Biology subjects

Sadeghi, M.

Publications and source records attributed to Sadeghi, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Longitudinal Subject Pairing in Cross-Sectional Neonatal Data Reveals Asynchronous Structural and Functional Brain Maturation

The asynchronous development of structural and functional brain networks in early childhood remains largely unexamined, primarily due to the scarcity of longitudinal neuroimaging data. Resolving this temporal dimension is critical, as it promises to reshape our understanding of structural-functional (S-F) coupling, revealing not only whether brain architecture supports function, but also when and over what timescale its influence emerges. However, while rapid neonatal brain maturation and logistical constraints continue to hinder longitudinal data collection, large-scale cross-sectional multimodal datasets are currently available to bridge this gap. Here, we propose a longitudinal subject-pairing framework that reconstructs developmental trajectories from cross-sectional data. It pairs the infants with a predefined age gap while maximizing their similarity in both structural and functional features, thereby approximating the longitudinal trajectory of functional changes in relation to structural maturation. As a case study, we applied this framework to the perisylvian region in a subset of 505 neonates from the multimodal dHCP brain dataset. The myelination index was derived as a structural feature from MRI, and the fractional amplitude of low-frequency fluctuations (fALFF) was derived as a functional feature from resting-state functional MRI. A conventional cross-sectional analysis revealed a moderate S-F correlation magnitude (r = 0.34). In contrast, the proposed framework demonstrated a significant increase in S-F coupling to r = 0.46 when the structural maturation precedes functional maturation by approximately five days. These findings provide novel evidence of a functional maturation lag relative to structural brain development in neonates. Beyond elucidating S-F relationships in the early developing brain, this work establishes a framework for future longitudinal studies and advances in brain modeling across developmental trajectories, aging, and disease prediction.

neuroscience↗

bioRxiv2026

TKI-Tolerant Persisters Emerge from a PKCα-Dependent and Highly Plastic Subpopulation of Stem-Like Cells in NSCLC

Reversible drug-tolerant persister states are emerging as key drivers of limited therapeutic durability, offering a complementary non-genetic perspective distinct from traditional models of acquired resistance. This is of particular interest in lung adenocarcinoma where EGFR tyrosine kinase inhibitors (TKIs) elicit dramatic responses, yet residual surviving cells persist and ultimately seed relapse. To define mechanisms that enable survival during this earliest residual-disease phase, we focused on the drug-tolerant persister population that remains after EGFR TKI exposure and can later give rise to outgrowth. Initial observations of elevated transcript levels of PRKCA, which encodes PKC, in established TKI-resistant models, together with markedly delayed tumor relapse following PKC suppression in vivo, nominated PKC as a candidate regulator of the persister-to-relapse transition. Genetic ablation of PRKCA or its inhibition with enzastaurin reduced residual survival and outgrowth after TKI exposure, indicating that PKC functions as an early dependency of drug-tolerant persisters rather than as a general mediator of acquired resistance. Mechanistically, PKC was required for persister-associated EMT, migratory capacity, and robust induction of ALDH1A1, the latter constraining oxidative stress and enhancing persister survival. Functionally, PKC was specifically necessary for survival of a rare, pre-existing CD44High stem-like subpopulation that exhibited marked plasticity and ultimately seeded persistence. Together, these data identify a PKC-dependent EMT/stemness/ROS pathway as a critical survival program in EGFR TKI-tolerant persister cells and support therapeutic strategies aimed at eliminating residual disease to prolong clinical responses.

