Method Article

Amplicon Sequencing using the Long-Read Sequencing Technologies

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DOI:

10.3791/68370

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August 29th, 2025

 ,  ,  ,  ,  ,  ,  , 
1Department of Science and Innovation - National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University

In This Article

Summary

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.

Abstract

The World Health Organization (WHO) continues to emphasize the urgent need for a rapid, cost-effective, and user-friendly diagnostic method for tuberculosis (TB) and drug-resistant TB (DR-TB). Next-generation sequencing (NGS) technologies, endorsed by the WHO, have significantly improved the detection of DR-TB. Among these, targeted NGS (tNGS) enables focused detection of genetic mutations associated with drug resistance, eliminating the need for traditional culture-based diagnostics. One widely used tNGS assay provides rapid and comprehensive drug susceptibility testing but has been primarily optimized for sequencing platforms with high accuracy. However, the high cost of these sequencing systems has limited accessibility in low- and middle-income countries, particularly across Africa. Portable sequencing technologies present a promising alternative, offering flexibility and reduced infrastructure requirements. In this study, DNA was extracted from rifampicin-resistant TB (RR-TB) isolates, amplified using a tNGS assay, and sequenced on a portable sequencing platform. The same amplification products were also sequenced on a high-accuracy short-read sequencing platform to serve as a reference. Data from the portable sequencer were processed using a bioinformatics pipeline designed for long-read sequencing, while short-read sequencing data were analyzed using an established web-based application. The analysis showed that the long-read sequencing approach successfully identified high-frequency resistance-associated variants detected by short-read sequencing but exhibited limitations in detecting low-frequency variants.

Introduction

Tuberculosis (TB) continues to be a major cause of mortality globally and presents an ongoing public health challenge, especially in low- and middle-income countries1,2. Despite initiatives aimed at enhancing TB control measures, advancements have been slow, partly due to difficulties in achieving rapid, accurate, cost-effective, and comprehensive diagnostic techniques3,4,5. While molecular diagnostic methods like line probe assays (LPAs) and automated nucleic acid amplification tests (NAATs) have sped up the identification of TB and drug-resistant TB (DR-TB), their limited mutation detection restricts thorough drug susceptibility testing (DST). This limitation is particularly significant in TB high-burden countries6,7,8,9.

To address these limitations, the World Health Organization (WHO) has recommended the use of next-generation sequencing (NGS) technologies, which have emerged as powerful tools for TB surveillance and resistance detection10,11. Both whole genome sequencing (WGS) and targeted NGS (tNGS) approaches offer broader mutation coverage, enabling the identification of resistance-associated variants across multiple drugs8,12,13,14,15. While whole genome sequencing (WGS) provides a comprehensive DST report, its reliance on culture makes it unsuitable for rapid diagnostics, as culture can take up to six weeks15,16,17. Targeted NGS offers a better alternative since it does not depend on culture; sequencing can be performed directly from clinical specimens18. As a result, the WHO has recommended the use of three tNGS assays for DST: Deeplex Myc-TB assay: This assay detects resistance to rifampicin, isoniazid, fluoroquinolones, aminoglycosides (amikacin, kanamycin, capreomycin), ethambutol, pyrazinamide, and ethionamide19,20,21. Sentinel TB assay: This targets resistance to rifampicin, isoniazid, fluoroquinolones, and second-line injectable drugs18,20. AQ-TB assay: This identifies resistance to rifampicin, isoniazid, fluoroquinolones, and second-line injectable drugs. These assays have been optimized for use on the short-read platform due to its high accuracy20. ONT MinION long-read platforms, on the other hand, provide real-time data, portability, and the potential for cost-effective implementation22,23. However, the widespread use of NGS is limited by the demands of infrastructure and cost, especially with short-read systems10.

The Deeplex assay is the most comprehensive of the three recommended assays. The assay was originally designed to perform multiplex PCR on 18 regions associated with resistance to 13 anti-TB drugs. However, the WHO recommended it for 10 anti-TB drugs, indicating sufficient sensitivity and specificity. This study optimized it for use with the ONT MK1B MinION, a long-read sequencing platform. The portable and reusable flow-cell system of this platform reduces both infrastructure and potentially sequencing costs per sample4,22,23. While other long-read-compatible assays have been developed, they tend to have a limited DST scope, typically targeting only a narrow range of resistance genes. In contrast, the assay offers broad target coverage, making it a more comprehensive diagnostic tool for decentralized DST24,25. A detailed list of the genomic targets amplified by the assay and their corresponding drug associations is provided in Table 1, highlighting the assay's diagnostic capabilities25.

