A Multiplex assay based on capillary electrophoresis to detect Mycobacterium tuberculosis complex: development and clinical validation

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Unlike conventional molecular diagnostic methods that target only single gene, which may lead to misdiagnosis or missed diagnosis, this CE-based multiplex approach provides a comprehensive detection to reduce diagnostic errors. Specificity testing with 76 microorganisms representing common respiratory pathogens confirmed 100% analytical specificity with no cross-reactivity, while sensitivity analysis demonstrated detection limits ranging from 10 to 20 copies/mL for all three target genes. In a prospective clinical validation study of 1,067 patients suspected of pulmonary tuberculosis, the multiplex assay showed 77.4% sensitivity (CI 74.9%-79.9%), 99.6% specificity (CI 99.2%-100%), 96.0% positive predictive value (CI 94.8%-97.2%), and 97.1% negative predictive value (CI 96.1%-98.1%). Notably, the study identified 6 MTBC strains (4.8% of TB patients) with IS6110 deletions through whole-genome sequencing, which would result in false-negative results for any commercial PCR kits targeting IS6110 . This integrated multiplex approach enhances diagnostic accuracy by simultaneously targeting multiple genes, then it offers potential to reduce misdiagnosis and missed diagnosis of tuberculosis. In summary, the multiplex assay provides a more comprehensive alternative to current single-target molecular methods for MTBC detection. Multiplex assay Mycobacterium tuberculosis complex Capillary electrophoresis IS6110 rpoB HSP65 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Key points The Multiplex assay provides one-run results for IS6110 , rpoB and HSP65. The Multiplex assay is a more comprehensive method to detect MTBC. This approach can reduce misdiagnosis and missed diagnosis of TB. Introduction Tuberculosis (TB), which is caused by Mycobacterium tuberculosis complex (MTBC) infection, is still a global health epidemic, showing significant morbidity and mortality (WHO. 2024). Indirect evidence suggests that one in four people is infected with MTBC worldwide, and 5–10% of those develop TB (Houben RM et al. 2016). According to the World Health Organization (WHO), an alarming 10.8 million people were diagnosed with TB in 2023, and the number of TB-related deaths was about 1.25 million (WHO. 2024). This highlights the need to take urgent action for TB prevention. Rapid identification of MTBC is of paramount importance towards early diagnosis of TB, leading to effective infection control. For the advantages over conventional diagnostic methods like mycobacterial culture, which is time-consuming and acid-fast bacilli (AFB) smear with low sensitivity, nucleic acid amplification tests (NAATs) have been widely applied for rapid diagnosis of TB, among which the Xpert MTB/RIF assay, endorsed by the World Health Organization (WHO) in 2010, has been a significant advancement offering rapid detection of Mycobacterium tuberculosis and rifampicin resistance in less than two hours. These techniques are based on the amplification of unique mycobacterial target sequences. Several appropriate genes, such as 16SrRNA , IS6110 , IS1081, HSP65 , and rpoB , have been utilized for these molecular methods. However, most of the molecular assays that are currently in use only target one gene, which can lead to the misdiagnosis of tuberculosis (Comín J et al. 2022 ; Huang WC et al. 2022 ; Pang Y et al. 2017 ; Jin W et al. 2023 ; Chin K et al. 2020 ). Meanwhile, due to point mutations in primer binding regions, low bacterial load, sample inhibitors and assay limitations, false -negative results may occur, resulting in a missed diagnosis of tuberculosis (Phyu MH et al. 2018 ; Moradiya K et al. 2020 ). Capillary electrophoresis (CE) can separate charged macromolecules, such as DNA, which separates molecules based on their differential migration in an electric field. CE can separate DNA fragments of up to 1000 nucleotides with single-nucleotide resolution. It is a robust analytical technique with several potential advantages, such as short analysis time, low sample volume requirements (nanoliter or less), and high efficiency. For the most part, it has multianalyte capability which allows it to assay multiple targets simultaneously. Furthermore, with flexible applications of parallel operation, CE has the potential for high-throughput analysis. We therefore developed a CE-based multiplex molecular detection assay capable of detecting three MTBC genes: IS6110 , rpoB , and HSP65 . We then evaluated this method's analytical performance and conducted clinical validation. Materials and methods Primer design Three pairs of oligonucleotides were required to detect the target genes of MTBC. Briefly, they were designed as follows: first, gene sequences were retrieved from NCBI for the following mycobacterium: M. tuberculosis (ATCC 27294), M. marinum (ATCC 927), M. gordonae (ATCC 14470), M. scrofulaceum (ATCC 19981), M. terrae (ATCC 15755), M. fortuitum subsp. fortuitum (ATCC 6841), M. asiaticum (ATCC 25276). Second, comparative analysis was performed through sequence alignment using the Clustal Omega to obtain the conserved regions of the three target genes. Third, Primer Premier 5 software was used to design the primers according to the conserved regions. Then, the specificity of these forward primers was tested in silico using the BLAST tools from NCBI. To discriminate the three targets, these three forward primers were labelled with fluorophores, 6-FAM and TAMRA, respectively, at the 5’-end to be subsequently detectable by electrophoresis. Additionally, cross-reaction of these reverse primers should be avoided. DNA extraction The Chelex-100 method was modified for DNA extraction. Specifically, two loops of freshly grown mycobacterial cultures from L-J medium were added to 300 µl of water containing Chelex resin. To improve the efficiency of DNA extraction, 10ul proteinase K (10mg/ml) was added to the DNA extraction process, considering the high lipid content in the MTBC membrane. Incubate at 56°C for 20 minutes and then boil at 100°C for 5 minutes to release DNA. Following, the sample was centrifuged to pellet cellular debris and Chelex resin, and the supernatant was used as the DNA template. Then, DNA concentration and purity were determined by spectrophotometer (NanoDrop One, Thermo Scientific, USA). Polymerase chain reaction In brief, the PCR reaction was carried out in a 50 µL mixture each containing 1.0µL dNTP (10mmol/L) (Invitrogen, USA), 2.0 µL AmpliTaq Gold™ DNA polymerase (5U/µL) (ABI, USA), 5.0 µL PCR Buffer(without Mg 2+ ) (ABI, USA), 8.0 µL MgCl 2 (25mmol/L)(ABI, USA), 26.0 µL Amplification grade water (Promega, USA), 0.5 µL each primer and 5.0 µL DNA template. The reaction was performed using an automated thermal cycler (Verity, ABI, USA). The following PCR protocol was used: predenaturation of 94℃ for 5min, 35 cycles of 94℃ for 30s, 55℃ for 1min, and 72℃ for 1min, then a final extension step of 72℃ for 1min. Capillary electrophoresis The 3130 genetic analyzer (ABI, USA) was utilized. The procedures were briefly as follows: first, a 9.0 µL mixture of LIZ 500 (Promega, USA) and HiDi buffer (Promega, USA) in a 1:130 ratio was added to a 96-well plate. 1.0 µL multiplex PCR product was then pipetted into each well, followed by a pre-denaturation process with heating the plate to 99℃ for 3min. Then, capillary electrophoresis was performed according to the manufacturer’s instructions. Whole-genome and Sanger sequencing Genomic DNA from MTBC isolates with discordant or irregular molecular assay results was sent to Majorbio (Shanghai, China) for whole-genome sequencing. To increase the accuracy and integrity of genome assembly, we employed a dual-platform strategy using both next-generation sequencing (Illumina) for high-depth short-read data and third-generation sequencing (PacBio) for long-read data. The raw Illumina reads were first quality-checked using FastQC and then filtered and trimmed. For long-read data, quality control was performed using the SMRT Analysis suite. Assembly was conducted using hybrid assembly approaches with SOAPdenovo and unicycler, which allowed us to leverage the strengths of both sequencing technologies. The assembled genomes were annotated using Prokka, and sequence alignments were performed with BLAST. For phylogenetic analysis, a set of 31 housekeeping genes was extracted from the assemblies, and the evolutionary relationships were constructed using MEGA 6.0 via the Neighbor-Joining method. Analytical evaluation The analytical sensitivities of the Multiplex assay were evaluated by determining the limit of detection (LOD). The LOD was measured using spiked samples with ATCC 27294. Twenty replicates were evaluated at five concentrations around LOD, and the LOD was determined using probit analysis. Then, studies were performed to determine the analytical specificity. Seventy-six (76) microorganisms (Table 1 ), which represent common respiratory pathogens, were tested at the following concentrations: DNA at 1×10 7 copies/mL for bacteria and fungi; nucleic acid at 2×10 9 copies/mL for viruses; DNA at 1×10 5 copies/mL for nontuberculous mycobacteria; and a concentration of 10 6 elementary bodies (EB) per mL for Chlamydia. All specificity and sensitivity assays were tested in duplicate. Table 1 Microorganisms tested for analytical evaluation Microorganisms Origin Microorganisms Origin Mycobacterium gastri ATCC15754 Haemophilus influenzae Clinical isolates Mycobacterium terrae ATCC15755 Haemophilus parainfluenzae Clinical isolates Mycobacterium xenopi ATCC19250 Klebsiella oxytoca Clinical isolates Mycobacterium smegmatis ATCC19420 Klebsiella pnenmoniae Clinical isolates Mycobacterium ulcerans ATCC19423 Legionella pneumophila Clinical isolates Mycobacterium thermoresistibile ATCC19527 Micrococcus luteus Clinical isolates Mycobacterium abscessus ATCC19977 Morganella morganii Clinical isolates Mycobacterium scrofulaceum ATCC19981 Mycobacterium fortuitum Clinical isolates