© 2019. Published by The Company of Biologists Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution and reproduction

in any medium provided that the original work is properly attributed.

In vivo cerebellar circuit function is disrupted in an mdx mouse model of

Duchenne muscular dystrophy

Trace L. Stay1,2,4, Lauren N. Miterko1,3,4, Marife Arancillo4, Tao Lin4, Roy V. Sillitoe1,2,3,4*

Affiliations:

1Department of Pathology & Immunology, Baylor College of Medicine

2Department of Neuroscience, Baylor College of Medicine

3Program in Developmental Biology, Baylor College of Medicine

4Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250

Moursund Street, Suite 1325, Houston, Texas 77030, USA

*Corresponding author:

Dr. Roy V. Sillitoe Mailing address:

Jan and Dan Duncan Neurological Research Institute

1250 Moursund Street

Houston TX 77030

Tel: 832-824-8913

Fax: 832-825-1251

Email: sillitoe@bcm.edu

ORCID ID: https://orcid.org/0000-0002-6177-6190

Abbreviated title: Cerebellar dysfunction in muscular dystrophy

Keywords: Duchenne muscular dystrophy, mdx mice, cerebellum, Purkinje cell, cerebellar

nuclei, circuitry, in vivo electrophysiology

Conflicts of Interest: No competing interests declared.

Contributions: T.L.S., L.N.M., M.A. and R.V.S. designed the experiments. T.L.S., L.N.M.,

M.A., and T.L. performed the experiments. T.L.S., M.A., L.N.M. and R.V.S. wrote the paper.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

http://dmm.biologists.org/lookup/doi/10.1242/dmm.040840Access the most recent version at First posted online on 8 November 2019 as 10.1242/dmm.040840

SUMMARY STATEMENT

The mdx mouse model of Duchenne muscular dystrophy has in vivo abnormalities in cerebellar

spike firing, which could promote the neurological symptoms observed in DMD patients.

ABSTRACT

Duchenne muscular dystrophy (DMD) is a debilitating and ultimately lethal disease involving

progressive muscle degeneration and neurological dysfunction. DMD is caused by mutations in

the dystrophin gene, which result in extremely low or a total loss of dystrophin protein

expression. In the brain, dystrophin is heavily localized to cerebellar Purkinje cells, which

control motor and non-motor functions. In vitro experiments in mouse Purkinje cells reported

that loss of dystrophin leads to low firing rates and high spiking variability. However, it is still

unclear how the loss of dystrophin affects cerebellar function in the intact brain. Here, we used in

vivo electrophysiology to record Purkinje cells and cerebellar nuclear neurons in awake and

anesthetized female mdx mice. Purkinje cell simple spike firing rate is significantly lower in mdx

mice compared to controls. Although simple spike firing regularity is not affected, complex

spike regularity is increased in mdx mutants. Mean firing rate in cerebellar nuclear neurons is not

altered in mdx mice, but their local firing pattern is irregular. Based on the relatively well-

preserved cytoarchitecture in the mdx cerebellum, our data suggest that faulty signals across the

Purkinje cell to cerebellar nuclei circuit drive the abnormal firing activity. The in vivo

requirements of dystrophin during cerebellar circuit communication could help explain the motor

and cognitive anomalies seen in patients with DMD.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

INTRODUCTION

Duchenne muscular dystrophy (DMD) is a devastating X-linked disease that affects ~1 in 5,000

boys (Guiraud et al., 2015). DMD is caused by mutations in the dystrophin gene (DMD, Burghes

et al., 1987; Hoffman et al., 1987; Monaco et al., 1986). The mutations eliminate the expression

of the 427 kDa protein dystrophin, or lower it to less than 5% of normal. DMD mutations also

cause the milder disease, Becker muscular dystrophy (BMD), as well as X-linked dilated

cardiomyopathy (XLDC). Interestingly, although heterozygous female carriers of DMD

mutations are typically asymptomatic, up to approximately 8% of these carriers are considered as

manifesting carriers who develop symptoms ranging from mild muscle weakness to a rapidly

progressive DMD-like muscular dystrophy (Birnkrant et al., 2018; Moser and Emery, 1974;

Norman and Harper, 1989; Taylor et al., 2007). Female carriers have also been reported to have

cognitive abnormalities (Imbornoni et al., 2014; Mercier et al., 2013; Papa et al., 2016).

Dystrophin functions as a tether for stabilizing protein complexes, and in the brain, it also

interacts with membrane proteins that mediate neuronal communication (Pilgram et al., 2010;

Waite et al., 2009). Accordingly, loss of dystrophin can impair brain function (Anderson et al.,

2002; Mirski and Crawford, 2014; Pereira da Silva et al., 2018; Snow et al., 2014). Cognition

and movement are often affected, although the neural bases of these behavioral defects are

unclear. In this study, we sought to gain a deeper understanding of how neuronal signals are

altered in the DMD brain. Towards this, we used an mdx mouse model to test how the loss of

dystrophin (Dp427 isoform) alters cerebellar function by measuring neuronal activity in vivo

(Grady et al., 2006; Ryder-Cook et al., 1988; Sicinski et al., 1989; Sillitoe et al., 2003).

