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Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis

Nature Neuroscience (2024)Cite this article

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Abstract

The generation of new myelin-forming oligodendrocytes in the adult central nervous system is critical for cognitive function and regeneration following injury. Oligodendrogenesis varies between gray and white matter regions, suggesting that local cues drive regional differences in myelination and the capacity for regeneration. However, the layer- and region-specific regulation of oligodendrocyte populations is unclear due to the inability to monitor deep brain structures in vivo. Here we harnessed the superior imaging depth of three-photon microscopy to permit long-term, longitudinal in vivo three-photon imaging of the entire cortical column and subcortical white matter in adult mice. We find that cortical oligodendrocyte populations expand at a higher rate in the adult brain than those of the white matter. Following demyelination, oligodendrocyte replacement is enhanced in the white matter, while the deep cortical layers show deficits in regenerative oligodendrogenesis and the restoration of transcriptional heterogeneity. Together, our findings demonstrate that regional microenvironments regulate oligodendrocyte population dynamics and heterogeneity in the healthy and diseased brain.

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Fig. 1: Three-photon microscopy enhances the detection of oligodendrocytes and myelin deep in the adult mouse brain.
Fig. 2: Optimization of excitation parameters permits long-term three-photon microscopy without tissue damage.
Fig. 3: Long-term three-photon imaging does not perturb damage markers or oligodendrogenesis.
Fig. 4: Region-specific differences in oligodendrogenesis correlate with transcriptional heterogeneity.
Fig. 5: Cuprizone affects gray and white matter oligodendrocyte populations similarly.
Fig. 6: Oligodendrocyte replacement is enhanced in the white matter and partially restores regional heterogeneity.
Fig. 7: Layer-specific differences in oligodendrogenesis correlate with changes in molecular heterogeneity.
Fig. 8: Decreased oligodendrogenesis and recovery of molecular identity in deep layers 5–6.

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Data availability

All data that support the findings, tools, and reagents will be shared on an unrestricted basis; requests should be directed to the corresponding author.

Code availability

Code for analysis associated with the manuscript is available at https://github.com/EthanHughesLab/; RNAScope analysis scripts are available at https://github.com/sbudoff/. The code to measure the brightest n% of pixels through a z-stack or time series was modified from macro scripts available via the NYU Imaging Core website https://microscopynotes.com/imagej/. The AO image optimization and plotting scripts are available at the Intelligent Imaging Innovations (3i) Github at https://github.com/3i-microscopes/Adaptive-Optics.

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Acknowledgements

We thank M. Hall for machining expertise, A. Scallon and the University of Colorado Anschutz Optogenetics and Neural Engineering Core (P30NS048154) for 3D printing and stage design, past and current members of the Hughes Lab and the University of Colorado Anschutz Myelin Research Group for discussions, J. Siegenthaler and S. Bonney (Andy Shih Lab) for helpful discussions on the vascular and pericyte analyses. M. Cammer for assistance with the histogram measurement ImageJ macros (New York University Langone Health Imaging Core). D. Stitch and the University of Colorado Anschutz Medical Campus Advanced Light Microscopy Core Facility of the NeuroTechnology Center that is supported in part by Rocky Mountain Neurological Disorders Core (P30NS048154) and by Diabetes Research Center (P30DK116073) for assistance with RNAScope imaging. Funding was provided by the National Institute of Neurological Disorders and Stroke (F31NS120540) to M.A.T. Funding was provided by the University of Colorado Department of Cell and Developmental Biology Pilot grant, the Whitehall Foundation and the National Multiple Sclerosis Society (RG-1701–26733) and National Institute of Neurological Disorders and Stroke (NS115975, NS125230 and NS132859) to E.G.H. Funding was provided by the National Institute of Neurological Disorders and Stroke (R01 NS118188 and UF1 NS116241) and the National Science Foundation (BCS-1926676) to E.A.G. and D.R. Funding was provided by the National Institutes of Health National Eye Institute (R01 EY030841) to A.P.-P.