Mycobacterium simiae ATCC25275 Mycobacterium gordonae Clinical isolates Escherichia coli ATCC25922 Mycobacterium intracellulare Clinical isolates Staphylococcus aureus ATCC25923 Mycobacterium kansassi Clinical isolates Pseudomonas aeruginosa ATCC27853 Neisseria meningitidis Clinical isolates Mycobacterium haemophilum ATCC29548 Nocardia asteroides Clinical isolates Mycobacterium malmoense ATCC29571 Nocardia brasiliensis Clinical isolates Shigella flexneri ATCC29903 Nocardia farcinica Clinical isolates Mycobacterium chelonae ATCC35752 Proteus mirabilis Clinical isolates Mycobacterium szulgai ATCC35799 Proteus vulgaris Clinical isolates Mycobacterium celatum ATCC51131 Pseudomonas aeruginosa Clinical isolates Mycobacterium genavense ATCC51234 Pseudomonas fluorescens Clinical isolates Mycobacterium marinum ATCC927 Pseudomonas putida Clinical isolates Mycobacterium colombiense CIP108962 Serratia marcescens Clinical isolates Mycobacterium paraintracellulare JCM30622 Shigella boydii Clinical isolates Mycobacterium Massiliense CIP108297 Staphylococcus capitis Clinical isolates Mycobacterium bolletii DSM45149 Staphylococcus epidermidis Clinical isolates Mycobacterium avium Clinical isolates Staphylococcus haemolyticus Clinical isolates Acinetobacter baumannii Clinical isolates Staphylococcus saprophyticus Clinical isolates Acinetobacter calcoaceticus Clinical isolates Stenotrophomonas maltophilia Clinical isolates Acinetobacter haemolyticus Clinical isolates Streptococcus agalactiae Clinical isolates Acinetobacter junii Clinical isolates Streptococcus midis Clinical isolates Alcaligenes faecalis Clinical isolates Streptococcus salivarius Clinical isolates Branhamella catarhalis Clinical isolates Adenovirus NIFDC 370057 − 202001 Candida albicans Clinical isolates Coronavirus NIFDC 370057 − 202001 Citrobacter freundii Clinical isolates Human metapneumovirus NIFDC 370057 − 202001 Corynebacterium diphtheriae Clinical isolates Influenza B Virus NIFDC 370057 − 202001 Enterobacter aerogenes Clinical isolates Parainfluenza virus NIFDC 370057 − 202001 Enterobacter cloacae Clinical isolates Respiratory syncytial virus NIFDC 370057 − 202001 Enterococcus faecalis Clinical isolates Rhinovirus NIFDC 370057 − 202001 Enterococcus faecium Clinical isolates Rubella virus NIFDC 370057 − 202001 ATCC: American Type Culture Collection; CIP: Collection of Institut Pasteur, France; JCM: Japan Collection of Microorganisms; DSM: Deutsche Sammlung von Mikroorganismen und Zellkulturen, German; NIFDC: National Institutes for Food and Drug Control, China. Clinical performance A prospective cohort study was conducted to evaluate the performance characteristics of the Multiplex assay. Inclusion criteria: Subjects 18 years or older were eligible for study if they were suspected of pulmonary tuberculosis (based on symptoms such as persistent cough, fever, weight loss, night sweats, and/or abnormal chest radiography findings) in Fujian Provincial Hospital, China, and on no TB treatment or with less than three days of TB treatment. Exclusion criteria: insufficient sputum volume. Then, we estimated that a sample size of 1100 patients is needed to obtain a between-group difference with more than 99% power. Meanwhile, this is an adequate sample size for evaluating the sensitivity and specificity according to the CLSI guideline. Testing should continue until results from at least 50 positive specimens, as a minimum guideline, are obtained with both the test and comparative method. The Institutional Ethics Committee of Fujian Provincial Hospital approved the study. Sputum specimens collected from subjects were tested using AFB smear, culture and Xpert MTB/RIF. Also, a single leftover sputum sample was tested using the Multiplex assay. All the participants were at least independently diagnosed by two doctors based on clinical and laboratory findings. If the diagnosis is different, another doctor is required. Then, the sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) of the four methods were calculated, respectively. Discordant results for MTBC culture positive and molecular assay negative, irrespective of Xpert MTB/RIF or Multiplex assay, were further evaluated using bi-directional sequencing of the corresponding region of the genome. If needed, WGS was used for further validation. Data analysis Statistical analyses were performed using SPSS Statistics 24, including the sensitivity, specificity, NPV, and PPV of the four methods adopted in this study, and their corresponding 95% confidence interval (CI). Probit analysis was used to determine the LOD of the Multiplex assay. The LOD was defined as the lowest DNA concentration detected in 95% of 20 replicates for every target gene. Result CE based Multiplex assay Specific primers (Table 2 ) targeted IS6110 , rpoB , and HSP65 were designed based on their conserved region, respectively. Then, the specificity of these forward primers were was examined in silico. Compared with core nucleotide BLAST database, which consists of 108970392 sequences, the number of hits for forward primer targeted IS6110 is 101, 99 for MTBC, and 2 for Mycobacterium avium complex. For rpoB , the number of hits is 109, which includes 2 for Pontimonas sp. and 107 for MTBC. The number of hits for the forward primer targeted HSP65 is 101, which is all for MTBC. Moreover, the identity of all these hits above is 100%. The result of Mycobacterium tuberculosis H37Rv (ATCC 27294) using this Multiplex assay is in line with expectations (Fig. 1 ). After targeted DNA sequencing and alignment with reference sequence, the identity is 99.3% (269/271), 99.3% (268/270) and 98.8% (342/346) for IS6110 , rpoB and HSP65 , respectively (Fig. S1 ). Analytical evaluation Three target genes were all successfully detected by the Multiplex assay with an LOD ranging from 10 to 20 copies/ mL (Table 3 ). Irrespective of the type of microorganisms, genomic DNA extracts from 76 respiratory pathogens were not detected by the multiplex method. So, the analytical specificity of the Multiplex assay is 100% at the given concentration regarding bacteria, fungi, viruses, Chlamydia, and nontuberculous mycobacteria. Table 2 Oligonucleotides used for amplification by PCR Gene Oligonucleotide Sequence Fluorophores Size IS6110 IS6110 -F 5’-TACGGTGCCCGCAAAGTG-3’ 5'-TAMRA 271bp IS6110 -R 5’-AGGCGTCGGTGACAAAGG-3’ / rpoB rpoB -F 5'-CCAATTCATGGACCAGAACAA-3' 5'-6-FAM 270 bp rpoB -R 5'-TACACGATCTCGTCGCTAACC-3' / HSP65 HSP65 -F 5'-AGCGATTTCGGCGGGTGA-3' 5'-6-FAM 346 bp HSP65 -R 5'-TCTTGTTGACGACCAGGGTG-3' / Table 3 Detection limit of Multiplex assay for three target genes Gene Multiplex assay Limit of detection (copies/ mL) a Number of replicates Number detected % detected IS6110 10 20 20 100 rpoB 20 20 19 95 HSP65 20 20 20 100 a The limit of detection (LOD) was defined as the lowest DNA concentration that was detected in 95% of 20 replicates. Clinical performance A total of 1100 patients were enrolled between January 2023 and December 2023, excluding 33 patients due to insufficient sputum volume. The final enrollment of 1067 patients was performed by AFB smear, culture, Xpert MTB/RIF and the Multiplex assay. Figure 2 shows the classification of patients included in this study. In total, 124 patients were diagnosed with pulmonary tuberculosis. The overall positive rates of AFB smear, culture, Xpert MTB/RIF, and the Multiplex assay, not taking the diagnosis into account, were 4.9%, 11.8%, 10.0% and 9.4%, respectively (Table 4 ). However, for the TB patients, the positive rates were 25.8%, 75.0%, 79.8% and 77.4%, respectively. Comparisons of the four methods for the MTBC are given in Table 4 . In total, 93 patients tested positive for multiplex assay, all of which were culture-positive. However, 31 patients who were not finally diagnosed with TB were culture-positive, all of which were Multiplex assay negative. Conversely, other 4 non-TB patients, who were diagnosed as obsolete pulmonary tuberculosis, were Xpert MTB/RIF positive and Multiplex assay positive, none of which were culture negative. The overall sensitivity of AFB smear for all 1067 patients was 25.8% ( CI 23.2%-28.4%), specificity 97.7% ( CI 96.9%-98.7%), PPV 60.4% ( CI 57.4%-63.3%) and NPV 90.9% ( CI 89.2%-92.7%). The corresponding values for culture were 75.0% ( CI 72.4%-77.6%), 96.7% ( CI 95.5%-97.7%), 74.4% ( CI 71.8%-77.0%) and 96.7% ( CI 95.6%-97.8%). Meanwhile, the Multiplex assay showed 77.4% ( CI 74.9%-79.9%) sensitivity, 99.6% ( CI 99.2%-100%) specificity, 96.0% ( CI 94.8%-97.2%) PPV and 97.1% ( CI 96.1%-98.1%) NPV. Identification of IS6110-like element in MTBC Among the 93 patients who were culture, Xpert MTB/RIF and Multiplex assay triple positive, we could not detect IS6110 element in 6 TB patients using the Multiplex assay (Fig. 3 ). Due to the possibility of misdiagnosis, a more careful analysis of the 6 isolates was carried out using WGS. The evolutionary relationship of the 6 isolates, based on dnaG, frr, infC, nusA, pgk, pyrG, rplA, rplB,rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, rpoB , rpsB, rpsC,rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB and tsf 31 housekeeping gene, is displayed in Fig. 4 (take A1 isolate as an example). Phylogenetic analysis revealed that the 6 isolates most likely belonged to Mycobacterium tuberculosis . Furthermore, the whole genomes were obtained after genome assembly (Fig. 5 A). As expected, we can’t find the oligonucleotide sequence designed for IS6110 in these genomes. Neither did the reverse complementary sequence. Since IS6110 was multicopy and belonged to mobile genetic elements, we attempted to position one deletion of these genomes. Then, sequence alignment with Mycobacterium tuberculosis H37Rv reference sequence (Accession ID:NC_000962) was carried out using BLAST tools. Finally, we positioned one deletion at location:1463537 (Fig. 5 B,C). In comparison with reference sequence, we find an approximate 1500bp deletion did exist in the IS6110 corresponding region. Table 4 Performance of different methods to diagnose TB in the cohort Detection Methods Test Results Rate Diagnosis