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Evaluation of the Real-time Polymerase Chain Reaction for Direct Detection of Mycobacterium Tuberculosis Complex

  • Faculty of Medicine - Suez Canal University

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Evaluation of the Real-time Polymerase Chain Reaction for Direct
Detection of Mycobacterium Tuberculosis complex
1Samaa A. Taha, 1Sahar Z. Elazab, 1Hasan N. Mohamed, 1Gehan S.
El-Hadidy, 2Mohamed N. Hamed Loay
1Department of Microbiology and Medical Immunology, 2Department of Internal Medicine
(Chest Unit), Faculty of Medicine, Suez Canal University.
Tuberculosis is considered the second most important public health problem in Egypt,
after schistosomiasis. The aim of this study was to evaluate the accuracy of real-time
PCR for direct detection of M. tuberculosis complex. The study was conducted on
patients with clinical data and chest radiography suggestive of pulmonary tuberculosis.
Sputum samples were collected, stained by ZN stain and cultured on LJ medium. Fifty
cases with positive smear and culture and twenty cases negative for both of them were
included in the study. Real-time PCR was done to detect TB-DNA in the seventy cases.
Results showed that real-time PCR has a sensitivity of 100%, a negative predicative
value of 100%, a specificity of 75%, and a positive predictive value of 91%. It showed
an accuracy of 92%. In conclusion, real-time PCR, with its rapidness, accuracy, and
ability to handle many samples, should replace the quantitative PCR methods now in
Key words: Mycobacterium tuberculosis, real-time PCR, sensitivity, specificity, internal
transcribed spacer.
Corresponding author: Dr. Sahar Zakaria Elazab, Lecturer of Microbiology and
Medical Immunology, Faculty of Medicine, Suez Canal University.
Tel: 01007163377
Tuberculosis (TB) remains the leading cause of death from a curable infectious
disease despite the availability of short-course therapy that can be both inexpensive and
effective (World Health Organization, 2003). Clinical management of cases in
developing countries is hampered by the lack of a simple and effective diagnostic test.
Correct diagnosis of TB is needed to improve treatment, reduce transmission, and
control development of drug resistance (Dye et al., 2005).
The diagnosis of mycobacterial infections remained practically unchanged for many
decades and probably would have not progressed at all without the unexpected
resurgence of TB which characterized the last twenty years of the 20th century (Tortoli
et al., 2007). Accurate case detection is the rate-limiting step in TB control. While as
many as two thirds of sputum smear-positive cases probably remain undetected
worldwide, the efforts to control the disease have focused more on curing TB cases than
on detecting them. Even though the laboratory is essential for the diagnosis and control
of TB, it does not receive enough attention in developing countries, where sputum
microscopy is often the only available method to diagnose TB (Dye, 2006).
Diagnostic tests devoted to the rapid, sensitive, and specific identification of the
causative agent are key elements for successful health programs aimed at disease control.
Moreover, the accurate determination of mycobacterial burden might be beneficial for
fast assessment of patient response to standard therapy, especially in those patients
suspected of harboring resistant M. tuberculosis strains. Traditional laboratory
techniques, such as direct microscopy observation and Mycobacterium culture on
semisolid or liquid media, are far from being sensitive and specific or adequate for a fast
M. tuberculosis identification. Moreover, the harsh decontaminating procedures
combined with the lack of homogeneity of the sputum and the tendency of Mycobacteria
to clump renders even quantitative culture systems unreliable (Broccolo et al., 2003).
Detection of M. tuberculosis-specific DNA sequences might represent a more
sensitive and fast diagnostic target; however, the successful use of DNA amplification
techniques is strongly dependent on the choice of the target sequence. Moreover, since
respiratory tract specimens are naturally contaminated by many different species of
commensal and pathogenic microorganisms, a high degree of specificity for M.
tuberculosis recognition is mandatory (Broccolo et al., 2003).
The aim of the study was to evaluate the real- time PCR with the internal transcribed
spacer (ITS) primers for direct detection and identification of M. tuberculosis in both
sputum and culture positive patients.
Subjects and methods:
Patients and specimens: The study was conducted on patients with clinical data and
chest radiography suggestive of pulmonary tuberculosis and who were admitted to
Ismailia Chest Hospital during the period from October 2009 to November 2010.
