About

Uri Manor, PhD, is the Principal Investigator of the Manor Lab at UCSD. Born with severe-to-profound hearing loss and a beneficiary of hearing aids, Uri has a profound personal connection to the biological mechanisms of health and disease. His research is focused on the development and application of new technologies to better understand biological systems in both health and disease, with a particular emphasis on deep learning-based imaging methods, the cytoskeleton, and organelle dynamics. His major areas of study include neurodegeneration, hearing loss, and cancer. Uri's work aims to leverage technological advances to facilitate improved understanding and treatment of these conditions. Outside of his scientific pursuits, Uri enjoys spending time with his family, listening to stand-up comedy, long bike rides, running on the beach, playing guitar, and photography.

Research topics

• Chemistry
• Biochemistry
• Biology
• Cell biology
• Computer Science
• Artificial Intelligence
• Biophysics
• Cancer research
• Nanotechnology
• Computer vision
• Neuroscience
• Materials science

Selected publications

• Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-08

  articleOpen access

  , an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload. Highlights: Cellouette provides accurate segmentation for single-cell spatial transcriptomics in cardiac tissue.Pressure overload creates spatial gradients of cardiomyocyte pro-fibrotic states.Cardiomyocyte pro-fibrotic progression is linked to changes in local cell composition and gene expression.Transcriptional states of non-muscle cells predict metabolic state of adjacent cardiomyocytes.

  PublisherDOI

• Endosome-generated interior actin network regulates mitotic fidelity and organelle homeostasis downstream of P-cadherin

  Research Square · 2026-04-27

  preprintOpen access
  PublisherOA PDFDOI

• The COX2-PGE2-PKA Axis Suppresses Antiviral Immunity by Inhibiting mtDNA-Dependent STING Activation

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-06

  articleOpen access

  SUMMARY The innate immune cGAS-STING pathway is activated by cytosolic double-stranded DNA (dsDNA) to induce type I interferon (IFN) response, which is essential for mounting the antiviral response. However, STING activation during viral infection is often insufficient to achieve complete viral clearance, suggesting the existence of additional mechanisms that evade its activity. Here, we identified COX2/PGE 2 as a negative regulator of STING activation, particularly in response to arising cytosolic mitochondrial DNA (mtDNA) generated during HSV-1 infection. Mechanistically, PGE 2 , through the EP4-cAMP-PKA axis, induces mitophagy to remove defective mitochondria and hence prevent the accumulation of immunostimulatory cytosolic mtDNA, thereby dampening STING-mediated type I IFN and antiviral response. Furthermore, we identified STOML2 as a downstream target of PKA that connects mitochondrial quality control with the regulation of innate immune signaling. Together, our findings establish the COX2/PGE 2 /PKA axis as a negative regulator of mtDNA-STING signaling that may be targeted to potentiate STING-mediated type I IFN and innate immunity. Abstract Figure Graphical abstract

  PublisherDOI

• An Open-Source Deep Learning-Based GUI Toolbox for Automated Auditory Brainstem Response Analyses (ABRA)

  Research Square · 2025-06-20 · 1 citations

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• Mitochondria- and ER-associated actin are required for mitochondrial fusion

  Nature Communications · 2025-01-07 · 51 citations

  articleOpen access

  Mitochondria are crucial for cellular metabolism and signalling. Mitochondrial activity is modulated by mitochondrial fission and fusion, which are required to properly balance metabolic functions, transfer material between mitochondria, and remove defective mitochondria. Mitochondrial fission occurs at mitochondria-endoplasmic reticulum (ER) contact sites, and requires the formation of actin filaments that drive mitochondrial constriction and the recruitment of the fission protein DRP1. The role of actin in mitochondrial fusion remains entirely unexplored. Here we show that preventing actin polymerisation on either mitochondria or the ER disrupts both fission and fusion. We show that fusion but not fission is dependent on Arp2/3, whereas both fission and fusion require INF2 formin-dependent actin polymerization. We also show that mitochondria-associated actin marks fusion sites prior to the fusion protein MFN2. Together, our work introduces a method for perturbing organelle-associated actin and demonstrates a previously unknown role for actin in mitochondrial fusion.

