ICTS

The large-scale organization of the bacterial chromosome usually relies on the activity of a single SMC complex. In several species, this complex also ensures proper chromosome segregation. Unusually, Pseudomonas aeruginosa encodes two SMC complexes: Smc-ScpAB and MksBEF. These complexes display distinct activities on chromosome management and act hierarchically. Using genomics, genetics and fluorescence microscopy, we dissected the coordination between these SMC complexes and DNA replication. Furthermore, to determine whether the coexistence of two SMC complexes is conserved across the Pseudomonas genus, we performed comparative genomics on 210 complete genomes. This analysis revealed major lineage-specific differences in genome size and structure, including a striking expansion of a poorly conserved, low-expression region near the replication terminus, especially in the P. fluorescens group. Together, our results link 1D genome evolution with 3D chromosome folding in Pseudomonas.

We elucidate the underlying mechanism of organization and segregation of the E. coli chromosomes in both slow and fast growth conditions, as it occurs concurrently with replication. We quantitatively match the organization of certain tagged loci (polymer segments) from our simulations [1], [2], [3], similar to those obtained from FISH experiments [4], [5], which is also consistent with HiC [6]. We also match the organization of the replication forks, reconciling the conflicting models of the train track and replication factory models of the motion of the replisome. We were able to reproduce the experiments by introducing a few long-range interactions, creating small loops within the chromosome. We also elucidate the underlying entropy based physical mechanism for the transport of one of the daughter OriCs from one pole to the other for the replicating C.crescentus chromosome, with suitable help from the ParABS system of proteins.

[1] D. Mitra, S. Pande, and A. Chatterji, Soft Matter,  18,  pp. 5615–5631 (2022). https://pubs.rsc.org/en/content/articlehtml/2022/sm/d2sm00734g[2] S. Pande, D. Mitra, and A. Chatterji, Physical Review E, 110, no. 5, (2024). https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.054401[3] D. Mitra, S. Pande, and A. Chatterji, Physical Review E, 106, (2022). https://journals.aps.org/pre/abstract/10.1103/PhysRevE.106.054502[4] J. A. Cass, N. J. Kuwada, B. Traxler, and P. A. Wiggins, Biophysical Journal, vol. 110, no. 12, pp. 2597–2609, 2016.[5] B. Youngren, H. J. Nielsen, S. Jun, and S. Austin, Genes and Development, vol. 28, no. 1, p. 71–84, Jan. 2014.[6] V. S. Lioy, A. Cournac, M. Marbouty, S. Duigou, J. Mozziconacci, O. Espéli, F. Boccard, and R. Koszul, Cell, vol. 172, no. 4, pp. 771– 783, 2018.

Active chromatin folding encodes additional layers of information that regulate gene activation and repression in a time-dependent manner. This folding spans multiple length scales — from the nucleosome to the entire chromosome — across several orders of magnitude. We will present physics-based models to understand chromatin folding and predict its properties across these scales. Additionally, we will discuss how active folding influences key biological processes such as DNA repair, gene regulation, and DNA packaging.

The lymphocyte immune response begins with antigen recognition on antigen-presenting cells, leading to the formation of the immunological synapse—a specialized interface for biochemical and biophysical exchange. At the synapse, most antigen-engaged receptor microclusters move inward toward the central supramolecular activation cluster (cSMAC) via retrograde F-actin flow, eventually clearing from the cell surface. This retrograde movement and receptor downregulation maintain antigen receptor homeostasis, critical for adaptive immunity, though its regulation remains unclear. Using live T cells, we identified a significant pool of antigen-engaged microclusters moving anterogradely toward the cell periphery, rather than the cSMAC. This movement was driven by actin waves propagating outward and coupling to microclusters through the Wiskott-Aldrich Syndrome Protein. These findings reveal a previously unrecognized mode of actin dynamics—anterograde actin waves—that co-exist with retrograde flow and direct microclusters away from the downregulation zone. This dual actin behavior underscores the complex cytoskeletal mechanisms T cells employ to regulate receptor distribution and maintain signaling homeostasis during immune activation.

