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<title>bioRxiv Subject Collection: Biophysics</title>
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<description>
This feed contains articles for bioRxiv Subject Collection "Biophysics"
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<title>bioRxiv</title>
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<link>https://www.biorxiv.org</link>
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<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.06.723223v1?rss=1">
<title>
<![CDATA[
Deep Learning-Enhanced TopoStats for the Automated Quantification of DNA and Complex Biomolecular Structures 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.06.723223v1?rss=1
</link>
<description><![CDATA[
Atomic force microscopy (AFM) enables nanometre-scale, label-free imaging of biomolecules and surfaces under near-native conditions, yet quantitative analysis of AFM data remains limited compared to other bioimaging modalities. This limitation largely arises from the absence of open, automated tools capable of addressing AFM-specific artefacts, data formats, and topographical outputs. Here, we present the latest version of TopoStats, an open-source Python package for automated and quantitative AFM image analysis, developed as a deep-learning enabled advancement of our original TopoStats software to support more complex samples and richer molecular characterisation. The pipeline integrates all key processing stages, including image flattening and noise correction, object detection and segmentation, morphometric feature extraction, and strand tracing with topological classification. Designed for accessibility and reproducibility, TopoStats adheres to the FAIR for Research Software (FAIR4RS) principles and provides configurable workflows adaptable to diverse biological samples. Combining high-resolution AFM and our analysis pipeline allows the quantification of subtle structural changes within a heterogeneous sample set, revealing properties not accessible with other structural biology techniques. We demonstrate the effectiveness of our pipeline to differentiate between plasmids with both different topology and sequence, by extracting meaningful quantitative descriptors that distinguish the samples with statistical significance. Collectively, these developments establish TopoStats as a versatile framework for high-throughput, quantitative AFM analysis, advancing AFM from a fundamentally qualitative visualisation technique toward a quantitative analytical tool.
]]></description>
<dc:creator><![CDATA[ Whittle, S., Firth, T. A., Gamill, M. C., Wiggins, L., Shephard, N., Allwood, T., Catley, T. E., Pyne, A. L. B. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.06.723223</dc:identifier>
<dc:title><![CDATA[Deep Learning-Enhanced TopoStats for the Automated Quantification of DNA and Complex Biomolecular Structures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.06.723082v1?rss=1">
<title>
<![CDATA[
UTag, a cysteine-free thermostable tagging system for tracking single mRNA translation live 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.06.723082v1?rss=1
</link>
<description><![CDATA[
Spatiotemporal regulation of mRNA translation is central to gene expression. Over the past decade, translation has become directly observable in live cells at single-mRNA resolution by tagging nascent chains with tandem arrays of short epitope tags recognized by genetically encodable fluorescent intracellular antibodies (intrabodies). While this technology has revolutionized our understanding of translation regulation, the current toolbox of tagging systems remains limited. Here, we developed a novel and tight-binding intrabody against a short (11-amino acid) HIV protease epitope (named UTag). To ensure robust intracellular folding of the anti-UTag intrabody, we further engineered a cysteine-free variant that folds and functions independently of disulfide-bond formation, as validated by X-ray crystallography. The cysteine-free anti-UTag intrabody retains high binding affinity comparable to the parental intrabody while exhibiting significantly improved thermostability. Importantly, the cysteine-free UTag system enables real-time tracking of single-mRNA translation in live cells with performance on par with the parental UTag system as well as the established SunTag and ALFA-tag. Collectively, these results demonstrate that the newly developed UTag system expands the toolbox for live-cell translation tracking and provides complementary tools for multiplexed applications.
]]></description>
<dc:creator><![CDATA[ Aguilera, L. U., Chen, S., Sears, R. M., Yarbro, J., DeRoo, J., Ogg, H. A., Geiss, B. J., Stasevich, T. J., Snow, C. D., Zhao, N. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.06.723082</dc:identifier>
<dc:title><![CDATA[UTag, a cysteine-free thermostable tagging system for tracking single mRNA translation live]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.05.722848v1?rss=1">
<title>
<![CDATA[
Temporal Hydrogen-Bond Network Analysis Reveals Substrate-Directed Connectivity in Dihydrofolate Reductase 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.05.722848v1?rss=1
</link>
<description><![CDATA[
Hydrogen-bond networks are central to protein function, but most network analyses rely on static representations that neglect how interactions evolve in time. Here, we introduce a framework that combines instantaneous and temporal graph analysis of hydrogen-bond networks derived from molecular dynamics trajectories to quantify ligand-directed hydrogen-bond connectivity. We apply the method to E. coli dihydrofolate reductase (DHFR) and its L28R mutant, computing shortest hydrogen-bond paths from all residues to the substrate dihydrofolate (DHF). The instantaneous analysis reveals that DHF-directed connectivity is organized through a sparse set of preferred routes, with D27 and T113 acting as prominent hubs in the wild-type enzyme. Temporal analysis highlights residues that preferentially support time-ordered DHF-directed connectivity. Comparison with L28R shows that the mutation preserves the main substrate-contacting architecture and the overall communication scaffold but redistributes pathway usage, persistence, and temporal convergence. The network-derived hotspots partially overlap with independent coevolution signals, most strongly in the K109-I115 region, while overlap with cryptic-site predictors is more limited. This pattern indicates that the hydrogen-bond network captures evolutionarily supported communication regions in DHFR that are not fully recovered by static structural approaches. The framework is broadly applicable to ligand-binding proteins and provides a route to identify persistent, delayed, and mutation-sensitive signaling pathways directly from time-ordered simulation data.
]]></description>
<dc:creator><![CDATA[ Guclu, T. F., ATILGAN, C., Atilgan, A. R. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.05.722848</dc:identifier>
<dc:title><![CDATA[Temporal Hydrogen-Bond Network Analysis Reveals Substrate-Directed Connectivity in Dihydrofolate Reductase]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.05.722045v1?rss=1">
<title>
<![CDATA[
Structural modelling and biophysical analyses reveal a dimeric coiled-coil architecture in the FAZ10 central region of Trypanosoma brucei 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.05.722045v1?rss=1
</link>
<description><![CDATA[
Trypanosoma brucei relies on the flagellum attachment zone (FAZ) to coordinate flagellum positioning, cell morphology, and cytokinesis. The giant FAZ10 protein, which contains both repetitive and structured regions, is essential for correct cleavage-furrow placement, yet its molecular organization remains unresolved due to its exceptional size. In this study, we define the architecture of the FAZ10 central region through structural modelling and biophysical validation. AlphaFold2 and molecular dynamics simulations defined a parallel coiled-coil dimer flanked by symmetric globular domains, with canonical hydrophobic core packing, complementary interhelical contacts, and local heptad discontinuities, including a stammer-stutter pair that modulates the superhelical geometry. Biophysical analyses show that this region forms a stable dimer in solution, mediated by the coiled-coil domain and consistent with a predominantly -helical structure. Together, these findings identify the FAZ10 central region as a semi-flexible dimeric scaffold that provides a structural framework for understanding FAZ supramolecular organization and the integration of large cytoskeletal assemblies in trypanosomatids.
