Evaluation of TaqMan Array Card (TAC) for the Detection of 28 Respiratory Pathogens

doi:10.21203/rs.2.9963/v1

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Evaluation of TaqMan Array Card (TAC) for the Detection of 28 Respiratory Pathogens

https://doi.org/10.21203/rs.2.9963/v1

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published 10 Nov, 2020

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Background: Respiratory infections are a serious threat to human health. So, rapid monitoring of all respiratory pathogens can facilitate prompt treatment and prevent the deterioration of respiratory disease. Previously published primers and probes of the TaqMan array card (TAC) for respiratory pathogens are not sensitive to Chinese clinical specimens. This study aimed to develop and improve the TAC assay to detect 28 respiratory viral and bacterial pathogens in a Chinese population. Methods: To improve the sensitivity, we redesigned the primers and probes, and labeled the probes with minor groove binders. The amplification efficiency, sensitivity, and specificity of the primers and probes were determined using target-gene containing standard plasmids. The detection performance of the TAC was evaluated on 736 clinical specimens and the results were compared with those from conventional methods. Results: The performance of the TAC assay was evaluated using 736 clinical throat swab samples and the results were compared with those from gold-standard methods. The sensitivity and specificity were 95.2% and 96.6%, respectively. The lowest detection limit of the TAC was 10 to 100 copies/μL. Conclusions: TAC is an efficient, accurate, and high-throughput approach to detecting multiple respiratory pathogens simultaneously and is a promising tool for the investigation and surveillance of pathogen outbreaks.

Infectious Diseases

Respiratory pathogen

TaqMan Array card

Real-time PCR

nucleic acid detection

Respiratory diseases, such as acute respiratory infections (ARIs) and community-acquired pneumonia (CAP), are a serious threat to human health (1-7). Infection with unexplained respiratory pathogens further aggravates the mortality worldwide (8, 9). Thus, rapid monitoring of all respiratory pathogens can facilitate prompt treatment and prevent the deterioration of respiratory disease (10). Infections of viruses, bacteria, and mycoplasmas, chlamydia, and rickettsia often present similar respiratory symptoms and thus may lead to antibiotics abuse when the pathogens were not properly identified (7, 11-13). Therefore, accurate identification of pathogens is essential for proper treatment of respiratory disease and avoidance of antibiotics abuse.

Viral and bacterial culture, serology, immunofluorescence staining, and conventional molecular diagnostics such as real-time PCR are common conventional approaches to detecting respiratory pathogens. These conventional detection methods have disadvantages; they have low sensitivity and are time-consuming, labor-intensive, expensive, and susceptible to contamination (1, 3, 14). Several molecular biological platforms for detecting multiple respiratory pathogens, such as fast-track diagnostics and other multiplex PCR detection systems have been developed (1, 3, 15, 16). However, these multiplex platforms sometimes lead to false results, and modification of primers and probes for one pathogen requires re-optimization of all the primers and probes on the platforms (1). The TaqMan array card (TAC) assay was developed to avoid amplicon contamination and to improve the detection efficiency for multiple pathogens (1, 17-19). The TAC is a customizable 384-well microfluidic real-time PCR system. Primers and probes that are specific to the targets are pre-allocated on the card. The TAC allows for simultaneous detection of up to 48 targets in one specimen, thus offering an easy means for multiple-pathogen detection (17, 18). Since the early model of TAC, which can detect 21 respiratory pathogen targets, was developed in early 2011 (1), several studies on the application of TAC to detect enteropathogens have been published and demonstrated its great effectivity to detect 19 enteropathogens (17, 20).

