Biology subjects

Shen, K.

Publications and source records attributed to Shen, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Genomic and environmental determinants of circular single-stranded DNA production in engineered E. coli

Single-stranded DNA with hundreds to thousands of bases is a critical reagent in biotechnology. While traditional chemical synthesis is not suitable for efficient production of such long oligonucleotides, M13 bacteriophage offers a scalable pathway towards custom, long, single-stranded DNA production. However, conventional helper plasmid-phagemid systems suffer from batch-to-batch variability and off-target packaging. To address these limitations, we previously engineered eScaf, an E. coli strain with the M13 genome stably integrated into its chromosome. eScaf produces circular, single-stranded DNA with high purity, but yields of only 100 and 200 g of DNA per liter of culture, too low for cost-effective scale-up. Here, we systematically investigate the genomic and environmental determinants of cssDNA yield in eScaf, revealing that cssDNA yield depends on both the number and chromosomal loci of integrated M13 genomes. Combining these insights with optimized media, we achieve ~4 mg/L of cssDNA in shake flasks, a 40-fold improvement. We also evaluate fed-batch bioreactor feeding strategies for cssDNA production using eScaf. Our new strain, eScaf-IS3, enables cost-effective production of cssDNA for high-throughput therapeutic screening, operon-length knock-in donor production, and large-scale DNA origami assembly.

bioengineering↗

bioRxiv2026

Bounded ecological memory in coral reefs: divergent demographic pathways under recurrent heatwaves and collapse under extreme thermal stress

Anthropogenic warming exposes coral reefs to recurrent marine heatwaves (MHWs), yet responses to comparable thermal stress remain highly variable. A central challenge is determining whether reduced bleaching reflects acclimatization-like persistence of existing colonies or mortality-driven filtering that produces demographically depleted assemblages. Using colony-level surveys across the Florida Reef Tract (2014-2023), we show bleaching sensitivity declined from 2014 through 2022, consistent with ecological memory. A spatial matched-event framework integrating bleaching severity and adult colony density resolved these reduced-bleaching outcomes into two distinct pathways: demographic persistence (stable/increasing density) and mortality-filtered tolerance (declining density). Persistence pathways were maintained under predictable exposure regimes characterized by lower interannual thermal variability. This persistence was driven by weedy life-history taxa (e.g., Porites spp.) replacing historical framework builders, indicating stability reflects ecological reassembly rather than uniform increases in thermal tolerance. Under the unprecedented extremes of the 2023 MHW, this acclimatization-like buffering broke down, causing widespread sensitization and collapse of previously persistent networks. These results support a bounded ecological memory framework; prior exposure reduces bleaching sensitivity under predictable thermal regimes but fails under extreme heat stress. Consequently, modern refugia are best defined by adult standing stock retention representing systems undergoing selective ecological reassembly rather than full functional recovery.

ecology↗

bioRxiv2026

Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning

Transcription factors (TFs) regulate gene expression through specific interactions with genomic DNA. While TF binding motifs from public databases describe sequence preferences, quantifying genome-wide affinity (Kd) is highly desirable for a more accurate thermodynamic description. Here, we report ivtFOODIE (in vitro FOOtprinting with DeamInasE), an assay that leverages deaminase-mediated cytosine-to-uracil conversion to measure Kd values for a given TF across accessible genomic regions from human cells. By pre-training on TF binding sites from JASPAR and fine-tuning with our ivtFOODIE data from 46 TFs representing 13 different DNA-binding domains (DBDs), we developed Seq2Kd, a deep learning model capable of predicting a TFs absolute binding affinity on DNA sequences. Seq2Kd enables de novo motif discovery of [~]500 previously uncharacterized human TFs and reveals the effects of genetic variation both in TF-coding regions and DNA-binding sites on gene expression and disease susceptibility. By correlating predicted affinity changes with the sign and magnitude of expression quantitative trait locus (eQTL) effects, we stratified TFs into activator-like and repressor-like groups. Compared to clinically benign variants, pathogenic single-nucleotide variants (SNVs) within regulatory and protein-coding regions show significantly larger predicted shifts in Kd. We provide an interactive web portal, the ENcyclopedia of Transcription-factor Interactions with Regulatory Elements (ENTIRE), which integrates the Seq2Kd model with the ivtFOODIE dataset. This resource offers thermodynamic prediction for TF-DNA interactions for functional genomics and human disease.

biophysics↗

bioRxiv2026

Deep Learning of High-throughput Transcription Factor-DNA Binding Affinity Data: Quantitative Comparison with Pairwise-Additive Models

Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences. Widely used models of TF-DNA binding, such as position weight matrices (PWMs) and position-specific affinity matrices (PSAMs), assume binding free energy is the sum of independent base contributions. However, there is ample evidence that non-additive effects significantly influence TF binding. Here, we utilize data from a high-throughput in vitro assay (ivtFOODIE) to generate genome-scale TF-DNA dissociation constants (Kd) and systematically evaluate sequence-to-affinity models of increasing complexity. We demonstrate that pairwise additive models exhibit systematic deviations from the measured affinity landscapes. Models incorporating adjacent dinucleotide interactions and deep learning architectures achieve markedly improved agreement with experimental Kd values. The magnitude of this non-pairwise-additivity depends strongly on the TF family. In silico mutation screening reveals widespread, TF-specific long-range interposition dependencies, highlighting the role of energetic coupling across distant positions in target recognition. These results provide a quantitative framework for comparing non-pairwise-additive energetic effects across diverse TFs.

biophysics↗

bioRxiv2026

Therapeutic targeting of fibrin-microglia interactions ameliorates Alzheimer disease-related hyperexcitability and brain network dysfunction

Brain network dysfunction--including hyperexcitability, altered oscillations, and sleep disruption--is prominent in Alzheimers disease (AD), but the contribution of vascular-neuroimmune processes to these alterations remains unclear. Here, we blocked the pro-inflammatory interaction of the blood protein fibrin with microglia using genetic (Fgg{gamma}390-396A mice) and antibody-based (5B8 and THN392) strategies to test its role in AD-related network dysfunction. The 5xFAD model of AD exhibited network hyperexcitability associated with oscillatory slowing, sleep states, and disrupted sleep-circadian rhythms. These deficits were largely attenuated by blocking fibrin-microglia interactions in 5xFAD;Fgg{gamma}390-396A mice. Notably, pharmacological interventions after disease onset with both anti-fibrin antibodies similarly attenuated these AD-related network deficits and behavioral abnormalities. We conclude that vascular-neuroimmune processes driven by fibrin-microglia interactions promote AD-related network dysfunction and that targeting the fibrin-microglia axis--currently under clinical evaluation with the humanized antibody THN391-- represents a promising therapeutic strategy for AD. There is a companion manuscript submitted to bioRxiv (Yan et al., 2026).110 HIGHLIGHTSO_LIFibrin promotes AD-related network hyperexcitability and oscillatory slowing in 5xFAD mice C_LIO_LIFibrin promotes AD-related disruption of sleep and circadian rhythms in 5xFAD mice C_LIO_LIGenetic blocking of fibrin-microglia interactions rescues AD-related brain network dysfunction C_LIO_LIAnti-fibrin antibodies (5B8 and THN392) show acute and chronic therapeutic benefit C_LI

neuroscience↗

bioRxiv2026

Interactions between age and sex in multiscale entropy and spectral power changes across the lifespan

Multiscale entropy (MSE) changes in relation to age, whereby aging is associated with an increasing bias towards fine scale entropy. This change is thought to represent a shift toward localized information processing in the brain as we age. However, this relationship has not been tested in large sample sizes alongside other demographic factors and cognitive behaviours. This study aimed to validate previously reported effects of aging on MSE in a large open access database (Cambridge Centre for Ageing and Neuroscience, N=587) and expand the findings to include an investigation of the effects of sex and a variety of cognitive behaviours. MSE curves and power spectrum densities (PSD) were calculated for each region of interest from the magnetoencephalography data. Multivariate partial least squares analyses were used to assess the relationship between MSE or PSD and 5 behavioural / demographic factors including: age, sex, fluid intelligence, visual short-term memory and a generalized measure of cognitive function. Age was associated with increased fine scale and decreased coarse scale entropy, as well as complementary spectral changes, including slowing of peak alpha rhythms, increased beta-band activity, and reduced gamma-band activity, which replicates prior MSE and PSD findings. In both domains, these age-related patterns differentiated based on sex with advancing age. Importantly, the unique effects of sex diverged between MSE and PSD. This result indicates that entropy-based measures can isolate aspects of temporal organization that are not clearly summarized by spectral structure alone.

neuroscience↗

bioRxiv2026

Reduced Complex III assembly dampens host inflammation as an adaptive response to viral infection

