Biology subjects

Radhakrishnan, A.

Publications and source records attributed to Radhakrishnan, A..

16 recordsLinked to original sources

bioRxiv2026

Controlling membrane tension by dynamic DNA nanorings

Membrane tension, defined as the energy cost to expand the membrane surface area, is a fundamental mechanical property of the lipid bilayer and an important modulator of various cellular processes. Liposomes provide model systems to study protein-mediated membrane dynamics, where membrane tension can be controlled by osmotic pressure and micropipette aspiration. However, it is challenging to individually control membrane tension of nanometer-sized liposomes, such as small unilamellar vesicles (SUVs), that are widely used for modeling subcellular membrane structures and drug delivery. To bridge this technological gap, we present reconfigurable DNA origami rings for dynamically controlling membrane tension of sub-100 nm liposomes. The DNA nanorings template the formation of uniformly sized SUVs and undergo trigger-responsive dilation and contraction, thus applying controlled and reversible mechanical stress to the SUV membranes. Electron microscopy analyses show deformed liposomes with ~2.5% expanded membrane area following ring dilation. The corresponding increase in membrane tension opens a mechanosensitive ion channel MscL with gating tension of ~10 mN/m. Selectively manipulating a mixture of SUV populations enables timed release of their distinct molecular cargos, either concurrently or one at a time. Furthermore, vesicles with expanded membranes are more conducive to SNARE-mediated fusion. The nanomechanical device thus provides a programmable platform for engineering the mechanics of synthetic nano-vesicles and studying membrane tension modulated processes at the molecular level.

biophysics↗

bioRxiv2026

Genetic Programming of Bacterial Microcompartments: Operon Order as a Tool for Nanoscale Morphogenesis

Gene order is a powerful design principle for protein nanomachines. In nature, gene organisation ensures the precise assembly of functional protein nanostructures. We demonstrate how genetic repositioning of the key structural gene pduN, within the operon encoding a self-assembling protein nanocompartment, sculpts the morphology and function of bacterial microcompartments (BMCs). Relocating pduN to new operonic positions dramatically altered the size, shape, and catalytic output of BMCs, despite identical protein sequences. These shifts reveal how gene order may control nanoscale assembly and compartmentalised function. Our findings establish operon architecture as a programmable genetic framework for nanostructure morphogenesis and provide a synthetic biology strategy to engineer self-assembling nanodevices with customised geometries and activities.

synthetic biology↗

bioRxiv2025

Curvature-Encoded Photochemistry for Programmable Isolation and Fractionation of Extracellular and Plasma Membrane Vesicles

AbstractLipid-based nanoparticles, including extracellular vesicles (EVs), cell membrane vesicles (CMVs), and biomimetic nanovesicles, are emerging as powerful carriers for therapy and diagnosis due to their ability to transport diverse payloads across biological barriers. EVs, in particular, show promise for liquid biopsy and systemic therapy because of their endogenous origin, biocompatibility, and intrinsic targeting capacity. Cell-derived plasma membrane nanovesicles complement EVs by preserving the source cells membrane architecture and receptor landscape, creating customizable scaffolds for biomimetic drug delivery. However, the full potential of these lipid nanovesicles has been challenging because current isolation workflows are labor-intensive, low-yield, and often lack purity, forming a critical bottleneck for clinical translation and standardized manufacturing. To overcome these challenges, we developed a programmable electrostatic and light-activated platform for isolating lipid vesicles directly from complex biological fluids in a rapid, high-purity, and scalable manner. Our approach employs photocleavable lipid nanoprobes (PLNs) that insert into vesicle membranes in a size-dependent fashion and, together with a cationic polymer, enable efficient capture on a solid support. A brief light exposure cleaves the probes to trigger on-demand release and fractionation of intact vesicles with high speed and precision. Using this platform, we demonstrate high-purity EV isolation with preserved membrane protein functionality, as well as single-step enrichment of right-side-out (RSO) cell membrane nanovesicles that maintain native membrane orientation for effective drug delivery. The capability to rapidly isolate and tailor vesicle subpopulations by size and orientation establishes a unified materials platform for precision nanomedicine and advanced therapeutics, paving the way toward clinical-grade vesicle production and next-generation liquid biopsy applications.

