Biology subjects

Mertens, S.

Publications and source records attributed to Mertens, S..

4 recordsLinked to original sources

bioRxiv2026

Fourier transform infrared spectroscopy reveals high intraspecies diversity of Malassezia pachydermatis in dogs with atopic dermatitis

1Canine atopic dermatitis (CAD) is a chronic inflammatory skin condition sometimes associated with microbial dysbiosis, including alterations in colonization by the lipophilic yeast Malassezia pachydermatis. This study investigated the population diversity of M. pachydermatis in the ear canals of healthy and CAD-affected dogs using Fourier-transform infrared (FTIR) spectroscopy and whole genome sequencing (WGS). Among 60 dogs, M. pachydermatis prevalence was significantly higher in CAD cases than in healthy controls. FTIR spectroscopy revealed greater strain heterogeneity in CAD-affected dogs, often with distinct genotypes in each ear, while healthy dogs exhibited more homogeneous populations. Using a previously developed FTIR-based artificial neural network classifier, we assigned strains to three phylogroups. Strains from phylogroups I and III were significantly enriched in CAD-affected dogs, while phylogroup II was most prevalent overall and the dominant phylogroup in healthy controls. This suggests that CAD-associated inflammation may favor specific M. pachydermatis phylogroups and sub-clusters within phylogroups, shaping colonization dynamics. FTIR-based typing showed full concordance with WGS across 35 sequenced isolates, recapitulating relationships among phylogenetically related isolates and their similar phenotypic profiles. Overall, our findings reveal strain-level shifts in M. pachydermatis populations associated with CAD and establish FTIR spectroscopy as a rapid, cost-effective tool for large-scale epidemiological studies.

microbiology↗

bioRxiv2025

Genome-guided manipulation of regulators of morphogenesis in a C. albicans strain with low virulence is not sufficient to trigger a high-virulence phenotype

As a member of the microbiome, C. albicans colonizes the oral cavity and other mucosal surfaces of the human body. While commensalism is tightly controlled by the host immune system, the fungal determinants enabling the fungus to colonize the host mucosa without causing tissue damage and inflammation remain less clear. In search of genetic determinants that may underly the commensal lifestyle of the low-virulent C. albicans isolate 101, we identified a small sequence duplication in one of the BRG1 allele resulting in a truncated loss-of-function allele (BRG1TRUNC). Replacing BRG1TRUNC by the full-length allele (BRG1FL) resulted in a modest increase in filamentation, but did not alter the phenotype of the fungus in the oral mucosa of experimentally colonized mice. Spontaneous outgrowth of highly virulent variants of the 101 strain with the BRG1TRUNC alleles replaced by a full-length allele identified the Cyr1-cAMP-PKA signalling pathway as a modulator of fungal virulence. Although the Glu-to-Lys mutation in CYR1 (CYR1E1541K), which converts Cyr1 into a hyperactive adenylate cyclase, greatly increased filamentation, the expression of hyphae-associated genes, and host cell damage when tested in vitro, it was insufficient to increase virulence of C. albicans strain 101 in the oral mucosa in vivo, irrespective of the BRG1 status. Together, this highlights that the low-virulent nature of strain 101 is firmly anchored and cannot be overcome by manipulating BRG1 and CYR1, two genes with known roles in C. albicans virulence. IMPORTANCEDuring homeostasis, the fungus Candida albicans establishes mutualistic interactions with its human host. It can however also adopt a pathogenic state and cause infections with diverse clinical manifestions that pose a significant challenge for diagnosis and therapy. Understanding the fungal determinants that underlie C. albicans colonization under steady state conditions may thus provide new avenues for modulating the fungus-host interaction in candidiasis patients to restore homeostasis. Here, we report gene variants that distinguish high-virulent from low-virulent C. albicans. Gene-exchange mutants provided evidence for the contribution of a BRG1 loss-of-function allele and a CYR1 gain-of-function mutation toward fungal pathogenicity. However, in vivo in an experimental model of C. albicans oral colonization, none of these gene variants individually or in combination were sufficient to change the virulence profile of the fungus. These findings indicate that C. albicans mucosal colonization is regulated by a complex gene network rather than by single genetic determinants.

microbiology↗

bioRxiv2025

High-resolution transcriptional atlas of growing maize shoot organs throughout plant development under well-watered and drought conditions

Crop improvement goals for maize (Zea mays L.) involve the targeted optimization of various organs, making it crucial to understand the developmental characteristics and gene expression patterns during organ development and in response to environmental stresses such as drought. In this study, we investigated the development of maize leaves and internodes at both macroscopic and cellular level, and identified a shared fundamental growth design with distinct timing between the two organs. By transcriptome profiling developmental zones of leaves and internodes of different ranks, and of the ear, at different growth stages under both well-watered and drought conditions, we generated a high-resolution spatiotemporal transcriptome dataset on 272 different tissues and conditions, which we make available as a searchable database. While the gene regulatory networks governing cell division and cell elongation were highly conserved across organs, precise expression regulation of particular gene families was observed across organs and within the same organ. Additionally, we highlight the expression of key genes involved in regulating leaf angle and vascular development, showing spatiotemporal regulation of differentiation parallel to growth. This comprehensive expression atlas, combined with phenotypic data, offers a deeper understanding of the similarities and differences among shoot organs and tissues during development and drought response, and provides a valuable resource for engineering organ-specific traits in maize.

plant biology↗

bioRxiv2023

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BackgroundThermography is a popular tool to assess plant water use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect drought stress. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. ResultsThe sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic difference in the plants water use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple thermal infrared indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. ConclusionOverall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

plant biology↗