Dystrophin protein complexes are heavily expressed in the cerebellum where they are localized

predominantly to Purkinje cells (Blake et al., 1999; Lidov et al., 1990; Lidov et al., 1993; Sillitoe

et al., 2003). Purkinje cells are the principal cell type of the cerebellum and the computational

center for executing all cerebellar dependent behaviors (Reeber et al., 2013). In mice, the loss of

dystrophin dramatically alters Purkinje cell microcircuit organization (Sillitoe et al., 2003). Such

structural alterations are consistent with the abnormal behaviors in mdx mutant mice, including

uncoordinated movement (Grady et al., 2006). These molecular and behavioral defects are also

consistent with defects in neuronal activity. In vitro electrophysiology experiments demonstrated

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

that dissociated Purkinje cell firing activity is compromised in mdx mice (Snow et al., 2014).

They found that Purkinje cells from the mdx mice fired more irregularly than control cells and

that the membrane potential was hyperpolarized (Snow et al., 2014). This study also reported a

lower-than-normal Purkinje cell firing frequency in dissociated mdx Purkinje cells. Their results

are consistent with other reports that showed a reduction in the number of GABA synapses on

Purkinje cells (Kueh et al., 2011), aberrant GABA release and uptake in cerebellar synaptosomes

(Pereira da Silva et al., 2018), and a reduction in postsynaptic long-term depression (LTD) in

mdx Purkinje cells (though Sesay et al., 1996 found no LTP changes in mdx urethane-

anesthetized hippocampal cells, which could be related to the anesthetic effects of urethane, e.g.

Hara and Harris, 2002). Interestingly, homosynaptic LTD at parallel fiber-Purkinje cell synapses

is enhanced in mdx mutant mice (Anderson et al., 2010). But how altering these intrinsic

membrane properties of Purkinje cells affects circuit function in the intact cerebellum in vivo

remains largely unsolved.

The cerebellum controls a variety of motor behaviors including coordination, learning, balance,

and posture (Reeber et al., 2013; Thach, 2014). It may also play a pivotal role in non-motor

functions such as cognition, language, emotion, reward, social interactions, and spatial working

memory (Buckner, 2013; Carta et al., 2019; D’Angelo and Casali, 2013; McAfee et al., 2019;

Stoodley, 2012). The execution of all these behaviors requires proper Purkinje cell function

(Heiney et al., 2014; Tsai et al., 2012; White et al., 2014). Importantly, motor and non-motor

Purkinje cell functions could be relevant to DMD (Anderson et al., 2002). In either case, the

canonical Purkinje cell circuit is likely involved. Purkinje cells receive direct excitatory input

from climbing fibers and granule cell parallel fiber axons, and inhibitory inputs from stellate and

basket cell interneurons. Purkinje cells are the only output of the cerebellar cortex, and inhibit

neurons in the cerebellar and vestibular nuclei. The cerebellar nuclei are located in the inner core

of the cerebellum and provide the main output of the cerebellum. We hypothesize that in DMD,

Purkinje cells fire abnormally and as a consequence behavioral output is negatively impacted. In

this study, we address how the loss of dystrophin affects Purkinje cell function, and we

specifically assess how their firing activity is affected in vivo in mice (Arancillo et al., 2015;

White et al., 2014).

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

We performed in vivo extracellular recordings in both anesthetized and awake adult control and

mdx mutant mice. The main objective of this study was to investigate whether functional changes

occur in vivo in Purkinje cells and in their downstream target cerebellar nuclear cells when

dystrophin is absent. Our experiments revealed three main findings: 1) Purkinje cell simple spike

firing rate is significantly lower in mdx mutant mice; 2) the pattern of firing in mdx cerebellar

nuclear neurons is more irregular compared to controls; and 3) the overall firing features of the

mdx Purkinje cells are highly reminiscent of the defects observed in several mutant mouse strains

that model cerebellar disease, including ataxia and dystonia (Fremont et al., 2014; Gao et al.,

2012; White and Sillitoe, 2017; White et al., 2014; White et al., 2016a). Altogether, our findings

provide a functional correlate to the well-studied anatomical and molecular pathogenesis of

DMD (Guiraud and Davies, 2019), and they also provide a valuable set of cell activity data for

evaluating exactly how different brain functions might be affected in vivo in the different

muscular dystrophies.

RESULTS

Circuit architecture is unaltered in mdx mice

Mouse models of disease often exhibit changes in the anatomy of cerebellar microcircuits

(Cendelin, 2014; Lalonde and Strazielle, 2007; Landis and Landis, 1978), which could affect the

normal properties of cerebellar function (Barmack and Yakhnitsa, 2008; Davie et al., 2008; De

Zeeuw et al., 2011; Ruigrok et al., 2011; Schmolesky et al., 2002). To address whether this is the

case in C57BL/10ScSn-Dmdmdx/J homozygous mutant mice (from here on referred to as mdx

mice), we examined the regional localization and layered tri-laminar distribution of cerebellar

cells in mdx mice by immunostaining with a panel of cell-specific molecular markers (Fig. 1). As

expected from this mouse model, we confirmed that the mdx Purkinje cells lack dystrophin

protein (Dp427; Fig. 1A). We first examined the inhibitory neurons of the cerebellar cortex using

markers that identify each cell type (Reeber and Sillitoe, 2011; White et al., 2014; White et al.,

