Biology subjects

Chilkoti, A.

Publications and source records attributed to Chilkoti, A..

7 recordsLinked to original sources

bioRxiv2026

Dual GLP-1/FGF21 agonism suppresses voluntary alcohol consumption, alcohol choice, and nucleus accumbens dopamine modulation

Excessive alcohol consumption remains a major public health challenge with limited therapeutic options. Both glucagon-like peptide-1 (GLP-1) and fibroblast growth factor-21 (FGF21) independently regulate alcohol intake through complementary metabolic and reward pathways, but their combined potential has not been explored. Here, we report that a long-acting dual agonist, GLP1-ELP-FGF21 modulates behavioural, neurophysiological, and cognitive components of alcohol seeking in mice. A single GLP1-ELP-FGF21 dose reversibly reduces voluntary alcohol intake for at least 72 hours in male mice, has sustained effects in female mice, and markedly blunts nucleus accumbens dopamine transients aligned to the initiation and termination of lick bouts during alcohol consumption. To assess its effects on decision-making, we used a novel two-choice (alcohol versus food) decision task modelled with evidence-accumulation frameworks. Alcohol choice behaviour conformed to evidence accumulation decision models: Linear Ballistic Accumulator (LBM) and Racing diffusion models (RDM). Critically, GLP1-ELP-FGF21 selectively reduces choices for alcohol and slows the latent accumulation rate for alcohol options, without affecting food-directed choice or non-decision processes. Sensory-specific satiety devaluation confirms that reductions in reward value are explained by reductions in accumulation rates. Together, these results highlight GLP1-ELP-FGF21 as a therapeutic strategy for alcohol use disorder via modulation of central reward pathways and decision-making when confronted with alcohol reward

animal behavior and cognition↗

bioRxiv2025

Intrinsically Disordered Protein Coating for Oral Delivery of Peptide Drugs

AbstractAdvancing oral delivery of peptide therapeutics requires innovative materials that overcome gastrointestinal barriers. We introduce the first engineered synthetic intrinsically disordered protein (SynIDP) that self-assembles into an enteric coating, encapsulating peptide drugs to enhance gastric acid resistance and intestinal targeting. This SynIDP recapitulates the molecular design principles and phase transitions of native IDPs to exhibit temperature-controlled condensation and pH-controlled solidification--both transitions being reversible and precisely tuned to intestinal cues. Through detailed analysis of the kinetics of the liquid-to-solid phase transition, we achieve control over the nano-to-microscale morphology of the protein coating, optimizing drug encapsulation and protection. The coating protects peptide-based weight loss drugs for over 60 minutes in simulated gastric conditions, then dissolves to release the active compound. Oral delivery to obese mice results in more consistent weight loss compared to the unencapsulated drug. This modular protein-based coating is a promising platform technology for enhancing oral peptide drug delivery and improving patient compliance.

bioengineering↗

bioRxiv2023

Global control of cellular physiology by biomolecular condensates through modulation of electrochemical equilibria

Control of the electrochemical environment in living cells is typically attributed to ion channels. Here we show that the formation of biomolecular condensates can modulate the electrochemical environment in cells, which affects processes globally within the cell and interactions of the cell with its environment. Condensate formation results in the depletion or enrichment of certain ions, generating intracellular ion gradients. These gradients directly affect the electrochemical properties of a cell, including the cytoplasmic pH and hyperpolarization of the membrane potential. The modulation of the electrochemical equilibria between the intra- and extra-cellular environments by biomolecular condensates governs charge-dependent uptake of small molecules by cells, and thereby directly influences bacterial survival under antibiotic stress. The shift of the intracellular electrochemical equilibria by condensate formation also drives a global change of the gene expression profile. The control of the cytoplasmic environment by condensates is correlated with their volume fraction, which can be highly variable between cells due to the stochastic nature of gene expression at the single cell level. Thus, condensate formation can amplify cell-cell variability of the environmental effects induced by the shift of cellular electrochemical equilibria. Our work reveals new biochemical functions of condensates, which extend beyond the biomolecules driving and participating in condensate formation, and uncovers a new role of biomolecular condensates in cellular regulation.

cell biology↗

bioRxiv2023

Spatial Organization of Gas Vesicles is Governed by Phase-separable GvpU

Gas vesicles (GVs) are microbial protein organelles that support cellular buoyancy, and the recent engineering of GVs has led to multiple applications including reporter gene imaging, acoustic control, and payload delivery. GVs often cluster into a honeycomb pattern to minimize their occupancy of cytosolic space; however, the molecular mechanism behind this process and its influence on cellular physiology remain unknown. Here, we identified GvpU as the protein governing this process. GvpU-mediated clustering is selective to the genotype of GVs, allowing the design of GV variants with genetically encodable clustering states. Furthermore, we uncovered that the clustering is modulated by phase transition behaviors encoded in the intrinsically disordered region of GvpU through a balanced contribution of acidic and aromatic residues, and such phase transition can directly modulate cellular fitness. Collectively, our findings elucidate the protein player, molecular mechanism, and functional roles of GV clustering, and its programmability for biomedical applications.

