bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.05.29.656872

Role of Pex31 in metabolic adaptation of the nucleus vacuole junction NVJ

Abstract

The nucleus vacuole junction NVJ in yeast is a multifunctional contact site between the nuclear ER membrane and the vacuole with diverse roles in lipid metabolism, transfer and storage. Adaptation of NVJ functions to metabolic cues is mediated by a striking remodeling of the size and the proteome of the contact site, but the extent and the molecular determinants of this plasticity are not fully understood. Using microscopy-based screens, we monitored NVJ remodeling in response to glucose availability. We identified Pex31, Nsg1, Nsg2, Shr5, and Tcb1 as NVJ residents. Glucose starvation typically results in an expansion of the NVJ size and proteome. Pex31 shows an atypical behavior, being specifically enriched at the NVJ at high glucose conditions. Loss of Pex31 uncouples NVJ remodeling from glucose availability, resulting in recruitment of glucose starvation-specific residents and NVJ expansion at glucose replete conditions. Moreover, PEX31 deletion results in alterations of sterol ester storage and a remodeling of vacuolar membranes that phenocopy glucose starvation responses. We conclude that Pex31 has a role in metabolic adaptation of the NVJ. SUMMARY STATEMENTUsing microscopy-based screens in yeast, we identified Pex31, Nsg1, Nsg2, Shr5 and Tcb1 as residents of the nucleus vacuole junction NVJ. Pex31 has a role in NVJ adaptation to glucose availability.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hugenroth, M., Höhne, P., Zhao, X.-T., Wälte, M., Diep, D. T. V., Fausten, R. M., Bohnert, M.. 2025-05-30. Role of Pex31 in metabolic adaptation of the nucleus vacuole junction NVJ. https://doi.org/10.1101/2025.05.29.656872

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Differential requirement for the Ire1 luminal domain in Candida albicans drug susceptibility and pathogenicity

The opportunistic human pathogen Candida albicans depends on the unfolded protein response (UPR) for cell wall integrity, antifungal tolerance, filamentous growth, and virulence. The UPR is driven by the conserved transmembrane sensor Ire1, which is activated either by misfolded proteins through its luminal domain or by lipid bilayer stress (LBS) through its transmembrane domain. In budding yeast, these two activation modes deploy divergent transcriptional programs. Whether the requirement for these two input domains is separable in C. albicans, where the cell membrane and cell wall are themselves the targets of major antifungal drug classes, remains unknown. Here, we engineered a C. albicans strain expressing Ire1 lacking an intact luminal domain (ire1{Delta}LD), which no longer detects proteotoxic stress. The ire1{Delta}LD strain grew in the presence of the azole antifungals fluconazole and miconazole but was highly sensitive to heat shock, cell wall stress, and the echinocandin caspofungin. It was also unable to sustain filamentous growth and showed reduced virulence in a Caenorhabditis elegans infection model. RNA sequencing revealed only modest changes to the steady-state transcriptome of ire1{Delta}LD cells. Together, these findings define a differential requirement for the input domains of C. albicans Ire1, uncoupling growth under azole-induced membrane stress from the cell wall, thermal, and virulence-associated outputs that depend on proteotoxic sensing, a distinction that could inform antifungal strategies targeting the UPR.

cell biology↗

Nucleosome Core Allostery Governs Chromatin Recognition and Cell Fate

Nucleosomes regulate chromatin folding, accessibility, and factor recruitment. Current models primarily attribute these functions to histone tail modifications, while the core is largely viewed as a structural scaffold. Yet subtle changes within the nucleosome core can produce profound functional consequences, and the mechanisms underlying these effects remain unclear. Here, we describe nucleosome core allostery as a fundamental principle of chromatin regulation that amplifies the impact of minimal nucleosome variations. Leveraging natural differences between H2A.Z variants, we show that the nucleosome core encodes distinct conformational dynamics that propagate allosterically, thereby controlling nucleosome accessibility and recognition by chromatin factors. As a result, a single buried amino acid substitution alone is sufficient to reprogram nucleosome dynamics and bias cell identity. Our findings establish the nucleosome core as an allosteric regulatory module and provide a generalizable framework for how subtle variation within nucleosomes is amplified into diverse biological outcomes in development and disease.

cell biology↗

A Novel Open-Source CellProfiler Pipeline for Automated, User-Friendly Hierarchical and K-Means Clustering of Microglial Morphology

Microglia represent a highly dynamic and heterogeneous cell type that is critically implicated in states of health and pathology. Microglial morphological subgroups have been identified that correspond to functional characteristics determining health-related outcomes. The identification of states based on morphological characteristics will therefore provide invaluable insights into the microglia-specific functional mechanisms driving treatment effects. The application of clustering analyses enables the detection of groupings within samples reflecting differences in morphological features. Here we propose the application of three custom-created modules to be used within the open-source software CellProfiler. These modules enable the automated detection of clusters present within the sample of microglia, as well as the assessment of the abundance of these clusters across conditions. The application of the analysis is conducted in a highly user-friendly manner, with a user interface integrated into the pipeline, enabling the performance of the analysis with only minimal user input. The workflow thereby includes the conduction of an outlier assessment, followed by hierarchical clustering and k-means clustering and the generation of interactive graphs to determine the number of microglia states present in the sample. Bar plots displaying the abundance of the microglia states across conditions included in the sample will be created. This approach will facilitate faster and more comparable detection of microglial morphological clusters across studies.

cell biology↗