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Liquid-liquid phase separation (LLPS) enables the formation of membraneless organelles, essential for cellular organization and implicated in diseases. We introduce catGRANULE 2.0 ROBOT, an algorithm integrating physicochemical properties and AlphaFold-derived structural features to predict LLPS at single-amino-acid resolution. The method achieves high performance and reliably evaluates mutation effects on LLPS propensity, providing detailed predictions of how specific mutations enhance or inhibit phase separation. Supported by experimental validations, including microscopy data, it predicts LLPS across diverse organisms and cellular compartments, offering valuable insights into LLPS mechanisms and mutational impacts. The tool is freely available at https://tools.tartaglialab.com/catgranule2 and https://doi.org/10.5281/zenodo.14205831 .

Background It is crucial to investigate protein functions in specific subcellular environments. Cross-linking mass spectrometry is a powerful tool to map the direct interactome of proteins by identifying inter-protein cross-links. However, it is challenging to identify inter-protein cross-linked peptides due to their low abundance. Results We chemically synthesize the cross-linkers ePDES1 and ePDES2 with an alkyne group and a compound with azide linked to a phosphate group to enrich for cross-linked peptides. Conclusion Based on the high-quality cross-linking spectra of ePDES1 and ePDES2, our methods achieve the identification of hundreds of directly interacting proteins or substrates of thioredoxins in the nucleus and mitochondria.

Background Subcellular RNA localization is crucial for the spatio-temporal control of protein synthesis and underlies key processes during development, homeostasis, and disease. In epithelial cells, RNA can localize asymmetrically along the apico-basal axis. Yet, the localization of most transcripts as well as the diversity of patterns that they adopt remains unexplored. Results Here, we use APEX-seq for proximity labeling and MERFISH for spatial transcriptomics to map subcellular transcript localization in intestinal organoids and tissue from adult mice. Many transcripts present localization bias, often localizing in granular structures. We uncover intrinsic and environmental factors that influence the formation of these patterns. Additionally, we identify translation-dependent and -independent localization patterns and pinpoint the role of 3′ untranslated regions and RNA-binding proteins. Conclusions This subcellular RNA atlas presents a detailed resource for understanding intestinal physiology.

HighlightsRecent advances in post-translational regulation have enabled rapid and precise metabolic flux control in microbial cell factories. Diverse protein degradation tags have been engineered to fine-tune the abundance of key pathway enzymes. Both natural subcellular compartments and synthetic membraneless organelles have been exploited to relocalize enzymes involved in metabolic pathways. Advances in artificial intelligence have facilitated the redesign and de novo construction of synthetic allosteric proteins for dynamic enzyme activity control.

Eukaryotic cells are highly structured and composed of multiple membrane-bound and membraneless organelles. Subcellular RNA localization is a critical regulator of RNA function, influencing various biological processes. At any given moment, RNAs must accurately navigate the three-dimensional subcellular environment to ensure proper localization and function, governed by numerous factors, including splicing, RNA stability, modifications, and localizing sequences. Aberrant RNA localization can contribute to the development of numerous diseases. Here, we explore diverse RNA localization mechanisms and summarize advancements in methods for determining subcellular RNA localization, highlighting imaging techniques transforming our ability to study RNA dynamics at the single-molecule level.

