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Oxygen-free metabolism in the bird inner retina supported by the pecten

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Abstract

Neural tissues are exceptionally sensitive to oxygen deprivation and rely on a dense network of blood vessels to support their extraordinarily high metabolic demands for oxygen, nutrients and clearance of waste products1,2,3,4. In birds, one of the metabolically most demanding neural tissue—the retina—lacks internal blood vessels5,6. This raises the question of how such a metabolically demanding neural tissue can function without blood perfusion. Here we show that, while the photoreceptor outer segments in the outer retina have access to oxygen, the inner bird retina operates under chronic anoxia, supported by anaerobic glycolysis in the retinal neurons. We provide evidence that the pecten oculi—a uniquely vascularized structure in the vitreous humour of birds, the function of which has been debated for centuries5,6,7,8,9—supplies the anoxic inner retina with glucose and removes lactic acid. We suggest that the pecten’s metabolic support of the bird retina’s anoxia tolerance enabled first the evolution of a thick cell-dense, avascular retina, which secondarily served as an exaptation enabling retinal function during high-altitude migrations.

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Fig. 1: Oxygen diffusion dynamics in the bird retina.
Fig. 2: Anaerobic glycolysis in the inner, anoxic bird retina.
Fig. 3: Metabolite and CO2 exchange of the pecten.
Fig. 4: Müller-cell-mediated nutrient exchange.
Fig. 5: Co-evolution of retinal anoxia tolerance and morphology.

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Data availability

The raw and aligned spatial and scRNA-seq data generated here are available at the Gene Expression Omnibus (GEO) (GSE309408). Comparative datasets were from lamprey (GSE236005), zebrafish (GSE237214), anole (GSE237205), chicken (GSE159107), opossum (GSE237207), ferret (GSE237203), pig (GSE237209), sheep (GSE237211), cow (GSE237202), shrew (GSE237213), marmoset (GSE237206), squirrel (GSE237212), Peromyscus (GSE237208), Phabdomys (GSE237210), macaque (PRJCA002731) and mouse (SCP2560). Processed bird and reptile data are available online (https://linlab.au.dk/Damsgaard_lab/CETA/). Imaging data of the micro-CT imaged zebra finch and green anole samples are available at Figshare61 (https://doi.org/10.6084/m9.figshare.30608753.v3). Source data are provided with this paper.

Code availability

No custom code was used in this study. All analyses were performed using standard software packages as described in the Methods.

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Acknowledgements

We thank R. Buchanan, C. Wandborg, S. Olsen and H. Meldgaard for help with animal handling; T. Mikkelsen for help with cryosectioning; J. Orthmann for technical assistance; J. J. Forst for help with one zebra finch dissection; the staff at the Core Facility Fluorescence Microscopy of the Carl von Ossietzky Universität Oldenburg, AU core facilities for bioimaging and flow cytometry; L. B. Pedersen for CO2 sensor construction, E. E. Petersen for laboratory assistance, J. B. Hurley, M. Bayley, M. Andersen and J. S. Theriault for manuscript feedback; and D. Altshuler, E. Gutierrez and L. Østergaard for project feedback. Funding was from the Carlsberg Foundation (C.D., CF18-0658; H.L., CF21-0605), the Lundbeck Foundation (C.D., R346-2020-1210; J.R.N., R480-2024-960), the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement (no. 754513) (C.D.), Aarhus University Research Foundation (C.D.), the Villum Foundation (C.D.), the Grundfos Foundation (N.P.R.), the Novo Nordisk Foundation (C.D., NNF24OC0095924; C.P.H.E., NFF20OC0063964), the Velux Foundations (H.L., 00022458), Deutsche Forschungsgemeinschaft (DFG, 395940726, SFB 1372 ‘Magnetoreception and navigation in vertebrates’; and 533653176, EXC 3051 ‘NaviSense’ to H. Mouritsen and K.D.), and the European Research Council (under the European Union’s Horizon 2020 research and innovation programme, grant agreement no. 810002, Synergy grant: QuantumBirds awarded to H. Mouritsen).

Author information

Authors and Affiliations

  1. Department of Biology, Aarhus University, Aarhus, Denmark

    Christian Damsgaard, Mia Viuf Skøtt, Catherine J. A. Williams, Hans Malte, Camilla Kruse Kidmose, Andreas H. Konradsen, Anne Sofie Stengel Rasmussen, Anna V. G. T. Mikkelsen, Katrine S. Johannsen, Niels Peter Revsbech & Tobias Wang

