Biology subjects

Chaudhari, P.

Publications and source records attributed to Chaudhari, P..

9 recordsLinked to original sources

bioRxiv2026

Remodelling of chromatin architecture and super-enhancer landscape in lamin A/C depleted HGSOC

Lamins are nuclear intermediate filament proteins that maintain nuclear architecture through interactions with the chromatin. The A- and B-type lamins tether the genome at the peripheral lamina underlying the inner nuclear membrane in the form of heterochromatic lamina-associated domains (LADs). However, LADs associated with A-type lamins are confined not only to lamina but also to the nuclear core, thereby pointing to their distinct and multifarious roles in chromatin organisation and regulation. Previous studies involving lamin B1 depletion depicted the detachment of LADs from the nuclear periphery, accompanied by alteration of chromatin distribution while preserving the topologically associating domains (TADs) in structurally intact form. In this piece of work, we have shown, for the first time in HGSOC, the effects of lamin A/C knockdown on chromatin organisation, which was characterised by significant detethering of gene-poor chromatin from the periphery along with active (A) to inactive (B) compartment switching. This was associated with a rewiring of oncogenic super-enhancer elements corroborated by the differential gene expression profile. Overall analysis tipped the scale in favour of reduced cellular proliferation upon lamin A/C knockdown. This finding was strengthened by the observed proliferative potential of spheroids ex vivo and tumours in a mouse xenograft model.

cancer biology↗

bioRxiv2026

A simple model of the co-emergence of grid and place fields

Grid cells in the medial entorhinal cortex and place cells in the hippocampus together support spatial navigation. The two regions are reciprocally connected, and there is a chicken-and-egg problem for how both arise and reinforce each other during development. Current computational accounts either derive one type from the other or use network dynamics to model the emergence of one type in isolation. We introduce a unified recurrent network model that instantiates Dales Law (every neuron is either excitatory or inhibitory), and is trained to predict the next sensory observation from masked previous sensory observations and egocentric motion. To our knowledge, this is the first single-objective model in which grid and place cells co-emerge without supervision of either type, or reliance on pre-existing spatial-cell representations. The two kinds of spatial codes coexist across 1,000 different training configurations, with their balance set by the amount of sensory noise and masking. Without retraining, the network qualitatively reproduces experimentally observed grid fragmentation in hairpin mazes, grid merging after wall removal, lattice alignment across connected rooms, locally ordered 3D fields observed in freely flying bats, as well as the developmental order in which place cells precede grid cells. We interpret these results in terms of two complementary encoding pressures within a single sensory-prediction objective: (1) correcting errors or reconstructing missing components of sensory observations, and (2) prediction of the next sensory state during navigation. Our results suggest a circuit-level account of the co-emergence of grid and place cells, and experimentally testable predictions for the two kinds of spatial codes. Codes for experiments are available at 1,2.

neuroscience↗

bioRxiv2025

Measuring Dependencies between Biological Signals with Temporal Self-supervision, and its Limitations

Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions that currently cannot be captured without a priori knowledge regarding the nature of dependence. We introduce a self-supervised approach, concurrence, which is inspired by the observation that if two signals are dependent, then one should be able to distinguish between temporally aligned vs. misaligned segments extracted from them. Experiments with fMRI, physiological and behavioral signals show that, to our knowledge, concurrence is the first approach that can expose relationships across such a wide spectrum of signals and extract scientifically relevant differences without ad-hoc parameter tuning or reliance on a priori information, providing a potent tool for scientific discoveries across fields. However, depencencies caused by extraneous factors remain an open problem, thus researchers should validate that exposed relationships truely pertain to the question(s) of interest.

bioinformatics↗

bioRxiv2025

REMI: Reconstructing Episodic Memory During Intrinsic Path Planning

Grid cells in the medial entorhinal cortex (MEC) and place cells in the hippocampus (HC) both form spatial representations. Grid cells fire in triangular grid patterns, while place cells fire at specific locations and respond to contextual cues. How do these interacting systems support not only spatial encoding but also internally driven path planning, such as navigating to locations recalled from cues? Here, we propose a system-level theory of MEC-HC wiring that explains how grid and place cell patterns could be connected to enable cue-triggered goal retrieval, path planning, and reconstruction of sensory experience along planned routes. We suggest that place cells autoassociate sensory inputs with grid cell patterns, allowing sensory cues to trigger recall of goal-location grid patterns. We show analytically that grid-based planning permits shortcuts through unvisited locations and generalizes local transitions to long-range paths. During planning, intermediate grid states trigger place cell pattern completion, reconstructing sensory experiences along the route. Using a single-layer RNN modeling the HC-MEC loop with a planning subnetwork, we demonstrate these effects in both biologically grounded navigation simulations using RatatouGym and visually realistic navigation tasks using Habitat Sim. Codes for experiments, simulations, and vision encoder are available at 1,2,3.