Prior to DNA extraction, samples must be decontaminated and inactivated under Biosafety Level 3 (BSL-3) conditions, following the necessary safety precautions25,26,27. Internal amplification and external controls should be incorporated in each run, with contamination tracked through negative controls and routine laboratory evaluations25. Important quality metrics, including read depth, coverage breadth, and amplification success, should be assessed after sequencing. For targeted sequencing, the WHO advises a minimum read depth of 100x for each amplicon and adequate coverage of all targeted drug-resistance regions to allow for the detection of minor variants that are present at ≥5%28. The World Health Organization endorses these targeted sequencing methods for identifying resistance to first- and second-line drugs, assuming that quality assurance systems are established and that all target regions are sufficiently covered28.

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Protocol

This research was conducted as part of the TS ELiOT project, which received ethical approval from the Human Research Ethics Committee (HREC) at Stellenbosch University (N21/09/093) on October 20, 2021. Additionally, it obtained authorization from Western Cape Health Research for the use of government facilities. Samples were collected through a collaborative effort with the NHLS Green Point and Stellenbosch University, under the SU HREC approval number N09/11/296. The reagents and the equipment used are listed in the Table of Materials.

1. Sample preparation

  1. Heat inactivation
    1. Incubate the MGIT cultures at 80 °C for 1 h to achieve complete heat inactivation under BSL-3 conditions.
    2. Proceed with DNA extraction using the InstaGene method29.
  2. DNA extraction
    1. Place 5 mL of heat-inactivated MGIT culture into a 15 mL tube.
    2. Centrifuge at 4000 x g for 30 min at room temperature (RT).
    3. Carefully remove the supernatant by pipetting, leaving the sediment.
    4. Add 200 µL of chelation-based DNA extraction reagent to the sediment and incubate at 56 °C for 15 min.
    5. Transfer the solution to a 2 mL screw-cap tube and add three 2 mm diameter glass beads to each.
    6. Vortex for 10 s to spread cells and place the tubes in a dry bath incubator at 100 °C for 8 min.
    7. Homogenize the samples using the bead-beating homogenizer with the following settings: 3 cycles of 20 s at 4.0 m/s.
    8. Centrifuge at 12,000 x g for 15 min at RT and carefully transfer 130 µL of the supernatant (DNA-containing liquid) to a 1.5 mL tube, avoiding sediment and debris.
    9. Resuspend the beads by flicking or vortexing and add 156 µL of the beads to the 1.5 mL tube containing the extracted DNA.
    10. Slowly pipette up and down 10 times to mix and incubate at RT for 5 min.
    11. Place the tubes on a magnetic rack for 5 min to separate the DNA-bound beads.
      NOTE: A clear supernatant should appear above a compact pellet of dark magnetic beads at the side of the tube facing the magnet, indicating readiness for supernatant removal.
    12. Pipette off the supernatant without disturbing the beads.
    13. Add 100 µL of freshly prepared 80% ethanol to the bead pellet while on the rack and leave for 30 s, then remove the ethanol. Repeat the wash step.
    14. Air-dry the bead pellet at RT for 5 min. Ensure the bead pellet appears matte and no visible liquid remains before proceeding to the next step.
    15. Remove the tube from the magnetic rack.
    16. Add 25 µL of Nuclease Free Water (NFW) directly to the dried beads and resuspend by gently pipetting up and down 10 times.
    17. Incubate at RT for 5 min.
    18. Return the tube to the magnetic rack for another 5 min.
    19. Carefully transfer the eluted DNA (supernatant) to a new 1.5 mL tube.
    20. Measure the DNA concentration using the high-sensitivity fluorescence-based dsDNA quantification reagent.
      NOTE: The DNA can be stored in a -20 °C freezer or proceed with PCR.
  3. Amplification (PCR)
    1. Multiplex PCR and post-PCR cleanup, following manufacturer's instructions25.
    2. Measure the DNA concentration using the high-sensitivity fluorescence-based dsDNA quantification reagent.
  4. Gel electrophoresis
    1. Prepare a 2% agarose gel by dissolving agarose powder in 1x TAE buffer through microwave heating until fully melted.
    2. Add  5 µL of nontoxic fluorescent DNA gel stain to the melted agarose and mix thoroughly.
    3. Pour the gel mixture into a gel casting tray fitted with a comb to form wells.
    4. Allow the gel to solidify at RT.
    5. Once solidified, remove the comb and place the gel tray in the electrophoresis tank filled with 1x TAE buffer.
    6. Load 5 µL of a  kb DNA ladder mixed with 5 µL of loading buffer into the first well.
    7. For each PCR product, mix 5 µL of the product with 5 µL of loading buffer and load into individual wells.
    8. Run the gel at 100 V for 1 h.
    9. Visualize the DNA bands using the gel documentation system with transillumination.