Mitochondrial electron transport and oxidative respiration are required for immunity and host tolerance. How the ETC contributes to viral infections - where a proinflammatory anti-viral response needs to be finely balanced with host-protective anti-inflammatory mechanisms - remains unclear. Here, we demonstrate that following infection by H1N1 influenza virus, murine macrophages reduce Complex III levels by downregulating the early CIII assembly factor called the COMB complex. To determine the effect of CIII suppression, we utilized Brawnin (Br or UQCC6) knockout mice, which lack COMB complexes and have reduced Complex III. Following H1N1 infection, Br KO bone marrow-derived macrophages (BMDMs) had reduced inflammation due to reduced CIII Qo site ROS. Br KO mice infected with a non-lethal dose of H1N1 had reduced lung immune pathology, viral burden and enhanced recovery following H1N1 infection. Single-cell RNAseq analysis revealed that H1N1-infected Br KO lungs had reduced abundance of hyper-inflammatory monocytes known to cause severe respiratory disease and reduced monocyte chemotaxis. Our study demonstrates that ETC Complex III suppression is part of an innate immune response to viral infection, and is a potential strategy to control host inflammation in acute respiratory viral infections.

immunology↗

bioRxiv2026

LONP-1 deficiency causes dysregulated protein synthesis within mitochondria that is restored by mitoribosomal mutations

Mitochondrial homeostasis is maintained by multiple molecular chaperones and proteases located within the organelle. The mitochondrial matrix-localized protease LONP-1 degrades oxidatively damaged or misfolded proteins. Importantly, LONP-1 also regulates mitochondrial DNA replication. Here, we show that mutations in C. elegans that impair LONP-1 function cause dysregulation of mitochondrial DNA replication, mitochondrial RNA transcription and protein synthesis within the mitochondrial matrix. LONP-1 deficient worms had reduced levels of oxidative phosphorylation proteins despite increased mtDNA-encoded protein synthesis. Via a forward genetic screen, we identified three mutations that restored mitochondrial function and the rate of development in lonp-1 mutants to levels comparable to those in wildtype worms. Interestingly, all three suppressor mutations were found in genes encoding mitochondrial ribosome proteins. A point mutation in the mitochondrial ribosome protein MRPS-38 restored oxidative phosphorylation in lonp-1 mutant worms. Combined, our results suggest that LONP-1 regulates mitochondrial protein synthesis and that the suppressor mutations within MRPS-38 or MRPS-15 enhance oxidative phosphorylation complex assembly by slowing translation.

cell biology↗

bioRxiv2026

Glucokinase links metabolism and lineage plasticity in neuroendocrine prostate cancer via interaction with AKT1

Cancer cells frequently rewire their metabolism to sustain growth and survival under stress. Despite the critical role of metabolic adaptation in tumorigenesis, how specific metabolic enzymes regulate lineage plasticity remains unclear. Here, through FDG-PET imaging and transcriptomic analyses, we reveal markedly elevated glucose uptake in neuroendocrine prostate cancer (NEPC) and identify glucokinase (GCK) as a MYCN-induced metabolic enzyme. Beyond its metabolic role, GCK is indispensable for maintaining the neuroendocrine lineage of prostate cancer cells by establishing a functional circuit with AKT1 through reciprocal regulation--AKT1 binds and phosphorylates GCK at S373, whereas GCK phosphorylates AKT1 at S473. Pharmacological disruption of this AKT1-GCK axis suppresses tumor growth in NEPC mouse models and patient-derived xenografts. Altogether, our findings uncover both the metabolic and noncanonical kinase functions of GCK and establish the AKT1-GCK axis as a key link between metabolic reprogramming and neuroendocrine lineage transition in prostate cancer.

cancer biology↗

bioRxiv2025

An AGO2 adaptor expands the functional and evolutionary reach of microRNA targeting

