Biology subjects

Song, C.

Publications and source records attributed to Song, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

CTGoMartini: A Python Framework for Simulating Biomolecular Conformational Transitions with Go-Martini Models

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. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/721921v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@75eb26org.highwire.dtl.DTLVardef@1a12accorg.highwire.dtl.DTLVardef@e927org.highwire.dtl.DTLVardef@1cb0dcd_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Using machine learning to overcome mosquito collections missing data for malaria modeling

Entomological surveillance plays a crucial role in areas where malaria remains endemic, yet gathering data on mosquito populations is often expensive and complicated, particularly in remote locations with challenging logistics and inconsistent sampling schedules. Access to extensive time series data on mosquito species at specific sites would greatly enhance insights into seasonal trends and the biting habits of vectors of malaria parasites. Gaps in mosquito count records pose a significant challenge for researchers and public health officials seeking to establish early warning systems and effective vector control programs. In this study, we apply quantitative machine learning techniques to address missing data in estimates of mosquito abundance collected from 2009 to 2016 in Bolivar State, Venezuela. We evaluated Linear Regression, Stochastic Linear Regression, K Nearest-Neighbor, and Gradient Boosting methods for imputing missing counts of Anopheles mosquitoes, employing a leave-one-out cross-validation strategy. Additionally, we developed a predictive malaria transmission model incorporating mosquito abundance and climate variables (El Nino 3.4 Index, rainfall, and mean air temperature) as covariates. Our generalized time series model forecasts malaria incidence of Plasmodium vivax and Plasmodium falciparum based on climate dynamics and imputed mosquito data. Model performance was assessed using root mean square error, mean absolute error, and mean absolute percentage error. The final results demonstrated that machine learning imputation significantly improved the accuracy and reliability of P. vivax malaria incidence predictions but failed to predict P. falciparum incidence. The study demonstrates that method choice significantly influences the reconstruction of seasonal abundance patterns and the performance of malaria incidence models. Nevertheless, the proposed models strengthen the foundation for targeted interventions and surveillance in endemic regions. Despite limitations in data continuity and coverage, the findings highlight the value of combining multiyear entomological data sets with robust imputation and sensitivity analyses to improve predictive modeling in resource-constrained, malaria-endemic settings.

bioinformatics↗

bioRxiv2026

Transformation-tolerant object recognition in tree shrews despite lacking a fovea

Object recognition depends on the ability to extract stable representations across changes in how they are viewed, yet it remains unclear how this capacity depends on visual acuity and cortical hierarchy. We combined behavioral testing and computational modeling to determine whether tree shrews, close relatives of primates with lower spatial acuity, can perform transformation-tolerant object recognition. Front-end modeling incorporating species-specific optics and photoreceptor sampling showed that, when scaled for acuity, tree shrew retinal filtering preserves the similarity structure of natural image categories relevant for object recognition. Behaviorally, tree shrews reliably discriminated complex objects across variations in position, scale, and viewpoint, including when embedded within natural scenes, and generalized to novel exemplars. Their recognition behavior was best explained by visual features emphasizing differences in global shape and size between objects and by representations from intermediate and deep layers of hierarchical neural network models. These results demonstrate that visual processing supporting object-level generalization can arise within visual systems lacking high-acuity front-end optics and establish the tree shrew as a key model for understanding the computational and evolutionary origins of high-level vision.

animal behavior and cognition↗

bioRxiv2026

An Optimized RNF126-Targeting Covalent Handle for Molecular Glue Degraders

Molecular glue degraders represent a powerful modality for targeting proteins that are refractory to traditional inhibition. However, rational design principles for molecular glue degraders remain poorly defined. Previously, we reported a chemistry-centric strategy to identify covalent degradative handles that, when appended to established ligands, convert non-degradative inhibitors into molecular glue degraders by engaging permissive E3 ligases. This effort identified a fumarate-based electrophilic handle that covalently modified the E3 ligase RNF126, enabling degradation of multiple protein targets when transplanted across diverse ligands. Despite its conceptual impact, the high intrinsic reactivity and cytotoxicity of the fumarate handle limited its translational utility. Here, we report the development of an optimized and metabolically stabilized RNF126-targeting covalent handle incorporating a trans-cyclobutane linker that exhibits reduced glutathione reactivity and diminished cytotoxicity while retaining robust degradative activity. When appended to the BET bromodomain inhibitor JQ1, this optimized handle yielded a potent and selective BRD4 degrader whose activity was dependent on RNF126. Importantly, transplantation of this handle onto a previously non-inhibitory ligand targeting the androgen receptor (AR) and its truncation variant, AR-V7, enabled selective degradation of both AR and AR-V7 in androgen-independent prostate cancer cells, thereby robustly inhibiting AR transcriptional activity beyond the established AR antagonist enzalutamide. Collectively, these findings demonstrate an optimized RNF126-based covalent handle for the rational development of molecular glue degraders against transcriptional regulators, including undruggable variants such as AR-V7.

