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bioRxiv2026

Scalable biophysical constraints for physiologically consistent metabolic states

Systems biology aims to develop predictive models that connect molecular mechanisms to cellular behavior. Genome-scale metabolic models are among the most widely used frameworks for integrating stoichiometric, thermodynamic, and omics-derived information to predict feasible metabolic phenotypes. However, cellular metabolism operates on timescales governed by enzyme kinetics and by the relationship between metabolic fluxes and metabolite pool sizes. In steady-state metabolic models, this relationship can be expressed in terms of metabolite turnover rates, defined as flux-to-pool-size ratios that quantify how rapidly metabolite pools are renewed. As a result, physiologically consistent steady-state solutions should not only satisfy mass-balance and thermodynamic constraints but also exhibit turnover rates consistent with enzyme-mediated cellular dynamics. Current constraint-based approaches can admit many steady-state flux-concentration states that do not account for turnover rates, resulting in phenotypes incompatible with realistic metabolic dynamics, even when multiple types of data are imposed. Here, we present METEOR-K, an optimization framework that links steady-state metabolic fluxes to metabolite concentrations via turnover rate constraints to identify dynamically plausible flux-concentration reference states. Because these constraints reshape the feasible solution space, we also introduce turnover-rate-aware sampling strategies to efficiently explore the resulting feasible region. We applied METEOR-K to models of increasing scope and scale, including a reduced glycolysis pathway, anaerobic E. coli, and near-genome-scale ovarian cancer models. METEOR-K narrowed the admissible steady-state solution space, reduced uncertainty in feasible flux-concentration states, and improved local dynamic behavior. In nonlinear ODE simulations of bioreactor cultivation and drug-response scenarios, METEOR-K-derived states produced intracellular response times compatible with growth-supporting metabolic operation and perturbation recovery. Overall, these results establish metabolite turnover rates as scalable biophysical constraints that improve the physiological consistency of steady-state metabolic modeling. Because turnover rates encode flux-to-pool-size timescale constraints, METEOR-K moves part of physiological-consistency assessment upstream of kinetic parameterization, yielding better-suited flux-concentration reference states for kinetic modeling and dynamic prediction.

systems biology↗

bioRxiv2026

FARM: Forecasting Antibiotic Resistance in Mycobacterium tuberculosis using biophysics and machine learning

Antibiotic-resistant tuberculosis remains a major public health challenge, and rapid diagnosis of resistant infections based on genomic markers holds promise for improving time to effective treatment. However, the vast majority of clinically observed variants in resistance-associated genes remain of uncertain significance, limiting the utility of predictors. Here we develop a multimodal forecasting framework, FARM (Forecasting Antibiotic Resistance in Mycobacterium tuberculosis) to determine whether a newly observed mutation in a resistance gene may indeed cause resistance. Our framework combines structural context, biophysical energy features, protein language model features, and mutational AAIndex physicochemical descriptors. Using 345 labeled mutations from the World Health Organization 2021 catalogue, we train interpretable models that distinguish resistance-associated from non-resistance-associated variants with holdout AUCs of 0.843-0.943. In a novel temporal evaluation of 62 mutations reclassified after the training data was released, the selected Combined model achieved 80.7% recall of resistant reclassifications (resistant-class F1=86.8; AUC=0.735). Applied to 4,525 current uncertain-significance mutations, the framework prioritizes 696 candidate resistance mutations, including genes associated with the new antibiotics bedaquiline, delamanid, and pretomanid. These forecasts are intended to support future catalogue updates and experimental follow-up.

bioinformatics↗

bioRxiv2026

Ultrasound-reconfigurable scaffolds enable dynamic control of biochemical and biophysical cues for vascular network formation

Vascularization, which is critical for most engineered tissue constructs, is dependent on interactions between endothelial cells and spatiotemporally presented biochemical and biophysical cues. Yet, most hydrogels define these cues at the time of fabrication, thus precluding adjustments to actively drive vascular formation. We developed acoustically responsive scaffolds (ARSs) that use focused ultrasound to trigger growth factor release and localized matrix remodeling within fibrin hydrogels. ARSs were formed by incorporating phase-shift emulsions containing basic fibroblast growth factor (bFGF) along with perfluorohexane (C6) or perfluorooctane (C8). Upon ultrasound exposure, stable bubbles were generated in C6-ARSs that locally compacted the matrix and increased macroscale stiffness. Comparatively, in C8-ARSs, ultrasound generated macropores without impacting viscoelastic properties. Ultrasound increased bFGF release from both ARS types, which enhanced in vitro and in vivo vasculogenic assembly in ARSs with co-encapsulated endothelial cells and fibroblasts. Our data also show that ultrasound-driven matrix remodeling without bFGF release increased endothelial sprouting. In C6-ARSs, elevated levels of F-actin were observed in both cell types adjacent to bubbles as well as increased YAP intensity and nuclear asymmetry. Together, these results establish ARSs as reconfigurable hydrogels that couple on-demand release of biochemical cues with programmable matrix restructuring to direct three-dimensional microvascular assembly.