How epigenetic information is inherited during cell division remains an interesting open question. While basic models have been proposed to investigate this problem, none so far have accounted for nucleosome binding, dissociation, and sliding dynamics. Based on recent experimental data, we simulate a model that includes nucleosome binding, dissociation, and sliding, and investigate how the interplay between nucleosome dynamics and deacetylation/methylation spreading reactions determine histone modification spreading and inheritance. First, we present how nucleosome density is affected by acetylation and methylation dynamics. We then extend this model to study the inheritance of histone modifications.

UV light absorption and subsequent energy transfer by aromatic residues can be harnessed to direct and dissipate electronic energy in proteins. However, the relationship of a protein’s electronic energy migration length with its other biochemical functions is not well understood. Here, we predict electronic energy migration lengths for the complete protein data bank (PDB) using a kinetic Monte Carlo simulation. We simulate repeated energy transfer through Forster Resonance Energy Transfer (FRET) and Dexter Energy Transfer (DET) hopping between aromatic residues, balancing energy transfer rates with intrinsic excited state lifetimes. We find patterns correlating the electronic energy migration length of a protein with its structure and function. We also show that electronic energy migration lengths are significant in idealized one-, two-, and three-dimensional aromatic residue lattices resembling various intracellular structures. Our work provides detailed insight into the relationship of a proteins’ light harvesting ability and its structural and functional properties.

Biomolecular condensates are dynamic, membrane-less compartments formed via phase separation, enabling spatial and temporal regulation of essential cellular processes. Their tunable material properties facilitate rapid cellular responses, while their dysregulation is increasingly implicated in disease. While the role of liquid–liquid phase separation (LLPS) in cellular organization is increasingly being uncovered, their interactions with membranes remain largely unexplored. To investigate this interplay, we assemble condensates in cell-mimetic systems. Here, we reconstitute nucleotide–peptide condensates within semipermeable Giant Unilamellar Vesicles (GUVs) with defined lipid compositions. This system allows precise control over condensate formation and facilitates the study of condensate–membrane interplay. By engineering electrostatic interactions, we observe that weakly interacting condensates induce membrane budding, while strong interactions cause membrane wrinkling. FRAP analysis quantifies slowed membrane diffusion due to condensate interactions in membrane wrinkling, while TEM and high-resolution imaging confirm condensate embedding within wrinkled membrane folds. Our findings suggest that charge-mediated interactions between condensates and membranes modulate droplet dynamics by altering wettability and inducing membrane curvature, similar to condensate-driven budding observed in protein storage vacuoles. Similarly, our observations of reduced membrane diffusion align with similar effects reported for ribonucleoprotein condensates at the endoplasmic reticulum. Finally, our findings elucidate the mechanistic role of lipid bilayers in modulating condensate size, providing critical insights into the biophysical principles governing condensate nucleation and spatial organization in cellular environments.

References : 1) Karthika S Nair, Sreelakshmi Radhakrishnan, and Harsha Bajaj, Dynamic Control of Functional Coacervates in Synthetic Cells, ACS Synthetic Biology 2023, 12 (7), 2168–2177.2) Sreelakshmi Radhakrishnan, Karthika S Nair, Samir Nandi, Harsha Bajaj. Engineering Semi-Permeable Giant Liposomes, Chemical Communications, 2023, 59 (93), 13863–138663) Karthika S Nair, Sreelakshmi Radhakrishnan, Harsha Bajaj, Dynamic Duos: Coacervate-Lipid Membrane Interactions in Regulating Membrane Transformation and Condensate Size, Small, 2025, 2501470.

