Diagnosing brain infections using metagenomics

22 June 2016

Proof of concept study applies next generation sequencing and metagenomics to successfully diagnose brain infections. 

Finding the cause of central nervous system inflammation is particularly difficult – more than 50% of cases go undiagnosed. Now a pilot study from experts at Johns Hopkins Medicine has shown that next generation sequencing and metagenomics can be used to identify the cause. 

The team sequenced biopsy samples from ten patients with symptoms of brain infection, then used a computer to remove the human DNA sequences, comparing the remainder to a database of known pathogenic genomes. The minimum time for sequencing was a day, whilst computer analysis took an hour per patient. 

In three patients they found mycobacterium tuberculosis, which sometimes infects the brain. In another they confirmed the presence of JC Polyomavirus and in a fifth sequencing identified Epstein Barr virus. Their findings were supported by traditional pathology, allowing the patients to be treated. Results for a sixth patient were inconclusive, but re-analysis a year later revealed a previously unknown pathogen Elizabethkingia, which, following an outbreak had been sequenced and added to the database. 

For the remainder, the results were indefinite, but still informative: the ruling out of specific pathogens may mean infection is not present, thereby suggesting other treatment options, as was the case for three of the patients in the study. As co-author on the study Steven Salzberg, Ph.D noted “one of the limitations of using this kind of diagnostic tool is that we can only identify the pathogens for which we have the genetic sequences available...As we continue to sequence the genomes of more organisms the tool will become more powerful”. 

Carlos Pardo-Villamizar, associate professor of neurology at Johns Hopkins said “we hope to develop this technique further as a way to bring the diagnosis rate of inflammatory brain disorders and infections closer to 100 percent so we can treat patients more effectively”.

More from us

Genomics and policy news