Sensitivity Specificity PPV NPV TB Non-TB CI CI CI CI AFB smear Positive 4.9% 32(25.8%) 21(2.2%) 25.8% 97.7% 60.4% 90.9% Negative 95.1% 92(74.2%) 922(97.7%) 23.2%-28.4% 96.9%-98.7% 57.4%-63.3% 89.2%-92.7% Culture Positive 11.8% 93(75.0%) 32(3.3%) 75.0% 96.7% 74.4% 96.7% Negative 88.2% 31(25.0%) 911(96.7%) 72.4%-77.6% 95.5%-97.7% 71.8%-77.0% 95.6%-97.8% Xpert MTB/RIF Positive 10.0% 99(79.8%) 8(0.8%) 79.8% 99.2% 92.5% 97.4% Negative 90.0% 25(20.2%) 935(99.2%) 77.4%-82.3% 98.6%-99.7% 91.0%-94.1% 96.4%-98.4% Multiplex assay Positive 9.4% 96(77.4%) 4(0.4%) 77.4% 99.6% 96.0% 97.1% Negative 90.6% 28(22.6%) 939(99.6%) 74.9%-79.9% 99.2%-100% 94.8%-97.2% 96.1%-98.1% PPV, Positive Predictive Value. NPV, Negative Predictive Value. CI, 95% upper and lower confidence interval. Discussion About a quarter of the population is globally estimated to have been infected with MTBC (Cohen A et al. 2019). Rapid and accurate detection of MTBC is of great significance in controlling the TB spread, devastating infectious disease (Naidoo K et al. 2022). Nowadays, various commercially available NAATs kits are adopted in clinical laboratories worldwide (Mousavi-Sagharchi SMA et al. 2024 ). Also various novel NAATs methods are developed for MTBC detection (Wang WH et al. 2024 ; Batuer M et al. 2024 ; Svensson E et al. 2021 ; Yee EH et al. 2020; Huang Z et al. 2022 ; Homann AR et al. 2021 ; Shan H et al. 2022 ). However, most of these molecular kits only target one gene. This can lead to the misdiagnosis and missed diagnosis of TB. Misdiagnosis of TB can bring about substantial negative consequences (Houben RMGJ et al. 2019 ). Firstly, a treatment course that lasts at least 6 months will be falsely recommended. Also, patients will incur substantial costs for clinical services and nonclinical expenses, like transportation, food, childcare, and lost wages (Laurence YV et al. 2015 ). Meanwhile, missed diagnosis of TB can result in the delay of treatment for patients, then do harm to TB prevention (Medrano BA et al. 2014 ). Here, we propose a novel, rapid and multi-target method that can detect three genes of MTBC simultaneously, aiming to provide a more comprehensive method for MTBC to reduce the misdiagnosis and missed diagnosis of TB. This is the first study that developed a multiplex assay to detect MTBC based on the CE platform. To ensure the specificity of this method, a two-step strategy was employed to design PCR primers. First, the conserved regions of the MTBC were identified through sequence alignment with several common NTM. Then, the BLAST tools from NCBI were utilized to test the specificity of these primers, which were designed based on the conserved regions. Specifically, compared with the core nucleotide BLAST database, it showed probable cross-reactivity with Pontimonas sp. for rpoB and Mycobacterium avium complex for IS6110 , proving no cross-reaction occurred by follow-up experiments. Also, here we report the performance of this method in a cohort, with 1067 patients finally enrolled, compared with AFB smear, culture, and Xpert MTB/RIF. Multiplex assay exhibited a sensitivity of 77.4% vs. 25.8% of AFB smear, 75.0% of culture, and 79.8% of Xpert MTB/RIF. The increment in sensitivity of the Multiplex assay over AFB smear was significant, whereas the increment in sensitivity of the Multiplex assay over culture was marginal. Also, we observed a low increment in specificity and NPV of Multiplex assay over AFB smear, culture, and Xpert MTB/RIF (specificity 99.6% vs. 97.7%, 96.7% and 99.2%, respectively, NPV 97.1% vs. 90.9%, 96.7%, and 97.4%, respectively). However, regarding PPV, the corresponding value of the Multiplex assay was 96.0% vs. 60.4%, 74.4% and 92.5% for AFB smear, culture, and Xpert MTB/RIF, respectively. Xpert MTB/RIF is acknowledged to be an excellent method to detect MTBC (WHO. 2020). In this context, it is worth noting that, with more target genes to be detected simultaneously, the Multiplex assay performed at least as well as Xpert MTB/RIF. During the clinical evaluation of the Multiplex assay, we discovered 6 strains of MTBC with suspected IS6110 deletion. First, we adopted Sanger sequencing for IS6110 , rpoB , and HSP65 , three genes, to identify these strains. Regarding rpoB and HSP65 , the results were in line with reference sequence of Mycobacterium tuberculosis (data not shown). Nevertheless, we could only obtain the IS6110 sequence result if we designed these primers. Then, the whole genomes were obtained using WGS based on the Illumina and Pacbio platforms. According to the phylogenetic analysis based on 31 housekeeping genes, these 6 strains belonged to Mycobacterium tuberculosis . Moreover, after the genome assembly, an approximate 1500bp deletion did exist in the IS6110 corresponding region. Owing to this finding, we could also recognize that the long gap was why we failed to get the results by Sanger sequencing. Certainly, in this regard, it would lead to false negative result for any commercial PCR kits targeted at IS6110 . Although we just discovered 6 IS6110 deletion strains (4.8%, 6/124) in our study, it was reported that the corresponding frequency was about 8% and 11% in Viet Nam and India, respectively (Chauhan DS et al. 2007 ). This indicates the necessity of the Multiplex assay we developed here to reduce the missed diagnosis of TB. The study has limitations. First, clinical validation of this Multiplex assay was performed on just one site, which may lead to bias. Second, considering sputum volume, we select Xpert MTB/RIF targeted rpoB as a comparison in the cohort, endorsed by WHO (WHO. 2020).. So, in this regard, another two molecular assays, targeted IS6110 and HSP65 , respectively, were needed. Third, although 76 microorganisms, which represent common respiratory pathogens, were selected for analytical specificity, we did not take Pontimonas sp., which showed 100% identity aligned with the oligonucleotide designed for rpoB , into evaluation, since the corresponding strain was not available in our library. In conclusion, the Multiplex assay simultaneously provides one-run results for IS6110 , rpoB and HSP65 , maintaining adequate sensitivity, specificity, PPV, and NPV for TB diagnosis. We present a more comprehensive method to detect MTBC. Although this is only a small fraction of the overall endeavor for accurate diagnosis, the Multiplex assay has the potential to reduce misdiagnosis and missed diagnosis of TB. To achieve the global end TB goals, the Multiplex assay, a comprehensive alternative to methods currently used, deserves further field evaluation. Declarations Transparency declaration The authors declare that they have no conflicts of interest. Ethical Approval The study was approved by the Institutional Ethics Committee of Fujian Provincial Hospital. Funding This work was supported by the Startup Fund for scientific research, Fujian Medical University, China (Grant No. 2020QH1167), and the Natural Science Foundation of Fujian Province, China (Grant No. 2023J011175). Author Contribution YC W and Z L conceived and designed research. Z L and YP L conducted clinical validation and sample collection. YC W and L L conducted analytical validation and testing. YC W and Z L analyzed data and performed phylogenetic analysis. YC W and Z L conducted statistical analysis. YC W and Z L wrote the manuscript. L L and Y H reviewed and edited the manuscript. L L and Y H supervised the project. All authors have reviewed and approved the manuscript. Acknowledgements The authors would like to thank the staff and technicians in the Division of Microbiology, Department of Clinical Laboratory, Fujian Provincial Hospital, for their assistance in collecting valuable microbiologic samples and isolates. Availability of data and materials Not applicable. References Batuer, M, Yuan, Y, Yu, M, Meng, C (2024). Establishment and evaluation of a new fluorescent probe method based on loop-mediated isothermal amplification for the detection of Mycobacterium tuberculosis complex. LUMINESCENCE, 39 (6), e4795. https://doi.org/10.1002/bio.4795 Chauhan, DS, Sharma, VD, Parashar, D, Chauhan, A, Singh, D, Singh, HB, Das, R, Aggarwal, BM, Malhotra, B, Jain, A, Sharma, M, Kataria, VK, Aggarwal, JK, Hanif, M, Shahani, A, Katoch, VM (2007) Molecular typing of Mycobacterium tuberculosis isolates from different parts of India based on IS6110 element polymorphism using RFLP analysis. 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INFECT DIS THER, 11 (2), 871-885. https://doi.org/10.1007/s40121-022-00610-2 Huang, Z, LaCourse, SM, Kay, AW, Stern, J, Escudero, JN, Youngquist, BM, Zheng, W, Vambe, D, Dlamini, M, Mtetwa, G, Cranmer, LM, Njuguna, I, Wamalwa, DC, Maleche-Obimbo, E, Catanzaro, DG, Lyon, CJ, John-Stewart, G, DiNardo, A, Mandalakas, AM, Ning, B, Hu, TY (2022) CRISPR detection of circulating cell-free Mycobacterium tuberculosis DNA in adults and children, including children with HIV: a molecular diagnostics study. Lancet Microbe, 3 (7), e482-e492. https://doi.org/10.1016/S2666-5247(22)00087-8 Jin, W, Wang, J, Yang, X (2023) Analysis of three cases with false positive PCR results of non tuberculosis mycobacterium. Respir Med Case Rep, 47 101973. https://doi.org/10.1016/j.rmcr.2023.101973 Laurence, YV, Griffiths, UK, Vassall, A (2015) Costs to Health Services and the Patient of Treating Tuberculosis: A Systematic Literature Review. PHARMACOECONOMICS, 33 (9), 939-55. https://doi.org/10.1007/s40273-015-0279-6 Medrano, BA, Salinas, G, Sanchez, C, Miramontes, R, Restrepo, BI, Haddad, MB, Lambert, LA (2014) A missed tuberculosis diagnosis resulting in hospital transmission. INFECT CONT HOSP EP, 35 (5), 534-7. https://doi.org/10.1086/675833 Moradiya, K, Muley, A, Kumar, S, Patel, K, Mahida, H (2020) Cartridge based nucleic acid amplification test negative in highly suspected case of tuberculosis: a case report Int J Res Med Sci, 8 (3), 1130. https://doi.org/10.18203/2320-6012.ijrms20200502 Mousavi-Sagharchi, SMA, Afrazeh, E, Seyyedian-Nikjeh, SF, Meskini, M, Doroud, D, Siadat, SD (2024) New insight in molecular detection of Mycobacterium