Biology subjects

Schaefer, K. G.

Publications and source records attributed to Schaefer, K. G..

2 recordsLinked to original sources

bioRxiv2024

A genome-scale screen identifies sulfated glycosaminoglycans as pivotal in epithelial cell damage by Candida albicans

Candidalysin is a cytolytic peptide produced by the opportunistic fungal pathogen Candida albicans. This peptide is a key virulence factor in mouse models of mucosal and hematogenously disseminated candidiasis. Despite intense interest in the role of candidalysin in C. albicans pathogenicity, its host cell targets have remained elusive. To fill this knowledge gap, we performed a genome-wide loss-of-function CRISPR screen in a human oral epithelial cell line to identify specific host factors required for susceptibility to candidalysin-induced cellular damage. Among the top hits were XYLT2, B3GALT6 and B3GAT3, genes that function in glycosaminoglycan (GAG) biosynthesis. Deletion of these genes led to the absence of GAGs such as heparan sulfate on the epithelial cell surface and increased resistance to damage induced by both candidalysin and live C. albicans. Biophysical analyses including surface plasmon resonance and atomic force and electron microscopy indicated that candidalysin physically binds to sulfated GAGs, facilitating its oligomerization or enrichment on the host cell surface. The addition of exogenous sulfated GAGs or the GAG analogue dextran sulfate protected cells against candidalysin-induced damage. Dextran sulfate, but not non-sulfated dextran, also inhibited epithelial cell endocytosis of C. albicans and fungal-induced epithelial cell cytokine and chemokine production. In a murine model of vulvovaginal candidiasis, topical dextran sulfate administration reduced host tissue damage and decreased intravaginal IL-1{beta} and neutrophil levels. Collectively, these data indicate that GAGs are epithelial cell targets of candidalysin and can be used therapeutically to protect cells from candidalysin-induced damage.

microbiology↗

bioRxiv2024

PS Poly: A chain tracing algorithm to determine persistence length and categorize complex polymers by shape

The fundamental molecules of life are polymers. Prominent examples include nucleic acids and proteins, both of which exhibit a large array of mechanical properties and three-dimensional shapes. The bending rigidity of individual polymers is quantified by the persistence length. The shape of a polymer, dictated by the topology of the polymer backbone, a line trace through the center of the polymer along the contour path, is also an important characteristic. Common biomolecular architectures include linear, cyclic (ring-like), and branched structures; combinations of these can also exist, as in complex polymer networks. Determination of persistence length and shape are largely informative to polymer function and stability in biological environments. Here we demonstrate Persistence length Shape Polymer (PS Poly), a near-fully automated algorithm designed to obtain polymer persistence length and shape from single molecule images obtained in physiologically relevant fluid conditions via atomic force microscopy. The algorithm, which involves image reduction via skeletonization followed by end point and branch point detection, is capable of rapidly analyzing thousands of polymers with subpixel precision. Algorithm outputs were verified by analysis of deoxyribonucleic acid, a very well characterized macromolecule. The method was further demonstrated by application to candidalysin, a recently discovered and complex virulence factor from Candida albicans. Candidalysin forms polymers of highly variable shape and contour length and represents the first peptide toxin identified in a human fungal pathogen. PS Poly is a robust and general algorithm. It can be used to extract fundamental information about polymer backbone stiffness, shape, and more generally, polymerization mechanisms.

biophysics↗