2. ONT library preparation

  1. End-prep
    1. Calculate 100 ng of each amplicon sample based on concentration and transfer the required volume into a clean PCR tube.
    2. To calculate the total mass (in ng) of amplicons in a given sample, multiply the concentration of the sample (ng/µL) by its remaining volume (µL) after quality control (QC).
      NOTE: For example, if a sample has a concentration of 2 ng/µL and a remaining volume of 1 µL post-QC, the total amplicon mass is:
      Total mass = 2 ng/µL × 1 µL = 45 ng
      To prepare 10 ng of amplicons for sequencing, use the dilution formula:
      C1V1 = C2V2
      Where: C1 = 45 ng, V1 = unknown, C2 = 10 ng, V2 = 1 µL, V1 = (C2 × V2) / C1 = (10 ng × 1 µL) / 45 ng =  µL
      ​Thus,  µL of the initial amplicon sample should be used to obtain 10 ng of DNA for sequencing.
    3. Adjust the total volume of each sample to 12.5 µL using NFW.
    4. Mix the samples gently by pipetting up and down 10 times and briefly spin.
    5. Add 1.75 µL of end-repair and A-tailing reaction buffer and 0.75 µL of endrepair and A-tailing enzyme mix to each sample.
    6. Mix thoroughly by pipetting up and down 10 times and briefly spin down.
    7. Incubate the tubes in a thermocycler at 25 °C for 30 min, followed by 65 °C for 30min.
      NOTE: At this stage, should the user decide to discontinue the process, it is advisable to utilize beads for the purification of the end-prepped DNA. The purified DNA can then be stored at 4 °C for a maximum duration of seven days.
  2. Native barcode ligation
    1. Thaw and prepare the magnetic beads for DNA purification and size selection, paramagnetic DNA cleanup beads, EDTA, and native barcodes (NB01-96) according to the manufacturer's instructions, and then place them on ice.
    2. In new PCR tubes, add the following in sequence: 2.75 µL of nuclease-free water,1 µL of end-prepped DNA, 1.25 µL native barcodes (NB01-96), and 5 µL of DNA ligation enzyme mix.
    3. Mix each reaction by pipetting gently 10 times, spin briefly using a microcentrifuge, and incubate for 20 min at RT.
    4. Add 1 µL of EDTA to each well, mix thoroughly by pipetting, and spin briefly.
    5. Pool-barcoded samples into a 1.5 mL microcentrifuge tube.
    6. Resuspend the DNA cleanup beads by vortexing and add 0.7x the total pooled sample volume (e.g., for 23 samples with a total volume of 253 µL, add 177.1 µL beads).
    7. Mix the solution by pipetting and incubate on a HulaMixer for 10 min at RT.
    8. Prepare 2 mL of 80% ethanol by mixing 1600 µL pure ethanol with 400 µL NFW.
    9. Place the tube on a magnetic rack for 5 min until the eluate is clear and colourless.
    10. Remove and discard the supernatant without disturbing the pellet.
    11. Wash the beads with 700 µL freshly prepared 80% ethanol without disturbing the pellet, then remove and discard the ethanol.
    12. Repeat the ethanol wash step.
    13. Centrifuge the tube briefly, return to the magnetic rack, and remove residual ethanol.
    14. Allow the beads to air dry for 30 s.
    15. Remove the tube from the magnetic rack, resuspend the beads in 35 µL nuclease-free water by gentle flicking, and incubate at 37 °C for 10 min.
    16. Return the tube to the magnetic rack until the eluate is clear and colourless.
    17. Transfer 35 µL of the eluate into a clean 1.5 mL microcentrifuge tube for subsequent steps.
      NOTE: The library can be stored at 4 °C overnight at this stage.
  3. Adapter ligation and cleanup
    1. Prepare the rapid DNA ligation reagent kit according to the manufacturer's instructions and place it on ice.
    2. Mix the Native Adapter (NA) and Quick Ligase by pipetting, then place on ice.
    3. Thaw the elution buffer (EB) at RT, vortex, centrifuge, and place it on ice.
    4. Thaw Short Fragment Buffer (SFB) at RT, vortex, centrifuge, and place on ice.
    5. In a 1.5 mL low-binding microcentrifuge tube, mix the following: 30 µL of pooled barcoded sample, 5 µL of Native Adapter (NA), 10 µL of rapid ligation reaction buffer, and 5 µL of rapid-acting T4 DNA ligase.
