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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

In this study, we demonstrate the use of kinematic gait analysis based on ventral plane imaging to monitor the subtle changes in motor coordination as well as the progression of neurodegeneration with advancing age in mouse models (e.g., endophilin mutant mouse lines).

Abstract

Motor behavior tests are commonly used to determine the functional relevance of a rodent model and to test newly developed treatments in these animals. Specifically, gait analysis allows recapturing disease relevant phenotypes that are observed in human patients, especially in neurodegenerative diseases that affect motor abilities such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and others. In early studies along this line, the measurement of gait parameters was laborious and depended on factors that were hard to control (e.g., running speed, continuous running). The development of ventral plane imaging (VPI) systems made it feasible to perform gait analysis at a large scale, making this method a useful tool for the assessment of motor behavior in rodents. Here, we present an in-depth protocol of how to use kinematic gait analysis to examine the age-dependent progression of motor deficits in mouse models of neurodegeneration; mouse lines with decreased levels of endophilin, in which neurodegenerative damage progressively increases with age, are used as an example.

Introduction

Neurodegenerative diseases impose a significant burden on patients, families, and society, and will become of even greater concern as life expectancy increases, and the world population continues to age. One of the most common symptoms of neurodegenerative diseases are balance and mobility problems. Thus, characterization of motor behavior in aging mammalian (e.g., rodent) models, and/or models showing neurodegenerative phenotypes, is a valuable tool to demonstrate the in vivo relevance of the specific animal model(s), or therapeutic treatments that aim to improve the disease symptoms. Almost every approach to treat neurodegenerative diseases ultimately requires testing in an animal model before initiation of a clinical trial in humans. Therefore, it is crucial to have reliable, reproducible behavior tests that can be used to consistently quantify disease-relevant phenotypes along age progression, in order to ensure that a candidate drug, which showed potential in an in vitro model, can effectively ameliorate the phenotype in a living animal.

One aspect of motor behavior assessment in rodents is kinematic gait analysis, which can be performed by VPI (also called ventral plane videography)1,2. This established method capitalizes on continuous recording of the underside of the rodents walking atop a transparent and motorized treadmill belt1,2,3,4. Analysis of the video feed data creates "digital paw prints" of all four limbs that dynamically and reliably recapitulate the rodent's walking pattern, as originally described by Kale et al.2 and Amende et al.3.

The principle of imaging-based gait analysis is to measure the paw area in contact with the treadmill belt over time, for each individual paw. Every stance is represented by an increase in paw area (in the braking phase) and a decrease in paw area (in the propulsion phase). This is followed by the swing phase in which no signal is detected. Swing and stance together form a stride. In addition to gait dynamics parameters, posture parameters can also be extracted from the recorded videos. Exemplary parameters and their definition are listed in Table 1 and include stance width (SW; the combined distance from the fore or hind paws to the snout-tail axis), stride length (SL; average distance between two strides of the same paw), or paw placement angle (the angle of the paw to the snout-tail axis). The posture and gait dynamics data allow drawing conclusions on animal balance (by posture parameters and their variability over several steps) and coordination (by gait dynamics parameters). Other parameters, such as ataxia coefficient (the SL variability calculated by [(max. SL−min. SL)/mean SL]), hind limb shared stance time (time that both hind limbs are in contact with the belt), or paw drag (total area of the paw on the belt from full stance to paw lift-off) can also be extracted, and have been reported to be changed in various neurodegenerative disease models5,6,7,8 (see Table 1).

ParameterUnitDefinition
swing timemsduration of time the paw is not in contact with the belt
stance timemsduration of time the paw is in contact with the belt
% brake% of stance timepercentage of stance time the paws are in the brake phase
% propel% of stance timepercentage of stance time the paws are in the propulsion phase
stance widthcmcombined distance from the fore or hind paws to the snout-tail axis
stride lengthcmaverage distance between two strides of the same paw
stride frequencystrides/snumber of complete strides per second
paw placement angledegangle of the paw in relation to the snout-tail axis of the animal
ataxia coefficienta.u.SL variability calculated by [(max SL-min SL)/mean SL]
% shared stance% of stancehind limb shared stance time; time that both hind limbs are in contact with the belt at the same time
paw dragmm2total area of the paw on the belt from full stance to paw lift-off
limb loadingcm2MAX dA/dT; maximal rate of change of paw area in the breaking phase
step angle variabilitydegstandard deviation of the angle between the hind paws as a function of SL and SW

Table 1. Definition of key gait parameters that can be tested by ventral plane imaging.

