Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.11.22.517009

Designed sensors reveal normal and oncogenic Ras signaling in endomembranes and condensates

Zhang, J. Z.·Nguyen, W. H.·Rose, J. C.·Ong, S.-E.·Maly, D. J.·Baker, D.
View original source ↗Export metadata ↓

Abstract

Genetically encoded biosensors have accelerated biological discovery, however many important targets such as active Ras (Ras-GTP) are difficult to sense as strategies to match a sensors sensitivity to the physiological range of target are lacking. Here, we use computational protein design to generate and optimize intracellular sensors of Ras activity (LOCKR-based Sensor for Ras activity: Ras-LOCKR-S) and proximity labelers of the signaling environment of Ras (LOCKR-based, Ras activity-dependent Proximity Labeler: Ras-LOCKR-PL). We demonstrate that our tools can measure endogenous Ras activity and environment at subcellular resolution. We illustrate the application of these tools by using them to identify Ras effectors, notably Src-Associated in Mitosis 68 kDa protein (SAM68), enriched in oncogenic EML4-Alk granules. Localizing these sensors to these granules revealed that SAM68 enhances Ras activity specifically at the granules, and SAM68 inhibition sensitizes EML4-Alk-driven cancer cells to existing drug therapies, suggesting a possible therapeutic strategy.

Source connections

Explore related subjects

cell biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhang, J. Z., Nguyen, W. H., Rose, J. C., Ong, S.-E., Maly, D. J., Baker, D.. 2022-11-23. Designed sensors reveal normal and oncogenic Ras signaling in endomembranes and condensates. https://doi.org/10.1101/2022.11.22.517009

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

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗
bioRxiv2026

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↗
bioRxiv2026

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↗