This project was supported by the National Institutes of Health R21 NS104801 (EMB)&#160;&#160;and R01 NS115994 (LBW/EB) and Children&#8217;s Healthcare of Atlanta Junior Faculty Focused Award (EMB). This work was also supported by the U.S. Department of Defense through the Congressionally Directed Medical Research Programs under Award No. W81XWH-18-1-0669 (LBW/EMB). Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the Department of Defense.&#160;This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1937971. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

All animal procedures are approved by Emory University Institutional Animal Care and Use Committee (IACUC) and followed the NIH Guidelines for the Care and Use of Laboratory Animals.
1. Weight-drop model of mild traumatic brain injury
<ol>
	<li>Prepare the weight-drop setup. Mount a vise on a flat surface with a 1 m guide tube (2.54 cm inner diameter) aligned vertically (check using a level). Use a 54 g bolt (0.95 cm basic body diameter, 2 cm head diameter, 10.2 cm length) for the impact.</l...

<ol>
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M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cumulative+effects+associated+with+recurrent+concussion+in+collegiate+football+players:+the+NCAA+Concussion+Study.">Cumulative effects associated with recurrent concussion in collegiate football players: the NCAA Concussion Study.</a> Journal of the American Medical Association. 290 (19), 2549-2555 (2003).</li><li>Longhi, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+window+of+vulnerability+to+repetitive+experimental+concussive+brain+injury.">Temporal window of vulnerability to repetitive experimental concussive brain injury.</a> Neurosurgery. 56 (2), 364-374 (2005).</li><li>Committee on Sports-Related Concussions in Youth, Board on Children, Youth, and Families, Institute of Medicine, National Research Council. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Sports-Related Concussions in Youth: Improving the Science, Changing the Culture. , (2014).</li><li>Barkhoudarian, G., Hovda, D. 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Herein we detail methods for assessment of the hemodynamic and neuroinflammatory response to repetitive mild traumatic brain injury. Further, we have shown how to integrate these data as part of a multivariate systems analysis using partial least squares regression. In the text below we will discuss some of the key steps and limitations associated with the protocol as well as the advantages/disadvantages of the methods over existing methods.
Weight-drop model of mild traumatic brain in...

