Diagnostics for human pathogenic fungal infections: Current status and future prospects

Human fungal infections represent a rapidly emerging global health threat, especially among immunocompromised populations. Although generally harmless, certain fungi, particularly Candida spp., can develop into life-threatening systemic diseases when the immune defenses are weakened. Early diagnosis is critical for effective treatment, yet most existing diagnostic approaches lack the required sensitivity, specificity, or rapidity for clinical practice. Here, we review the recent progress in diagnostic methodologies, including serological assays, point-of-care diagnostics, polymerase chain reaction-based and sequencing technologies, as well as artificial intelligence (AI)- and machine learning (ML)-powered tools. We highlight the vital role of diagnostic technologies in profiling antifungal resistance, focusing on the challenges posed by drug-resistant strains such as Candida auris and Aspergillus fumigatus . We also address the hurdles involved in scaling these technologies and propose strategies for their implementation in both clinical settings and resource-limited environments. Finally, we discuss the future directions in diagnostics, specifically the development of multi-microbial tools for simultaneously detecting fungi, bacteria, and viruses. Further innovations in the diagnosis of human pathogenic fungal infections could increase the speed at which results are obtained and diagnostic accuracy, enabling the development of more targeted treatment strategies and ultimately improving patient outcomes.