOD and LOQ is taken as a non-quantifiable positive result. Presenting quantificational data of the genome in this manner conforms more precisely to the process of analyses (amplification of the genome). In fact, in cell culture experiments, expression of the viral load by TCID50 (median tissue culture infective dose) is dependent on the nature of the cells and virus strains. Each strain line possesses its unique infection kinetics and some viruses like EHV-2 can take several days before the first cytopathogenic effect is apparent.
In conclusion, this new method of characterization of qRT-PCR should facilitate the harmonization of data presentation and interpretation between laboratories. This will be very useful for potential new applications of qRT-PCR in the future like the establishment of a cut-off value for declaration of the disease status instead of merely the presence or absence of the pathogen.

Equid herpesvirus-2 (EHV-2) is involved in a respiratory syndrome, with potential clinical manifestations such as nasal discharge, pharyngitis and swollen lymph nodes1-3. This virus is also suspected to be associated with the poor-performance of horses, which may result in a significant and negative economic impact for the horse industry2.
Until now, the gold standard for gamma-EHV (&#947;-EHV) detection was the cell culture method. The first inconvenience of this procedure was the absence of discrimination between EHV-2 and other &#947;-EHV&#39;s (e.g., EHV-5). The second inconvenience was the slow development of the cytopathic process, which takes from 12 to 28 days to manifest4,5.
Development of a validated and normalized quantitative real-time polymerase chain reaction (qRT-PCR) method will help to rapidly detect the virus, to discriminate between EHV-2 and EHV-5 and to study the relationship between the viral genome load and the disease thanks to the quantification aspect.
Polymerase chain reaction (PCR) was described for the first time in 1986 by Mullis6 and is about to become the new gold standard in most of the fields of biological diagnosis (human, environment and veterinary). This method, which is based on the amplification of a part of the genome of pathogens, presents many advantages: specificity, sensitivity and rapidity. Moreover, the risk of amplicon contamination receded since the advent of qRT-PCR and quality assurance7. Nevertheless, the recognition of PCR as a new gold standard method necessitated more than just improved performance data but also the demonstration of the control of development and validation steps of the whole method without degradation of the performance over time.
The first molecular tools used for the detection of EHV-2 were time consuming and involved non-specific amplification with nested PCR followed by sequencing8. The targeted genes for herpes viruses were deoxyribonucleic acid (DNA) polymerase and DNA packaging9. However, nested PCR presents a high risk of contamination by amplicons. Since then, conventional PCR tests have been designed to amplify the interleukin 10-like gene or glycoprotein B gene, reviewed in 20092. More recently, real-time PCR characteristics were described for the quantification of EHV-210 but no data were available concerning validation of the whole method including the extraction process.
In this protocol, development and validation procedures are described for a quantitative PCR method for the detection and quantification of EHV-2 DNA in equine respiratory fluids according to the Association fran&#231;aise de normalisation (AFNOR) norm NF U47-6003,11,12, which is the French representative in the international normalization committee. This norm details the &#34;Requirements and recommendations for the implementation, development and validation of veterinary PCR in animal health analysis method&#34;11,12, according to the NF EN ISO/CEI 17025, 200513 and to OIE (World Organization for Animal Health) recommendations, 201014. The EHV-2 qRT-PCR validation protocol involves a three-part procedure: (a) development of the qRT-PCR assay, (b) characterization of qRT-PCR assay alone and (c) characterization of the whole analytical method (from extraction of nucleic acids from the biological sample to PCR analysis).
The characterization of the qRT-PCR assay and of the whole analytical method include the definition of two limits: the limit of detection (LOD) and the limit of quantification (LOQ). The LOD95% PCR represents the lowest number of nucleic acid copies per unit volume that can be detected in 95% of all cases. The LOQ95% PCR represents the lowest quantity of nucleic acid copies that can be determined taking into account the uncertainties.
This qRT-PCR method allows the precise detection and rapid quantification of EHV-2 in respiratory fluids. Furthermore, the method could be applied in other laboratories to ensure a standardized procedure and as general template for the development of other new qRT-PCR assays.