2016b). Using CAR8 staining (Miterko et al., 2019a; White et al., 2016a), we found that mutant

Purkinje cells were arranged into the characteristic monolayer and exhibited their signature,

wide-spanning dendritic architecture, as also observed in C57BL/10ScSnJ controls (from here on

referred to as controls; Fig. 1B). Overall inhibitory interneuron distribution was also similar

between genotypes when revealed with parvalbumin staining (Fig. 1C). Basket cell projections

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

were identified in the mdx mice, as seen through staining for NFH (Fig. 1D). Additionally, the

overall distribution of Golgi cells in the granule cell layer of mdx mice was equivalent to

controls, as shown by neurogranin staining (Fig. 1E). These data suggest that inhibitory neurons

in the cerebellar cortex of mdx mice have similar dorsoventral patterning and regional

distributions to the control mice.

We next examined the excitatory neurons and the excitatory afferent inputs to the cerebellar

cortex through immunohistochemistry (White et al., 2014; White et al., 2016b). Adult

differentiated granule cells were stained with GABAaRα6; they were correctly accumulated in

the granule cell layer in mdx mice (Fig. 1F). Unipolar brush cells are a specialized type of

neuron localized predominantly to lobules IX and X (Diño et al., 1999), with a secondary site of

localization in lobules VI and VII (Sillitoe et al., 2003). In mdx mice, the unipolar brush cells

were heavily immunoreactive for calretinin, and as in control mice, were located mainly in

lobules IX and X (Fig. 1G). We used VGLUT1 expression to demonstrate that the terminals of

granule cell projections, found on their parallel fibers, were represented in their typical

abundance in the molecular layer in mdx mice (Fig. 1H). Mossy fiber inputs to the granular layer

and climbing fibers inputs to the molecular layer were clear in mdx mice, with both classes of

terminals revealed by VGLUT2 (Fig. 1I). The climbing fibers were also visualized with CART

(Fig. 1J), which showed the normal climbing trajectory of axons in the molecular layer of mdx

mice. Overall, the normal cellular layering, cell distribution, neuronal patterning, and afferent

terminal field localization in the cerebellar circuit of mdx mice argues against any major

developmental morphogenetic rearrangements as a major contributor to the neurological deficits

observed in the mdx mice.

Lack of overt neurodegeneration in mdx mice

Cerebellar size and molecular layer thickness can also be altered in disease models, with

variations from the normal range indicative of improper development and function (Hansen et

al., 2013). These two measures are also useful anatomical readouts of neurodegeneration and cell

loss. If Purkinje cells succumb to degeneration, regression of their large dendritic trees, the most

notable entity of the molecular layer, results in a significant decrease in the size of the cerebellar

cortex (Miterko et al., 2019a). Towards this, we analyzed cerebellar size and molecular layer

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

thickness in mdx and control mice to provide an overall impression of cerebellar architectural

integrity. The distance we measured was from the apical edge of the Purkinje cell soma to the

pial boundary of the molecular layer region directly above (Brown et al., 2019; White et al.,

2014; White et al., 2016a). Measurements from three mice of each genotype did not reveal a

significant difference in total cerebellar size or molecular layer thickness (Fig. 2; Cerebellar size:

control = 30.1 x 106 ± 2.8 x 106 μm2, mdx = 29.2 x 106 ± 1.9 x 106 μm2, t(4) = 0.280, p = 0.79;

molecular layer thickness: control = 152.3 ± 3.7 μm, mdx = 155.7 ± 4.0 μm, t(4) = -0.623, p =

0.57). A more detailed analysis of Purkinje cell numbers, cerebellar nuclear areas, and cerebellar

nuclear densities additionally confirm that overt neurodegeneration does not occur in mdx mice

at the ages examined (Fig. S1). The number of Purkinje cells in mdx mice does not differ from

controls when counted from all vermis lobules or when counts are taken from specific zones

(Fig. S1A-D; control = 569.2 ± 32.7 (whole), 256.0 ± 12.9 (anterior), 169.4 ± 7.4 (central), 143.8

± 14.3 (posterior/nodular), mdx = 578.7 ± 6.7 (whole), 260.6 ± 3.6 (anterior), 181.4 ± 5.1

(central), 136.7 ± 2.3 (posterior/nodular); t(4) = -0.286, p = 0.79, t(4) = -0.340, p = 0.75, t(4) = -

1.345, p = 0.25, t(4) = 0.489, p = 0.65, respectively). Likewise, the areas and densities of the

cerebellar nuclei in the mdx mice are comparable to that of control mice (Fig. S1E-J; Areas:

control = 1,242.5 ± 154.9 μm2 (Fastigial, FN), 4,051.9 ± 385.4 μm2 (Interposed, IN), mdx =

1,483.5 ± 287.7 μm2 (FN), 3,015.8 ± 567.9 μm2 (IN); Densities (number of nuclei/50 μm):

control = 17.36 ± 1.61 (FN), 36.11 ± 3.12 (IN), mdx = 21.26 ± 1.20 (FN), 33.19 ± 1.14 (IN); t(4)

= -0.737, p = 0.50, t(4) = 1.510, p = 0.21, t(4) = -1.9646, p = 0.12, t(4) = 0.880, p = 0.43,

respectively). These data suggest that the main cellular components of the cerebellar circuit

maintain their anatomical integrity in the mdx mice.

