Biology subjects

Liu, T.

Publications and source records attributed to Liu, T..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

Ninjurin2 Regulates Vascular Smooth Muscle Cell Phenotypic Switching and Vascular Remodeling through Interacting with PDGF Receptor-β

Vascular smooth muscle cell (VSMC) phenotypic switching from a contractile to synthetic state plays a pivotal role in vascular remodeling. Although genome-wide association studies have linked NINJ2 (encode Ninjurin2) polymorphisms are associated with risk of atherosclerosis and related conditions like ischemic stroke and coronary artery disease, its functional role in regulating VSMC plasticity remains unexplored. Here, using Ninj2 knockout (Ninj2-/-) and smooth muscle-specific overexpressing (Ninj2smcTG) mice subjected to carotid artery ligation, we demonstrate that Ninjurin2 deficiency exacerbates injury-induced intimal hyperplasia, whereas its overexpression attenuates this pathological remodeling. Mechanistically, Ninjurin2 knockdown promoted PDGF-BB-mediated VSMC phenotypic switching, proliferation, and migration, while biochemical studies revealed that Ninjurin2 interacts with PDGFR{beta} to suppress FAK signaling. These findings identify Ninjurin2 as a novel regulator of VSMC phenotypic switching via the PDGFR{beta}/FAK axis, offering new mechanistic insights into vascular remodeling and potential therapeutic avenues for atherosclerosis.

pathology↗

bioRxiv2025

Genome-wide CRISPR screens identify PTGES3 as a novel AR modulator

The androgen receptor (AR) is a critical driver of prostate cancer (PCa). To study regulators of AR protein levels and oncogenic activity, we created the first live cell quantitative endogenous AR fluorescent reporters. Leveraging this novel AR reporter, we performed genome-scale CRISPRi flow cytometry sorting screens to systematically identify genes that modulate AR protein levels. We identified and validated known AR protein regulators including HOXB13 and GATA2 and also unexpected top hits including PTGES3, a poorly characterized gene in PCa. PTGES3 repression resulted in loss of AR protein, cell cycle arrest, and cell death in AR-driven PCa models. PTGES3 is not a commonly essential gene, and our data nominate it as a prime PCa therapeutic target. Clinically, analysis of PCa data demonstrate that PTGES3 expression is associated with AR-directed therapy resistance. Mechanistically, we show PTGES3 binds directly to AR, forms a protein complex with AR in the nucleus, regulates AR protein stability in vitro and in vivo and modulates AR function in the nucleus at AR target genes. PTGES3 represents a novel therapeutic target for overcoming known mechanisms of resistance to existing AR-directed therapies in PCa.

cancer biology↗

bioRxiv2025

PEDOT:PSS Microparticles for Extrudable and Bioencapsulating Conducting Granular Hydrogel Bioelectronics

Conducting hydrogels are promising materials for forming physiomimetic bioelectronic interfaces to monitor and stimulate biological activity. However, most developed materials are non-microporous and possess fixed shapes, both of which can limit the integration of cells and tissues with devices. In non-conducting biomaterials, materials fabrication strategies imparting microporosity and dynamic mechanical properties have been shown to support cell infiltration and support biointerfaces of various geometries. Specifically, granular hydrogels have enabled encapsulating, conformal, and injectable interfaces through these features. However, granular hydrogels remain largely unexplored as conducting biomaterials. We present methods for fabricating spherical, poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) hydrogel microparticles. When densely packed, these microparticles form a conducting granular hydrogel with microporosity as well as shear-thinning and self-healing dynamic mechanical properties. The PEDOT:PSS granular hydrogel can be extruded and maintain structure post-3D printing. Modulating microparticle PSS content achieves high granular hydrogel conductivity (137 S/m), and microparticles exhibit excellent cytocompatibility (>98% viability). Finally, we demonstrate utility as bioencapsulating electrodes for electrophysiological monitoring. These results highlight the functionality of our PEDOT:PSS conducting granular hydrogel, suggesting its potential as 3D printed bioencapsulating electrodes, 3D tissue engineering scaffolds for monitoring encapsulated cells, and injectable therapies for enhanced cell recruitment and tissue regeneration combined with electronic stimulation.

bioengineering↗

bioRxiv2025

ECCFP: a consecutive full pass based bioinformatic analysis for eccDNA identification using Nanopore sequencing data

