Tools for efficient analysis of neurons in a 3D reference atlas of whole mouse spinal cord

Abstract

To fill the prevailing gap in methodology for whole spinal cord (SC) analysis, we have (1) designed scaffolds (SpineRacks) that facilitate efficient and ordered cryo-sectioning of the entire SC in a single block, (2) constructed a 3D reference atlas of adult mouse SC, and (3) developed software (SpinalJ) to register images of sections and for standardized analysis of cells and projections in atlas space. We have verified mapping accuracies for known neurons and demonstrated the usefulness of this platform to reveal unknown neuronal distributions. Together, these tools provide high-throughput analyses of whole mouse SC and enable direct comparison of 3D spatial information between animals and studies.

Graphical abstract

Figure 1

Embedding and sectioning of mouse spinal cord using SpineRacks and image processing and registration in SpinalJ (A) Cutting scheme for synchronous sectioning of nine parallel embedded tissue pieces of the adult mouse SC. Red arrowhead in (A)–(D), (F) and (Q) indicates r-c orientation. (B) The SC was divided into three equal pieces. Red dashed lines in (B) and (C) indicate cuts. (C and D) Each piece was then split again into three (C), resulting in a total of nine pieces of SC (D). (E) Design and dimensions of SpineRacks. (F–H) For embedding (F), a SpineRack was sunk into a plastic mold filled with OCT (G; see also Figure S1) and SC pieces were placed into the wells of the rack, each with its rostral end facing down (H). Red-filled image corner indicates the orientation of the tissue block for tracking as in (J) and (K). (I) Order of tissue pieces within the SpineRack. Pieces 1–3 were embedded left to right in the top row, 4–6 in the middle row, and 7–9 in the bottom row. (J) Eight cryostat block sections (a–h) were collected in two rows (1–4, top left to right; 5–8, bottom left to right) on each slide (shown here as brightfield photo). In this arrangement, >1,000 sections of adult mouse SC fit on 16 slides. (K) Each block section, comprising nine tissue sections, was scanned on a slide scanning microscope and saved as a single image file (here shown NT 640/660 signal). Images of block sections were ordered according to their position on the slide (A–H) to match sectioning sequence and segmented into nine individual tissue section images (1–9) in SpinalJ. (L) Images were then sorted rostro-caudally. Section 1, slide I, block a = 1(Ia). (M and N) For horizontal alignment of sections (M), images were centered and thresholded using the NT or DAPI (not shown) channel. The resulting image was split vertically (dotted line) and the left half (L) was mirrored and overlaid with the right half (R) to calculate the average intensity of the absolute difference of both images (|L-R|). This value was minimized when both image halves aligned perfectly, indicating horizontal orientation (N). (O) To determine horizontal orientation for each section automatically, images were rotated by increments of 10° from −60° to +60° (reflecting the range of typical embedding orientations; blue shaded area) and the angle resulting in the lowest mean difference intensity was applied to align the section. (P) Montage of 1,086 sorted and aligned images of a sample spanning C1–S1. (Q) Dorsal view of the 3D reconstructed dataset (NT channel) shown in (P) after section registration.

