Biology subjects

Riley, N.

Publications and source records attributed to Riley, N..

5 recordsLinked to original sources

bioRxiv2026

Bilayer thickness and transmembrane domain dynamics drive directional ER-Golgi traffic via Erv14/cornichon

Directionality of protein traffic during secretion is driven by sorting receptors that bind cargo in one compartment and release them in another. Erv14/cornichon family receptors mediate delivery from the endoplasmic reticulum (ER) to the Golgi. Erv14 traffics its client, Mid2, via a conserved interface formed by two transmembrane helices (TMHs). Molecular dynamics simulations of Erv14-Mid2 suggest that Erv14 TMHs undergo dynamic movement in response to both client binding and lipid bilayer thickness. Interaction between charged residues that flank the TMHs of Mid2 and Erv14 couple client binding to stabilization of the Erv14 export signal and thus engagement with the COPII coat. We term this mechanism Helix Engagement Induced Signal-mediated Traffic (HEIST) and suggest it as a general mechanism where changes in membrane biophysical properties drive directional transport.

cell biology↗

bioRxiv2025

3D Hybrid Bioprinting for Complex Multi-Tissue Engineering

3D bioprinting has revolutionized tissue engineering, enabling intricate, physiologically relevant constructs unattainable with conventional techniques, yet it remains limited in integrating soft and rigid multifunctional components for complex multi-tissue applications. In this study, we introduce a 3D hybrid bioprinting approach implementing the Hybprinter platform, which integrates multiple 3D printing modules under optimized conditions for a continuous bioprinting process with multiple soft and hard biomaterials. This approach demonstrates robust biocompatibility and broad tissue engineering potential for modeling and therapeutic applications. The capacity to fabricate multi-hydrogel hybrid constructs is illustrated by representative examples highlighting vascularization, multifunctionality, mechanical robustness, and implant suturability. Notably, compared with commonly fabricated hydrogel-only constructs, the resulting hybrid constructs achieve over a 1000-fold increase in mechanical strength, and demonstrated enhanced osteogenic differentiation, underscoring their suitability for load-bearing musculoskeletal and orthopedic tissue engineering. Additionally, cell-laden hydrogel constructs demonstrated robust chondrogenic differentiation, highlighting the capacity for lineage-specific tissue development in vitro. Beyond these outcomes, the presented hybrid bioprinting approach integrates essential tissue engineering attributes that unites mechanical robustness and suturable capacity with multi-material integration, gradient property design, incorporation of bioactive agents, and support for multi-cell loading. This versatile platform advances complex tissue engineering and holds promise for patient specific, organ-on-demand applications.

bioengineering↗

bioRxiv2024

Dietary lipid is largely deposited in skin and rapidly affects insulating properties

Skin has been shown to be a regulatory hub for energy expenditure and metabolism: mutations of skin lipid metabolism enzymes can change the rate of thermogenesis and susceptibility to diet-induced obesity. However, little is known about the physiological basis for this function. Here we show that the thermal properties of skin are highly reactive to diet: within three days, a high fat diet reduces heat transfer through skin. In contrast, a dietary manipulation that prevents obesity accelerates energy loss through skins. We found that skin was the largest target in a mouse body for dietary fat delivery, and that dietary triglyceride was assimilated both by epidermis and by dermal white adipose tissue. Skin from mice calorie-restricted for 3 weeks did not take up circulating lipids and showed a highly depleted stratum corneum. Dietary triglyceride acyl groups persist in skin for weeks after feeding. Using multi-modal lipid profiling, we have implicated both keratinocytes and sebocytes in the altered lipids which correlate with thermal function. In response to high fat feeding, wax diesters and ceramides accumulate, and triglycerides become more saturated. In contrast, in response to the dramatic loss of adipose tissue that accompanies restriction of the branched chain amino acid isoleucine, skin becomes more heat-permeable, resisting changes induced by Western diet feeding, with a signature of depleted signaling lipids. We propose that skin should be routinely included in physiological studies of lipid metabolism, given the size of the skin lipid reservoir and its adaptable functionality.