It is commonly known that extrachromosomal circular DNA (eccDNA) has the potential as a molecular marker because of its close relationship with cancer progress and its prevalent existence in eukaryotic organisms. The mainstream technique of eccDNA detection is using high-throughput sequencing supported by bioinformatics analysis. Although these have various analysis pipelines for sequencing data, they are restricted by sequencing platforms or have shortcomings in accuracy and efficiency. To address these limitations, we design ECCFP, a bioinformatic analysis pipeline that detects eccDNAs amplified by rolling circle amplification (RCA) from long-read sequencing data and outputs eccDNA genomic coordinates and consensus sequences. This pipeline proposes a rigorous algorithm to retain all consecutive full passes derived from individual reads to obtain candidate eccDNAs, followed by systematic consolidation of candidate eccDNAs to detect unique eccDNAs. Using simulated datasets and experimental eccDNA sequencing datasets, we estimated ECCFP in several aspects and compared it with other existing pipelines. It exhibits a marked reduction in false positive rates compared with eccDNA_RCA_nanopore and superior sensitivity relative to CReSIL and FLED. Besides, inverse PCR and Sanger sequencing further validated the existence and accuracy of the position of detected eccDNAs by ECCFP. Collectively, ECCFP provides a more efficient choice for eccDNA detection from long-read sequencing data.

bioinformatics↗

bioRxiv2025

Chromosomal instability shapes the tumor microenvironment of esophageal adenocarcinoma via a cGAS-chemokine-myeloid axis

Chromosomal instability (CIN), a characteristic feature of esophageal adenocarcinoma (EAC), drives tumor aggressiveness and therapy resistance, presenting an intractable problem in cancer treatment. CIN leads to constitutive stimulation of the innate immune cGAS-STING pathway, which has been typically linked to anti-tumor immunity. However, despite the high CIN burden in EAC, the cGAS- STING pathway remains largely intact. To address this paradox, we developed novel esophageal cancer models, including a CIN-isogenic model, discovering myeloid-attracting chemokines - with the chemokine CXCL8 (IL-8) as a prominent hit - as conserved CIN-driven targets in EAC. Using high-resolution multiplexed immunofluorescence microscopy, we quantified the extent of ongoing cGAS-activating CIN in human EAC tumors by measuring cGAS-positive micronuclei in tumor cells, validated by orthogonal whole-genome sequencing-based CIN metrics. By coupling in situ CIN assessment with single-nucleus RNA sequencing and multiplex immunophenotypic profiling, we found tumor cell-intrinsic innate immune activation and intratumoral myeloid cell inflammation as phenotypic consequences of CIN in EAC. Additionally, we identified increased tumor cell-intrinsic CXCL8 expression in CINhigh EAC, accounting for the inflammatory tumor microenvironment. Using a novel signature of CIN, termed CINMN, which captures ongoing CIN-associated gene expression, we confirm poor patient outcomes in CINhigh tumors with signs of aberrantly rewired cGAS-STING pathway signaling. Together, our findings help explain the counterintuitive maintenance and expression of cGAS-STING pathway components in aggressive, CINhigh tumors and emphasize the need to understand the contribution of CIN to the shaping of a pro-tumor immune landscape. Therapeutic strategies aimed at disrupting the cGAS-driven inflammation axis may be instrumental in improving patient outcomes in this aggressive cancer.

cancer biology↗

bioRxiv2025

spRefine Denoises and Imputes Spatial Transcriptomics with a Reference-Free Framework Powered by Genomic Language Model

The analysis of spatial transcriptomics is hindered by high noise levels and missing gene measurements, challenges that are further compounded by the higher cost of spatial data compared to traditional single-cell data. To overcome this challenge, we introduce spRefine, a deep learning framework that leverages genomic language models to jointly denoise and impute spatial transcriptomic data. Our results demonstrate that spRefine yields more robust celland spot-level representations after denoising and imputation, substantially improving data integration. In addition, spRefine serves as a strong framework for model pre-training and the discovery of novel biological signals, as highlighted by multiple downstream applications across datasets of varying scales. Notably, spRefine enhances the accuracy of spatial ageing clock estimations and uncovers new aging-related relationships associated with key biological processes, such as neuronal function loss, which offers new insights for analyzing ageing effect with spatial transcriptomics.

genomics↗

bioRxiv2025

STPath: A Generative Foundation Model for Integrating Spatial Transcriptomics and Whole Slide Images

