Biology subjects

Ko, H.

Publications and source records attributed to Ko, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Dynamic Nanoparticle Assembly-Based Biomedical Microrobots

Precise drug delivery within anatomically complex tissues demands systems capable of both active navigation and deep tissue access, properties that have remained difficult to reconcile in existing nanocarriers and microrobots. Here we introduce Dynabots, a dynamic microrobotic assembly constructed from multifunctional nanoparticles covalently linked by thermally cleavable molecular connectors. This nanoparticle-rich architecture enables the integration of magnetic, imaging, and therapeutic components while preserving a high content of functional material. Collective assembly imparts enhanced magnetic responsiveness and maneuverability, enabling controlled navigation through tortuous biological environments. Upon exposure to mild thermal stimuli, the assemblies undergo programmed disassembly, releasing individual nanoparticles that can diffuse through tissue for localized therapeutic action. We establish the programmable transitions, biocompatibility, and therapeutic efficacy of this process across in vitro and in vivo models, including real-time fluoroscopic guidance within anatomically realistic phantoms and live rodent and porcine systems. By integrating magnetic control, reconfigurable architecture, and stimulus-triggered disassembly, Dynabots unite navigational precision with tissue permeability, providing a versatile platform for adaptive and deep-tissue drug delivery.

bioengineering↗

bioRxiv2026

nELAVL phosphorylation by CDKL5 regulates inter-condensates composition and communication to promote experience-dependent maturation of the visual cortex

Mutations in Cyclin-Dependent Kinase-Like 5 (CDKL5) cause CDKL5 deficiency disorder (CDD), an X-linked neurodevelopmental condition. Through a phosphoproteomic screen, we identified the neuron-specific nELAVL family of RNA-binding proteins as direct activity-dependent substrates of CDKL5. In support of this regulatory axis, single-nuclei transcriptomics of Cdkl5 knockout (KO) cortices revealed an enriched reduction in activity-dependent mRNAs. Mechanistically, we show that nELAVL proteins undergo phase separation to form biomolecular condensates, the size of which is gated by CDKL5 phosphorylation. Loss of CDKL5 leads to enlarged nELAVL condensates, which exhibit reduced binding affinity for the target mRNA Fos, resulting in its accelerated degradation. This disruption extends to inter-condensate communication: phosphodeficient nELAVL show diminished interaction with P-bodies, which themselves become enlarged in CDD mutant iNeurons. Functionally, the absence of nELAVL phosphorylation recapitulates the deficits in experience-dependent visual function observed in Cdkl5 KO mice. Our findings establish a critical molecular mechanism by which CDKL5-mediated phosphorylation governs mRNA metabolism by tuning the properties of nELAVL condensates and their communication with other biomolecular condensates, ultimately promoting experience-dependent maturation of the visual cortex.

neuroscience↗

bioRxiv2026

Springtail-inspired compliant hinge enables terrain-adaptable takeoff in insect-scale robots

Springtails execute millisecond-scale escape jumps with a single appendage, the furca, on soil, snow, leaf litter, and water. Across 15 taxonomic families (n=552 individuals), relative furca length is bimodal. High-speed video and confocal imaging show that in some long-furca springtails, the resilin-rich manubrium-dens joint behaves as a compliant hinge. It bends during push-off to prolong contact, suppress pitch, and bias takeoff forward, whereas rigid joints drive backward launches with rapid body rotation. We translate this mechanism to a 20-mm, 84-mg jumping robot with an elastic robo-furca hinge. This flexible hinge reduces body rotation by [~] 90% on flat ground compared to rigid-hinge designs, while maintaining takeoff speed on gravel, springboards, leaves, and pine needles, enabling passive, terrain-adaptable launches for power-limited insect-scale robots without onboard sensing or active control.

animal behavior and cognition↗

bioRxiv2026

Microglial Lag3 Drives α-Synuclein--induced Neurotoxic Activated (A1) Astrocytes and Neurodegeneration

