Biology subjects

Green, A.

Publications and source records attributed to Green, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Comparison of Techniques for Isolating Small Extracellular Vesicles from Drosophila Larval Hemolymph

Extracellular vesicles (EVs) are membrane-delimited nanoparticles, secreted by virtually all tested cell types to mediate intercellular and interorgan communication by transporting biomolecules, such as proteins, nucleic acids, and lipids, to recipient cells. Many EV isolation techniques have been developed for mammalian EVs and exploit specific EV properties, such as size, density, and solubility. Although Drosophila has emerged as a simple yet robust animal model for studying fundamental EV biology in its native context, it remains unclear whether commonly used EV isolation techniques can be applied to hemolymph (Drosophila blood). In this study, we first provide an in-depth characterization of particles in hemolymph using two complementary particle analysis techniques: dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA). We then evaluate the performance of three commonly used small EV isolation methods--solvent precipitation, ultracentrifugation, and size-exclusion chromatography--for their ability to isolate small EVs from Drosophila larval hemolymph. All three methods can enrich small EVs from hemolymph to varying degrees, but none completely remove circulating proteins and lipoproteins. In particular, size-exclusion chromatography yields the purest small EV fractions, as evidenced by the enrichment of Drosophila orthologs of human small EV markers, including Tetraspanin 42Ee (Tsp42Ee), Tetraspanin 42Ed (Tsp42Ed), Tetraspanin 96F (Tsp96F), and Annexin B11 (AnxB11), although it produces the lowest protein yield. Altogether, our study provides practical guidance on both selecting an appropriate small EV isolation method and rigorously characterizing isolated small EV fractions according to specific research needs. More broadly, the knowledge gained from this study provides a framework for the isolation and characterization of small EVs in other insects, thereby facilitating future EV research across diverse insect species.

cell biology↗

bioRxiv2026

Leveraging Targeted Gene Sets and Neural Networks for Zebrafish Transcriptome Extrapolation in High-Throughput Toxicogenomics

BackgroundZebrafish (Danio rerio) are a powerful vertebrate model for developmental toxicology and chemical safety assessment, yet large-scale transcriptomics in zebrafish remains limited by cost and data heterogeneity. Targeted transcriptomics offers a cost-effective alternative, but gene extrapolation methods tailored to zebrafish have not been systematically developed or evaluated. ObjectivesWhile the S1500+ platform is widely used for toxicogenomics research with rat, mouse, and human cell lines as model systems, its use in zebrafish has been limited due to data scarcity and lack of suitable bioinformatics approaches for analysis of such data. To that end, we sought to (i) curate a large zebrafish transcriptomic training data resource, and (ii) evaluate multiple machine learning strategies for reconstructing unmeasured transcriptome-wide expression profiles for data originating from the zebrafish-specific reduced representation gene set ("Zf S1500+"). MethodsWe assembled 14,924 zebrafish RNA-Seq samples covering 21,930 genes across 1,246 studies. Using the Zf S1500+ gene subset (3,062 genes), we trained and tested three extrapolation approaches: principal components regression (PCR), a locally weighted extension of PCR (PCR+), and a neural network mixture-of-experts model (NN-MoE). Model performance was assessed using mean absolute error (MAE), mean squared regression error (MSRE), and weighted variants of these metrics. ResultsExtrapolation performance using the baseline approach was strongly influenced by tissue and developmental context, with within-tissue models outperforming cross-tissue models. Errors were lowest when training and testing were conducted within the same tissue or between developmentally related tissues. Both PCR+ and NN-MoE improved upon the baseline PCR approach, with NN-MoE reducing average MAE by [~]20% and MSRE by [~]17%. Importantly, extrapolation remained reliable for the majority of genes, even when limiting output to high-confidence predictions using an empirical MAE threshold. ConclusionsWe demonstrate that targeted transcriptomics can be effectively extended to zebrafish, enabling robust transcriptome-wide extrapolation at reduced cost. The NN-MoE method provided the most substantial gains, highlighting the value of non-linear and ensemble modeling in heterogeneous datasets. These results establish a scalable framework for zebrafish toxicogenomics and suggest that accuracy will continue to improve with larger, better-annotated datasets, paving the way for broader application in chemical safety assessments.

bioinformatics↗

bioRxiv2026

A Modular Platform for Purification of Organelle-associated Mitochondria Reveals Functional Specialization at Organelle Contact Sites

