Biology subjects

Ly, R.

Publications and source records attributed to Ly, R..

9 recordsLinked to original sources

bioRxiv2026

Cryo-EM structures reveal the mechanism of phosphatidylserine remodeling by membrane-bound glycerophospholipid O-acyltransferase 1

Lands cycle remodeling of glycerophospholipid acyl chains is crucial for cells to maintain appropriate membrane composition. Glycerophospholipids are cleaved at the glycerol sn2-position by phospholipase A. The lysophospholipids are reacylated by enzymes of the membrane-bound O-acyltransferase (MBOAT) family to incorporate specific fatty-acyl chains to adjust membrane properties. How MBOAT enzymes recognize specific acyl-CoA donors, select lysophospholipid acceptors, and release products is unclear. Phosphatidylserine (PS), a critical anionic phospholipid, controls membrane surface charge, signaling-protein recruitment, and cell-death-associated membrane recognition, and PS acyl-chain remodeling is linked to ferroptosis resistance. Here, we showed that MBOAT1 preferentially generates monounsaturated fatty acid-containing PS from lyso-PS. High-resolution cryo-electron microscopy structures of human MBOAT1 captured distinct binding poses of the fatty acyl donor, lyso-PS acceptor, and PS product. With lipidomics, enzymology and molecular dynamics simulations, these structures reveal the mechanism and pathway of MBOAT1-dependent PS remodeling.

biochemistry↗

bioRxiv2026

A Paracrine Dietary Lipid Axis Constrains Antitumor Immunity in Liver Cancer

Overnutrition-related liver dysfunction and cancer are increasingly prevalent and highly resistant to immunotherapy. While metabolic dysregulation is a hallmark of hepatocellular carcinoma (HCC), how nutrient overload impairs antitumor immunity remains unclear. Here, we show that short-term Western diet (WD) exposure drives near-complete loss of CD8 T cell infiltration and antitumor function in HCC. We identify dietary linoleic acid (LA), the most abundant {omega}-6 fatty acid, as the dominant immunosuppressive driver. Cancer cell-restricted FADS2-mediated desaturation of LA to longer-chain {omega}-6 PUFAs drives their accumulation in the tumor interstitial fluid, suppressing infiltrating CD8 T cells via lipid peroxidation. FADS2 inhibition restores CD8 T cell function and sensitizes WD-driven HCC to PD-1-based immunotherapy. Further, the Parkinsons disease-associated deglycase DJ-1 protects LA-handling proteins from methylglyoxal-mediated glycation, sustaining tumoral immunosuppressive PUFA production. Across multiple independent human MASLD-HCC cohorts, LA metabolic activity correlates with CD8 T cell impairment, immune exclusion, and immunotherapy resistance. Overall, these studies identify a dietary lipid axis as a therapeutically actionable vulnerability in WD-associated HCC.

Cancer Biology↗

bioRxiv2025

Disruption of theta-timescale spiking impairs learning but spares hippocampal replay

The ability to rapidly learn and retrieve salient information about new environments is critical for survival. In mammals, the hippocampus plays a crucial role in that learning. Specialized features of hippocampal population coding, including network-level theta oscillatory activity, location-specific firing of principal cells, and reactivation of experience during immobility (replay), have been implicated in rapid storage and retrieval of spatial information. Disruptions of theta and replay jointly, or replay alone, are sufficient to impair learning; however, the specific contribution of theta-associated temporal structure during locomotion remains unknown. In this study, we manipulated hippocampal spiking activity in rats specifically during locomotion by optogenetically activating septal parvalbumin-expressing GABAergic neurons. We developed a closed-loop, theta phase-specific stimulation protocol that reliably reduced theta power shortly after stimulation onset. This manipulation preserved the place codes of individual cells but disrupted the fine temporal structure of endogenous spatio-temporal representations (i.e., theta sequences) at the pairwise and population level. Theta disruption during locomotion was also sufficient to cause pronounced deficits in learning the more cognitively challenging component of a spatial alternation task, even though disruption was applied on only [~]66% of trials. Notably, network effects accompanying theta disruption were restricted to locomotor periods; we did not observe changes in replay rate, length, or content during immobility. Together, these results demonstrate the importance of the precise temporal microstructure of locomotion-associated spatial representations in the hippocampus for learning.

neuroscience↗

bioRxiv2025

Facilitating analysis of open neurophysiology data on the DANDI Archive using large language model tools

The DANDI Archive is a key resource for sharing open neurophysiology data, hosting over 400 datasets in the Neurodata Without Borders (NWB) format. While these datasets hold tremendous potential for reanalysis and discovery, many researchers face barriers to reuse, including unfamiliarity with access methods and difficulty identifying relevant content. Here we introduce an AI-powered, agentic chat assistant and a notebook generation pipeline. The chat assistant serves as an interactive tool for exploring DANDI datasets. It leverages large language models (LLMs) and integrates with agentic tools to guide users through data access, visualization, and preliminary analysis. The notebook generator analyzes dataset structure with minimal human input, executing inspection scripts and generating visualizations. It then produces an instructional Python notebook tailored to the dataset. We applied this system to 12 recent datasets. Review by neurophysiology data specialists found the generated notebooks to be generally accurate and well-structured, with most notebooks rated as "very helpful." This work demonstrates how AI can support FAIR principles by lowering barriers to data reuse and engagement.