Although a number of articles have reported the use of the TAC for the detection of respiratory pathogens, comparison of its detection performance versus that of other diagnostic methods on large-scale clinical samples is still lacking (1, 15, 16, 18). Moreover, the TAC released in 2011 had low sensitivity to some clinical specimens (1). Further, the profile of prevalent respiratory pathogen strains in China may be different from the well-characterized profile that is used for the commercial TAC. Thus, the current study aimed to develop a broad-spectrum TAC to detect 28 prevalent respiratory pathogens in China and to compare the performance of the TAC assay with that of gold-standard methods including viral and bacterial culture, real-time PCR, and conventional PCR. We anticipate that this novel method can be applied in China for pathogen detection, especially in surveillance and outbreak backgrounds.

Strains

Bacterial and viral strains that had been isolated from clinical specimens were used to validate the TAC. Briefly, the following 20 viruses and 5 bacteria, and 3 other pathogens were collected from other laboratories: influenza type A virus, influenza type B virus, enterovirus, parainfluenza virus (subtypes 1 to 3), respiratory syncytial virus (subtypes A and B), human metapneumovirus (subtypes A and B), pan-adenovirus, rhinovirus, human bocavirus, human coronavirus (subtypes HCOV-229E, HCOV-NL63, HCOV-KU1, and HCOV-OC43), measles virus, mumps virus, rubella virus, Mycoplasma pneumoniae, Chlamydia pneumoniae, Coxiella burnetii, pan-Legionella, Haemophilus influenza, Mycobacterium tuberculosis, Streptococcus pneumonia, and Bordetella pertussis.

Clinical specimens

Clinical specimens were obtained from the Affiliated Hospital of the Academy of Military Medical Sciences and the Center for Disease Control and Prevention of Shunyi District in Beijing, China. The protocol for collecting and handling of clinical specimens had been approved by the institutional review boards of both institutes. In total, 736 clinical specimens were collected between July 2013 and May 2015 from patients presenting respiratory syndromes including fever, cough, and runny nose. Nasopharyngeal/oropharyngeal (NP/OP) swabs were kept in 1 mL of universal transport medium and stored at -80°C. Of the 736 specimens, 352 were positive for respiratory pathogens and 384 were negative.

Total nucleic acid extraction

Total nucleic acid was extracted from the clinical specimens (NP/OP swabs) and the bacterial and viral isolates using QIAamp cador Pathogen Mini Kit following the manufacturer’s instructions. Briefly, for nucleic acid extraction from all pathogens except M. tuberculosis, 200 μL of the medium containing NP/OP swabs was mixed with lysis buffer containing 20 μL proteinase K and 100 μL buffer VXL with 1 μg carrier RNA and incubated at 25°C for 15 min. Total nucleic acid from each sample was eluted in 80 μL buffer AVE. For nucleic acid extraction from M. tuberculosis, pretreatment with buffer ATL and pathogen Lysis L with glass beads was performed according to the manufacturer’s instruction. The extracted total nucleic acid was aliquoted and stored in -80°C for future use.

Plasmid construction

Standard plasmids were used to estimate the amplification efficiency and the limit of detection of the TAC assay. Plasmids containing 30 target genes, including 20 viral and 5 bacterial genes, 3 genes of others pathogens, and 2 internal positive controls were constructed and used as standard plasmids. The 28 target genes were synthesized and amplified by PCR. The amplified segments were inserted to the plasmid using the P-EASY-Blunt Zero Cloning Kit (Tran, Beijing, China). Recombinant plasmids were verified by sequencing. The RNA templates were first reverse-transcribed into cDNA, and then amplified and inserted into the plasmid of the cloning kit. The constructed plasmids were purified using the TIANprep Mini Plasmid Kit (Tran) according to the manufacturer’s instructions. The DNA concentration and quality of the purified recombinant plasmids was determined using a NanoDrop 2000 (Thermo Scientific, Waltham, MA). The number of copies per μL of each standard plasmid was calculated according to the equation: copies/es = (A × 10⁹/0.3956 × 6.6 × 10⁶) × 6.02 × 10²³.