tuberculosis. AMB Express, 14 (1), 74. https://doi.org/10.1186/s13568-024-01730-3 Naidoo, K, Dookie, N (2022) Can the GeneXpert MTB/XDR deliver on the promise of expanded, near-patient tuberculosis drug-susceptibility testing? LANCET INFECT DIS, 22 (4), e121-e127. https://doi.org/10.1016/S1473-3099(21)00613-7 Pang, Y, Lu, J, Su, B, Zheng, H, Zhao, Y (2017) Misdiagnosis of tuberculosis associated with some species of nontuberculous mycobacteria by GeneXpert MTB/RIF assay. INFECTION, 45 (5), 677-681. https://doi.org/10.1007/s15010-017-1044-x Phyu, MH, Kyaw, KWY, Myint, Z, Thida, A, Satyanarayana, S, Aung, ST (2018) Sputum smear-positive, Xpert® MTB/RIF-negative results: magnitude and treatment outcomes of patients in Myanmar. Public Health Action, 8 (4), 181-186. https://doi.org/10.5588/pha.18.0056 Shan, H, Wang, Y, Wu, T, Ying, B, Xu, G (2022) Development of asymmetric hairpins-mediated nucleic acid isothermal amplification-based lateral flow detection of Mycobacterium tuberculosis Sens Actuators B Chem, 350 130836. https://doi.org/10.1016/j.snb.2021.130836 Svensson, E., Folkvardsen, DB., Rasmussen, EM., Lillebaek, T, (2021). Detection of Mycobacterium tuberculosis complex in pulmonary and extrapulmonary samples with the FluoroType MTBDR assay. CLIN MICROBIOL INFEC, 27 (10), 1514.e1-1514.e4. https://doi.org/10.1016/j.cmi.2020.12.020 Wang, WH, Lin, CY, Jain, SH, Lu, PL, Chen, YH (2024) Development of the novel gene chip and restriction fragment length polymorphism (RFLP) methods for rapid detection of Mycobacterium tuberculosis complex in broth culture. J Microbiol Immunol Infect, 58 (1), 56-61. https://doi.org/10.1016/j.jmii.2024.09.003 World Health Organization (2020) WHO consolidated guidelines on tuberculosis: Module 3: diagnosis–rapid diagnostics for tuberculosis detection. World Health Organization, Geneva World Health Organization (2024) Global tuberculosis report, 2024. World Health Organization, Geneva. Licence: CC BY-NC-SA 3.0 IGO. Yee, EH, Sikes, HD (2020) Polymerization-Based Amplification for Target-Specific Colorimetric Detection of Amplified Mycobacterium tuberculosis DNA on Cellulose. ACS Sens, 5 (2), 308-312. https://doi.org/10.1021/acssensors.9b02424 Additional Declarations No competing interests reported. Supplementary Files supplementaryfigure.docx Cite Share Download PDF Status: Published Journal Publication published 02 Feb, 2026 Read the published version in Applied Microbiology and Biotechnology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6746494","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476942338,"identity":"331d27be-0b4e-4ef1-992c-a131d957f041","order_by":0,"name":"Yaocheng Wang","email":"","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yaocheng","middleName":"","lastName":"Wang","suffix":""},{"id":476942339,"identity":"da358915-31cc-4f41-a6c9-506e80188c4f","order_by":1,"name":"Zhen Li","email":"","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Li","suffix":""},{"id":476942340,"identity":"1a0c8541-7b0b-4ff7-8410-3ba80a25df73","order_by":2,"name":"Li Lai","email":"","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Lai","suffix":""},{"id":476942341,"identity":"8c744e41-9dee-4521-ab5a-58ecae7480f3","order_by":3,"name":"Yiping Liu","email":"","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yiping","middleName":"","lastName":"Liu","suffix":""},{"id":476942342,"identity":"93ff7c35-9ee6-4076-9de4-000bf2ec86b4","order_by":4,"name":"Li Li","email":"","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Li","suffix":""},{"id":476942343,"identity":"f6dc57e3-b3de-436c-a4bd-e6a69aee47b8","order_by":5,"name":"Yi Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACAwbGxgeJ/yTk2NibDxCtpdngA5uNMR/PsQRitTCwSc5gS0ucJ5GjQJwWc4nkZmMensPpbQw5DAw/KrYR1mI5I7HxMY/E4dw2hrMHGHvO3CbCYTcSgbYYALUw9iUwM7YRp6VNmifhcDobM48B8VokZxxIS2BjI1rLmYfNBh8bbAzbeNgSDhLnl+PpDx8kNkjIy89/fPDBjwoitDAIJCDYB4hQDwT8RKobBaNgFIyCEQwA+/E+ifyI0UoAAAAASUVORK5CYII=","orcid":"","institution":"Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yi","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-05-26 02:58:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6746494/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6746494/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00253-025-13701-0","type":"published","date":"2026-02-02T15:57:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85822220,"identity":"461b26cc-e0f6-4784-ba60-28ed54689252","added_by":"auto","created_at":"2025-07-02 06:45:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37687,"visible":true,"origin":"","legend":"\u003cp\u003eThe result of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e H37Rv (ATCC 27294) using Multiplex assay.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/f80f99026054aab552d2ac81.png"},{"id":85822225,"identity":"34e1e068-3ca6-4830-a4cc-b0564d4dc8f4","added_by":"auto","created_at":"2025-07-02 06:45:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34690,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of patients included in this study.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/1382c4495d01c0d5873348d4.png"},{"id":85822222,"identity":"b72a4289-c430-4d81-be81-c3a8e2002793","added_by":"auto","created_at":"2025-07-02 06:45:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35582,"visible":true,"origin":"","legend":"\u003cp\u003eExample of the result of TB patients(\u003cem\u003eIS6110\u003c/em\u003e deletion) using Multiplex assay.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/bf33831f2fd665b9fb2ec62b.png"},{"id":85822224,"identity":"667bd5bd-c180-48a1-a313-501126cd48d0","added_by":"auto","created_at":"2025-07-02 06:45:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":85900,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of A1 isolate. The phylogenetic analysis was conducted based on \u003cem\u003ednaG, frr, infC, nusA, pgk, pyrG, rplA, rplB,rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, rpoB, rpsB, rpsC,rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB \u003c/em\u003eand\u003cem\u003e tsf\u003c/em\u003e 31 housekeeping gene, using MEGA 6.0 by Neighbor-Joining method.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/d12a2bfd418468c2641d0abc.png"},{"id":85822226,"identity":"bffbd6f8-8afe-4159-8e00-a345214dc335","added_by":"auto","created_at":"2025-07-02 06:45:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1988512,"visible":true,"origin":"","legend":"\u003cp\u003eThe location of \u003cem\u003eIS6110\u003c/em\u003e deletion. (A) Circos plot of the genome of A1 strain. (B) Alignment of sequence in the location of \u003cem\u003eIS6110\u003c/em\u003e deletion with \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e H37Rv reference sequence. (C) Dot plot of the alignment.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/7f3e6800db29f56108b83053.png"},{"id":102234005,"identity":"0f0d1ac8-ffe6-431f-a584-00347d781dc8","added_by":"auto","created_at":"2026-02-09 16:03:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2906250,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/b74f06d3-7779-4df8-93df-deec840f89fb.pdf"},{"id":85822219,"identity":"4a3ccc76-0547-4273-8ad1-1d86e7e26071","added_by":"auto","created_at":"2025-07-02 06:45:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":66243,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-6746494/v1/6d25f684300053158f0f9e51.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multiplex assay based on capillary electrophoresis to detect Mycobacterium tuberculosis complex: development and clinical validation","fulltext":[{"header":"Key points","content":"\u003cul start=\"50\"\u003e\n \u003cli\u003eThe Multiplex assay provides one-run results for \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e and \u003cem\u003eHSP65.\u0026nbsp;\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003eThe Multiplex assay is a more comprehensive method to detect MTBC.\u003c/li\u003e\n \u003cli\u003eThis approach can reduce misdiagnosis and missed diagnosis of TB.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eTuberculosis (TB), which is caused by \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC) infection, is still a global health epidemic, showing significant morbidity and mortality (WHO. 2024). Indirect evidence suggests that one in four people is infected with MTBC worldwide, and 5\u0026ndash;10% of those develop TB (Houben RM et al. 2016). According to the World Health Organization (WHO), an alarming 10.8\u0026nbsp;million people were diagnosed with TB in 2023, and the number of TB-related deaths was about 1.25\u0026nbsp;million (WHO. 2024). This highlights the need to take urgent action for TB prevention. Rapid identification of MTBC is of paramount importance towards early diagnosis of TB, leading to effective infection control.\u003c/p\u003e \u003cp\u003eFor the advantages over conventional diagnostic methods like mycobacterial culture, which is time-consuming and acid-fast bacilli (AFB) smear with low sensitivity, nucleic acid amplification tests (NAATs) have been widely applied for rapid diagnosis of TB, among which the Xpert MTB/RIF assay, endorsed by the World Health Organization (WHO) in 2010, has been a significant advancement offering rapid detection of Mycobacterium tuberculosis and rifampicin resistance in less than two hours. These techniques are based on the amplification of unique mycobacterial target sequences. Several appropriate genes, such as \u003cem\u003e16SrRNA\u003c/em\u003e, \u003cem\u003eIS6110\u003c/em\u003e, IS1081, \u003cem\u003eHSP65\u003c/em\u003e, and \u003cem\u003erpoB\u003c/em\u003e, have been utilized for these molecular methods. However, most of the molecular assays that are currently in use only target one gene, which can lead to the misdiagnosis of tuberculosis (Com\u0026iacute;n J et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Huang WC et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pang Y et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jin W et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chin K et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Meanwhile, due to point mutations in primer binding regions, low bacterial load, sample inhibitors and assay limitations, false -negative results may occur, resulting in a missed diagnosis of tuberculosis (Phyu MH et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Moradiya K et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCapillary electrophoresis (CE) can separate charged macromolecules, such as DNA, which separates molecules based on their differential migration in an electric field. CE can separate DNA fragments of up to 1000 nucleotides with single-nucleotide resolution. It is a robust analytical technique with several potential advantages, such as short analysis time, low sample volume requirements (nanoliter or less), and high efficiency. For the most part, it has multianalyte capability which allows it to assay multiple targets simultaneously. Furthermore, with flexible applications of parallel operation, CE has the potential for high-throughput analysis.