]]></description>
<dc:creator><![CDATA[ Osorio-Mogollon, C. M., Leonardo, D. A., Izumi, C., Alves, L. C., Olivos-Ramirez, G. E., Poma, A., Baqui, M. M. A. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.05.722045</dc:identifier>
<dc:title><![CDATA[Structural modelling and biophysical analyses reveal a dimeric coiled-coil architecture in the FAZ10 central region of Trypanosoma brucei]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.722641v1?rss=1">
<title>
<![CDATA[
Epigenetic Control of Spatiotemporal Dynamics of Pancreatic Cancer Cells via Brg1-Rac1 Signaling 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.722641v1?rss=1
</link>
<description><![CDATA[
Pancreatic ductal adenocarcinoma (PDA) arises from distinct precursor lesions with different clinical outcomes, yet the mechanisms linking epigenetic regulation to invasive cell behavior remain poorly understood. Here, we investigate how the chromatin remodeler Brg1 influences the dynamic properties of cancer cell migration. Using a biomimetic supported membrane system combined with label-free interferometric imaging, we quantitatively analyze the spatiotemporal dynamics of PDA cells derived from pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasms (IPMN). Despite their similar morphology under conventional conditions, PanIN- and IPMN-derived PDA cells exhibit markedly different migration behaviors. PanIN-derived cells migrate faster and display enhanced dynamic remodeling, whereas IPMN-derived cells show persistent elongation with limited displacement. These differences are captured by quantitative analyses of cell trajectories and deformation dynamics. Mechanistically, PanIN-derived PDA cells exhibit elevated Rac1 activity, supporting a model in which a Brg1-Rac1 axis regulates cytoskeletal dynamics and migration behavior. Together, our findings demonstrate that epigenetic regulation is linked to distinct dynamic phenotypes of cancer cells and highlight the importance of quantitative analysis of cell behavior for understanding invasive potential.
]]></description>
<dc:creator><![CDATA[ Yamamoto, A., Fukuda, A., Fukunaga, Y., Hayashi, K., Seno, H., Tanaka, M. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.722641</dc:identifier>
<dc:title><![CDATA[Epigenetic Control of Spatiotemporal Dynamics of Pancreatic Cancer Cells via Brg1-Rac1 Signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.722627v1?rss=1">
<title>
<![CDATA[
Quantum kernel support vector machines for trabecular bone classification: comparing feature reduction strategies on synthetic micro-CT data 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.722627v1?rss=1
</link>
<description><![CDATA[
Quantum kernel methods offer a potential advantage for classification tasks in high-dimensional feature spaces, yet their practical benefit critically depends on how input features are prepared. We compare five dimensionality reduction strategies - principal component analysis (PCA), Gaussian random projection (RP Gaussian), sparse random projection (RP Sparse), partial least squares (PLS), and uniform manifold approximation and projection (UMAP) - as pre-processing steps for quantum kernel support vector machines (SVMs) applied to trabecular bone classification from synthetic micro-computed tomography (micro-CT) data. Using a custom procedural generator based on Gaussian random field zero-crossings, we produced 500 synthetic trabecular bone volumes with controlled morphometric properties such as bone volume fraction (BV/TV), trabecular thickness (Tb.Th), number (Tb.N) and spacing (Tb.Sp). Texture features extracted from grayscale slices are reduced to 8-dimensional quantum circuit inputs via each method, then classified using both classical radial basis function (RBF)-SVMs and quantum kernel SVMs with ZZ feature maps on a statevector simulator, both evaluated with 5x5 repeated stratified cross-validation (25 folds). Our results show that UMAP is the only reduction method where the quantum kernel remains competitive with the classical baseline. Under repeated cross-validation, UMAP showed a +0.032 accuracy gap favouring the quantum kernel (Dietterich 5x2 CV p = 0.177); however, validation on 10 fully independent datasets - each with independently generated samples, separate reduction fits, and separate kernel matrices - reversed the sign to -0.030 (paired t-test p = 0.123; Wilcoxon p = 0.193; quantum wins 3/10 datasets), indicating that the apparent advantage was likely inflated by fold dependence. Nevertheless, UMAP's gap remains small and non-significant in both analyses, whereas all linear methods (PCA, RP Gaussian, PLS) show substantial quantum deficits of -0.090 to -0.116 across BV/TV classification, with PCA and PLS remaining significant under corrected tests (5x2 CV p=0.004 and p=0.007 respectively). We additionally evaluate quantum kernel ridge regression for continuous morphometric prediction, finding that ZZ quantum kernels fail uniformly at regression (negative R2 for all methods except PLS at 4 qubits), suggesting that the ZZ kernel captures decision boundaries but not smooth metric structure. These findings provide practical guidance for feature engineering in near-term quantum machine learning pipelines and demonstrate that the choice of dimensionality reduction can determine whether quantum kernels remain competitive with classical baselines.
]]></description>
<dc:creator><![CDATA[ Florez, I., Farhat, A., Le Houx, J., Altamura, E., Tozzi, G. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.722627</dc:identifier>
<dc:title><![CDATA[Quantum kernel support vector machines for trabecular bone classification: comparing feature reduction strategies on synthetic micro-CT data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.722635v1?rss=1">
<title>
<![CDATA[
Coupled Binding and Folding of NS2B/NS3 Protease and Linker Effects Revealed by Topology-based Modeling 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.722635v1?rss=1
</link>
<description><![CDATA[
Orthoflavivirus, such as West Nile Virus (WNV), dengue virus (DENV) and ZIKA virus (ZIKV), are globally distributed pathogens that pose substantial threats to human health. Currently, there are still no effective antiviral drugs for WNV or ZIKV. Despite the availability of two licensed DENV vaccines, their use remains limited due to potential risks, highlighting an urgent need for antiviral drug development. The highly conserved orthoflavivirus protease NS2B/NS3 is required for viral replication, making it a promising anti-flavivirus target. A major challenge, however, is the highly charged active site of this enzyme, which requires charged chemical matters with low bioavailability. An alternative and more attractive strategy is to target potential allosteric sites or folding intermediate states of the protease. In this work, we employ the topology-based coarse-grained G[o] modeling to explore the coupled binding and folding pathways of WNV NS2B/NS3 protease and study the effects of the widely used experimental construct with a G4SG4 linker between NS2B and NS3 on stability and folding. Our results provide a holistic conformational landscape of the protease binding and folding, including several key intermediate states. We find that the presence of the G4SG4 linker alters the folding pathways and destabilizes the NS2B C-terminus. The latter is consistent with experimental observations that the G4SG4 linked protease has lower activity and adopts an open state without the substrate in crystal structures. Together, these findings provide for the first time a complete picture of the binding and folding of the NS2B/NS3 protease and identify important folding intermediate states that could be targeted for allosteric antiviral drug development.