In vivo Purkinje cell function is abnormal in mdx mice

Having established that the gross anatomy and basic circuit features of the cerebellum are

undisturbed in the mdx mice, we next tested functional properties (Fig. 3). We first recorded

from anesthetized control and mdx Purkinje cells (Fig. 3A, B) to provide a large cell yield.

Recordings revealed similar membrane voltages between the genotypes (e.g. example voltage

traces in Fig. 3C, D) and based on their firing signatures, both genotypes had recognizable

Purkinje cells, with clear complex spikes confirming their cell identity (noted by green asterisks

in Fig. 3C, D). Additionally, individual simple spike and complex spike waveforms were

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

comparable between control and mdx mice (Fig. 3E-H). These data provided us with confidence

that if Purkinje cells in the mdx mice are functionally abnormal, it would be due to changes in

their spike firing patterns rather than due to a change in or loss of the different spike types

themselves (e.g. after conditional deletion of complex spike activity, White and Sillitoe, 2017).

Therefore, in order to examine how the Purkinje cells behave in vivo, we analyzed and compared

their mean firing summary statistics.

Genotype had a significant effect on the combined set of anesthetized simple spike mean firing

rate, mean CV, and mean CV2 (one-way MANOVA, Wilk’s λ(1,92) = 0.9028, p = 0.026).

However, even though simple spike firing was ~13% lower in mdx animals compared to controls

(Fig. 3I, 26.8 ± 1.9 Hz vs 30.8 ± 1.6 Hz; Wilcoxon rank sum test, z = 1.99, p = 0.047), this

change was not significant when corrected for multiple comparisons. Neither overall irregularity

(CV) nor local irregularity (CV2) showed significant differences (z = 1.76, p = 0.079 and z = -

1.48, p = 0.14, respectively). Genotype also did not have a significant effect on complex spike

firing (Fig. 3J, Wilk’s λ(1,92) = 0.9929, p = 0.89). Given the trend toward lower simple spike

firing in mdx mice, our previous data demonstrating that anesthesia can suppress Purkinje cell

activity in vivo (Arancillo et al., 2015), and the multiple reports of mdx Purkinje cell changes in

vitro (Anderson et al., 2002; Pereira da Silva et al., 2018; Snow et al., 2014), we were next

motivated to test whether cerebellar circuit dysfunction in the mdx mice might be more robust

and pronounced when analyzed in an awake and behaving context (Fig. 4).

Compared to anesthetized animals, visual inspection of the raw traces shows more complex

spikes in awake animals, as reported in previous studies (Arancillo et al., 2015). Upon further

examination of the raw firing traces between mdx mice and controls, we determined that the

structure of the spikes was similar between genotypes (Fig. 4C-D). Mean spike waveform shape

was identical for both simple spikes and complex spikes between genotypes (Fig. 4E-H). In

awake Purkinje cells, genotype had a significant effect on the set of simple spike mean firing

rate, mean CV, and mean CV2 (one-way MANOVA, Wilk’s λ(1,46)= 0.8266, p = 0.0371).

Interestingly, mean simple spike firing rate was significantly different, at ~19% lower in mdx

Purkinje cells (Fig. 4I, 69.1±3.4 vs 85.3±4.3 Hz; Wilcoxon rank sum test z = 2.53, p = 0.012).

No effects were observed in the regularity of spikes (CV z = -0.03, p = 0.98, CV2 z = -0.13, p =

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

0.89). In addition, complex spikes also differed between genotypes in the awake state (Fig. 4J,

Wilk’s λ(1,46)= 0.7772, p = 0.0106). While overall complex spike rate was not changed (Hz z =

-0.55, p = 0.58), overall complex spike variability was lower in mdx mice (CV = 0.76 ± 0.02 vs

0.92 ± 0.04; z = 3.17, p = 0.0016). Complex spike CV2 was not affected in Purkinje cells that

lack dystrophin (z = 0.75, p = 0.45). Together, these data demonstrate that in awake animals,

simple spike firing frequency is lower in mdx mice compared to controls. It also reveals less

variable complex spike firing in awake mdx mice.

We accounted for the expression of other dystrophin isoforms (i.e., Dp71, Dp116, Dp140, and

Dp260) in the mdx Purkinje cells by probing for expression of the common c-terminus domain

(Fig. S2). We confirmed antibody specificity by demonstrating heavy expression in the control

hippocampus, as previously reported (Blake et al., 1999), and antibody localization to the plasma

membrane of Purkinje cells (Fig. S2). We also evaluated the number of days since surgery (Fig.

S3) and the recording depth (Fig. S4; evaluated with respect to dorso-ventral and medio-lateral

coordinates relative to Paxinos and Franklin, Mouse Brain in Stereotaxic Coordinates, 3rd ed. via

labs.gaidi.ca/mouse-brain-atlas) as additional potential predictor variables. Through staining of

the c-terminus domain of the dystrophin protein, we found that the Purkinje cells of mdx mice

have comparable dystrophin expression to control Purkinje cells (Fig. S2). This suggests that the

mdx mutation and our electrophysiological findings are specific to the loss of the Dp427 isoform.