biochemistry↗

bioRxiv2026

PepMCP: A Graph-Based Membrane Contact Probability Predictor for Membrane-Lytic Antimicrobial Peptides

MotivationThe membrane-lytic mechanism of antimicrobial peptides (AMPs) is often overlooked during their in silico discovery process, largely due to the lack of a suitable metric for the membrane-binding propensity of peptides. Previously, we proposed a characteristic called membrane contact probability (MCP) and applied it to the identification of membrane proteins and membrane-lytic AMPs. However, previous MCP predictors were not trained on short peptides targeting bacterial membranes, which may result in unsatisfactory performance for peptide studies. ResultsIn this study, we present PepMCP, a peptide-tailored model for predicting MCP values of short peptides. We collected more than 500 membrane-lytic AMPs from the literature, conducted coarse-grained molecular dynamics (MD) simulations for these AMPs, and extracted their residue MCP labels from MD trajectories to train PepMCP. PepMCP employs the GraphSAGE framework to address this node regression task, encoding each peptide sequence as a graph with 4-hop edges. PepMCP achieved a Pearson correlation coefficient of 0. 883 and an RMSE of 0. 123 on th e node-level test set. It can recognize membrane-lytic AMPs with the predicted MCP values for each sequence, thereby facilitating mechanism-driven AMP discovery. Additionally, we provide a database, MemAMPdb, which includes the membrane-lytic AMPs, as well as the PepMCP web server for easy access. Availability and ImplementationThe code and data are available at https://github.com/ComputBiophys/PepMCP. Contactc.song@pku.edu.cn Supplementary InformationSupplementary data are available online.

bioinformatics↗

bioRxiv2026

Intermittent AP-1 activation in muscles contributes to exercise-induced health benefits

Regular physical exercise extends healthspan, yet the molecular mechanisms that translate intermittent contractile stress into lasting benefit remain incompletely understood. Using global nuclear run-on (GRO-seq) in mouse skeletal muscle after treadmill running, we profiled enhancer RNA (eRNA), a sensitive marker of enhancer activity. Activation protein-1 (AP-1), a family of pioneering factors for senescence, emerged as the top transcription factor with motif enrichment in exercise-activated enhancers. Our screen in the contracting C2C12 myotubes pinpointed cFos/JunD as the primary AP-1 factor responsible for contraction-induced transcriptional changes. Muscle-specific overexpression of A-Fos, a dominant-negative mutant of cFos, disrupted transcriptomic responses to exercise and attenuated exercise-mediated improvement in muscle functions. Interestingly, intermittent but not continuous overexpression of cFos/JunD in mouse muscles mimicked exercise-induced transcriptomic changes, increased mitochondrial volume density, enhanced muscle strength and fatigue resistance, and improved glucose tolerance. These results define a transcriptional regulatory signaling pathway linking exercise intermittency to beneficial adaptations and highlight the necessary recovery cycles in training. The paradoxical anti- and pro-aging roles of AP-1 offer insights into the timing and dynamics of stressors and stress responses in shaping senescence and healthspan.

molecular biology↗

bioRxiv2026

Multitimescale Computation by Astrocytes

The basic computational unit of the brain has long been defined as the neuron. However, mounting evidence suggests that other cells, especially astrocytes, also perform computations. Here, we demonstrate that cerebellar astrocytes decompose norepinephrine input into slow and fast calcium ion activities through differential adrenergic receptor engagement. During reward learning in mice, these slow and fast activities selectively target and modulate distinct synaptic pathways. Causal manipulations reveal that fast 2-adrenergic signals govern event-triggered responses and reinforcement learning, whereas slow 1-adrenergic signals maintain behavioral states and coordinate transitions. Remarkably, an actor-critic neural network trained on a similar sequence task spontaneously recapitulates these multitemporal dynamics, suggesting that astrocytes implement critic-like computations that evaluate states and modulate neuronal learning. These findings establish astrocytes as multilevel processors that transform univariate neuromodulatory inputs into multivariate, pathway-specific circuit controls operating in parallel with neuronal processing.

neuroscience↗

bioRxiv2025

Multi-Timescale Neural Adaptation Failure as a Mechanistic Signature of Major Depression