]]></description>
<dc:creator><![CDATA[ Dong, K., Huang, J., Chen, M., Chen, J. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.722635</dc:identifier>
<dc:title><![CDATA[Coupled Binding and Folding of NS2B/NS3 Protease and Linker Effects Revealed by Topology-based Modeling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.721587v1?rss=1">
<title>
<![CDATA[
Nanoscale rheological heterogeneity revealed by Single Particle orientation Tracking (SPoT) of ultrashort carbon nanotubes in brain tissue 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.721587v1?rss=1
</link>
<description><![CDATA[
Transport in complex biological tissues is governed by local rheological heterogeneity at the nanoscale, yet probing such environments deep inside living systems remains challenging. Here, we introduce an orientation- sensitive single-particle tracking (SPoT) approach that simultaneously resolves translational and rotational dynamics of individual carbon nanotubes deep within biological tissue. By exploiting the intrinsic dipole-like emission and short-wave infrared luminescence of carbon nanotubes enhanced through the incorporation of quantum color-centers our method enables long-duration tracking with high signal-to-noise ratio in optically dense environments. Crucially, the length of these nanotubes can be precisely shortened down to a few tens of nanometers to adapt to diffusion environmental dimensions, further optimizing the tracking applicability. SPoT of single carbon nanotubes provides access to relative changes in local viscosity, steric constraints, and environmental anisotropy. When applied to the brain extracellular space, SPoT demonstrates that local variations in the translational and rotational diffusion of tracers are heterogeneous and not systematically correlated. This allows to disentangle the local effects of viscosity and spatial tortuosity within the brain extracellular space, which are distinct features that would otherwise remain undetected through translational diffusion analysis alone. By enabling combined translational and rotational tracking of nano-emitters over unprecedented depths and timescales, this work establishes a new framework for probing nanoscale transport and rheological heterogeneity in intact biological tissues and more generally in complex diffusive environments.
]]></description>
<dc:creator><![CDATA[ Ruan, L., Manko, H., Gresil, Q., Aleman-Castaneda, L. A., Meras, M., Sebastian, F., Flavel, B., Zaumseil, J., Groc, L., Brasselet, S., Tondusson, M., Cognet, L. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.721587</dc:identifier>
<dc:title><![CDATA[Nanoscale rheological heterogeneity revealed by Single Particle orientation Tracking (SPoT) of ultrashort carbon nanotubes in brain tissue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.722763v1?rss=1">
<title>
<![CDATA[
ZBTB38 requires an extended N-terminal zinc finger network to read mCpG- and discriminate TpG-containing DNA sequences 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.722763v1?rss=1
</link>
<description><![CDATA[
Methylation of cytosine bases in the CpG context (mCpG) is an essential regulatory mechanism cells use to spatially and temporally orchestrate access to genomic regions and mediate transcription. In many diseases, DNA methylation patterns become inappropriately distributed leading to aberrant transcriptional outcomes. Methyl-CpG binding proteins (MBPs) are key epigenetic mediators that selectively recognize mCpG sites, translating these signals into discrete transcriptional responses. ZBTB38 is a zinc finger (ZF) MBP that uniquely harbors two sets of five ZF clusters; each capable of selectively distinguishing mCpG sites. While the cognate DNA sequence and molecular basis for selective mCpG recognition have been defined for the ZBTB38 C-terminal (C-term) ZF domain, the molecular basis for differentiating DNA targets by the N-terminal (N-term) ZF domain remained uncharacterized. Here we report the mCpG-containing consensus sequence for the ZBTB38 N-term ZFs and demonstrate that unlike the other two ZBTB MBP family members ZBTB33 (Kaiso) and ZBTB4, the three shared core ZF domain discriminates against binding to TpG-containing DNA, and that at least one additional N-term ZF is required to stabilize DNA engagement. In addition, we demonstrate that each ZBTB38 ZF domain exhibits preferential target recognition for their respective cognate methylated DNA consensus motif. These findings expand understanding for how ZBTB38 differentially mediates epigenetic-based transcriptional process in normal and disease-state cells by providing new insight into the molecular basis by which the ZBTB38 N-term ZF domain differentiates DNA targets and offering further insight into the interplay between the N- and C-term ZF domains in directing cellular activities.
]]></description>
<dc:creator><![CDATA[ Boster, J., Gangi, C., Hudson, N. O., Billings, D. E., Guerra Castanaza Jenkins, B. L., DIng, V. L., Buck, B. A. ]]></dc:creator>
<dc:date>2026-05-07</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.722763</dc:identifier>
<dc:title><![CDATA[ZBTB38 requires an extended N-terminal zinc finger network to read mCpG- and discriminate TpG-containing DNA sequences]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.04.722628v1?rss=1">
<title>
<![CDATA[
Cell Growth and Division Shape mRNA-Protein Correlations 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.04.722628v1?rss=1
</link>
<description><![CDATA[
Correlations between cellular variables, such as gene-expression levels, provide insights into regulatory mechanisms. We focus here on correlations between mRNA and protein levels and re-examine previously derived analytical predictions. We test this prediction on single-cell E. coli data and see substantial disagreement. We hypothesize that this discrepancy arises from the assumption of constant cell volume and develop a theoretical framework for mRNA--protein correlations in growing and dividing cells. Within this framework, we derive an analytical expression for mRNA--protein correlations and show that explicit incorporation of growth and division substantially alters these correlations. The resulting relation is invariant to upstream transcriptional dynamics, and we validate it using stochastic simulations across multiple gene-regulatory architectures. Finally, we show that the derived predictions are consistent with the E. coli data.