Author information

Authors and Affiliations

  1. Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Michael A. Thornton, Michael E. Stockton, Alexandra N. Ramirez, Diego Restrepo & Ethan G. Hughes

  2. Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Gregory L. Futia & Emily A. Gibson

  3. Physiology and Biophysics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Samuel A. Budoff & Alon Poleg-Polsky

  4. Intelligent Imaging Innovations, Denver, CO, USA

    Baris Ozbay, Omer Tzang & Karl Kilborn

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Contributions

E.G.H. and M.A.T. conceived the project. M.A.T. designed and performed experiments, analyzed data and generated all figures. G.L.F. and E.A.G. built the three-photon microscope. M.E.S., S.A.B. and M.A.T. performed the RNA ISH labeling and imaging experiments. M.E.S. and S.A.B. analyzed the RNA ISH data. M.E.S. contributed images and data to Figs. 4–8 and Extended Data Figs. 7 and 9. S.A.B. contributed images and data to Figs. 4–7 and Extended Data Figs. 7 and 9 and wrote the R code to analyze the QuPath output datasets (see ‘Code availability’). A.N.R. performed experiments and analyzed data for Figs. 2 and 3 and Extended Data Figs. 4 and 5. B.O., O.T. and K.K. developed the software and helped with three-photon microscope setup and expertise. E.A.G., D.R. and E.G.H. supervised the three-photon microscope development and application. E.A.G., D.R., A.P.-P. and E.G.H. secured funding and E.G.H. supervised the project. M.A.T. and E.G.H. wrote the paper with input from other authors.

Corresponding author

Correspondence to Ethan G. Hughes.

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Competing interests

K.K. is a co-founder and part-owner of 3i. The other authors declare no competing financial interests.

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Nature Neuroscience thanks Erin Gibson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Custom three-photon light path and modifications for longitudinal in vivo imaging.

3P excitation source and light path, including motorized half-wave plate for power modulation (λ/2), Glan-Thompson polarizer (GT), dual prism compressor, beam expanding telescope, ALPAO deformable mirror, beam reduction lens relay, galvo-galvo scan mirrors, scan lens, tube lens, dichroic mirror (FF-488-di02, cut at 488 nm), and moveable objective microscope system with collection filters for third harmonic generation signal (430/25 nm, PMT1) and EGFP emission (520/70 nm, PMT2).

Extended Data Fig. 2 Mobp-EGFP and THG labeling of mature oligodendrocytes and myelin in the cortex and subcortical white matter.

a) Confocal image of a tissue section from the deep posterior parietal cortex stained for transgenic Mobp-EGFP and ASPA. Arrowheads show large, putative newly-generated oligodendrocytes that are MOBP-EGFP-positive and ASPA-negative. b) Confocal image of ASPA/Mobp-EGFP immunofluorescence in the subcortical white matter beneath the posterior parietal cortex (dotted white lines). Arrowheads show Mobp-EGFP-positive and ASPA-negative white matter oligodendrocytes of varying sizes and brightness. c) 99.5% (cortex) and 99.6% (white matter) of ASPA-positive cells express MOBP-EGFP. n = 4 mice, 2 sections per mouse. d) 95.6% (cortex) vs. 86.5% (white matter) of Mobp-EGFP-positive oligodendrocytes were also positive for ASPA (Unpaired, two-tailed Student’s t-test for equal variance, p = 0.016). n = 4 mice, 2 sections per mouse. e) 9 μm z-projection of layer 1 in the posterior parietal cortex showing Mobp-EGFP labeling of myelin sheaths (green) and THG-labeling of myelin sheaths and blood vessels (magenta). f) Zoom image of an isolated EGFP/THG-labeled myelin sheath from the white box in (e) excited with 1300 nm three-photon excitation. g) Isolated Mobp-EGFP sheath from layer 1 of a separate mouse visualized with 920 nm two-photon excitation combined with Spectral Confocal Reflectance (SCoRe) microscopy. Note the decreased THG/SCoRe labeling at putative nodes of Ranvier in (f) and (g) (arrowheads). h) 9 μm z-projection of a single mature oligodendrocyte in layer 1 from a third mouse showing EGFP-labeled processes connected to multiple THG-labeled sheaths. i) 5-pixel line intensity plot from the white line drawn in (d) showing relative fluorescence intensity of EGFP- and THG-labeled myelin sheaths and a THG-labeled blood vessel (arrowhead). All images pixel size = 0.36 μm. *p < 0.05, box plots represent the median, interquartile ranges and minimum/maximum values.