BackgroundNeuroinflammation and pathologic -synuclein (-syn) aggregation cooperate to drive dopaminergic neurodegeneration in Parkinsons disease, but the glial receptors that couple extracellular -syn to inflammatory cascades remain incompletely defined. Microglia express higher levels of lymphocyte activation gene 3 (Lag3) than neurons, yet the contribution of microglial Lag3 to -syn recognition, glial crosstalk, and neurodegeneration is unknown. MethodsBiochemical binding assays, live-cell imaging, cytokine profiling, and neuron-microglia-astrocyte co-culture paradigms were used to define Lag3-dependent -syn preformed fibril (PFF) binding, uptake, and microglial activation. To interrogate in vivo function, microglia-specific Lag3 conditional knockout mice (Lag3L/L-Cx3cr1CreER) and littermate controls received unilateral intrastriatal -syn PFF injections, followed by histological, biochemical, and behavioral assessments of -syn pathology, gliosis, nigrostriatal integrity, and motor performance. Results-syn PFFs bound microglial Lag3 with high specificity and nanomolar affinity and required Lag3 for efficient fibril internalization and induction of proinflammatory cytokines. Microglial Lag3 deficiency markedly blunted -syn PFF-evoked microglial activation, prevented cytokine-driven conversion of astrocytes into neurotoxic reactive A1 astrocytes, and abolished astrocyte-dependent neuronal death in vitro. In vivo, microglia-specific Lag3 deletion reduced cortical, striatal, and substantia nigra pS129 -syn pathology, suppressed microgliosis and A1 astrocyte induction, preserved substantia nigra dopaminergic neurons and striatal dopamine transporter/tyrosine hydroxylase expression, and ameliorated -syn PFF-induced motor deficits. ConclusionsThis study identifies microglial Lag3 as a key receptor linking extracellular -syn PFF recognition to inflammatory amplification, neurotoxic reactive A1 astrocyte conversion, and dopaminergic neurodegeneration. Together with prior work on neuronal Lag3, these findings support a cell-type-specific dual-axis model in which neuronal Lag3 mediates -syn propagation while microglial Lag3 drives glia-dependent neurotoxicity, positioning Lag3 as a promising precision therapeutic target in -synucleinopathies.

neuroscience↗

bioRxiv2025

Microbial-inspired antidotes to repurpose toxic compounds as antibiotics

Antibiotic-resistant (AMR) bacterial infections are a major global health threat. Despite the critical need for new antimicrobials, progress is constrained by protracted development timelines, as well as the requirement for chemical novelty to avoid cross-resistance. Although advances in high-throughput screening, genome mining, and machine learning have greatly accelerated antimicrobial discovery, insufficient separation between antibacterial efficacy and host toxicity remains a bottleneck, precluding the clinical development of many promising compounds. Here, we establish a generalizable, two-component strategy to engineer antimicrobial safety and mobilize otherwise inaccessible chemical space for antimicrobial therapy, using calicheamicin, a potent cytotoxin with unacceptable host toxicity, as a proof of concept. In the first arm, we engineer a conditionally-active drug conjugate that limits calicheamicin activity to infected tissue, thereby reducing systemic toxicity. In the second arm, we co-administer a re-engineered self-resistance enzyme from Micromonospora echinospora, the natural producer of calicheamicin, as an "antidote" to neutralize calicheamicin present outside of infected tissue, further mitigating off-target toxicity. The conditionally-active conjugate exhibits activity against Gram-negative and Gram-positive pathogens in response to a protease present within the infected microenvironment. When delivered in combination with the antidote, antibacterial efficacy is maintained while off-target toxicity is reduced in mouse models of Gram positive and negative bacterial pneumonia. We anticipate that our dual strategy, which engineers, rather than selects for enhanced drug safety, by combining conditional drug activity with antidote-driven neutralization of off-target effects, provides a generalizable framework for mobilizing other promising but toxic compounds as antimicrobials.