Major depression (MD) is usually characterized in terms of momentary abnormalities, such as negative bias or emotional blunting, derived from paradigms that measure only the first response to a stimulus. Yet depressive experience in daily life is repetitive and cumulative. Here we test the hypothesis that a failure of neural adaptation across repetitions is a core feature of MD. Using a repeated negative-stimulus paradigm, we quantified adaptation at micro (within-trial) and macro (across-session) scales via electroencephalography in 28 MD patients and 34 healthy controls, measuring both conventional event-related potentials and large-scale traveling-wave propagation. MD patients exhibited pervasive maladaptation: neural rigidity at the micro scale (absent repetition suppression) and progressive regulatory depletion at the macro scale (escalating emotional reactivity with declining cognitive control). Across analyses, adaptation-based metrics revealed larger group differences than single-shot indices, and classifiers built on adaptation features--especially traveling-wave dynamics--outperformed single-shot models (task AUC = 0.83 vs 0.78) and generalized to two independent datasets (up to AUC = 0.91). These findings challenge conventional symptom-based characterizations of MD, establishing adaptation failure--not initial reactivity--as the mechanistically primary pathological signature. This reframing provides a unified mechanistic explanation for rumination and cognitive inflexibility while offering a standardized, low-cost biomarker requiring minimal electrodes ([≤]8 channels), enabling large-scale screening in resource-limited settings.

neuroscience↗

bioRxiv2025

Torsins Organize CLCC1 Assembly to Safeguard ER Bilayer and Lipid Homeostasis

The TMEM41B scramblase and its regulatory partner CLCC1 initiate lipid flux by equilibrating newly-synthesized phospholipids across the endoplasmic reticulum (ER) bilayer, a fundamental process required for diverse events ranging from membrane biogenesis to bulk lipid supply. Loss of CLCC1/TMEM41B causes ER bilayer imbalance, inducing giant ER-enclosed lipid droplets (geLDs) and driving rapid progression into severe MASH. Here we identify CLCC1 as the long-missing client of the lumenal Torsin ATPases, which selectively engage oligomerized CLCC1 at sites of ER bilayer imbalance. Hepatic TorsinA inactivation triggers geLD formation amid disrupted lipoprotein biogenesis and severe MASH, closely phenocopying CLCC1/TMEM41B deficiency. Mechanistically, Torsins act as foldases that drive CLCC1 oligomerization for its recruitment to imbalanced bilayers. Remarkably, ectopic CLCC1 expression reverses cellular and systemic lipid disorders arising from hepatic TorsinA deficiency. Hence, Torsin ATPases emerge as fundamental regulators that organizes CLCC1 and the downstream TMEM41B scramblase to govern lipid partitioning and membrane homeostasis.

cell biology↗

bioRxiv2025

Master clock-thalamic-prefrontal circuit controls circadian social priority

Social behaviors arise from complex brain operations that adapt to changing social contexts and internal states. However, how internal states guide the resolution of competing social goals remains unclear. Here, we show that prioritization between competing instincts follows a circadian pattern via a circuit linking the suprachiasmatic nucleus (SCN) to the medial prefrontal cortex (mPFC). Specifically, SCNVIP neurons project to Vipr2-expressing neurons in the nucleus reuniens (RE), which innervate the mPFC to regulate social prioritization. Vipr2 signaling in the RE is essential for circadian modulation of appetitive and consummatory social behaviors, aligning social behaviors with clock-regulated reproductive system. Overall, this SCN-RE-mPFC circuit provides a neural principle through which the master clock coordinates the prefrontal cortex to resolve a conflict of motivated behaviors by referencing an internal state.

neuroscience↗

bioRxiv2025

Mechanics and growth coordination define SOSEKI-based polarity fields

The formation of organs requires the coordinated growth of cells and tissues relative to the main body axes. Plant growth is typically anisotropic and mechanically coupled through contiguous cell walls, yet how these physical patterns link to cell and tissue polarity remains unclear. Here, we use SOSEKI (SOK) proteins--previously thought to report global polarity fields--as markers to dissect how polarity arises during lateral root (LR) organogenesis. Live imaging revealed that SOK polarisation does not follow a uniform global field but instead responds to local differences in growth and mechanical state between neighbouring tissues. SOKs accumulate at interfaces separating domains of distinct growth behaviour and dissipate under compressive stress. After perturbing tissue interfaces or the mechanical continuity of the tissue, the coherence of the polarity was disrupted, indicating that stable axis establishment requires mechanical coupling across the cell wall network. Our results suggest that SOK polarisation is mechanoresponsive, linking tissue mechanics to polarity and axis establishment.

