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. 2018 Apr 26;7:e33670. doi: 10.7554/eLife.33670

Figure 1. Cortical capillaries are prone to spontaneous obstruction.

(A) Side projection from in vivo two-photon imaging stack (0.027 mm3) showing pial surface at the top with labeled plasma (magenta). Insert shows a flowing (Note streaking pattern in line scans caused by RBC movement) and obstructed capillary (no streaks). Red arrow indicates occluding debris/cells. Scale bars are 50 µm and 15 µm for inset. (B) Distribution of microsphere obstructed capillaries as it relates to depth from the pial surface determined by confocal imaging from post-mortem brain sections. Red bars indicate the relative amount of microsphere obstructions for each depth expressed as a fraction of total obstructions. Black line indicates fraction of total capillaries by depth (error bars are 95% CI) as well as raw numbers of capillaries/ mm3 by depth are provided in parentheses. Note 0.04 obstructions occurred below 1000 μm from cortical surface but are not shown. (C) Distribution showing spontaneous and microsphere obstructed capillaries expressed as a function of arteriole branch order and relative to the distribution of all capillaries [n(all)=3 mice, 285 capillaries; n(spont.)=5 mice, 21 obstructions; n(micro.)=5 mice, 59 obstructions). Note that lower order capillaries are more susceptible to obstruction. Inset illustrates branch order which started with the penetrating arteriole (0 order branch). Scale bar 15 µm. (D) Mean branch order of spontaneous or microsphere-induced capillary obstructions ([one way ANOVA F(2,360)=32.36, p<0.0001, all capillaries compared to spontaneous obstructions unpaired t-test t(302)=4.180, p<0.0001, or microsphere obstructions unpaired t-test t(342)=6.95, p<0.0001; spontaneous vs microsphere obstructions t(76)=0.46, p=0.65]. ***p<0.001, n.s. = not significant. Error bars are S.E.M.

Figure 1.

Figure 1—figure supplement 1. Work flow and validation of automated estimates of vessel density.

Figure 1—figure supplement 1.

A) To provide an automated, unbiased approach for estimating vessel densities, we wrote and validated a custom macro in FIJI (Schindelin et al., 2012). In vivo imaging stacks of dye filled cortical vessels (see maximum z-projection in top left and side view projection of image stack in top right) were manually split into sub-stacks of 10 images (2 µm z-steps between images). Sub stacks were then each maximally projected in the z plane, and each automatically thresholded using the built in ImageJ threshold function Triangle (Zack et al., 1977), which was determined to best capture vascular signal through trial and error. The area and fractional vascular volume of vascular signal (number of black pixels after thresholding) was measured for each sub-stack image projection after applying a median filter (radius of 2 pixels) to eliminate speckling. Thresholded sub-stacks were then binarized and skeletonized using built in functions (Arganda-Carreras et al., 2010) and total vascular length was taken as the number of skeleton pixels. From the vascular length, average vessel width (w = A/L) was also calculated. (B–C) Graphs show that both the fractional vascular volume (v/v) and the estimated number of capillaries per imaging stack (0.02 mm3 volume) were sensitive to the volume of images projected. For fractional vascular volume, projecting 20 µm sub-stacks led to estimates of ~0.01% vascular volume which closely matches published data (Blinder et al., 2013; Schmid et al., 2017). As for capillary number, we validated 20 µm sub-stack z projections by comparing automated estimates with those derived from blinded manual counts (data from four mice, two imaging areas per animal). (D) Box and whisker plots (+is mean) showing close agreement between manual and automated estimates of capillary number per imaging stack [paired t-test t(3)=0.33, p=0.76]. Error bars are S.E.M.
Figure 1—figure supplement 2. Fluorescent microspheres as a model of spontaneous naturally occurring capillary obstructions.

Figure 1—figure supplement 2.

Given the relative rarity of spontaneous microvascular obstructions, and the experimental challenges of capturing and following a spontaneous event we developed an inducible model of capillary obstructions that allowed us control over the timing of obstruction and the ability to standardize, with low variability, the number of obstructions between experimental groups (A) Image of fluorescently labelled (580/605 nm excite/emit) 4 µm diameter polystyrene microspheres. (B) Quantification of microspheres in blood after i.v. injection. By 30 min, microspheres were reduced to 11% of starting concentration and undetectable by 60 min (n = 5 mice per timepoint). C) Presence of microspheres in other organs at 4, 15 and 21 days after injection (n = 3–14 mice). D–J) To rule out any systematic effects on the cardiovascular system, we assessed body weight (D), tissue oxygenation (measured at thigh, (E), systolic and diastolic blood pressure (F, G), heart rate (H), and breath rate (I). All parameters were unaffected by microsphere injection (n = 4 mice, oneway ANOVA, all p>0.05) (J) No effect of microsphere injection on blood gases, electrolytes, glucose or hematocrit (n = 3 sham and four mice per time point). Error bars are S.E.M.
Figure 1—figure supplement 3. Microsphere based obstruction and pruning did not induce a microglial response or cell death.

Figure 1—figure supplement 3.

A) In vivo time lapse imaging of microglia (green) and blood flow (labeled with 4% Rhodamine dextran) in CX3CR1+/GFP mice. Microglia were not responsive to the capillary obstruction at any time point, in any mice (n = 6 mice, 2–3 areas per mouse), even when the segment was pruned between 6 and 10 days. Inset shows microglial accumulation following laser ablation as a positive control. Scale bars 25 µm. (B) Fluorojade C staining in the cortex, liver or lung 24 hr after injection did not reveal any detectable cell degeneration or death (n = 3 mice). A positive control illustrating cell death following ischemia is shown for comparison. Sections were stained with FJC as previously described (Reeson et al., 2015). Scale bar 100 µm.
Figure 1—figure supplement 4. Microsphere obstructions are distributed across major cerebral vascular territories.

Figure 1—figure supplement 4.

(A) Representative images of cortical obstructions (see blue arrowheads) 4 days after microsphere injection in coronal sections ordered relative to bregma. Scale bar 250 µm. (B) Average microsphere density (microspheres /mm3) as a function of time after injection and position relative to bregma. There were no significant main effects of position relative to bregma at any time studied [+4 days: F(10,22)=0.17, p=0.99, +10 days: F(10,22)=0.77, p=0.65, +31 days: F(10,33)=0.26, p=0.98]. Error bars are S.E.M.