bioengineering↗

bioRxiv2026

RhabdoForge: A Modular, Biophysically-Grounded Rendering Framework for Insect Vision Neuroethology

Insects solve complex behavioural tasks with remarkable efficiency, using minimal neural hardware tuned to the specific requirements of their ecological niches. To truly understand or replicate these behaviours, it is insufficient to model the brain in isolation: one must account for the dynamic, closed-loop interactions between the environment, the physical organisation of the sensory periphery, and internal biophysical dynamics. To address these issues for visually controlled behaviours, we present RhabdoForge, a modular, hardware-agnostic and high-performance rendering framework specifically designed for insect neuroethology and neuromorphic research. Designed for seamless integration into Python-based workflows, RhabdoForge implements both real-time ray-tracing and stochastic path-tracing using hardware-agnostic GPU pipelines. Crucially, the engine moves beyond the static "ommatidium-as-a-pixel" paradigm by introducing a fully parametrisable model where every layer of the compound eye (from the geometric shape and the topological lattice to the internal rhabdomere blueprint) is a discrete, swappable component. The engine is capable of simulating the high-frequency, sub-ommatidial rhabdomere photomechanical actuation, allowing for the investigation of a variety of active sensing phenomena within a real-time closed-loop environment. The framework also includes an automated morphological pipeline that allows transforming 2D anatomical data into faithful 3D sensory models. We validate the engine through two case studies: a closed-loop optic-flow centring response in a virtual tunnel, and the recovery of spatial hyperacuity via rhabdomere microsaccades. By providing a bridge between high-fidelity visual ecology and neuromorphic modelling, RhabdoForge enables researchers to explore how the interplay of sensory optics and neural processing can generate complex behaviour in both biological and artificial agents.

neuroscience↗

bioRxiv2026

A Biophysical Platform for Electromechanical Stimulation of Engineered Cardiac Tissues

Human engineered cardiac tissues (ECTs) provide an in vitro model for studying human cardiac physiology and drug responses, but their performance remains limited by culture systems that do not fully reproduce the heart's electrical and mechanical environment. Electrical stimulation (ES) and mechanical stimulation (MS) have each been used to improve ECT function. Their combination, referred to as electromechanical stimulation (ES+MS), can provide further benefits. However, ES+MS depends not only on the presence of both cues but also on how they are coordinated in time. Here, we developed an incubator-compatible biophysical platform that delivers ES and MS independently or in combination, with programmable control over timing, amplitude, frequency, duration, and waveform. Calibration and dynamic characterization demonstrated tissue-relevant strain delivery, rapid and repeatable motion, and minimal attenuation and timing lag at the designated frequency of 1.5 Hz. We then compared four 6 h conditioning regimens: unstimulated control, ES alone, unsynchronized ES+MS, and synchronized ES+MS. We hypothesized that the synchronized ES+MS group, in which electrical excitation was aligned with peak externally applied strain, would produce the greatest increase in contractile force. Consistent with this hypothesis, synchronized ES+MS increased normalized twitch force by approximately 44% on average, whereas the other groups showed no comparable improvement. Twitch-timing metrics did not exhibit coordinated enhancement after 6 h, suggesting that the force increase reflects an adaptive biomechanical response rather than broad tissue maturation. These findings identify ES-MS timing as an important design parameter for ECT conditioning.

bioengineering↗

bioRxiv2026

Comparative Biochemical and Biophysical Insights into SufC ATPases from Mycobacterium tuberculosis and Mycolicibacterium smegmatis mc2155