plant biology↗

bioRxiv2025

Rapid and accurate quantification of viable Listeria monocytogenes with clonal specificity using microfluidic droplet digital PCR based technology

To overcome the technical bottlenecks in the precise quantification and molecular typing of viable foodborne pathogens, this study establishes a microfluidic droplet digital PCR (ddPCR) based method for rapid and accurate detection and quantification of viable Listeria monocytogenes with clonal specificity. In contrast to the time-consuming plate culture methods and unspecific rapid detection methods, the method in this study employs clonal complex (CC) specific primers and probe for strain-specificity and integrate the nucleic acid dye propidium monoazide (PMA) to effectively distinguish viable from dead bacteria. The rapid and precise quantification of viable bacteria is achieved through microdroplet counting. This method does not require DNA extraction, and the entire detection process takes only about 3 hours, with a quantitative detection limit of 3.3x102 CFU/mL, providing strong technical support for the risk monitoring of highly pathogenic specific types of L. monocytogenes.

microbiology↗

bioRxiv2025

MEDUSA: Maintaining Entire DNA Duplexes for Utmost Sequencing Accuracy

Highly accurate DNA sequencing is essential for many applications. Duplex sequencing-based methods achieve unparalleled accuracy by requiring reads from both strands of the original DNA duplex to match. Yet, methods to prepare dsDNA for sequencing may resynthesize portions of each DNA duplex and cause base damage errors on one strand to become indistinguishable from true mutations on both strands. Here, we report MEDUSA (Maintaining Entire DNA Duplexes for Utmost Sequencing Accuracy) which minimizes dsDNA resynthesis to maximize duplex sequencing accuracy and yield. MEDUSA carefully repairs and blunts fragmented dsDNA, then employs apyrase to digest residual dNTPs, followed by restricted dA-tailing to prevent resynthesis. MEDUSA affords full genome coverage in a simplified protocol that is broadly compatible with dsDNA fragmentation and library preparation kits. We benchmarked MEDUSA on sheared genomic DNA and cell-free DNA and found a residual SNV frequency within a median 1.23-fold (range 0.92-1.88; p < 0.001) of what was expected if resynthesis was mostly blocked, but with full genome coverage and duplex yields within a median 1.02-fold (range 0.33 - 1.46; p = 0.258) of traditional methods that do not limit resynthesis. In all, MEDUSA could enable high breadth or depth of duplex sequencing while limiting false discovery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/687202v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@1ddbc77org.highwire.dtl.DTLVardef@802ca9org.highwire.dtl.DTLVardef@f443ecorg.highwire.dtl.DTLVardef@974bdb_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Species interactions are internally constrained despite large climatic variability

Understanding how vital rates and species interactions vary over time is crucial for predicting community responses to environmental change. Considerable progress has been made in understanding the drivers of variation in vital rates. However, the question of whether interactions are highly plastic and context-dependent, or strongly constrained by internal (e.g., species traits and composition) and/or external factors (e.g., environmental conditions) remains unclear. We applied a theoretical approach based on the feasibility domain --the range of conditions allowing coexistence-- to a nine-year dataset of time-changing interactions between annual plants under large variability in annual precipitation. Using subcommunities of three species, we found that species interactions are strongly constrained, forming a "core-periphery" structure of consistently feasible combinations across years. This main finding means that species sample repeatedly a restricted range of opportunities for coexistence. Similar findings were obtained for subcommunities of four species. Crucially, the constraints to variation in biotic interactions are determined by species identity (internal constraints) rather than precipitation or temporal autocorrelation (external environmental factors). Furthermore, we found a contrasting effect of precipitation on the feasibility of subcommunities. While wetter years increase similarity between subcommunities and reduce the overall feasible range, drier years increase dissimilarity between subcommunities and increase the probability of coexistence when the conditions seem harsher. These findings suggest that constraints to biotic interactions tend to be alike across species in wetter years, but more context dependency occurs across species in drier years. Our findings challenge the assumption of highly plastic species interactions even in a highly dynamic system of annual plants. Our results also highlight the critical importance of internal constraints generated by species identity in mediating community persistence and predicting community responses to environmental change.

ecology↗

bioRxiv2025

MemConverter: An Iterative Pipeline for Reprogramming Protein Localization in Membrane or Aqueous Solution