Conventional detection methods

Gold-standard detection methods including viral and bacterial culture, real-time PCR, and conventional PCR were used in this study. Thus, for some respiratory pathogens, more than two detection methods were used. Moreover, in order to avoid contamination, all experiments involving conventional detection methods were performed at the Affiliated Hospital of the Academy of Military Medical Sciences and the Center for Disease Control and Prevention of Shunyi District in Beijing, China.

Primer and probe design for TAC and TAC reaction conditions

Primers and probes for 30 target genes (Fig. 1), designed using Primer Express 3.0 or adopted from published reports, were spotted onto the TAC. The primers and probes were designed to detect 28 respiratory pathogens, including a few subtypes, e.g., respiratory syncytial viruses (subtypes A and B), human metapneumovirus (subtypes A and B), parainfluenza virus (subtypes 1 to 3), and human coronavirus (subtypes HCOV-229E, HCOV-NL63, HCOV-KU1, and HCOV-OC43). Highly conserved regions were identified by multiple sequence alignment. To improve the specificity, we labeled probes with minor groove binders instead of black hole quenchers, which are commonly used in commercial TACs. The target genes and the resources of primers and probes are displayed in Table 1.

The final primer and probe concentrations on the plate were 900 nM and 250 nM, respectively. The quantitative One Step qRT-PCR Kit (Tiangen, Beijing, China) was used and each 100-µL reaction mixture contained 50 µL 2× Quant One Step Probe qRT-PCR master Mix, 4 µL HotMaster Taq polymerase, 2 µL QuantRTase, 20 µL DNA/RNA, and 24 µL RNase-free water. The thermal cycling conditions were: 50°C for 30 min, 92°C for 3 min, and 40 cycles of denaturation at 92°C for 10 s, annealing at 62°C for 20 s, and elongation at 68°C for 20 s. The PCR reactions were completed in a ViiA7 real-time PCR instrument (Life Technologies).

Assessment of the amplification efficiency and detection limit of the primers and probes

Linearity and amplification efficiency were assessed as described previously (1, 18). A 10-fold serial dilution of each target gene-containing standard plasmid (10⁷to 10³copies/µL) was prepared. Standard plasmids at two concentrations (high and low) were tested in triplicate to assess the intra- and interassay variability. The coefficient of variance (CV) was calculated based on cycle threshold (C_t) values. The lowest detection limit (LOD) was defined as the lowest detectable concentration of standard plasmids. When ≥ 5 out of 7 replicates of a standard plasmid at 10² copies/µL to 10⁰copies/µL were detected, the test was considered positive.

Evaluation of the TAC assay using clinical specimens

Out of the 736 clinical specimens, 352 tested positive and 384 negative in the gold-standard tests. All the negative samples were first processed on the ViiA7 to prevent contamination. RNase-free water was added to each card as a negative control template. A Ct cut-off value of 36 cycles was used to differentiate between positive and negative samples for all clinical specimens and the negative control on the TAC. The sensitivity and specificity of the TAC were evaluated by comparing the results from TAC assay with those from the gold-standard methods. The gold-standard methods were assumed to have 100% sensitivity and specificity. PCR products of 18 randomly chosen positive clinical specimens were sequenced to verify the accuracy of the TAC.

Statistical analysis

Repeatability (three replicates within one card) and reproducibility (three replicates between cards) of the TAC are shown as CV values. Cohen’s κ was calculated to estimate the degree of consistency between TAC and the gold-standard methods by SPSS 17.0 software. Cohen’s κ was interpreted as follows: < 0, poor; 0–0.20, slight; 0.21–0.40, fair; 0.41–0.60, moderate; 0.61–0.80, substantial; and 0.81–1.00, almost perfect agreement (20). P < 0.05 was regarded statistically significant.

Ethics statement

The study was approved by the Fifth Medical Centre, Chinese PLA General Hospital and the Center for Disease Control and Prevention of Shunyi District in Beijing, China. Written informed consent was obtained from each patient or a guardian.