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Extended Data Fig. 3 Adaptive optics improves SBR and axial resolution in the subcortical white matter.

a) System adaptive optics (AO) correction with a two-dimensional 1.0 µm red polychromatic microsphere sample. Lateral (top) and axial (bottom) projections show a slight enhancement in peak signal after AO correction for system aberrations (8% increase, lateral; 9% increase, axial). The bead sample was diluted 1:10000, coverslipped with Prolong Gold, and the average power at the sample was <0.3 mW. System resolution = 0.88 µm (lateral) and 2.55 µm (axial) as calculated by the full width at half maximum of the gaussian fit after system AO correction. b) Deformable mirror (DM) amplitude plot showing the optimized stroke amplitudes (units = µm RMS) for each Zernike Mode in the system AO correction. c) In vivo, indirect, modal adaptive optics (AO) corrections were made at 775–825 µm depth (just above the white matter) by optimizing on the mean intensity of the third harmonic generation channel. The in vivo AO correction revealed cross sections through myelinated axons just dorsal to the corpus callosum (white dotted selection, top, 800 µm) and increased the mean intensity of EGFP-positive oligodendrocytes in the white matter ventral to the plane of the AO correction (bottom, 835 µm). Example images are single-slice images at the depth of the AO correction, 0.14 µm / pixel. d) Deformable mirror (DM) amplitude plot showing the optimized stroke amplitudes (units = µm RMS) for each Zernike Mode in the in vivo AO correction shown in (c). e) (Left) XY (top) and XZ (bottom) projections for a single EGFP-positive OL cell body from the example image shown in (c). (Right) Lateral and axial Gaussian fits of OL cell bodies from the field of view in (c). f) The peak intensity of the EGFP-oligodendrocyte signal was significantly enhanced by the AO correction (Paired, two-tailed Student’s t-test, p = 0.0002, n = 2 mice, 11 cells). g) The axial resolution of EGFP-oligodendrocyte cell bodies was significantly enhanced by the AO correction (Paired, two-tailed Student’s t-test, p = 0.014, n = 2 mice, 11 cells). h) AO correction enhances the peak intensity of OL processes by 202% (n = 2 mice, 4 processes). i) Average power vs. depth plot shows the average power at the sample through the depth of the white matter after AO correction (black, left), and the theoretical power curve (gray, right) necessary to maintain the same signal to background ratio without AO. Data are represented as individual points and mean ± SEM. Curves in a, e, and h represent the mean of the gaussian fits for each analyzed region (cell bodies in a, e, cell processes in h) with 95% confidence intervals. The intensity was integrated over a line plotted through the center of the cell structure (10 µm wide, cell bodies, 1 µm wide, processes). Zernike modes in (b), (d) = Spherical (12), Horizontal Trefoil (9), Horizontal Coma (8), Vertical Coma (7), Oblique Trefoil (6), Astigmatism (5), Oblique Astigmatism (3). For detailed statistics, see Supplementary Table 3.

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Extended Data Fig. 4 Mechanical, scanning, and optical modifications to increase 3P signal and decrease average power.

a) The third harmonic generation (THG) signal at the surface of the cranial window was used to align the preparation orthogonally to the excitation light. b) Scanning modifications to increase SBR and decrease average power to mitigate risk of tissue damage. Frame averaging was advantageous compared to increasing the pixel dwell time to reduce risk of nonlinear damage. Z-stack acquisition was paused periodically to allow for heat dissipation (1 min. pause per 3 min. scanning). Laser pulses were blanked on the galvanometer overscan to reduce the average power applied to the preparation at each z-plane. c) Imaged-based AO correction increased SBR at depth (left) and modulating the spherical aberration correction linearly with depth improved SBR throughout the imaging volume (right). For longitudinal imaging, the AO correction was made before acquiring each time point at the same z-plane just above the scattering white matter (750–850 µm depth).