Mitochondria perform diverse metabolic and signaling functions, yet how these activities are spatially organized within the mitochondrial network of cells remains poorly understood. Organelle contact sites are spatially restricted hubs that regulate mitochondrial metabolism, signaling, and dynamics, and are therefore well positioned to influence mitochondrial specialization. Investigation of contact site-associated mitochondrial populations has been hindered by a lack of methods to isolate these subpopulations. Here, we develop Organelle Contact-dependent Affinity Purification (ORCA), a workflow for the isolation and analysis of subpopulations of intact mitochondria and associated proteins defined by their organelle contacts. ORCA revealed distinct proteomes for mitochondria associated with the endoplasmic reticulum, lysosomes, peroxisomes, and the Golgi apparatus, demonstrating that organelle contacts define biochemically specialized mitochondrial populations. Focused analysis of Golgi-associated mitochondria showed enrichment of mitochondrial ribosomes and increased mitochondrial translation, revealing an unexpected role for Golgi-mitochondria contacts in regulating mitochondrial protein homeostasis. ORCA also identified the previously uncharacterized Golgi protein KIAA0930/GMO1 as an evolutionarily conserved regulator of oxidative phosphorylation at Golgi-mitochondria contacts. Together, our findings establish ORCA as a broadly applicable approach for investigating the spatial organization of intracellular organelles and reveal organelle contacts as key determinants of mitochondrial specialization.

cell biology↗

bioRxiv2026

An Open-Source, Excitation-Resolved UV-NIR Imaging Platform for Bioluminescence, Luminescence-Decay, and Chemical Discrimination Measurements

Multispectral imaging is a cornerstone of chemical imaging, with bioluminescence, fluorescence, and phosphorescence imaging underpin much of preclinical and analytical chemical measurements. However, conventional implementations are typically proprietary, costly, and resolve spectral content from the reflectance of a broadband source, without control over the excitation spectrum. This architecture cannot isolate excitation-dependent photophysical processes. Spectral discrimination through sequentially resolved narrowband excitation, detected on a single broadband-sensitive camera, instead enables excitation-dependent fluorescence, phosphorescence, and reflectance measurements not available to such broadband approaches. We describe AURORA-MSI, an open-source multispectral platform that inverts this arrangement with fourteen narrowband LEDs spanning 367-940 nm, a 120-element annular illumination ring with eight independently addressable azimuthal sectors, and a thermoelectrically cooled monochrome CMOS camera. Radiometric calibration, spatial uniformity mapping, and camera noise characterization establish the quantitative measurement foundation. In bioluminescence imaging, AURORA-MSI localized sources in a calibrated tissue-mimicking mouse phantom comparably to a commercial Revvity IVIS Spectrum, detected luciferase-expressing HSJD-GBM1-001 glioblastoma cells across a dilution series, with reduced replicate consistency at the lowest densities, and mapped substrate-free fungal-pathway emission in an intact bioluminescent Petunia hybrida, none requiring photon-counting instrumentation. Time-resolved phosphorescence decay imaging of six inorganic phosphors over 33 minutes found tri-exponential models adequate at early times, while distributed-lifetime models were preferred at extended timescales. Multispectral image-texture features extracted across all fourteen excitation bands discriminated ten pharmaceutical and household powders spanning distinct chemical compositions and, in two cases, distinct formulations of the same compound. Generality beyond these regimes was established through dual-excitation fluorescence fingerprinting of fifteen mineral specimens and wavelength-selective plant-tissue imaging exploiting UV and NIR penetration-depth differences. Excitation-side spectral encoding enables photophysical measurements that detection-side systems with uncontrolled broadband illumination cannot isolate, and the cooled-camera architecture supports weak-signal modalities without photon-counting instrumentation.

biophysics↗

bioRxiv2026

Stimulating neurogenesis of distinct retinal lineages in human retinal pigmented epithelium (RPE) with proneural transcription factors

There are currently few promising approaches for treatment of photoreceptor pathologies: for example, gene therapy to augment or replace mutated genes, has proven successful in preclinical studies, and some of these therapies are moving towards the clinic. Another approach aims to unlock the inherent stem-cell potential of non-neuronal retinal cells to regenerate neurons in situ. This line of research is based on the discovery that some vertebrates can restore even severely damaged retina from RPE with all the necessary cell types to regain full functionality. To determine whether this approach can be applied to humans, we established a robust in vitro culture system using fetal human RPE, and employed a barcode-multiplexed, single cell RNAseq based screen to find factors that would reprogram human RPE into a photoreceptors. With this approach we were able to identify NEUROD1 as a complimentary factor to ASCL1. Their combined overexpression together with a treatment with bFGF and Activin A inhibitor produced RPE-derived neuronal cells with expression patterns characteristic of photoreceptors and other lineages.