Validation of the TAC

The TAC contained 48 pairs of primers and probes to detect 30 different target genes, including one replicate for influenza A, influenza B, parainfluenza virus1/2/3, human metapneumovirus A/B, human rhinovirus, human enterovirus, human pan-adenovirus, respiratory virus A/B, M. pneumoniae, C. pneumoniae, S. pneumoniae, and M. tuberculosis, and two internal controls. The primers and probes were designed to detect 28 respiratory pathogens, including 20 viruses (including different subtypes), 5 bacteria, and 3 other pathogens. These pathogens are well recognized to cause respiratory symptoms in China (6).

The linearity and amplification efficiency of the primers and probes for 25 pathogens and two internal controls were analyzed using the standard plasmids. The linear coefficient (r²) for the 30 targets was between 0.990 and 1. The amplification efficiency was 90% to 105% and detection limit ranged from 5 to 50 copies/µL for the 28 pathogen target genes and one internal positive control target gene (Table 2). The intra-assay variation was 0.5% to 3% and the interassay variation assessed using 3 TACs was 1.5% to 10%.

In preliminary experiments, good amplification efficiency of primers and probes based on the analysis of standard plasmids did not always represent good amplification on clinical specimens. Thus, we optimized the primer and probes including their sequences and the concentrations spotted on the array using both the standard plasmids and clinical specimens.

To analyze the specificity of the TAC, bacterial and viral isolates and positive clinical samples were detected on the panel (Table 3). All assays showed 100% specificity and no cross-reaction was observed.

TAC performance for clinical specimens

The 736 clinical specimens contained 352 pathogen positive and 384 negative samples. All the specimens were tested with the gold-standard methods including real-time PCR, PCR, and culturing. Most of the pathogens detected from the specimens were viruses. Compared with the results from the gold-standard methods, the diagnostic sensitivity of the TAC was 95.2% and the specificity was 96.6% (Table 4). Cohen’s κ indicated almost perfect agreement between the TAC assay and the gold-standard methods, except for human coronavirus (Table 5). Additionally, in 15.7% (52/345) of positive specimens, more than two pathogens were detected by the TAC assay (data not shown).

To assess the accuracy of the TAC assay, we randomly selected 18 specimens that were positive for pathogens according to the gold-standard tests and sequenced the corresponding amplified segments. The sequencing results showed that in 17 of the 18 specimens, the pathogen was accurately identified by the TAC assay (Table 6), with only one false negative result. Human coronavirus was not identified by the TAC in one specimen.

ARIs and CAP are caused by viral or bacterial infection (1, 2, 6, 12, 14). The TAC assay is a simple, sensitive, rapid, and high-throughput method to detect respiratory pathogens (1, 17, 18). The use of TAC to detect respiratory pathogens has been reported previously (1, 17, 18, 27). However, the detection performance of the TAC assay as compared with other methods remains unclear. Kodani et al. (1) and Geoffrey et al. (15) compared the performance of TAC assay with that of individual real-time PCR using identical primers and probes and found that TAC appeared less sensitive than the PCR with a sensitivity of 54–95% and a specificity of 98–99% for different clinical specimens. A recent report showed comparable performance of TAC assay and fast-track diagnostics for detection of 13 respiratory pathogens (16). To develop a TAC that suits the respiratory pathogen profile in China, we designed primers and probes to detect 28 pathogens known to commonly cause infections in China. The performance of the TAC assay was evaluated using 736 clinical throat swab samples and the results were compared with those from gold-standard methods.

The 30 primers and probes used in this study to detect 28 respiratory pathogens commonly occurring in China were either newly designed or modified from published sequences. We analyzed the linearity, amplification efficiency, and the LOD of the microfluid system, which all revealed near-ideal performance. In addition, because in a preliminary study, the amplification efficiency of the primers and probes as determined using the standard plasmids was not always an indicator of their effectiveness for target detection in clinical samples, we optimized the primers and probes using both standard plasmids and clinical specimens. The following reasons may contribute to the inconsistency in amplification efficiency between standard plasmids and clinical specimens: 1) some factors in clinical samples may interfere in the interaction between primers and templates; 2) some pathogens may have unknown subtypes, which may not be amplified by the primers and probes that are designed for the known subtypes; 3) the copy number of pathogens in clinical specimens may be extremely low.