bioengineering↗

bioRxiv2025

PD-1 blockade during T cell priming enhances long-term protection against metastatic tumors by epigenetically tuning T cell exhaustion

In cancer, CD8+ T cell responses are dominated by exhausted T cells, which can be reinvigorated using immune checkpoint blockade therapy and can control large tumors. However, it remains unclear which T cell fate best supports long-term immunity following tumor regression or clearance and a period of minimal antigen load. This question is particularly relevant following surgical tumor resection, when tuning the immune system could prevent recurrence. To determine which T cell fate provides durable protection following surgery and metastatic rechallenge, we modulated T cell priming using anti-PD-1, IFN-{beta} or agonistic anti-CD40 and assessed effects on CD8+ T cell differentiation and overall survival. IFN-{beta} and anti-CD40 promoted effector and memory-like T cell states, respectively, whereas anti-PD-1 did not markedly alter T cell differentiation, yet conferred the greatest survival benefit against metastatic tumors. Notably, anti-PD-1 induced epigenetic remodeling, which was detectable upon metastatic recall, consistent with the maintenance of a circulatory intermediate-exhausted T cell state. Thus, while effector and memory precursor-like T cells could be generated with IFN-{beta} and agonistic anti-CD40, only the intermediate-exhausted T cell state driven by anti-PD-1 supported durable anti-tumor immunity. SummaryThis study shows that PD-1 blockade during T cell priming promotes a circulatory intermediate-exhausted CD8 T cell state that uniquely supports durable anti-tumor immunity after surgical resection and metastatic challenge, outperforming effector or memory-like T cell responses generated by IFN-{beta} or CD40 agonist treatment, respectively.

immunology↗

bioRxiv2025

Single-cell tracking of genetically minimized Salmonella reveals mechanisms of effector gene cooperation.

Bacterial pathogens encode secretory systems that deliver large repertoires of effector proteins directly into host cells. While many effector proteins have been characterized biochemically, it is unclear where and when they function within complex cellular systems of host tissues. This problem exists because of the extensive genetic and functional redundancies found in large effector protein repertoires. Here, we coupled targeted genome minimization with single cell mass cytometry to track the cellular location where Salmonella Typhimurium (S.Tm) SPI-2 Type Three Secretion System effector proteins function in a time-resolved animal model of infection. This approach revealed the temporal progression of S.Tm transmission within a complex tissue and pinpointed effector genes responsible for pathogen dissemination between host immune cell types. We further show how coupling two effector gene networks acquired during distinct episodes of bacterial evolution has shaped the cellular and tissue tropism of non-Typhoidal Salmonella species. Together, these results illustrate a top-down genetic approach to interrogate host-pathogen interactions hidden by functional redundancies within large virulence factor gene networks.

microbiology↗

bioRxiv2025

The Golgi Rim is a Precise Tetraplex of Golgin Proteins that Can Self-Assemble into Filamentous Bands

Golgin proteins have long been suspected to be organizers of the Golgi stack. Using three-dimensional super-resolution microscopy, we comprehensively localize the human golgin family at the rim of the Golgi apparatus at 10-20 nm resolution in situ. Unexpectedly, we find that the golgins are precisely organized into a tetraplex with four discrete layers, each containing a specific set of rim golgins. We observe no golgins inside the stack between its membrane-bound cisternae. Biochemically characterizing most of the golgins as isolated proteins, we find that they form anti-parallel dimers and further self-assemble into bands of multi-micron-long filaments. Based on our findings, we propose an "outside-in" physical model, the Golgin Organizer Hypothesis, in which the Golgi stack of cisternae and its overall ribbon morphology directly result from bending circumferential bands of rim golgin filaments onto a membrane surface, explaining stack formation without the need for special "stacking proteins."

cell biology↗

bioRxiv2024

Single-cell image-based genetic screens systematically identify regulators of Ebola virus subcellular infection dynamics