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			(containing: QIAamp Mini column, AVL&#160; buffer,&#160; AW1 buffer, AW2 buffer, AVE buffer, collection tubes)&#160;</td>
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development and validation of a quantitative pcr method for equid herpesvirus-2 diagnostics in respiratory fluids

The protocol describes a quantitative RT-PCR method for the detection and quantification of EHV-2 in equine respiratory fluids according to the NF U47-600 norm. After the development and first validation step, two distinct characterization steps were performed according to the AFNOR norm: (a) characterization of the qRT-PCR assay alone and (b) characterization of the whole analytical method. The validation of the whole analytical method included the portrayal of all steps between the extraction of nucleic acids and the final PCR analysis. 
Validation of the whole method is very important for virus detection by qRT-PCR in order to get an accurate determination of the viral genome load. Since the extraction step is the primary source of loss of biological material, it may be considered the main source of error of quantification between one protocol and another. For this reason, the AFNOR norm NF-U-47-600 recommends including the range of plasmid dilution before the extraction step. In addition, the limits of quantification depend on the source from which the virus is extracted. Viral genome load results, which are expressed in international units (IU), are easier to use in order to compare results between different laboratories. 
This new method of characterization of qRT-PCR should facilitate the harmonization of data presentation and interpretation between laboratories.

The quantitative RT-PCR method, as described above, was implemented to detect and quantify equid herpesvirus-2 in respiratory fluids. Figure 1 illustrates a schematic workflow chart for the development and validation of a quantitative RT-PCR method according to the AFNOR norm NF U47-600. Specificity of the primers and probes were validated during the step-by-step development of the PCR. Only EHV-2 strains were amplified in this system. Subsequently, the performance of the qRT-PCR had to be characterized.
Firstly, to estimate the LODPCR, a 6 ten-fold serial dilution was performed to establish the abatement zone (Figure 2). In this example, 6 ten-fold serial dilutions were made between 10-5 and 10-10 (between 26,000 and 0.26 copies/2.5 &#181;l sample) to estimate the LODPCR. The abatement zone lies between dilutions of 10-9 and 10-10 (between 2.6 and 0.26 copies/2.5 &#181;l sample). To determine the LODPCR value in this case, 6 two-fold serial dilutions of the plasmid were made in this abatement zone between 5.2 and 0.16 copies/2.5 &#181;l sample. The LODPCR value was 2.6 copies/2.5 &#181;l sample.
To determine the linearity range and LOQPCR, the LODPCR value was used to start the range of 6 ten-fold serial dilutions, between 2.6 (LODPCR) and 260,000 copies/2.5 &#181;l sample. Figure 3 illustrates a linear regression for the EHV2 qRT-PCR from one trial. The performances of linear regression (Figure 4) are validated in quadruplicate using the calculations described in Table 3. The calculations are performed to define the linearity range according to the criteria absolute Biasi value &#8804;0.25 log10, whatever the level i of plasmid load. In this case, the linearity range lay between 2.6 and 260,000 copies/2.5 &#181;l sample. The LOQPCR is the lowest concentration in the linearity range (i.e., 2.6 copies/2.5 &#181;l sample in this case). ULIN was determined to be 0.12 log10 in the range 2.6-260,000 copies/2.5 &#181;l of DNA.
After development (Figure 1, blue) and characterization of the qRT-PCR (Figure 1, yellow), the AFNOR NF U47-600 norm recommends characterization of the whole analytical method from DNA extraction to qRT-PCR (Figure 1, orange). The diagnostic sensitivity and specificity were calculated as described in Table 4. The quantitative performances of the qRT-PCR whole analytical method was evaluated and validated with an accuracy profile (Figure 5).