Current models of microRNA (miRNA) silencing posit that RNA-sequence rules are sufficient for canonical targeting of mRNAs by Argonaute 2 (AGO2), the central protein of the miRNA-induced silencing complex (miRISC). Using chimeric eCLIP in CRISPR-edited LIMD1+/+, LIMD1+/-, and LIMD1-/- human small airway epithelial cells (hSAECs), we reveal a transcriptome-wide dependency on LIMD1, an AGO2 adaptor, for effective miRNA targeting and repression. In LIMD1-deficient cells, miRNA loading is uncoupled from productive targeting: despite increased AGO2-miRNA interactions, complexes engage fewer transcripts and sites, reducing occupancy and more than halving both the breadth and depth of targeting. We also observe altered AGO2 positional footprints across targets in LIMD1-deficient cells. LIMD1 dependence is most pronounced at defined RNA contexts: weak (GC-poor) seed pairings, interactions involving evolutionarily young miRNAs or sites that nonetheless form thermodynamically stable duplexes, with these losses particularly enriched in coding sequences of rapidly evolving C2H2-zinc-finger genes. Even within canonical seed repertoires of individual AGO2-miRNAs, LIMD1 is most critical at poorly conserved sites, indicating that LIMD1 broadens miRNA regulation beyond ancient, deeply conserved targets. In culture, LIMD1 deficiency de-represses oncogenic proteins that, in vivo, inversely correlate with LIMD1 levels in normal lung and adenocarcinoma, where LIMD1 is characteristically reduced, and whose dysregulation predicts poor survival. Thus, LIMD1 emerges as a key determinant of miRISC architecture, targeting, and potency, challenging RNA-centric models of miRNA function and exemplifying how adaptor proteins diversify post-transcriptional regulation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=180 HEIGHT=200 SRC="FIGDIR/small/680889v2_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@e0f4f5org.highwire.dtl.DTLVardef@f23fd9org.highwire.dtl.DTLVardef@3de3f2org.highwire.dtl.DTLVardef@1404af2_HPS_FORMAT_FIGEXP M_FIG LIMD1 defines the scope of miRNA-mediated targeting and repression O_LIAGO2-chimeric eCLIP in CRISPR-edited human small airway epithelial cells (hSAECs) shows LIMD1 is required for productive AGO2-miRNA engagement transcriptome-wide. C_LIO_LILIMD1 deficiency reduces the AGO2-miRNA:targetome. Each AGO2-miRNA binds fewer targets, with lower occupancy per site and per transcript and fewer global silencing events. C_LIO_LILIMD1 dependence is strongest for GC-poor seed-sites, less conserved miRNAs and sites, and thermodynamically stronger duplexes. C_LIO_LIDosage-dependent effects of LIMD1 deficiency are broadly observed. C_LIO_LITarget-mRNA decay and translational repression are reduced in LIMD1-deficient hSAECs, increasing protein output. C_LIO_LIIn vivo, LIMD1 LOH-associated deficiency is prevalent and typically clonal in NSCLC. LIMD1 expression inversely correlates with oncogene levels in normal lung and adenocarcinoma, and target dysregulation predicts poor survival. C_LI C_FIG

molecular biology↗

bioRxiv2025

Segmentation Matters: Recognizing the Cell Segmentation Challenge in Spatial Transcriptomics

Probe-based in situ hybridization spatial transcriptomics has emerged as a state-of-the-art for neuroscience research. Accurate segmentation of neurons and non-neuronal cells, a critical step for downstream analysis, remains a big challenge. Using human sensory ganglia neurons as an example, we systematically explore this problem. We evaluated multiple automatic segmentation approaches using quantitative performance metrics and downstream results. We show that careful parameter tuning is essential for achieving accurate segmentation; however, even with optimized parameters, different models still yield distinct classes of errors. To mitigate these errors, we propose a manual quality check, which can validate and refine automated segmentation results. As a future direction, integrating multi-modal imaging data with tailored neural networks may further improve segmentation accuracy. In summary, our results argue that each automated segmentation method has distinct strengths, weaknesses, and characteristic error patterns; and that a manual review is necessary.

neuroscience↗

bioRxiv2025

Using DNA origami to study nanoscale organization of plasma membranes

Plasma membrane (PM) lipids and proteins are organized into nanoscale regions called nanodomains, which regulate essential cellular processes by controlling local membrane organization. Despite advances in super-resolution microscopy and single particle tracking, the small size and temporal instability of nanodomains make them difficult to study in living cells. To overcome these challenges, we built fluorescent DNA origami probes that insert into the PM via lipid anchors displayed on the cell. The number and spatial distribution of anchors between the origami and the cell surface were precisely defined by the origami, enabling nanometer-scale sampling of the cell surface. Inserting these DNA origami particles into the membrane with lipid anchors allowed them to passively diffuse across the membrane, and we tracked their movement using single particle tracking to survey the PM landscape. By varying the number and spatial arrangement of lipid anchors connecting the DNA origami to the cell surface, we showed that immobilization of DNA origami particles requires simultaneous interactions with multiple nanodomains. Disruption of the actin cytoskeleton reduced immobilization, confirming its role in supporting nanodomain stability. Moreover, transient mechanical stretching of cells led to reversible increases in DNA origami mobility, indicating that mechanical force can reversibly regulate PM nanodomain organization. Altogether, we present a novel membrane-integrated DNA origami approach that provides mechanistic insights into PM nanodomain architecture and dynamics in living cells.