Overview 
Mild traumatic brain injuries (mTBIs) impact ~1.6-3.8 million athletes annually1. These injuries, including sub-concussive and concussive injuries, can leave patients with transient physical, emotional, psychological and cognitive symptoms2. Moreover, repetitive mTBI (rmTBI) sustained within a &#8220;window of vulnerability&#8221; can lead to cumulative severity and duration of cognitive consequences that last longer than the effects of a single mTBI alone3, and ultimately even to permanent loss of function4,5,6. Although many patients recover within a relatively short time frame (&#60;1 week), 10-40% of patients suffer longer lasting effects of mTBI for &#62; 1 month, with some lasting up to 1 year3,7,8,9. Despite the high prevalence and lasting consequences of these injuries, injury mechanisms are poorly understood and no effective treatment strategies exist.
Given the high variability in outcomes after mTBI/rmTBI, one challenge in identifying early-stage molecular triggers from tissue obtained in terminal mTBI/rmTBI studies is the lack of longitudinal data demonstrating definitive &#34;acute molecular links&#34; of these molecular triggers to longer-term outcomes. To overcome this challenge, our group has discovered that acutely reduced cerebral blood flow&#160;measured acutely using&#160;an optical tool called diffuse correlation spectroscopy (DCS), strongly correlates with longer-term cognitive outcome in a mouse model of rmTBI10. Using this hemodynamic biomarker, we showed that mice with acutely low cerebral blood flow (and, by extension, worse predicted long-term outcome) have concomitant acute increases in neuronal phospho-signaling within both MAPK and NF&#954;B pathways, increases in neuronal expression of pro-inflammatory cytokines, and increases in expression of the phagocyte/microglial marker Iba111. These data suggest a possible role for neuronal phospho-signaling, cytokine expression, and microglial activation in both the acute regulation of cerebral blood flow post injury as well as in triggering a signaling cascade that leads to neuronal dysfunction and worse cognitive outcome. Herein, we detail our approach to simultaneously probe both the hemodynamic and neuroinflammatory environment after rmTBI and how to integrate these complex datasets. Specifically, we outline procedures for four key steps to this comprehensive approach: (1) a weight-drop model of mild traumatic brain injury, (2) assessment of cerebral blood flow with diffuse correlation spectroscopy, (3) quantification of the neuroinflammatory environment, and (4) data integration (Figure 1). Below, we provide a brief introduction to each of these key steps to help guide readers through the rationale behind our methods. The remainder of the manuscript provides a detailed protocol for each of these key steps.
Weight-drop model of mild traumatic brain injury 
Although many excellent preclinical models of repetitive mild TBI exist12,13,14,15,16,17,18, we employ a well-established and clinically relevant weight-drop closed head injury model. Key features of this model include (1) blunt impact of the intact skull/scalp followed by unrestricted rotation of the head about the neck, (2) no overt structural brain injury, edema, blood&#8211;brain barrier damage, acute cell death, or chronic brain tissue loss, and (3) persistent (up to 1 year) cognitive deficits that emerge only after multiple hits19 (Figure 2).
Assessment of cerebral blood flow with diffuse correlation spectroscopy 
Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique that measures blood flow5,20,21. In DCS, a near-infrared light source is placed on the tissue surface. A detector is placed at a fixed distance from the source on the tissue surface to detect light that has multiply scattered through the tissue (Figure 3). Scattering off moving red blood cells causes the detected light intensity to fluctuate with time. A simple analytical model known as correlation diffusion theory is used to relate these intensity fluctuations to an index of blood flow (CBFi, Figure 4). Although the units of CBFi (cm2/s) are not the traditional units of flow (mL/min/100 g), a previous study in mice has shown that CBFi strongly correlates with cerebral blood flow measured by arterial spin labeled MRI21.
For reference, the DCS instrument used here was built in-house and is comprised of an 852 nm long coherence-length laser, an array of 4 photon counting avalanche photodiodes, and a hardware autocorrelator board (single tau, 8 channel, 100 ns minimum sample time)21,22. Data is acquired with homemade software written in LabView. The animal interface for the device consists of a 400 &#956;m multimode source fiber (400-2200 nm wavelength range, pure silica core, TECS Hard Cladding) and a&#160;780 nm single mode detector fiber (780-970 nm wavelength range, pure silica core, TECS Hard Cladding, 730 &#177; 30 nm second mode cut-off) spaced 6 mm apart and embedded in a black 3D-printed sensor (4 mm x 8 mm, Figure 3).
Quantification of the neuroinflammatory environment 
Although neuroinflammation is regulated by diverse cellular processes, two key relevant mechanisms are extracellular signaling by cytokines/chemokines and intracellular signaling by phospho-proteins. To investigate the neuroinflammatory environment of the brain post-injury, brains are extracted from mice, microdissected, and cytokines/chemokines and phospho-proteins are quantified using Luminex (Figure 5, Figure 6, Figure 7). Luminex multiplexed immunoassays enable simultaneous quantification of a diverse collection of these proteins by coupling enzyme-linked immunosorbent assays (ELISAs) to fluorescently tagged magnetic beads. Distinct fluorescent tags are used for each protein of interest, and beads of each tag are functionalized with a capture antibody against that particular protein. Hundreds of beads for capturing each protein are mixed together, placed in a 96 well plate, and incubated with sample. After sample incubation, a magnet is used to trap the beads in the well while the sample is washed out. Next, biotinylated detection antibody binds to the analyte of interest to form an antibody-antigen sandwich similar to a traditional ELISA, but with the ELISA for each protein occurring on a different fluorescently tagged bead. Adding phycoerythrin-conjugated streptavidin (SAPE) completes each reaction. The Luminex instrument then reads the beads and separates the signal according to each fluorescent tag/protein.
Data integration 
Because of the large number of analytes (e.g., cytokines) measured in the Luminex assay, data analysis can be difficult to interpret if each quantified protein is analyzed individually. To simplify analysis and to capture trends observed among analytes, we use a multivariate analysis method called partial least squares regression (PLSR, Figure 8)23. PLSR works by identifying an axis of weights corresponding to each measured protein (i.e., cytokines or&#160;phospho-proteins, referred to as &#8220;predictor variables&#8221;) that together optimally explain co-variance of the measured proteins with a response variable (e.g., cerebral blood flow). The weights are referred to as &#8220;loadings&#8221; and are assembled into a vector known as a latent variable (LV). By projecting (referred to as &#8220;scoring&#8221;) the measured protein data on each of two LVs, the data can be re-plotted in terms of these LVs. After computing the PLSR, we use a varimax rotation to identify a new LV that maximizes the covariance between the sample projections onto the LV and the predictor variable24. This approach allows us to define LV1 as the axis for which the variance of the response variable is best explained. LV2 maximizes co-variance between the response variable and LV1 residual data, which may be associated with biological or technical variability between samples. Lastly, we conduct a Leave One Out Cross Validation (LOOCV) to ensure that the PLSR model is not heavily dependent upon any one sample23.
In this protocol, we detail methods to characterize the neuroinflammatory and hemodynamic tissue response to mTBI. The general workflow is outlined in Figure 1. In this protocol, mice are subject to one or more mTBIs using a weight-drop closed head injury model. Cerebral blood flow is measured longitudinally before and at multiple time points after injury. At the time point of interest for interrogation of neuroinflammatory changes, the animal is euthanized, and the brain is extracted. Brain regions of interest are isolated via microdissection and then lysed to extract protein. Lysates are then used for both Luminex multiplexed immunoassays of cytokine and phospho-protein expression as well as Western blot. Finally, this holistic dataset is integrated using a partial least squares regression analysis.