Sputum samples were collected from all the patients and stained by ZN stain. After
decontamination-concentration procedure which was done by the Petroff's method (Kent
and Kubica, 1985), sediment of each sputum sample was divided into three equal parts;
one was cultured immediately on LJ medium, the second part was stained by ZN stain,
and the third part was kept at -50°C until used in DNA extraction. After eight weeks,
colonies grown on LJ medium were identified and confirmed as M. tuberculosis by
niacin test and nitrate reduction test. According to the results of ZN stain and culture, the
study included only 70 patients (54 males and 16 females); 50 patients with positive
results for both ZN stain and culture and 20 patients with negative results for both ZN
stain and culture. Age of the patients ranged from 22 to 71 years old.
DNA extraction: M. tuberculosis DNA was extracted from sputum samples using RTP
Mycobacteria kit, Spin Protocol (Invitek Co., Germany) according to the instructions in
the manual provided by the manufacturer. Extracted DNA was stored at -20°C until real-
time PCR run.
Real-time PCR: M. tuberculosis DNA load was determined using PCR Fluorescence
Quantitative Diagnostic Kit (BIOER Technology Co., Ltd, Hangzhou, China). The kit
adopted one pair of primers and a particularly designed Taqman probe to amplify and
bind specifically to the internal transcribed spacer (ITS) region within the 16S rRNA
gene. The instrument used was Line-Gene K real-time PCR detection system. PCR
reagents and Taq polymerase were defrosted. References and controls in the kit were
turned to room temperature. All reagents were centrifuged for a few seconds before use.
Dosage per reaction was 34.6 µl PCR reagent, 0.4µl Taq polymerase, and 1 µl internal
control. After mixing, they were distributed into 0.2 ml PCR tubes as 36 µl per tube and
placed in the refrigerator at -20ºC. Nucleic acid samples, controls and references were
added as 4 µl in each PCR tube and centrifuged at 8,000 rpm for 10 sec. PCR reaction
protocol was 94ºC for 5 min, 94ºC for 15 seconds, 60ºC for 15 seconds, 72ºC for 40
seconds. The reaction was done for 40 cycles. F1 (FAM) and F2 (HEX) channels were
chosen when collecting fluorescent signals. Fluorescence detection was set at 72ºC. Gain
value was adjusted to make the F1 background between 15 and 25 while F2 background
was between 20 and 30.
Result analysis: The concentration of the four references was inputted. Standard curve
for the four reference strains was plotted and one positive control (PC) was used to
confirm the validity of the test. The base line (zero adjustment) was confirmed by getting
the fluorescent signals of F1 and F2. The noise limit was made just beyond the peak of
the amplification curve of normal negative control; then quantitative analysis was done.
Quantification of mycobacterial DNA in the samples was accomplished by measuring
their respective Ct values and using the standard curve to determine their copy numbers.
The instrument software performed the whole process of calculating the Ct values,
preparing a standard curve, and determining the copy numbers of the samples. When the
cycle threshold (Ct) value is zero, negative judgment was reported.
Quality Control: Coefficient of correlation of the standard curve -0.990. The negative
control is negative for DNA. The positive control TB-DNA was among 1 x 105 and 5
x107 copies/ml. Critical positive TB-DNA was among 1 x 103 and 9 x 104 copies/ml. The
cycle threshold (Ct) for the internal control was among 35 or less. If the Ct value was
more than 35, it could be convicted that PCR determination was inhibited and re-sample
dilution or re-determination was proposed.
Statistical analysis: Quantitative data were expressed as mean (X) and standard
deviation (SD), while qualitative data were expressed as number (No.) and percent (%).
The analysis was performed using chi-square X2 test and the P value was considered
significant at P < 0.05. Sensitivity, specificity and overall predictivity (accuracy) were
also calculated according to their specific equations.