The sulfur mobilization (SUF) system is the only Fe-S cluster biosynthesis pathway in Mycobacterium tuberculosis (M. tb) and Mycolicibacterium smegmatis (M. smegmatis). In this pathway, SufC protein acts as an ATPase in the SufBC2D scaffold for Fe-S cluster biogenesis. This crucial role positions SufC as a promising target for the development of antimycobacterial therapeutics. However, the SufC ATPases from Mycobacterial species are not yet characterized. This study includes cloning, expression, purification, and characterization of SufC homologs from M. tb (Rv1463) and M. smegmatis (MSMEG_3124) using biochemical, biophysical, and computational approaches. Both SufC proteins were purified using affinity and size-exclusion chromatography and observed to exist as monomers in solution. Although both proteins have the conserved domains, they exhibit different ATP-dependent kinetic efficiencies, demonstrating differences in their local environment and catalytic behavior. Furthermore, CRISPR interference targeting MSMEG_3124 results led to diminished M. smegmatis growth, highlighting the critical role of SufC in cellular viability. Modeling and virtual screening led to the identification of three candidate compounds, of which Z2911048515 and Z66741142 were selected for experimental evaluation. Circular dichroism spectroscopy analysis revealed slight differences in the spectral features of Rv1463 in the presence of Z2911048515 and Z66741142, while significant spectral variations were observed for MSMEG_3124. Importantly, Z66741142 was able to cause changes in the fluorescence spectra of both SufC protein homologs. Surprisingly, both compounds showed only limited inhibition of SufC ATPase activity, exhibited distinct modes of action, and may serve as preliminary chemical scaffolds for optimization and testing as effective inhibitors. This study presents functional diversity of mycobacterial SufC proteins across pathogenic and non-pathogenic species and provides a basis for developing a framework for further mechanistic and structure-guided investigation within the indispensable SUF pathway.

biochemistry↗

bioRxiv2016

Direct coevolutionary couplings reflect biophysical residue interactions in proteins

Coevolution of residues in contact imposes strong statistical constraints on the sequence variability between homologous proteins. Direct-Coupling Analysis (DCA), a global statistical inference method, successfully models this variability across homologous protein families to infer structural information about proteins. For each residue pair, DCA infers 21x21 matrices describing the coevolutionary coupling for each pair of amino acids (or gaps). To achieve the residue-residue contact prediction, these matrices are mapped onto simple scalar parameters; the full information they contain gets lost. Here, we perform a detailed spectral analysis of the coupling matrices resulting from 70 protein families, to show that they contain quantitative information about the physico-chemical properties of amino-acid interactions. Results for protein families are corroborated by the analysis of synthetic data from lattice-protein models, which emphasizes the critical effect of sampling quality and regularization on the biochemical features of the statistical coupling matrices.

Biophysics↗

bioRxiv2016

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

Tethered enzymatic reactions are ubiquitous in signalling networks but are poorly understood. Here, a novel mathematical analysis is established for tethered signalling reactions in surface plasmon resonance (SPR). Applying the method to the phosphatase SHP-1 interacting with a phosphorylated tether corresponding to an immune receptor cytoplasmic tail provides 5 biophysical/biochemical constants from a single SPR experiment: two binding rates, two catalytic rates, and a reach parameter. Tether binding increased the activity of SHP-1 by 900-fold through a binding-induced allosteric activation (20-fold) and a more significant increase in local sub-strate concentration (45-fold). The reach parameter indicates that this local substrate concentration is exquisitely sensitive to receptor clustering. We further show that truncation of the tether leads not only to a lower reach but also to lower binding and catalysis. The work establishes a new framework for studying tethered signalling processes and highlights the tether as a control parameter in clustered signalling.

Biophysics↗

bioRxiv2020

Functional insights from biophysical study of TREM2 interactions with ApoE and Aβ1-42

INTRODUCTIONTREM2 is an innate immune receptor expressed on myeloid cells including microglia in the brain. How TREM2 engages different ligands remains poorly understood. METHODSWe used comprehensive BLI analysis to investigate the TREM2 interactions with ApoE and monomeric amyloid beta (mA{beta}42). RESULTSTREM2 binding did not depend on ApoE lipidation, and there were only slight differences in affinity observed between ApoE isoforms (E4 > E3 > E2). Surprisingly, disease-linked TREM2 variants within a "basic patch" minimally impact ApoE binding. Instead, TREM2 has a unique hydrophobic surface that can bind to ApoE. This direct engagement requires the hinge region of ApoE. TREM2 directly binds mA{beta}42 and can potently inhibit A{beta}42 polymerization, suggesting a potential mechanism for soluble TREM2 (sTREM2) in preventing AD pathogenesis. DISCUSSIONThese findings demonstrate that TREM2 has at least two separate surfaces to engage ligands and uncovers a potential function for sTREM2 in directly inhibiting A{beta} polymerization.