cancer biology↗

bioRxiv2026

Dissociable Effects of Early and Adolescent Adversity on Emotional Contagion

BackgroundEarly-life adversity can alter emotional and social development and increase vulnerability to later life stress. We investigated how early adverse experiences (EAE) and later adverse experiences (LAE) shape adult emotional contagion (EC) responses in female and male rats. MethodsEAE was induced using the limited bedding and nesting model during the first postnatal week. LAE was induced via footshocks during adolescence. In adulthood, male and female rats underwent an EC test in which observers witnessed a conspecific receiving footshocks. ResultsAdolescence-footshock exposed observers showed cingulate cortex-associated increased immobility, proximity, and attention toward distressed conspecifics during adulthood, compared to adult-exposed and sham animals, both in male and female animals. While EAE did alter maternal care, pup stress physiology, and pup weight, we found evidence that it did not alter immobility during EC. However, female demonstrators paired with EAE observers showed increased immobility, linked to a reduced rate and lower frequency of the observers 50-kHz vocalizations. Mediation analysis revealed that a shift toward lower-frequency 50-kHz vocalizations specifically mediated this effect, suggesting a sex-specific pathway by which early adversity shapes social behavior. ConclusionsEarly and adolescent adversity influenced distinct aspects of emotional contagion: EAE mediated an observer-to-demonstrator emotional transfer during EC, while LAE impacted a demonstrator-to-observer transfer, with no evidence of additive effects. Our results highlight developmentally specific and sex-dependent mechanisms by which early and later adversity alter social-affective responses in adulthood.

neuroscience↗

bioRxiv2025

Neonatal BCG Vaccination Engages the Vasculature to Elicit γδ T Cell-Mediated Protection against Tuberculosis

The Bacillus Calmette-Guerin (BCG) vaccine remains the only approved vaccine against tuber-culosis (TB). Although its efficacy against pulmonary TB in adults is limited, BCG provides re-markable protection against miliary TB when administered during infancy. Despite more than 100 million infants worldwide receiving BCG annually, the mechanisms underlying its neonatal protective effects remain poorly defined. Here, we demonstrate that subcutaneous neonatal BCG vaccination (BCG-sc) induces a marked expansion of {gamma}{delta} T cells producing IL-17 and IL-22, which mediated protection against subsequent Mycobacterium tuberculosis (Mtb) experimental infection. A similar expansion of {gamma}{delta} T cells was observed in a longitudinal cohort of infants, from birth to three months of infants followed after intradermal BCG vaccination. Mechanistical-ly, BCG-mediated protection in neonates was linked to its early vascular dissemination through the distinct structure of neonatal skin, resembling the protective effects of intravenous BCG in adults. Moreover, neonatal BCG-sc vaccination generated a distinct BCG-induced microbiome signature, characterized by enrichment of Prevotellaceae, Tannerellaceae, and Bifidobacteriaceae, which was associated with protection. Together, these findings identify {gamma}{delta} T cells as key mediators of early-life BCG-induced immunity and highlight the role of the gut-lung axis in long-term protection against TB from infancy into adulthood.

immunology↗

bioRxiv2025

Quantitative pharmacology methods for bispecific T cell engagers

T Cell Engager (TCE)s are an exciting therapeutic modality in immuno-oncology that acts to bypass antigen presentation and forms a direct link between cancer and immune cells in the Tumor Microenvironment (TME). TCEs are efficacious only when the drug is bound to both immune and cancer cell targets. Therefore, approaches that maximize the formation of the drug-target trimer in the TME are expected to increase the drugs efficacy. In this study, we quantitatively investigate how the concentration of ternary complex and its biodistribution depend on both the targets specific properties and the design characteristics of the TCE, and specifically on the binding kinetics of the drug to its targets. A simplified mathematical model of drug-target interactions is considered here, with insights from the "three-body" problem applied to the model. Parameter identifiability analysis performed on the model demonstrates that steady state data, which is often available at the early pre-clinical stages, is sufficient to estimate the binding affinity of the TCE molecule to both targets. We used the model to analyze several existing antibodies, both clinically approved and under development, to explore their common kinetic features. The manuscript concludes with an assessment of a full quantitative pharmacology model that accounts for drug disposition into the peripheral compartment.

systems biology↗

bioRxiv2025

SimMapNet: A Bayesian Framework for Gene Regulatory Network Inference Using Gene Ontology Similarities as External Hint