Figure 2

Mapping registered SC sections to a novel 3D atlas in SpinalJ (A and B) Creation of the 3D reference atlas used 34 Nissl-stained sections (A) (shown for C1) and corresponding annotated sections (B) of the ASCA (Allen Institute for Brain Science, 2008). (C) Digitized annotations of all sections (one for each SC segment, C1–Co3). (D) A 3D Nissl template (dorsal view) was created by registering and extruding the sections representing each segment. (E) The transformation to create (D) was then applied to the annotated sections (C) to generate a 3D annotated atlas. (F) Segment boundaries were placed according to the relative positions of sections in the ASCA and the relative lengths of segments (blue bars) as reported in the literature (Harrison et al., 2013). (G and H) Example of mapping the same experimental dataset (magenta) to the Nissl template (green) using either (G) NT or (H) DAPI. Dashed lines indicate GM/WM boundary in C2. (I) Distribution of NT signal between GM and WM along the entire SC of four animals, measured manually (gray bar) and after SpinalJ atlas mapping using NT (magenta bar) or DAPI (blue bar). NT signal in GM: 93.68% (manual), 84.09% (±1.73%) (NT), 80.92% (±4.76%) (DAPI). NT signal in WM: 6.32% (manual), 15.91% (±1.73%) (NT), 19.08% (±4.76%) (DAPI). Error bars = SD. With reference to manually determined signal distributions, SpinalJ mapping accuracies were 89.76% (NT) and 86.37% (DAPI), respectively. (J) Heatmaps of mean NT intensity distribution after template mapping with NT, summarized for each segment. (K) Heatmaps of mean NT intensity distribution after template mapping with DAPI.

Figure 3

Intensity and cell density mapping of ChAT⁺ SNs (A) Hemisegment of SC section labeled with ChAT antibody. Scale bar, 500 μm. (B) Heatmap montage showing the spatial distribution of mean ChAT intensity per atlas region and segment. (C) Heatmap matrix plot showing the distribution of mean ChAT intensity in atlas region groups of the GM (laminae I–X) and WM (df, dorsal funiculus; lf, lateral funiculus; vf, ventral funiculus). (D) Pixel probabilities for classifier cells (red) after training in Ilastik. (E) Cells detected after image segmentation using pixel probabilities. (F) Spatial distribution of relative ChAT⁺ cell density per atlas region and segment. (G) Heatmap matrix plot showing the distribution of relative ChAT⁺ cell density in atlas region groups. Gray hatched areas in (C) and (H) mark regions without data. (H) Relative distribution of ChAT signal intensities (gray bars) and cell densities (red bars) within atlas regions of the GM (laminae I–X). Error bars = SD between values from both hemisegments.

Figure 4

Intensity and projection density mapping of IB4⁺ fibers (A) Hemisegment of SC section labeled with IB4-FITC. Scale bar, 500 μm. (B) Spatial distribution of mean IB4 intensity per atlas region and segment. (C) Distribution of mean IB4 intensity in atlas region groups of the GM (laminae I–X) and WM (df, dorsal funiculus; lf, lateral funiculus; vf, ventral funiculus). (D) Pixel probabilities for classifier projections (green) after training in Ilastik. (E) Projections detected after image segmentation using pixel probabilities. (F) Spatial distribution of relative projection density per atlas region and segment. (G) Distribution of relative projection density in atlas region groups. Gray hatched areas in (C) and (H) mark regions without data. (H) Relative distribution of IB4 signal intensities (gray) and projection densities (green) within atlas regions of the GM (laminae I–X). Inset shows projection densities within laminae II (IIi and IIo). Error bars = SD between values from both hemisegments.

Figure 5

Intensity and projection density mapping of AAV-labeled CST axons (A) tdTomato signal in a dorsal view of the brain shows AAV-tdTomato injection sites in left sensory and motor cortex. Yellow dotted lines indicate positions of sections shown in (B). Scale bar, 3 mm. (B) Coronal sections of the brain at levels indicated in (A), showing tdTomato (red) and DAPI (blue). Scale bar, 1 mm. (C) 3D reconstruction of registered SC sections. Image shows the 3D dataset (composite of tdTomato [magenta] and DAPI [blue]) in a frontal and dorsal view. (D) Cervical SC section showing the distribution of tdTomato signal. Inset shows same image reduced in brightness. Scale bar, 500 μm. (E) Pixel probabilities for classifiers projections (green) after training in Ilastik. (F) Spatial distribution of relative projection density per atlas region and segment. (G and H) Distribution of relative projection density in atlas region groups of the GM (laminae I–X) and WM (df, dorsal funiculus; lf, lateral funiculus; vf, ventral funiculus) within the left (G; ipsilateral) and right (H; contralateral) hemisegments. Gray hatched areas mark regions without data. (I) Distribution of relative projection density in atlas regions within the df of the right hemisegment (dcs, dorsal corticospinal tract; gr, gracile fasciculus; psdc, postsynaptic dorsal column pathway; cu, cuneate fasciculus). See also Figure S4. (J) Relative distribution of mean intensities (dark gray bars) and projection densities (green bars) within atlas regions of the GM of segments C4–C7. Light gray bars show the relative distribution of CST axon area as measured in a manual mapping study (Ueno et al., 2018). Error bars = SD of values from all segments within the analyzed range. (K) Distribution of relative projection densities within atlas regions of the GM of cervical (plain green bars), thoracic (diagonally banded bars), and lumbar (checkerboard patterned bars) segments. Error bars = SD of values from all segments.