This protocol, which uses state-of-the-art molecular technology, allowed us to detect and quantify the EHV-2 viral genome load in 172 nasal swab samples obtained from horses with respiratory disorders and/or clinical suspicion of infection. The incidence of EHV-2 from field (biological) samples was 50% (86/172) in this population. The quantitative analyses showed that viral genome loads of EHV-2 were significantly higher in young horses and the repartition of viral genome loads decreased with age (Figure 6). In the present study, the highest EHV-2 viral genome load (1.9 x 1011 copies/ml) was detected in foals (Figure 6).
<img alt="Figure 1" src="/files/ftp_upload/53672/53672fig1.jpg" /> 
Figure 1: Workflow chart for the development (blue), the characterization of the quantitative RT-PCR (yellow) and the characterization of the whole analytical method from DNA extraction to qRT-PCR (orange) according to the AFNOR norm NF U47-600-2. The workflow chart resumes the different steps for the development, the characterization of the quantitative RT-PCR and the characterization of the whole analytical method from DNA extraction to qRT-PCR. For each step, the workflow chart indicates the number of required runs, dilutions to be perform and the number of required analysts. <a href="https://www.jove.com/files/ftp_upload/53672/53672fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53672/53672fig2.jpg" /> 
Figure 2: Determination of the abatement zone with representative results from real-time PCR curves obtained with 6 ten-fold serial dilutions of plasmid. To estimate the abatement zone, 6 ten-fold serial dilutions are made between 10-5 (26,000 copies/2.5 &#181;l sample) and 10-10 (0.26 copies/2.5 &#181;l sample). The abatement zone lies between dilutions of 10-9 (2.6 copies/2.5 &#181;l sample) and 10-10 (0.26 copies/2.5 &#181;l sample). In this case, 6 two-fold serial dilutions of plasmid were made in this abatement zone to determine the LOD 95% PCR, between 5.2 and 0.16 copies/2.5 &#181;l sample. <a href="https://www.jove.com/files/ftp_upload/53672/53672fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53672/53672fig3.jpg" /> 
Figure 3: Linear regression for EHV2 qRT-PCR. The linearity of quantitative testing is the ability to generate results which are proportional to the concentration of the target present in a specific range. This can be modeled by linear regression (y = ax + b) between the instrumental response (Cycle threshold or Ct) and the logarithm of the quantity of the target (number of target copies/2.5 &#181;l sample). <a href="https://www.jove.com/files/ftp_upload/53672/53672fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/53672/53672fig4.jpg" /> 
Figure 4: Performance of linear regression of EHV-2 qPCR. Mean bias represent the mean difference between the measured plasmid quantity (<img alt="fig4-1" src="/files/ftp_upload/53672/fig4-1.jpg" />) and the theoretical plasmid quantity (x&#39;i) for each plasmid level. Vertical bars represent the linearity uncertainty (ULINi) given by the formula 
<img alt="fig4-2" src="/files/ftp_upload/53672/fig4-2.jpg" /> 
where SD&#39;i is the standard deviation of measured plasmid quantity. <a href="https://www.jove.com/files/ftp_upload/53672/53672fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/53672/53672fig5.jpg" /> 
Figure 5: Accuracy profiles based on the validation results of the EHV-2 qRT-PCR method. The green line (circles) represents the trueness of the data (systematic error, or bias). The acceptability limits are defined at &#177; 0.75 Log10 by the laboratory (dashed lines). The lower and the upper accuracy limits were determined for each plasmid load level from the mean bias &#177; twice the standard deviation of the reliability data (red lines). <a href="https://www.jove.com/files/ftp_upload/53672/53672fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/53672/53672fig6.jpg" /> 