MotivationGene regulatory network (GRN) reconstruction is a fundamental challenge in computational biology, and is crucial for understanding gene interactions. In this study, we aim to incorporate Gene Ontology (GO) similarities into the construction of GRNs. Our key assumption is that genes with higher similarity in Molecular Function, Biological Process, or Cellular Component categories are more likely to be functionally related and, therefore, more likely to be connected in the network. We introduce SimMapNet, a Bayesian framework that estimates the precision matrix, which serves as the adjacency matrix in a Gaussian graphical model (GGM) for GRN inference. SimMapNet enhances network inference by integrating GO similarities, which inform the hyperparameters of the prior distribution through a kernel function, incorporating biological prior knowledge in a principled manner. ResultsWe evaluate SimMapNet on three datasets: two datasets from the SOS DNA-repair response pathway in Escherichia coli and one dataset from Drosophila melanogaster. The results demonstrate the algorithms superior performance compared to state-of-the-art methods such as GLASSO, GENIE3, and KBOOST in terms of F1-score. SimMapNet has low time complexity, making it suitable for constructing large networks. Our simulation results confirm that SimMapNet is particularly well-suited for scenarios with limited sample sizes, where traditional methods often struggle. Availability and implementationThe datasets and R package of SimMapNet are available in the github repository, https://github.com/maryam-shahdoust/SimMapNet.

bioinformatics↗

bioRxiv2025

Poor prognosis in IBD-complicated colon cancer through gut dysbiosis-related immune response failure

BackgroundColorectal cancer (CRC) results from the accumulation of mutations and epigenetic changes in gut epithelial cells likely due to gut microbiota dysbiosis. However, limited research has been done to explore the link between host tumour dysbiosis and disease outcome. MethodsThe mechanisms influencing outcomes of 97 colorectal cancer (CRC) patients, including 13 with Lynch syndrome, 20 with inflammatory bowel disease (IBD), and 64 sporadic cases, were analyzed using a multiomics approach. These patients were categorized into two groups: "disease-free/stable disease" and "progression disease" survival outcomes. The analysis included tumor adherent microbiota composition (16S rRNA), somatic gene mutations (WES), gene expression (RNAseq), immune markers (RNAscope), and immune infiltrate cells (immunohistochemistry). ResultsIBD-CRC patients had worse outcomes than those with Lynch or sporadic CRC, regardless of TNM staging or treatment. Symbiotic bacteria like Lactococcus lactis were significantly reduced in IBD-CRC tissues. Patient outcomes were influenced by the abundance of virulent (Escherichia coli) relative to beneficial bacteria (Lactococcus lactis). Although no significant increase in deleterious somatic mutations was found in IBD-CRC. 16sRNA revealed increased virulent- and decreased anti-inflammatory symbiotic-bacteria correlating with the upregulation of oncogenes and downregulation of anti-oncogenes like PHLPP1. The multiplex in situ hybridization of CD8, IFN{gamma} and PHLPP1 an anti-oncogene revealed significant decrease of immune cells with detectable PHLPP1 expression in IBD-CRC tumour tissues as compared to sporadic CRCs. ConclusionThe poor outcomes in IBD-CRC patients are likely due to gut dysbiosis and immune cell alterations, possibly triggered by microbiota-related epigenetic pathways. What You Need to KnowO_ST_ABSBACKGROUND AND CONTEXTC_ST_ABSColorectal cancer (CRC) is associated with gut microbiota dysbiosis. Inflammatory bowel disease-related CRC (IBD-CRC) is classified as an environment-related condition. NEW FINDINGSIn relation with patient outcomes, tumour tissues from three types of CRC (Sporadic-, IBD-, and Lynch syndrome-CRC) were analyzed using a multiomic approach. This included examining tissue adherent virulent bacteria, gene analyses, and quantifying immune cell infiltration in the mucosa. IBD-CRC patients had the worst outcomes, associated with the down regulation of PHLPP1 gene, virulent/symbiotic imbalance, and immune response failure. LIMITATIONSLack of animal experiments using FMT of fresh stool from IBD-CRC patients. CLINICAL AND TRANSLATIONAL RESEARCH RELEVANCEAmong the different types of CRC, IBD-CRC patients showed a greater imbalance between harmful and beneficial bacteria, along with immune response failure. Lay summaryThis study compares the pathological and clinical characteristics of patients with colorectal cancer (CRC) across three distinct etiologies: sporadic CRC, inflammatory bowel disease (IBD)-associated CRC, and Lynch syndrome-associated CRC (LS-CRC). Distinct differences in tumor-adherent microbiota, gene expression and immune response profiles were observed. Notably, IBD-CRC patients demonstrated the poorest prognosis depending on microbe-host gene interaction highlighting potential biomarkers for disease prognosis and treatment strategies.

immunology↗

bioRxiv2025

Dynamic nanoscale architecture of synaptic vesicle fusion in mouse hippocampal neurons