Compared with the gold-standard methods, the TAC assay showed consistent results. The sensitivity and specificity of the TAC assay was 95.2% and 96.6%, respectively. The sensitivity was higher than that in the previous studies of Kodani et al. and Geoffrey et al. There are several possible reasons: 1) In the previous studies, clinical specimens had been stored over long periods, which might have led to sample disintegration. In our study, we used short-term-stored clinical specimens obtained from out- and in-patients from 2013 to 2015. 2) In the current study, the samples originated from Beijing, China, thus the epidemic pathogens might be different from those in other countries.

We used individual real-time PCR as the gold-standard method to verify negative results from the TAC assay in clinical specimens. Some clinical specimens showed an extremely low level of pathogen infection according to the TAC assay, and the Ct of those specimens was very close to the Ct cutoff value of 36 (1, 18). We considered these specimens as “suspicious positive specimens” when their Ct was between 36 and 38. Individual real-time PCR on these suspicious positive specimens using primers and probes identical to those of the TAC showed positive amplification of the target gene in all cases. These results suggest that the TAC is less sensitive than individual real-time PCR assays, as reported by Kodani et al. (1). This may be explained by the small reaction volume (1 μl), containing only 0.2 μl nucleic acid, used in the TAC assay, while 2 μl of clinical samples was added to a 25-μl reaction volume for individual real-time PCR. However, in real clinical practice, such low-level infection is not significant for diagnosis.

Conventional diagnostic methods for respiratory diseases, such as bacterial culture, agarose gel electrophoresis, and individual real-time PCR, are often associated with some disadvantages. For example, germiculture is usually time consuming, agarose gel electrophoresis may lead to inaccurate results, and individual real-time PCR is labor-intensive for the detection of multiple pathogens (1, 3). A standard diagnostic method for all 28 pathogens detected in this study is currently unavailable. As respiratory diseases can spread quickly (6) and may lead to serious pandemics, rapid identification of respiratory pathogens is critical for disease control. The TAC assay can identify multiple respiratory pathogens in two hours.

The current study was limited by the small number of positive clinical specimens for some of the tested infectious agents. Thus, validation of the primers and probes for those pathogens may appear challenging. We are currently collecting additional clinical specimens to further test the TAC. Nevertheless, our findings suggest that the TAC assay is a rapid, convenient, and high-throughput assay for simultaneous detection of multiple pathogens. Thus, the TAC may provide a promising method for efficient surveillance of outbreaks of respiratory pathogens in China.

TAC: TaqMan array card; CT: cycle threshold; NP/OP: Nasopharyngeal/oropharyngeal

Funding

This work was supported by the Chinese State Key Project Specialized for Infectious Diseases (2018ZX10711001-003) and the National Natural Science Foundation of China (81772144). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and materials

The datasets are available by request to the corresponding author.

Authors’ contributions

KKL and PL drafted the manuscript and designed the study with YQJ, SPC and PL. KKL, HBJ, YC and XZ performed laboratory work. HJ, DCK and YLZ analyzed the data. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Ethics statement

Consent for publication

Not applicable. The manuscript does not contain personal details.

Competing interests

The authors declare that they have no competing interests.

Author details

¹State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China; ²Department of Laboratory Medicine, Shunyi District Center for Disease Control and Prevention, Beijing, China; ³Department of Laboratory Medicine, the Fifth Medical Centre, Chinese PLA General Hospital, Beijing, China.

Acknowledgements

We thank Yan Li and Shuang Zhang for collecting and preparing clinical samples.

