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DOI: 10.3791/68370-v
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
I investigate whether portable long-read sequencing can provide TB drug-resistant susceptibility results in resource-limited settings with accuracy comparable to gold standards method, advancing accessible, high-quality tuberculosis diagnostics. Utilizing targeted next-generation sequencing as a diagnostic tool for drug-resistant tuberculosis by offering a comprehensive resistance profile directly from clinical sample without bioinformatics expertise. Our protocol utilizing long-read sequencing has the potential to provide quicker turnaround times, simpler workflow than in real-time resistance detection, facilitating comprehensive TB diagnostics and enhancing outbreak tracking in resource-limited environment with minimal infrastructure.
To begin, calculate 100 nanograms of each amplicon sample based on the concentration and transfer the required volume into a clean PCR tube. To determine the total mass of amplicons in the sample, use the given formula. Adjust the total volume of each sample to 12.5 microliters using nuclease-free water.
Mix the samples gently by pipetting up and down 10 times and briefly spin them in a microcentrifuge. Next, add 1.75 microliters of end-repair and adenylation reaction buffer to each sample, followed by 0.75 microliters of end-repair and adenylation enzyme mix. After mixing and spinning the samples, place the tubes in a thermocycler at 25 degrees Celsius for 30 minutes, followed by 65 degrees Celsius for 30 minutes.
For native barcode ligation, add the components shown on the screen in new PCR tubes. Mix the reactions gently by pipetting and spin briefly using a microcentrifuge. Next, add one microliter of EDTA to each tube.
Then, mix thoroughly and spin briefly as shown earlier. Pull the barcoded samples into a 1.5 milliliter microcentrifuge tube. Vortex the DNA cleanup beads to resuspend them completely and add a volume equal to 0.7 times the pooled sample volume.
Mix the bead sample solution and incubate it on a HulaMixer at room temperature for 10 minutes. Next, to prepare two milliliters of 80%ethanol, mix 1, 600 microliters of pure ethanol with 400 microliters of nuclease-free water. Place the tube on a magnetic rack for five minutes until the eluate appears clear and colorless.
Then, remove and discard the supernatant without disturbing the pellet. Wash the beads with 700 microliters of freshly prepared 80%ethanol and centrifuge the tube briefly. After placing the tube on the magnetic rack, remove the residual ethanol.
Now, remove the tube from the magnetic rack. Resuspend the beads in 35 microliters of nuclease-free water by gentle flicking and incubate at 37 degrees Celsius for 10 minutes. Return the tube to the magnetic rack until the eluate becomes clear and colorless.
Then, transfer 35 microliters of the eluate into a clean 1.5 milliliter microcentrifuge tube for further use. For adapter ligation, mix the given components in a 1.5 milliliter low-binding microcentrifuge tube. Centrifuge the tube briefly and incubate at room temperature for 20 minutes.
Vortex the DNA cleanup beads to resuspend them completely. Add 20 microliters of beads to the tube and mix gently. Incubate on a HulaMixer for 10 minutes at room temperature.
Then, place the tube on a magnetic rack to pellet the beads and aspirate the supernatant without disturbing the pellet. Add 125 microliters of short fragment buffer and gently flick the tube to resuspend the beads. Centrifuge briefly and return the tube to the magnetic rack.
Aspirate the supernatant again after the beads have pelleted. Now, remove the tube from the magnetic rack and resuspend the beads in 15 microliters of elution buffer by gentle pipetting or flicking. Briefly centrifuge the tube to collect the contents, then incubate it at 37 degrees Celsius for 10 minutes to elute the DNA.
Place the tube on a magnetic rack until the eluate is clear and colorless. Then, aspirate 15 microliters of eluate and transfer it into a clean, 1.5 milliliter microcentrifuge tube. To prepare the flow cell priming solution, mix the given components thoroughly.
Open the priming port of the flow cell, aspirate approximately 20 microliters of buffer to remove air bubbles, and load 800 microliters of the priming mix into the port without introducing air bubbles. To prepare the DNA library, thoroughly mix the components shown on the screen. Gently lift the sample port cap of the flow cell, load 200 microliters of priming mix into the priming port without introducing air bubbles.
After mixing the prepared DNA library, load 75 microliters of the library dropwise into the sequencing flow cell sample port. Close the flow cell sample port cap, ensuring the bung securely enters the sample port, and then close the priming port tightly. Gel electrophoresis confirmed amplicon integrity across nearly all samples, but lanes corresponding to samples 89 and 136 displayed faint or absent bands.
Samples 89 and 136 had insufficient amplicon concentrations, leading to their exclusion from long-read sequencing. Across all targeted genes, the long-read and short-read platforms achieved high coverage depths with the EIS gene showing the highest average values and RRS gene exhibiting the lowest coverage depths. Despite the range in coverage depth, both platforms maintained a high coverage breadth of 99.9%across all resistance-associated genes.
Drug resistance variants for ethambutol, fluoroquinolones, kanamycin, amikacin, and capreomycin were detected with 100%concordance across short and long-read sequencing platforms. No resistance-associated mutations were found for linezolid, bedaquiline, and clofazimine using either sequencing approach. Streptomycin resistance detection showed lower concordance between platforms, with only 71.43%agreement.
Detection sensitivity for key genes rpoB, katG/fabG1/ahpC/inhA, fabG1/inhA, and pncA ranged from 89.47%to 96.77%between platforms.
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