To assess the impact of the days post-surgery and the recording depth on our data, we binarized

each factor into low or high conditions relative to the median value (Figs. S3 and S4) and found

that neither factor had significant effects on awake simple spike firing in one-way MANOVAs

(respective Wilk’s λ’s: λ(1,46) = 0.9613, λ(1,46) = 0.9985; respective p-values: 0.63, 0.99). We

likewise examined the effect of predictor variables on complex spike firing in awake Purkinje

cells. Again, the recording days post-surgery and recording depth did not show significant effects

(λ(1,46) = 0.8533, p = 0.070; λ(1,46) = 0.9943, p = 0.97, respectively). Moreover, because

recording depth did not differ significantly between cells recorded in control compared to the

mdx mice (Wilcoxon rank sum test, z = 0.58, p = 0.56), it indicated that the differences in firing

between genotypes were not attributable to differential sampling. These data suggest that based

on the factors that we tested, the only factor showing a significant effect on simple spike and

complex spike firing properties in the awake mouse was the genotype of the mice; namely, the

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

loss of dystrophin, isoform Dp427, in the mdx mice. We therefore postulated that the simple

spike and complex spike firing defects in the mdx mice should alter the ability of Purkinje cells

to communicate their inhibitory output signals to their target neurons that are located in the three

divisions of the cerebellar nuclei.

Cerebellar nuclei output function is compromised in mdx mice

Having observed changes in Purkinje cell spike firing, we sought to determine what effect

changes in their output would have on cerebellar nuclei firing (Fig. 5A, B). Raw voltage traces

showed clear spike trains in the mutant mice (Fig. 5C-D). Days post-surgery, recorded position

(dorsoventral, anteroposterior, or mediolateral), or targeted nuclei all had no significant effect on

firing properties in our recorded sample (λ(1,49) = 0.9785, p = 0.79; λ(1,49) = 0.9022, p = 0.18;

λ(1,49) = 0.9174, p = 0.25; λ(1,49) = 0.8891, p = 0.13; λ(1,49) = 0.9019, p = 0.18, respectively;

Fig. S5). Genotype, however, did have a significant effect (λ(1,49) = 0.7494, p = 0.0033). In

pairwise testing, cerebellar nuclear firing rate and overall variability did not differ (z = -1.47, p =

0.14, z = -0.71, p = 0.48), but CV2 was ~19% higher in mdx mice (Fig. 5E; CV2 = 0.46 ± 0.02

vs 0.39 ± 0.02; z = -2.36, p = 0.018). This suggests that the net effect that lower Purkinje cell

simple spike firing output and lower complex spike variability has on cerebellar nuclear cells in

mdx mice is to increase the local variability of firing, or the variability in timing between one

spike and the next. This effect is not likely due to a change in full-length dystrophin expression

in the cerebellar nuclei themselves because the very modest expression in a small population of

cells is comparable between control and mdx mice (Fig. S6). It should be noted that in many

cells, the staining is barely beyond the level of background. Therefore, the changes we find in

Purkinje cell activity appear to affect cerebellar nuclei output activity with little to no impact

from dystrophin in the cerebellar nuclei. Activity changes in the cerebellar nuclei are predicted to

alter the manner in which the cerebellum communicates with the rest of the brain and spinal cord

during different behaviors. D

isea

se M

ode

ls &

Mec

hani

sms

• D

MM

• A

ccep

ted

man

uscr

ipt

DISCUSSION

DMD causes progressive muscle degeneration and fibrosis, which leads to loss of motor strength

and respiratory insufficiency (Falzarano et al., 2015). At later stages of disease, cardiomyopathy

develops, with heart failure or respiratory complications leading to death, on average in the mid-

30s, even with modern treatment regimens. Therapy for DMD has benefited significantly from

studies of genetic mouse models of muscular dystrophy, including the mdx model developed in

the late 1980s (Crone and Mah, 2018). Current investigational therapies for DMD with ongoing

research in DMD mouse models include exon skipping, micro-dystrophin or surrogate gene

therapy, gene editing, inflammation blockers, and stem cell delivery (Long et al., 2016; Min et

al., 2019). Canine models also offer immense insight into therapeutic approaches (Amoasii et al.,

2018), though for studies of how DMD impacts brain anatomy and circuit function, the mouse

still has advantages with respect to in vivo electrophysiology and complex genetics experiments.

Therefore, in addition to their utility for measuring muscle pathology, DMD mice could be a

promising avenue for uncovering the neural impairments often seen in individuals with DMD

(Anderson et al., 2002; Rae and O’Malley, 2016; Vaillend et al., 2004). In this regard, the

cerebellum has been a major target of interest (Cyrulnik and Hinton, 2008). Previous studies of

mdx electrophysiology have reported changes in GABA release and uptake from cerebellar

synaptosomes (Pereira da Silva et al., 2018) and lower firing rates and higher variability in the

firing of dissociated Purkinje cells (Snow et al., 2014). However, whether these deficits are seen

in awake mice has not previously been tested. Here, we tested this possibility and found that the

loss of dystrophin alters Purkinje cell and cerebellar nuclei communication in behaving mdx

mice.