  PublisherOA PDFDOI

• ZBTB11 depletion targets metabolic vulnerabilities in KRAS inhibitor-resistant PDAC

  Nature Chemical Biology · 2025-08-11 · 3 citations

  articleOpen access
  PublisherOA PDFDOI

• PSSR2: a user-friendly Python package for democratizing deep learning-based point-scanning super-resolution microscopy

  BMC Methods · 2025-01-02 · 2 citations

  articleOpen accessSenior author

  Background: To address the limitations of large-scale high quality microscopy image acquisition, PSSR (Point-Scanning Super-Resolution) was introduced to enhance easily acquired low quality microscopy data to a higher quality using deep learning-based methods. However, while PSSR was released as open-source, it was difficult for users to implement into their workflows due to an outdated codebase, limiting its usage by prospective users. Additionally, while the data enhancements provided by PSSR were significant, there was still potential for further improvement. Methods: To overcome this, we introduce PSSR2, a redesigned implementation of PSSR workflows and methods built to put state-of-the-art technology into the hands of the general microscopy and biology research community. PSSR2 enables user-friendly implementation of super-resolution workflows for simultaneous super-resolution and denoising of undersampled microscopy data, especially through its integrated Command Line Interface and Napari plugin. PSSR2 improves and expands upon previously established PSSR algorithms, mainly through improvements in the semi-synthetic data generation ("crappification") and training processes. Results: In benchmarking PSSR2 on a test dataset of paired high and low resolution electron microscopy images, PSSR2 super-resolves high-resolution images from low-resolution images to a significantly higher accuracy than PSSR. The super-resolved images are also more visually representative of real-world high-resolution images. Discussion: The improvements in PSSR2, in providing higher quality images, should improve the performance of downstream analyses. We note that for accurate super-resolution, PSSR2 models should only be applied to super-resolve data sufficiently similar to training data and should be validated against real-world ground truth data.

  PublisherOA PDFDOI

• Astrocyte glypican 5 regulates synapse maturation and stabilization

  Cell Reports · 2025-03-01 · 13 citations

  articleOpen access

  The maturation and stabilization of appropriate synaptic connections is a vital step in neural circuit development; however, the molecular signals underlying these processes are not fully understood. We show that astrocytes, through production of glypican 5 (GPC5), are required for maturation and refinement of synapses in the mouse cortex during the critical period. In the absence of astrocyte GPC5, thalamocortical synapses show structural immaturity, including smaller presynaptic terminals, decreased postsynaptic density area, and presence of more postsynaptic partners at multisynaptic connections. This structural immaturity is accompanied by a delay in developmental incorporation of GLUA2-containing AMPARs at intracortical synapses. The functional impact of this is that mice lacking astrocyte GPC5 exhibit increased levels of ocular dominance plasticity in adulthood. This demonstrates that astrocyte GPC5 is necessary for maturation and stabilization of synaptic connections, which has implications for disorders with altered synaptic function where GPC5 levels are altered, including Alzheimer's disease and frontotemporal dementia.

  PublisherDOI

• Molecular design of a therapeutic LSD analogue with reduced hallucinogenic potential

  Proceedings of the National Academy of Sciences · 2025-04-14 · 28 citations

  articleOpen access

  Decreased dendritic spine density in the cortex is a key pathological feature of neuropsychiatric diseases including depression, addiction, and schizophrenia (SCZ). Psychedelics possess a remarkable ability to promote cortical neuron growth and increase spine density; however, these compounds are contraindicated for patients with SCZ or a family history of psychosis. Here, we report the molecular design and de novo total synthesis of (+)-JRT, a structural analogue of lysergic acid diethylamide (LSD) with lower hallucinogenic potential and potent neuroplasticity-promoting properties. In addition to promoting spinogenesis in the cortex, (+)-JRT produces therapeutic effects in behavioral assays relevant to depression and cognition without exacerbating behavioral and gene expression signatures relevant to psychosis. This work underscores the potential of nonhallucinogenic psychoplastogens for treating diseases where the use of psychedelics presents significant safety concerns.

  PublisherOA PDFDOI

• Roadmap on deep learning for microscopy

  Journal of Physics Photonics · 2025-10-06 · 2 citations

  preprintOpen access

  Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

  PublisherDOI

Recent grants

• A Novel Model System for Restoring Hearing in vivo

  NIH · $505k · 2020–2022

Frequent coauthors

• David B. Rosenberg

  Harvard University

  41 shared

• Richard T. Osgood

  Massachusetts Eye and Ear Infirmary

  38 shared

• Yushi Hayashi

  Massachusetts Eye and Ear Infirmary

  38 shared

• Leonardo R. Andrade

  38 shared

• Christopher J. Buswinka

  Eaton (United States)

  38 shared

• Artur A. Indzhykulian

  Harvard University

  37 shared

• Pierrick Bordiga

  Massachusetts Eye and Ear Infirmary

  37 shared

• Bechara Kachar

  37 shared

Labs

• Manor LabPI

Awards & honors

• Chan-Zuckerberg Imaging Scientist Award