bioengineering↗

bioRxiv2025

Fish locomotor variation: connecting energetics and kinematic modulation

Analyses of vertebrate locomotion have frequently revealed variations in locomotor energetics and movement both among individuals and through time within an individual. This variation is often collapsed into mean values for broad comparative analyses of function. However, kinematic patterns of locomotion, even when animals move at a near-constant mean speed, frequently vary with both the physical and biological context. Here we demonstrate, using analyses of fish locomotion and energetics, how variation among individuals in kinematic gaits can manifest as changes in dynamics of metabolic rate (estimated from oxygen uptake). We present kinematic data from a small school of giant danio (Devario aequipinnatus) to show that fish within a school frequently modulate their kinematics and change position, even when the school moves at an overall constant mean speed. We show that rainbow trout (Oncorhynchus mykiss), swimming over a range of speeds, exhibit considerable variation in tail beat frequency and metabolic rate among speeds. By experimentally altering the fluid dynamic environment, we demonstrate that brook trout (Salvelinus fontinalis) show correlated modulation of both kinematics and metabolic rate. Simultaneous measurement of energetic and biomechanical characteristics can unveil the physiological, biomechanical, and fluid dynamic mechanisms that underlie dynamic changes in vertebrate locomotor gaits.

physiology↗

bioRxiv2025

Neuronal titration of Snca via enhancer disruption mitigates disease onset in a Parkinson's disease mouse model

-synuclein (SNCA) is the greatest genetic risk factor for sporadic Parkinsons Disease (PD). Misfolding and overexpression of SNCA underlie pathognomonic features of PD, including SNCA aggregates and midbrain dopaminergic (mbDA) neurodegeneration. We recently identified an SNCA intronic sequence that harbors variation associated with PD risk and demonstrated its role as a neuronal cis-regulatory element (CRE). Here, we engineered a mouse model lacking this sequence, which exhibits significantly reduced Snca transcription in mbDA neurons. Employing a battery of motor, molecular, and histological assays in an established mouse model of PD, we demonstrate that mice lacking this Snca enhancer are protected against PD-relevant histopathology and motor impairments. By targeting a cell-dependent CRE to diminish PD onset/progression in mice, we introduce a potentially powerful therapeutic avenue for PD.

genetics↗

bioRxiv2024

Engineering Multiplexed Synthetic Breath Biomarkers as Diagnostic Probes

Breath biopsy is emerging as a rapid and non-invasive diagnostic tool that links exhaled chemical signatures with specific medical conditions. Despite its potential, clinical translation remains limited by the challenge of reliably detecting endogenous, disease-specific biomarkers in breath. Synthetic biomarkers represent an emerging paradigm for precision diagnostics such that they amplify activity-based biochemical signals associated with disease fingerprints. However, their adaptation to breath biopsy has been constrained by the limited availability of orthogonal volatile reporters that are detectable in exhaled breath. Here, we engineer multiplexed breath biomarkers that couple aberrant protease activities to exogenous volatile reporters. We designed novel intramolecular reactions that leverage protease-mediated aminolysis, enabling the sensing of a broad spectrum of proteases, and that each release a unique reporter in breath. This approach was validated in a mouse model of influenza to establish baseline sensitivity and specificity in a controlled inflammatory setting and subsequently applied to diagnose lung cancer using an autochthonous Alk-mutant model. We show that combining multiplexed reporter signals with machine learning algorithms enables tumor progression tracking, treatment response monitoring, and detection of relapse after 30 minutes. Our multiplexed breath biopsy platform highlights a promising avenue for rapid, point-of-care diagnostics across diverse disease states.

bioengineering↗

bioRxiv2024

Conditional fusogenic lipid nanocarriers for cytosolic delivery of macromolecular therapeutics

Macromolecular therapeutics designed for intracellular targets must overcome systemic delivery barriers, target cell membrane impermeability, and inefficient endosomal escape. Here, we engineer a class of conditional fusogenic liposomes (C-FLIPs) that harness the catalytic activity of extracellular proteases present in the pathological microenvironment. This context-specific activation enables on-target membrane fusion with cells in diseased tissue, resulting in cytosolic delivery of therapeutic payloads. We describe the cytoplasmic delivery of three prototypic macromolecular therapeutic classes: peptide degraders, cytotoxic proteins, and ribonucleoprotein particles (RNPs). We further develop C-FLIP to deliver granzyme B (GzmB) to the cytoplasm of cancer cells in vivo and induce pyroptosis in immunologically-inert tumors. Treatment with C-FLIP/GzmB reprograms the immunosuppressive tumor microenvironment and synergizes with checkpoint blockade to result in the regression of established tumors and induce immunological memory. This modular, non-viral, cytosolic delivery platform represents a promising approach to leverage pathological protease activity for targeted delivery of biologics.