Spatial transcriptomics (ST) has shown remarkable promise in pathology applications, shedding light on the spatial organization of gene expression and its relationship to the tumor microenvironment. However, its clinical adoption remains constrained due to the limited scalability of current sequencing technologies. While recent methods attempt to infer ST from whole slide images (WSIs) using pretrained image encoders, they remain restricted by limited gene coverage, organ-specific training, and the need for dataset-specific fine-tuning. In light of this, we introduce STPath, a generative foundation model pretrained on a large-scale collection of WSIs paired with ST profiles. This extensive pretraining enables STPath to directly predict gene expression across 38,984 genes and 17 organs without requiring downstream fine-tuning. STPath integrates multiple data modalities, including histological images, gene expressions, organ type, and sequencing technology information, within a novel geometry-aware Transformer architecture. Unlike previous methods that directly map WSIs to gene expression, STPath is trained using a masked gene expression prediction objective guided by tailored noise schedules, effectively balancing between capturing gene-gene dependencies and performing high-quality predictions. We evaluate STPath across 6 tasks spanning 23 datasets and 14 biomarkers, including gene expression prediction, spot imputation, spatial clustering, biomarker prediction, gene mutation prediction, and survival prediction. These results demonstrate STPaths strong ability to infer spatially resolved gene expression and reveal crucial pathological structures within tissue samples, underscoring its promise for scalable ST-based pathology applications.

pathology↗

bioRxiv2025

Heme-NO dilates arteries via mobilization of NO moieties from a vascular intracellular NO store

Nitrosyl heme (heme-NO) has recently emerged as a surrogate signaling entity for nitric oxide (NO). However, questions remain about how heme-NO signals across the cell membrane. Herein, we test the hypothesis that heme-NO signals as a nitrodilator that vasodilates by mobilizing NO moiety from a nitrodilator-activated intracellular NO store (NANOS) in the vasculature. We identify a novel mechanism for glutathione-catalyzed formation of a model compound, alb-heme-NO, and determine glutathione (GSH) as a ligand in its structure. Heme-NO complexes with plasma proteins in blood and, as such, it is impermeable to red blood cells or the vascular wall. Alb-heme-NO-mediated vasodilation, both in vitro and in vivo, is attenuated by prior depletion of the NANOS and potentiated by NANOS supplementation. Incubation with alb-heme-NO induces efflux of NO moieties from arteries. Additionally, the role of nitrosyl hemoglobin (HbNO) in mediating NO bioactivity export from erythrocytes is challenged. In conclusion, heme-NO functions as an extracellular nitrodilator via activation of the intracellular NANOS.

physiology↗

bioRxiv2025

Rare-variant aggregate association analysis using imputed data is a powerful approach.

Imputation can cost-effectively generate genotypes for millions of variants. The power of performing rare variant aggregate association tests using imputed genotypes was evaluated. White Europeans from the UK Biobank with exome sequence and genotype array data were analyzed. Using the genotype type array data from the UK Biobank, imputation was performed using the HRC r1.1 (N=64,976 Haplotypes) and TOPMed r3 (N=267,194 haplotypes) reference panels. Simulations were used to compare the power of performing rare variant aggregate association analysis using sequence and imputed data. Additionally, the number of genes with >2 rare variants (missense, nonsense, splice site) was approximately the same for exome sequence and TOPMed imputed data, but HRC imputed data had [~]10% fewer genes. For the imputed data, using a less stringent R2 threshold (i.e., >0.3 vs. >0.8) led to greater power to detect aggregate associations due to additional rare variants included in the test. Exome sequence data provided the highest power for rare variant aggregate association testing, with TOPMed imputed variants usually having less than a 20% reduction in power. HRC imputed variants provided substantially less power. We also performed rare variant aggregate association analyses using UK Biobank phenotype, exome sequence data, and imputed variants for PCSK9 and low-density lipoprotein (N=159,904 study subjects) and APOC3 and triglyceride levels (N=160,036 study subjects). For these analyses, even when ultra-rare variants (minor allele frequency<0.001) were analyzed, significant aggregate associations could be detected for the exome sequence data and TOPMed and HRC imputed variants. Although there is a decrease in power for rare variant aggregate association tests when analyzing imputed variants compared to sequence data due to missing variants and uncertainty in genotypes, analysis of imputed data is a viable approach to detect rare variant aggregate associations when sequence data is unavailable.

bioinformatics↗

bioRxiv2025

Dynamic Pathway of Guanidine-III Riboswitch Folding Revealed by Single-Molecule FRET: Mg2+-Assisted Preorganization and Ligand-Induced Kinetic Trapping