During neurotransmission, presynaptic action potentials trigger synaptic vesicle fusion with the plasma membrane within milliseconds. To visualize membrane dynamics before, during, and right after vesicle fusion at central synapses under near-native conditions, we developed an experimental strategy for time-resolved in situ cryo-electron tomography with millisecond temporal resolution. We coupled optogenetic stimulation with cryofixation and confirmed the stimulation-induced release of neurotransmitters via cryo-confocal microscopy of a fluorescent glutamate sensor. Our morphometric analysis of tomograms from stimulated and control synapses allowed us to characterize five states of vesicle fusion intermediates ranging from stalk formation to the formation, opening, and collapsing of a fusion pore. Based on these measurements, we generated a coarse-grained simulation of a synaptic vesicle approaching the active zone membrane. Both, our morphofunctional and computational analyses, support a model in which calcium-triggered fusion is initiated from synaptic vesicles in close proximity to the active zone membrane, whereby neither tight docking nor an induction of membrane curvature at the active zone are favorable. Numbers of filamentous tethers closely correlated to the distance between vesicle and membrane, but not to their respective fusion readiness, indicating that the formation of multiple tethers is required for synaptic vesicle recruitment preceding fusion.

neuroscience↗

bioRxiv2024

β-Glucan Reprograms Neutrophils to Induce Disease Tolerance Against Influenza A Virus

ABSTRACTDisease tolerance is an evolutionarily conserved host defence strategy that preserves tissue integrity and physiology without affecting pathogen load. Unlike host resistance, the mechanisms underlying disease tolerance remain poorly understood. In the present study, we investigated whether an adjuvant ({beta}-glucan) can reprogram innate immunity to provide protection against Influenza A virus (IAV) infection. Here we observe that {beta}-glucan treatment reduced the morbidity and mortality against IAV infection, independent of host resistance (viral load). Increased survival of {beta}-glucan treated mice against IAV is associated with the accumulation of neutrophils via RoR{gamma}t+ T cells in the lung tissue. Using gain-and-loss-of-function approaches, we demonstrate that {beta}- glucan reprogrammed neutrophils are essential for promoting disease tolerance, limiting pulmonary tissue damage, and enhancing survival against IAV infection. {beta}-glucan treatment promotes granulopoiesis in a type 1 interferon-dependent manner that leads to the generation of a unique subset of neutrophils, which are less mature with higher mitochondrial mass utilizing mitochondrial oxidative (OXPHOS) metabolism. Collectively, our data indicate that {beta}-glucan reprograms hematopoietic stem cells (HSCs) to generate neutrophils with a novel "regulatory" function, which is required for promoting disease tolerance and maintaining lung tissue integrity against viral infection.

immunology↗

bioRxiv2024

β-glucan reprograms alveolar macrophages via neutrophil/IFNγ axis to promote lung injury

Alveolar macrophages (AMs) reside in the lower airways and play a crucial role in lung health and response to sterile inflammation and infections. AMs possess remarkable adaptability to different environmental challenges that can persist through their memory capacity (trained immunity). {beta}-glucan has been characterized as a potent inducer of central trained immunity by reprogramming hematopoietic stem cells (HSCs) in the bone marrow. In the present study, we show that systemic administration of {beta}-glucan induces peripheral trained immunity by reprogramming alveolar macrophages (AMs) in the lungs, in a Dectin1-independent manner. We furthermore demonstrate that AM reprogramming at both the transcriptional and metabolic levels exacerbate lung injury following bacterial (LPS) or viral (polyI:C) challenges via a neutrophil/IFN-{gamma} dependent manner. These findings identify an additional facet of {beta}-glucan in trained immunity involving AM reprogramming and shed light on the potential detrimental effects of trained immunity.