The study showed that among the fifty TB smear and culture-positive patients; 39
patients (78%) were males and 11 patients (22%) were females. Their age ranged from
15-73 years old with mean age 43.98 years. Also, most (75%) of the TB smear and
culture-negative patients were males and 25% were females. Their mean age was 50.15
years old. There was no statistical significant difference between the two groups (Table
Table 1: Age and sex distribution among the studied patients:
+ve group
ve group
7 (14%)
3 (15%)
0.1 (NS)*
16 (32%)
4 (20%)
21 (42%)
6 (30%)
6 (12%)
7 (35%)
43.98 ± 12.9
50.15 ± 18.1
15 73
15 73
39 (78%)
15 (75%)
0.8 (NS)
11 (22%)
5 (25%)
*NS: Not Significant.
Quantitative real-time PCR technology was used to measure the bacterial load in all the
specimens and reference strains. Standard curve for the four reference strains was
plotted (figure 1) and one positive control (PC) was used to confirm the validity of the
test. Real- time amplification of the specimens was done and a curve was plotted; the
threshold cycle against the relative fluorescence (figure 2). TB-DNA with different
bacterial loads was demonstrated by difference in threshold cycle. The earlier the
threshold cycle the higher the bacterial load.
Figure 1: Standard curve for real-time quantification of TB-DNA using four
reference strains (R1, R2, R3 & R4) with known bacterial loads ranging from (1~ 5) x
107 down to (1~ 5) x 104 copies/ml.
Figure 2: Real-time PCR amplification curves of TB-DNA; each amplification plot
corresponds to a sample positive for TB-DNA. The last sample to the right of the
curve was considered negative where no fluorescence was demonstrated above the
base line up to cycle 40.
Internal control was included in the specimens to exclude PCR inhibition. Real-
time PCR amplification curves of the internal control of the previous specimens are
shown in figure 3. Fluorescence was demonstrated above the baseline for all the positive
samples and the negative one indicating validity of the test and absence of PCR
Table 2 shows that smears quantified as having few or numerous AFB (according
to WHO, 1998) are correlated with Ct values 31-39 and 26-35 cycles, respectively,
reflecting good detection by smear and the real-time PCR assay. A greater number of
smears with rare numbers of AFB were associated with later Ct cycles (36-39) or smaller
M. tuberculosis DNA (TB-DNA) concentrations which is expected. However, five
smear-negative specimens showed low Ct values (26-35) and high concentrations of TB-
Table 3 shows that real-time PCR was able to detect all smear and culture-
positive cases with sensitivity of 100% and negative predicative value of 100%.
However, the test gave positive results for 5 cases that showed negative culture with
specificity of 75% and positive predictive value of 91%. The real- time PCR test showed
accuracy of 92%. The predictive values of real-time PCR are shown in figure 4.
Accurate and early diagnosis of tuberculosis is a critical part of the
management and control of the disease. Diagnostic work up for tuberculosis
involves the detection of acid-fast bacilli in clinical samples by microscopy
(smear) and culture. These conventional tests are not always helpful in
making the diagnosis. Microscopy, although rapid and inexpensive, has
only modest sensitivity and specificity. Mycobacterial cultures, although
very specific, might be negative in 10%20% of cases, and the results are
often not available for weeks. In the context of these limitations, nucleic
acid amplification (NAA) tests have emerged with the intended goal of
enabling clinicians to make a rapid and accurate diagnosis. PCR is the best
known and most widely used NAA test (Pai, 2004). For active TB, the
development of nucleic acid amplification (NAA) tests has been hailed as
an important breakthrough in TB diagnosis.This study was conducted to
evaluate the accuracy of real-time PCR with the internal transcribed spacer
(ITS) primers for direct detection and identification of M. tuberculosis
The study revealed that most (78%) of the tuberculosis culture-
positive patients were males while the females were 22%. The age of the
majority of patients (42%) ranged from 45 to 60 years old with mean age
43.98 years. Also, most (75%) of the tuberculosis culture-negative patients
were males and 25% were females with most of them (35%) in the age
group 60 to 73 years old with the mean age 50.15 years old.
This pattern of sex and age agrees with the WHO (2011) which reported
that TB is more common among men than women, and affects mostly adults
in the economically productive age groups; around two-thirds of cases are
estimated to occur among people aged 1559 years. Also Borgdorff (2000)
reported that in most countries more cases of TB are among men than
women. This difference is partly due to the fact that women have less access
to diagnostic facilities in some settings, but the broader pattern also reflects
real epidemiological differences between men and women, both in exposure
to infection and in susceptibility to disease.