]]></description>
<dc:creator><![CDATA[ Biswas, K., Sheinman, M., Sepulveda, L. A., Golding, I., Amir, A. ]]></dc:creator>
<dc:date>2026-05-06</dc:date>
<dc:identifier>doi:10.64898/2026.05.04.722628</dc:identifier>
<dc:title><![CDATA[Cell Growth and Division Shape mRNA-Protein Correlations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.02.722446v1?rss=1">
<title>
<![CDATA[
Extracting Parsimonious Quantitative Predictors of Biological Effectiveness from 'First-Principles' Radiobiology: Application to the Mixed-Quality Problem 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.02.722446v1?rss=1
</link>
<description><![CDATA[
Developing parsimonious, mechanism-aware quantitative models that predict how biological effectiveness changes with different modifiers remains, in general, an unsolved problem. Advances in radiobiological research have created a large knowledge base of 'first-principles' mechanistic models of radiation response that, in principle, could accurately predict radiosensitivity across different experimental and clinical conditions. However, in practice these mechanistic models come with an overabundance of parameters, the majority of which are practically unidentifiable and, moreover, likely unnecessary if one simply wishes to predict how radiosensitivity changes for some specific modifier of interest. Nevertheless, determining which few details in the full mechanistic model are relevant for a given purpose, as well as how to remove any other extraneous details, remains a highly non-trivial task. In this study, we demonstrate the potential of model reduction, starting from a detailed mechanistic description, as a systematic strategy for deriving parsimonious, experimentally falsifiable radiobiological descriptors. As a proof-of-concept demonstration, we apply the Manifold Boundary Approximation Method (MBAM) to a Mechanistic Model of DNA Repair and Survival (MEDRAS), for the problem of cell survival prediction following an acute exposure. Our findings reveal that the complete MEDRAS model for an arbitrary mixed-quality exposure can be structurally simplified to a reduced three-parameter model for an effective uniform-quality, named MEDRAS-LPL. Additional MBAM analysis on MEDRAS-LPL identifies two boundaries in parameter space, corresponding to sparsely ionizing and densely ionizing radiation. Mapping of MEDRAS-LPL parameter space on to effective LQ space further demonstrates that parameters close to the sparsely ionizing boundary line up with expectations from the theory of dual radiation, while parameters close to the densely ionizing boundary line up with expectations from a purely linear model based on a target-theory description. Moreover, our formalism predicts enhanced synergistic interactions between sparsely ionizing and densely ionizing radiation beyond the Zaider Rossi model (ZRM) paradigm, in line with empirical observations. The results highlight the potential for using reduced-order models not only for predictive applications but also for generating novel hypotheses that can inform future experimental designs and optimization strategies in radiobiology.
]]></description>
<dc:creator><![CDATA[ Yusufaly, T., Transtrum, M., Huang, L., Sabok-Sayr, S., Sgouros, G., Hobbs, R., Jia, X. ]]></dc:creator>
<dc:date>2026-05-06</dc:date>
<dc:identifier>doi:10.64898/2026.05.02.722446</dc:identifier>
<dc:title><![CDATA[Extracting Parsimonious Quantitative Predictors of Biological Effectiveness from 'First-Principles' Radiobiology: Application to the Mixed-Quality Problem]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.721819v1?rss=1">
<title>
<![CDATA[
Time-step restrictions for numerical approximations of the Poisson-Nernst-Planck (PNP) equations 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.721819v1?rss=1
</link>
<description><![CDATA[
The Poisson-Nernst-Planck (PNP) system is an accurate model of electrodiffusion of ionic species. It is commonly used in situations where nanoscale resolution is required, for instance close to ion channels in the membranes of biological cells. The inherent stiffness of the equations has made them challenging to solve and has limited the applicability of the system. In particular, the time step required for stable solutions has typically needed to be very short (nanoseconds), which makes simulations on the time scale of an action potential (milliseconds) difficult. Recently, it has been observed that avoiding operator splitting and instead solving the concentration equations and the electrostatic equation in a coupled manner relaxes the time-step limitation considerably. However, no theoretical explanation of this observation has been provided. Here, we aim to explain why the coupled scheme allows much larger time steps. We illustrate the mechanism by considering special cases that define necessary, but not sufficient, conditions for stability. We also show that these conditions remain relevant for the fully coupled PNP model in 3D.
]]></description>
<dc:creator><![CDATA[ Jaeger, K. H., Tveito, A. ]]></dc:creator>
<dc:date>2026-05-06</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.721819</dc:identifier>
<dc:title><![CDATA[Time-step restrictions for numerical approximations of the Poisson-Nernst-Planck (PNP) equations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.03.722550v1?rss=1">
<title>
<![CDATA[
Dynamics of synthetic transcriptional condensates emerge from RNA synthesis and degradation 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.03.722550v1?rss=1
</link>
<description><![CDATA[
At sites of active gene expression, dynamic compartments known as transcriptional condensates assemble and dissolve on timescales relevant to RNA synthesis and degradation. Yet how the non-equilibrium dynamics of these condensates emerge from the coupling of RNA concentration and phase separation remains poorly understood. Here we engineer synthetic active condensates in which T7 RNA polymerase transcribes RNA in situ, triggering phase separation with a cationic scaffold protein. By using RNA concentration as a tunable parameter, we drive condensates along defined paths through a characterized phase diagram. This reaction-phase separation coupling gives rise to three emergent dynamic phenomena not accessible in passive systems: a rapid switch-like nucleation burst, RNA-mediated positive and negative feedback regulation of transcription, and oscillatory condensate formation in which RNA degradation spontaneously renucleates condensates. Together, these results show that the dynamic functions of transcriptional condensates emerge from their reaction-driven paths through phase space, providing a quantitative framework for understanding how RNA flux governs condensate dynamics in living cells.
]]></description>
<dc:creator><![CDATA[ Liao, J., Ahn, S. Y., Obermeyer, A. C. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.03.722550</dc:identifier>
<dc:title><![CDATA[Dynamics of synthetic transcriptional condensates emerge from RNA synthesis and degradation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.03.722537v1?rss=1">
<title>
<![CDATA[
An underlying bistability sets amplitude and explains temperature compensation in the cyanobacterial circadian clock 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.03.722537v1?rss=1
</link>
<description><![CDATA[
Circadian clocks create free-running biological rhythms with a period close to 24 hours. A universal property of these systems is temperature compensation, where the period of oscillation remains nearly invariant even as the amplitude changes with temperature. In the cyanobacterial system, where the core oscillator can be reconstituted from purified KaiABC proteins, we identify a key temperature-dependent positive feedback process: antagonism between KaiA and KaiB creates a bistable switch in protein-protein interaction. The region of bistability is strongly temperature dependent and correlated with oscillator amplitude. Combining this bistable mechanism with the temperature scaling of phosphorylation and dephosphorylation rates in a mathematical model recapitulates the overall temperature compensation of the oscillator. This capacity for history-dependent switching suggests that bistable dynamics underpin the generation of circadian rhythms.
]]></description>
<dc:creator><![CDATA[ Liu, Y., Pattanayak, G. K., Chi, C., Yoo, H., Dinner, A., Rust, M. J. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.03.722537</dc:identifier>
<dc:title><![CDATA[An underlying bistability sets amplitude and explains temperature compensation in the cyanobacterial circadian clock]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722238v1?rss=1">
<title>
<![CDATA[
Differential histone tail citrullination by PAD Enzymes observed via NMR spectroscopy 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722238v1?rss=1
</link>
<description><![CDATA[
Citrullination is a charge-modifying post-translational modification whereby proteinogenic arginine is converted to the non-coded amino acid citrulline by calcium-activated protein arginine deiminases (PADs; EC 3.5.3.15). The five known PAD enzymes in humans (PADs 1, 2, 3, 4, and 6) are differentially expressed and have distinct targets, including histones. While some PAD histone citrullination sites are known, a comprehensive investigation of all histone tail arginines targeted by catalytically active PADs 1-4 is lacking. Here, we sought to identify PAD citrullination sites in histone tails, both within histone peptides and in reconstituted nucleosomes. Toward this objective, we utilized a real-time 1H-15N NMR spectroscopy-based assay. By monitoring both arginine and citrulline backbone amide peak intensities over time, we identified sites of citrullination in 15N-labeled histone tails within peptides and reconstituted nucleosome core particles. We found that PADs 1, 2, and 4 citrullinate all directly observable histone tail arginines to varying degrees. This is distinct from PAD3, which only moderately citrullinates H2A and H4 arginine residues and does not modify H3 tail arginines. Together, these data suggest a level of histone arginine specificity by each PAD. Furthermore, histone tail citrullination is altered within nucleosomes compared to isolated peptides, which we interpret to reflect changes in conformation and accessibility. We speculate that citrullination increases nucleosomal histone tail dynamics, with implications for crosstalk between sites of histone citrullination and other important sites of regulation by PTMs (including lysines) within and between tails.
