Extracellular space preservation aids the connectomic analysis of neural circuits

Abstract

Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

Keywords: connectomics; extracellular space; gap junction; machine learning; mouse; neuroscience; tissue fixation.

Figure 1.. ECS preservation in acutely isolated tissues.

(A) A model of the changes brain tissue undergoes during chemical tissue fixation and possible interventions to preserve ECS. (B) ECS fraction of mouse olfactory bulb (x), retina (o), and cortex (□) correlates with increasing fixative vehicle concentration. Dashed line is the linear fit to olfactory bulb data, solid line is the linear fit to cortex data (olfactory bulb: R = 0.80, p = 0.0006; cortex: R = 0.79, p = 0.0113). (C–F) EM images from the external plexiform layer of the mouse olfactory bulb from a perfused brain (C) or from acute sections fixed with increasing buffer concentrations (D–F). ECS fractions are 0.6% (C), 5.8% (D), 11.3% (E), and 23.9% (F). Scale bars: 1 µm (C–F). ECS: Extracellular space; EM: Electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.003

Figure 1—figure supplement 1.. Change of tissue dimensions and uniformity of ECS preserved sections.

(A) Vibratome sections were cut from the cerebral cortex of acutely isolated brains (for ECS preservation) or from perfused animals. Section thickness was nominally 500 µm as determined by the slice thickness setting of the vibratome. Sections were stained for EM and the cross-sectional thickness measured from EM images (mean +/- SEM; n = 20 slices from 6 animals, one-way ANOVA: p = 0.46). (B) Sample images from the edges (Bi, Biii) and center (Bii) of a 500-µm-thick section of the mouse olfactory bulb. ECS is evenly preserved across the section. ECS: Extracellular space; EM: Electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.004

Figure 1—figure supplement 2.. Effect of temperature on the preservation of ECS.

(A,B) Vibratome sections were cut from the olfactory bulbs of acutely isolated brains at either 4°C or 25°C and then fixed at 25°C in 0.1 M CB + 2% GA. (C,D) Vibratome sections were cut from the olfactory bulbs of acutely isolated brains at either 4°C or 25°C and then fixed at 25°C in 0.2 M CB + 2% GA. ECS preservation was similar under both conditions indicating the temperature of solutions during tissue dissection is not a major determinant for ECS preservation. Scale bars: 1 μm. ECS: Extracellular space; EM: Electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.005

Figure 2.. Automated 2D segmentation of extracellular space preserved data.

(A) Four raw EM images (first column) of varying ECS fractions (0.6, 5.8, 11.3, and 23.9%) were analyzed. The lowest ECS fraction (0.6%) is the perfused preparation while the others are the acute slice preparations. Pixels in each image were annotated (second column) as either intracellular (white), extracellular (gray), or plasma membrane (black). Representative test image pixel classifications (third column) yielded network classification errors of 9.3, 8.1, 6.7, and 7.2% for the four examples shown. Intracellular pixel probabilities were thresholded and segmented (fourth column) to yield minimum Rand errors of 0.11, 0.06, 0.06, and 0.07 for the four examples shown. (B) Pixel classification errors plotted versus ECS fraction from an ninefold cross-validation, median values in red, shows no significant difference between perfused and acute preparations (K-W test: p=0.05). (C) Rand error plotted versus ECS fraction for the ninefold cross-validation, median values in red, shows a significant difference between perfused and acute preparations (K-W test: p<0.01; Wilcoxon rank-sum test: p=0.0017 [5.8%], p=0.0091 [11.3%], p=0.031 [23.9%]). (D) Total number of splits and merger per object in each test image plotted versus ECS fraction for the ninefold cross-validation, median values in red, shows a significant difference between perfused and acute preparations (K-W test: p<0.001; Wilcoxon rank-sum test: p=0.00049 [5.8%], p=0.00035 [11.3%], p=0.00035 [23.9%]). Scale bars: 2 μm. p-Values: *p<0.05, **p<0.01, ***p<0.001. ECS: Extracellular space; EM: Electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.006

Figure 2—figure supplement 1.. Warping error of automated segmentations.