The main goal of this paper was to investigate cerebellar function in vivo. The rationale was to

determine whether the neurological defects reported in human DMD patients are reflected by

changes in specific circuit functions in an alert state. Towards this, we recorded and examined

the electrophysiological properties of cerebellar neurons in the intact brain, in an mdx mouse

model of DMD. We chose to analyze only female mice to dissociate cerebellar functional output

from potential compensation (e.g. Xu-Wilson et al., 2009; Zwergal et al., 2013) due to higher

muscle degradation in males; however, it would be informative in future work to extend these

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

analyses to the more severely affected male mice (Hakim and Duan, 2012; Hourdé et al., 2013;

Salimena et al., 2000), or to heterozygous mice that express a relevant phenotype. Notably, we

did not observe any overt behavioral deficits in the mdx mice at the ages we examined,

suggesting that changes in the firing properties likely precede the onset of pathological motor

symptoms.

Before interrogating circuit function, we first determined that several anatomical properties of

the cerebellar microcircuit are unaffected in mdx mice, including cell type distribution, molecular

layer thickness, molecular patterning, and afferent terminal localization. We next recorded

cerebellar activity in vivo and found a significant decrease of approximately 19% in mean

Purkinje cell simple spike firing rate in mdx mice compared to controls (Fig. 4). Two measures

of simple spike variability showed no difference by genotype, but compared to controls, complex

spikes were ~17% less variable in the mdx mice (Fig. 4). The centrality of Purkinje cells in the

cerebellar cortical circuits place these findings in a broader context of cerebellar function in

disease (Reeber et al., 2013). Inputs from climbing fibers, inputs from mossy fiber-granule cell-

parallel fiber pathways, and local modulation by inhibitory molecular layer interneurons all

converge upon the Purkinje cell dendrites. Therefore, whatever the disease-causing injury

(genetic or physical) or the ultimate impact on the circuit, the Purkinje cells are almost always

involved in executing the response of the cerebellum. In mouse models of ataxia, in vitro

electrophysiological analyses of Purkinje cell spiking reveal alterations as a consequence of

molecular pathological defects and degeneration (SCA1 transgenic, Inoue et al., 2001), which

can start before the onset of obvious pathology (Purkinje cell specific SCA2 transgenic, Hansen

et al., 2013), or due to changes in Purkinje cell intrinsic excitability (SK3-1B-GFP, Shakkottai et

al., 2017). These data are supported by in vivo recordings demonstrating that Purkinje cell

activity is dramatically altered in ataxia, as revealed in the Car8wdl model that exhibits a severe

ataxia without neurodegeneration (Miterko et al., 2019a; White et al., 2016a). The significant

tremor in Car8wdl also implicates the Purkinje cell firing defects as a source of the 4-12 Hz

oscillations that might drive tremor pathophysiology (Kuo et al., 2019; White et al., 2016a).

Purkinje cell firing defects are also the source of the high-stepping gait, abnormal twisting of the

trunk and limbs, and poor mobility that is observed in different models of dystonia (Calderon et

al., 2011; Fremont et al., 2015; Fremont et al., 2017; Luna-Cancalon et al., 2014; White and

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Sillitoe, 2017). Here, we show that a mouse model of DMD, which is primarily a muscle

degenerative disease but with clear neurological and neuropsychiatric components, contains

cerebellar circuit deficits that fall into an expanding theme of activity-related firing disruptions.

Defective Purkinje cell spiking could therefore mediate a wide range of behavioral changes in all

conditions that involve cerebellar dysfunction.

Notably, Purkinje cells do not function in isolation: they synapse directly onto cerebellar nuclei

neurons, which communicate cerebellar information to regions such as the thalamus, red nucleus,

vestibular nuclei, and the inferior olive. Since defects in Purkinje cell spike firing can have

significant effects on their target neurons (Todorov et al., 2012; White et al., 2014) with resulting

problems in motor control and learning (Schonewille et al., 2010; White et al., 2014), we also

recorded from cerebellar nuclear neurons. Cerebellar nuclear neurons in mdx mice had around a

19% higher local variability in firing (CV2) compared to control mice. Again, this result is

reminiscent of the irregular cerebellar nuclei firing in ataxia (Hoebeek et al., 2008; White et al.,

2014) and dystonia (Fremont et al., 2014; White and Sillitoe, 2017). However, it is unclear

whether irregular firing of the cerebellar nuclei in one disease is exactly equivalent, at the

behavioral level, to irregular firing in other diseases. Part of the complication is that the

cerebellar nuclei have multiple targets, and it is unclear if the same target neurons are implicated

in different diseases. For example, it is postulated that the thalamic nuclei and connections to the

basal ganglia are central to dystonia (Chen et al., 2014; White and Sillitoe, 2017), but is this the

same pathway that also mediates motor defects in DMD? Perhaps, but DMD also involves non-

motor dysfunctions, which are likely served through a different set of circuits. One argument is

that the cerebellum might process all functions through a “universal cerebellar transform”

(Schmahmann et al., 2019). This theory postulates that regardless of whether the cerebellum is

modulating action or cognition, its role as a coordinator of several neural tasks is the same.