Extended Data Fig. 5 Calculation of mouse-specific effective attenuation lengths in the posterior parietal cortex.

a) The mean intensity of the top 1% of the brightest pixels (experimental 3P signal) plotted with depth beneath the brain surface for an example mouse. b) Data from the mouse shown in (a) normalized to the cube of the pulse energy shows the decay of the 3P signal with depth in the mouse brain. c) Logarithm of the data in (b) shows a linear decrease with depth. The single mouse-specific effective attenuation length (EAL) can be calculated from the slope of the linear fit (gray = gray matter, blue = white matter). A steeper slope represents a shorter EAL due to increased scattering. d) Semilogarithmic plot showing gray matter and white matter EALs for n = 10 mice at the first time point of longitudinal imaging. Mean EAL (GM) = 249 ± 12.7 µm, Mean EAL (WM) = 169 ± 8.9 µm. e) Distributions of experimental mouse-specific EALs in the gray matter (gray) and white matter (blue). n = 10 mice. Linear fits (black line plots in c, d) were calculated separately by region. Box plots represent the median, interquartile ranges and minimum/maximum values.

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Extended Data Fig. 6 Optimized longitudinal three-photon imaging does not increase glial, neuronal, or vascular reactivity.

a) Related to Fig. 3. Coronal brain section from the imaged (right) and contralateral (left) posterior parietal cortex (PPC) of a mouse that was perfused 24 hrs. following 10 weeks of chronic 3P imaging. b) Coronal brain section from the imaged (right) and contralateral (left) posterior parietal cortex (PPC) of a mouse that received supra-threshold excitation across the cortex and white matter to generate laser-induced positive control tissue (laser injury, right). c) High-resolution confocal images of the contralateral (left), longitudinal imaging field (middle) and laser-induced injury (right) regions in the deep cortical layers of the PPC, stained for transgenic Mobp-EGFP expression (mature oligodendrocytes), Iba-1 (microglia), GFAP (reactive astrocytes), 8-hydroxyguanosine (8-OHG, neuronal RNA oxidation), and CD13/Lectin-49 (pericytes, vasculature, respectively). All images were taken with identical power settings, processed with a 100-pixel rolling ball background subtraction and 0.7 pixel gaussian blur, and brightness/contrast correction was applied identically across channels. The bottom row shows an example of the trainable WEKA segmentation to measure pericytes (green) and vascular coverage (magenta, see Methods). Note the Lectin-positive microglia-like cells present in the laser injury vasculature image (white arrowheads). d) No difference in the density of Mobp-EGFP OLs between the contralateral and imaged regions in healthy mice. e) No difference in the density of Mobp-EGFP OLs between the contralateral and imaged regions in laser-induced injury tissue. f) The ratio of the EGFP mean intensity for the imaged:contralateral (contra.) hemispheres was ~1 for healthy mice and did not change significantly in the positive control tissue. g) No difference in the density of Iba-1 microglia (MG) between the contralateral and imaged regions in healthy mice. h) Density of Iba-1 MG is significantly increased on the ipsilateral side of laser-induced injury tissue (p = 0.016). i) The ratio of the imaged:contralateral Iba-1 mean intensity was ~1 for healthy mice and significantly increased in positive controls (p = 0.026). j) No difference in the density of GFAP-positive reactive astrocytes (rAstros) between the contralateral and imaged regions in healthy mice. k) Density of GFAP+ rAstros is significantly increased on the damaged side in laser-induced injury tissue (p = 0.017). l) The ratio of the imaged:contralateral (contra.) GFAP mean intensity was ~1 for healthy mice and was significantly increased in positive controls (p = 0.037). m) No difference in the density of 8-OHG-positive neurons after auto-thresholding (see Methods) between the contralateral and imaged regions in healthy mice. n) No difference in the density of 8-OHG-positive neurons between contralateral and imaged regions in laser-induced injury tissue. o) No difference in the imaged:contralateral ratio of 8-OHG mean intensities between healthy vs. laser-damaged mice. p) No difference in vessel coverage (% positive pixels) between the contralateral and imaged hemispheres of healthy multi-month longitudinal 3P imaging mice. q) Increase in vessel coverage (%) on the ipsilateral hemisphere of laser-induced injury positive control mice (p = 0.022). r) No difference in the density of pericytes between the contra. and ipsi. hemispheres of healthy long-term 3P mice. s) No difference in the density of pericytes between the contra. and ipsi. hemispheres of laser-induced injury mice. *p < 0.05, **p < 0.01, n.s., not significant; n = 5 mice (healthy longitudinal), 5 mice (laser-induced injury), 2 sections, 4 hemispheres per condition. Statistical comparisons in d, e, g-h, j-k, m-n, and p-s were made with paired, two-sided Student’s t-tests (parametric) or two-sided Wilcoxon signed-rank test (nonparametric). Statistical comparisons in f,i,l,o were made with unpaired two-sided Student’s t-tests for equal/unequal variances (parametric) or two-sided Wilcoxon rank sum test (nonparametric). Box plots represent the median, interquartile ranges and minimum/maximum values. For detailed statistics, see Supplementary Table 3.

