The research team: (from left) Dr Chayaporn Suphavilai, Ms Lim Kar Mun, Ms Tan Mei Gie, Associate Professor Niranjan Nagarajan and Dr Karrie Ko inspecting cultures of Candida auris // Credit: A*STAR’s Genome Institute of Singapore
Comparing the genome of our patient’s Candida auris against an international genome sequence database, we generated more than six million genome pairs, revealing six distinct genetic clusters: the five known clades and a new one.
We had indeed discovered a new variant, bringing the total number of Candida auris clades known globally to six.
By uncovering the new clade early, we can improve surveillance strategies to keep a close watch on its emergence and contain the spread.
If not for the mundane observation of the lack of recent travel history and a few usual traits, the new clade may have remained undetected even as it circulated, potentially developing into a silent outbreak.
Although our algorithm is still being tested, we showed that a machine learning approach can potentially be used to automatically classify microbial genomes.
This means that we can take a culture isolate from a patient sample and read the entire sequence of DNA inside it. We can then feed the microbial genomes into our model, which can automatically classify genomes, and flag any unusual clusters or outliers for further investigation.
This will help to provide early alerts for any suspicious genome clusters or novel genomes, and safeguard patients from public health threats.
Apart from this work on Candida auris, I am interested in deploying microbial genomics and metagenomics to improve infectious disease surveillance and diagnostics.
Metagenomic approaches save time by eliminating the need to grow the organism from the patient’s sample in a petri dish, which can be laborious and slow, before we can test what it is.
Unlike the targeted nature of polymerase chain reaction (PCR) tests, metagenomic approaches can read all the nucleic acid present in the patient’s sample in an untargeted manner—giving it the potential to detect thousands of pathogens in a single test.
Together with partners in the Genome Institute of Singapore and NUS Medicine, we are working to bring metagenomics into the clinical space.