\u003c/p\u003e \u003cp\u003eWe therefore developed a CE-based multiplex molecular detection assay capable of detecting three MTBC genes: \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, and \u003cem\u003eHSP65\u003c/em\u003e. We then evaluated this method's analytical performance and conducted clinical validation.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePrimer design\u003c/h2\u003e \u003cp\u003eThree pairs of oligonucleotides were required to detect the target genes of MTBC. Briefly, they were designed as follows: first, gene sequences were retrieved from NCBI for the following mycobacterium: \u003cem\u003eM. tuberculosis\u003c/em\u003e (ATCC 27294), \u003cem\u003eM. marinum\u003c/em\u003e (ATCC 927), \u003cem\u003eM. gordonae\u003c/em\u003e (ATCC 14470), \u003cem\u003eM. scrofulaceum\u003c/em\u003e (ATCC 19981), \u003cem\u003eM. terrae\u003c/em\u003e (ATCC 15755), \u003cem\u003eM. fortuitum subsp. fortuitum\u003c/em\u003e (ATCC 6841), \u003cem\u003eM. asiaticum\u003c/em\u003e (ATCC 25276). Second, comparative analysis was performed through sequence alignment using the Clustal Omega to obtain the conserved regions of the three target genes. Third, Primer Premier 5 software was used to design the primers according to the conserved regions. Then, the specificity of these forward primers was tested in silico using the BLAST tools from NCBI. To discriminate the three targets, these three forward primers were labelled with fluorophores, 6-FAM and TAMRA, respectively, at the 5’-end to be subsequently detectable by electrophoresis. Additionally, cross-reaction of these reverse primers should be avoided.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eThe Chelex-100 method was modified for DNA extraction. Specifically, two loops of freshly grown mycobacterial cultures from L-J medium were added to 300 µl of water containing Chelex resin. To improve the efficiency of DNA extraction, 10ul proteinase K (10mg/ml) was added to the DNA extraction process, considering the high lipid content in the MTBC membrane. Incubate at 56°C for 20 minutes and then boil at 100°C for 5 minutes to release DNA. Following, the sample was centrifuged to pellet cellular debris and Chelex resin, and the supernatant was used as the DNA template. Then, DNA concentration and purity were determined by spectrophotometer (NanoDrop One, Thermo Scientific, USA).\u003c/p\u003e\n\u003ch3\u003ePolymerase chain reaction\u003c/h3\u003e\n\u003cp\u003eIn brief, the PCR reaction was carried out in a 50 µL mixture each containing 1.0µL dNTP (10mmol/L) (Invitrogen, USA), 2.0 µL AmpliTaq Gold™ DNA polymerase (5U/µL) (ABI, USA), 5.0 µL PCR Buffer(without Mg\u003csup\u003e2+\u003c/sup\u003e) (ABI, USA), 8.0 µL MgCl\u003csub\u003e2\u003c/sub\u003e(25mmol/L)(ABI, USA), 26.0 µL Amplification grade water (Promega, USA), 0.5 µL each primer and 5.0 µL DNA template. The reaction was performed using an automated thermal cycler (Verity, ABI, USA). The following PCR protocol was used: predenaturation of 94℃ for 5min, 35 cycles of 94℃ for 30s, 55℃ for 1min, and 72℃ for 1min, then a final extension step of 72℃ for 1min.\u003c/p\u003e\n\u003ch3\u003eCapillary electrophoresis\u003c/h3\u003e\n\u003cp\u003eThe 3130 genetic analyzer (ABI, USA) was utilized. The procedures were briefly as follows: first, a 9.0 µL mixture of LIZ 500 (Promega, USA) and HiDi buffer (Promega, USA) in a 1:130 ratio was added to a 96-well plate. 1.0 µL multiplex PCR product was then pipetted into each well, followed by a pre-denaturation process with heating the plate to 99℃ for 3min. Then, capillary electrophoresis was performed according to the manufacturer’s instructions.\u003c/p\u003e\n\u003ch3\u003eWhole-genome and Sanger sequencing\u003c/h3\u003e\n\u003cp\u003eGenomic DNA from MTBC isolates with discordant or irregular molecular assay results was sent to Majorbio (Shanghai, China) for whole-genome sequencing. To increase the accuracy and integrity of genome assembly, we employed a dual-platform strategy using both next-generation sequencing (Illumina) for high-depth short-read data and third-generation sequencing (PacBio) for long-read data. The raw Illumina reads were first quality-checked using FastQC and then filtered and trimmed. For long-read data, quality control was performed using the SMRT Analysis suite. Assembly was conducted using hybrid assembly approaches with SOAPdenovo and unicycler, which allowed us to leverage the strengths of both sequencing technologies. The assembled genomes were annotated using Prokka, and sequence alignments were performed with BLAST. For phylogenetic analysis, a set of 31 housekeeping genes was extracted from the assemblies, and the evolutionary relationships were constructed using MEGA 6.0 via the Neighbor-Joining method.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnalytical evaluation\u003c/h2\u003e \u003cp\u003eThe analytical sensitivities of the Multiplex assay were evaluated by determining the limit of detection (LOD). The LOD was measured using spiked samples with ATCC 27294. Twenty replicates were evaluated at five concentrations around LOD, and the LOD was determined using probit analysis. Then, studies were performed to determine the analytical specificity. Seventy-six (76) microorganisms (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which represent common respiratory pathogens, were tested at the following concentrations: DNA at 1×10\u003csup\u003e7\u003c/sup\u003e copies/mL for bacteria and fungi; nucleic acid at 2×10\u003csup\u003e9\u003c/sup\u003e copies/mL for viruses; DNA at 1×10\u003csup\u003e5\u003c/sup\u003e copies/mL for nontuberculous mycobacteria; and a concentration of 10\u003csup\u003e6\u003c/sup\u003e elementary bodies (EB) per mL for Chlamydia. All specificity and sensitivity assays were tested in duplicate.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMicroorganisms tested for analytical evaluation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroorganisms\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrigin\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicroorganisms\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOrigin\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium gastri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC15754\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium terrae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC15755\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eHaemophilus parainfluenzae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium xenopi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella oxytoca\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium smegmatis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19420\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pnenmoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium ulcerans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19423\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eLegionella pneumophila\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium thermoresistibile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19527\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMicrococcus luteus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium abscessus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19977\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMorganella morganii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium scrofulaceum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC19981\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium fortuitum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium simiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC25275\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium gordonae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC25922\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium intracellulare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC25923\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium kansassi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC27853\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNeisseria meningitidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium haemophilum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC29548\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNocardia asteroides\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium malmoense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC29571\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNocardia brasiliensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eShigella flexneri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC29903\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNocardia farcinica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium chelonae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC35752\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eProteus mirabilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium szulgai\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC35799\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eProteus vulgaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium celatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC51131\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium genavense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC51234\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas fluorescens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium marinum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCC927\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas putida\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium colombiense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCIP108962\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSerratia marcescens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium paraintracellulare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJCM30622\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eShigella boydii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium Massiliense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCIP108297\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium bolletii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDSM45149\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium avium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter calcoaceticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus agalactiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter junii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus midis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlcaligenes faecalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus salivarius\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBranhamella catarhalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAdenovirus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCoronavirus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCitrobacter freundii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eHuman metapneumovirus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCorynebacterium diphtheriae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eInfluenza B Virus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter aerogenes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eParainfluenza virus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRespiratory syncytial virus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterococcus faecalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRhinovirus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterococcus faecium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical isolates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRubella virus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNIFDC 370057 − 202001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eATCC: American Type Culture Collection; CIP: Collection of Institut Pasteur, France; JCM: Japan Collection of Microorganisms; DSM: Deutsche Sammlung von Mikroorganismen und Zellkulturen, German; NIFDC: National Institutes for Food and Drug Control, China.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical performance\u003c/h3\u003e\n\u003cp\u003eA prospective cohort study was conducted to evaluate the performance characteristics of the Multiplex assay. Inclusion criteria: Subjects 18 years or older were eligible for study if they were suspected of pulmonary tuberculosis (based on symptoms such as persistent cough, fever, weight loss, night sweats, and/or abnormal chest radiography findings) in Fujian Provincial Hospital, China, and on no TB treatment or with less than three days of TB treatment. Exclusion criteria: insufficient sputum volume. Then, we estimated that a sample size of 1100 patients is needed to obtain a between-group difference with more than 99% power. Meanwhile, this is an adequate sample size for evaluating the sensitivity and specificity according to the CLSI guideline. Testing should continue until results from at least 50 positive specimens, as a minimum guideline, are obtained with both the test and comparative method. The Institutional Ethics Committee of Fujian Provincial Hospital approved the study.\u003c/p\u003e \u003cp\u003eSputum specimens collected from subjects were tested using AFB smear, culture and Xpert MTB/RIF. Also, a single leftover sputum sample was tested using the Multiplex assay. All the participants were at least independently diagnosed by two doctors based on clinical and laboratory findings. If the diagnosis is different, another doctor is required. Then, the sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) of the four methods were calculated, respectively.\u003c/p\u003e \u003cp\u003eDiscordant results for MTBC culture positive and molecular assay negative, irrespective of Xpert MTB/RIF or Multiplex assay, were further evaluated using bi-directional sequencing of the corresponding region of the genome. If needed, WGS was used for further validation.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS Statistics 24, including the sensitivity, specificity, NPV, and PPV of the four methods adopted in this study, and their corresponding 95% confidence interval (CI). Probit analysis was used to determine the LOD of the Multiplex assay. The LOD was defined as the lowest DNA concentration detected in 95% of 20 replicates for every target gene.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003ch2\u003eCE based Multiplex assay\u003c/h2\u003e\u003cp\u003eSpecific primers (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) targeted \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, and \u003cem\u003eHSP65\u003c/em\u003e were designed based on their conserved region, respectively. Then, the specificity of these forward primers were was examined in silico. Compared with core nucleotide BLAST database, which consists of 108970392 sequences, the number of hits for forward primer targeted \u003cem\u003eIS6110\u003c/em\u003e is 101, 99 for MTBC, and 2 for Mycobacterium avium complex. For \u003cem\u003erpoB\u003c/em\u003e, the number of hits is 109, which includes 2 for Pontimonas sp. and 107 for MTBC. The number of hits for the forward primer targeted \u003cem\u003eHSP65\u003c/em\u003e is 101, which is all for MTBC. Moreover, the identity of all these hits above is 100%.\u003c/p\u003e\u003cp\u003eThe result of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e H37Rv (ATCC 27294) using this Multiplex assay is in line with expectations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After targeted DNA sequencing and alignment with reference sequence, the identity is 99.3% (269/271), 99.3% (268/270) and 98.8% (342/346) for \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e and \u003cem\u003eHSP65\u003c/em\u003e, respectively (Fig.\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003ch2\u003eAnalytical evaluation\u003c/h2\u003e\u003cp\u003eThree target genes were all successfully detected by the Multiplex assay with an LOD ranging from 10 to 20 copies/ mL (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Irrespective of the type of microorganisms, genomic DNA extracts from 76 respiratory pathogens were not detected by the multiplex method. So, the analytical specificity of the Multiplex assay is 100% at the given concentration regarding bacteria, fungi, viruses, Chlamydia, and nontuberculous mycobacteria.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOligonucleotides used for amplification by PCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOligonucleotide\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFluorophores\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eIS6110\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eIS6110\u003c/em\u003e-F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5’-TACGGTGCCCGCAAAGTG-3’\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5'-TAMRA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e271bp\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eIS6110\u003c/em\u003e-R\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5’-AGGCGTCGGTGACAAAGG-3’\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003erpoB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpoB\u003c/em\u003e-F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5'-CCAATTCATGGACCAGAACAA-3'\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5'-6-FAM\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e270 bp\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpoB\u003c/em\u003e-R\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5'-TACACGATCTCGTCGCTAACC-3'\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eHSP65\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHSP65\u003c/em\u003e-F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5'-AGCGATTTCGGCGGGTGA-3'\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5'-6-FAM\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e346 bp\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHSP65\u003c/em\u003e-R\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5'-TCTTGTTGACGACCAGGGTG-3'\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetection limit of Multiplex assay for three target genes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eMultiplex assay\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimit of detection (copies/ mL)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of replicates\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber detected\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% detected\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIS6110\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003erpoB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHSP65\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e \u003csup\u003ea\u003c/sup\u003e The limit of detection (LOD) was defined as the lowest DNA concentration that was detected in 95% of 20 replicates.