Published in PLOS One on 2026-09-17, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Marius P Ngouanom Kuate, Kesini Ramkumar, Jezreel Dalmieda, Javeriya Nadeem, Javid Hemmati, Celine N Nkenfou, Roland N Ndip, Jianping Xu, Katherine Borkovich
Source: PLOS One • DOI 10.1371/journal.pone.0355362
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Aspergillus flavus is a ubiquitous fungus commonly found in a variety of ecological niches including soil, crops, the air, and humans. In humans, it is the second leading cause of invasive aspergillosis (IA) and is linked to other illnesses through contamination of agricultural products with aflatoxins. As such, A. flavus threatens food safety, economic wellbeing, and human health, particularly in less developed regions and countries such as Cameroon. To mitigate these effects, farmers and clinicians rely on triazoles to reduce aflatoxin contamination and treat IA. However, a consequence of increasing triazole use is the emergence and spread of triazole resistance in both agriculture and clinics. To identify the prevalence of triazole resistance and the potential genetic relationships among triazole resistant and susceptible strains, this study investigated antifungal susceptibility to both clinical and agricultural triazoles and analyzed genetic variation among various ecological niche populations of A. flavus in Cameroon. Strain genotypes were obtained through analysis of six polymorphic microsatellite markers. Our analyses revealed that 30.3% (17/56) of the strains were resistant to at least one of the four triazoles, with increased minimum inhibitory concentrations found among crop-isolated strains. A Permutational Multivariate Analysis of Variance suggested limited ecological niche-based clustering of genotypes, consistent with frequent gene flow and dispersal among ecological niches. A multilocus linkage disequilibrium analysis revealed evidence of non-random recombination in A. flavus. Overall, this study elucidates the interplay between ecological pressures, antifungal resistance, and genetic differentiation, and invites alternative methods to control aflatoxin contamination in foods without the use of agricultural fungicides.
Introduction
Aspergillus flavus is a ubiquitous, filamentous mold and a significant threat to humans through both food contamination and human infection [1]. It is a notorious producer of highly potent, polyketide-derived hepatocarcinogenic aflatoxins that contaminate staple crops including maize and groundnuts [2]. Chronic exposure to these aflatoxins is associated with liver cancer, immunosuppression, and other health problems [3]. The contamination of agricultural products threatens food safety and economic wellbeing, especially in sub-Saharan Africa, where up to 40% of agricultural production was lost in some regions each year due to aflatoxin contamination, corresponding to ~US $450 million [4]. In addition, A. flavus is the second leading cause of invasive aspergillosis (IA), an often-fatal fungal infection in immunocompromised individuals [5]. Environmental conditions such as high temperature and humidity facilitate growth of A. flavus and consequently, crop contamination [6]. Thus, it is imperative to investigate A. flavus populations in regions where the species is particularly prevalent, such as parts of Africa, Asia, and the Middle East, to elucidate important characteristics like genetic structure and antifungal resistance [5]. As A. flavus is a saprotrophic organism that can produce airborne conidia, it occupies a wide range of ecological niches that provide unique environmental pressures, potentially influencing variations in antifungal susceptibility and genetic diversity [7].
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider research & evidence desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Marius P Ngouanom Kuate, Kesini Ramkumar, Jezreel Dalmieda, Javeriya Nadeem, Javid Hemmati, Celine N Nkenfou, Roland N Ndip, Jianping Xu, Katherine Borkovich. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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