physiology↗

bioRxiv2024

irCLIP-RNP and Re-CLIP reveal patterns of dynamic protein associations on RNA

RNA binding proteins (RBPs) control varied processes, including RNA splicing, stability, transport, and translation1-3. Dysfunctional RNA-RBP interactions contribute to the pathogenesis of human disease1,4,5, however, characterizing the nature and dynamics of multiprotein assemblies on RNA has been challenging. To address this, non-isotopic ligation-based ultraviolet crosslinking immunoprecipitation6 was combined with mass spectrometry (irCLIP-RNP) to identify RNA-dependent associated proteins (RDAPs) co-bound to RNA with any RBP of interest. irCLIP-RNP defined landscapes of multimeric protein assemblies on RNA, uncovering previously unknown patterns of RBP-RNA associations, including cell-type-selective combinatorial relationships between RDAPs and primary RBPs. irCLIP-RNP also defined dynamic RDAP remodeling in response to epidermal growth factor (EGF), uncovering EGF-induced recruitment of UPF1 adjacent to HNRNPC to effect splicing surveillance of cell proliferation mRNAs. To identify the RNAs simultaneously co-bound by multiple studied RBPs, a sequential immunoprecipitation irCLIP (Re-CLIP) method was also developed. Re-CLIP confirmed binding relationships seen in irCLIP-RNP and detected simultaneous HNRNPC and UPF1 co-binding on RND3 and DDX3X mRNAs. irCLIP-RNP and Re-CLIP provide a framework to identify and characterize dynamic RNA-protein assemblies in living cells.

molecular biology↗

bioRxiv2018

PRESTO, a new tool for integrating large-scale -omics data and discovering disease-specific signatures

BackgroundCohesive visualization and interpretation of hyperdimensional, large-scale -omics data is an ongoing challenge, particularly for biologists and clinicians involved in current highly complex sequencing studies. Multivariate studies are often better suited towards non-linear network analysis than differential expression testing. Here, we present PRESTO, a PREdictive Stochastic neighbor embedding Tool for Omics, which allows unsupervised dimensionality reduction of multivariate data matrices with thousands of subjects or conditions. PRESTO is intuitively integrated into an interactive user interface that helps to visualize the multidimensional patterns in genome-wide transcriptomic data from basic science and clinical studies.\n\nResultsPRESTO was tested with multiple input omics platforms, including microarray and proteomics from both mouse and human clinical datasets. PRESTO can analyze up to tens of thousands of genes and shows no increase in processing time with a large number of samples or patients. In complex datasets, such as those with multiple time points, several patient groups, or diverse mouse strains, PRESTO outperformed conventional methods. Core co-expressed gene networks were intuitively grouped in clusters, or gates, after dimensionality reduction and remained consistent across users. Networks were identified and assigned to physiological and pathological functions that cannot be gleaned from conventional bioinformatics analyses. PRESTO detected gene networks from the natural variations among mouse macrophages and human blood leukocytes. We applied PRESTO to clinical transcriptomic and proteomic data from large patient cohorts and detected disease-defining signatures in antibody-mediated kidney transplant rejection, renal cell carcinoma, and relapsing acute myeloid leukemia (AML). In AML, PRESTO confirmed a previously described gene signature and found a new signature of 10 genes that is highly predictive of patient outcome.\n\nConclusionsPRESTO offers an important integration of powerful bioinformatics tools with an interactive user interface that increases data analysis accessibility beyond bioinformaticians and coders. Here, we show that PRESTO out performs conventional methods, such as DE analysis, in multi-dimensional datasets and can identify biologically relevant co-expression gene networks. In paired samples or time points, co-expression networks could be compared for insight into longitudinal regulatory mechanisms. Additionally, PRESTO identified disease-specific signatures in clinical datasets with highly significant diagnostic and prognostic potential.

bioinformatics↗