neuroscience↗

bioRxiv2023

How Occam's razor guides human decision-making

Occam's razor is the principle that, all else being equal, simpler explanations should be preferred over more complex ones. This principle is thought to guide human decision-making, but the nature of this guidance is not known. Here we used preregistered behavioral experiments to show that people tend to prefer the simpler of two alternative explanations for uncertain data. These preferences align quantitatively with predictions of formal theories of model selection that penalize excessive flexibility. These penalties emerge when considering not just the best explanation but the integral over all possible, relevant explanations. We further show that these simplicity preferences persist in humans, but not in certain artificial neural networks, even when they are maladaptive. Our results imply that principled notions of statistical model selection, including integrating over possible, latent causes to avoid overfitting to noisy data, may play a central role in human decision-making.

neuroscience↗

bioRxiv2022

Time as a supervisor: temporal regularity and auditory object learning

Sensory systems appear to learn to transform incoming sensory information into perceptual representations, or "objects", that can inform and guide behavior with minimal explicit supervision. Here, we propose that the auditory system can achieve this goal by using time as a supervisor, i.e., by learning features of a stimulus that are temporally regular. We will show that this procedure generates a feature space sufficient to support fundamental computations of auditory perception. In detail, we consider the problem of discriminating between instances of a prototypical class of natural auditory objects, i.e., rhesus macaque vocalizations. We test discrimination in two ethologically relevant tasks: discrimination in a cluttered acoustic background and generalization to discriminate between novel exemplars. We show that an algorithm that learns these temporally regular features affords better or equivalent discrimination and generalization than conventional feature-selection algorithms, i.e., principal component analysis and independent component analysis. Our findings suggest that the slow temporal features of auditory stimuli may be sufficient for parsing auditory scenes and that the auditory brain could utilize these slowly changing temporal features.

neuroscience↗

bioRxiv2022

Nuclear Location Bias of HCAR1 Drives Cancer Malignancy through Numerous Routes

The involvement of G-Protein-Coupled Receptors (GPCR) location bias in diverse cellular functions and their misregulation in pathology is an underexplored territory. HCAR1, a GPCR for lactate is linked to cancer progression, mainly due to Warburg effect, but its mechanism of action remains elusive. Here, we show HCAR1 has a nuclear localization, capable of signaling intranuclearly to induce nuclear-ERK and AKT phosphorylation concomitant with higher cancer cell proliferation and survival. We determine its nuclear interactome, proving its involvement in protein-translation and DNA-damage repair. Nuclear HCAR1 (N-HCAR1) directly interacts with chromatin/DNA promoting expression of genes involved in cellular migration. Notably, we show N-HCAR1 particularly regulates a broader transcriptomic signature than its PM counterpart, emphasizing on the facts that functional output of N-HCAR1 is larger than PM localized HCAR1. Our study presents several unprecedented processes by which a GPCR through location-biased activity regulate various cellular functions and how cancer cells exploit these.

cell biology↗

bioRxiv2020

Induction of intracellular wild-type p53 amyloids leading to cellular transformation and tumor formation in mice

Tumor suppressor p53 mutations, with subsequent loss-of-tumor suppressive function and gain-of oncogenic functions, are associated with more than 50% of human cancers. Aggregation and amyloid formation are also mechanisms by which wild type and mutant p53 might be involved in cancer, but the direct evidence of how aggregated p53 acts as an oncogene is lacking. In this study, we directly demonstrate that wild-type p53 amyloid formation imparts oncogenic properties to normal cells. Cells with p53 amyloids show enhanced survival, apoptotic resistance with increased proliferation and migration rates. The tumorigenic potential of p53 amyloid transformed cells is further confirmed in a mice xenograft model, wherein the tumor showed p53 amyloid aggregates. Gene-expression analysis and proteomic profiling suggest that p53 amyloid formation triggers aberrant expression of pro-oncogenes while downregulating the tumor-suppressive genes. Interestingly, disaggregating p53 rescues the cellular transformation and also inhibits tumor development in mice. We propose that wild-type p53 amyloid formation can potentially contribute to the initiation of tumor development.

cancer biology↗

bioRxiv2018

ERBB2 and KRAS Alterations Mediate Response to EGFR Inhibitors in early stage Gallbladder Cancer

The uncommonness of gallbladder cancer has contributed to the generally poor understanding of the disease, with scant reports restricted to advance-stage tumors. Here, using an integrated analysis of whole exome and phospho-proteome, we show recurrent activating ERBB2 and KRAS somatic mutations are present in 6 and 3 of 44 early-stage rare gallbladder tumors, respectively. In vitro and in vivo cell-based and biochemical assays reveal an essential role of ErbB pathway activation for the survival of gallbladder cells. Interestingly, the genetic and pharmacological dependencies of gallbladder cells are dependent on the KRAS mutant allele status, reminiscent of the clinical algorithm commonly practiced to opt for anti-EGFR treatment in colorectal cancer. In overall, we present the first evidence that the presence of KRAS (G12V), but not KRAS (G13D) mutation, may preclude gallbladder cancer patients to respond to anti-EGFR treatment, leading to an early adoption of an approved treatment regimen for gallbladder cancer patients.

cancer biology↗