Developmental Biology↗

bioRxiv2026

A de novo CO2 Reductase Featuring a Cysteine-Ligated Cobalt Porphyrin Cofactor

Modern protein design methods based on deep learning allow generation of customized protein scaffolds with diverse geometries and functionalities. Here, we capitalize on these recent advances to develop hyper-thermostable de novo CO2 reductases featuring a cobalt porphyrin IX cofactor (CoPPIX). CoPPIX containing enzymes were assembled in vivo through media supplementation with cobalt salts and assessed for photocatalytic CO2 reductase activity. We identified two cysteine-ligated designs that exhibit high activity (>1000 turnovers at rates of up to 25 min-1) while suppressing competing hydrogen evolution pathways. A 2.1 [A] crystal structure shows close agreement to the design model with the Co-Cys bond programmed as intended. This study showcases the power of computational protein design in developing artificial enzymes to activate challenging molecules such as CO2.

biochemistry↗

bioRxiv2025

A century of breeding has preserved genetic variation, accumulated favorable alleles, and shaped the Rht gene portfolio in North American spring wheat

Hard red spring wheat (HRSW) is an important market class of wheat in North America with a rich history of breeding. We genotyped 1,013 HRSW lines representing a century of breeding material using a SNP array and targeted KASP genotyping to assess the changes in genetic diversity and Rht genes in HRSW from North America. Results show that early breeding efforts broadened an initially narrow gene pool derived from a few founders and subsequently maintained the genetic diversity. Analysis of Rht genes revealed that Rht-D1b was the predominant semi-dwarf allele from introduction of the Green Revolution genes (Rht-B1 and Rht-D1) in 1960s until the FHB epidemics of 1990s, when most breeding programs shifted to Rht-B1b. However, adoption of Rht-B1b and Rht-D1b remains low in some regions of the Great Plains. The dwarf alleles at GA-sensitive Rht24 and Rht25 have persisted in the region at low frequencies before the introduction of Green Revolution genes and have increased in frequency in recent decades. We also analyzed the effect of Rht genes on plant height (PH) in the HRSW growing region and found that Rht-B1b or Rht-D1b results in [~]12% reduction in PH, which decreases to [~]9% in dry environments. Notably, combining dwarfing alleles at Rht24 and Rht25 reduced height by [~]6% in dry environments, suggesting an alternative approach for reducing PH. Our analysis also revealed significant genetic interactions between Rht-B1 and Rht25, as well as between Rht-D1 and Rht24, which could help fine-tune PH for different environments by employing appropriate Rht combinations. Furthermore, our results demonstrate positive selection for photoperiod sensitivity in recent decades, particularly in high-latitude regions. This study provides a valuable genomic resource, and the findings enhance our understanding of past breeding efforts while offering insights to guide future plant breeding strategies.

plant biology↗

bioRxiv2025

Software System Design to Support Scale in Mammalian Cell Line Engineering.

Cell line engineering (CLE) is the process of gene editing cell lines for a variety of purposes for research and development or bioproduction processes. Traditionally, CLE workflows have been manual and low throughput. Here, we describe the development of several software-based processes implemented alongside wet-lab automation and robotics, built to improve the throughput of our CLE platform to three times its previous capacity. A markup language (GEML) was developed to enable eCommerce capabilities and connections to internal manufacturing systems. A Laboratory Information Management System (LIMS) specifically designed to track CLE projects through all stages was created to manufacture the cell line specified by the GEML. Cell line engineering required analysis of images in brightfield without fluorescent staining therefore a machine learning (ML)-based method for analysing engineered clones imaged captured on an automated imaging platform was created. Our work demonstrates that combining both wet-lab automation and software approaches is essential to allow CLE workflows to reach their full potential, allowing the development of high-throughput robust platforms that meet the increasing demands of the field.

synthetic biology↗

bioRxiv2025

Genetic Gains from Sixty Years of Spring Wheat Breeding in the Northern Plains of the US

