Near-Infrared Spectroscopy as a Diagnostic Screening Tool for Lethal Chytrid Fungus in Eastern Newts

Authors

• Li Dunn Chen, Mississippi State University
• Edward D. Carter, The University of Tennessee, Knoxville
• Merrie P. Urban, The University of Tennessee, Knoxville
• Carmen T. Merolle, The University of Tennessee, Knoxville
• Devin M. Chen, Mississippi State University
• Andrew J. Kouba, Mississippi State University
• Matthew J. Gray, The University of Tennessee, Knoxville
• Debra L. Miller, The University of Tennessee, Knoxville
• Carrie K. Kouba, Mississippi State University

ORCID

LChen: https://orcid.org/0000-0002-9653-9814; Carter: https://orcid.org/0000-0001-6187-9010; DChen: https://orcid.org/0000-0001-6418-3801; Gray: https://orcid.org/0000-0001-8243-9217; Miller: https://orcid.org/0000-0002-8544-174X; CKouba: https://orcid.org/0000-0001-8466-6077

MSU Affiliation

College of Agriculture and Life Sciences; Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology; College of Forest Resources; Department of Wildlife, Fisheries and Aquaculture

Creation Date

2026-10-30

Abstract

The emergence of Batrachochytrium salamandrivorans (Bsal) poses an imminent threat to caudate biodiversity worldwide, particularly through anthropogenic-mediated means such as the pet trade. Bsal is a fungal panzootic that has yet to reach the Americas, Africa, and Australia, presenting a significant biosecurity risk to naïve amphibian populations lacking the innate immune defenses necessary for combating invasive pathogens. We explored the capability of near-infrared spectroscopy (NIRS) coupled with predictive modeling as a rapid, non-invasive Bsal screening tool in live caudates. Using eastern newts (Notopthalmus viridescens) as a model species, NIR spectra were collected in tandem with dermal swabs used for confirmatory qPCR analysis. We identified that spectral profiles differed significantly by physical location (chin, cloaca, tail, and foot) as well as by Bsal pathogen status (control vs. exposed individuals; p < 0.05). The support vector machine algorithm achieved a mean classification accuracy of 80% and a sensitivity of 92% for discriminating Bsal-control (-) from Bsal-exposed (+) individuals. This approach offers a promising method for identifying Bsal-compromised populations, potentially aiding in early detection and mitigation efforts alongside existing techniques.

Publication Date

4-17-2025

Publication Title

Communications Biology

Publisher

Nature Research

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Rights

© The Author(s) 2025

Recommended Citation

Chen, LD., Carter, E.D., Urban, M.P. et al. Near-infrared spectroscopy as a diagnostic screening tool for lethal chytrid fungus in eastern newts. Commun Biol 8, 625 (2025). https://doi.org/10.1038/s42003-025-08025-8