Performance of QuantaMatrix Microfluidic Agarose Channel system integrated with mycobacteria growth indicator tube liquid culture

Kim, Hye-Jin; Lee, Sangyeop; Jo, Eunji; Kim, Suyeoun; Kim, Haeun; Kim, Eun-Geun; Kwon, Sunghoon; Shin, So–Youn

doi:10.1007/s00253-021-11446-0

Cited by 3 publications

(6 citation statements)

References 32 publications

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“…Fast and sensitive methods for TB drug susceptibility testing using direct microscopic observation of broth cultures have been proposed before. However, the median turnaround time for these tests was 5.4 to 9.5 days 35,[54][55][56] . In our method an accurate growth rate is calculated for thousands of single cells, allowing us to reach statistical significance for growth-rate differences quicker than what would be possible for the corresponding bulk measurement.…”

Section: Discussionmentioning

confidence: 99%

“…M. tuberculosis was loaded into a microfluidic chip by Chung et al, (2023) to investigate the growth at the single-cell level 31 . Notably, microfluidics and direct imaging combined with agarose channels were used for rapid pDST on various bacterial strains, including Mtb [32][33][34][35] . The system, called QuantaMatrix microfluidic agarose channel (QMAC), was integrated with MGIT liquid culture, resulting in a short turnaround time of the culture identification (~2 weeks) and subsequent pDST from Mtb clumps (~1 week) 35 .…”

Section: Introductionmentioning

confidence: 99%

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One-day phenotypic drug susceptibility testing forMycobacterium tuberculosisvariantbovisBCG using single-cell imaging and a deep neural network

Tran,

Larsson,

Grip

et al. 2024

Preprint

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Drug-resistant tuberculosis (TB) kills approximately 200,000 people every year. A contributing factor is the slow turnaround time associated with anti-tuberculosis drug susceptibility diagnostics. The prevailing gold standard for phenotypic drug susceptibility testing (pDST) takes at least two weeks. In this study, we used Mycobacterium tuberculosis variant bovis BCG (M. bovis BCG) and Mycobacterium smegmatis as models for tuberculous and nontuberculous pathogens. The bacteria were loaded into a microfluidic chip, trapping them in microchambers, and allowing simultaneous tracking of single-cell growth with and without antibiotic exposure. A deep neural network image-segmentation algorithm was employed to quantify the growth rate over time and determine how the strains responded to the drugs compared to the untreated reference. We determined that the response time of the susceptible strains to isoniazid (INH), ethambutol (EMB), and linezolid (LZD) at MIC was within 3 hours and 1.5 hours for M. bovis BCG and M. smegmatis, respectively. Resistant strains of M. smegmatis were identifiable within 3 hours, suggesting that growth-based pDST can be conducted in less than 12 hours for slow-growing M. bovis BCG. The results obtained for M. bovis BCG are most likely comparable to what we expect for M. tuberculosis as these strains share 99.96% genetic identity.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

One-day phenotypic drug susceptibility testing forMycobacterium tuberculosisvariantbovisBCG using single-cell imaging and a deep neural network

Tran,

Larsson,

Grip

et al. 2024

Preprint

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“…They also depend on the skill of laboratory personnel for result interpretation and are not efficient for processing large sample volumes [22][23][24][25]. QMAC-DST addresses several limitations of traditional pDST by offering rapid TAT, the ability to test various first-and second-line drugs, high throughput, reduced labor intensity, effectiveness regardless of inoculum size, enhanced safety with sealing film and a locking lid, along with an agarose matrix embedding the MTB and elimination of errors due to the MTB tracking failure [12][13][14][15]. However, because QMAC-DST uses colonies derived from the LJ medium, the timing for the confirmation of QMAC-DST results after the start of treatment can be delayed, depending on the time required for the MTB culture.…”

Section: Discussionmentioning

confidence: 99%

“…Following image acquisition, an algorithmic approach was used for subsequent processing and analysis. Further details regarding experimental methodologies and procedures are available in a previous publication [15]. The critical concentrations for drug resistance determination were set as follows: INH, 0.1 µg/mL; RIF, 1.5 µg/mL; EMB, 5 µg/mL; RFB, 1.25 µg/mL; OFX, 2 µg/mL; LFX, 0.75 µg/mL; MFX, 0.5 µg/mL; SM, 1.0 µg/mL; AMK, 2 µg/mL; KM, 2.5 µg/mL; CM, 2.5 µg/mL; PTO, 2.5 µg/mL; CS, 16 µg/mL; PAS, 4 µg/mL; and LZD, 1.0 µg/mL.…”

