Multi-omics Signature of Candida auris , an Emerging and Multidrug-Resistant Pathogen
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Abstract
Abstract Candida auris is a recently described pathogenic fungus that is causing invasive outbreaks on all continents. The fungus is of high concern given the numbers of multidrug-resistant strains that have been isolated in distinct sites across the globe. The fact that its diagnosis is still problematic suggests that the spreading of the pathogen remains underestimated. Notably, the molecular mechanisms of virulence and antifungal resistance employed by this new species are largely unknown. In the present work, we compared two clinical isolates of C. auris with distinct drug susceptibility profiles and a Candida albicans reference strain using a multi-omics approach. Our results show that, despite the distinct drug-resistance profile, both C. auris strains appear to be very similar, albeit with a few notable differences. However, when compared to C. albicans both C. auris strains have major differences regarding their carbon utilization and downstream lipid and protein content, suggesting a multi-factorial mechanism of drug resistance. The molecular profile displayed by C. auris helps to explain the antifungal resistance and virulence phenotypes of this new emerging pathogen. Importance Candida auris was firstly described in Japan in 2009 and has now been the cause of significant outbreaks across the globe. The high number of isolates that are resistant to one or more antifungals, as well as the high mortality rates from patients with bloodstream infections, has caught the attention of the medical mycology, infectious disease and public health communities to this pathogenic fungus. In the current work, we performed a broad multi-omics approach on two clinical isolates isolated in New York, the most affected area in the USA and found that the omic profile of C. auris differs significantly from C. albicans . Besides our insights into C. auris carbon utilization and lipid and protein content, we believe that the availability of these data will enhance our ability to combat this rapidly emerging pathogenic yeast.
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Clinical features of C. auris infections include biofilm persistence on abiotic surfaces and skin, immune evasion, and antifungal drug resistance.
“The clinical features of these infections include biofilm persistence on abiotic surfaces and skin, immune evasion, and antifungal drug resistance (7–12).”
From Dual function of <i>Candida auris</i> mannosyltransferase, MNT5, in biofilm community protection from antifungal therapy and the host (2025) · cites this paper as [8]
The Introduction reports C. auris on abiotic surfaces, biofilm production, resilience on hospital substrates, and antifungal resistance; the Results section on antifungal resistance documents a resistant clinical isolate. Our copy does not establish biofilm persistence on skin or immune evasion as features of C. auris infection. (LLM, conf=0.87)
Experimental — accuracy not yet measuredC. auris metabolism is likely to favour respiration because proteomic profiling demonstrated relative enrichment of TCA cycle and decreased glycolysis proteins compared to C. albicans.
“C. auris metabolism is likely to favour respiration because proteomic profiling demonstrated relative enrichment of tricarboxylic acid (TCA) cycle and decreased glycolysis proteins compared to C. albicans [60].”
From Lansoprazole interferes with fungal respiration and acts synergistically with amphotericin B against multidrug-resistant <i>Candida auris</i> (2024) · cites this paper as [60]
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- Authors
- Zamith-Miranda, D., Heyman, H. M., Cleare, L. G., Couvillion, S. P., Clair, G. C., Bredeweg, E. L., Gacser, A., Nimrichter, L., Nakayasu, E. S., & Nosanchuk, J. D.
- Affiliations
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York, USA
- Pacific Northwest National Laboratory (US)
- Albert Einstein College of Medicine (US)
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
- Department of Microbiology, Interdisciplinary Excellence Centre, University of Szeged, Szeged, Hungary
- Universidade Federal do Rio de Janeiro (BR)
- Corresponding author
- Nosanchuk, Joshua D.
- ORCID
- Venue
- mSystems
- Publisher
- American Society for Microbiology
- Published
- 2019-08-27
- Volume
- 4
- Issue
- 4
- ISSN
- 2379-5077 (ISSN-L)
- PMC
- PMC6561322
- OpenAlex
- W2950798794
- Cited by
- 99
- References
- 61
- Citations by year
- 2026: 10 · 2025: 14 · 2024: 13 · 2023: 8 · 2022: 16 · 2021: 15 · 2020: 20 · 2019: 3
- FWCI
- 10.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- mSystems (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- SZTE Publicatio Repozitórium (University of Szeged) (acceptedVersion, other-oa)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research, Development and Innovation Office (K 123952)
- GINOP (2-3-2-15-2016-00015, 2.3.3-15-2016-00006)
- Ministry of Human Capacities - Hungary (20391-3/2018/FEKUSTRAT)
- HHS | National Institutes of Health (R21 AI124797)
- Topics
- Health Sciences › Medicine › Infectious Diseases › Antifungal resistance and susceptibility
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Yeasts and Rust Fungi Studies
- Keywords
- Candida auris, Candida albicans, multidrug resistance, antifungal resistance, multi-omics, clinical isolates, carbon utilization, lipid content, protein content, emerging fungal pathogens, bloodstream infection, comparative genomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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