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Table 1 Primers and probes applied in this study

Pathogen	Target gene	Primer/probe sequence	Reference or Source
INF-A	M	F, AAGACCAATCCTGTCACCTCTGA	(2) (modified)
		R, AAGCGTCTACGCTGCAGTCC
		P, ACGCTCACCGTGCC
INF-B	HA	F, AAATACGGTGGATTAAACAAAAGCAA	(21) (modified)
		R, CCAGCAATAGCTCCGAAGAAA
		P, TGGGCAATTTCCTATGGC
PIV-1	HN	F, TGATTTAAACCCGGTAATTTCTCAT	(22)
		R, CCTTGTTCCTGCAGCTATTACAGA
		P, ACGACAACAGGAAATC
PIV-2	HN	F, AGGACTATGAAAACCATTTACCTAAGTGA	(22) (modified)
		R, AAGCAAGTCTCAGTTCAGCTAGATCA
		P, TGTTCAGTCACTGCTATAC
PIV-3	HN	F, AAAAGTTGATGAAAGATCAGATTATGCAT	(22) (modified)
		R, CCGGGACACCCAGTTGTG
		P, AAAGGCAAAATAATATTTCTC
HMPV-A	F	F, AGAGATGTAGGCACCACAACTGC	Beijing Genomics institution
		R, CTGATCCTAGAGCCGTGCAAA
		P, TTCATCATTGCAGCAAGA
HMPV-B	F	F, ACAATGGCAACTTTGCTTAAAGAA	Beijing Genomics institution
		R, GATTATAGGTGTGTCTGGTGCTGAA
		P, ATATTCCACAAAATCAGAGGC
HRV	5' UTR	F, TTCCAGCCTGCGTGGC	(1) (modified)
		R, GAAACACGGACACCCAAAGTAGTC
		P, CCCCTGAATGYGGC
HEV	5' UTR	F, GGTGYGAAGAGYCTATTGAGC	Beijing Genomics institution
		R, ACGGACACCCAAAGTAGTCG
		R, TCCGGCCCCTGAAT
HAdV	Hexon	F, CCCAGTGGTCTTACATGCACAT	(3) (modified)
		R, GCCACGGTGGGGTTTCTAA
		P, CCGGGTCTGGTGCAG
RSV-A	N	F, AGATCAACTTCTGTCATCCAGCAA	(21) (modified)
		R, TTCTGCACATCATAATTAGGAGTATCAAT
		P, CGGAGCACAGGAGAT
RSV-B	N	F, AAGATGCAAATCATAAATTCACAGGA	(23)
		R, TGATATCCAGCATCTTTAAGTATCTTTATAGTG
		P, CTGGACATAGCATATAAC
M. pneumoniae	P1	F, GCAGTTGCTGGCGCTAAGTT	Beijing Genomics institution
		R, AAGCGAGGTACGGTAGCGGTAT
		P, TGGTAGGGAACTCGTTTTA
C. pneumoniae	MOMP	F, CGTGGAGCCTTATGGGAATG	Beijing Genomics institution
		R, CGTCTGTTGGCAAGGGGA
		P, CAGTCCAAACCTAAAGTT
S. pneumoniae	lytA	F, ACGCAATCTAGCAGATGAAGCA	(1) (modified)
		R, TCGTGCGTTTTAATTCCAGCT
		P, AACGCTTGATACAGGGAG
M. tuberculosis	orfB	F, GGCTGTGGGTAGCAGACC	(24) (modified)
		R, CGGGTCCAGATGGCTTG
		P, ACCTGGGCAGGGTT
HBOV	NP1	F, AGAGGCTCGGGCTCATATCA	(25) (modified)
		R, CACTTGGTCTGAGGTCTTCGAA
		P, CAATCARCCACCTATCGTCT
Measles virus	P	F, GCAATTGGATCAACTGAAGGC	Beijing Genomics institution
		R, AGAGTCAGCATCTTGGATTCCCT
		P, ACAGCGGTGAAGCG
Rubella Virus	E1	F, ACGCCGCACGGACAACT	Beijing Genomics institution
		R, TGTTGGTTGCCGGTGTAATTC
		P, AGGTCCCGCCCGAC
Mumps virus	P	F, GCAATTGGATCAACTGAAGGC	Beijing Genomics institution
		R, AGAGTCAGCATCTTGGATTCCCT
		P, ACAGCGGTGAAGCG
Coxiella burnetii	ICD	F, AATTTGGAGCAAAGCCCTTAGA	Beijing Genomics institution
		R, GTAAAAAGGCGTCGGCAATAAC
		P, ACCCTGGCATGTCT
HCoV-229E	N	F, CAGTCAAATGGGCTGATGCA	(21) (modified)
		R, CAAAGGGCTATAAAGAGAATAAGGTATTCT
		P, AACGTGGTCGTCAGGG
HCoV-NL63	N	F, GCGTGTTCCTACCAGAGAGGAA	(21) (modified)
		R, GCTGTGGAAAACCTTTGGCA
		P, TGCTTTGGTCCTCGTGAT
HCoV-OC43	N	F, CGATGAGGCTATTCCGACTAGGT	(26) (modified)
		R, CCTTCCTGAGCCTTCAATATAGTAACC
		P, TGGCACGGTACTCC
HCoV-HKU1	N	F, AGGGATCCTACTAYTCAAGAAGCTATCC	(3) (modified)
		R, ATGAACGATTATTGGGTCCACG
		P, CGCCTGGTACGATTT
Pan-Legionella	5S-23S	F, GTACTAATTGGCTGATTGTCTTGACC	(1) (modified)
		R, CCTGGCGATGACCTACTTTCG
		P, ACTCTTTACCAAACCTG
H. influenzae	bexA	F, GGACAAACATCACAAGCGGTTA	(1) (modified)
		R, TGCGGTAGTGTTAGAAAATGGTATTATG
		P, TTGTAGTATTGATACGCTTTGT
B. pertussis target I	IS481a	F, CAAGGCCGAACGCTTCAT	(1) (modified)
		R, GAGTTCTGGTAGGTGTGAGCGTAA
		P, CCTTGCGTGAGTGGG
B. pertussis target II	PtxA	F, GCCGCCAGCTCGTACTTC	(1) (modified)
		R, GGATACGGCCGGCATTG
		P, CGTCGACACTTATGGCGA
IPCO			ABI
RNP	RPP30	F, AGATTTGGACCTGCGAGCG	WHO (modified)
		R, GAGCGGCTGTCTCCACAAGT
		P, CTGAAGGCTCTGCGC