Section: Drug Susceptibility Testmentioning

confidence: 99%

“…By using a microfluidic chip and imaging technologies, QMAC-DST is capable of determining resistance to >15 anti-TB drugs within a week using a culture specimen [12]. Its high concordance with the conventional LJ-DST has been validated in previous studies [13][14][15]. This multicenter study seeks to investigate the impact of QMAC-DST on the treatment of pulmonary TB patients, with a particular focus on comparing QMAC-DST and LJ-DST.…”

Section: Introductionmentioning

confidence: 99%

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QMAC-DST for Rapid Detection of Drug Resistance in Pulmonary Tuberculosis Patients: A Multicenter Pre–Post Comparative Study

Kwak,

Lee,

Kim

et al. 2024

JCM

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Background/Objectives: This study explores the impact of QMAC-DST, a rapid, fully automated phenotypic drug susceptibility test (pDST), on the treatment of tuberculosis (TB) patients. Methods: This pre–post comparative study, respectively, included pulmonary TB patients who began TB treatment between 1 December 2020 and 31 October 2021 (pre-period; pDST using the Löwenstein–Jensen (LJ) DST (M-kit DST)) and between 1 November 2021 and 30 September 2022 (post-period; pDST using the QMAC-DST) in five university-affiliated tertiary care hospitals in South Korea. We compared the turnaround times (TATs) of pDSTs and the time to appropriate treatment for patients whose anti-TB drugs were changed based on these tests between the groups. All patients were permitted to use molecular DSTs (mDSTs). Results: A total of 182 patients (135 in the M-kit DST group and 47 in the QMAC-DST group) were included. The median TAT was 36 days for M-kit DST (interquartile range (IQR), 30–39) and 12 days for QMAC-DST (IQR, 9–15), with the latter being significantly shorter (p < 0.001). Of the total patients, 10 (5.5%) changed their anti-TB drugs based on the mDST or pDST results after initiating TB treatment (8 in the M-kit DST group and 2 in the QMAC-DST group). In the M-kit DST group, three (37.5%) patients changed anti-TB drugs based on the pDST results. In the QMAC-DST group, all changes were due to mDST results; therefore, calculating the time to appropriate treatment for patients whose anti-TB drugs were changed based on pDST results was not feasible. In the QMAC-DST group, 46.8% of patients underwent the first-line line probe assay compared to 100.0% in the M-kit DST group (p < 0.001), indicating that rapid QMAC-DST results provide quicker assurance of the ongoing treatment by confirming susceptibility to the current anti-TB drugs. Conclusions: QMAC-DST delivers pDST results more rapidly than LJ-DST, ensuring faster confirmation for the current treatment regimen.

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The contribution of microfluidics to the fight against tuberculosis

Cañadas-Ortega

Gomez-Cruz

Vaquero

et al. 2021

Nanotechnology Reviews

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The high mortality associated with tuberculosis brings forward the urgency of developing new therapies and strategies against the disease. With the advance of drug-resistant strains, traditional techniques have proven insufficient to manage the disease appropriately. Microfluidic devices have characteristics that can enhance treatment prescription and significantly advance our knowledge about the disease and its interaction within the human body. In addition, microfluidic systems provide advantages in terms of time and costs, which are particularly important in countries with low income and resources. This review will highlight how microdevices can help bridge the gaps in disease management, including their use for drug testing and development, drug susceptibility, basic research, and novel approaches to anti-TB vaccines and organ-on-chip studies.

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Performance of QuantaMatrix Microfluidic Agarose Channel system integrated with mycobacteria growth indicator tube liquid culture

Cited by 3 publications

References 32 publications

One-day phenotypic drug susceptibility testing forMycobacterium tuberculosisvariantbovisBCG using single-cell imaging and a deep neural network

One-day phenotypic drug susceptibility testing forMycobacterium tuberculosisvariantbovisBCG using single-cell imaging and a deep neural network

QMAC-DST for Rapid Detection of Drug Resistance in Pulmonary Tuberculosis Patients: A Multicenter Pre–Post Comparative Study

The contribution of microfluidics to the fight against tuberculosis

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