Figure 6: Quantification of viral genome loads of EHV-2 according to age. The viral genome load distribution of EHV-2 detected in nasal swab samples is represented for the different age groups. The horizontal lines represent the median values within the standard deviation (m = months). * Significantly different by ANOVA with Newman-Keuls post-hoc test (p &#60;0.05). <a href="https://www.jove.com/files/ftp_upload/53672/53672fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Target gene</td>
			<td colspan="3">Primers, probe and plasmide sequences (5&#39;-3&#39;)</td>
			<td>Nucleotide position</td>
			<td>Product size (nucleotides)</td>
			<td colspan="2">Thermal cycling conditions</td>
			<td>References</td>
		</tr>
		<tr>
			<td rowspan="4">EHV2 gB 
			(HQ247755.1)</td>
			<td colspan="3">Forward: GTGGCCAGCGGGGTGTTC&#160;</td>
			<td>2113-2130</td>
			<td rowspan="4">78</td>
			<td>95 &#176;C 5 min</td>
			<td></td>
			<td rowspan="4">11</td>
		</tr>
		<tr>
			<td colspan="3">Reverse: CCCCCAAAGGGATTYTTGAA</td>
			<td>2189-2170</td>
			<td>95 &#176;C 15 sec</td>
			<td rowspan="2">45 cycles</td>
		</tr>
		<tr>
			<td colspan="3">Probe: FAM-CCCTCTTTGGGAGCATAGTCTCGGGG-MGB</td>
			<td>2132-2157</td>
			<td>60 &#176;C 1 min</td>
		</tr>
		<tr>
			<td colspan="3">Plasmid: 
			ACCTGGGCACCATAGGCAAGGTGGTGGTCA 
			ATGTGGCCAGCGGGGTGTTCTCCCTCTTTG 
			GGAGCATAGTCTCGGGGGTGATAAGCTTTTT 
			CAAAAATCCCTTTGGGGGCATGCTGCTCATA 
			GTCCTCATCATAGCCGGGGTAGTGGTGGTG 
			TACCTGTTTATGACCAGGTCCAGGAGCATAT 
			ACTCTGCCCCCATTAGAATGCTCTACCCCGG 
			GGTGGAGAGGGCGGCCCAGGAGCCGGGCG 
			CGCACCCGGTGTCAGAAGACCAAATCAGGA 
			ACATCCTGATGGGAATGCACCAATTTCAG</td>
			<td>2081-2381</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 1: Sequences of primers, probes and positive synthetic DNA controls used in this protocol. The sequence of plasmid (positive synthetic DNA) corresponds to nucleotide positions 2081-2381 of EHV2gB sequence (HQ247755.1). The design of primers and probes used in this protocol was obtained by using specific software.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2">PATHOGENS</td>
			<td rowspan="2">Reference (origin)</td>
			<td rowspan="2">Number of strains</td>
			<td>RESULTS</td>
		</tr>
		<tr>
			<td>EHV-2</td>
		</tr>
		<tr>
			<td rowspan="2">EHV-2</td>
			<td>VR701 (ATCC)</td>
			<td rowspan="2">20</td>
			<td rowspan="2">Positive</td>
		</tr>
		<tr>
			<td>20 samples (FDL collection)</td>
		</tr>
		<tr>
			<td rowspan="2">EHV-5</td>
			<td>KD05 (GERC)</td>
			<td rowspan="2">20</td>
			<td rowspan="2">Negative</td>
		</tr>
		<tr>
			<td>20 samples (FDL collection)</td>
		</tr>
		<tr>
			<td rowspan="2">EHV-3</td>
			<td>VR352 (ATCC)</td>
			<td rowspan="2">2</td>
			<td rowspan="2">Negative</td>
		</tr>
		<tr>
			<td>T934 WSV (GERC)</td>
		</tr>
		<tr>
			<td rowspan="2">EHV-1</td>
			<td>Kentucky strain Ky A (ATCC)</td>
			<td rowspan="2">3</td>
			<td rowspan="2">Negative</td>
		</tr>
		<tr>
			<td>2 samples (FDL collection)</td>
		</tr>
		<tr>
			<td>EHV-4</td>
			<td>VR2230 (ATCC)</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Asinine herpesvirus AHV5</td>
			<td>FDL Collection</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td rowspan="2">Equine Influenza Virus&#160;</td>
			<td>A/equine/Jouars/4/2006 (H3N8)</td>
			<td rowspan="2">1</td>
			<td rowspan="2">Negative</td>
		</tr>
		<tr>
			<td>(Accession Number JX091752)</td>
		</tr>
		<tr>
			<td>Equine Arteritis Virus</td>
			<td>VR796 (ATCC)</td>
			<td>2</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Rhodococcus equi</td>
			<td>FDL Collection</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Streptococcus equi subsp. Zooepidemicus</td>
			<td>FDL Collection</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Streptococcus equi subsp. equi</td>
			<td>FDL Collection</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Coxiella burnetii&#160;</td>
			<td>ADI-142-100 (Adiagene)</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Chlamydophila abortus</td>
			<td>ADI-211-50 (Adiagene)</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td>Klebsiella pneumoniae</td>
			<td>FDL Collection</td>
			<td>1</td>
			<td>Negative</td>
		</tr>
	</tbody>
</table>
Table 2: Analytical specificity of qRT-PCR for EHV-2.
