This paper describes a method by which the vascular architecture in the brain can be quantified using in vivo and ex vivo two-photon microscopy.
Human Immunodeficiency Virus 1 (HIV-1) infection frequently results in HIV-1 Associated Neurocognitive Disorders (HAND), and is characterized by a chronic neuroinflammatory state within the central nervous system (CNS), thought to be driven principally by virally-mediated activation of microglia and brain resident macrophages. HIV-1 infection is also accompanied by changes in cerebrovascular blood flow (CBF), raising the possibility that HIV-associated chronic neuroinflammation may lead to changes in CBF and/or in cerebral vascular architecture. To address this question, we have used a mouse model for HIV-induced neuroinflammation, and we have tested whether long-term exposure to this inflammatory environment may damage brain vasculature and result in rarefaction of capillary networks. In this paper we describe a method to quantify changes in cortical capillary density in a mouse model of neuroinflammatory disease (HIV-1 Tat transgenic mice). This generalizable approach employs in vivo two-photon imaging of cortical capillaries through a thin-skull cortical window, as well as ex vivo two-photon imaging of cortical capillaries in mouse brain sections. These procedures produce images and z-stack files of capillary networks, respectively, which can be then subjected to quantitative analysis in order to assess changes in cerebral vascular architecture.
Human Immunodeficiency Virus 1 (HIV-1) invades the brain during the acute phase of virus infection, and productively infects both microglia and brain resident macrophages, leading to their activation – and the release of both host-derived inflammatory mediators and soluble HIV-1 virotoxins such as Tat and gp120 (reviewed in 1,2). As a consequence, a chronic neuroinflammatory state becomes established in the CNS, which is thought to contribute to the pathogenesis of HIV-1 Associated Neurocognitive Disorders (HAND)3-5.
Chronic overexpression of HIV-1 Tat or interleukin (IL)-17A within the CNS of mice has been shown to result in microvascular rarefaction6,7. This raises the possibility that chronic neuroinflammation may contribute to the pathogenesis of HAND through effects on the cerebral vasculature. In order to further examine this question, we have developed methods to quantify cerebral vascular structures.
This paper describes a method for quantifying the number of capillary nodes, capillary segments, mean segment length, total segment length, mean capillary diameter, and total capillary volume using in vivo imaging of capillary networks through a thin skull cortical window (modified from previously described protocols)8,9, as well as ex vivo imaging of brain sections, using two-photon microscopy. This combined approach provides for a holistic quantitation of cerebral vascular parameters, since the in vivo thin-skull cortical window allows for the preservation of the cerebral environment, while ex vivo imaging of capillary networks in brain slices enables the reconstruction of complete, three-dimensional capillary networks – which can then be quantified using commercially available software.
The University of Rochester's University Committee on Animal Resources approved all procedures performed in this paper.
1. Pre-surgical Preparation (and Mice)
2. Preparation of the Thin-skull Cranial Window
3. Monitoring of Physiological Parameters
4. Injection of the Fluorescent Dye
5. In Vivo Two-Photon Imaging
6. Ex Vivo Two-Photon Imaging
7. Data Processing
The thin-skull cortical window allows for in vivo two-photon imaging of cortical capillaries (Figure 1). A suitable area to image shows numerous, distinct capillaries (Figure 1A). In the same field of view, there is no arterial cell wall autofluorescence, and there may be other fluorescent signals, such as collagen fluorescence, induced by second harmonic generation11 (Figure 1B).
Once the preparation of the brain slice is complete, an imaging area approximately 1.5mm from midline is located (Figure 2A). A 100 µm z-stack produces a three-dimensional image used for analysis in the Amira analytical software (Figure 2B). The capillary network is then manually traced by placing nodes at the beginning and end of a capillary, or any location where one capillary branches into another (Figure 2C). This produces a fully skeletonized image from which morphological parameters are automatically extracted (Figure 2D). The number of capillary nodes, segments, mean segment length, total segment length, and total capillary volume can be extracted using two-photon ex vivo imaging of mouse brain slices (Figure 2).
Figure 3 shows representative results obtained using the method presented in this paper. In this experiment, a transgenic mouse model of HIV neuroinflammation was used10. Production of the HIV virotoxin Tat was induced in Tat+ mice by doxycycline-infused food for 12 weeks. The control group consisted of Tat- littermates fed the same food. There was no statistically significant difference between Tat+ and Tat- mice in any of the capillary parameters measured. Thus, 12 weeks' exposure of brain tissue to HIV-1 Tat is insufficient to cause rarefaction of the brain microvasculature. In contrast, our previously published data show that more prolonged (20 weeks) chronic CNS expression of Tat results in rarefaction of cerebral vasculature7. Thus, the data shown here (Figure 3) provides valuable new information in regards to the kinetics of Tat-induced vascular remodeling within the CNS of mice.