bioengineering↗

bioRxiv2024

Automated cell tracking using 3D nnUnet and Light Sheet Microscopy to quantify regional deformation in zebrafish

Light Sheet Microscopy (LSM) in conjunction with embryonic zebrafish, is rapidly advancing three-dimensional, in vivo characterization of myocardial contractility. Preclinical cardiac deformation imaging is predominantly restricted to a low-order dimensionality image space (2i) or suffers from poor reproducibility. In this regard, LSM has enabled high throughput, non-invasive 4i (3d+time) characterization of dynamic organogenesis within the transparent zebrafish model. More importantly, LSM offers cellular resolution across large imaging Field-of-Views at millisecond camera frame rates, enabling single cell localization for global cardiac deformation analysis. However, manual labeling of cells within multilayered tissue is a time-consuming task and requires substantial expertise. In this study, we applied the 3i nnU-Net with Linear Assignment Problem (LAP) framework for automated segmentation and tracking of myocardial cells. Using binarized labels from the neural network, we quantified myocardial deformation of the zebrafish ventricle across 4-6 days post fertilization (dpf). Our study offers tremendous promise for developing highly scalable and disease-specific biomechanical quantification of myocardial microstructures.

bioengineering↗

bioRxiv2024

Chemosensory modulation of eye-body coordination in larval zebrafish

Coordinated eye-body movements are essential for adaptive behavior, yet little is known about how multisensory input, particularly chemosensory cues, shapes this coordination. Using our enhanced Fish-on-Chips optofluidic platform, we uncovered complex dynamics in how larval zebrafish coordinate saccadic eye movements with tail flips. Under baseline conditions, spontaneous tail flips dynamically align with saccades in frequency and direction for coordinated turns. Chemosensory valence further modulates this coordination: death-associated cues intensify both the strength and relative frequency of coupled saccade-tail flips during turns, whereas food-related cues promote forward gliding without altering saccade coupling. Concurrent brain-wide neuronal imaging reveals that the zebrafish pallium represents the mapping between aversive valence and enhanced saccade-tail coordination, with stronger coupling associated with higher pallium activation. These findings uncover the neural representations and behavioral strategies by which chemosensory inputs of different valences are associated with amplified eye-body coordination and adaptive locomotion in a developing vertebrate, offering insights into principles of sensory-motor integration.

neuroscience↗

bioRxiv2024

Beyond planar: fish schools adopt ladder formations in 3D

The coordinated movement of fish schools has long captivated researchers studying animal collective behavior. Classical literature from Weihs and Lighthill suggests that fish schools should favor planar diamond formations to increase hydrodynamic efficiency, inspiring a large body of work ranging from fluid simulations to hydrofoil experiments. However, whether fish schools actually adopt and maintain this idealized formation remains debated and unresolved. When fish schools are free to self-organize in three dimensions, what formations do they prefer? By tracking polarized schools of giant danios (Devario aequipinnatus) swimming continuously for ten hours, we demonstrate that fish rarely stay in a horizontal plane, and even more rarely, in the classical diamond formation. Of all fish pairs within four body-lengths from each other, only 25.2% are in the same plane. Of these, 54.6% are inline, 30.0% are staggered, and 15.4% are side-by-side. The diamond formation was observed in less than 0.1% of all frames. Notably, a "ladder formation" emerged as the most probable formation for schooling giant danios, appearing in 79% of all fish pairs and fish schools elongate at higher swimming speeds. These findings highlight the dynamic and three-dimensional nature of fish schools and suggest that hydrodynamic benefits may be obtained without requiring fixed positions. This research provides a foundation for future studies that examine the hydrodynamics and control of underwater collectives in 3D formations.

biophysics↗

bioRxiv2024

Bacterial motility patterns adapt smoothly in response to spatial confinement and disorder