]]></description>
<dc:creator><![CDATA[ Kowalczyk, A. J., Morrison, E. A. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722238</dc:identifier>
<dc:title><![CDATA[Differential histone tail citrullination by PAD Enzymes observed via NMR spectroscopy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722215v1?rss=1">
<title>
<![CDATA[
Counting fluorescent emitters with a single photon avalanche diode array 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722215v1?rss=1
</link>
<description><![CDATA[
For decades, the photon counting histogram (PCH) was used as the sole method to quantify fluorophore numbers in a diffraction-limited focal volume. This technique combines spatial excitation profiles, and the distribution of photon counts to register the photon emission statistics of individual fluorophores. However, this approach has not yet been transferred to widefield fluorescent imaging due to the lack of fast and single photon sensitive camera sensors which can capture the photon emission statistics of a single fluorophore. Here, we explore avenues towards quantitative analysis of the active fluorophore number by leveraging recent advancements in single photon avalanche diode (SPAD) array technology. Binary exposures of a SPAD array can be synchronized with picosecond laser pulses to measure the PCH in a widefield setting. Then, by modeling the statistical relationship between the active fluorophore number and the PCH in a region of interest following a laser pulse, we can perform Bayesian inference of this number. The model is demonstrated experimentally by counting quantum dots and various numbers of fluorescent dye molecules bound to DNA origamis. We find that this method has several important applications in widefield microscopy, including enhanced localization microscopy and constrained fitting of multiple unresolvable fluorescent emitters.
]]></description>
<dc:creator><![CDATA[ Seitz, C., Evans-Molina, C., Liu, J. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722215</dc:identifier>
<dc:title><![CDATA[Counting fluorescent emitters with a single photon avalanche diode array]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722258v1?rss=1">
<title>
<![CDATA[
Loop Extrusion Reversal by Condensin Motor is Mediated by Catch Bonds 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722258v1?rss=1
</link>
<description><![CDATA[
Structural Maintenance Complexes (SMC) are energy consuming motors that are important in folding the genome by loop extrusion (LE) in all stages of the cell cycle. Single molecule magnetic tweezer pulling experiments have revealed that condensin, a member of the SMC family involved in mitosis, takes occasional backward steps, thus coughing up the gains in the length of the extruded loop. To reveal the mechanism of the forward and backward steps simultaneously, we developed a theory using the stochastic kinetic model and the scrunching mechanism for LE. The calculations quantitatively account for the measured force-dependent step size and dwell time distributions in both the directions. By postulating the existence of an intermediate state in the ATP-driven cycle that is poised to take a forward or a backward step, we predict that its lifetime increases as the external mechanical force increases till a critical value and subsequently decreases at higher forces. The surprising finding of lifetime increase in an active motor, at sub-piconewton forces, is the characteristic of catch bonds, known in force-induced rupture of several passive protein complexes. The identification of catch bond-like states in condensin not only expands our understanding of LE but also highlights the significance of mechanical forces in regulating genome organization.
]]></description>
<dc:creator><![CDATA[ Dey, A., Shi, G., Takaki, R., Thirumalai, D. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722258</dc:identifier>
<dc:title><![CDATA[Loop Extrusion Reversal by Condensin Motor is Mediated by Catch Bonds]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722010v1?rss=1">
<title>
<![CDATA[
Synthetic Biomolecular Condensates as Tunable Microtubule Assembly Hubs 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722010v1?rss=1
</link>
<description><![CDATA[
Phase separation of proteins and nucleic acids (NAs) into nano-to-microscale condensates can regulate biochemical processes, including assembly and organization of cytoskeletal networks such as actin and microtubules. This study examines the functional role of condensate material properties in microtubule assembly. Learning from the sequence grammar of naturally occurring intrinsically disordered regions in microtubule-associated proteins, two-component peptide-NA condensates with programmable material properties were designed. These synthetic condensates catalyze tubulin polymerization into microtubule filaments with tunable outcomes. Tubulin preferentially partitions to the condensate interface and nucleates microtubule assembly. Enhanced tubulin self-assembly produces long filaments that exhibit branching and bundling. Using a minimal stochastic chemo-mechanical model, we show that sequence-encoded condensate viscoelasticity is a tunable element that controls filament morphologies and identifies interfacial rheology as the key regulator of filament growth. Fluorescence recovery after photobleaching experiments support this model, revealing a direct correlation between interfacial tubulin mobility and condensate-directed microtubule assembly. Distinct regimes emerge due to competition between bulk adsorption and lateral diffusion of tubulin at the condensate interface, which determines whether filament tips grow or stall. Since dynamic microtubule assembly and restructuring are essential for various cellular functions, this work highlights a critical role of condensate interfacial rheology in cytoskeletal organization.
]]></description>
<dc:creator><![CDATA[ Srinivasan, S., Singh, A., Potoyan, D. A., Banerjee, P. R. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722010</dc:identifier>
<dc:title><![CDATA[Synthetic Biomolecular Condensates as Tunable Microtubule Assembly Hubs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722179v1?rss=1">
<title>
<![CDATA[
Phylogenetic Analysis and Structural Evaluation of Staphylococcus aureus Serine-Aspartate Repeat-Containing Protein D with a Focus on Periprosthetic Joint Infection 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722179v1?rss=1
</link>
<description><![CDATA[
Serine-aspartate repeat-containing protein D (SdrD) is a Staphylococcus aureus cell wall-anchored, calcium-binding adhesin member of the MSCRAMM Sdr subfamily that may contribute to bacterial adhesion and virulence. S. aureus is the most common cause of periprosthetic joint infection (PJI). Population-level distribution and sequence diversity of SdrD among clinical PJI isolates have not been systematically characterized, and the SdrD binding mechanism is still not well understood. To address these gaps, sdrD alleles were queried across 156 newly sequenced PJI isolates and compared to publicly available S. aureus genomes, and nucleotide- and protein-level phylogenies of the sdrCDE locus constructed. The SdrD crystal structure from S. aureus JH1 was determined, with solution small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations, and assessment of conformational changes with calcium depletion. Three dominant sdrD subtypes were defined, associating with USA300, JH1, and TCH60; the JH1 sdrD subtype was predominant among PJI isolates. Structural studies showed that the conformation of individual domains and interdomain organization of the multidomain SdrD have limited flexibility in solution, and that the calcium-binding B domain retains its core fold under conditions of calcium depletion. Together, the findings presented support functional diversification among Sdr family members in mediating host attachment and inform a re-evaluation of the ligand-binding mechanism previously proposed for SdrD.
