Candida auris, a multidrug-resistant fungal pathogen, is a global threat. It’s highly transmissible, persistent in healthcare environments, and can cause significant mortality rates among vulnerable patient groups.

Now, recent research has uncovered a new, sixth clade of C. auris in Singapore. This means the pathogen is more diverse (and possibly more dangerous) than we knew — posing more problems for health officials worldwide.

Candida was only first identified in 2009. It is, to put it simply, a very, very resilient fungus. It can withstand almost everything we throw at it. It’s particularly dangerous in hospital settings, where it can persist on surfaces and spread easily among patients. The World Health Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC) have both classified C. auris as a serious threat.

In a recent study published in Lancet Microbe, researchers from the Genome Institute of Singapore and various Singaporean hospitals characterized three unusual C. auris samples from unlinked inpatients at a large hospital in Singapore. Whole-genome sequencing (WGS) and hybrid assemblies revealed that these samples were genetically distinct from all known C. auris clades (I-V), suggesting the presence of a new clade. A clade is essentially a group of organisms with a common ancestor — a single branch on the tree of life.

“The implications of this discovery extend far beyond the laboratory. Now that we have discovered the sixth Candida auris clade, there is a pressing need to improve surveillance capability or develop new methods to augment current surveillance strategies so that healthcare facilities can keep a close watch on its emergence and contain the spread once found,” said Dr. Karrie Ko, co-first author of the study. She is also Consultant, Department of Microbiology, SGH, and Genomics Director of the Pathology Academic Clinical Program under SingHealth and Duke-NUS Medical School.

Surveillance for pathogens

Singapore Hospital has an active surveillance system for Candida, where high-risk patients are tested. Patients who test positive are isolated and screened as part of the hospital’s strategy to contain the spread. This program uncovered the new clade with the aid of a newly-developed machine learning algorithm. The same algorithm scanned external databases and found another sample belonging to this clade in Bangladesh.

“This study demonstrated that the machine learning approach can improve surveillance capabilities by automatically detecting unusual outlier genomes. Our human-in-the-loop machine learning workflow facilitates continuous learning from new data, so that we can detect and investigate potential novel genomes as early as possible. This has the potential to strengthen surveillance against emerging public health threats,” said co-first author of the study, Dr. Chayaporn Suphavilai, Senior Scientist, A*STAR’s GIS.

It’s unclear how much of a threat this new clade is, but discovering it is the first step towards understanding it better.

We’ve only known about this pathogen for a few years and there’s plenty we haven’t uncovered about it. However, given the propensity of C. auris for multidrug resistance and healthcare-associated outbreaks, the study emphasizes the need for rigorous surveillance and containment strategies. Effective sequencing and analysis are vital for identifying novel strains and mitigating the clinical impact of C. auris infections.

Ultimately, the identification of a sixth clade of Candida auris in Singapore shows there’s much we need to figure out about the pathogen’s genetic diversity. This discovery calls for heightened surveillance and innovative genomic tools to combat the ongoing threat posed by C. auris, particularly in regions with limited resources.

The war against Candida is in full swing, and our detection systems are getting better at spotting it it.

Journal Reference: Chayaporn Suphavilai et al, Detection and characterisation of a sixth Candida auris clade in Singapore: a genomic and phenotypic study, The Lancet Microbe (2024). DOI: 10.1016/S2666-5247(24)00101-0