Biology subjects

Yasuoka, K.

Publications and source records attributed to Yasuoka, K..

4 recordsLinked to original sources

bioRxiv2026

Coarse-grained models for simulations of double-stranded nucleic acids for mixed protein-nucleic acid condensates

Biomolecular condensates function as membraneless compartments, and some protein condensates can selectively concentrate single-stranded nucleic acids while excluding double-stranded nucleic acids. Understanding how nucleic acid structure affects partitioning into condensates has important implications for nucleic acid activity and function within condensates. Here, we present a set of coarse-grained two-bead-per-nucleotide models for simulations of double-stranded RNA and DNA in the CALVADOS framework. Our models separately represent the backbone and base, and maintain the helical structures using an elastic network potential tuned to capture chain stiffness. For dsRNA, the base stickiness was tuned using experimental data on differential partitioning of single- and double-stranded RNA into Ddx4N1 condensates in order to account for reduced base accessibility upon duplex formation. This RNA structural selectivity varied with the balance of electrostatic and non-electrostatic interactions, as revealed by simulations of condensates of the CAPRIN1 disordered region at varying ionic concentrations and with an R-to-K sequence variant. Finally, we developed parameters for double-stranded DNA using a similar approach. We envision that the CALVADOS models for double-stranded RNA and DNA will be useful for studying co-condensates of proteins and structured nucleic acids.

biophysics↗

bioRxiv2025

Molecular interactions underlying selective partitioning of clients into MED1 and FUS condensates

AbstractBiomolecular condensates selectively recruit and exclude proteins, and this partitioning is sometimes dictated by their intrinsically disordered regions. Factors that determine partitioning include client-scaffold interactions and stabilisation of the scaffold network within the condensate, yet a molecular and predictive understanding has not been fully achieved. Here, we used coarse-grained molecular dynamics simulations to elucidate molecular interactions between two types of nuclear proteins as scaffolds: the charge-rich disordered region of Mediator 1 (MED1) and the aromaticrich disordered region of Fused in sarcoma (FUS), in mixtures with client intrinsically disordered regions from six different proteins. We show distinct partitioning into the MED1 and FUS condensates, while enrichment of RNA in the dilute phase modulated partitioning in FUS condensates. Favourable client-scaffold interaction energies within condensates were associated with client partitioning, while client-scaffold interactions competed with scaffold self-interactions. Analysis of interaction energies of individual residues revealed that the interactions were localised to specific sequence regions: charged blocks for interactions with MED1, and dispersed aromatic residues for interactions with FUS. Based on these molecular insights, we developed a sequence-based predictor of partitioning trends and applied it to a set of 243 sequences. Our prediction approach for partitioning can be extended to other biomolecules, offering a framework to analyse their partitioning in cellular environments.

biophysics↗

bioRxiv2024

A coarse-grained model of disordered RNA for simulations of biomolecular condensates

Protein-RNA condensates are involved in a range of cellular activities. Coarse-grained molecular models of intrinsically disordered proteins have been developed to shed light on and predict single-chain properties and phase separation. An RNA model compatible with such models for disordered proteins would enable the study of complex biomolecular mixtures involving RNA. Here, we present a sequence-independent coarse-grained, two-bead-per-nucleotide model of disordered, flexible RNA based on a hydropathy scale. We parameterize the model, which we term CALVADOS-RNA, using a combination of bottom-up and top-down approaches to reproduce local RNA geometry and intramolecular interactions based on atomistic simulations and in vitro experiments. The model semi-quantitatively captures several aspects of RNA-RNA and RNA-protein interactions. We examined RNA-RNA interactions by comparing calculated and experimental virial coefficients, and non-specific RNA-protein interaction by studying reentrant phase behavior of protein-RNA mixtures. We demonstrate the utility of the model by simulating the formation of mixed condensates consisting of the disordered region of MED1 and RNA chains, and the selective partitioning of disordered regions from transcription factors into these, and compare the results to experiments. Despite the simplicity of our model we show that it captures several key aspects of protein-RNA interactions and may therefore be used as a baseline model to study several aspects of the biophysics and biology of protein-RNA condensates.

biophysics↗

bioRxiv2024

Serine chirality guides metabolic flow between one-carbon metabolism and neuromodulator synthesis

O_SCPLOWLC_SCPLOW-serine serves as a central metabolic node that integrates glycolytic flux, lipid metabolism, and one-carbon metabolism. In the mature central nervous system, O_SCPLOWLC_SCPLOW-serine is actively stereo-converted to O_SCPLOWDC_SCPLOW-serine, which functions as a neurotransmitter. However, the role of O_SCPLOWDC_SCPLOW-serine in cellular metabolism remains unclear. Here, we show that O_SCPLOWDC_SCPLOW-serine competes with mitochondrial O_SCPLOWLC_SCPLOW-serine transport, thereby suppressing one-carbon metabolism. Metabolomic analysis revealed that O_SCPLOWDC_SCPLOW-serine reduces intracellular glycine and formate levels, indicating inhibition of the initial step of the one-carbon pathway. Molecular dynamics simulations and enzymatic assays revealed that O_SCPLOWDC_SCPLOW-serine has low affinity for serine hydroxymethyltransferase 2 (Shmt2), which catalyzes the first step in mitochondrial one-carbon metabolism, and does not directly inhibit its activity. Instead, membrane transport assays demonstrated that O_SCPLOWDC_SCPLOW-serine competes with mitochondrial O_SCPLOWLC_SCPLOW-serine transport, depleting the substrate of Shmt2. Functionally, under O_SCPLOWLC_SCPLOW-serine poor conditions in vitro and ex vivo, O_SCPLOWDC_SCPLOW-serine inhibited the proliferation of immature and undifferentiated neural cells including glioblastoma stem cells, which depend highly on one-carbon metabolism. Notably, endogenous O_SCPLOWDC_SCPLOW-serine levels were low during early neurodevelopment, but increased with maturation, coinciding with a shift in the transcriptional profiles of serine metabolic enzymes at the cellular level. Given that O_SCPLOWLC_SCPLOW-serine supports neurodevelopment and O_SCPLOWDC_SCPLOW-serine modulates neurotransmission, this developmental shift in serine enantiomer metabolism appears to align with the functional transitions of the maturing nervous system. Thus, our findings reveal that serine chirality can influence mitochondrial substrate availability and one-carbon flux, offering previously unappreciated insight into the stereoselective regulation of cellular metabolism.

developmental biology↗