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Extended Data Fig. 7 Immunofluorescent and in situ hybridization techniques allow for probing OPC proliferation and oligodendrocyte subpopulations in the cortex and subcortical white matter.

a) Experimental timeline of tissue collection for EdU and RNAScope analyses in healthy and cuprizone mice. Healthy Mobp-EGFP mice were injected with 5 mg/kg of the thymidine analog EdU twice a day (10–12 hr. interval) for seven days starting at P70 and perfused the following day. Healthy Mobp-EGFP mice were perfused at P60 and P140 to assess aging-dependent changes in adult oligodendrocyte subpopulations. Mobp-EGFP mice that were fed 0.2% cuprizone for three weeks were perfused at 4 days post-cuprizone removal (peak demyelination, matched to in vivo imaging data; Fig. 4), and 7 weeks post-cuprizone removal (regeneration, matched to the final time point of in vivo imaging, see timeline; Fig. 4). b) EdU-positive proliferated OPCs in the posterior parietal cortex (top, GM) and subcortical white matter (bottom, WM, dashed border). c) The density of PDGFR-α-positive OPCs was significantly increased in the WM compared to the GM (248.6 ± 23.8 vs. 181.2 ± 7.7, Unpaired, two-tailed Student’s t-test for equal variance, t(6) = 2.69, p = 0.036). d) The percentage PDGFR-α + /EdU+ OPCs is increased in the WM compared to the GM (Unpaired, two-tailed Student’s t-test for equal variance, 51.6 ± 6.6 vs. 14.6 ± 2.5, t(6) = 5.29, p = 0.002). e) Coronal sections from the mid-thoracic spinal cord of healthy Mobp-EGFP mice were taken at P140 and run in parallel with brain sections to confirm the labeling specificity of our oligodendrocyte subpopulation probe-set (Egr2, MOL1, cyan; Klk6, MOL2/3, magenta; Ptgds, MOL5/6, orange). f) Egr2 and Ptgds preferentially label oligodendrocytes in the spinal gray matter, while Klk6 predominantly labels oligodendrocytes in the spinal white matter (Unpaired, two-tailed students t-test for unequal variance). g) Coronal sections from the posterior parietal cortex of Mobp-EGFP mice (−1.7 to −2.3 mm posterior and 1 to 3 mm lateral to bregma) showing the pattern of OL subpopulation labeling at the experimental time points described in (a). *p < 0.05, **p < 0.01, n = 4 mice, 4 sections per mouse. Boxplots represent the median, interquartile range and the minimum and maximum values. For detailed statistics, see Supplementary Table 3.

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Extended Data Fig. 8 Modeling oligodendrocyte growth, loss, and regeneration in adult mouse cortex and white matter.

