NEW YORK (GenomeWeb) – In a step toward developing rapid sequencing-based pathogen diagnostics, researchers have demonstrated in a pilot study that Oxford Nanopore's MinIon device can be used to identify the causative pathogen and provide an antimicrobial resistance profile in patients with severe urinary tract infections.
The group, which presented early results of the pilot last year, published the results today in the Journal of Antimicrobial Chemotherapy.
The group is also moving ahead with developing tests for sepsis and respiratory infections and has developed proprietary technology for separating out host DNA from pathogen DNA, Justin O'Grady, an author of the study and senior lecturer in medical microbiology at Norwich Medical School, told GenomeWeb.
O'Grady added that the goal of the pilot was to demonstrate that the technology could identify the pathogen and antimicrobial resistance profile rapidly. Patients with severe urinary tract infections, particularly those who are at a high risk of developing sepsis, will often start an initial round of antibiotics and a second round eight hours later. "If you can provide pathogen identification and a resistance profile before the second dose of antibiotics is given, then you can have a true impact on treatment and the management of the patient," O'Grady said.
In the pilot study, the researchers analyzed clinical urine samples from 10 patients and five control samples that they spiked with multi-resistant Escherichia coli using metagenomic sequencing on the MinIon.
A key portion of the process is first removing human DNA, O'Grady said. In this study, the researchers used several commercially available processes. First they used centrifugation to remove human cells, followed by a lysis step that breaks up human cells and destroys their DNA. They then extracted and purified the bacterial DNA.
Out of the 10 clinical samples, the researchers identified the pathogen in six samples, although they noted that the first four samples failed due to technical issues that have since been improved upon. For instance, in one sample, human DNA was not sufficiently removed. In two other samples, the "flow cells were poor quality."
In the first four samples, the researchers were using Oxford Nanopore's R7.0 flow cell chemistry, but for the remaining samples, used the R7.3 chemistry. For all six of the clinical samples plus the five controls analyzed via the R7.3 technology, the researchers identified the pathogen and antimicrobial resistance genes. In addition, they were able to do so in clinically relevant turnaround times, eventually reducing sequencing time to one hour and total turnaround time to around four hours.
However, there were still a number of challenges with using the MinIon, particularly for identifying the resistance genes and the specific mutations within those genes. The researchers compared MinIon sequencing with Illumina sequencing and found that of 55 resistance genes that were identified by Illumina, 51 were found by MinIon. Three of the four genes the MinIon missed were in a sample with poor nanopore sequencing coverage.
The MinIon struggled to call specific resistance-conferring mutations, the researchers noted, or sometimes identified multiple potential variants, while Illumina sequencing was more definitive. In addition, the MinIon was not able to discern details of the ampC gene that can affect resistance. The gene can either be located on a plasmid, which is associated with resistance or on a chromosome, where resistance activity is less clear and depends on its level of expression. While the MinIon could identify if ampC was present, it could not distinguish whether the gene was located on a plasmid or chromosome, nor could it determine its level of expression.
O'Grady noted that the group has since upgraded to the R9 pore and flow cell chemistry and said that results have improved substantially. In this study, "our coverage wasn't sufficient in the time frame we had to call SNPs that are related to drug resistance," he said. "But, some of our latest results are generating large amounts of data really quickly … and with improved yields in a shorter time frame, we can get the coverage we need to SNP call."
For instance, he said, while with the previous technology it took about one hour to get 10x coverage, now the team can generate about 30x coverage in one hour, which provides enough coverage to SNP call.
O'Grady said that the researchers are continuing to work on the bioinformatics and test the assay in additional patient samples. Moving forward, however, he said that the lab plans to focus on developing similar tests for sepsis and respiratory tract infections, indications that he said would have a much greater clinical impact. He said that the team decided to start with urinary tract infections rather than sepsis, because analyzing pathogen DNA from a urine sample is much easier than from a blood sample because the ratio of human to bacterial DNA is so much higher in blood. The ratio of human DNA to bacterial DNA in a blood sample can be one billion to one, he said, but that can be about eightfold lower in a urine sample.
O'Grady said his team would publish a paper soon describing a protocol for sepsis diagnosis using the MinIon. In order to detect pathogen DNA present at such low frequencies, he said his team has been developing various methods for removing the host DNA from the sample. In the upcoming study, he said the group would demonstrate a technique that combined two commercially available approaches — immunomagnetic separation of white cells with the differential lysis of the remaining blood cells, followed by the digestion of that human DNA.
That "gives us good enrichment, but is cumbersome and expensive," O'Grady said. So, his team has also developed its own method. He did not provide details about that method because the group plans to apply for a patent on it, but said it would be as effective as the combination approach but quicker and less expensive.
O'Grady noted that one other hurdle of the test would be cost. Because speed was a priority, the researchers ran one sample on a flow cell, costing between $500 and $900 each. Depending on the situation, O'Grady said this cost could still be worthwhile. For instance, he said, the UTI test would likely only be cost effective for the sickest patients and those at risk of becoming septic. However, "for life-threatening conditions like sepsis or respiratory infections, the costs associated with these tests are affordable," he said.