cell biology↗

bioRxiv2025

Young and old adult brains experience opposite effects of acute sleep restriction on the functional connectivity network

Chronic, long-term sleep loss is detrimental to brain health and cognitive ability. However, older adults are affected differently by acute, short-term loss of sleep than young and middle-aged adults. Older adults are more resilient to the effects of acute sleep loss and, depending on the cognitive domain, may be completely unaffected while younger adults suffer. To elucidate the brain network responses to sleep loss underlying these cognitive differences between age groups, we investigated the static and dynamic functional connectivity effects of sleep restriction (sleep limited to 3 hours) and how these effects differ between younger adults (20-30 years) and older adults (65-75 years). We found a functional connectivity subnetwork that was primarily strengthened in younger adults after sleep restriction but weakened in older adults after sleep restriction. Similar crossover interactions were consistently observed in further analyses of functional connectivity degree, modularity, and dynamic functional connectivity state fractional occupancy. Our findings demonstrate that the effect of sleep restriction on older adults is fundamentally different from younger adults. These results most strongly support the compensation theory of aging, which predicts a fundamental shift in the effects of sleep loss, rather than a mere dampening of the sleep benefits experienced by younger adults.

neuroscience↗

bioRxiv2025

Comparative transcriptomics of lateral hypothalamic cell types reveals conserved growth hormone-tachykinin dynamics in feeding

The lateral hypothalamus (LH) is a highly heterogeneous brain region regulating hunger and motivated behaviors. In zebrafish, the LH shows distinct neural activity across hunger, feeding, and satiety states. However, the functional and evolutionary conservation of relevant neural circuits remain unclear. Using integrative transcriptomics of zebrafish and mouse LH, we identify conserved cellular clusters with shared molecular markers, particularly within GABAergic neurons. We highlight a conserved GABAergic population expressing tachykinin and growth hormone receptors, which is responsive to food cues and modulated by hunger and feeding states. This cluster may mediate acute appetite-enhancing effects of growth hormone. In both species, feeding elevates growth hormone receptor and tachykinin expression and activates these neurons, while human growth hormone increases their activity and food intake in zebrafish. These findings suggest a conserved neural mechanism by which metabolic hormones influence feeding behavior. Our comparative LH atlas highlights the evolutionary biology of appetite regulation and the integration of hormonal and neural signals driving energy homeostasis.

neuroscience↗

bioRxiv2025

Rag GTPases Suppress Renal Cystic Disease by Inhibiting TFEB Independently of mTORC1

Aberrant mTORC1 activation in renal tubular epithelial cells (rTECs) is implicated as a critical driver of renal cystic diseases (RCDs), including autosomal dominant polycystic kidney disease (ADPKD) and tuberous sclerosis (TSC), yet its precise role remains unclear. Rag GTPases recruit mTORC1 to lysosomes, its intracellular activation site. Unexpectedly, we found that deleting RagA/B in rTECs, despite inhibiting mTORC1, triggers renal cystogenesis and kidney failure. We identify TFEB as the key driver of cystogenesis downstream of RagA/B loss and show that Rag GTPases, rather than mTORC1, are the primary suppressors of TFEB in vivo. We further highlight increased nuclear TFEB as a shared feature of several RCD models, whereas differences in mTORC1 activity may explain the variable efficacy of mTORC1 inhibitors. Finally, we provide evidence that nuclear TFEB, rather than mTORC1 activation, is a more consistent biomarker of cyst-lining epithelial cells in ADPKD. Overall, these findings challenge the prevailing view that mTORC1 hyperactivation is required for renal cystogenesis, which has important translational implications. TeaserA serendipitous finding uncovers the Rag GTPases as strong suppressors of renal cystogenesis with important disease implications.

cell biology↗

bioRxiv2025

ERM proteins regulate the shape and number of Endoplasmic Reticulum-Plasma Membrane Junctions in neurons