In unconfined environments, bacterial motility patterns are an explicit expression of the internal states of the cell. Bacteria operating a run-and-tumble behavioral program swim forward when in a run state, and are stalled in place when in a reorienting tumble state. However, in natural environments, motility dynamics often represent a convolution of bacterial behavior and environmental constraints. Recent investigations showed that Escherichia coli swimming through highly confined porous media exhibit extended periods of trapping punctuated by forward hops, a seemingly drastic restructuring of run-and-tumble behavior. We introduce a microfluidic device to systematically explore bacterial movement in a range of spatially structured environments, bridging the extremes of unconfined and highly confined conditions. We observe that trajectories reflecting unconstrained expression of run-and-tumble behavior and those reflecting hop-and-trap dynamics coexist in all structured environments considered, with ensemble dynamics transitioning smoothly between these two extremes. We present a unifying swim-and-stall framework to characterize this continuum of observed motility patterns and demonstrate that bacteria employing a consistent set of behavioral rules can present motility patterns that smoothly transition between the two extremes. Our results indicate that the control program underlying run-and-tumble motility is robust to changes in the environment, allowing flagellated bacteria to navigate and adapt to a diverse range of complex, dynamic habitats using the same set of behavioral rules.

biophysics↗

bioRxiv2024

Functional and multi-omic aging rejuvenation with GLP-1R agonism

Identifying readily implementable methods that can effectively counteract aging is urgently needed for tackling age-related degenerative disorders. Here, we conducted functional assessments and deep molecular phenotyping in the aging mouse to demonstrate that glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment attenuates body-wide age-related changes. Apart from improvements in physical and cognitive performance, the age-counteracting effects are prominently evident at multiple omic levels. These span the transcriptomes and DNA methylomes of various tissues, organs and circulating white blood cells, as well as the plasma metabolome. Importantly, the beneficial effects are specific to aged mice, not young adults, and are achieved with a low dosage of GLP-1RA which has a negligible impact on food consumption and body weight. The molecular rejuvenation effects exhibit organ-specific characteristics, which are generally heavily dependent on hypothalamic GLP-1R. We benchmarked the GLP-1RA age-counteracting effects against those of mTOR inhibition, a well-established anti-aging intervention, observing a strong resemblance across the two strategies. Our findings have broad implications for understanding the mechanistic basis of the clinically observed pleiotropic effects of GLP-1RAs, the design of intervention trials for age-related diseases, and the development of anti-aging-based therapeutics.

systems biology↗

bioRxiv2024

Pathologic α-Synuclein-NOD2 Interaction and RIPK2 Activation Drives Microglia-Induced Neuroinflammation in Parkinson's Disease

Pathological aggregation of -Synuclein (-Syn) and neuroinflammation are closely linked to Parkinsons disease (PD). However, the specific regulators of the neuroinflammation caused by pathological -syn remain obscure. In this study, we show that NOD2/RIPK2 signaling is a crucial regulator of neuroinflammation in PD. Pathological -syn binds to NOD2, causing self-oligomerization and complex formation with RIPK2, leading to RIPK2 ubiquitination and activation of MAPK and NF-kB. Notably, this NOD2/RIPK2 signaling is particularly active in microglia of human PD brains and the -Syn preformed fibril (-Syn PFF) mouse model. Depleting NOD2 or RIPK2 reduces neuroinflammation and protects against dopamine neuron degeneration in a pathologic -Syn mouse model by blocking the formation of neurotoxic reactive astrocytes caused by microglia activation. The discovery of NOD2/RIPK2 signaling as a key regulator of neuroinflammation in PD provides a new understanding of -Syn-driven neuroinflammation and neurodegeneration in PD and a potential new therapeutic strategy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/580982v2_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@10c010aorg.highwire.dtl.DTLVardef@1183b23org.highwire.dtl.DTLVardef@1d289dborg.highwire.dtl.DTLVardef@158b6ef_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefPathological -Synuclein (-Syn) binds to the microglial NOD2 protein, which in turn triggers NOD2/RIPK2 complex and RIPK2 phosphorylation/ubiquitination. This process activates the NF-kB/MAPK pathways, ultimately leading to neurotoxic reactive astrocyte-induced dopaminergic neurodegeneration. Depletion of RIPK2 (RIPK2 KO) or NOD2 (NOD2) protects dopamine neurons in a mouse model of Parkinsons disease (PD). These findings provide insights into -Syn-driven neuroinflammation and offer potential therapeutic strategies for PD. HighlightsNOD2/RIPK2 signaling is identified as a crucial regulator of neuroinflammation in PD. NOD2/RIPK2 signaling is highly active in microglia in human PD brains and -Syn PFF mouse models. Pathological -Syn binds to NOD2, triggering self-oligomerization and RIPK2 complex formation, leading to MAPK and NF-kB activation Genetic depletion of NOD2 or RIPK2 reduces neuroinflammation and protects dopamine neurons by blocking the formation of neurotoxic reactive astrocytes.