Certainly, there is strong clinical evidence for the cerebellum in emotion-based disorders

(Schmahmann, 2019), and experimentally its contribution to behaviors such as reward and social

behavior are emerging (Carta et al., 2019). Indeed, during non-motor function the cerebellum

must communicate with the cerebral cortex (Wagner et al., 2017; Wagner et al., 2019). Multiple

anatomical pathways linking the cerebellum to cortical sites likely sub-serve these different non-

motor functions (Bostan et al., 2013). The number of cerebral cortical sites that communicate

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

with the cerebellum is potentially widely distributed (Marek et al., 2018), perhaps a pre-requisite

to the cerebellum’s involvement in non-motor function in different and perhaps unexpected

cases, such as DMD. It stands to reason that powerful cerebellar computations are necessary to

drive such critical behaviors. One possibility is that the cerebellum promotes coherent activity

between cortical brain regions; an example could be an increase in hippocampal-prefrontal

cortex coherence upon Purkinje cell activation (McAfee et al., 2019). Interestingly, the

hippocampus (Hoogland et al., 2019; Krasowska et al., 2014; Miranda et al., 2015; Miranda et

al., 2016) and prefrontal cortex (Suzuki et al., 2017) exhibit abnormalities in human DMD and

mdx mice. It is therefore tantalizing to hypothesize that the decreased Purkinje cell simple spike

output and the more variable cerebellar nuclear output in mdx mice could contribute to the motor

or cognitive deficits reported in individuals with DMD.

Previous reports have noted changes in the distribution of GABAA receptors on Purkinje cells in

mdx mice (Grady et al., 2006). Though this molecular change could potentially contribute to the

altered firing we report in mdx Purkinje cells, it is currently not clear what effect it might have.

Specifically, because Purkinje cell dendrites have active rather than passive conduction

properties, the exact distribution of GABAA receptors is critical to predicting their effect on

Purkinje cell output. For instance, in biophysical simulations, distal dendritic inhibition has a

larger effect on firing rate than proximal inhibition (Solinas et al., 2006). Therefore, it is difficult

to predict how the changes in mdx GABAA receptor distribution would ultimately impact

Purkinje cell firing properties without a more detailed and quantitative description of the exact

composition of dendritic channels in the mdx mice, and across the different cerebellar lobules.

We also note that dystrophin is expressed in at least 7 isoforms (Muntoni et al., 2003), and while

the full-length Dp427 isoform is the one most strongly expressed in Purkinje cells (Górecki et

al., 1992), smaller isoforms like Dp71 and Dp140 could potentially compensate to some degree

for the mdx mutation and loss of Dp427. Nevertheless, our results point to an important role for

Dp427 in cerebellar function that cannot completely be compensated for by other isoforms.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

The loss of dystrophin expression in mdx mice does not prevent specific cell populations from

differentiating, eliminate certain classes of neurons, or prevent any of the main cerebellar cell

types from attaining their proper position within the tri-laminar cerebellar cortex (Fig. 1).

However, despite the correct location of cells and afferent fibers, cerebellar zonal topography is

altered. The cerebellum is organized into a series of sagittal zones that are defined by neuronal

birth date, lineage restriction, embryonic gene expression, afferent topography, neuronal spike

properties, and molecular marker expression (Apps et al., 2018; Miterko et al., 2019b). Zones are

organized around the Purkinje cells, which express the most striking of all zonal patterns.

Previous work demonstrated that dystrophin is not expressed at equal levels in all Purkinje cells,

but instead in a pattern of zones that fall within the fundamental cerebellar map (Blake et al.,

1999). In both the muscle and the brain, dystrophin binds to a complex of proteins including the

dystrobrevins and a coiled-coil protein called dysbindin (Benson et al., 2001). Dysbindin is

heavily expressed in mossy fiber terminals, where it also forms an array of zones that respect the

topography of Purkinje cells (Sillitoe et al., 2003). Loss of dystrophin in mdx mice alters the

terminal field distribution of dysbindin-expressing mossy fibers (Sillitoe et al., 2003). The

changes in Purkinje cell function and the accompanied defects in mossy fiber patterning in the

mdx model is reminiscent of ataxic mice that have a lack of Purkinje cell neurotransmission with

poorly defined mossy fiber zones (White et al., 2014). Moreover, there is no overt

neurodegeneration in either model. It therefore tempting to speculate that the behavioral deficits

in mdx mice are, at least in part, due to zonal miswiring. Based on the distribution of firing

properties, we likely recorded from Purkinje cells in zebrinII+ as well as zebrinII- zones (Fig. 3,

Fig. 4; Xiao et al., 2014; Zhou et al., 2014). If there are functional zonal defects in mdx mice, we

predict their involvement in a number of different behaviors. However, how motor and non-

motor information are simultaneously encoded in zones is unclear, although the convergence of

Purkinje cell zonal information within the cerebellar nuclei (Person and Raman, 2011) would

have an impact on how signals are altered in mdx mice (Fig. 5). Specifically, changes in complex

spikes would be predicted to alter cerebellar output (Tang et al., 2019), especially since the

climbing fiber projections also adhere strictly to the boundaries of the Purkinje cell zonal map

(Gravel et al., 1987; Sugihara and Quy, 2007), and contribute to behavior (Horn et al., 2010).