Assessing the motor behavior of rodent models for neurodegenerative diseases can be challenging depending on the severity of the phenotype of a specific model at a given age. Several diseases, most prominently PD, show strong motor behavior (locomotion) deficits, both in patients and in animal models. One of the four key symptoms in PD is bradykinesia, which progresses with aging and manifests in severe gait impairments already in early stages of PD9. Studies of the acute PD model, rodents treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridin (MPTP), have already used VPI gait analysis10,11,12. However, given the acute nature of this model, these studies do not address the age-related progression of motor deficits. Several recent studies have conducted gait analysis in aged mice with neurodegenerative changes, for example13,14,15, emphasizing the relevance of understanding the disease progression with advancing age.

In addition to motor deficits, animal models of neurodegenerative diseases often have difficulties focusing on the examination tasks and show prominent cognitive impairments, in particular with advancing age. Such a phenotype can influence the result of motor behavior tests. Namely, one of the most widely used tests to examine motor deficits, the rotarod test16, relies on cognition, attention, and stress17,18. While the willingness to walk on a motorized treadmill also depends on these factors, the recorded read-out is running, which is a more standardized feature and far less influenced by altered cognition. Effects of stress and attention may be visible in specific parameters, like swing/stance time for stress, and SL for attention19,20, but not in overall running ability.

The kinematic gait analysis approach further offers the advantage of having options to adjust the challenge for rodent models. The treadmill with adjustable angle and speed allows walking speeds from 0.1 - 99.9 cm/s, so that rodents with severe walking impairments may still be able to run at a slow speed (~10 cm/s). Non-impaired animals can be measured at faster running speeds (30 - 40 cm/s). The observation of whether or not the tested animals are able to run at a certain speed provides a result by itself. Further, the rodent can be additionally challenged to run up an incline, or down a decline, by tilting the treadmill to a desired angle with the help of a goniometer, or by attaching a weighted sled to mouse or rat hind limbs.

In addition to numerous studies of single proteins that are mutated in patients, there is a recent increasing awareness of the links between defective endocytosis process and neurodegeneration13,21,22,23,24,25,26,27,28. Mouse models with reduced levels of endophilin-A (henceforth endophilin), a key player in both clathrin-mediated endocytosis13,21,29,30,31,32,33,45 and clathrin-independent endocytosis34, were found to show neurodegeneration and age-dependent impairments in locomotor activity13,21. Three genes encode the family of endophilin proteins: endophilin 1, endophilin 2, and endophilin 3. Notably, the phenotype resulting from depletion of endophilin proteins varies greatly depending on the number of missing endophilin genes13,21. While triple knock-out (KO) of all endophilin genes is lethal just a few hours after birth, and mice without both endophilin 1 and 2 fail to thrive and die within 3 weeks after birth, single KO for any of the three endophilins shows no obvious phenotype for tested conditions21. Other endophilin mutant genotypes show reduced lifespan and develop motor impairments with increasing age13. For example, endophilin 1KO-2HT-3KO mice display walking alterations and motor coordination problems (as tested by kinematic gait analysis and rotarod) already at 3 months of age, while their littermates, endophilin 1KO-2WT-3KO animals, display a significant reduction in motor coordination only at 15 months of age13. Due to the vast diversity of phenotypes in these models, it is necessary to identify and apply a test that can integrate a variety of challenges corresponding to the animal's motor and cognition abilities, as well as the age. Here, we detail the experimental procedures that capitalize on the kinematic gait analysis to assess the onset and progression of motor impairments in a mouse model that shows neurodegenerative changes (i.e., endophilin mutants). This includes measuring gait parameters at various ages and different severities of locomotion impairments.

Protocol

All animal experiments reported here are conducted according to the European Guidelines for animal welfare (2010/63/EU) with approval by the Niedersächsisches Landesamt für Verbraucherschutz und Lebensmittelsicherheit (LAVES), registration number 14/1701.