<table>
	<tbody>
		<tr>
			<td>Adjustable pipettes</td>
			<td></td>
			<td></td>
			<td>any adjustable pipette</td>
		</tr>
		<tr>
			<td>Aluminum foil</td>
			<td>VWR</td>
			<td>89107-726</td>
			<td></td>
		</tr>
		<tr>
			<td>Bio-Plex cell lysis kit</td>
			<td>C Bio-Rad</td>
			<td>171304012</td>
			<td></td>
		</tr>
		<tr>
			<td>BRAND BRANDplates pureGrade Microplates, Nonsterile</td>
			<td>BrandTech</td>
			<td>781602 96</td>
			<td></td>
		</tr>
		<tr>
			<td>Complete mini protease inhibitor tablet</td>
			<td>Sigma-Aldrich</td>
			<td>11836153001</td>
			<td></td>
		</tr>
		<tr>
			<td>Depilatory cream</td>
			<td>Amazon</td>
			<td>Nair</td>
			<td></td>
		</tr>
		<tr>
			<td>DiH2O</td>
			<td>VWR</td>
			<td>VWRL0200-1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Handheld magnetic separator block for 96 well flat bottom plates</td>
			<td>Millipore Sigma Catalogue</td>
			<td>40-285</td>
			<td></td>
		</tr>
		<tr>
			<td>Hardware Autocorrelator Board</td>
			<td>www.correlator.com</td>
			<td>Flex05-8ch</td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane 250 mL</td>
			<td>MED-VET INTERNATIONAL</td>
			<td>RXISO-250</td>
			<td></td>
		</tr>
		<tr>
			<td>Kimwipe (11.2 x 21.3 cm)</td>
			<td>VWR</td>
			<td>21905-026</td>
			<td></td>
		</tr>
		<tr>
			<td>Laboratory vortex mixer</td>
			<td>VWR</td>
			<td>10153-838</td>
			<td></td>
		</tr>
		<tr>
			<td>LabView</td>
			<td>National Instruments</td>
			<td>LabVIEW</td>
			<td></td>
		</tr>
		<tr>
			<td>Luminex 200, HTS, FLEXMAP 3D, or MAGPIX with xPONENT software</td>
			<td>Luminex Corporation</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Luminex Drive Fluid</td>
			<td>Luminex</td>
			<td>MPXDF-4PK</td>
			<td></td>
		</tr>
		<tr>
			<td>Luminex sheath fluid</td>
			<td>EMD Millipore</td>
			<td>SHEATHFLUID</td>
			<td></td>
		</tr>
		<tr>
			<td>MILLIPLEX MAP Mouse Cytokine/Chemokine Magnetic Bead Panel - Premixed 32 Plex - Immunology Multiplex Assay</td>
			<td>Millipore Sigma</td>
			<td>MCYTMAG-70K-PX32</td>
			<td></td>
		</tr>
		<tr>
			<td>MILLIPLEX MAPK/SAPK Signaling 10-Plex Kit-Cell Signaling Multiplex Assay</td>
			<td>Millipore Sigma</td>
			<td>48-660MAG</td>
			<td></td>
		</tr>
		<tr>
			<td>Mini LabRoller rotator</td>
			<td>VWR</td>
			<td>10136-084</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenylmethylsulfonyl fluoride</td>
			<td>Sigma-Aldrich</td>
			<td>P7626-1G</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate-buffered Saline (PBS)</td>
			<td>VWR</td>
			<td>97064-158</td>
			<td></td>
		</tr>
		<tr>
			<td>Plate Sealer</td>
			<td>VWR</td>
			<td>82050-992</td>
			<td></td>
		</tr>
		<tr>
			<td>Polypropylene microfuge tubes</td>
			<td>VWR</td>
			<td>20901-547</td>
			<td></td>
		</tr>
		<tr>
			<td>Mini LabRoller</td>
			<td>Millipore Sigma</td>
			<td>Z674591</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent Reservoirs</td>
			<td>VWR</td>
			<td>89094-668</td>
			<td></td>
		</tr>
		<tr>
			<td>R Programming Language</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>RStudio</td>
			<td>www.rstudio.com</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sonicator</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Titer plate shaker</td>
			<td>VWR</td>
			<td>12620-926</td>
			<td></td>
		</tr>
		<tr>
			<td>Tween20</td>
			<td>Sigma-Aldrich</td>
			<td>P9416-50ML</td>
			<td></td>
		</tr>
		<tr>
			<td>1 m acrylic guide tube</td>
			<td>McMaster-Carr</td>
			<td>49035K85</td>
			<td></td>
		</tr>
		<tr>
			<td>4 photon counting avalanche photodiode</td>
			<td>Perkin-Elmer</td>
			<td>SPCM-AQ4C-IO</td>
			<td></td>
		</tr>
		<tr>
			<td>400 um multimode source fiber</td>
			<td>Thorlabs Inc.</td>
			<td>FT-400-EMT</td>
			<td></td>
		</tr>
		<tr>
			<td>54 g bolt</td>
			<td>Ace Hardware</td>
			<td></td>
			<td>0.95 cm basic body diameter, 2 cm head diameter, 10.2 cm length</td>
		</tr>
		<tr>
			<td>780 nm single mode detector fiber</td>
			<td>Thorlabs Inc.</td>
			<td>780HP</td>
			<td></td>
		</tr>
		<tr>
			<td>852 nm long-coherence length laser</td>
			<td>TOPTICA Photonics</td>
			<td>iBeam smart</td>
			<td></td>
		</tr>
	</tbody>
</table>