]]></description>
<dc:creator><![CDATA[ Joachimiak, A., Tan, K., O'Connor, K. A., Zhou, X., Gade, P., Garcia, E., Tan, A., Nijhawan, A., Endres, M., Kim, Y., Greenwood-Quaintance, K., Patel, R. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722179</dc:identifier>
<dc:title><![CDATA[Phylogenetic Analysis and Structural Evaluation of Staphylococcus aureus Serine-Aspartate Repeat-Containing Protein D with a Focus on Periprosthetic Joint Infection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.721955v1?rss=1">
<title>
<![CDATA[
Self-organized tiling generates tissue-scale hyperuniformity during development 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.721955v1?rss=1
</link>
<description><![CDATA[
Biological tissues require branched cellular architectures to maximize spatial coverage while minimizing redundancy. Yet, how cells decode local spatial information to collectively tile territories without a global blueprint remains a key open question. Here, we develop a biophysical theory of interacting branched cells, and show that coupling their growth to short-range repulsion drives efficient tiling with minimal territorial overlap. Our model predicts that the same local mechanism simultaneously suppresses long-range density fluctuations, driving the cellular collective toward hyperuniformity. We confirm these theoretical predictions with experiments on microglial patterning in the developing retina, and show that perturbations resulting in limited cell growth disrupt both tiling and fluctuation suppression. Our results reveal that two seemingly distinct optimization principles of biological patterning, large-scale regularity and efficient tiling, are intimately linked and can arise from a single growth-repulsion feedback, suggesting a general principle for self-organized tissue coverage.
]]></description>
<dc:creator><![CDATA[ Siegert, S., Kanari, L., Ucar, M. C. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.721955</dc:identifier>
<dc:title><![CDATA[Self-organized tiling generates tissue-scale hyperuniformity during development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.722034v1?rss=1">
<title>
<![CDATA[
MACRO-MOLECULAR CROWDING FAVORS WRITHE IN UNWOUND DNA 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.722034v1?rss=1
</link>
<description><![CDATA[
Genomic DNA is subject to forces and torsion. Some arise mechanically, while others can be entropic, such as those due to crowding within the nuclear environment. Indeed, about 30-40% of the cell is occupied by molecules other than water, and of these, the vast majority are macromolecules. Here, we explore both experimentally and theoretically the interplay between tension, torsion, and macromolecular crowding. Using pharmaceutically relevant crowders of different molecular weights, Dextran 70, and polyethylene glycol, we observed that macromolecular crowding of unwound, stretched DNA effectively opposed the tension and promoted the formation of plectonemes. A theoretical model representing the equilibrium between B- and L-form DNA fit to the experimental measurements indicates the contractile tension produced by macromolecular crowding of DNA.
]]></description>
<dc:creator><![CDATA[ Qian, J., Montgomery, Z. Z., Spakowitz, A. J., Dunlap, D. D., Finzi, L. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.722034</dc:identifier>
<dc:title><![CDATA[MACRO-MOLECULAR CROWDING FAVORS WRITHE IN UNWOUND DNA]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722229v1?rss=1">
<title>
<![CDATA[
Cholesteryl Esters Modulate Lipid Droplet Rigidity and Monolayer Organization during Liver Cancer Progression 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722229v1?rss=1
</link>
<description><![CDATA[
In mammalian cells, lipid monolayers support the integrity of lipid droplets (LDs), organelles that function as storage for neutral lipids. Liver-targeting illnesses such as liver cancer interrupt normal LD metabolism and prompt changes in the chemical content of these organelles, which can have effects on structural and organizational behavior of the lipids. In LDs, liver cancer induces concentric crystalline phases of cholesteryl esters (CEs) and triglycerides near the NL-monolayer interface, which become more pronounced as CE concentration increases. Yet, there is little known about how this phenomenon may link to persistence of undigested LDs in liver cancer patients. To shed light on this, all-atom molecular dynamics simulations were used to model LD micropipette aspiration experiments and gain insight into the effect of CE concentration on partitioning, structural, and mechanical properties of LDs. We successfully model micropipette aspiration by application of constant surface tension laterally, which stretches lipid bilayers and monolayers as the magnitude increased. The results show increased phospholipid packing due to insertion of CE fatty tails into the monolayer. Increasing CE concentration induces a non-linear change in surface packing defects on the LDs, notable rigidification, and stiffness. Taken together, these insights improve our understanding of the physical properties at the LD monolayer-core interface during liver cancer progression.
]]></description>
<dc:creator><![CDATA[ Campbell, O., Leal, C., Monje, V. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722229</dc:identifier>
<dc:title><![CDATA[Cholesteryl Esters Modulate Lipid Droplet Rigidity and Monolayer Organization during Liver Cancer Progression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722286v1?rss=1">
<title>
<![CDATA[
Npl4 decodes polyubiquitin length and gates D1-D2 coupling in human VCP/p97 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722286v1?rss=1
</link>
<description><![CDATA[
VCP/p97 binds the Npl4-Ufd1 heterodimer adaptor to extract polyubiquitinated substrates for proteasomal degradation, but how it decodes K48-linked chain length and how D1-coupled events license downstream D2 power strokes remain unclear. Here we introduce smUbiRAD, or single-molecule ubiquitin recognition and dynamics, and identify a sharp chain-length threshold: Npl4 binds transiently to short chains but switches to long-lived, multivalent engagement on tetra- and penta-ubiquitin. Ufd1 and p97 further stabilize these complexes mainly by suppressing Npl4 dissociation without affecting initial encounter. In fully assembled p97-Ufd1-Npl4-substrate complexes, D1 ATP hydrolysis--rather than D2--drives rapid Npl4 exchange. These results support a model in which D1-powered conformational changes promote cofactor Npl4, but not Ufd1, turnover and gate iterative coupling to downstream D2-driven substrate processing. Finally, we show that multisystem proteinopathy variants R155H and A232E bias p97 toward a high-affinity resting state and accelerate Npl4 exchange, implicating hyperactive cofactor cycling as a disease-linked dysregulation.