(A) Split/merger curves parameterized by threshold of the network output. Shaded area is the standard error of the mean, lines are the mean number of splits/mergers per object, and the circles are the mean of the minimum total splits + mergers per object. (B) Network segmentations at the minimum warping error threshold, same regions as in Figure 2A. Warping errors were 0.68 (0.6% ECS), 0.32 (5.8% ECS), 0.52 (11.3% ECS), and 0.56 (23.9% ECS) for the four examples shown. (C) Cumulative distributions of the number of ground truth intracellular pixels per object for the four datasets. The difference in these distributions motivated the use of a Bernoulli sampling procedure for calculating the adapted Rand Error metrics in Figure 2C. Scale bars: 2 μm. ECS: Extracellular space. DOI: http://dx.doi.org/10.7554/eLife.08206.011

Figure 3.. Automated 3D segmentation of extracellular space preserved data.

(A) A 10 x 10 x 12 μm³ 3D SBEM cube (left) of perfused tissue (LowECS), a dense skeletonization of all neurites in the volume (middle), and an automated segmentation of the volume (right). (B) A 10 x 10 x 12 μm³ 3D SBEM cube (left) of ECS-preserved tissue (HighECS), a dense skeletonization of all neurites in the volume (middle), and an automated segmentation of the volume (right). (C) Adapted Rand error of automated segmentations compared to dense skeletonizations as a function of the segmentation threshold for the HighECS (brown) and LowECS (blue) data volumes. (D) The fraction of merged skeleton nodes versus split skeleton edges as a function of network threshold. Solid points indicate the minimum sum of the error fractions. (E) The total error-free skeleton path length recovered as a function of network threshold. Shaded regions in C–E are the 99% confidence intervals based on a Bernoulli sampling of the data. Scale bars in A, B = 1 μm. SBEM: Serial block-face scanning electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.012

Figure 3—figure supplement 1.. Cumulative distributions for 3D hand-labeled volumes and skeletonizations of the LowECS (blue) and HighECS (brown) data volumes.

(A) Cumulative distribution frequency (CDF) of number of intracellular ground truth voxels per object. The distribution medians are significantly different (Wilcoxon rank-sum test, p <0.0001). (B) CDF of path length per skeleton, medians 10.2 (LowECS) and 10.1 (HighECS) μm. The distributions are not significantly different (two-sample Kolmogorov–Smirnov (KS) test, p = 0.91). (C) CDF of the number of nodes annotated per skeleton, medians 16 (LowECS) and 17 (HighECS) nodes. The distributions not significantly different (two-sample KS test, p = 0.77). DOI: http://dx.doi.org/10.7554/eLife.08206.017

Figure 4.. Extracellular space aids the identification of gap junctions.

(A) Reconstructed dendrites of an AII amacrine cell (gray) and surface renderings of tight (yellow) and cleft (black) contacts. (B-D) Example EM images and volumetric reconstructions of (B) an AII (gray) to AII (blue) tight contact, (C) an AII (gray) to cone bipolar cell (green) tight contact (C), and (D) a cleft contact identified as a chemical synapse between a presynaptic amacrine cell (cyan) and the AII cell (gray). (E) Tight contact surface renderings color-coded by the identity of the synaptic partner: AII amacrine cell (blue), cone bipolar cell (green), presynaptic amacrine cell (cyan). (F) Summary of the number of contacts color-coded by the cell type of the contacting cell: AII (blue), cone bipolar (green), presynaptic amacrine cell (cyan), other (black). Scale bars: 2 µm (A,E), 1 µm (B–D). EM: Electron microscopy. DOI: http://dx.doi.org/10.7554/eLife.08206.018

Figure 4—figure supplement 1.. Simple measures of contact geometry do not predict gap junctions.

(A) Surface area and the volume of the convex hull bounding each contact are plotted for cleft contacts (gray), AII amacrine cell tight contacts (blue) and cone bipolar cell tight contacts (green). DOI: http://dx.doi.org/10.7554/eLife.08206.022

Figure 5.. Extracellular space preservation increases access to antibodies.

(A) Flat-mounted retinas were immunolabeled for vACHT with and without ECS preservation. Retinas were then cross-sectioned and confocal images were taken to directly visualize penetration depth. (B) Same as A, but immunolabeled for vGAT. (C) Fullwidth half-maximal penetration distances (mean +/- SEM) for retinas with and without ECS preservation (n = 20 retina slices from two animals, unpaired Student’s t-test, vACHT: ***p<0.0001, vGAT: ***p<0.0001). (D) EM images collected from the regions of interest in panel B indicated by dotted rectangles. Scale bars: 50 μm (A,B), 1 μm (D). DOI: http://dx.doi.org/10.7554/eLife.08206.023