systems analysis of the neuroinflammatory and hemodynamic response to traumatic brain injury

Mild traumatic brain injuries (mTBIs) are a significant public health problem. Repeated exposure to mTBI can lead to cumulative, long-lasting functional deficits. Numerous studies by our group and others have shown that mTBI stimulates cytokine expression and activates microglia, decreases cerebral blood flow and metabolism, and impairs cerebrovascular reactivity. Moreover, several works have reported an association between derangements in these neuroinflammatory and hemodynamic markers and cognitive impairments. Herein we detail methods to characterize the neuroinflammatory and hemodynamic tissue response to mTBI in mice. Specifically, we describe how to perform a weight-drop model of mTBI, how to longitudinally measure cerebral blood flow using a non-invasive optical technique called diffuse correlation spectroscopy, and how to perform a Luminex multiplexed immunoassay on brain tissue samples to quantify cytokines and immunomodulatory phospho-proteins (e.g., within the MAPK and NF&#954;B pathways) that respond to and regulate activity of microglia and other neural immune cells. Finally, we detail how to integrate these data using a multivariate systems analysis approach to understand the relationships between all of these variables. Understanding the relationships between these physiologic and molecular variables will ultimately enable us to identify mechanisms responsible for mTBI.

Previously collected data were taken from prior work in which a group of eight C57BL/6 mice were subjected to three closed-head injuries (Figure 2) spaced once daily11. In this work, cerebral blood flow was measured with diffuse correlation spectroscopy 4 h after the last injury (Figure 3, Figure 4). After post-injury CBF assessment, the animals were euthanized, and brain tissue was extracted for quantificati...

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Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

This protocol presents methods to characterize the neuroinflammatory and hemodynamic response to mild traumatic brain injury and to integrate these data as part of a multivariate systems analysis using partial least squares regression.

Mild traumatic brain injuries (mTBIs) are a significant public health problem. Repeated exposure to mTBI can lead to cumulative, long-lasting functional ...