Ebola virus (EBOV) is a high-consequence filovirus that gives rise to frequent epidemics with high case fatality rates and few therapeutic options. Here, we applied image-based screening of a genome-wide CRISPR library to systematically identify host cell regulators of Ebola virus infection in 39,085,093 million single cells. Measuring viral RNA and protein levels together with their localization in cells identified over 998 related host factors and provided detailed information about the role of each gene across the virus replication cycle. We trained a deep learning model on single-cell images to associate each host factor with predicted replication steps, and confirmed the predicted relationship for select host factors. Among the findings, we showed that the mitochondrial complex III subunit UQCRB is a post-entry regulator of Ebola virus RNA replication, and demonstrated that UQCRB inhibition with a small molecule reduced overall Ebola virus infection with an IC50 of 5 M. Using a random forest model, we also identified perturbations that reduced infection by disrupting the equilibrium between viral RNA and protein. One such protein, STRAP, is a spliceosome-associated factor that was found to be closely associated with VP35, a viral protein required for RNA processing. Loss of STRAP expression resulted in a reduction in full-length viral genome production and subsequent production of non-infectious virus particles. Overall, the data produced in this genome-wide high-content single-cell screen and secondary screens in additional cell lines and related filoviruses (MARV and SUDV) revealed new insights about the role of host factors in virus replication and potential new targets for therapeutic intervention.

microbiology↗

bioRxiv2023

Synthetic Lethality Screening with Recursive Feature Machines

Synthetic lethality refers to a genetic interaction where the simultaneous perturbation of gene pairs leads to cell death. Synthetically lethal gene pairs (SL pairs) provide a potential avenue for selectively targeting cancer cells based on genetic vulnerabilities. The rise of large-scale gene perturbation screens such as the Cancer Dependency Map (DepMap) offers the opportunity to identify SL pairs automatically using machine learning. We build on a recently developed class of feature learning kernel machines known as Recursive Feature Machines (RFMs) to develop a pipeline for identifying SL pairs based on CRISPR viability data from DepMap. In particular, we first train RFMs to predict viability scores for a given CRISPR gene knockout from cell line embeddings consisting of gene expression and mutation features. After training, RFMs use a statistical operator known as average gradient outer product to provide weights for each feature indicating the importance of each feature in predicting cellular viability. We subsequently apply correlation-based filters to re-weight RFM feature importances and identify those features that are most indicative of low cellular viability. Our resulting pipeline is computationally efficient, taking under 3 minutes for analyzing all 17, 453 knockouts from DepMap for candidate SL pairs. We show that our pipeline more accurately recovers experimentally verified SL pairs than prior approaches. Moreover, our pipeline finds new candidate SL pairs, thereby opening novel avenues for identifying genetic vulnerabilities in cancer.

bioinformatics↗

bioRxiv2023

Two successive oligomeric Munc13 assemblies scaffold vesicle docking and SNARE assembly to support neurotransmitter release

The critical presynaptic protein Munc13 serves numerous roles in the process of docking and priming synaptic vesicles. Here we investigate the functional significance of two distinct oligomers of the Munc13 core domain (Munc13C) comprising C1-C2B-MUN-C2C. Oligomer interface point mutations that specifically destabilized either the trimer or lateral hexamer assemblies of Munc13C disrupted vesicle docking, trans-SNARE formation, and Ca2+-triggered vesicle fusion in vitro and impaired neurotransmitter secretion and motor nervous system function in vivo. We suggest that a progression of oligomeric Munc13 complexes couples vesicle docking and assembly of a precise number of SNARE molecules to support rapid and high-fidelity vesicle priming.

neuroscience↗

bioRxiv2023

Synaptophysin Chaperones the Assembly of 12 SNAREpins under each Ready-Release Vesicle