Evaluating genetic gains over time is essential for assessing the success of breeding programs and refining strategies for ongoing improvement. Hard red spring (HRS) wheat is an important wheat class in the US and is primarily grown in the Northern Great Plains. Despite a long history of breeding efforts in this region, long-term quantification of genetic gains for key traits has remained limited. This study analyzes over sixty years of data from the USDA-coordinated Hard Red Spring Wheat Uniform Regional Nursery (HRSWURN) to evaluate genetic advancements in agronomic traits across multiple phases. A significant positive genetic gain of 0.61% per annum was observed for grain yield in HRS wheat released in the Northern US region, which is lower than the expected gains needed to meet future wheat demand. The change was 0.07% for test weight, -0.04% for days to heading, and -0.16% for plant height. Notably, sustained yield improvements have not affected grain protein levels since they were first measured in 1995, indicating that ongoing selection has effectively balanced grain yield and protein despite their negative correlation (r = -0.31). Assessment of genetic gains over 20-year phases suggested slowing rates of genetic gains for grain yield but did not indicate any plateaus. The realized genetic gains were generally higher for individual breeding programs when breeding for target environments, with the public breeding program in Minnesota observing gains of approximately 1% per annum. These findings highlight the significant impact of long-term breeding efforts and offer valuable insights for refining future breeding strategies.

plant biology↗

bioRxiv2025

Mouse Bio-behavioral Phenotyping Using a Digital Homecage Framework for Long-timescale, High-resolution, and Multi-factor Data Collection and Analytics

MOTIVATION Long-term monitoring of behavioral and physiological processes is critical for understanding complex brain-based phenomena and disorders that develop over extended periods, such as chronic stress, circadian disorders, and metabolic conditions. While digital phenotyping is available in humans using smart devices, there remains a deficit in rodent models. To address this lack of long-term rodent phenotyping, we introduce the "Digital Homecage" (DHC) system. Our system uses accessible components and is designed for seamless integration with brain recording technologies. The Digital Homecage (DHC) allows uninterrupted, long-timescale recording of more than 20 behavioral metrics in single-housed mice, captured at sub-second resolution via video, operant interactions, and wheel-running data. This report demonstrates the DHCs capacity to enable continuous, automated tracking of behaviors like actigraphy, sleep, grooming, and food choice options over weeks, thereby opening up new avenues for longitudinal analyses of chronic conditions. Data collected reveal circadian patterns in multiple spontaneous behaviors, aligning with known nocturnal tendencies. The systems potential to facilitate groundbreaking observations on the long-term behavioral correlates of various neuropsychiatric syndromes is aided by open-source software and relatively low cost. The DHC sets the stage for community-driven innovation, potentially transforming our approach to studying complex traits of brain function and behavior in laboratory settings.

animal behavior and cognition↗

bioRxiv2025

Effects of Combination Therapy of a CDK4/6 and MEK Inhibitor in Diffuse Midline Glioma Preclinical Models