Figure 1. Acquisition of cortical capillary diameter. (A) Following a thin-skull cortical window preparation and intravenous fluorescent dye injection, two-photon microscopy was used to image cerebral vasculature. In our experiments, we used a dextran conjugated to a red emitting rhodamine dye that was excited at 780 nm, and fluorescence was visualized through a 607/36 bandpass emission filter. (B) The same field of view should show no arterial autofluorescence as detected through a 480/20 bandpass emission filter. Second harmonic generation may induce other fluorescent signals to appear through the filters11. Please click here to view a larger version of this figure.
Figure 2. Generation of skeletonized capillary networks. (A) Mice were intravenously injected with a fluorescent dye and sacrificed. A 2 mm coronal section of brain was taken between bregma 0 and bregma -2, and imaging was performed at the 0 bregma approximately 1.5 mm from midline. A representative image of the cortical location chosen for imaging (black box) from a C57BL/6 mouse is shown. This region, the somatosensory cortex, was chosen because we have previously shown that dysregulation of cerebral blood can occur at this site in Tat+ mice12. (B) Representational three dimensional z-stack images of capillary networks. (C) Diagram of the method used to manually trace capillaries during vessel quantification. (D) Representative image of skeletonized z-stack image. Please click here to view a larger version of this figure. Please click here to view a larger version of this figure.
Figure 3. Quantification of cerebral vascular architecture in Tat- mice versus mice exposed to the candidate HIV virotoxin Tat for 12 weeks. Mice with a doxycycline (DOX) inducible HIV-1 Tat transgene driven by the astrocyte-specific glial fibrillary protein (GFAP) promoter (HIV Tat-Tg mice) were used to examine the effect of HIV-1 induced neuroinflammation on cerebral vascular structure, as described7. These mice (Tat+, n=3) were exposed to a chronic (12 week) regimen of Tat induction (i.e., 12 weeks of DOX). Tat- mice (n=4) were used as age-matched controls (these mice correspond to non-transgenic littermates of the Tat+ mice, and therefore do not express HIV-1 Tat). Like the Tat+ mice, the Tat- mice also received 12 weeks of DOX exposure. In the mice exposed to Tat for 12 weeks (Tat+), versus those not exposed to Tat (Tat-), there was no statistically significant difference in the number of nodes (A), the number of segments (B), mean segment length (C), or total capillary length (D), capillary diameter (for the Tat+ mice, we analyzed 14 capillaries in 6 imaging areas; for Tat- mice, we analyzed 7 capillaries in 4 imaging areas) (E), or total capillary volume (F). Since the data were not normally distributed (as determined by the Shapiro-Wilk test), the exact Wilcoxon rank sum test was used to calculate statistical significance (determined in this case as P<0.05). Please click here to view a larger version of this figure. Please click here to view a larger version of this figure.
The method described here can be applied to analyze brain microvascular structures in a wide range of experimental models/settings. For the success of this method, three critical steps must be mastered. First, the thin-skull window must not damage the skull or underlying brain. It is easy to puncture the skull during thinning, or cause heat induced vascular leakage. This can interfere with imaging as the fluorescent dye will leak into the plane of focus and obscure the capillaries. If the skull frequently breaks during the thin-skull preparation, it is most likely caused by too great a downward pressure. Holding the microtorque drill as close as possible to the burr allows for greater tactile control that will decrease the downward pressure on the skull.
Second, arterial catheterization should occur as quickly as possible once the artery has been cut. Failure to insert the catheter quickly can cause excessive blood loss that will compromise the physiological integrity of the mouse. Difficulty inserting the catheter is usually due to the relatively large size of the catheter compared to the femoral artery. It may be necessary to stretch the catheter in order to reduce its diameter. Additionally, the tips of the #5 forceps can be used to grab and enlarge the opening made in the artery to ease in the placement of the catheter.
Third, the duration of the in vivo surgical procedures should be minimized so that the urethane anesthesia can be administered as soon as possible. The isoflurane anesthesia can cause vasodilation of cerebral blood vessels13, thus skewing the capillary diameter data.