Figure 6

Mapping ChAT cells in multiple animals (A) Sections labeled with anti-ChAT antibody. Scale bar, 500 μm. (B) 3D distribution of the positions of ChAT⁺ SNs detected in three different samples (animals 1–3, red, blue, green) in a dorsal (left) and lateral (right) view. See also Figure S5. (C) Spatial distribution of ChAT⁺ SNs from different samples within each segment. (D and E) Cell distributions within each hemisegment (shown for L4, left hemisegment; D) were analyzed to determine the centroid for each animal, spinal level, and hemisegment (shown for L4, left in E). (F) Average pairwise centroid distances indicate mapping offset between animals within left (dark gray) and right (light gray) hemisegments at different spinal levels. Red line indicates average centroid distance across all segments (13.3 μm). Error bars = SD.

Figure 7

Spatial distribution of VAChT⁺/Foxp1⁺ cells and inter-animal mapping accuracy (A) SC sections showing tdTomato⁺ cells. Arrowheads mark cell clusters in the LMC (black), PGC (white), and HMC/MMC (yellow). (B) 3D distribution of VAChT⁺/Foxp1⁺ (Foxp1) cells detected in four samples (animals 1–4, red, blue, green, magenta) in a dorsal (left) and lateral (right) view. Arrowheads mark motor columns as in (A). See Figure S6 for 2D distributions of cells in individual segments. (C) Average number of Foxp1 cells per segment across all animals. Error bars = SD. (D and E) Cell distributions within each hemisegment (shown for L4, left hemisegment; D) were analyzed to determine the centroid for each animal, spinal level, and hemisegment (E). (F) Average pairwise centroid distances indicate the mapping offset between animals within the left (dark gray) and right (light gray) hemisegment at different spinal levels. Red line indicates the average centroid distance across all segments (30.3 μm). Error bars = SD. (G) Section showing VAChT/Foxp1:tdTomato-labeled SNs (arrowheads) in T4. Scale bar, 500 μm. (H) Anti-ChAT counterstaining of section in (A). (I) Overlay of tdTomato (red) and ChAT (blue) signal from (G) and (H). (J) Overlay of segmented tdTomato (red) and ChAT (blue) signals used for cell detection in the same field of view. (K) Relative contributions of Foxp1 cells (red bars) and ChAT⁺ cells (blue bars) to motor columns of four animals (SAC, spinal accessory motor column; PMC, phrenic motor column). Foxp1: LMC, 73%; PGC, 12%; HMC, 6%; MMC, 7%; SAC, 1%; PMC, 1%. ChAT⁺: LMC, 50%; PGC, 7%; HMC, 25%; MMC, 15%; SAC, 1%; PMC, 2%. (L) Top row: overlay of the positions of detected Foxp1 cells (red) and ChAT⁺ cells (blue) at C8, T4, and L4 from all four animals. Arrowheads mark cell clusters in the LMC (black), PGC (gray), and HMC/MMC (white). Middle row: overlay of Foxp1 and ChAT⁺ cell positions, measured in one animal (#2). Bottom row: overlay of cell positions from different animals: Foxp1 in animal #3, ChAT⁺ in animal #4.