BackgroundDiffuse midline glioma (DMG) is an incurable brain cancer without a single FDA-approved drug that prolongs survival. CDK4/6 inhibitors have been evaluated in children with DMG with limited efficacy. Since MAPK pathway activation is upstream of cell proliferation, we hypothesized that MEK inhibitors may increase the anti-tumor effects of CDK4/6 inhibitors. Here, we evaluated the efficacy of the CDK4/6 inhibitor ribociclib and the MEK inhibitor trametinib in human and murine DMG models to investigate combinational effects. MethodsWe conducted in vitro and in vivo assays using DMG cell lines from human patient-derived xenografts (PDX) and murine genetically engineered models (GEM). In vitro, we assessed synergy across human DMG lines. In vivo, we evaluated therapeutic effects with histological examinations, survival analysis, pharmacokinetic measurements, and RNA-sequencing analysis. ResultsIn vitro, ribociclib and trametinib had variable synergistic effects against human DMG cell lines. In vivo, a five-day treatment with combination therapy in the GEM DMG model significantly decreased cell proliferation and increased apoptosis compared with the vehicle, with trametinib having mostly cytotoxic effects and ribociclib having primarily cytostatic effects. In addition, a 21-day treatment with combination therapy significantly prolonged mice survival compared with the vehicle in the GEM DMG model (median survival: 112 days vs. 71.5 days, log rank test p=0.0195). In an orthotopic PDX model, combination therapy did not prolong mice survival compared with vehicle, ribociclib, and trametinib. LC/MS analysis showed adequate drug delivery across the blood-brain-barrier (BBB) into tumor tissue in both GEM and PDX models. Transcriptomic analysis in the GEM model suggests that combination therapy inhibited the MAPK pathway and inflammation. ConclusionsCombination therapy with ribociclib and trametinib significantly prolonged survival in the GEM model but not in the PDX model, highlighting the importance of testing novel therapies in diverse models. Key PointsO_LICombination therapy had cytotoxic and cytostatic effects in vivo in the GEM model. C_LIO_LICombination therapy had variable synergy in vitro in human DIPG models. C_LIO_LICombination therapy significantly prolonged mice survival compared with the vehicle in the GEM model. C_LIO_LICombination therapy did not prolong survival in the PDX model. C_LIO_LITranscriptional analysis suggests that the combination modulated inflammation in the GEM model. C_LIO_LIThis work highlights the importance of testing novel therapies in diverse models. C_LI Importance of the StudyDMG is an incurable brain cancer without a single FDA-approved drug that prolongs survival. CDK4/6 inhibitors have been evaluated in children with DMG with limited efficacy. As MAPK pathway activation is known to be upstream of cell proliferation, we hypothesize that combination therapy will have additive effects relative to monotherapy. In this study, we evaluated the efficacy of the CDK4/6 inhibitor ribociclib and the MEK inhibitor trametinib in GEM and PDX DMG models. In vitro, the inhibitor combination demonstrated variable synergy in DMG human cell-lines, but in vivo, it had limited efficacy in a PDX orthotopic model. In the GEM model, the combination prolonged survival compared with the vehicle and with single agents. PK studies showed similar drug levels in tumor tissue between the GEM and PDX models. Transcriptomic analysis in the GEM suggests that the drug combination significantly inhibited inflammation. These results highlight the importance of testing therapies in diverse models and suggest that this combination may be an effective therapy in patients with DMG.

cancer biology↗

bioRxiv2025

SARC028 samples reveal an interplay between TGF-beta, interferon signaling and low HLA class I expression as contributors to Ewing sarcoma checkpoint blockade resistance

PurposeEwing sarcoma, in contrast to some adult sarcoma subtypes, generally does not respond to single agent immunotherapy targeting PD1. The features of Ewing sarcoma that preclude the effectiveness of immunotherapy remain largely unknown. To address this question, we utilized biopsies from patients with Ewing sarcoma obtained pre- and post-pembrolizumab (anti-PD1) therapy from the phase 2 clinical trial SARC028 to interrogate the Ewing tumor microenvironment and features associated with resistance to checkpoint inhibition. Experimental DesignWe utilize multiplexed immunofluorescence, spatial proteomics and spatial transcriptomics to analyze paired pre- and 8 weeks post-treatment biopsy specimens from patients with Ewing sarcoma enrolled on SARC028. ResultsPembrolizumab therapy did not alter the quantity of immune cell infiltration in Ewing tumor biopsies. Analysis of tumor-associated protein markers revealed increased immunoregulatory markers after pembrolizumab. Spatial transcriptomics identified ten cellular neighborhoods (CN) across patients consisting of specific cell subsets. CN10 was consistently observed across patients with poor response. This cellular neighborhood was enriched for a tumor subpopulation with high TGF-{beta} response, low interferon (IFN) response, and low HLA class I expression. IFN response, HLA class I expression, and overall immune infiltration were correlated. ConclusionsAnalyses of the tumor microenvironment from Ewing sarcoma biopsies reveals an immunosuppressive triad, the disruption of which should be pursued to improve antitumor immunity. This work highlights the unique insight that can be gained from the analysis of paired patient Ewing sarcoma tumor biopsy samples from clinical trials. Statement of translational relevanceSingle agent checkpoint inhibitors have demonstrated limited clinical benefit in bone sarcomas, including Ewing sarcoma (EwS). While in vitro and limited patient tumor analyses have suggested mechanisms of immunotherapy resistance in EwS, tumor biopsies following checkpoint inhibitor administration have not been examined. SARC028 was a phase II study investigating blockade of programmed cell death-1 (PD-1) in patients with relapsed/refractory sarcomas, including EwS. Tumor biopsies were collected prior to and 8 weeks after anti-PD1 therapy. Here, we leverage a unique opportunity to understand EwS immunotherapy resistance through analysis of paired tumor samples from SARC028. Using a multi-omics approach, we identify features of EwS that contribute to primary resistance to anti-PD1 including TGF-{beta}, reduced interferon signaling and low HLA class I expression. This study provides an improved understanding of tumor characteristics driving poor response to immunotherapy in relapsed EwS and will guide the development of future trials to modulate this immunosuppressive axis.