The synaptic vesicle protein Synaptophysin has long been known to form a complex with the v-SNARE VAMP, but a more specific molecular function or mechanism of action in exocytosis has been lacking because gene knockouts have minimal effects. Utilizing fully-defined reconstitution and single-molecule measurements, we now report that Synaptophysin functions as a chaperone that determines the number of SNAREpins assembling between a ready-release vesicle and its target membrane bilayer. Specifically, Synaptophysin directs the assembly of 12 {+/-} 1 SNAREpins under each docked vesicle, even in the face of an excess of SNARE proteins. The SNAREpins assemble in successive waves of 6 {+/-} 1 and 5 {+/-} 2 SNAREpins, respectively, tightly linked to oligomerization of and binding to the vesicle Ca++ sensor Synaptotagmin. Templating of 12 SNAREpins by Synaptophysin is likely the direct result of its hexamer structure and its binding of VAMP2 dimers, both of which we demonstrate in detergent extracts and lipid bilayers. Significance StatementSynaptophysin is the most abundant protein and a unique constituent of synaptic vesicles, yet it has no known function, due to minimal genetic phenotypes and the lack of biochemical assays. Here, we directly establish using two independent methods that the synaptic vesicle protein Synaptophysin forms a hexameric complex containing 12 copies of the v-SNARE VAMP2. These v-SNAREs assemble into SNAREpins as ready-release vesicles are formed in a fully-defined cell-free system, and do so in two equal waves organized by oligomerization of the Ca++ sensor Synaptotagmin. In the absence of Synaptophysin, two waves are also observed, but the number of SNAREpins in each varies widely. We suggest that a single Synaptophysin hexamer in each vesicle symmetrically organizes 6 pairs of peripheral and central SNAREpins, the latter being directly bound to the Synaptotagmin ring. This gives rise to the symmetrical ring-like arrangement of densities observed by cryo-EM tomography under each synaptic vesicle (1, 2).

neuroscience↗

bioRxiv2022

A concerted mechanism involving ACAT and SREBPs by which oxysterols deplete accessible cholesterol to restrict microbial infection

Most of the cholesterol in the plasma membranes (PMs) of animal cells is sequestered through interactions with phospholipids and transmembrane domains of proteins. However, as cholesterol concentration rises above the PMs sequestration capacity, a new pool of cholesterol, called accessible cholesterol, emerges. The transport of accessible cholesterol between the PM and the endoplasmic reticulum (ER) is critical to maintain cholesterol homeostasis. This pathway has also been implicated in the suppression of both bacterial and viral pathogens by immunomodulatory oxysterols. Here, we describe a mechanism of depletion of accessible cholesterol from PMs by the oxysterol 25-hydroxycholesterol (25HC). We show that 25HC-mediated activation of acyl coenzyme A: cholesterol acyltransferase (ACAT) in the ER creates an imbalance in the equilibrium distribution of accessible cholesterol between the ER and PM. This imbalance triggers the rapid internalization of accessible cholesterol from the PM, which is sustained for long periods of time through 25HC-mediated suppression of SREBPs. In support of a physiological role for this mechanism, 25HC failed to suppress Zika virus and human coronavirus infection in ACAT-deficient cells, and Listeria monocytogenes infection in ACAT-deficient cells and mice. We propose that selective depletion of accessible PM cholesterol triggered by ACAT activation and sustained through SREBP suppression underpins the immunological activities of 25HC and a functionally related class of oxysterols.

cell biology↗

bioRxiv2022

Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State

A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardio-vascular state. In particular, we use our framework to construct such cross-modal representations from cardiac magnetic resonance images (MRIs), containing structural information, and electrocardiograms (ECGs), containing myoelectric information. We leverage the learned cross-modal representation to (1) improve phenotype prediction from a single, accessible phenotype such as ECGs; (2) enable imputation of hard-to-acquire cardiac MRIs from easy-to-acquire ECGs; and (3) develop a framework for performing genome-wide association studies in an unsupervised manner. Our results provide a framework for integrating distinct diagnostic modalities into a common representation that better characterizes physiologic state.

bioinformatics↗

bioRxiv2020

Molecular Basis for the Adaptive Evolution of Environment Sensing by H-NS Proteins