    6. Gently pipette to mix, briefly centrifuge, and incubate for 20 min at RT.
    7. Resuspend DNA cleanup beads by vortexing and add 20 µL (0.4x) of beads to the reaction.
    8. Mix gently by pipetting and incubate on a HulaMixer for 10 min at RT.
    9. Pellet the beads on a magnetic rack and aspirate the supernatant without disturbing the pellet.
    10. Wash the beads by adding 125 µL of Short Fragment Buffer (SFB), resuspend by flicking, centrifuge briefly, and return to the magnetic rack.
    11. Pellet the beads and aspirate the supernatant; repeat the washing step once.
    12. Briefly centrifuge, return the tube to the magnetic rack, and aspirate any residual supernatant.
    13. Remove the tube from the magnetic rack and resuspend the beads in 15 µL of Elution Buffer (EB).
    14. Briefly centrifuge and incubate at 37 °C for 10 min to elute the DNA.
    15. Place the tube on the magnetic rack, pellet the beads until the eluate is clear and colorless, and aspirate 15 µL of the eluate into a clean 1.5 mL microcentrifuge tube.
    16. Quantify 1 µL of the eluate.
    17. Dilute the library to 20 fmol (calculate using the NEB calculator) and use 12 µL of the 20 fmol prepared library for sequencing on the R10.4.1 flow cell.
      NOTE: The library can now be stored at -20 °C, allowing for repeated use.
  4. Priming and loading the nanopore sequencing flow cell
    1. Thaw the Sequencing Buffer (SB), Library Beads (LIB), Flow Cell Tether (FCT), and Flow Cell Flush (FCF) at RT, mix them by vortexing, and spin them down.
    2. Prepare the flow cell priming mix by combining 5 µL of Bovine Serum Albumin (BSA, 50 mg/mL), 30 µL of Flow Cell Tether (FCT), and 1170 µL of Flow Cell Flush (FCF), mixing the solution by inversion and pipetting.
    3. Open the priming port of the flow cell, aspirate ~20 µL of buffer to remove air bubbles, load 800 µL of the priming mix into the priming port without introducing air bubbles, and wait for 5 min.
    4. Prepare the library by mixing 37.5 µL of Sequencing Buffer (SB), 25.5 µL of Library Beads (LIB) or Library Solution (LIS), and 12 µL of the 20 fmol DNA library in a 1.5 mL microcentrifuge tube, mixing thoroughly by pipetting.
    5. Prime the flow cell again by gently lifting the flow cell sample port cap, loading 200 µL of the priming mix into the priming port without introducing air bubbles, and preparing the library for loading.
    6. Mix the prepared library gently by pipetting and load 75 µL of the library into the sequencing flow cell sample port dropwise, ensuring each drop flows into the port before adding the next.
    7. Close the flow cell sample port cap, ensuring the bung enters the flow cell sample port, then close the priming port.
    8. Connect the portable sequencing device to a computer (with an uninterrupted power supply) and initiate sequencing using a sequencing device control and analysis software.
  5. Software parameters
    NOTE: This software application, developed by ONT, is utilized for the comprehensive management of sequencing runs and the generation of detailed reports.
    1. To initiate the sequencing process, please select the Start option followed by Start sequencing.
      NOTE: One will then be prompted to designate a folder for file storage and provide a name for your sequencing run, for example, "sequencing_run_1." Afterward, click on Continue to settings to select the appropriate kit name, such as library-sequencing-amplicons-native-barcoding-v14-sqk-nbd114-96, and customize the desired run time, for instance, 20 h (the maximum run time is 72 h).
    2. Next, choose the output file type, selecting from options such as POD5 for raw output reads and FASTQ for basecalled outputs. Subsequently, select the FAST-Basecalling model.
    3. Please note that some of the default settings include frequent pore scanning every 1.5 h, a minimum read length of 200 bp, and a minimum quality score of 8. Lastly, review the settings and commence the reading process.