Accurate case detection is the rate-limiting step in TB control. Taylor
et al., (2001) stated that several protocols have been developed to detect M.
tuberculosis complex, the majority have been performed in cultures and
only a few protocols applied directly to clinical specimens. The molecular
methods for the diagnosis of tuberculosis (TB) directly with clinical
specimens, in use since the early 1990s, remain far from replacing
microscopy and culture. Their major limitation is poor sensitivity with
paucibacillary specimens such as microscopy-negative and extrapulmonary
samples (Sarmiento et al., 2003). Overall, the reported sensitivity of real-
time PCR in clinical specimens has ranged from 71.6% to 98.1%, thereby it
was not greatly different from classical NAA tests except in one study
where the sensitivity with real-time PCR was lower (71.4%) than with
conventional NAA (92.8%). But according to Van Coppenraet et al.
(2004) the main advantage of real-time PCR is its utility in quantitative
analysis which is not possible by the conventional PCR. Another advantage
is the rapidity of the test mainly due to fact that post PCR detection by
electrophoresis or hybridization can be omitted and enables the user to
monitor the amplification of PCR product simultaneously, in real-time and
on line. In addition, Broccolo et al., (2003) reported that real-time PCR
eliminated the precautions that must be taken with amplified products to
avoid contamination because the technique is performed in completely
sealed wells. This is a great improvement over the conventional PCR
assays, which have considerable risks of carryover contamination.
The present study showed that real-time PCR was able to detect all
positive cases with sensitivity of 100% and negative predicative value of
100%. No false negative cases were detected. This result was higher than
that of Kraus et al. (2001) who reported that the sensitivity of detection of
TB DNA using the real-time PCR assay was 85.5%. This difference in
results may be due to the fact that all our positive cases were positive for
both microscopy and culture which greatly increases the possibility of true
positive results with real-time PCR.
On the other hand, the real-time PCR in our study detected 5 positive
cases that were negative for both smear and culture with specificity of 75%
and positive predictive value of 91%. These results are lower than those of
Chang et al. (2008) who found that the specificity of real-time PCR was
88.5%. The low specificity of real-time PCR in our study can be due to the
low sensitivity of LJ medium (Worodria et al., 2011) and to the ability of
the PCR test to detect very low number and even dead bacteria in a sample
which can be present in a symptomatic individual (Bechnoosh et al., 1997).
The real-time PCR test showed accuracy of 92%.
Based on these findings, a positive PCR for a smear-positive
specimen would be indicative of real TB. A positive PCR, however, for a
smear-negative specimen would provide less clinical certainty for the
diagnosis of TB, and the results should be interpreted with caution and
always in parallel with clinical information. This emphasizes that Z.N.
staining of sputum samples is still the gold standard for diagnosis of TB.
In summary, this study showed that real-time PCR has the advantage of
accurate measurement of mycobacterial load by template quantification in
the clinical samples leading to precise diagnosis and also estimation of load
of infection. In spite that Z.N. staining is still the gold standard for diagnosis
of TB, PCR seems to be a fully controlled, fast, high throughput diagnostic
tool for the rapid identification of mycobacterial infection especially M.
In conclusion, real-time technology for the quantification of bacterial
DNA in clinical samples provides significant improvements in terms of
convenience and throughput over other quantitative PCR methods. So, with
its rapidness, accuracy, and ability to handle many samples, real-time PCR
should replace the other quantitative PCR methods now in use.
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Table 2: Real- time PCR Ct values compared to AFB smear quantified
Smear Result
20- 25
26- 30
31- 35
36- 39
> 40
Rare (+1)
1-9 AFB/100fields
Few (2+)
1-9 AFB/10 fields
Numerous (4+)
>9 AFB/field
Table 3: Predictive values of real- time PCR in comparison to ZN smear:
Real-time PCR
ZN smear
Figure 3: Real-time PCR amplification curves of the internal control of
the previous samples.
Figure 4: Predictive values of real-time PCR for detection of TB-DNA.
Sensetivity Specificity Positve
predictive value Negative
predictive value Accuracy
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