  2. Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark

    Christian Damsgaard, Catherine J. A. Williams & Joanna Kalucka

  3. Department of Animal and Veterinary Sciences, Aarhus University, Tjele, Denmark

    Catherine J. A. Williams

  4. Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark

    Morten Busk

  5. Neurosensory/Animal Navigation Group, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany

    Karin Dedek & Henrik Mouritsen

  6. Research Centre for Neurosensory Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany

    Karin Dedek & Henrik Mouritsen

  7. Department of Biomedicine, Aarhus University, Aarhus, Denmark

    Jesper Skovhus Thomsen, Mikkel Vendelbo, Joanna Kalucka & Lin Lin

  8. Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark

    Mikkel Vendelbo

  9. Sound Communication and Behavior Group, Department of Biology, University of Southern Denmark, Odense, Denmark

    Coen P. H. Elemans

  10. Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark

    Joanna Kalucka & Lin Lin

  11. Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Nina Kerting Iversen

  12. Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Henrik Lauridsen

  13. Core Center for Molecular Morphology, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Jens Randel Nyengaard

  14. Department of Pathology, Aarhus University Hospital, Aarhus, Denmark

    Jens Randel Nyengaard

Authors
  1. Christian Damsgaard
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  2. Mia Viuf Skøtt
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  3. Catherine J. A. Williams
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  4. Hans Malte
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  16. Henrik Mouritsen
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Contributions

C.D. proposed the study. C.D., M.V.S., C.J.A.W., H. Malte, M.B., K.D., M.V., H. Mouritsen, J.K., L.L., N.K.I., T.W., H.L. and J.R.N. designed the experiments. C.D., M.V.S., C.J.A.W., C.K.K. and A.H.K. measured retinal gases. M.V.S., M.B. and K.D. performed tissue staining and imaging. H. Malte performed oxygen diffusion modelling. C.D. and M.B. performed autoradiography. C.D. performed spatial and single-cell transcriptomics. C.K.K. and A.V.G.T.M. measured metabolite levels. C.D., A.S.S.R., J.S.T. and H.L. performed micro-CT imaging. C.D., M.B., C.P.H.E., N.P.R., M.V., H. Mouritsen, J.K., L.L., T.W., H.L. and J.R.N. contributed essential resources, infrastructure and funding. C.D., M.V.S., H. Malte, C.K.K., M.B., K.D., H. Mouritsen, K.S.J., L.L. and H.L. analysed the experimental data. C.D. prepared the paper with input from all of the authors.

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Correspondence to Christian Damsgaard.

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Nature thanks Michael Berenbrink, Tom Baden, Rui Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Structure of the avian pecten oculi and reptilian conus papillaris.

a, transversal virtual slices and maximum intensity projections (MIP) of diffusible iodine-based contrast-enhanced micro-CT images showing the pecten oculi of the avian zebrafinch (Taeniopygia guttata) (left, n = 1) and the conus papillaris of reptilian green anole (Anolis carolinensis) (right, n = 1). While the pecten oculi presents as a feather-like structure with a large surface area, the conus papillaris is a smaller cone-like structure. b, model of the arterial blood supply to the pecten oculi in the zebra finch from vascular casting followed by micro-CT imaging. The arterial blood supply to the pecten oculi derives from the ophthalmotemporal artery originating in the rete opthalmicum, which is ultimately supplied by the common carotid artery. The fully interactive model (rotate, pan, zoom, toggle layers, adjust transparency) is provided separately as Supplementary 3D Model 1 (3D PDF).

Extended Data Fig. 2 Spatial distribution of redox metabolism in the bird retina.

a, Modelled in vivo \({{p}}_{{{\rm{O}}}_{2}}\) mapped onto tissue sections. b-d, Tissue mapping of aggregated gene expression scores for genes associated with glycolysis, pentose phosphate pathway, and glutathione metabolism shows that glycolysis is not linked to redox metabolism (n = 4). e-h, This conclusion was supported by uniform expression patterns of SOD1, SOD2, CAT, and TXN. Expression levels of individual genes represent unitless variance-stabilized expression values, adjusted for sequencing depth across spots. Pathway scores are unitless enrichment scores calculated from the average expression of all genes in a pathway relative to a set of randomly selected control genes.

Extended Data Fig. 3 Single cell atlas of zebra finch retinal cells.

Gene expression markers of the major retinal cell types in zebra finches (n = 6 birds, 40,496 cells). Dots are colour-coded for average expression levels, and dot sizes are proportional to the proportion of cells of each cell type with non-zero expression.

Source data

Extended Data Fig. 4 Metabolite transport expression in vertebrate Müller glia cells.

a, Phylogenetic relationship among species included in the analysis. b, gene expression pattern of key metabolite transporter genes in Müller glia cells shows high expression of GLUT1 and MCT1 in bird Müller glia cells. Dots are colour-coded for average expression levels, and dot sizes are proportional to the proportion of cells of each cell type with non-zero expression. Data are from this study (zebra finch) and published studies57,58,59.