neuroscience↗

bioRxiv2024

Unifying community-wide whole-brain imaging datasets enables robust automated neuron identification and reveals determinants of neuron positioning in C. elegans

We develop a data harmonization approach for C. elegans volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org). We use this repository to train three existing automated cell identification algorithms to, for the first time, enable accuracy in neural identification that generalizes across labs, approaching human performance in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. To facilitate communal use of this repository, we created open-source software, code, web-based tools, and tutorials to explore and curate datasets for contribution to the scientific community. This repository provides a growing resource for experimentalists, theorists, and toolmakers to (a) study neuroanatomical organization and neural activity across diverse experimental paradigms, (b) develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and (c) inform models of neurobiological development and function.

neuroscience↗

bioRxiv2024

Spyglass: a data analysis framework for reproducible and shareable neuroscience research

Scientific progress depends on reliable and reproducible results. Progress can be accelerated when data are shared and re-analyzed to address new questions. Current approaches to storing and analyzing neural data involve bespoke formats and software that make replication and reuse of data difficult. To address these challenges, we created Spyglass, an open-source data management and analysis framework written in Python. Spyglass provides reproducible pipelines for common neuroscience analyses and sharing of raw data, intermediate analyses, and final results within and across labs. Spyglass uses the Neurodata Without Borders (NWB) standard and includes pipelines for spectral filtering, spike sorting, pose tracking, and neural decoding. Spyglass can be extended to apply existing and newly developed pipelines to datasets from multiple sources. We demonstrate these features in the context of a cross-laboratory replication by applying advanced state space decoding algorithms to publicly available data. New users can try out Spyglass on a Jupyter Hub hosted by HHMI and 2i2c: https://spyglass.hhmi.2i2c.cloud/.

neuroscience↗

bioRxiv2024

Structured behavioral data format: An NWB extension standard for task-based behavioral neuroscience experiments

Understanding brain function necessitates linking neural activity with corresponding behavior. Structured behavioral experiments are crucial for probing the neural computations and dynamics underlying behavior; however, adequately representing their complex data is a significant challenge. Currently, a comprehensive data standard that fully encapsulates task-based experiments, integrating neural activity with the richness of behavioral context, is lacking. We designed a data model, as an extension to the NWB neurophysiology data standard, to represent structured behavioral neuroscience experiments, spanning stimulus delivery, timestamped events and responses, and simultaneous neural recordings. This data format is validated through its application to a variety of experimental designs, showcasing its potential to advance integrative analyses of neural circuits and complex behaviors. This work introduces a comprehensive data standard designed to capture and store a spectrum of behavioral data, encapsulating the multifaceted nature of modern neuroscience experiments.

neuroscience↗

bioRxiv2021

The Neurodata Without Borders ecosystem for neurophysiological data science

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWBs impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

neuroscience↗

bioRxiv2018

Pulvinar influences parietal delay activity and information transmission between dorsal and ventral visual cortex in macaques

The fronto-parietal attention network represents attentional priorities and provides feedback about these priorities to sensory cortical areas. Sustained spiking activity in the posterior parietal cortex (PPC) carries such prioritized information, but how this activity is sustained in the absence of feedforward sensory information, and how it is transmitted to the ventral visual cortical pathway, is unclear. We hypothesized that the higher-order thalamic nucleus, the pulvinar, which is connected with both the PPC and ventral visual cortical pathway, influences information transmission within and between these cortical regions. To test this, we simultaneously recorded from the pulvinar, lateral intraparietal area (LIP) and visual cortical area V4 in macaques performing a selective attention task. Here we show that LIP influenced V4 during the delay period of the attention task, and that the pulvinar regulated LIP-V4 information exchange. Pulvino-cortical effects were consistent with the pulvinar supporting sustained activity in LIP. Taken together, these results suggest that pulvinar regulation of cortical functional connectivity generalizes to dorsal and ventral visual cortical pathways. Further, the pulvinars role in sustaining parietal delay activity during selective attention implicates the pulvinar in other cognitive processes supported by such delay activity, including decision-making, categorization and oculomotor functions.\n\nSignificance StatementA network of areas on the brains surface, in frontal and parietal cortex, allocate attention to behaviorally relevant information around us. Such areas in parietal cortex show sustained activity during maintained attention and transmit behaviorally relevant information to visual cortical areas to enhance sensory processing of attended objects. How this activity is sustained and how it is transmitted to visual areas supporting object perception is unclear. We show that a subcortical area, the pulvinar in the thalamus, helps sustain activity in the cortex and regulates the information transmitted between the fronto-parietal attention network and visual cortex. This suggests that the thalamus, classically considered as a simple relay for sensory information, contributes to higher-level cognitive functions.

neuroscience↗