a, b) Cumulative oligodendrocyte population growth (% gain over time) in the healthy brain was modeled using asymptote-restricted exponential mechanistic growth curve-fitting. a) Cumulative OL gain (%) and mechanistic growth fit in the gray matter (left) and the white matter (right) for an example mouse. b) Cumulative OL gain (%) and mechanistic growth fits in the gray matter (left) and the white matter (right) for the healthy group (n = 6 mice). c, d) Cumulative oligodendrocyte population loss (% loss over time) due to cuprizone administration was modeled using three-parameter Gompertz Sigmoid curve-fitting. c) Cumulative OL loss (%) and three-parameter Gompertz curves in the gray matter (left) and the white matter (right) for an example mouse. d) Cumulative OL loss (%) and three-parameter Gompertz curves in the gray matter (left) and the white matter (right) for the cuprizone de/remyelination group (n = 6 mice). e, f) Cumulative oligodendrocyte population regeneration (% cell replacement over time) following cuprizone cessation was modeled using three-parameter Gompertz Sigmoid curve-fitting. e) Cumulative OL replacement (%) and three-parameter Gompertz curves in the gray matter (left) and the white matter (right) for an example mouse. f) Cumulative OL replacement (%) and three-paramter Gompertz curves in the gray matter (left) and the white matter (right) for the cuprizone de/remyelination group (n = 6 mice). Modeled rate and timing metrics in Main Figs. 4–7 were calculated by fitting curves to data from individual mice and then extracting summary data (for example timing of inflection point).

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Extended Data Fig. 9 Layer and region-dependent proportions of MOL1, MOL2/3, and MOL5/6 across healthy aging and cuprizone treatment.

Related to Figs. 7,8. a) Raw counts of the total # of segmented Mobp-EGFP OLs (top), MOL1+ OLs (row 2), MOL2/3+ OLs (row 3) and MOL5/6+ OLs (bottom) across cortical and subcortical layers (x-axes) and experimental time points (shaded background colors). Data are from n = 6 mice (Healthy P60), n = 8 mice (Healthy P140), n = 5 mice (Cup. + 4 days) and n = 7 mice (Cup. + 7 weeks), 2 sections per mouse. Bar graphs represent the mean + /- SEM. Data presented in the main figures were expressed either as the percentage of total OLs for each probe (Figs. 7–8), or the change in proportion of each marker from the healthy P140 time point (Figs. 4–6).

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Extended Data Fig. 10 Layer-dependent differences in the temporal dynamics of cuprizone-induced loss and regeneration.

a-e) Related to Fig. 7. a) OL population replacement (%) plotted over weekly time bins following cuprizone cessation for each anatomically defined region. Replacement rate is increased from healthy baseline from 2–4 weeks post-cuprizone in L1-3 and CC, and 3–4 weeks post-cuprizone in L4 and L5-6 (Kruskal-Wallis test followed by Steel method for comparison with control, p = 0.034 for L1-3, Weeks 2–4 vs. Healthy; p = 0.034 for L4 Weeks 3–4 vs. Healthy; p = 0.034 for L5-6, Weeks 3–4 vs. Healthy; p = 0.034 for CC Weeks 2–4 vs. Healthy). n = 6 mice (cuprizone), 2 mice were imaged at an extra time point during Week 6. b) First-derivative of the modeled growth curves for healthy baseline and OL replacement (Mechanistic Growth, Gompertz 3P, respectively) showing the response duration of regeneration across regions. c) The regeneration response duration, calculated as the full width at half maximum of the rate curves in (b), is significantly longer in the superficial layers 1–3 compared to the CC (One-way ANOVA followed by Tukey’s HSD, p = 0.048). d) The magnitude of the regeneration response, as calculated by the area under the curve above the healthy baseline rate, is significantly suppressed in L5-6 compared to the CC (One-way ANOVA followed by Tukey’s HSD, p = 0.037). e, f) No significant differences in the duration or magnitude of the cuprizone cell loss response across regions. Data in (a) were calculated based on the raw % change in cell population from baseline. Data in b-f were derived from the modeled and scaled growth curves. n = 6 mice (cuprizone), n = 6 mice (healthy). *p < 0.05, **p < 0.01, n.s. = not significant; for growth curves, cubic splines approximate the measure of center and error bars are 95% confidence intervals; box plots represent the median, interquartile ranges and minimum/maximum values. For detailed statistics, see Supplementary Table 3.

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Supplementary information

Supplementary Information

Supplementary Tables 1–3.

Reporting Summary

Supplementary Video 1

Fly-through of in vivo three-photon microscopy across cortical and subcortical regions in an Mobp–EGFP mouse showing mature oligodendrocytes (green) and THG signal from the vasculature and myelin sheaths (magenta).

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Thornton, M.A., Futia, G.L., Stockton, M.E. et al. Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis. Nat Neurosci (2024). https://doi.org/10.1038/s41593-024-01613-7

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