Nanoparticle-based drug delivery is redefining precision medicine; however, their efficacy is shaped by how these carriers interact with cellular machinery. Once internalized, nanoparticles are sorted and transported through distinct endosomal pathways based on their physicochemical properties. We aim to uncover the cellular mechanisms that direct nanoparticles to specific intracellular fates and identify druggable targets that can augment drug delivery efficiency. Using super-resolution and live-cell imaging, we investigated how negatively charged bare(uncoated)mesoporous silica nanoparticles (MSNs) and positively charged chitosan-coated MSNs are differentially sorted and trafficked within epithelial cells. We found that surface charge had a striking effect on early intracellular behavior. Within one hour of internalization, bare MSNs moved retrogradely (toward the nucleus), while chitosan-coated MSNs displayed anterograde movement (towards cell periphery)—suggesting opposite sorting cues. This spatial divergence pointed to involvement of distinct membrane identities presumably of phosphoinositides (PI). Indeed, bare MSNs were enriched in PI3P-positive compartments, while chitosan-coated MSNs localized to PI4P-positive ones. Since PI3P is a hallmark of early endosomes (EEs) and PI4P is associated with recycling endosomes and the Golgi, our results indicated that MSNs of different charge engage distinct endocytic pathways. STORM imaging revealed that Rab5, a key EE marker, exhibited differential nanoscale clustering depending on MSN charge, further confirming charge-mediated membrane alterations. Notably, both types of MSNs altered EE motility, affecting speed, run length, and pause frequency in a charge-specific manner.  Given that endosomal positioning and transport are driven by microtubules, we examined cytoskeletal engagement. Cytoskeletal analysis revealed bare MSNs preferentially associated with detyrosinated microtubules, a stable subset linked to long-range transport. Together, these results reveal that nanoparticle surface charge programs their intracellular itinerary by rewiring the lipid–Rab–cytoskeletal network. This network acts as a tunable interface, offering opportunities to control nanoparticle fate within cells and improve drug delivery efficacy.

Immune cells, such as T-cells, must perform immunosurveillance for healthy immunity. A crucial step during T-cell immunosurveillance that underlies the adaptive immune response is the formation of a specialized cell-cell contact interface, between a T-cell and its target, known as the immunological synapse. It is a highly dynamic interface where precise recruitment and regulation in space and time of surface receptors and signaling molecules, integrated with constant remodeling and repositioning of cytoskeletal elements, dictates an optimal immune response. The actin cytoskeleton is one such indispensable element, and T-cells are known to display a diverse repertoire of actin architectures and dynamics, however, the structure-function relationship between actin networks and their roles during synapse progression, is poorly established. Indeed, how the unit filament network may enable a vast variety of functions at a given time and place at the synapse, remains an outstanding question. A primary reason for this gap is that the tools for perturbation of selective actin architectures in a spatiotemporally controlled fashion are currently lacking. The routine ablation of the cytoskeleton using pharmacological inhibitors or genetic perturbations does not provide spatial or temporal control and leads to gross network perturbation. To address the mechanistic gap, we developed a novel photo-sensitive inhibitor, that can ablate actin in a defined space, at a given time, on demand. I will present unpublished data on characterization of the novel perturbation agent, using in-silico, in-vitro, and ex-vivo assays, in which actin was manipulated at an unprecedented spatiotemporal resolution at multi-cell, single-cell, and subcellular levels. Finally, I will present the insights into T cell synapse biology and sub-cellular actin dynamics achieved using the inhibitor with implications for not just immune cells, but for other cellular systems where a temporally controlled and spatially scalable manipulation is desired.