immunology↗

bioRxiv2023

Sub-membrane actin rings compartmentalize the plasma membrane

The compartmentalization of the plasma membrane is a fundamental feature of cells. The diffusivity of membrane proteins in the plane of the membrane is significantly lower in cells than observed in artificial membranes. This seems due to the sub-membranous actin cortex, but tractable assays to prove a direct dependence of membrane protein motion on actin filaments have been elusive. We recently showed that a periodic array of sub-membrane actin filaments that surround neuronal axons in ring-like structures in the axonal initial segment (AIS) confines membrane protein motion between them, but the local enrichment of ion channels may offer an alternative explanation for compartmentalization. Here we show using computational modeling that in contrast to actin rings, the dense array of ion channels in the AIS cannot mediate membrane protein confinement. We go on to show that indeed the actin rings are closely apposed to the plasma membrane, and that they confine membrane protein motion between them in a [~] 200 nm periodic pattern in progenitor-derived neuronal cells. We find that this compartmentalization is also detectable for inner-leaflet membrane proteins and multi-spanning receptors. Strikingly, several cell types with actin rings in their protrusions, like progenitor-derived astrocytes and oligodendrocytes, also exhibit lateral confinement of membrane proteins in a periodic pattern consistent with actin ring spacing. Actin ring-mediated membrane compartmentalization is thus not unique to neurons. Finally, we show that acute actin disruption in live progenitor-derived neuronal cells leads to a loss of membrane compartmentalization in areas that were compartmentalized before treatment. Taken together, we here develop a much-needed tractable experimental system for the investigation of membrane compartmentalization and show that actin rings compartmentalize the plasma membrane of cells.

biophysics↗

bioRxiv2023

Correspondence between Signaling and Developmental Patterns by Competing Cells: A Computational Perspective

Arrangement of variant phenotypes in ordered spatial assemblies during division of stem cells is essential for the self-organization of cell tissues. The cellular patterns of phenotypes competing for space and resources against one another are mostly driven by secreted diffusible chemical signaling clues. This complex process is carried out within a chronological framework of interplaying intracellular and intercellular events. This includes receiving external stimulants-whether secreted by other individuals or provided by the environment-interpreting these environmental signals and incorporating the information to designate cell fate. An enhanced understanding of the building blocks of this framework would be of help to set the scene for promising regenerative therapies. In this study, by proposing a designative computational map, we show that there is a correspondence between signaling and developmental patterns that are produced by competing cells. That is, the model provides an appropriate prediction for the final structure of the differentiated cells in a competitive environment. Besides, given that the final state of the cellular organization is known, the corresponding regressive signaling patterns are partly predictable following the proposed map. Author SummaryMulticellular organisms are made of repeated divisions of single cells and aggregation of their offspring together. However, the aggregated formations are not colony-like accumulations of piled-up cells. Instead, they are "emergent" spatiotemporal structures of developmentally differentiated cell types. The functionally integrated structures remain relatively constant throughout the life of the organisms, despite the death and production of new cells. The question is: How differentiated cells are capable of making variant patterns without any predefined templates? It is shown that with a variety of differentiated cell types, emergence of complex patterns is feasible through the interplay of intercellular interactions and intracellular decision-making switches. Such conceptual understanding has the potential to generate a multitude of novel and precisely controlled cellular behaviors.

biophysics↗

bioRxiv2023

Inferring control objectives in a virtual balancing task in humans and monkeys

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different control objectives. Given only observations of behavior, is it possible to infer the control strategy that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular control strategy. This study presents a three-pronged approach to infer an animals control strategy from behavior. First, both humans and monkeys performed a virtual balancing task for which different control objectives could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control strategies to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer strategies from animal subjects. Being able to positively identify a subjects control objective from behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination. Impact statementA computational approach identifies control objectives in humans and monkeys to serve as basis for analysis of neural correlates of skillful manipulation.

neuroscience↗

bioRxiv2022

Free energy profile and kinetics of the formation of membrane invaginations by membrane-bending peripheral proteins

Peripheral proteins, known to induce curvature, have been identified as key agents in the spontaneous remodeling of bilayer membranes, leading to invaginations and the genesis of membrane tubules. For proteins like cholera and Shiga toxin, which impart the membrane with locally isotropic curvatures, the resultant membrane-mediated interactions remain notably subtle. Consequently, the collective action of these proteins, culminating in the formation of dense clusters on the membrane and subsequent invagination, unfolds over an extended timescale, often spanning several minutes. This gradual progression challenges direct simulation of the invagination process, even with coarsegrained models. In this study, we introduce a steered molecular dynamics protocol wherein peripheral proteins are impelled to converge on a membrane patch, instigating an invagination. Utilizing the Jarzynski equality, we derive the free energy profile of this process from a suite of non-equilibrium simulation replicas. Examining two distinct membrane-associated proteins, we elucidate the influence of protein flexibility and the distribution of induced curvatures on both the remodeling process and the corresponding free energy profile. We delve into the role of membrane-mediated effects in shaping protein organization within the invaginated domain. Building on the free energy profile, we model the formation of invaginations as a Markovian process, and offer estimates of the corresponding timescales. Our findings yield minute-long implied timescales that resonate well with empirical observations.