Riboswitches are structured RNA elements that regulate gene expression by sensing and binding small molecules. The guanidine-III riboswitch, a critical bacterial regulator responding to guanidine toxicity, undergoes precise conformational changes that remain poorly characterized at a dynamic, mechanistic level. In this study, we employed single-molecule Forster Resonance Energy Transfer (smFRET) coupled with molecular dynamics (MD) simulations to delineate how the guanidine-III riboswitch transitions among distinct conformational states. We identify three principal states [-] an extended (E-state), a compacted prefolded intermediate (P-state), and a folded pseudoknot structure (F-state) [-] with rapid interconversion in the absence of ligand. Magnesium ions significantly stabilize intermediate states via a cooperative, preorganization mechanism, enhancing ligand binding efficiency. Binding of guanidine drastically suppresses the reverse transitions, kinetically trapping the riboswitch into its active folded state primarily through a conformational selection mechanism, with additional contributions from induced-fit dynamics. This work illuminates the unique dynamic pathway by which the guanidine-III riboswitch integrates ionic and ligand cues, ensuring precise gene regulatory responses in bacteria.

biophysics↗

bioRxiv2025

PepPCBench is a Comprehensive Benchmark for Protein-Peptide Complex Structure Prediction with AlphaFold3

Peptides mediate up to 40% of protein-protein interactions (PPIs), offering high specificity and the ability to target binding sites inaccessible to small molecules, making them promising candidates for drug development. Accurate modeling of protein-peptide complexes is crucial for understanding fundamental biological processes and for advancing peptide-based drug design. However, due to the high conformational flexibility of peptides, predicting their interactions with proteins remains a significant challenge. Recent advancements in artificial intelligence (AI), exemplified by all-atom protein folding neural networks (PFNNs) such as AlphaFold3 (AF3), have expanded predictive capabilities beyond proteins to encompass protein-peptide complexes. Nevertheless, existing evaluations of these methods are often limited in scope and lack systematic, multi-dimensional, and fair comparisons of PFNN performance in protein-peptide complex prediction. Here, we introduce PepPCBench, a comprehensive benchmark framework specifically developed to evaluate AF3s capabilities in predicting protein-peptide complexes. This study utilizes a carefully curated dataset named PepPCSet, which is excluded from the AF3s training or validation sets. This dataset includes 261 protein-peptide complexes with peptide lengths ranging from 5 to 30 residues. Our benchmark results indicate that AF3 outperforms other PFNNs in prediction accuracy and structural validation. However, its performance remains insufficient for practical peptide drug discovery, indicating room for improvement. It is expected that PepPCBench can provide some valuable insights into the enhancement of protein-peptide complex structure prediction and the development of peptide-based therapeutics. The dataset and pipeline protocols are available at https://github.com/zhaisilong/PepPCBench.

bioinformatics↗

bioRxiv2025

Manipulation of the Extracellular Vesicle Biogenesis Pathway in Paternal Somatic Cells Contributes to the Phenotypic Fate of the Next Generation

Human and animal studies have shown that risk factors for certain diseases are linked to our fathers physiological and psychological condition. So far, mainly in vitro evidence indicates extracellular vesicles (EVs) as one of the potential mediators of these paternal effects. In a full in vivo model system, we demonstrate that targeting the EV biogenesis pathway within somatic cells of the male Drosophila melanogaster reproductive tract induces sex-specific phenotypic changes in the progeny. These findings highlight the critical role of the EV pathway in paternal somatic cells in shaping the phenotypic destiny of the next generation and underscore the necessity for further investigations into the mechanisms of somatic to germline information transfer.

physiology↗

bioRxiv2025

INHBA promotes the progression of gastric cancer by activating MAPK signaling pathway via targeting ITGA6

Gastric cancer (GC) is one of the most common malignancies, ranking as the fifth most common cancer and the fourth leading cause among cancer related deaths worldwide. Upregulated INHBA expression in gastric cancer tissues compared to adjacent non-cancerous tissues was confirmed by immunohistochemistry and qRT-PCR analysis. This increased expression of INHBA was found to be significantly associated with the incidence of tumor lesion, lymph node metastasis and the progression to more advanced TNM stages in patients. Functional experiments showed that INHBA could promote the proliferation of GC cells, enhance migration and invasion in vitro, while simultaneously facilitating the inhibition of apoptosis. To test whether INHBA regulated the tumor growth in vivo, the animal studies were performed. The indicated that INHBA over-expression promoted the tumor growth, including weight and volume. Moreover, this study demonstrated through a series of experiments including RNA-seq, Co-IP, Co-IF, Western blot, and Rescue studies that INHBA promotes the progression of GC by targeting ITGA6 to regulate the MAPK signaling pathway. In summary, understanding the role of INHBA/ITGA6/MAPK in tumourigenesis could provide new insights into gastric cancer therapy and targeted inhibition of INHBA might be a potential therapeutic approach for GC treatment.