neuroscience↗

bioRxiv2024

Nanobody-targeted conditional antimicrobial therapeutics

Conditional therapeutics that rely on disease microenvironment-specific triggers for activation are a promising strategy to improve therapeutic cargos. Among the investigated triggers, protease activity is used most often, because of its dysregulation in several diseases. How to optimally fine-tune protease activation for different therapeutic cargos remains a challenge. Here, we designed nanobody-targeted conditional antimicrobial therapeutics to deliver a model therapeutic peptide and protein to the site of bacterial infection. We explored several parameters that influence proteolytic activation. We report the use of targeting nanobodies to enhance the activation of therapeutics that are otherwise activated inefficiently, despite extensive optimization of the cleavable linker. Specifically, pairing of Ly6G/C or ADAM10-targeting nanobodies with ADAM10-cleavable linkers improved activation via proximity-enabled reactivity. More broadly, this optimization framework provides a guideline for the development of conditional therapeutics to treat various diseases where protease activity is dysregulated.

bioengineering↗

bioRxiv2024

Collective movement of schooling fish reduces locomotor cost in turbulence

The ecological and evolutionary benefits of collective behaviours are rooted in the physical principles and physiological mechanisms underpinning animal locomotion. We propose a turbulence sheltering hypothesis that collective movements of fish schools in turbulent flow can reduce the total energetic cost of locomotion by shielding individuals from the perturbation of chaotic turbulent eddies. We test this hypothesis by quantifying energetics and kinematics in schools of giant danio (Devario aequipinnatus) compared to solitary individuals swimming under control and turbulent conditions over a wide speed range. We discovered that, when swimming at high speeds and high turbulence levels, fish schools reduced their total energy expenditure (TEE, both aerobic and anaerobic energy) by 63-79% compared to solitary fish. Solitary individuals spend [~]25% more kinematic effort (tail beat amplitude*frequency) to swim in turbulence at higher speeds than in control conditions. However, fish schools swimming in turbulence reduced their three-dimensional group volume by 41-68% (at higher speeds) and did not alter their kinematic effort compared to control conditions. This substantial energy saving highlighted a [~]261% higher TEE when fish swimming alone in turbulence are compared to swimming in a school. Schooling behaviour could mitigate turbulent disturbances by sheltering fish within schools from the eddies of sufficient kinetic energy that can disrupt the locomotor gaits. Providing a more desirable internal hydrodynamic environment could be one of the ecological drivers underlying collective behaviours in a dense fluid environment. One-Sentence SummaryThe collective movement of fish schools substantially reduces the energetic cost of locomotion in turbulence compared to that of swimming alone.

physiology↗

bioRxiv2023

Machines learn ecological networks: automated discovery of ecological networks based on empirical data

Constructing ecological networks is known to be important and challenging in community ecology. In particular, to construct the holistic structure of ecological networks, identifying species interaction is essential but often costly and impalpable. Recent studies providing major challenges in assembling ecological networks have highlighted the need of new and more powerful approaches to reconstruct biological networks, including species interaction networks. In literature, there are no promising verifications in using machine leaning (ML) approaches to reconstruct ecological networks. In this work, we develop and employ a variety of ML methods, including penalized regression and graphical tools, to reconstruct ecological networks. For evaluation, we apply the methods to empirical time series data sets of 20 species abundances collected at Lake Constance in central Europe. We use resampled data to identify highly-ranked interactions among species and measure their consistency across 7 ML methods and 5,000 learning processes. We show that the best precision, recall, and F1 score were 0.48, 0.97, and 0.64, respectively, among all penalized regression methods under comparison. In summary, our study shows that machine learning methods offer promising data-driven and automated tools for reconstructing ecological networks and discovering underlying biological interactions among species.

ecology↗