Source data

Extended Data Fig. 5 Vimentin is a marker for Müller cells in the zebra finch retina.

a, Sox2 labels Müller cell nuclei which show a distinct shape and are surrounded by GluR1 positive membranes (arrowheads), spanning from the nerve fibre layer to the end of the outer nuclear layer. b, GluR1 and vimentin almost fully colocalize in the zebra finch retina (arrowheads), establishing vimentin as a marker for Müller cells in this species. For these stainings, the retina was fixed in 2% paraformaldehyde. Areas marked by rectangles are shown in higher magnification. GCL, ganglion cell layer; INL/IPL, inner nuclear/plexiform layer; NFL, nerve fibre layer; ONL, outer nuclear layer. Scale bars: 20 µm; higher magnification images: 10 µm. n = 2.

Extended Data Fig. 6 Specificity of GLUT1 and MCT1 antibodies.

a, An anti-GLUT1 antibody from guinea pig (Synaptic Systems, 419 005), which targeted a different epitope in the GLUT1 protein as the one used in Fig. 4b (Alomone, AGT-021), also labelled Müller glia cells (visualized by GluR1) with prominent GLUT1 staining in Müller cell endfeet. b, Pre-adsorption of the GLUT1 antibody (Alomone) with the immunization peptide eliminated the Müller cell staining, leaving a weak staining in the outer plexiform layer (asterisk) which is likely unspecific. Secondary antibody control for the GLUT1 staining (obtained by omitting the primary antibody). c, Pre-adsorption of the MCT antibody (Alomone) with the immunization peptide eliminated the Müller cell staining and the nucleic staining in the inner nuclear and ganglion cell layer. Blastp analysis revealed a homology of the antibody to Sox12 and Sox11 which are expressed in both layers in the chicken retina (data based on Yamagata et al., 2021). Secondary antibody control for the MCT1 staining (obtained by omitting the primary antibody). Please note that confocal stacks for GLUT1/MCT1, pre-adsorbed antibodies, and secondary antibody controls were scanned and processed identically. Images were not filtered. GCL, ganglion cell layer; INL/IPL, inner nuclear/plexiform layer; NFL, nerve fibre layer; ONL, outer nuclear layer. Scale bars: 20 µm. n = 2.

Extended Data Fig. 7 Similar gene expression profiles of the conus and pecten.

a) Integration and cluster analysis of gene expression spots group ocular tissues from zebra finches (b, n = 4), pigeons (c, n = 1), chickens (d, n = 1), and anoles (e, n = 2) into 17 gene expression clusters. Mapping the gene expression clusters back to tissue morphology identifies distinct gene expression clusters of the pecten/conus, retina, and optical nerve head.

Extended Data Fig. 8 Transcript distribution in the birds’ pecten and anole conus.

a,c,e,g,i,k,m,o,q,s,u,x, Tissue sections of zebra finch (n = 4), pigeon (n = 1), chicken (n = 1), and green anole (n = 1) eyes colour-coded for expression of the glucose transporter GLUT1 (SLC2A1; a,g,m,s), monocarboxylate transporter MCT1 (SLC16A1; c,i,o,u) and carbonic anhydrase 4 (CA4; e,k,q,x). Expression levels represent unitless variance-stabilized expression values, adjusted for sequencing depth across spots. b,d,f,h,j,l,n,p,r,t,v,y, Violin plots showing variance-stabilized expression levels across gene-expression spots covering the pecten (birds) or conus (anole) (red) and the neural retina (yellow) for the corresponding genes. Note that panels for the zebra finch in a-f are from Fig. 3 and are included here for comparison with pigeon, chicken, and anoles.

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Extended Data Fig. 9 Model fits for estimating retinal oxygen consumption.

Measured (blue points) and modelled (red lines) oxygen partial pressure profiles were used to estimate the uninhibited and realized oxygen consumption rates of the retina and the oxygen fluxes from the choroid and the pecten. The 11 panels show the data from 11 individual anaesthetized zebra finches measured during ventilation with air. Data are plotted as a function of eye radius, where r = 0.18 cm represents the position of the choroid.

Extended Data Table 1 Summary of species-specific anaesthesia and instrumentation
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Supplementary information

Supplementary Information

Supplementary Information 1–3, Supplementary Fig. 1 and Supplementary references. Detailed descriptions of the oxygen diffusion modelling (finite element calculations, boundary conditions, and O2 flux estimates), the construction, calibration and application of Clark-type CO2 microsensors, and a representative flow cytometry dot plot.

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Supplementary Data 1

Interactive micro-CT model of the arterial blood supply to the zebra finch pecten oculi. Users can rotate, pan, zoom and toggle layers, including adjusting transparency. Requires desktop Adobe Acrobat/Reader with 3D content enabled.

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Damsgaard, C., Skøtt, M.V., Williams, C.J.A. et al. Oxygen-free metabolism in the bird inner retina supported by the pecten. Nature (2026). https://doi.org/10.1038/s41586-025-09978-w

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