The spatial clustering of proteins and lipids within cellular membranes is fundamental to all signaling events. Capturing these associations and understanding their molecular determinants requires a platform capable of directly detecting lipid-protein noncovalent interactions from lipid membranes. To address this, we have developed a novel lipid-bilayer native-mass spectrometry (nMS) platform. We have also integrated this with ion mobility-mass spectrometry (IM-MS), confocal microscopy, molecular dynamics (MD) simulations, and bulk fusion assay for the precise determination of the organization, stability of membrane protein-lipid complexes, and their functional role. We applied these platforms to understand how protein-lipid interactions regulate the spatial clustering of SNARE proteins and neurotransmitter release. Our findings demonstrate how specific binding of phosphatidylcholine (PC) and cholesterol (CHL) to VAMP2, the vesicular protein regulates the molecular clustering. IM-MS analysis indicated that increasing CHL in the membrane stabilizes VAMP2, which in turn stabilizes its cluster. Confocal microscopy experiments further demonstrate how these CHL-mediated associations between VAMP2 and lipids regulate the spatial clustering of VAMP in SV-like membranes. Finally, by combining these results with functional assays, we have elucidated how such organization of VAMP2 and lipids regulates the speed of neurotransmitter release. This work establishes a broadly applicable experimental platform for capturing membrane protein-lipid clustering and determining the specific molecular associations that drive these critical cellular processes. I have applied these platforms to VAMP7, another crucial vesicle-associated membrane protein which forms trimer and binds to both PC and CHL in bilayer. VAMP7 plays distinct roles in intracellular trafficking and fusion events, particularly in neuronal and immune cells. Understanding how these interactions influence VAMP7's conformation and its role in membrane fusion will further enhance our understanding of the diverse molecular mechanisms that govern vesicle fusion, offering potential insights into neurological disorders and cellular communication pathways.

Across the myriad lifeforms spanning biological scales from microns to meters, the two most profoundly influential, yet ubiquitously varying biological regulators are oxygen availability and environmental mechanics. While diverse cellular processes such as metabolism, proliferation, motility, tumorigenesis, and fate decisions are affected by both varying oxygen availability and heterogeneous mechanical milieus, our present understanding is primarily shaped by independently interrogating the roles of either of these regulators without perturbing the other. Thus, a critical question remains unanswered: how do combinatorial inputs of oxygen partial pressures and microenvironment mechanics regulate cellular state? Our present work subjects cells to a combination of oxygen partial pressures and ECM densities - an oxo-mechanical cue - and profiles the cellular state by combining biophysical morphometrics, bulk transcriptome analyses, as well as chemical modulation of intracellular mechanics and oxygen-driven signaling. At lower ECM densities, acute oxygen deprivation significantly alters the cellular state, whereas, at higher ECM densities, the effect of oxygen deprivation is negligible. We independently show that a cell's response to varying oxygen availability depends on both substrate and intracellular mechanics; while the cell's engagement with mechanically diverse substrates is influenced by oxygen-driven signaling processes. Finally, using ATAC-Seq, we show that substrate mechanics alters the global chromatin accessibility, which allows hypoxic dysregulation to profoundly manifest specifically in low ECM density environments - providing a mechanistic basis for oxo-mechanical effects. Together, our work identifies an oxo-mechanical regulatory paradigm governing cellular behavior in 3D ECM-like contexts.

Deciphering the spatial organization of biological functions within tissues necessitates frameworks that can seamlessly integrate multi-modal data while preserving the intrinsic geometries of cellular interactions. In this presentation, we introduce a unified approach that amalgamates two complementary computational frameworks—GardenMap and Proximogram—to analyze tissue architecture through the lenses of spatial statistics and Riemannian geometry. GaWRDenMap employs geographically weighted regression (GWR) to quantify spatially varying interactions between cell types, such as epithelial and immune cells, across tissue sections. By transforming the distributions of GWR coefficients into probability density functions (PDFs) and mapping them onto a Riemannian manifold of square-root densities, we capture the nuanced variations in cellular interactions. This geometric representation facilitates the computation of intrinsic distances and supports principal component analysis within the manifold, enabling robust classification of tissue states based on spatial interaction signatures. Complementing this, Proximogram constructs graph-based representations that integrate spatial imaging data with single-cell omics profiles. By embedding independently acquired datasets into a joint graph structure, Proximogram captures both molecular profiles and spatial contexts. Utilizing graph convolutional networks (GCNs), this framework enhances the classification of disease states and uncovers spatially informed biomarkers, demonstrating improved discriminatory power over models relying solely on spatial data. Together, these frameworks provide a comprehensive toolkit for analyzing the spatial organization of biological functions. By integrating spatial statistics, Riemannian geometry, and graph-based multi-omics analysis, we offer novel insights into tissue heterogeneity and disease pathology. This unified approach holds promise for advancing our understanding of complex biological systems and informing therapeutic strategies.