\u003c/p\u003e\u003ch2\u003eClinical performance\u003c/h2\u003e\u003cp\u003eA total of 1100 patients were enrolled between January 2023 and December 2023, excluding 33 patients due to insufficient sputum volume. The final enrollment of 1067 patients was performed by AFB smear, culture, Xpert MTB/RIF and the Multiplex assay. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the classification of patients included in this study. In total, 124 patients were diagnosed with pulmonary tuberculosis. The overall positive rates of AFB smear, culture, Xpert MTB/RIF, and the Multiplex assay, not taking the diagnosis into account, were 4.9%, 11.8%, 10.0% and 9.4%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, for the TB patients, the positive rates were 25.8%, 75.0%, 79.8% and 77.4%, respectively.\u003c/p\u003e\u003cp\u003eComparisons of the four methods for the MTBC are given in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In total, 93 patients tested positive for multiplex assay, all of which were culture-positive. However, 31 patients who were not finally diagnosed with TB were culture-positive, all of which were Multiplex assay negative. Conversely, other 4 non-TB patients, who were diagnosed as obsolete pulmonary tuberculosis, were Xpert MTB/RIF positive and Multiplex assay positive, none of which were culture negative. The overall sensitivity of AFB smear for all 1067 patients was 25.8% ( CI 23.2%-28.4%), specificity 97.7% ( CI 96.9%-98.7%), PPV 60.4% ( CI 57.4%-63.3%) and NPV 90.9% ( CI 89.2%-92.7%). The corresponding values for culture were 75.0% ( CI 72.4%-77.6%), 96.7% ( CI 95.5%-97.7%), 74.4% ( CI 71.8%-77.0%) and 96.7% ( CI 95.6%-97.8%). Meanwhile, the Multiplex assay showed 77.4% ( CI 74.9%-79.9%) sensitivity, 99.6% ( CI 99.2%-100%) specificity, 96.0% ( CI 94.8%-97.2%) PPV and 97.1% ( CI 96.1%-98.1%) NPV.\u003c/p\u003e\u003ch2\u003eIdentification of IS6110-like element in MTBC\u003c/h2\u003e\u003cp\u003eAmong the 93 patients who were culture, Xpert MTB/RIF and Multiplex assay triple positive, we could not detect \u003cem\u003eIS6110\u003c/em\u003e element in 6 TB patients using the Multiplex assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Due to the possibility of misdiagnosis, a more careful analysis of the 6 isolates was carried out using WGS. The evolutionary relationship of the 6 isolates, based on dnaG, frr, infC, nusA, pgk, pyrG, rplA, rplB,rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, \u003cem\u003erpoB\u003c/em\u003e, rpsB, rpsC,rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB and tsf 31 housekeeping gene, is displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e (take A1 isolate as an example). Phylogenetic analysis revealed that the 6 isolates most likely belonged to \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eFurthermore, the whole genomes were obtained after genome assembly (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). As expected, we can’t find the oligonucleotide sequence designed for \u003cem\u003eIS6110\u003c/em\u003e in these genomes. Neither did the reverse complementary sequence. Since \u003cem\u003eIS6110\u003c/em\u003e was multicopy and belonged to mobile genetic elements, we attempted to position one deletion of these genomes. Then, sequence alignment with \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e H37Rv reference sequence (Accession ID:NC_000962) was carried out using BLAST tools. Finally, we positioned one deletion at location:1463537 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB,C). In comparison with reference sequence, we find an approximate 1500bp deletion did exist in the \u003cem\u003eIS6110\u003c/em\u003e corresponding region.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerformance of different methods to diagnose TB in the cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003c/colgroup\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDetection Methods\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTest Results\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-TB\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAFB smear\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(25.8%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21(2.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.8%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e97.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e60.4%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e90.9%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.1%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92(74.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e922(97.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.2%-28.4%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e96.9%-98.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e57.4%-63.3%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e89.2%-92.7%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCulture\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.8%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93(75.0%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32(3.3%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e96.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e74.4%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e96.7%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.2%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(25.0%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e911(96.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.4%-77.6%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95.5%-97.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e71.8%-77.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e95.6%-97.8%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eXpert MTB/RIF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99(79.8%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(0.8%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.8%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.2%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e92.5%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e97.4%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(20.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e935(99.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.4%-82.3%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e98.6%-99.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e91.0%-94.1%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e96.4%-98.4%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMultiplex assay\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.4%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96(77.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(0.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.4%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.6%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e96.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e97.1%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.6%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(22.6%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e939(99.6%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74.9%-79.9%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.2%-100%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e94.8%-97.2%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e96.1%-98.1%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003ePPV, Positive Predictive Value. NPV, Negative Predictive Value. CI, 95% upper and lower confidence interval.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAbout a quarter of the population is globally estimated to have been infected with MTBC (Cohen A et al. 2019). Rapid and accurate detection of MTBC is of great significance in controlling the TB spread, devastating infectious disease (Naidoo K et al. 2022). Nowadays, various commercially available NAATs kits are adopted in clinical laboratories worldwide (Mousavi-Sagharchi SMA et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Also various novel NAATs methods are developed for MTBC detection (Wang WH et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Batuer M et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Svensson E et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yee EH et al. 2020; Huang Z et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Homann AR et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shan H et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, most of these molecular kits only target one gene. This can lead to the misdiagnosis and missed diagnosis of TB. Misdiagnosis of TB can bring about substantial negative consequences (Houben RMGJ et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Firstly, a treatment course that lasts at least 6 months will be falsely recommended. Also, patients will incur substantial costs for clinical services and nonclinical expenses, like transportation, food, childcare, and lost wages (Laurence YV et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Meanwhile, missed diagnosis of TB can result in the delay of treatment for patients, then do harm to TB prevention (Medrano BA et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Here, we propose a novel, rapid and multi-target method that can detect three genes of MTBC simultaneously, aiming to provide a more comprehensive method for MTBC to reduce the misdiagnosis and missed diagnosis of TB.