Table 2 Validation of the TAC

Target	Linearity r² (amplification efficiency %)	Detection limit (copies/µL)
INF-A	0.998 (97.0)	10
INF-B	0.997 (99.0)	15
PIV-1	0.992 (99.2)	15
PIV-2	0.994 (97.3)	10
PIV-3	0.989 (95.6)	10
HMPV-A	0.998 (97.0)	10
HMPV-B	0.997 (93.7)	15
HRV	0.996 (95.0)	10
HEV	0.992 (103.6)	5
HAdV	0.995 (100.1)	10
RSV-A	0.998 (93.6)	10
RSV-B	0.999 (96.0)	10
M. pneumoniae	0.995 (97.3)	10
C. pneumoniae	0.998 (97.6)	50
S. pneumoniae	0.997 (94.7)	10
M.T	0.998 (93.5)	50
HBOV	0.995(104.5)	10
MV	0.999 (99.0)	5
RV	1.000 (94.8)	5
MPV	0.998(95.0)	15
CB	0.997(96.2)	50
HCOV-229E	0.996 (95.1)	10
HCOV-NL63	0.997 (96.2)	10
HCOV-OC43	0.993 (97.7)	10
HCOV-KU1	0.995 (93.7)	10
PL	0.997 (94.5)	10
HI	1.000 (100.1)	10
B. pertussis I	0.998 (97.6)	15
B. pertussis II	0.997 (98.1)	15
RNP	0.999 (99.6)	10