1. Study Design

  1. As animal behavior work requires careful planning, consider the following parameters while designing the experiment.
    1. Number of animals needed per group.
      1. Use a statistical software (e.g., PASS, EDA, or GPower) to calculate the required group size.
        NOTE: The group size depends on the variation between animals and the severity of the phenotype. For the kinematic gait analysis, the number of mice is usually 10 - 20 per group.
    2. Sex of the experimental animals.
      1. Consider the effect of estrogen levels on the experiment, depending on the animal strain.
        NOTE: Many behavior studies focus on males in order to avoid the influence of estrogen levels on the experiment. These influences are more or less strong depending on the animal background strain.
      2. If both sexes will be used, test for sex influence and evaluate the two sexes independently when necessary.
    3. Age of the experimental animals.
      1. Use adult animals (2 months of age, or older) if only one-time point is needed.
      2. Select several time points when change in motor behavior with advancing age is to be studied. The earliest possible time point is 1 month, after mice are weaned from their mothers. Test the animals in regular intervals, e.g., every 1, 2, or 3 months.
  2. Apply for authorization from the local authorities to perform animal behavior testing.
  3. Make plans for procuring the test animals.
    1. Make a breeding plan or contact an animal distributor in a timely manner so that enough experimental animals are available on the day when the experiments start.
    2. Allow the animals to habituate for one week if they are kept in a new room/setting during the experiments.

2. Video Recording

NOTE: To illustrate the use of kinematic gait analysis, here a commercially available imaging system with its accompanying imaging and analysis software (see the Table of Materials) are used.

  1. Start the computer and the imager software.
  2. Determine the health status and well-being of each animal by observing it in its home cage, and weighing it on a balance.
  3. When needed, gently apply red finger paint to the animal's paws with a brush. Allow the paint to dry for ~5 min in a spare clean cage.
    NOTE: Avoid painting the animal's abdomen as the paint is used to enhance the contrast between paws and body. It is useful to have black finger paint handy for corrections. This step is needed for animals with brown fur, or in case the paws have been tattooed for identification. If chosen to paint the paws of one animal, all animals in the same group and control group need to be painted as well.
  4. Set the speed of the treadmill on the top right panel of the apparatus; If more than one running speed will be applied, start with the slowest speed first.
  5. Place the animal in the test chamber (avoid clamping the tail or paws when closing the chamber). Cover the chamber with a dark cloth and allow each animal to adjust for 1 - 2 min.
  6. Turn on the light in the test chamber by turning the treadmill light rotary switch to the "on" position. Turn the treadmill rotary switch to "forward" to start the treadmill, then click the "record" button in the imager software.
    NOTE: While the treadmill is running, it is important to observe animal performance carefully and constantly: stop the treadmill immediately if the animal cannot keep up with the treadmill speed, or shows secondary symptoms non-related to locomotion (e.g., epileptic seizures). Testing conditions may need to be readjusted.
  7. When the animal runs stably (no quick escapes to the sides, front, or back), record for at least 5 s before stopping the treadmill. Stop recording by clicking "stop" on the imager software, and turn the treadmill rotary switch back to the "off" position.
    NOTE: To avoid unstable running of animals it can be helpful to let them run for several seconds, or to allow them to run in the other direction (by turning the treadmill rotary switch to "reverse" instead of "forward").
  8. Click the "processing" button in the imager software to open a menu in which the start and the end point of the video section (to be used for analysis) can be set. To do this, use the slider on the bottom of the screen to navigate through the video.
  9. To select the current time point as the start or end point, click "from frame #" and "to," respectively. Make sure the section contains at least 7 steps/paw (14 steps in total) of the animal running stably at a constant speed.
  10. Enter the animal identification, birth date, weight, and sex. Save the data on a desired location on the computer or server. Click "camera" to return to the recording interface.
  11. If multiple running speeds need to be recorded, repeat steps 2.6 - 2.10 with the desired running speeds. Before recording the next video, ensure that the red paint is still present on the paw, otherwise repeat step 2.3.
  12. After recording, release the animal to its home cage. After removing an animal, clean the treadmill belt thoroughly with soapy water followed by disinfectant to prepare it for the next experimental animal.