Endoplasmic Reticulum (ER) - Plasma Membrane (PM) Junctions (EPJs) are specialized contact sites between ER membrane and the inner leaflet of PM. These junctions are critical for lipid exchange and Ca2+ signaling. In excitable cells like neurons and muscle, EPJs further modulate membrane excitability by regulating Ca2+ homeostasis. The mechanisms controlling EPJ abundance and morphology remain poorly understood. Using in vivo fluorescence imaging and electron microscopy of C. elegans neurons, we showed that EPJs form discrete, patch-like structures distributed across the soma. Through a forward genetics screen, we identified two conserved ERM (Ezrin-Radixin-Moesin) proteins, FRM-4 and FRM-1, as key regulators of EPJ shape and abundance. Both proteins localize to EPJs and exhibit liquid-liquid phase separation properties (LLPS). in vitro, purified FRM-4 binds to FRM-1, and together bundle filamentous actin. However, their presence in LLPS condensates and actin-bundling activity are mutually exclusive. In vivo, F-actin cables surround--but do not penetrate--EPJs, where FRM proteins are enriched as phase-separated condensates. Loss of FRM-4, FRM-1, or disruption of F-actin led to increased mobility of EPJs that fused into fewer but enlarged junctions. Together, our findings demonstrate that FRM-4 and FRM-1 control EPJ morphology by organizing peri-junctional F-actin networks, thereby restricting EPJ mobility and fusion.

cell biology↗

bioRxiv2025

Super Recombinator (SuRe): An in vivo recombination system for scalable and efficient transgene assembly at a single genomic locus

The capacity to engineer organisms with multiple transgenic components is crucial to synthetic biology and basic biology research. For the former field, transgenic organisms allow the creation of novel biological functions; for the latter, such organisms provide potent means of dissecting complex biological pathways. However, the size limitations of a single transgenesis event and challenges associated with the assembly of multiple DNA fragments hinder the efficient integration of multiple transgenes. To overcome these hurdles, here we introduce a building block for synthetic design termed an integrated genetic array (IGA), which incorporates all genetic components into a single locus to prevent their separation during genetic manipulations. Since the natural recombination rate for genes located in the same locus is near zero, to construct IGAs we developed the Super Recombinator (SuRe) system, which uses CRISPR/Cas9, alone or in combination with site-specific serine recombinases, for in vivo transgene recombination at a single genomic locus. SuRe effectively doubles the number of elements assembled in each recombination round, exponentially accelerating IGA construction. By preventing the separation of transgenic elements, SuRe greatly reduces screening burdens, as validated here through studies of Drosophila melanogaster and Caenorhabditis elegans. To optimize SuRe, we compared CRISPR/Cas9-induced homology-directed recombination to site-specific recombination using various serine recombinases. Optimized versions of SuRe achieved efficiency and fidelity values near their theoretical maxima and allowed the generation of recombinant products up to 4.2 Mbp in size in Drosophila. Using SuRe, we created fruit flies with 12 transgenic elements for fluorescence voltage imaging of neural activity in precisely defined cell-types. Mathematical modeling of the scalability of SuRe to large transgene assemblies showed that integration times and gene assembly workloads respectively scale logarithmically and linearly with the number of transgenes, both major improvements over conventional approaches. Overall, SuRe enables the efficient integration of multiple genes at individual loci, up to the chromosomal scale.

synthetic biology↗

bioRxiv2025

A dendritic guidance receptor functions in both ligand dependent and independent modes

The formation of an appropriately shaped dendritic arbor is critical for a neuron to receive information. Dendritic morphogenesis is a dynamic process involving growth, branching, and retraction. How the growth and stabilization of dendrites are coordinated at the molecular level remains a key question in developmental neurobiology. The highly arborized and stereotyped dendritic arbors of the Caenorhabditis elegans PVD neuron are shaped by the transmembrane DMA-1 receptor through its interaction with a tripartite ligand complex consisting of SAX-7, MNR-1, and LECT-2. However, receptor null mutants exhibit strongly reduced dendrite outgrowth, whereas ligand null mutants show disordered branch patterns, suggesting a ligand-independent function of the receptor. To test this idea, we identified point mutations in dma-1 that disrupt receptor-ligand binding and introduced corresponding mutations into the endogenous gene. We show that the ligand-free receptor is sufficient to drive robust, disordered dendritic branch formation but results in a complete loss of arbor shape. This disordered outgrowth program utilizes similar downstream effectors as the stereotyped outgrowth program, further arguing that ligand binding is not necessary for outgrowth. Finally, we demonstrate that ligand binding is required to maintain higher-order dendrites after development is complete. Taken together, our findings support a surprising model in which ligand-free and ligand-bound DMA-1 receptors have distinct functions: the ligand-free receptor promotes stochastic outgrowth and branching, whereas the ligand-bound receptor guides stereotyped dendrite morphology by stabilizing arbors at target locations.

developmental biology↗