Justin O’Grady
Professor Justin O’Grady on using a targeted nanopore sequencing-based method to rapidly detect drug-resistant tuberculosis

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Drug resistance is a huge hurdle to reducing the spread of tuberculosis (TB), the world’s deadliest infectious disease. An estimated 10 million cases and more than 1.6 million deaths are attributed to TB each year. The greatest impediment to treatment and prevention efforts is drug resistant TB (DR-TB).

There are half-a-million cases of multi-drug resistant TB (MDR-TB) annually, and more than 6% of these cases are now classified as extremely drug resistant (XDR-TB). All of them are very difficult to cure. TB is most prevalent in middle- and Southern-Africa, but most instances of new TB cases with drug resistance, including XDR-TB, occur in Russia, China and India.

Justin O’Grady, a senior lecturer at University of East Anglia, UK, is using nanopore sequencing to develop new ways to identify and track TB and has been able to develop a rapid and accurate test to detect DR-TB. He says that nanopore sequencing using Oxford Nanopore’s MinION platform is “flexible and cost-effective and very easily deployable.”

Seq & Treat

Next-generation sequencing (NGS) has great potential for rapidly diagnosing DR-TB. “TB takes a long time to grow,” in culture, O’Grady says, and that process doesn’t always result in an accurate means of determining resistance to antibiotics. NGS is more comprehensive than current rapid tests, which only look at a limited set of targets across the genome. Nonetheless, uptake of sequencing can be hindered by concerns regarding its cost, integration into existing lab workflows, skills required for using the technology, and management and interpretation of the sequencing data.

A world map of MDR/DR-TB cases tested for susceptibility to second-line drugs, O’Grady points out, shows how well-financed places are performing tests for TB identification, but they aren’t doing enough testing for second-line resistance in locations with MDR-TB or XDR-TB. To address this issue, the Seq & Treat programme was started as a joint effort by the Foundation for Innovative New Diagnostics (FIND) and Unitaid. The goal is to evaluate the use of targeted NGS (tNGS) for diagnosis of DR-TB in low- to middle-income countries by generating clinical evidence to support WHO guidance for the use of targeted sequencing for DR-TB identification.

This process involves evaluating the performance of existing tNGS methods, with the aim of integrating selected tests into established diagnostic workflows globally in the near future.

The programme requires a test for DR-TB to fulfil the following criteria:

  • >98% specificity and sensitivity for drug resistance detection;
  • 100-5,000 CFU/ml as the limit of detection;
  • detection of hetero-resistance from 1–10% (equal to 10 resistant reads in 100-1,000 reads, and 500 resistant bacteria in 4,500);
  • minimal cross reactivity with non-tuberculous mycobacteria (NTM); and
  • <5% indeterminate results.

O’Grady has been working to devise a test to fulfil these criteria using the Oxford Nanopore MinION. The MinION offers: easy deployment globally at low cost; real-time analysis and rapid turnaround of results; flexible sample numbers (depending on the size of the sequencing facility and the number of samples); and low cost-per-sample ($15 per sample at 80 samples/flow cell, which is the output they are aiming for).

The workflow for nanopore sequencing and turnaround involves 1 hour of DNA extraction, a 17-target PCR (2.5 hours), library preparation (4.5 hours for many samples, using the Ligation Sequencing Kit and PCR barcoding expansion), MinION sequencing overnight, (although “if you have twelve you could do this in a few hours,” he says), and finally, analysis using the EPI2ME workflow to investigate the TB resistance profile. The 17 targets examined are associated with both first- and second-line drug resistance. In all, the workflow time ranges from 9-24 hours, depending on how many samples are being run.

By the Numbers

In terms of sequencing metrics, O’Grady’s team have designed the primers to have an average read length of ~1 kb, which typically have a quality score around 10. The mean depth of coverage achieved is ~12,871x (range 2,382x – 28,301x). O’Grady says that he would like the depth of coverage to be more even across the 17 targets, but considering it took some time to get a few of the targets working, he says, “we can live with that.”

By performing serial dilutions, the limit of detection was determined between~10–100 cells per ml (>50x coverage), or about 10x depth of coverage on the 10-cell equivalent. O’Grady says he was “very pleased” that the primers were working down to such low concentrations of DNA.

To establish the test’s specificity, O’Grady has used the test on clinical sputum containing a range of mycobacterial species and compared the results with publicly available non-tuberculous mycobacteria (NTM) FastQ datasets. O’Grady says that 15/17 assay targets were consistently specific for MTB members. (the two exceptions target 16S and 23S rDNA, O’Grady isn’t too concerned about this lower specificity for these targets.)

The resistance profile of TB samples is accurately predicted using the EP2ME TB analysis tool which identifies SNPs in the target amplicons known to cause drug resistance.

O’Grady says his team now plans to test their method on about 400 well-defined sputum samples, provided by FIND, to define clinical performance. These samples contain varying levels of TB bacteria, different resistance phenotypes and genotypes, as well as other bacteria.

“We have got to see if we can find all that,” he says. The test will proceed to a global trial if performance is sufficiently promising.

 

Watch Justin’s full talk nanoporetech.com/justinogrady

…or read more about O’Grady’s research on metagenomic sequencing for rapid investigation of bacterial lower respiratory tract infections: nanoporetech.com/ogradypublication

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