cancer biology↗

bioRxiv2025

Nuc3DMap delineates finer nucleosome-based three-dimensional chromatin architecture

Currently, there lacks a method to delineate finer nucleosome-based 3D chromatin architecture. In this study, we develop a novel computational method, nucleosome-based 3D chromatin map (Nuc3DMap), to integrate MNase-seq, Hi-C and Micro-C data. Nuc3DMap implements an ensembled LOESS-sparse Knight-Ruiz algorithm to efficiently balance nucleosome-based contact matrix and adapts a bottom-up approach to identify nano-scale chromatin organization including nucleosome-based topological domain (NucD), boundary (NucB), gap (NucG) as well as nucleosome-based chromatin interaction loci (NucIL) and chromatin loop (NucL). We evaluate Nuc3DMap on publicly available data in H1 and GM12878 cells and identify the distinct subtypes of functional NucBs and NucLs, respectively, by integrating them with more than a hundred of multi-omics modalities data. Interestingly, functional NucBs exert distinct nucleosome organizational features and different insulation capability; and Pol2-related NucLs implicated Pol2 as a noncanonical regulator in mediating gene looping and cell type specificity. Furthermore, our work systematically demonstrates the relationship between interaction intensity and transcriptional activity, unveiling an activation-like behavior of chromatin looping. Overall, Nuc3DMap represents a conceptual advancement in chromatin conformation analysis, offering a refined view of genome organization from the fundamental nucleosome level to higher-order chromatin structures, as well as serves as a foundational framework for advancing computational methods development in dissecting nano-scale 3D genome organization, enabling new discoveries and fostering innovation in chromatin organization modeling.

bioinformatics↗

bioRxiv2025

Genomic insights into polysaccharide substrate utilization and novel genera resource mining in macroalgal epiphytic bacteria

Marine macroalgae, among the fastest photosynthesizing organisms, play a crucial role in the ocean carbon cycle by converting fixed carbon dioxide into polysaccharides. Macroalgal epiphytic bacteria possessing specific polysaccharide utilization loci (PULs) have a generalized polysaccharide degradation potential that facilitates their growth and colonization. In this study, we conducted extensive research on their polysaccharide degradation potential. Through sampled and purified epiphytic bacteria and metagenomic analysis revealed a high prevalence of novel genera and species. Two novel genera, 1117T and 3-347T, were taxonomically characterized and conducted detailed functional analyses. The results demonstrated that these genera possess abundant PULs and strong capabilities for synthesizing secondary metabolites. Furthermore, their high relative abundance on macroalgal surfaces aligns with global ecological distribution patterns. These traits facilitate their colonization, growth, and environmental adaptation on macroalgal surfaces. We further performed in-depth annotation of a large number of PULs and CAZyme genes of macroalgal epiphytic bacteria. Potential polysaccharide substrates for their degradation can be predicted and focused on. Additionally, we conducted growth curve analyses by starch, xylan, {beta}-1,3-glucan, and carboxymethyl cellulose substrates to validate the genomic predictions. In summary, our findings demonstrate that macroalgal epiphytic bacteria possess significant potential for degrading algal polysaccharides. This capability may enhance their competitiveness and survival probability on macroalgal surfaces. These bacteria, originating from different sources and genera, possess similar PULs, which may result from horizontal gene transfer or evolutionary relationships. ImportanceMacroalgae are major primary producers in coastal areas and their carbon sequestration capacity per unit area far exceeds that of terrestrial forests. In this work, we extensively studied macroalgal epiphytic bacteria with polysaccharide degradation potential. We found that epiphytic bacteria from different macroalgal sources and genera share similar PULs to degrade the same polysaccharide, which may be the result of horizontal gene transfer or evolutionary relationships. Core taxa on the macroalgal surface have gradually evolved polysaccharide-degrading abilities of different marine macroalgae in order to expand their colonization and survival chances. We also identified a large number of uncultivated algal biosphere species and unreported new genera and species for expansion of macroalgal epiphytic bacteria studies. These studies have thus highlighted the important ecological and research value of macroalgal epiphytic bacteria, especially in influencing polysaccharide carbon storage and marine carbon cycling.