biophysics↗

bioRxiv2022

A Compartmentalized Model to Directional Sensing: How can an Amoeboid Cell Unify Pointwise External Signals as an Integrated Entity?

After being exposed to an external chemical attractant, several internal cellular downstream signal transduction pathways control the chemotactic machinery of eukaryotes. The spatial activation of these pathways ultimately leads to some sort of symmetry breaking around the cell periphery in the form of redistribution of several biochemicals, e.g., polymerized actin at one side of the cell for propulsion and the assembly of myosin II at nearly opposite side for retraction. In this study, we revisit the modeling of this process, which is called directional sensing, with a compartment-based design. In our model, we consider a network of excitable elements around cell circumference which are stimulated occasionally with local colored noise. The exciting elements are capable of sharing information with their close neighbors. We show that the dynamic can distinguish a temporary but enough long-lasting direction, statistically, pointing towards the gradient of external stimulants that can be deemed as the preferred orientation of the cell periphery during the directional sensing process in eukaryotes.

biophysics↗

bioRxiv2022

Protein nanobarcodes enable single-step multiplexed fluorescence imaging

Multiplexed cellular imaging typically relies on the sequential application of detection probes, such as antibodies or DNA barcodes, which is complex and time-consuming. To address this, we developed here protein nanobarcodes, composed of combinations of epitopes recognized by specific sets of nanobodies. The nanobarcodes are read in a single imaging step, relying on nanobodies conjugated to distinct fluorophores, which enables a precise analysis of large numbers of protein combinations.

cell biology↗

bioRxiv2022

3D-surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semi-supervised deep learning

Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nm range and strong contrast for membranous structures without requirement for labeling or chemical fixation. The short acquisition time and the relatively large volumes acquired allow for fast acquisition of large amounts of tomographic image data. Segmentation of these data into accessible features is a necessary step in gaining biologically relevant information from cryo-soft X-ray tomograms. However, manual image segmentation still requires several orders of magnitude more time than data acquisition. To address this challenge, we have here developed an end-to-end automated 3D-segmentation pipeline based on semi-supervised deep learning. Our approach is suitable for high-throughput analysis of large amounts of tomographic data, while being robust when faced with limited manual annotations and variations in the tomographic conditions. We validate our approach by extracting three-dimensional information on cellular ultrastructure and by quantifying nanoscopic morphological parameters of filopodia in mammalian cells.

bioinformatics↗

bioRxiv2022

Investigating the entropic nature of membrane-mediated interactions driving the aggregation of peripheral proteins

Peripheral membrane-associated proteins are known to accumulate on the surface of biomembranes as result of membrane-mediated interactions. For a pair of rotationally-symmetric curvature-inducing proteins, membrane mechanics at the low-temperature limit predicts pure repulsion. On the other hand, temperature-dependent entropic forces arise between pairs of stiff-binding proteins suppressing membrane fluctuations. These Casimir-like interactions have thus been suggested as candidates for attractive force leading to aggregation. With dense assemblies of peripheral proteins on the membrane, both these abstractions encounter multi-body complications. Here, we make use of a particle-based membrane model augmented with flexible peripheral proteins to quantify purely membrane-mediated interactions and investigate their underlying nature. We introduce a continuous reaction coordinate corresponding to the progression of protein aggregation. We obtain free energy and entropy landscapes for different surface concentrations along this reaction coordinate. In parallel, we investigate time-dependent estimates of membrane entropy corresponding to membrane undulations and coarse-grained tilt field and how they also change dynamically with protein aggregation. Congruent outcomes of the two approaches point to the conclusion that for low surface concentrations, interactions with an entropic nature may drive the aggregation. But at high concentrations, energetic contributions due to concerted membrane deformation by protein clusters are dominant.

biophysics↗