Biology subjects

Xu, R. J.

Publications and source records attributed to Xu, R. J..

5 recordsLinked to original sources

bioRxiv2025

Electrophysiology in small compartments

Voltage-gated ion channels play important roles in many membrane-enclosed structures, including synaptic vesicles, endosomes, mitochondria, chloroplasts, viruses and bacteria. Here we study how compartment size and channel gating interact to shape voltage dynamics and ion content in sub-micron structures. In small compartments, assumptions underlying conductance-based (Hodgkin-Huxley type) models of membrane voltage must be relaxed: [1] stochastic gating of individual ion channels can quickly and substantially change membrane voltage; [2] these changes can equilibrate faster than channel state transitions; and [3] ionic currents, even through as few as two channels, can substantially alter ionic concentrations. We adapted conductance-based models to incorporate these effects, and we then simulated voltage dynamics of small vesicles as a function of vesicle radius and channel density. We identified regimes in this parameter space with qualitatively distinct dynamics. We then performed stochastic simulations to explore the role of NaV1.5 in maturation of macrophage endosomes. The stochastic model predicted dramatically different dynamics compared to a deterministic approach. Electrophysiology of nanoscale structures can be very different from larger structures, even when ion channel composition and density are preserved. SIGNIFICANCEWith tools of optical electrophysiology, one can measure and perturb membrane voltage in sub-micron structures. Recent experiments in organelles, dendritic spines, and bacteria motivate a re-examination of basic assumptions about bioelectrical phenomena in these compartments. This paper provides a framework for predicting and interpreting bioelectrical dynamics in small structures.

biophysics↗

bioRxiv2025

An image-based transcriptomics atlas reveals the regional and microbiota-dependent molecular, cellular, and spatial structure of the murine gut

The gastrointestinal environment is home to a massive diversity of diet-, host-, and microbiota-derived small molecules, collectively sensed by a remarkable variety of cells. To explore the cellular and spatial organization of sensation, we used MERFISH to profile receptor expression across 2.1 million cells in multiple regions of the murine gut under specific-pathogen-free (SPF) and germ-free (GF) conditions. This atlas revealed expected and novel cell types--including a candidate murine homolog of human BEST4 enterocytes--demonstrated cell-type regional specialization, discovered extensive location-dependent spatial fine-tuning in mucosal cell expression, and suggested cell-type specific mediators of the effects of microbiota-derived small molecules. In addition, this atlas revealed that, aside from immune cell abundance, many aspects of the murine gut are host-intrinsic and modified only modestly in the absence of a microbiota. Collectively, this atlas provides a valuable resource for understanding the cellular and spatial organization underlying small molecule sensation in the gut.

genomics↗

bioRxiv2025

Protocol Optimization Improves the Performance of Multiplexed RNA Imaging

Spatial transcriptomics has emerged as a powerful tool to define the cellular structure of diverse tissues. One such method is multiplexed error robust fluorescence in situ hybridization (MERFISH). MERFISH identifies RNAs with error tolerant optical barcodes generated through sequential rounds of single-molecule fluorescence in situ hybridization (smFISH). MERFISH performance depends on a variety of protocol choices, yet their effect on performance has yet to be systematically examined. Here we explore a variety of properties to identify optimal choices for probe design, hybridization, buffer storage, and buffer composition. In each case, we introduce protocol modifications that can improve performance, and we show that, collectively, these modified protocols can improve MERFISH quality in both cell culture and tissue samples. As RNA FISH-based methods are used in many different contexts, we anticipate that the optimization experiments we present here may provide empirical design guidance for a broad range of methods.

genomics↗

bioRxiv2024

Identifying spatially variable genes by projecting to morphologically relevant curves

Spatial transcriptomics enables high-resolution gene expression measurements while preserving the two-dimensional spatial organization of the biological sample. A common objective in spatial transcriptomics data analysis is to identify spatially variable genes within predefined cell types or regions within the tissue. However, these regions are often implicitly one-dimensional, making standard two-dimensional coordinate-based methods less effective as they overlook the underlying tissue organization. Here we introduce a methodology grounded in spectral graph theory to elucidate a one-dimensional curve that effectively approximates the spatial coordinates of the examined sample. This curve is then used to establish a new coordinate system that reflects tissue morphology. We then develop a generalized additive model (GAM) to estimate spatial patterns which permits the detection of genes with variable expression in the new morphologically relevant coordinate system. Our approach directly models gene counts, thereby eliminating the need for normalization or transformations to satisfy normality assumptions. A second important advantage over existing hypothesis-testing approaches is that our method not only improves performance but also accurately estimates gene expression patterns and precisely pinpoints spatial loci where deviations from constant expression occur. We validate our approach through extensive simulation and by analyzing experimental data from multiple platforms such as Slide-seq and MERFISH. As an example of its ability to enable biological discovery, we demonstrate how our methodology enables the identification of novel interferon-related subpopulations in the mouse mucosa, as well as markers of inflammation-associated fibroblasts in a multi-sample spatial transcriptomic dataset.

bioinformatics↗

bioRxiv2023

Charting the cellular biogeography in colitis reveals fibroblast trajectories and coordinated spatial remodeling

Gut inflammation involves contributions from immune and non-immune cells, whose interactions are shaped by the spatial organization of the healthy gut and its remodeling during inflammation. The crosstalk between fibroblasts and immune cells is an important axis in this process, but our understanding has been challenged by incomplete cell-type definition and biogeography. To address this challenge, we used MERFISH to profile the expression of 940 genes in 1.35 million cells imaged across the onset and recovery from a mouse colitis model. We identified diverse cell populations; charted their spatial organization; and revealed their polarization or recruitment in inflammation. We found a staged progression of inflammation-associated tissue neighborhoods defined, in part, by multiple inflammation-associated fibroblasts, with unique expression profiles, spatial localization, cell-cell interactions, and healthy fibroblast origins. Similar signatures in ulcerative colitis suggest conserved human processes. Broadly, we provide a framework for understanding inflammation-induced remodeling in the gut and other tissues.

immunology↗