biophysics↗

bioRxiv2020

Biophysical characterization of the SARS-CoV2 spike protein binding with the ACE2 receptor explains increased COVID-19 pathogenesis

SARS-CoV-2 is a novel highly virulent pathogen which gains entry to human cells by binding with the cell surface receptor - angiotensin converting enzyme (ACE2). We computationally contrasted the binding interactions between human ACE2 and coronavirus spike protein receptor binding domain (RBD) of the 2002 epidemic-causing SARS-CoV-1, SARS-CoV-2, and bat coronavirus RaTG13 using the Rosetta energy function. We find that the RBD of the spike protein of SARS-CoV-2 is highly optimized to achieve very strong binding with human ACE2 (hACE2) which is consistent with its enhanced infectivity. SARS-CoV-2 forms the most stable complex with hACE2 compared to SARS-CoV-1 (23% less stable) or RaTG13 (11% less stable) while occupying the greatest number of residues in the ATR1 binding site. Notably, the SARS-CoV-2 RBD out-competes the angiotensin 2 receptor type I (ATR1) which is the native binding partner of ACE2 by 35% in terms of the calculated binding affinity. Strong binding is mediated through strong electrostatic attachments with every fourth residue on the N-terminus alpha-helix (starting from Ser19 to Asn53) as the turn of the helix makes these residues solvent accessible. By contrasting the spike protein SARS-CoV-2 Rosetta binding energy with ACE2 of different livestock and pet species we find strongest binding with bat ACE2 followed by human, feline, equine, canine and finally chicken. This is consistent with the hypothesis that bats are the viral origin and reservoir species. These results offer a computational explanation for the increased infectivity of SARS-CoV-2 and allude to therapeutic modalities by identifying and rank-ordering the ACE2 residues involved in binding with the virus.

biophysics↗

bioRxiv2020

Predicting Metastasis with a Novel Biophysical Cell-Adhesion Force Technique

Metastasis is widely accepted to be responsible for approximately 90% of all cancer deaths. Current research on metastasis prediction often centers on gene sequencing; however, these analyses must account for the complexity of gene regulation and rely on comprehensive datasets. To investigate the process from a simpler, non-genomic angle, some studies indicate differences in cell adhesion force, an important physical process in metastasizing cells. However, cell adhesion force methods tend to focus on cell population approaches and therefore have their drawbacks in cost or efficiency, rendering them impractical outside a research setting. In this work, we test a novel and inexpensive bead-pipette assay to investigate the adhesion forces of non-metastatic NIH3T3 cells and mutated RasV12 cells, a metastatic model cell line. Control cells and RasV12 cells were evaluated with wound healing, spreading area, and focal adhesion (FA) analysis assays. Then cells were tested by the novel bead-pipette assay, which uses a fibronectin-coated bead and a glass micropipette to measure cell adhesion force using Hookes law. The RasV12 cells had faster migration, polarized cell shape, and smaller FA area than control cells. The RasV12 cells also exerted higher adhesion forces than control cells and a potential force threshold was determined for distinguishing metastatic cells through a Receiver Operating Characteristic (ROC) curve. An ROC curve was computed for all other assays and the bead-pipette assay was shown to perform higher as a classifier than other assays. The RasV12 cells had increased metastatic potential compared to control. The novel bead-pipette assay showed potential as a classifier for determining metastasizing cells from non-metastatic cells. With further work, it may serve as a clinical diagnostic tool for cancer patients or as a testbed to be used in the development of anti-metastatic drugs.

biophysics↗

bioRxiv2020

Biophysical interaction of levothyroxine with bovine serum albumin: a spectroscopic assay