These methods can be used to characterize neuroinflammatory and hemodynamic responses to brain injury as part of a multivariate system analysis using partial least squares regression. These techniques are used to give more of a holistic view of the brain's response to injury. To induce an injury, confirm a lack of response to toe pinch in an anesthetized mouse and place mouse in the prone position on the center of a thin membrane.Using both hands to hold the tissue taught, secure the mouse's tail under a thumb and position to mouse head under the guide tube. When the mouse is in position, aiming for the impact between the back of the eyes and the front of the ears, drop the bolt from the top of the guide tube onto the dorsal aspect of the mouse's head. Upon impact, the mouse will break through the tissue, allowing rapid acceleration of the head about the neck.After the injury, allow the mouse to recover in the supine position on a 37-degree Celsius warming pad. After a two-minute period of stabilization, gently rest the DCS sensor over the right hemisphere of the mouse's skull, such that the top edge of the optical sensor lines up with the back of the eye and the side of the sensor lines up along the midline. Cup a hand over the sensor to shield it from room light and acquire five seconds of data.Then, reposition the sensor over the left hemisphere and acquire five seconds of left hemisphere data. To assess multiplexed cytokine and phospho-protein production, add 150 microliters of mixed lysis buffer per approximately three milligrams of harvested animal brain tissue. And use a 1, 000-microliter pipette tip to mechanically triturate the tissue 15 to 20 times.Place the homogenized samples on a rotator for 30 minutes at four degrees Celsius before collecting the tissue debris by centrifugation. Transfer the supernatants into new tubes and centrifuge the samples to remove any remaining precipitate. Transfer the supernatants to new tubes and determine the protein concentration by BCA assay according to standard protocols.Prepare 25 microliters of each sample at the optimal protein concentration as determined by the linear range analysis in new tubes. Using assay buffer to normalize the total volume of each sample to 25 microliters. To prepare an assay plate, add 200 microliters of wash buffer to each well of a 96-well plate and shake the plate on a shaker for 10 minutes at 750 revolutions per minute.At the end of the incubation, decant the wash buffer and tap the plate onto a paper towel to remove any residue. Next, add 25 microliters of assay buffer to each well, followed by 25 additional microliters of buffer to the background wells. Add 25 microliters of the diluted samples to the appropriate sample wells and vortex the via of multiplexed magnetic beads for one minute, before adding 25 microliters of the thoroughly re-suspended beads to each well.When all of the beads have been added, seal the plate with a plate sealer and cover the plate with foil for an overnight incubation with shaking at two to eight degrees Celsius. The next morning, place the plate on a magnetic separator, making sure that the wells are aligned with the magnets. After two minutes, decant the well contents with the plate still attached to the magnetic separator and add 200 microliters of wash buffer to each well.After keeping it shaking for two minutes, place the plate onto the magnetic separator for two minutes. Then, decant the well contents with the plate still attached to the magnetic separator and wash the plate with a fresh 200 microliters of wash buffer per well, as just demonstrated. After the second wash, add 25 microliters of detection antibody per well and re-cover with foil for a one-hour incubation at 750 revolutions per minute at room temperature.At the end of the incubation, add 25 microliters streptavidin phycoerythrin to each well and return the plate to the shaker for an additional 30 minutes at room temperature. At the end of the incubation, place the plate onto the magnetic separator for two minutes before decanting the well contents. Wash the plate two times with 200 microliters of fresh washing buffer per wash and add 75 microliters of the appropriate drive fluid to each well.Then, re-suspend the beads on the plate shaker for five minutes at room temperature and read the plates on the analyzer according to the manufacturer's instructions. In this analysis, the cerebral blood flow was measured with diffuse correlation spectroscopy four hours after the last injury. The cerebral blood flow index and mean cerebral flow index for each hemisphere can then be determined.A linear range analysis can be conducted to determine an appropriate protein loading mass prior to collecting data from all samples. Cytokine data can be prepared by subtracting the background measurements from the sample data, then computing Z-score data for each anolyte. Partial least squares regression can be conducted by using a phagocyte microglial activation marker or other variable of interest as the response variable, and the cytokine measurements as the predictor variables.Varimax rotation can be performed to maximize the covariance of the data on latent variable one, with the activation marker measurements. High loading weights in latent variable one correspond with the cytokine expressions most associated with high expression of the activation marker. Linear regressions between the activation marker and cytokines illustrate that those cytokines with the greatest loading weights in latent variable one were also statistically significant for this analysis.Although we focused this protocol on traumatic brain injury, these methods are widely generalizable to the study of a plethora of pathological conditions that affect the brain. We use these techniques to help us identify tractable targets to modulate in future experiments to establish causal mechanistic relationships and ultimately with the goal of developing novel therapeutic strategies for mild traumatic brain injury.

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JoVE Journal

Neuroscience

3.0K vistas.  Georgia Institute of Technology and Emory University. Estos métodos se pueden utilizar para caracterizar las respuestas neuroinflamatorias y hemodinámicas a la lesión cerebral como parte de un análisis del sistema multivariante utilizando la regresión parcial de mínimos cuadrados. Estas técnicas se utilizan para dar una visión más holística de la respuesta del cerebro a las lesiones. Para inducir una lesión, confirme la falta de respuesta al pellizco del dedo del pie en un ratón anestesiado y coloque el ratón en la posición prona e...