We propose a pipeline, MemConverter, for the conversion of soluble proteins to membrane proteins and vice versa, based on the prediction of membrane contact probability (MCP). By fine-tuning ProteinMPNN with a membrane protein dataset to create MemProtMPNN, and integrating it with iterative structure refinement using AlphaFold2, our approach enables precise reprogramming of protein surface properties. The pipeline utilizes MCP-guided sequence fusion to direct the evolution of protein sequences towards the desired membrane or soluble environments. During this process, selective residues are fixed to concentrate design efforts on regions requiring alteration. The pipeline demonstrates superior performance compared to existing methods, and molecular dynamics simulations validate that the designed proteins exhibit stable membrane integration or enhanced solubility, depending on the target localization. This pipeline introduces a novel computational tool for engineering proteins to be localized in membranes or aqueous solutions.

biophysics↗

bioRxiv2025

Disruption of a six-nucleotide miRNA motif improves PKD1 dosage and ameliorates polycystic kidney disease

Disrupting microRNA interactions to restore protein expression from haploinsufficient genes offers a promising precision-therapy strategy for monogenic disorders. PKD1 heterozygosity underlies autosomal dominant polycystic kidney disease (ADPKD), a disorder affecting nearly 12 million people worldwide, where reduced PKD1 dosage drives progressive cyst formation and kidney failure. We previously identified a 55-bp cis-repressive element in the PKD1 3'UTR. Here, we define a six-nucleotide miR-17 seed match within this element that is sufficient to reproduce PKD1 repression. In vivo base substitution of this motif stabilizes Pkd1 mRNA and increases polycystin-1 (PC1) protein levels, producing a robust reduction in cyst growth and preservation of kidney function in mouse models. To therapeutically recapitulate this effect, we developed a steric-blocking oligonucleotide that occludes the motif, stabilizes PKD1 transcript levels, increases PC1 expression, and mitigates cyst-pathogenic events in both murine and patient-derived ADPKD cells. Together, these findings establish a minimal, targetable cis-regulatory motif and provide proof-of-concept for oligonucleotide-mediated PKD1 derepression, while offering a potentially generalizable strategy to restore other haploinsufficient genes.

genetics↗

bioRxiv2025

Rice Ethylene Receptors Function as Ca2+-Permeable Ion Channels to Orchestrate Calcium-Dependent Antagonism of Ethylene Responses in Roots

The gaseous phytohormone ethylene governs essential plant processes spanning development, productivity, and stress resistance. As an essential nutrient and second messenger, calcium (Ca2+) is widely implicated in diverse plant physiological activities; however, its role in the ethylene signal transduction pathway remains elusive. Here, we identified a calcium-dependent antagonism of ethylene response (CAER) specifically modulates root elongation in the model cereal rice (Oryza sativa). Interestingly, we demonstrate that the ethylene receptors OsERS1 and OsERS2 both function as Ca2+-permeable channels, with OsERS1 further acting as a non-selective cation channel capable of permeating both monovalent and divalent cations. Mutagenesis analysis reveals that OsERS1 channel activity relies on homomeric assembly sites (C4/C6) rather than its ethylene-binding site (C65), indicating a clear decoupling of the molecular modules governing receptor signaling and ion channel function. The loss-of-function mutant Osers1/2 does not exhibit the CAER phenotype of the wild type (WT), confirm that this calcium-dependent regulatory mechanism is dependent on both OsERS1 and OsERS2. These findings uncover an unexpected ion-channel function of ethylene receptors, redefining their molecular identity beyond canonical signaling proteins and establishing the novel "hormone receptor-type ion channel (HRIC)" paradigm--one that fundamentally expands our understanding of how plant hormones transduce signals at the membrane.

developmental biology↗

bioRxiv2025

Lipid Bilayer Membranes with Asymmetrically Distributed LPC and DAG

The complex chemical and biophysical characteristics of biomembranes are influenced by the asymmetric distribution of specific lipids. In vitro, the introduction of lysophosphatidylcholine (LPC) into one leaflet of lipid bilayers is frequently utilized to regulate membrane protein activity. In vivo, the conversion of phosphatidylinositol 4,5-bisphosphate (PIP2) to diacylglycerol (DAG) in one leaflet can also modulate membrane protein activities. However, the effects of such variations in lipid composition, lipid quantity, and particularly the asymmetry of lipid distribution on the properties and morphology of biomembranes remain to be fully elucidated. Through molecular dynamics simulations, we demonstrate that the asymmetric distribution of LPC and the asymmetric conversion of PIP2 induce asymmetric alterations in membrane structures and lipid dynamics. Such alterations can generate an imbalance in the lateral pressure distribution between the two leaflets, potentially leading to membrane curvature. The extent of membrane curvature is also influenced by the length and degree of unsaturation of the lipid acyl tail chain. Our findings underscore the critical role of lipid asymmetry in shaping biomembrane structure and dynamics, providing new insights into the regulation of membrane proteins and cellular functions mediated by these specific lipids.

biophysics↗