Bovine serum albumin (BSA) acts as a carrier for many endogenous and exogenous compounds, such as thyroid hormones or corresponding drugs. Binding of the hydrophilic compound levothyroxine (LT4) to BSA can significantly alter the pharmacological properties of the compound. Therefore, studying its interaction with BSA could be a difficult issue. In this work, the binding mechanism and affinity of the interaction between LT4 and BSA were investigated, both in solution using UV-Vis, Fourier-transform infrared spectroscopy (FT-IR), fluorescence and fluorescence resonance energy transfer (FRET), as well as by Surface Plasmon Resonance (SPR) with BSA confined to a gold-coated chips, as far as we know for the first time used to study the interactions between LT4 and proteins. Quenching of BSA fluorescence by LT4 combined with UV-Vis spectroscopy shows a ground-state complex formation that may be accompanied by a nonradiative energy transfer process. FT-IR revealed the changes induced by LT4 in the secondary structure of BSA molecules, due to the partial unfolding of BSA native structure upon LT4 binding. Scatchard approach allowed the determination of the binding constant and the thermodynamic parameters, which correspond to an enthalpic process, driven mainly by hydrogen bonds and van der Waals forces. Using SPR, the adsorbed amount of biomolecules was calculated and the binding affinity of LT4 with confined-BSA was characterized using the Hill-Langmuir equation, indicating that the BSA immobilization plays an important role in LT4 binding. As preliminary results, both fluorescence quenching and SPR can be used as a stepping stone for the development of a spectroscopic biosensor for LT4 detection, with a limit of detection as low as 0.23 x 10-6 M.

biophysics↗

bioRxiv2020

Selection, biophysical and structural analysis of synthetic nanobodies that effectively neutralize SARS-CoV-2

The coronavirus SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Therapeutic neutralizing antibodies constitute a key short-to-medium term approach to tackle COVID-19. However, traditional antibody production is hampered by long development times and costly production. Here, we report the rapid isolation and characterization of nanobodies from a synthetic library, known as sybodies (Sb), that target the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Several binders with low nanomolar affinities and efficient neutralization activity were identified of which Sb23 displayed high affinity and neutralized pseudovirus with an IC50 of 0.6 {micro}g/ml. A cryo-EM structure of the spike bound to Sb23 showed that Sb23 binds competitively in the ACE2 binding site. Furthermore, the cryo-EM reconstruction revealed a novel conformation of the spike where two RBDs are in the up ACE2-binding conformation. The combined approach represents an alternative, fast workflow to select binders with neutralizing activity against newly emerging viruses.

biophysics↗

bioRxiv2020

CHO/LY-B cell growth under limiting sphingolipid supply: correlation between lipid composition and biophysical properties of sphingolipid-restricted cell membranes

ABSTRACTSphingolipids (SL) are ubiquitous in mammalian cell membranes, yet there is little data on the behavior of cells under SL-restriction conditions. LY-B cells derive from a CHO line in which serine palmitoyl transferase (SPT), thus de novo SL synthesis, is suppressed, while maintaining the capacity of taking up and metabolizing exogenous sphingoid bases from the culture medium. In the present study LY-B cells were adapted to grow in a fetal bovine serum (FBS)-deficient medium to avoid external uptake of lipids. The lowest FBS concentration that allowed LY-B cell growth, though at a slow rate, under our conditions was 0.04%, i.e. 250-fold less than the standard (10%) concentration. Cells grown under limiting SL concentrations remained viable for at least 72 h. Enriching with sphingomyelin the SL-deficient medium allowed the recovery of control LY-B cell growth rates. Studies including whole cells, plasma membrane preparations, and derived lipid vesicles were carried out. Laurdan fluorescence was recorded to measure membrane molecular order, showing a significant decrease in the rigidity of LY-B cells, not only in plasma membrane but also in whole cell lipid extract, as a result of SL limitation in the growth medium. Plasma membrane preparations and whole cell lipid extracts were also studied using atomic force microscopy in the force spectroscopy mode. Force measurements demonstrated that lower breakthrough forces were required to penetrate samples obtained from SL-poor LY-B cells than those obtained from control cells. Mass-spectroscopic analysis was also a helpful tool to understand the rearrangement undergone by the LY-B cell lipid metabolism. The most abundant SL in LY-B cells, sphingomyelin, decreased by about 85% as a result of SL limitation in the medium, the bioactive lipid ceramide and the ganglioside precursor hexosylceramide decreased similarly, together with cholesterol. Quantitative SL analysis showed that a 250-fold reduction in sphingolipid supply to LY-B cells led to a 6-fold decrease in membrane sphingolipids, underlining the resistance to changes in composition of these cells. Plasma membrane compositions exhibited similar changes, at least qualitatively, as the whole cells with SL restriction. A linear correlation was observed between the sphingomyelin concentration in the membranes, the degree of lipid order as measured by laurdan fluorescence, and membrane breakthrough forces assessed by atomic force microscopy. Concomitant changes were detected in glycerophospholipids under SL-restriction conditions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2020