]]></description>
<dc:creator><![CDATA[ Khamari, L., Tang, J., Moon, S., Walter, N. G. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722286</dc:identifier>
<dc:title><![CDATA[Npl4 decodes polyubiquitin length and gates D1-D2 coupling in human VCP/p97]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722320v1?rss=1">
<title>
<![CDATA[
Defining state-selective lipid binding to brain GPCRs - introducing REVEAL 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722320v1?rss=1
</link>
<description><![CDATA[
Membrane lipids are central regulators of G protein-coupled receptor (GPCR) function. Defining receptor-specific lipid interactions in native, fully modified mammalian systems remains challenging. Extensive post-translational modifications generate heterogeneous proteoforms that confound conventional mass spectrometry approaches. Here we introduce REVEAL (REceptor enVironment Elucidation by Activated Lipid-release), an automated native top-down mass spectrometry strategy that discriminates specifically bound lipids from background. Applied here to intact, heterogeneous mammalian membrane protein complexes, incubated with a brain polar lipid extract (>1000 components), we define receptor-specific lipid-binding for two neuronal class C GPCRs. We show that agonism remodels lipid occupancy, selectively enriching a reduced repertoire of bound lipids. Plasmalogen lipids emerge as persistent binders across all conformational states of the metabotropic glycine receptor and are preferentially depleted under oxidative stress, implying a protective role at the receptor surface. These findings position lipids as dynamic regulators of both function and response to the cellular redox environment.
]]></description>
<dc:creator><![CDATA[ Lawrence, S. A. S., Kirschbaum, C., Lutomski, C. A., Song, H., Hinkle, J. D., Butroid, F. I., Melani, R., Syka, J. E. P., Mullen, C., El-Baba, T. J., Robinson, C. V. ]]></dc:creator>
<dc:date>2026-05-05</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722320</dc:identifier>
<dc:title><![CDATA[Defining state-selective lipid binding to brain GPCRs - introducing REVEAL]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.721940v1?rss=1">
<title>
<![CDATA[
Mechanics-Driven Emergence of Mesenchymal Migration Features 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.721940v1?rss=1
</link>
<description><![CDATA[
Cell migration plays a central role in numerous physiological and pathological processes and emerges from the coordinated interplay between intracellular force generation, adhesion dynamics, and mechanical interactions with the environment. A minimal, mechanistically grounded understanding of these processes is required to disentangle the respective contributions of cell-intrinsic and environmental cues. Here, a two-dimensional in silico cell motility model is introduced to describe mesenchymal migration driven by intracellular traction forces generated within actin-rich protrusions anchored to a substrate. The model explicitly accounts for adhesion nucleation, maturation, force buildup and rupture, and relies on a small set of physically interpretable parameters.

A systematic mechanical analysis identifies parameter regimes that permit effective cell translocation and delineates conditions leading to stalled or mobile cells. Within motile regimes, the model reproduces a broad spectrum of cell morphologies and migratory behaviours. In particular, cell trajectories exhibit the statistical features of a persistent random walk, with a crossover from ballistic to diffusive motion that arises solely from adhesion dynamics and force balance, without imposing polarization or directional bias. Cell morphology is shown to strongly regulate migration speed, persistence, and pausing behaviour.

Altogether, this model provides a minimal reference framework for cell migration on non-deformable substrates and establishes a baseline for future studies of mechanically driven guidance. By construction, it is well suited for extension to deformable fibrous substrates, where cell-induced matrix remodeling and stiffness feedback are expected to bias migration and regulate cell encounters relevant to tissue morphogenesis and anastomosis.
]]></description>
<dc:creator><![CDATA[ Louviaux, N., Cheddadi, I., Verdier, C., Stephanou, A., Chauviere, A. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.721940</dc:identifier>
<dc:title><![CDATA[Mechanics-Driven Emergence of Mesenchymal Migration Features]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.721921v1?rss=1">
<title>
<![CDATA[
CTGoMartini: A Python Framework for Simulating Biomolecular Conformational Transitions with Go-Martini Models 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.721921v1?rss=1
</link>
<description><![CDATA[
Characterizing conformational transitions between distinct structural states is essential for understanding protein function but remains challenging due to the timescale limitations of atomistic molecular dynamics. While coarse-grained models like Martini accelerate sampling, classical elastic-network or G[o]-like restraints often trap proteins in a single energy basin, precluding the study of transition pathways between distinct functional states. Here, we present CTGoMartini, a comprehensive Python package designed to simulate protein conformational transitions using G[o]-Martini models in explicit membranes. CTGoMartini addresses key methodological limitations of existing approaches by redefining native contacts as a dedicated interaction type, thereby eliminating spurious protein aggregation artifacts in multi-copy simulations. The package implements both switching and multiple-basin approaches (Exponential and Hamiltonian mixing) to sample transitions between experimentally defined states. Furthermore, it integrates Hamiltonian replica exchange molecular dynamics (HREMD) with PyMBAR analysis, enabling efficient optimization of mixing parameters that govern barrier heights and relative state stabilities. We demonstrate the power of CTGoMartini through two biologically significant membrane protein systems: (1) capturing the inward-open to outward-open transition of the lipid transporter SPNS2, revealing the molecular mechanism of S1P translocation; and (2) elucidating how membrane surface tension and anionic lipids (POPA, PIP2) modulate the conformational equilibrium of the mechanosensitive ion channel TREK1. By streamlining model construction, simulation, and analysis, CTGoMartini offers an easy-to-use platform that connects static structural snapshots with their underlying dynamic functional mechanisms.

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]]></description>
<dc:creator><![CDATA[ Yang, S., Song, C. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.721921</dc:identifier>
<dc:title><![CDATA[CTGoMartini: A Python Framework for Simulating Biomolecular Conformational Transitions with Go-Martini Models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.30.721971v1?rss=1">
<title>
<![CDATA[
Condensate-Like Organization in Respiratory Aerosols Modulates the Dynamics of an Airborne Virus 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.30.721971v1?rss=1
</link>
<description><![CDATA[
The molecular behavior of viruses within respiratory aerosols plays a critical role in airborne disease transmission yet remains largely inaccessible to experimental characterization. Here, we use a billion-atom all-atom molecular dynamics simulation of a virus-laden respiratory aerosol to uncover how respiratory proteins, lipids, ions, and water collectively assemble around SARS-CoV-2, giving rise to structured microenvironments that influence viral stability and spike dynamics. We find that respiratory components rapidly evolve into heterogeneous networks characterized by protein-rich aggregates, patchy lipid assemblies, and spatially structured ion and water dynamics. These features create distinct microenvironments that constrain molecular transport and stabilize regions surrounding the virion. Within this crowded aerosol context, we observe sustained and selective interactions between aerosol components and the viral spike protein, including preferential recruitment of surfactant lipids and persistent coordination by divalent cations. These interactions modulate spike conformational dynamics, enhancing domain breathing motions and flexibility at key hinge regions while preserving a stable membrane anchor. Together, these observations reveal a condensate-like physical regime in which multivalent aerosol components coalesce into a soft, heterogeneous matrix that selectively modulates viral protein dynamics under extreme crowding. By framing virus-laden respiratory aerosols within this physical context, this work establishes an in situ molecular framework for understanding how aerosols influence viral persistence and offers a platform for exploring mechanisms relevant to airborne disease transmission and mitigation strategies.