Table 3 TAC performance for clinical isolates

28 respiratory pathogens	Amount	Result
Influenza A virus	3	+
Influenza B virus	4	+
Parainfluenza virus 1	2	+
Parainfluenza virus 2	1	+
Parainfluenza virus 3	3	+
HMPV-A	4	+
HMPV-B	3	+
Rhinovirus	5	+
Enterovirus	4	+
Pan-adenovirus	6	+
RSV-A	4	+
RSV-B	2	+
M. pneumoniae	6	+
C. pneumoniae	1	+
S. pneumoniae	2	+
M. tuberculosis	3	+
Human Bocavirus	3	+
Measles virus	7	+
Rubella Virus	2	+
Mumps virus	1	+
C. burnetii	1	+
HCoV-229E	1	+
HCoV-NL63	1	+
HCoV-OC43	1	+
HCoV-KU1	1	+
Pan-Legionella	1	+
Haemophilus influenzae	1	+
Bordetella pertussis target I/II	2	+
Total	75	+

Table 4 Comparison of the results from TAC assay and those of the gold-standard methods

Pathogens	Established-method positive n = 352		Established-method negative n = 384
	TAC+	TAC-	TAC+	TAC-
INF-A	51	4	2	35
INF-B	30	1	0	20
PIV-1	3	0	0	15
PIV-2	1	0	0	20
PIV-3	22	0	0	16
HMPV	26	0	0	40
HRV	33	4	2	23
HEV	21	1	2	20
HADV	18	2	1	34
RSV	62	2	0	19
MPN	18	0	3	36
SP	10	0	0	10
MT	15	0	0	15
HBOV	23	2	1	23
MV	13	0	0	15
RV	2	0	0	10
HCOV	5	1	2	20
Total	335	17	13	371
	Sensitivity = 95.2%		Specificity = 96.6%

Table 5 Kappa values between TAC and gold-standard methods

Pathogen	Kappa value	P value
INF-A	0.866	＜0.05
INF-B	0.959	＜0.05
PIV-1	1.000	＜0.05
PIV-2	1.000	＜0.05
PIV-3	1.000	＜0.05
HMPV	1.000	＜0.05
HRV	0.801	＜0.05
HEV	0.864	＜0.05
HADV	0.881	＜0.05
RSV	0.934	＜0.05
MPN	0.883	＜0.05
SP	1.000	＜0.05
MT	1.000	＜0.05
HBOV	0.878	＜0.05
MV	1.000	＜0.05
RV	1.000	＜0.05
HCOV	0.700	＜0.05

Table 6 Confirmation of TAC results by PCR and sequencing the amplified segment

PCR	TAC	Sequencing	Accuracy of TAC
HRV	HEV	HEV	100%
HRV	HEV	HEV	100%
HRV	HEV	HEV	100%
HRV	HEV	HEV	100%
HRV	Negative	Negative	100%
HADV	Negative	Negative	100%
HADV	Negative	Negative	100%
HADV	Negative	Negative	100%
HCOV	INF-A	H3N2	100%
HCOV	INF-A	H3N3	100%
HCOV	Negative	Negative	100%
HCOV	Negative	Negative	100%
HCOV	HCOV-OC43	HCOV-OC43	100%
HCOV	HCOV-OC43	HCOV-OC43	100%
HCOV	HCOV-KU1	HCOV-KU1	100%
HCOV	Negative	HCOV-KU1	0

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published 10 Nov, 2020

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Editorial decision: Major revision
26 Nov, 2019
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Evaluation of TaqMan Array Card (TAC) for the Detection of 28 Respiratory Pathogens

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