cancer biology↗

bioRxiv2025

Environmental and geographic drivers of global bat phylogenetic diversity

AimUnderstanding the patterns and factors that shape biodiversity is vital to conserving species. We combined open-source genetic, environmental, and geographic information to analyze bat phylogenetic diversity (PD) patterns in continuous ecoregions across the globe. This information is important for developing bat conservation strategies, and our methodology can work for any taxa with sufficient georeferenced genetic data available. LocationGlobal. MethodsAfter curating a global dataset containing 14,037 COI DNA sequences from 343 described species of bats, we calculated PD for continuous ecoregions at different spatial scales. To avoid the difficulties of using current species names, we used genetic OTUs identified by a single-locus species delimitation method to reconstruct and date a phylogeny. We then calculated PD, estimated a lineage through time plot, and used random forest predictive modeling to identify environmental and geographic predictors of PD. ResultsIn addition to current temperature, temperature during the last glacial maximum and temperature changes between the last glacial maximum and last interglacial were most closely associated with PD. However, at different spatial scales, the top variables differed slightly. When using smaller ecoregions, latitude and population density were also identified as important, though not significant. Southeast Asia and South America had the highest levels of PD, along with parts of Africa and the Himalayas. We demonstrate that, regardless of spatial scale and uneven sampling across the globe, single-locus genetic data can reflect species diversity gradients and identify predictors of PD. Main conclusionsWe show that publicly-available, single-locus data can be used to analyze large-scale evolutionary patterns and inform conservation efforts. Additionally, choice of biodiversity measure and spatial scale matter when assessing species patterns. When looking at bats, temperature variables with a historical component are most important for predicting PD broadly, but latitude and population density could also be important on smaller scales.

evolutionary biology↗

bioRxiv2025

Network-based framework for studying etiology and phenotype diversity in primary ciliopathies

Recent advances in sequencing technologies have increasingly enabled the identification of genetic causes for human monogenic diseases. However, systematic understanding remains limited due to the rarity, genetic heterogeneity, and complex genotype-phenotype relationships of these diseases. Primary ciliopathies are a diverse group of rare disorders caused by variants in genes associated with the cilium, a cellular organelle involved in signaling during development and cell homeostasis. These genetic variants result in a wide spectrum of clinical phenotypes involving the brain, eye, kidney and skeleton. It remains unclear to what extent this phenotypic diversity can be attributed to the disease-causing genes and their specific roles in ciliary function. Here, we systematically compared human primary ciliopathies with each other and with mouse phenotypes by propagating known disease genes through a network of protein interactions. Network propagation improved the clustering of primary ciliopathies with shared clinical phenotypes and facilitated the identification of mouse phenotypes closely related to primary ciliopathies due to shared groups of proteins in the interaction network. By leveraging this phenotype-specific approach, we prioritized candidate genes for ciliopathies and identified likely pathogenic variants in CEP43, a novel candidate gene for human primary ciliopathies in three previously unsolved cases. This study demonstrates that network propagation enhances the genetic and phenotypic understanding of primary ciliopathies, aiding in the prioritization of candidate genes and identification of relevant mouse models for these rare disorders, and providing a framework for unraveling shared underlying mechanisms for other rare genetic diseases.

genetics↗

bioRxiv2024

Imaging synaptic density in ageing and Alzheimer's Disease with -SynVesT-1

Monitoring synaptic injury in neurodegenerative diseases may provide new insights into the evolution of the degenerative process as well as a potential mechanism to target for preservation of function. Synaptic density imaging with PET is a relatively new approach to this issue. However, there are remaining questions about technical approaches to data analysis including reference region selection, and how specific phenotypic presentations and symptoms of Alzheimers Disease (AD) are reflected in alterations in synaptic density. MethodsUsing an SV2A PET ligand radiolabeled with the 18F isotope ([18F]-SynVesT-1) we performed sensitivity analyses to determine the optimal reference tissue modelling approach to derive whole brain ratio images. Using these whole brain images from a sample of young adults, older adults, and patients with varied phenotypic presentations of AD we then contrast regional SV2A density and in vivo AD biomarkers. ResultReference tissue optimisation concluded that a cerebellar grey matter reference region is best for deriving whole brain ratio images. Using these whole brain ratio images, we find a strong inverse association between [18F]-SynVesT-1 PET uptake and amyloid beta and tau PET deposition. Finally, we find that individuals with lower temporal grey matter volume but higher temporal [18F]-SynVesT-1 PET uptake show preserved performance on the MMSE. Conclusions[18F]-SynVesT-1 PET shows a close association with in vivo AD pathology and preserved SV2A density may be a possible marker for resilience to neurodegeneration.