It should be acknowledged that the Amira analytical software can automatically extract the radii of manually traced vessels; however, when using this feature to analyze z-stack images from ex vivo brains, the value is inaccurate. This is because, after removing the brain, the cerebral capillaries are no longer pressurized, and may become morphologically distorted. The in vivo capillary diameter measurement circumvents this problem because the capillaries are pressurized under normal, physiological conditions.
It must also be noted that this method is not without limitations. First, significant training is required to master the in vivo imaging preparation. A researcher must learn to efficiently perform two technically challenging techniques (thin skull cortical window and arterial catheterization); an error in either technique can compromise the experiment and invalidate the data. Second, analysis of the ex vivo z-stacks is time-intensive. The skeletonization of one z-stack image can take up to 2.5 hr. Furthermore, it is advisable that this analysis be completed by an experienced researcher to ensure consistency of the skeletonization process (which involves careful manual tracing of blood vessels).
Once all aspects of this protocol are mastered, the data obtained provide a more in-depth and physiologically accurate quantitation of vascular parameters in comparison to other traditionally used methods that show capillary density as capillaries per unit volume, or capillaries per field of view. The in vivo imaging technique allows for the study of other parameters including, but not limited to, red blood cell velocity, arteriole dilation, and red blood cell flux7,12, which may also be able to be examined in longitudinal studies. Furthermore, it can easily be adapted and modified to study research questions related to brain microvascular structure. Such studies could include quantitating pathogenic changes in capillary morphology in other neurocognitive diseases, or measuring age-related changes in capillary density. Therefore, the method presented in this paper is a versatile and powerful tool for the quantitative analysis of cerebral vascular architecture.
The authors have nothing to disclose.
We thank Maria Jepson, Dr. Paivi Jordan, and Dr. Linda Callahan at the University of Rochester Multiphoton Core for technical advice throughout the completion of this protocol. We also thank Dr. Changyong Feng for expert statistical advice, and Dr. Maiken Nedergaard at the University of Rochester Medical Center for the headplate design used in this paper. This work was supported in part by grants T32GM007356 and R01DA026325 from the National Institutes of Health (NIH); and by the University of Rochester Center for AIDS Research grant P30AI078498 (NIH).
Leica Microscope | Leica Inc. | MZ8 | |
High Intensity Illuminator | Dolan-Jenner | 180 | |
Heating Pad | Stryker | TP3E | |
T/PUMP | Gaymar Industries, Inc. | TP-500 | |
TEC-4 Isoflurane Vaporizer | Datex Ohmeda | 447 | |
Artificial Tear Gel | Butler AHS | 7312 | |
Povidone-Iodine solution | Aplicare | 52380-1855-9 | |
Extra Fine Bonn Scissors | Fine Science Tools | 14084-08 | |
Dumot #5 Forceps | Fine Science Tools | 11295-10 | |
Dumont #5/45 Forceps | Fine Science Tools | 11251-35 | |
Ferric Chloride Solution | Ricca Chemical Company | 3120-16 | |
Loctite 454 Prism Instant Adhesive Gel | Henkel | 45404 | |
Dental Cement | Stoelting | 51459 | |
Microtoruqe II Handpiece Kit | Pearson Dental | R14-0002 | |
005 Burr for Micro Drill | Fine Science Tools | 19007-05 | |
Norland Blade (Dental Microblade) | Salvin Dental | 6900 | |
Urethane | Sigma-Aldrich | U2500 | Group 2B Carcinogen |
Braided Suture | Ethicon | 735G | |
Vannas Spring Scissors | Fine Science Tools | 15000-03 | |
Arterial Catheter | SAI Infusion Technologies | MAC-01 | The end of the catheter was manually stretched out in order to decrease its diameter. |
Blood Pressure Moniter | World Precision Intruments | SYS-BP1 | |
Blood Pressure Transducer and Cable | World Precision Intruments | BLPR2 | |
RAPIDLab Blood Gas Analyzer | Siemens | 248 | |
40 μl Capillary Tube | VWR | 15401-413 | |
Texas Red-dextran (70,000 MW, 10 mg/kg dissolved in saline) | Invitrogen | D-1830 | |
Adult Mouse Brain Slicer Matrix | Zivic Instruments | BSMAS001-1 | |
Olympus Fluoview 1000 AOM-MPM Multiphoton Microscope | Olypmus | FV-1000 MPE | |
MaiTai HP DeepSee Ti:Sa laser | Spectra-Physics | ||
ImageJ Software | National Institutes of Health (NIH) | Available at http://rsb.info.nih.gov/ij/download.html | |
Amira Software | Visage Imaging |