Background Cells contain membraneless organelles that have been proposed to form via phase separation involving dense networks of multivalent intermolecular interactions. As it is notoriously difficult to experimentally distinguish punctate structures formed by phase separation from those formed by other mechanisms, this issue is controversial. To complement experimental assays, we present a computational by-the-numbers approach to phase separation. We mine publicly available datasets to perform a molecular census of prominent subnuclear organelles in mouse embryonic stem cells: nucleoli, transcriptional condensates, heterochromatin foci, and Polycomb bodies. We estimate copy numbers and intermolecular distances and compare the latter to the Debye length, which is the characteristic distance over which intermolecular interactions typically occur. Results We find that none of the organelles studied here contain any protein species that shows intermolecular distances below the estimated Debye length if molecules in the organelles are randomly distributed, which disfavors the classical one-component phase separation scenario. Considering multiple species based on databases of phase-separating proteins, we find that nucleoli and transcriptional condensates are compatible with multi-component phase separation driven by proteins and RNAs, while heterochromatin foci and Polycomb bodies are better explained by a model in which proteins bind to chromatin without phase-separating via dense multivalent interaction networks. We also provide an interactive tool that allows testing of alternative multi-component scenarios. Conclusion We introduce a computational by-the-numbers approach to benchmark different demixing models that may explain the assembly of membraneless organelles. Our results suggest that cells use different mechanisms to form subnuclear organelles with different biophysical properties.

Multivalent interactions between proteins with intrinsically disordered regions or prion-like domains can drive liquid–liquid phase separation (LLPS) and form membraneless condensates essential for diverse cellular functions. Here, we predict phase separation scores for all annotated rice proteins and present ricePSP ( https://ricepsp.github.io/ ), a database of phase separation-associated proteins. AlphaFold structural predictions further validate the phase separation potential of these proteins. As a proof of concept, we apply ricePSP to identify flowering-related phase separation proteins, revealing insights into how LLPS may regulate flowering. Collectively, ricePSP provides a valuable resource for studying crop phase separation proteins and LLPS-related mechanisms in crop trait regulation.

Background Numerous cellular processes rely on biomolecular condensates formed through liquid–liquid phase separation (LLPS). Recently, it has become evident that somatic mutations can interfere with or over-activate the formation of phase-separated condensates. Results Here, we set out to systematically study the connection between cancer and biological condensation, specifically mapping the extent to which LLPS is affected in cancer and understanding the molecular pathomechanisms and therapeutic consequences of mutations affecting LLPS scaffolds. We identify both known and novel combinations of molecular functions that are specific to oncogenic fusion proteins and thus have a high potential for driving tumorigenesis. Protein regions driving condensate formation show an increased association with DNA- or chromatin-binding domains of transcription regulators within oncogenic fusion proteins, indicating a common molecular mechanism underlying several soft tissue sarcomas and hematologic malignancies where phase-separation-prone oncogenic fusion proteins form abnormal condensates along the DNA and thereby dysregulate gene expression programs. Conclusions We find that proteins initiating LLPS are frequently implicated in somatic cancers, even surpassing their involvement in neurodegeneration. Our data shows that cancer-driving LLPS scaffolds tend to be potent oncogenes, giving rise to dominant phenotypes and lacking targeting options by current FDA-approved drugs. Finding the currently missing drugs to shut down oncogenic fusion proteins, to disrupt the condensation enabled by them, and to offset their downstream effects could provide cancer drugs widely applicable to diverse cancer incidences previously defying standard treatments.

Cellular senescence is accompanied by extensive genomic reorganization, such as senescence-associated heterochromatin foci and expanded interchromatin compartments, to ultimately affect gene expression. Here, we demonstrate that chromatin structural changes in senescent cells drive significant alterations in the phase behavior and motility of paraspeckles, a type of interchromatin compartment condensate. We observe increased numbers, size, and elongation of paraspeckles harboring NONO and NEAT1_2, driven by elevated levels of those components, consistent with the micellization model of longitudinal growth rather than condensate coalescence. Enhanced paraspeckle motility is associated with HP1α-mediated heterochromatin condensation and interchromatin expansion found in cellular senescence.

The tight correlation between topologically associating domains (TADs) and epigenetic domains in Drosophila suggests that the epigenome contributes to define TADs. However, it is still unknown whether histone modifications are essential for TAD formation and structure. By either deleting or shifting key regulatory elements needed to establish the epigenetic signature of Polycomb TADs, we show that the epigenome is not a major driving force for the establishment of TADs. On the other hand, physical domains have an important impact on the formation of epigenetic domains, as they can restrict the spreading of repressive histone marks and looping between cis-regulatory elements.