3. Video Processing

  1. Start the analysis software and click "select study folder" to select the folder with the recorded videos.
  2. Select one video, or several videos that can be processed consecutively, and click "go."
  3. Use the "redraw" function to select the area where the mouse is running; this section should only contain the mouse and white background.
  4. If the "reverse" treadmill function was previously used, choose "Check if subject's nose is to your right >>>" to mirror the video since the software is designed to only analyze animals running to the left. Click "accept" to proceed.
  5. Use the "refresh" function to see the default mask and paw print that the software detects.
    NOTE: The original video is displayed on the left, and a black and white image of the proposed paw prints is on the right.
  6. Enter values in the "length" and "width" boxes to change the mask that excludes the red area around the snout of the animal for analysis; as the color is similar to the paws, not masking that area could result in the software accidentally classifying the snout area as a paw.
  7. Adjust the sliders "filter noise" and "filter fur and dark patches" to optimize the black and white paw print. Set the "filter noise" slider to ~800 - 950 for black animals and to ~700 - 800 for brown or white animals, depending on the exact fur color of the animal. Select "ok" when the settings are satisfactory.
    NOTE: The "filter fur and dark patches" slider depends on how "red" the paw is. For painted paws, the value is usually around 100 - 120, and for non-painted paws the best value is around 50 - 100. These settings depend on the color shadings of the fur and paws, and need to be optimized for every animal. The black and white paw print should have clear representations of the paws with as little background noise as possible.
  8. Select one or several videos that passed the first adjustment (labeled with "@@" before the video name) and select the "go" function to start the analysis of these videos.
    NOTE: The analysis takes 2 - 5 min per video. It is possible to run the analysis of several videos overnight since this step requires no input from the experimenter.
  9. Select an analyzed video (labeled with "@@@") and click "go." Note that the paw area (in cm2) in contact with the belt over time (gait dynamics ) for each separate paw can now be seen. To compare the original video and the calculated paw print for a selected area, use the "play video" function.
  10. Use the following (three) tools to correct small mistakes made by the software.
    1. Use the "correct" option to delete a wrong signal, e.g., when the software records a signal even though the corresponding paw is not in contact with the belt. Click once to zoom into the relevant area, and mark the left border of the object to remove with the second click and the right border with the third click.
    2. Use the "connect" option to combine two signals, e.g., when no signal is recorded for a few frames even though the paw is in contact with the belt. Click once to zoom into the relevant area and double-click in the middle of the two objects to combine.
    3. Use the "delete" option to remove time points from the analysis completely. Use this option only if the mistake cannot be fixed with the "correct" or "connect" function, e.g., when a signal from the left forelimb paw is accidentally recorded for the left hind limb paw. Click once to zoom into the relevant area, and mark the left border of the area to remove with the second click and the right border with the third click.
      NOTE: The tools may only be used to correct small mistakes; systematic failures (e.g., if the signal from one paw was extremely weak) cannot be corrected: the video should be excluded from analysis and the recording of the respective animal repeated, when possible. Note that the "play video" option is no longer available after the "correct," "connect," or "delete" option has been used, and clicking the "undo" button will reset all 3 editing tools.
  11. Select "next limb" to proceed through the 4 limbs; when "next limb" is clicked after the last paw, the software completes the analysis and shows the results for this animal on 4 screens.

4. Gait Analysis

  1. When all videos from one experiment are analyzed, select all videos and click "re-organize results" to export the results (a list of parameters in spreadsheet files).
  2. Open the file with the ending "reorganized_stride_info" and add information that is not included in this spreadsheet: group information (e.g., genotype, treatment), age, and the measurements of animal length and width which are saved in another spreadsheet file with the ending "SFI_TFI_PFI_reorganized_stride_info."
  3. Normalize the gait parameters to animal width or length where necessary, e.g., SL to animal length and SW to animal width.
  4. Sort the results by group, age, and running speed: analyze all these conditions independently.
    NOTE: Different ages or running speeds cannot be combined within a same group.
  5. Calculate the average (mean) values, standard deviation, and standard error of the mean for each parameter for all experimental conditions.
  6. Perform statistical analysis according to the experimental design, e.g., use a 2-tailed t-test to compare mutant/treated animal to a wild-type (WT)/control, or ANOVA to compare several independent groups.
  7. Look at all measured parameters: it is helpful to plot each parameter to better visualize the results. If there are statistical differences in a given parameter, check if other dependent parameters change correspondingly.
    NOTE: For example, if the SL is significantly decreased in a certain test group, this will also cause a higher stride frequency (since the running speed is the same) and may result in an increased SW (in order to maintain posture stability).
  8. Select parameters that are most relevant for a model, and/or are comparable to observations in the human disease. For a presentation, create representative videos for each group and complement them by graphs showing the readout for the relevant parameters, since subtle gait changes are often not obvious from the videos.