neuroscience↗

bioRxiv2024

Targeting complement C3a receptor resolves mitochondrial hyperfusion and subretinal microglial activation in progranulin-deficient frontotemporal dementia

Mutations in progranulin (GRN) cause frontotemporal dementia (GRN-FTD) due to deficiency of the pleiotropic protein progranulin. GRN-FTD exhibits diverse pathologies including lysosome dysfunction, lipofuscinosis, microgliosis, and neuroinflammation. Yet, how progranulin loss causes disease remains unresolved. Here, we report that non-invasive retinal imaging of GRN-FTD patients revealed deficits in photoreceptors and the retinal pigment epithelium (RPE) that correlate with cognitive decline. Likewise, Grn-/- mice exhibit early RPE dysfunction, microglial activation, and subsequent photoreceptor loss. Super-resolution live imaging and transcriptomic analyses identified RPE mitochondria as an early driver of retinal dysfunction. Loss of mitochondrial fission protein 1 (MTFP1) in Grn-/- RPE causes mitochondrial hyperfusion and bioenergetic defects, leading to NF-kB-mediated activation of complement C3a-C3a receptor signaling, which drives further mitochondrial hyperfusion and retinal inflammation. C3aR antagonism restores RPE mitochondrial integrity and limits subretinal microglial activation. Our study identifies a previously unrecognized mechanism by which progranulin modulates mitochondrial integrity and complement-mediated neuroinflammation.

neuroscience↗

bioRxiv2024

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson's disease

The cortico-basal ganglia network in Parkinsons disease (PD) is characterized by the emergence of transient episodes of exaggerated beta frequency oscillatory synchrony known as bursts. Although it is well established that bursts of prolonged duration associate closely with motor impairments, the mechanisms leading to burst initiation remain poorly understood. Crucially, it is unclear whether there are features of basal ganglia activity which reliably predict burst onset. Current adaptive Deep Brain Stimulation (aDBS) approaches can only reactively deliver stimulation following burst detection and are unable to stimulate proactively to prevent burst onset. The discovery of predictive biomarkers could allow for such proactive stimulation, thereby offering potential for improvements in therapeutic efficacy. Here, using deep learning, we show that the timing of subthalamic nucleus (STN) beta bursts can be accurately predicted up to 60 ms prior to onset. Furthermore, we highlight that a dip in the beta amplitude - which is likely to be indicative of a phase reset of oscillatory populations occurring between 80-100 ms prior to burst onset - is a predictive biomarker for burst occurrence. These findings demonstrate proof-of-principle for the feasibility of beta burst prediction for DBS and provide insights into the mechanisms of burst initiation.

neuroscience↗

bioRxiv2024

A bispecific antibody-drug conjugate targeting pCAD and CDH17 has antitumor activity and improved tumor specificity

P-cadherin (pCAD) and LI-cadherin (CDH17) are cell surface proteins belonging to the cadherin superfamily that are both highly expressed in colorectal cancer. This co-expression profile presents a novel and attractive opportunity for a dual targeting approach using an antibody-drug conjugate (ADC). In this study, we used a unique avidity-driven in vitro screening approach to generate pCAD x CDH17 bispecific antibodies that selectively targets cells expressing both antigens over cells expressing only pCAD or only CDH17. Based off the in vitro results we selected a lead bispecific antibody to link to the cytotoxic payload MMAE to generate a pCAD x CDH17 bispecific MMAE ADC. In in vivo dual flank mouse models, we demonstrated antitumor activity of the bispecific ADC in tumors expressing both antigens, but not in tumors expressing only pCAD or only CDH17. Overall, the preclinical data presented here suggests that a pCAD x CDH17 bispecific MMAE ADC has the potential to provide clinical benefit to colorectal cancer patients.

cancer biology↗