Cell-Scale Biophysical Cues from Collagen Fiber Architecture Instruct Cell Behavior and the Propagation of Mechanosensory Signals

Mechanosensory cues from the extracellular matrix underpin numerous cellular behaviors including tumor cell migration yet are influenced by the local structure and organization of the matrix in unknown ways. To investigate mechanical cues with respect to local collagen organization, we used a combination of intravital imaging of the mammary tumor microenvironment and 3D collagen gel systems with both migratory MDA-MB-231 cells and acellular pNIPAAm beads. We identified that fiber organization directs a bias in cell response along the axis of alignment. Using innovative methodology, we determined that local collagen alignment resulted in a 30-fold difference in directional cell-scale stiffness and also dramatically altered the rate at which cell-induced fiber displacements decayed over distance. Our results reveal differential mechanical properties across orthogonal directions in aligned matrices that provide sizeable cues to the cell and have important implications for cellular mechanosensing and cell-cell communication within the tissue microenvironment.

biophysics↗

bioRxiv2020

Exploring the binding of resveratrol to promoter DNA sequence d(CCAATTGG)2 using biophysical studies

We report the interaction of resveratrol with an octamer DNA sequence d(CCAATTGG)2, present in the promoter region of many oncogenes, using a combination of absorption, fluorescence, calorimetric and nuclear magnetic resonance techniques to probe the binding. Resveratrol binds to the duplex sequence with a binding constant 2.20x106 M-1 in absorption studies. A ligandduplex stoichiometry of 2.2:1 was obtained with binding constant varying from 109 to 106M-1 with the concentration of DNA varied in fluorescence titration measurements. Spectral changes indicated external binding of resveratrol to duplex DNA. Circular dichroism data displayed minimal variation suggesting external binding. Melting temperatures of DNA and its 1:1 complex showed a difference of approximately 2.25{degrees}C, which supports the external binding. Nuclear magnetic resonance data showed resveratrol binds to the minor groove region near the AT basepair from the nuclear Overhauser effect spectroscopic cross peaks. Distance restrained molecular dynamics was employed in explicit solvent condition to obtain the lowest energy structure. The complex was stable and retained the B-DNA conformation. Findings in this study identify resveratrol as a minor groove binder to the AT region of DNA and pave the way for exploring resveratrol and its analogues as promising anticancer/antibacterial drug.

biophysics↗

bioRxiv2021

Counterdiabatic control of biophysical processes

The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time--via external interventions like time-varying concentrations of chemical species--is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. Though CD driving is limited to target trajectories that are instantaneous stationary states, we show how to generalize the approach to allow for non-stationary targets and local control--where only a subset of system states are targeted. The latter is particularly useful for biological implementations where there may be only a small number of available external control knobs, insufficient for global control. We derive simple graphical criteria for when local versus global control is possible. Finally, we illustrate the formalism with global control of a genetic regulatory switch and local control in chaperone-assisted protein folding. The derived control protocols in the chaperone system closely resemble natural control strategies seen in experimental measurements of heat shock response in yeast and E. coli.

biophysics↗

bioRxiv2021

nucGEMs probe the biophysical properties of the nucleoplasm

The cell interior is highly crowded and far from thermodynamic equilibrium. This environment can dramatically impact molecular motion and assembly, and therefore influence subcellular organization and biochemical reaction rates. These effects depend strongly on length-scale, with the least information available at the important mesoscale (10-100 nanometers), which corresponds to the size of crucial regulatory molecules such as RNA polymerase II. It has been challenging to study the mesoscale physical properties of the nucleoplasm because previous methods were labor-intensive and perturbative. Here, we report nuclear Genetically Encoded Multimeric nanoparticles (nucGEMs). Introduction of a single gene leads to continuous production and assembly of protein-based bright fluorescent nanoparticles of 40 nm diameter. We implemented nucGEMs in budding and fission yeast and in mammalian cell lines. We found differences in particle motility between the nucleus and the cytosol at the mesoscale, that mitotic chromosome condensation ejects nucGEMs from the nucleus, and that nucGEMs are excluded from heterochromatin and the nucleolus. nucGEMs enable hundreds of nuclear rheology experiments per hour, and allow evolutionary comparison of the physical properties of the cytosol and nucleoplasm.

biophysics↗