5. Troubleshooting

NOTE: Some animals, especially mouse models with an anxiety phenotype, may have difficulties to perform even a simple task like running on a treadmill. The following are steps that can be taken to lower anxiety levels and encourage running.

  1. Habituation and positive enforcement.
    1. At 2 - 3 days before the first test, place the mouse in the test chamber, cover it with a dark cloth, and leave the light turned off. Let the mouse adjust to the new environment for ~5 min. Add chow or chocolate/nut butter (e.g., Nutella) to the test chamber so a positive association may be formed.
  2. Negative enforcement by air puffs/rear boundary.
    1. Mice do not like air puffs or a movement behind them, and will run away from the disturbance. To motivate running, use mild air puffs, or rhythmic movement of the flexible bar that forms the rear boundary of the test chamber, to encourage the mouse to run towards the front part of the test chamber.
  3. Slow start.
    1. When testing fast running speeds, start the treadmill at a lower speed and then slowly increase the treadmill speed towards the desired testing condition.
  4. Minimize free movement.
    1. The test chamber length is limited by two adjustable bars in the front and back. If a test animal keeps up with the running speed but does not run steadily, limit the chamber's length to result in more steady running.
  5. If the above-mentioned measurements are not successful, record running on the next day. If the animal still refuses to run after testing on three days, record this as the finding, and exclude the animal from further testing.
    NOTE: The results of the gait analysis depend on good-quality video recording. There is no reason to exclude videos during the analysis if the videos have been recorded carefully. If the video quality is insufficient, it will become obvious during step 3.6 when the parameters for the creation of the digital paw print are being set. If any other body part except the paws and snout appears red (e.g., due to the missing fur around the genitals or finger paint sprinklings on the abdomen), the quality drops significantly. The adjustments in step 3.6 allow correcting only small issues, and if this cannot bring the video to an acceptable signal/noise ratio, the video needs to be excluded from the analysis, and recording needs to be repeated. Thus, it is recommended to analyze videos soon after recordings are performed.

Results

To illustrate the use of kinematic gait analysis, we have performed gait analysis on WT C57BL/6J mice with advancing age, as well as several endophilin mutant lines, using commercially available instrumentation and software (please refer to the Table of Materials). In this setup, a high-speed camera under a transparent treadmill records the running of a mouse (Figure 1A). The software then recognizes the contrast between the red colored paws ...

Discussion

Studying the motor coordination is a useful approach in the characterization of models of neurodegenerative diseases, especially for diseases like PD in which motor coordination is severely affected. With the help of a kinematic gait analysis functional assay, we can identify subtle changes in the gait of animals at the onset of locomotion problems, or in models with weak neurodegeneration and hence relatively modest phenotype. Given the wide range of phenotypes in various models of neurodegenerative diseases that encomp...

Disclosures

The authors declare no competing financial interests.

Acknowledgements

We thank animal caretakers at the ENI's Animal facility for help with breeding, and Dr. Nuno Raimundo for useful comments on the manuscript. I.M. is supported by the grants from the German Research Foundation (DFG) through the collaborative research center SFB-889 (project A8) and SFB-1190 (project P02), and the Emmy Noether Young Investigator Award (1702/1). C.M.R. is supported by the fellowship from the Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences (GGNB).

Materials

NameCompanyCatalog NumberComments
DigiGaitMouse Specifics, Inc., Framingham, Massachusetts, USADigiGait Imager and Analysis Software are included with the hardware
non-transparent blanket or dark clothcover the test chamber to reduce the animal's feeling of exposure/stress
balancee.g. Satoriusbalance with 0.1 g accuracy and a maximum load of at least 100 g
red finger painte.g. Kreul or Staedtlerfor increasing the contrast between paws and animal’s body
small paint brushsoft brush to apply finger paint to the animal paws
diluted detergentfor cleaning
disinfectant, e.g. Meliseptol or 70% ethanole.g. B.Braunfor desinfection

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