The DNA-binding protein H-NS is a pleiotropic gene regulator in gram-negative bacteria. Through its capacity to sense temperature and other environmental factors, H-NS allows pathogens like Salmonella to adapt their gene expression, and hence toxicity and biological responses, to their presence inside or outside warm-blooded hosts. To investigate how this sensing mechanism may have evolved to fit different bacterial lifestyles, we compared H-NS orthologs from bacteria that infect humans, plants, and insects, and from bacteria that live on a deep-sea hypothermal vent. The combination of biophysical characterization, high-resolution proton-less NMR spectroscopy and molecular simulations revealed, at an atomistic level, how the same general mechanism was adapted to specific habitats and lifestyles. In particular, we demonstrate how environment-sensing characteristics arise from specifically positioned intra- or intermolecular electrostatic interactions. Our integrative approach clarified the mechanism for H-NS-mediated environmental sensing and suggests that it resulted from the exaptation of an ancestral protein feature.

biochemistry↗

bioRxiv2019

Multi-Domain Translation between Single-Cell Imaging and Sequencing Data using Autoencoders

The development of single-cell methods for capturing different data modalities including imaging and sequencing have revolutionized our ability to identify heterogeneous cell states. While various methods have been proposed to integrate different sequencing data modalities, coupling imaging and sequencing has been an open challenge. We here present an approach for integrating vastly different modalities by learning a probabilistic coupling between the different data modalities using autoencoders to map to a shared latent space. We validate this approach by integrating single-cell RNA-seq and chromatin images to identify distinct sub-populations of human naive CD4+ T-cells that are poised for activation. Collectively, our approach provides a framework to integrate and translate between data modalities that cannot yet be measured within the same cell for diverse applications in biomedical discovery.

bioinformatics↗

bioRxiv2019

Sphingomyelin suppresses Hedgehog signaling by restricting cholesterol accessibility at the ciliary membrane

Transmission of the Hedgehog signal across the plasma membrane by Smoothened is proposed to be triggered by its direct interaction with cholesterol. But how is cholesterol, an abundant lipid, regulated tightly enough to control a signaling system that can cause birth defects and cancer? Using toxin-based sensors that distinguish between distinct pools of cholesterol, we find here that Smoothened activation and Hedgehog signaling are driven by a biochemically defined fraction of membrane cholesterol, termed accessible cholesterol. Increasing accessible cholesterol levels by depletion of sphingomyelin, which sequesters cholesterol in complexes, potentiates Hedgehog signaling. By inactivating the transporter-like protein Patched 1, Hedgehog ligands trigger an increase in cholesterol accessibility in the ciliary membrane, the subcellular location for Smoothened signaling. Thus, compartmentalization of Hedgehog signaling in the primary cilium may allow cholesterol accessibility to be used as a second messenger to mediate the communication between Patched 1 and Smoothened, without causing collateral effects on other cellular processes.

cell biology↗

bioRxiv2017

Scikit-ribo: Accurate estimation and robust modeling of translation dynamics at codon resolution

Ribosome profiling (Riboseq) is a powerful technique for measuring protein translation, however, sampling errors and biological biases are prevalent and poorly understand. Addressing these issues, we present Scikit-ribo (https://github.com/hanfang/scikit-ribo), the first open-source software for accurate genome-wide A-site prediction and translation efficiency (TE) estimation from Riboseq and RNAseq data. Scikit-ribo accurately identifies A-site locations and reproduces codon elongation rates using several digestion protocols (r = 0.99). Next we show commonly used RPKM-derived TE estimation is prone to biases, especially for low-abundance genes. Scikit-ribo introduces a codon-level generalized linear model with ridge penalty that correctly estimates TE while accommodating variable codon elongation rates and mRNA secondary structure. This corrects the TE errors for over 2000 genes in S. cerevisiae, which we validate using mass spectrometry of protein abundances (r = 0.81) and allows us to determine the Kozak-like sequence directly from Riboseq. We conclude with an analysis of coverage requirements needed for robust codon-level analysis, and quantify the artifacts that can occur from cycloheximide treatment.

bioinformatics↗