3. Post-sequencing analysis

  1. System requirements
    NOTE: Guide for setting up the environment and analyzing Mycobacterium tuberculosis amplicon sequencing data using the ONT-TB-NF pipeline. The instructions cater to both Windows (via WSL) and macOS users.
    1. Use the following - Operating System: Windows 10/11 (with WSL2) or macOS; Memory: Minimum 8 GB RAM (16 GB recommended); Storage: At least 50 GB of free disk space; Internet: Required for downloading packages and data; Permissions: Ability to install software and manage environments.
  2. Ensure the following environment setup: Windows Users (Using WSL2). Enable WSL2.
    1. Open PowerShell as Administrator and run: wsl - install.
    2. Restart the computer when prompted.
  3. Install Ubuntu
    1. After restarting, launch the Microsoft Store, search for Ubuntu, and install the preferred version (e.g., Ubuntu 22.04 LTS).
    2. Launch Ubuntu from the Start Menu.
    3. Create a new UNIX username and password when prompted.
    4. Update package Lists: sudo apt update && sudo apt upgrade -y.
  4. macOS Users
    1. Install Homebrew (if not already installed): /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)".
    2. Install required packages: brew install git wget
  5. Installing Conda or Mamba
    1. Visit the Miniconda download page to download the correct installer for the operating system.
    2. To install Miniconda, run the installer and follow the on-screen instructions. After the installation is complete, please restart the terminal.
    3. Configure Conda Channels:
      conda config --add channels defaults
      conda config --add channels bioconda
      ​conda config --add channels conda-forge
    4. Installing Mambaforge (Mamba)
      For Linux:
      wget
      https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh
      For macOS:
      wget https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-MacOSX-arm64.sh
    5. Install Mambaforge: bash Mambaforge-*.sh
    6. Follow the prompts to complete the installation, and restart your terminal to activate Mamba.
  6. Setting up the ONT-TB-NF pipeline
    1. Create a new Conda environment: conda create -n ont_tb_env samtools=1.15.1 minimap2=2.24 nanoplot=1.40.2 mosdepth=0.3.3 flye=2.9.1 nanofilt fastqc bedtools -c bioconda
    2. Alternatively, use Mamba: mamba create -n ont_tb_env samtools=1.15.1 minimap2=2.24 nanoplot=1.40.2 mosdepth=0.3.3 flye=2.9.1 nanofilt fastqc bedtools -c bioconda
    3. Activate the environment: conda activate ont_tb_env
    4. Install Nextflow: curl -s https://get.nextflow.io | bash, sudo mv nextflow /usr/local/bin/
    5. Clone the ONT-TB-NF repository: git clone https://github.com/HKU-BAL/ONT-TB-NF.git
      cd ONT-TB-NF
    6. Pull Required Docker Images (if using Docker)
      docker pull hkubal/clair3:v0.1-r12
      ​docker pull quay.io/biocontainers/tb-profiler:4.3.0--pypyh5e36f6f_0
  7. Running the pipeline
    1. Concatenate each samples's Basecalled FASTQ files independently using the following command.
      cat *.fastq.gz > concatenated.fastq.gz
      nextflow run run_tb_amplicon.nf \
      read_fq /path/to/concatenated.fastq.gz \
      sample_name SAMPLE_ID \
      amplicon_bed /path/to/amplicon_regions.bed \
      threads 16 \
      ​output_dir /absolute/path/to/output_directory
  8. Output files and interpretation
    1. Upon successful execution, ensure that the pipeline generates the following outputs in the specified output directory:
      1. Aligned Reads: *.bam files.
      2. Variant Calls: *.vcf files containing SNPs and indels.
      3. Summary Reports: *.csv or *.tsv files summarizing drug resistance mutations and other relevant metrics.
      4. Quality Control Reports: *.htmL files generated by tools like MultiQC.
      5. Logs: Detailed logs of the pipeline execution.
      6. Intermediate Files: Stored in the work/ directory (can be deleted after successful run).
        NOTE: In the event of encountering permission errors, it is essential to verify that one possess the necessary permissions to read and write files, as well as to execute scripts. Regarding environmental issues, please ensure that the appropriate Conda environment is activated prior to executing the pipeline. For those utilizing Docker profiles, it is imperative to confirm that Docker is both installed and operational. Additionally, one must monitor system resources meticulously to avert any memory or storage limitations during execution. An overview of these methodologies is presented in Figure 1.

