Biology subjects

Navarro, R. S.

Publications and source records attributed to Navarro, R. S..

3 recordsLinked to original sources

bioRxiv2026

Lipid Network Crosslinked Hydrogels: Controlling MaterialDynamics Across Multiple Length Scales Through Lipid Movement

Control over network dynamics at different length scales is a feature of natural materials challenging to replicate in synthetic hydrogels. Hydrogel viscoelasticity is commonly controlled by tuning the kinetics of reversible crosslinks; however, this strategy inherently links the resulting macroscale and nanoscale dynamics of the individual network components. Taking inspiration from biological materials that feature lipids as structural elements, we introduce Lipid Network Crosslinked (LINC) hydrogels that exploit the mobility of individual lipids within self-assembled liposomes as covalent, network-crosslinking points. These mobile, covalent crosslinks increase hydrogel stress relaxation rates over 20-fold compared to polymer-only hydrogels with equivalent crosslinking chemistries and stiffnesses. We demonstrate that liposome design parameters, including degree of surface functionalization and tail saturation, provide a means to independently control the macroscale storage moduli and stress relaxation behavior. Finally, as an application where control over network dynamics at different length scales is critical, we placed cell-adhesive ligands onto more mobile or less mobile network elements. Human neural progenitor cells cultured within LINC hydrogels of identical macroscale viscoelasticity significantly altered their phenotype in response to nanoscale ligand dynamics. These results establish LINC hydrogels as biomimetic materials that leverage nanoscale lipid mobility within a macroscale polymeric network to control dynamics at multiple length scales.

bioengineering↗

bioRxiv2026

Hydrogel-imposed boundary conditions guide single-lumen neuroepithelial morphogenesis

Three-dimensional (3D) stem cell-based cultures have emerged as promising in vitro model systems for studying human neurodevelopment. Current neural organoid protocols lack well-defined extracellular matrix (ECM) signaling and are limited by the formation of irregular tissue morphologies with multiple organizing centers, in contrast to the single neuroepithelial structure that emerges during embryonic development. This variability limits inter-organoid reproducibility and constrains their utility for modeling early developmental processes. To overcome these limitations, we leverage a materials-based approach to impose dynamic boundary conditions that extrinsically guide the self-organization of human induced pluripotent stem cells (iPSCs). Specifically, we develop a family of hyaluronic acid-elastin-like protein (HELP) hydrogels crosslinked with dynamic covalent bonds that recapitulate key biochemical and biophysical properties of the developing human neural ECM. Within these HELP hydrogels, iPSCs robustly self-organize from a single cell into complex neuroepithelial tissues with a single lumen. By tuning the boundary conditions imposed by the hydrogel, we identify matrix stress relaxation rate and tensional homeostasis as key regulators of single-lumen rosette formation and maintenance. With this hydrogel-enabled system, we identify phenotypic abnormalities in an early neurodevelopmental model of 22q11.2 deletion syndrome. Ultimately, our tunable engineered hydrogel supports the initiation of single-cell derived 3D neuroepithelial tissues, enables investigation into how matrix-imposed boundary conditions guide developmental morphogenesis, and establishes a reproducible platform for disease modeling.

bioengineering↗

bioRxiv2025

epsSMASH uncovers exopolysaccharide biosynthetic gene clusters in environmental and human microbiomes

Biofilms represent the default mode of bacterial life in natural and built environments, with extracellular polysaccharides (exoPS) serving as essential structural and functional components of the biofilm matrix. Despite their importance, exoPS production in these environments is largely unknown. Here we present epsSMASH, a bioinformatic tool and web service for predicting known and novel exoPS biosynthetic gene clusters (BGCs) in bacterial genomes. Benchmarking showed that comprehensive detection of exoPS gene clusters requires highly contiguous high-quality genome assemblies. We applied epsSMASH to high-quality bacterial genome catalogues representing four major ecosystems: Human gut, soil, ocean and activated sludge from wastewater treatment systems. In all catalogues, epsSMASH identified exoPS BGCs in most genomes (52.8-85.4%), with a median of 1-2 exoPS BGCs per genome. The number of exoPS BGC per genome was highly variable, with some taxa containing up to 19 distinct exoPS BGCs. Pel BGCs were abundant in human gut, ocean and activated sludge microbiomes, and were detected in 14 different phyla, making it the most phylogenetically widespread BGC in these environments. The vast majority (62-96%) of detected exoPS BGCs were uncharacterised. By constructing gene cluster families from uncharacterised systems, we identified novel and phylogenetically widespread exoPS BGCs. We investigated a novel exoPS gene cluster from the activated sludge microbiome and showed that it is conserved in most genera within the order Sphingomonadales. Our results highlight the remarkable number of uncharacterised exoPS gene clusters in environmental microbiomes and establish epsSMASH as an effective tool for identifying and classifying novel exoPS systems.

bioinformatics↗