synthetic biology↗

bioRxiv2021

Double-stranded RNA drives SARS-CoV-2 nucleocapsid protein to undergo phase separation at specific temperatures

Betacoronavirus SARS-CoV-2 infections caused the global Covid-19 pandemic. The nucleocapsid protein (N-protein) is required for multiple steps in the betacoronavirus replication cycle. SARS-CoV-2-N-protein is known to undergo liquid-liquid phase separation (LLPS) with specific RNAs at particular temperatures to form condensates. We show that N-protein recognizes at least two separate and distinct RNA motifs, both of which require double-stranded RNA (dsRNA) for LLPS. These motifs are separately recognized by N-proteins two RNA binding domains (RBDs). Addition of dsRNA accelerates and modifies N-protein LLPS in vitro and in cells and controls the temperature condensates form. The abundance of dsRNA tunes N-protein-mediated translational repression and may confer a switch from translation to genome packaging. Thus, N-proteins two RBDs interact with separate dsRNA motifs, and these interactions impart distinct droplet properties that can support multiple viral functions. These experiments demonstrate a paradigm of how RNA structure can control the properties of biomolecular condensates.

molecular biology↗

bioRxiv2020

Design of intrinsically disordered proteins that undergo phase transitions with lower critical solution temperatures

Many naturally occurring elastomers are intrinsically disordered proteins (IDPs) built up of repeating units and they can demonstrate two types of thermoresponsive phase behavior. Systems characterized by lower critical solution temperatures (LCST) undergo phase separation above the LCST whereas systems characterized by upper critical solution temperatures (UCST) undergo phase separation below the UCST. There is congruence between thermoresponsive coil-globule transitions and phase behavior whereby the theta temperatures above or below which the IDPs transition from coils to globules serve as useful proxies for the LCST / UCST values. This implies that one can design sequences with desired values for the theta temperature with either increasing or decreasing radii of gyration above the theta temperature. Here, we show that the Monte Carlo simulations performed in the so-called intrinsic solvation (IS) limit version of the temperature-dependent the ABSINTH (self-Assembly of Biomolecules Studied by an Implicit, Novel, Tunable Hamiltonian) implicit solvation model, yields a useful heuristic for discriminating between sequences with known LCST versus UCST phase behavior. Accordingly, we use this heuristic in a supervised approach, integrate it with a genetic algorithm, combine this with IS limit simulations, and demonstrate that novel sequences can be designed with LCST phase behavior. These calculations are aided by direct estimates of temperature dependent free energies of solvation for model compounds that are derived using the polarizable AMOEBA (atomic multipole optimized energetics for biomolecular applications) forcefield. To demonstrate the validity of our designs, we calculate coil-globule transition profiles using the full ABSINTH model and combine these with Gaussian Cluster Theory calculations to establish the LCST phase behavior of designed IDPs.

biophysics↗

bioRxiv2020

Connecting coil-to-globule transitions to full phase diagrams for intrinsically disordered proteins

Phase separation is thought to underlie spatial and temporal organization that is required for controlling biochemical reactions in cells. Multivalence of interaction motifs also known as stickers is a defining feature of proteins that drive phase separation. Intrinsically disordered proteins with stickers uniformly distributed along the linear sequence can serve as scaffold molecules that drive phase separation. The sequence-intrinsic contributions of disordered proteins to phase separation can be discerned by computing or measuring sequence-specific phase diagrams. These help to delineate the combinations of protein concentration and a suitable control parameter such as temperature that support phase separation. Here, we present an approach that combines detailed simulations with a numerical adaptation of an analytical Gaussian cluster theory to enable the calculation of sequence-specific phase diagrams. Our approach leverages the known equivalence between the driving forces for single chain collapse in dilute solutions and the driving forces for phase separation in concentrated solutions. We demonstrate the application of the theory-aided computations through calculation of phase diagrams for a set of archetypal intrinsically disordered low complexity domains. STATEMENT OF SIGNIFICANCEIntrinsically disordered proteins that have the requisite valence of adhesive linear motifs can drive phase separation and give rise to membraneless biomolecular condensates. Knowledge of how phase diagrams vary with amino acid sequence and changes to solution conditions is essential for understanding how proteins contribute to condensate assembly and dissolution. In this work, we introduce a new two-pronged computational approach to predict sequence-specific phase diagrams. This approach starts by extracting key parameters from simulations of single-chain coil-to-globule transitions. We use these parameters in our numerical implementation of the Gaussian cluster theory (GCT) for polymer solutions to construct sequences-specific phase diagrams. The method is efficient and demonstrably accurate and should pave the way for high-throughput assessments of phase behavior.

biophysics↗