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Results

The selected DNA extraction method was chosen for its efficiency and superior yield compared to other rapid techniques. It consistently produced high-quality genomic DNA (gDNA), and integrating a bead-based cleanup step helped minimize processing time while reducing per-sample costs. This was achieved by eliminating the need for additional quality control assessments such as spectrophotometric measurements, with fluorometry as the sole DNA quantification tool. Post-PCR concentrations were found to be optimal for sequenci...

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Discussion

The long-read sequencing platform demonstrated notable advantages in this study, particularly its ability to achieve rapid sequencing with consistently high coverage breadth. Across all successfully sequenced isolates, a coverage breadth of 99.9% was achieved, indicating near-complete representation of resistance-associated genomic regions. The average coverage depth across all targeted genes was 4462X, with the eis gene showing the highest depth at 22,242.08X and the rrs gene the lowest at 99.46X. Thes...

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Acknowledgements

We would like to express our sincere gratitude to the SAMRC Centre for Tuberculosis at Stellenbosch University for providing the essential resources and facilities. We are also deeply thankful to the TS ELiOT Study for supplying the samples that were integral to this study.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
15 mL & 1.5 mL or 2 mL Lo-binding TubesEppendorfEP0030108051-250EA
1kb ladderThermo Fisher ScientificSM0311
2 mL screw cap TubesScientific Specialties IncP2TUB056C-0001.5ST
2 mm sterile glass beadsSigma-AldrichZ273627-1EA
AMPure XP BeadBeckman ColterA63881
Deeplex Myc-TB GenoScreen20090205
Electrophoresis chamberThermo Fisher ScientificA25977
Ethyl alcohol, PureSigma-AldrichE7023-500ML
FastPrep HomogenizerMP Biomedicals116005500
Filter pipette tips (10 µL) Bio-Smart ScientificFT-10-R
Filter pipette tips (1000 µL) Bio-Smart ScientificFT-1000-R
Filter pipette tips (20 µL) Bio-Smart ScientificFT-20-R
Filter pipette tips (200 µL) Bio-Smart ScientificFT-200-R
Flow-cell Oxford Nanopore TechnologiesFLO-MIN114
Heating-blockEppendorf5382000031
InstaGene MatrixBio-RadBBRD7326030
Magnetic Rack Thermo Fisher Scientific 12321D
MicrocentrifugeEppendorf 5406000046
MinIONOxford Nanopore TechnologiesMK1B
Native-barcoding kit V14 Oxford Nanopore TechnologiesSQK-NBD114.24
NEB Blunt/TA Ligase Master MixNEBM0367
NEBNext Quick Ligation ModuleNEBE6056
NEBNext Ultra II End repair/dA-tailing ModuleNEBE7546
Nuclease-free water (NFW)Thermo Fisher ScientificAM9937
Pipettes (P10, P20, P200 and P1000)EppendorfEP3123000918-1EA
Qubit Assay TubesThermo Fisher ScientificQ32856
Qubit dsDNA HS Assay KitThermo Fisher ScientificQ33231
Qubit fluorometerThermo Fisher ScientificQ33226
SYBR Safe DNA gel StrainThermo Fisher ScientificS33102
UltraPure AgaroseThermo Fisher Scientific17852
Universal Hood III transilluminator (Molecular Imager Gel Doc XR System)Bio-Rad170-8170
Vortex mixerLasecWMBB0L0E0216

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Drug Resistant TuberculosisTargeted NGSPortable SequencingDNA Library PreparationResistance Variant DetectionFlow Cell PrimingGel ElectrophoresisBioinformatics Pipeline

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