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O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/721971v1_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@87cf4aorg.highwire.dtl.DTLVardef@3a2ea1org.highwire.dtl.DTLVardef@1cb5c8eorg.highwire.dtl.DTLVardef@299582_HPS_FORMAT_FIGEXP  M_FIG C_FIG SynopsisRespiratory aerosols exhibit condensate-like physical properties that govern the evolution of the particle and modulate the behavior of airborne SARS-CoV-2.
]]></description>
<dc:creator><![CDATA[ Wauer, N., Calvo-Tusell, C., Dommer, A., Casalino, L., Kearns, F., Caparotta, M., Rosenfeld, M., Morris, C., Amaro, R. E. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.04.30.721971</dc:identifier>
<dc:title><![CDATA[Condensate-Like Organization in Respiratory Aerosols Modulates the Dynamics of an Airborne Virus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.02.722415v1?rss=1">
<title>
<![CDATA[
Connecting Cryo-EM and Crystallographic Views of RNA Folding through Ionic Conditions and Structural Flexibility 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.02.722415v1?rss=1
</link>
<description><![CDATA[
Discrepancies between biomolecular structures resolved by cryo-electron microscopy (cryo-EM) and X-ray crystallography (XRD) often arise from differences in ionic conditions and construct design, yet their mechanistic impact on RNA folding remains unclear. In the SARS-CoV-2 frameshifting stimulatory element, cryo-EM and XRD structures reveal distinct pseudoknot conformations--a bent and a coaxially stacked state--complicating its structure-function relationship. Here, combining all-atom explicit-solvent simulation results with a structure-based electrostatic model, we show that Mg{superscript 2} ions drive transitions between these states by stabilizing long-range tertiary interactions and modulating local dynamical coupling involving the slippery site and stem 3. Energy landscape analysis reveals distinct folding pathways, while deletion of the slippery segment in crystallographic constructs alters intermediates and produces pathways inconsistent with single-molecule optical tweezer experiments. This study demonstrates how condition-dependent experiments encode complementary interaction-level information and how physics-based computational approaches integrate these to yield a coherent, mechanistic picture of RNA folding.

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]]></description>
<dc:creator><![CDATA[ Mainan, A., Roy, S., Kirmizialtin, S. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.05.02.722415</dc:identifier>
<dc:title><![CDATA[Connecting Cryo-EM and Crystallographic Views of RNA Folding through Ionic Conditions and Structural Flexibility]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.04.29.721778v1?rss=1">
<title>
<![CDATA[
MeTAL enables multiparametric risk prediction for human KCNH2 variants 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.04.29.721778v1?rss=1
</link>
<description><![CDATA[
BackgroundClinical interpretation of missense variants in the hERG potassium channel encoded by the KCNH2 gene remains a major challenge in inherited arrhythmia syndromes. Functional studies often rely on a minimal set of channel properties, mainly current amplitude measurements, which do not capture the multidimensional nature of channel gating and its impact on ventricular repolarization. We developed a multiscale computational framework to quantitatively link multiparametric channel dysfunction to ECG phenotypes.

MethodsWe generated multiparametric electrophysiological profiles for KCNH2 variants using high-throughput patch-clamp, quantifying nine biophysical properties including conductance, voltage dependence, and gating kinetics. These parameters were incorporated into a modified formulation of IKr embedded in a human ventricular electrophysiology model. The resulting framework, termed MeTAL (Multiscale-enriched Transformation and Analysis for Long-QT), produces physiologically calibrated pseudo-ECGs enabling quantitative evaluation of QT dynamics. We systematically analyzed the contribution of individual and combined gating parameters and applied the model to 41 KCNH2 variants across ACMG classes, comparing simulated QTc values with clinical data.

ResultsMultiparametric profiling revealed complex functional signatures in most variants, with concurrent gain- and loss-of-function effects affecting distinct gating processes. Simulations demonstrated that ventricular repolarization, though strongly determined by current amplitude, is substantially influenced by inactivation-related parameters, particularly the slope and voltage dependence of inactivation. Interaction analyses showed nonlinear relationships between gating parameters, explaining why variants with similar current density can produce divergent QT phenotypes. In heterozygous simulations, MeTAL reproduced clinically observed QTc distributions across variant classes and accurately predicted the repolarization regime (normal, long-QT, or short-QT) in most cases.

ConclusionsMultiparametric integration of ion-channel function within a multiscale electrophysiological model enables mechanistic prediction of QT behavior beyond conductance-based metrics. This approach provides a scalable framework for interpretation of KCNH2 variants and solves the issue of risk stratification in inherited arrhythmia syndromes while offering new opportunities for variant-specific and pharmacological modeling of repolarization.
]]></description>
<dc:creator><![CDATA[ Ribeiro de Oliveira Mendes, B., Voisin, E., Marbouty, M., Gregoire, A., Alameh, M., Montnach, J., Thollet, A., Charpentier, F., Denjoy, I., Probst, V., Loussouarn, G., Baro, I., De Waard, M., Majumder, R. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.04.29.721778</dc:identifier>
<dc:title><![CDATA[MeTAL enables multiparametric risk prediction for human KCNH2 variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.05.01.722017v1?rss=1">
<title>
<![CDATA[
In vivo elastography of the human retina using light-evoked intrinsic actuation 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.05.01.722017v1?rss=1
</link>
<description><![CDATA[
The biomechanical properties of the retina govern its function, structural integrity, and susceptibility to disease, yet remain difficult to measure in vivo due to the lack of safe, spatially localized mechanical actuation. Here, we introduce a framework for probing retinal biomechanics in the living human eye by leveraging intrinsic optical actuation driven by phototransduction. Using phase-resolved optical coherence tomography with a local phase-referencing approach, we resolved signed, nanometer-scale displacements of the major outer retinal interfaces evoked by light. The resulting deformation field, originating in the photoreceptor outer segment, was distributed across retinal compartments in an eccentricity-dependent manner, with efficient axial transfer in the fovea and attenuated propagation in the parafovea. A hybrid analytical and finite-element framework was developed that retrieved the biomechanical properties of the retinal compartments based on their coordinated deformation and the anatomical variation in retinal structure versus eccentricity. In retinitis pigmentosa, the paradigm enabled the detection of light-evoked deformation in the transition zone despite the loss of native lamination, enabling a functional readout of the vulnerable photoreceptors at the leading edge of degeneration. Together, these results establish intrinsic optical stimulation as a basis for in vivo retinal elastography and enable the non-invasive, quantitative imaging of retinal biomechanics and function in the living human retina.
]]></description>
<dc:creator><![CDATA[ Liu, T., Li, H., Pandiyan, V. P., Chen, K., Bharadwaj, P., Wendel, B. J., Mustafi, D., Chao, J. R., Ling, T., Sabesan, R. ]]></dc:creator>
<dc:date>2026-05-04</dc:date>
<dc:identifier>doi:10.64898/2026.05.01.722017</dc:identifier>
<dc:title><![CDATA[In vivo elastography of the human retina using light-evoked intrinsic actuation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