\u003c/p\u003e \u003cp\u003eThis is the first study that developed a multiplex assay to detect MTBC based on the CE platform. To ensure the specificity of this method, a two-step strategy was employed to design PCR primers. First, the conserved regions of the MTBC were identified through sequence alignment with several common NTM. Then, the BLAST tools from NCBI were utilized to test the specificity of these primers, which were designed based on the conserved regions. Specifically, compared with the core nucleotide BLAST database, it showed probable cross-reactivity with Pontimonas sp. for \u003cem\u003erpoB\u003c/em\u003e and Mycobacterium avium complex for \u003cem\u003eIS6110\u003c/em\u003e, proving no cross-reaction occurred by follow-up experiments. Also, here we report the performance of this method in a cohort, with 1067 patients finally enrolled, compared with AFB smear, culture, and Xpert MTB/RIF. Multiplex assay exhibited a sensitivity of 77.4% vs. 25.8% of AFB smear, 75.0% of culture, and 79.8% of Xpert MTB/RIF. The increment in sensitivity of the Multiplex assay over AFB smear was significant, whereas the increment in sensitivity of the Multiplex assay over culture was marginal. Also, we observed a low increment in specificity and NPV of Multiplex assay over AFB smear, culture, and Xpert MTB/RIF (specificity 99.6% vs. 97.7%, 96.7% and 99.2%, respectively, NPV 97.1% vs. 90.9%, 96.7%, and 97.4%, respectively). However, regarding PPV, the corresponding value of the Multiplex assay was 96.0% vs. 60.4%, 74.4% and 92.5% for AFB smear, culture, and Xpert MTB/RIF, respectively. Xpert MTB/RIF is acknowledged to be an excellent method to detect MTBC (WHO. 2020). In this context, it is worth noting that, with more target genes to be detected simultaneously, the Multiplex assay performed at least as well as Xpert MTB/RIF.\u003c/p\u003e \u003cp\u003eDuring the clinical evaluation of the Multiplex assay, we discovered 6 strains of MTBC with suspected \u003cem\u003eIS6110\u003c/em\u003e deletion. First, we adopted Sanger sequencing for \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, and \u003cem\u003eHSP65\u003c/em\u003e, three genes, to identify these strains. Regarding \u003cem\u003erpoB\u003c/em\u003e and \u003cem\u003eHSP65\u003c/em\u003e, the results were in line with reference sequence of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e (data not shown). Nevertheless, we could only obtain the \u003cem\u003eIS6110\u003c/em\u003e sequence result if we designed these primers. Then, the whole genomes were obtained using WGS based on the Illumina and Pacbio platforms. According to the phylogenetic analysis based on 31 housekeeping genes, these 6 strains belonged to \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e. Moreover, after the genome assembly, an approximate 1500bp deletion did exist in the \u003cem\u003eIS6110\u003c/em\u003e corresponding region. Owing to this finding, we could also recognize that the long gap was why we failed to get the results by Sanger sequencing. Certainly, in this regard, it would lead to false negative result for any commercial PCR kits targeted at \u003cem\u003eIS6110\u003c/em\u003e. Although we just discovered 6 \u003cem\u003eIS6110\u003c/em\u003e deletion strains (4.8%, 6/124) in our study, it was reported that the corresponding frequency was about 8% and 11% in Viet Nam and India, respectively (Chauhan DS et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This indicates the necessity of the Multiplex assay we developed here to reduce the missed diagnosis of TB.\u003c/p\u003e \u003cp\u003eThe study has limitations. First, clinical validation of this Multiplex assay was performed on just one site, which may lead to bias. Second, considering sputum volume, we select Xpert MTB/RIF targeted \u003cem\u003erpoB\u003c/em\u003e as a comparison in the cohort, endorsed by WHO (WHO. 2020).. So, in this regard, another two molecular assays, targeted \u003cem\u003eIS6110\u003c/em\u003e and \u003cem\u003eHSP65\u003c/em\u003e, respectively, were needed. Third, although 76 microorganisms, which represent common respiratory pathogens, were selected for analytical specificity, we did not take Pontimonas sp., which showed 100% identity aligned with the oligonucleotide designed for \u003cem\u003erpoB\u003c/em\u003e, into evaluation, since the corresponding strain was not available in our library.\u003c/p\u003e \u003cp\u003eIn conclusion, the Multiplex assay simultaneously provides one-run results for \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e and \u003cem\u003eHSP65\u003c/em\u003e, maintaining adequate sensitivity, specificity, PPV, and NPV for TB diagnosis. We present a more comprehensive method to detect MTBC. Although this is only a small fraction of the overall endeavor for accurate diagnosis, the Multiplex assay has the potential to reduce misdiagnosis and missed diagnosis of TB. To achieve the global end TB goals, the Multiplex assay, a comprehensive alternative to methods currently used, deserves further field evaluation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eTransparency declaration\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical Approval\u003c/h2\u003e \u003cp\u003e The study was approved by the Institutional Ethics Committee of Fujian Provincial Hospital.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Startup Fund for scientific research, Fujian Medical University, China (Grant No. 2020QH1167), and the Natural Science Foundation of Fujian Province, China (Grant No. 2023J011175).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYC W and Z L conceived and designed research. Z L and YP L conducted clinical validation and sample collection. YC W and L L conducted analytical validation and testing. YC W and Z L analyzed data and performed phylogenetic analysis. YC W and Z L conducted statistical analysis. YC W and Z L wrote the manuscript. L L and Y H reviewed and edited the manuscript. L L and Y H supervised the project. All authors have reviewed and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to thank the staff and technicians in the Division of Microbiology, Department of Clinical Laboratory, Fujian Provincial Hospital, for their assistance in collecting valuable microbiologic samples and isolates.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBatuer, M, Yuan, Y, Yu, M, Meng, C (2024). Establishment and evaluation of a new fluorescent probe method based on loop-mediated isothermal amplification for the detection of Mycobacterium tuberculosis complex. LUMINESCENCE, 39 (6), e4795. https://doi.org/10.1002/bio.4795\u003c/li\u003e\n\u003cli\u003eChauhan, DS, Sharma, VD, Parashar, D, Chauhan, A, Singh, D, Singh, HB, Das, R, Aggarwal, BM, Malhotra, B, Jain, A, Sharma, M, Kataria, VK, Aggarwal, JK, Hanif, M, Shahani, A, Katoch, VM (2007) Molecular typing of Mycobacterium tuberculosis isolates from different parts of India based on IS6110 element polymorphism using RFLP analysis. 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J Microbiol Immunol Infect, 58 (1), 56-61. https://doi.org/10.1016/j.jmii.2024.09.003\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2020) WHO consolidated guidelines on tuberculosis: Module 3: diagnosis\u0026ndash;rapid diagnostics for tuberculosis detection. World Health Organization, Geneva\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2024) Global tuberculosis report, 2024. World Health Organization, Geneva. Licence: CC BY-NC-SA 3.0 IGO.\u003c/li\u003e\n\u003cli\u003eYee, EH, Sikes, HD (2020) Polymerization-Based Amplification for Target-Specific Colorimetric Detection of Amplified Mycobacterium tuberculosis DNA on Cellulose. ACS Sens, 5 (2), 308-312. https://doi.org/10.1021/acssensors.9b02424\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multiplex assay, Mycobacterium tuberculosis complex, Capillary electrophoresis, IS6110, rpoB, HSP65","lastPublishedDoi":"10.21203/rs.3.rs-6746494/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6746494/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents a novel multiplex assay based on capillary electrophoresis (CE) for the simultaneous detection of three \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC) genes: \u003cem\u003eIS6110\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, and \u003cem\u003eHSP65\u003c/em\u003e. Unlike conventional molecular diagnostic methods that target only single gene, which may lead to misdiagnosis or missed diagnosis, this CE-based multiplex approach provides a comprehensive detection to reduce diagnostic errors. Specificity testing with 76 microorganisms representing common respiratory pathogens confirmed 100% analytical specificity with no cross-reactivity, while sensitivity analysis demonstrated detection limits ranging from 10 to 20 copies/mL for all three target genes. In a prospective clinical validation study of 1,067 patients suspected of pulmonary tuberculosis, the multiplex assay showed 77.4% sensitivity (CI 74.9%-79.9%), 99.6% specificity (CI 99.2%-100%), 96.0% positive predictive value (CI 94.8%-97.2%), and 97.1% negative predictive value (CI 96.1%-98.1%). Notably, the study identified 6 MTBC strains (4.8% of TB patients) with \u003cem\u003eIS6110\u003c/em\u003e deletions through whole-genome sequencing, which would result in false-negative results for any commercial PCR kits targeting \u003cem\u003eIS6110\u003c/em\u003e. This integrated multiplex approach enhances diagnostic accuracy by simultaneously targeting multiple genes, then it offers potential to reduce misdiagnosis and missed diagnosis of tuberculosis. In summary, the multiplex assay provides a more comprehensive alternative to current single-target molecular methods for MTBC detection.\u003c/p\u003e","manuscriptTitle":"A Multiplex assay based on capillary electrophoresis to detect Mycobacterium tuberculosis complex: development and clinical validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 06:45:22","doi":"10.21203/rs.3.rs-6746494/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ef32649-723c-4865-80e6-514479b4bf1d","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:00:50+00:00","versionOfRecord":{"articleIdentity":"rs-6746494","link":"https://doi.org/10.1007/s00253-025-13701-0","journal":{"identity":"applied-microbiology-and-biotechnology","isVorOnly":false,"title":"Applied Microbiology and Biotechnology"},"publishedOn":"2026-02-02 15:57:37","publishedOnDateReadable":"February 2nd, 2026"},"versionCreatedAt":"2025-07-02 06:45:22","video":"","vorDoi":"10.1007/s00253-025-13701-0","vorDoiUrl":"https://doi.org/10.1007/s00253-025-13701-0","workflowStages":[]},"version":"v1","identity":"rs-6746494","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6746494","identity":"rs-6746494","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}