<img alt="Table 3" src="/files/ftp_upload/53672/53672table3.jpg" /> 
Table 3: Calculation of the bias and linearity uncertainty (adapted from NF U47-600-212). For each trial, the performances of linear regression (y = ax+b) are validated using the table where y is the cycle threshold obtained; a is the slope obtained; x is the plasmid level and b is the intercept. i is the plasmid level (i varies from 1 to k levels); k is the number of plasmid levels used (e.g, k = 6 in this table); j is the trial (j varies from 1 to I trials); I is the number of trials, comprised between 3 and 6 trials (e.g. I = 4 in this table). xi is the estimated plasmid quantity for each i plasmid level. x&#39;i&#160; is the theoretical plasmid quantity obtained with equation x&#39;i = log10(xi) for each i plasmid level. During each j trial, the cycle threshold obtained for each i plasmid level is calculated with the linear regression yi,j = ajxi,j + bj. <img alt="table3-1" src="/files/ftp_upload/53672/table3-1.jpg" /> is the measured plasmid quantity during the trial j. Biasi is the difference observed between the measured plasmid quantity and the theoretical plasmid quantity for each trial and each plasmid level. <img alt="table3-2" src="/files/ftp_upload/53672/table3-2.jpg" /> is the mean value of <img alt="table3-3" src="/files/ftp_upload/53672/table3-3.jpg" /> by each i plasmid level; SD&#39;i is the standard deviation of measured quantity <img alt="table3-4" src="/files/ftp_upload/53672/table3-4.jpg" /> for each i plasmid level; Mean bias is the mean of Biasi; ULINi is the linearity uncertainty determined for each i plasmid level calculated from SD&#39;i and mean bias. <a href="https://www.jove.com/files/ftp_upload/53672/53672table3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td colspan="2">Real status of sample</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>Positive</td>
			<td>Negative</td>
		</tr>
		<tr>
			<td rowspan="3">Results obtained with whole method</td>
			<td>Positive</td>
			<td>RP (real positive)</td>
			<td>FP (false positive)</td>
		</tr>
		<tr>
			<td>Negative</td>
			<td>FN (false negative)</td>
			<td>RN (real negative)</td>
		</tr>
		<tr>
			<td>Total</td>
			<td>RP+FN</td>
			<td>FP+RN</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>Se = RP/(RP+FN)</td>
			<td>Sp = RN/(RN+FP)</td>
		</tr>
	</tbody>
</table>
Table 4: Calculation of diagnostic sensitivity (Se) and specificity (Sp) of the whole method. A Schwartz table was used to calculate the confidence interval at 95% of sensitivity and specificity of the whole method as described in NF U47-600-2.

Watch this Scientific Journal Video about Development and Validation of a Quantitative PCR Method for Equid Herpesvirus-2 Diagnostics in Respiratory Fluids at JoVE.com

Development and Validation of a Quantitative PCR Method for Equid Herpesvirus-2 Diagnostics in Respiratory Fluids

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The protocol describes a quantitative RT-PCR method for the detection and quantification of EHV-2 in equine respiratory fluids according to the NF U47-600 ...

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