microbiology↗

bioRxiv2025

SpatialAgent: An Autonomous AI Agent for Spatial Biology

Advances in AI are transforming scientific discovery, yet spatial biology, a field that deciphers the molecular organization within tissues, remains constrained by labor-intensive workflows. Here, we present SpatialAgent, an autonomous AI agent for spatial biology research. SpatialAgent couples large language models with a Plan-Act-Conclude architecture, dynamic tool and skill retrieval, multimodal interpretation, and verification modules that audit generated claims. It supports the full discovery loop, from gene-panel design and multimodal annotation to trajectory inference, cell-cell communication analysis, imputation, and hypothesis generation. Across human and mouse brain, heart, tonsil, colon, and prostate datasets, SpatialAgent outperformed established computational baselines and matched or surpassed expert scientists in key tasks. In open-ended case studies, it recovered known tissue organization and generated spatially grounded hypotheses. In a prospective mouse prostate cancer Xenium study, it designed a compact 100-gene add-on panel that profiled 4.2 million cells across 21 samples, improved cell-type and malignant-state prediction, and captured spatially structured tumor and microenvironment programs. SpatialAgent establishes a framework for autonomous and collaborative discovery in spatial biology.

bioinformatics↗

bioRxiv2025

Biosynthesis of modular signaling molecules requires functional diversification of carboxylesterases in Pristionchus pacificus

The model nematode Pristionchus pacificus produces four types of complex ascaroside pheromones named UBAS, DASC, NPAR, and PASC. However, the exact biosynthetic pathways of these modular signaling molecules remain enigmatic. We have previously identified a carboxylesterase Ppa-UAR-1 for the biosynthesis of UBAS, enabling the attachment of ureidoisobutyric acid at the 4-position of simple ascarosides. Here, we report three new carboxylesterases Ppa-UAR-5, Ppa-UAR-6 and Ppa-UAR-12 from P. pacificus. Ppa-UAR-5 functions downstream of Ppa-UAR-1 to furnish the biosynthesis of ubas#1 and ubas#2, whereas Ppa-UAR-12 specifically links two ascr#1 at the 4-position to synthesize dasc#1. Finally, Ppa-UAR-6 is essential for the biosynthesis of npar#1-3 and part#9. The expression patterns of Ppa-uar-6 and Ppa-uar-12 in the intestinal and epidermal cells suggest pheromone biosynthesis to be restricted to specific tissues. These findings indicate that the expansion and functional diversification of carboxylesterases plays a crucial role in the evolution of complex pheromones in nematodes. SIGNIFICANCEOur study identified three new carboxylesterase genes (Ppa-uar-5, Ppa-uar-12 and Ppa-uar-6) from P. pacificus. The encoded enzymes separately regulated the biosynthesis of three types of modular pheromones (UBAS, DASC, and NPAR-types) in worms intestinal cells and exhibited extremely high substrate-specificity. For example, we verified that Ppa-UAR-12 specifically linked one ascr#1 to the 4-position of another ascr#1 to finally furnish the biosynthesis of ascaroside dimer dasc#1. These new discoveries largely clarify the delicate biosynthetic mechanisms of how diversification of carboxylesterases functions in P. pacificus to build up enormous complexity of modular signaling molecules. Such a biosynthetic mechanism of nematode pheromones might be widely conserved in the phylum Nematoda.

biochemistry↗

bioRxiv2025

Optoretinography reveals rapid rod photoreceptor movement upon photoisomerization

Rod photoreceptors are essential for vision under dim light conditions. The onset of rod-mediated vision is marked by the isomerization of rhodopsin. Here we demonstrate that human and rodent rods undergo a minute and rapid contraction of their outer segments immediately upon photoisomerization. The contraction is explained as an electro-mechanical manifestation of the rod early receptor potential generated in the disk membranes, which is challenging to access in electrophysiology. The bleach-strength dependence of the contraction was accounted by a voltage-dependent membrane tension model, developed earlier to explain a similar behavior in cones. The in vivo optical imaging of light-evoked electrical activity in rodent rods was facilitated by an ultrahigh-resolution point-scan optical coherence tomography (OCT) system coupled with unsupervised learning, while in humans, an adaptive optics line-scan OCT facilitated high-speed recordings in individual rods. The non-invasive in vivo optical imaging of rhodopsin activation will have a significant impact on diagnostics and treatment of retinal disease, especially given the vulnerability of rods in inherited and age-related macular degeneration.

bioengineering↗