Within each zone, loss of dystrophin could, in theory, impact learning mechanisms via zone-

dependent changes in neurotransmission and plasticity (Kostadinov et al., 2019; Paukert et al.,

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

2010; Wadiche and Jahr, 2005). Similar to the synchronous activation of cell ensembles that

control individual muscles (Welsh et al., 1995), cerebellar firing properties and circuit patterning

could also instruct non-motor communication across higher order brain centers. Our extracellular

recordings included cells in lobules VI-VII of the vermis and CrusI and II of the hemispheres,

regions known to be involved in motor behaviors, with additional and growing evidence that

they contribute to various non-motor behaviors (Koziol et al., 2014; McAfee et al., 2019;

Shipman and Green, 2019). Based on the abnormalities we uncovered, we speculate that the

function of cerebellar dystrophin complexes could mediate such functions in vivo, during

behavior.

CONCLUSION

DMD is a debilitating disease that results in death. Boys are affected in the severe forms, which

start with muscle degeneration, although cardiac and respiratory problems often determine the

end-point of the disease. Unfortunately, during the course of disease, patients also have to deal

with neurological deficits that may be motor as well as non-motor in nature. A number of brain

regions such as the hippocampus and prefrontal cortex could mediate the cognitive defects in

humans and in animal models such as the mdx genetic model. In addition, the cerebellum, a

region involved in motor and non-motor functions, has been implicated in DMD. Behavioral

studies as well as in vitro electrophysiology experiments in mdx mice support a contribution of

the cerebellum to DMD. Here, we used mdx mice to show that Purkinje cells fire abnormally in

vivo, and their altered spiking properties are communicated downstream to cerebellar nuclear

neurons, which are also defective. We demonstrate that cerebellar output is more variable, a

circuit modification that could have signaling consequences similar to diseases such as ataxia,

tremor, and dystonia. We postulate that erroneous cerebellar output could mediate the motor and

non-motor abnormalities in DMD.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

MATERIALS AND METHODS

Animal maintenance. Mouse husbandry and experiments were performed under an approved

Institutional Animal Care and Use Committee (IACUC) protocol at Baylor College of Medicine.

Female C57BL/10ScSnJ control (Stock #000476; N = 22) and C57BL/10ScSn-Dmdmdx/J

homozygous mutant (Stock #001801; N = 22; mdx/mdx) mice were obtained from The Jackson

Laboratories (Bar Harbor, ME). The use of this specific control mouse line is based on known

difficulties in breeding the mutant strain and is supported by previous work demonstrating the

validity of their use (e.g. Rybalka et al., 2014; Xu et al., 2019; Yoon et al., 2019). We used only

one gender to avoid any potential sex differences in cerebellar function (Mercer et al., 2016).

Specifically, we chose to use female mice to try to dissociate the effect of the loss of dystrophin

as much as possible from potential compensatory changes in cerebellar output; changes in

muscle function could potentially induce compensatory changes in cerebellar activity (e.g. Xu-

Wilson et al., 2009; Zwergal et al., 2013), and females mutants have more modest muscular

deficits compared to male mutants when younger than 6 months old (Hakim and Duan, 2012;

Hourdé et al., 2013; Salimena et al., 2000). Of note, though, our previous work using female

homozygous (mdx/mdx) and male hemizygous (mdx/Y) mice did not reveal differences in

cerebellar functional anatomy or sensitivity to molecular patterning changes between the sexes

(Sillitoe et al., 2003). Regardless, in this work we analyzed cerebellar function in adult, 2 – 5-

month old female mice.

Surgery. For anesthetized recordings, the mice were anesthetized with 3% isoflurane and then

with a cocktail containing 75 mg/kg ketamine and 0.5 mg/kg dexmedetomidine. We then

transferred the mice from the anesthesia chamber to a stereotaxic platform (David Kopf

Instruments, Tujunga, CA, USA) that is integrated with an in vivo recording rig. Throughout the

experiment, mice were connected to a breathing tube and isoflurane concentration was

maintained at 0.15% - 0.25%. The head was fixed in place with metal ear bars. Fur in the back of

the head was removed using depilatory cream. An antero-posterior incision was made with a

scalpel blade to expose the skull. Depending on the age, the muscle was cut and reflected away if

the area for the craniotomy was covered. All craniotomies were performed from 0-1.5 mm to the

right of the midline with reference to bregma (Paxinos and Franklin, 2001), and above the region

that approximately corresponds to lobules VI-VII of the vermis or CrusI and II of the

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

hemispheres. A hole approximately 1 mm in diameter was drilled into the skull using a Dremel

handheld rotary drill (model 4000). Once the skull was drilled to translucence, the remaining

bone and cartilage were etched with an 18-gauge needle until a circular flap could be removed to

expose the brain. The craniotomy was performed carefully because even minimal tissue damage

causes brain and blood vessel pulsations, which inhibit stable single-unit recordings. Moisture

within the craniotomy was maintained by keeping the opening full with drops of 0.9% w/v saline

solution. During anesthesia, Purkinje cells were recorded between 0.2-2.4 mm (median = 1.1

mm) ventral to the surface of the brain.

For awake recordings, surgical procedures were similar to what we previously reported (White et

al., 2016b, Stay el al., 2019), with the following modifications: mice were anesthetized with 3%

isoflurane at induction, followed by 1-2% for maintenance. After the craniotomy, a custom 2 mm

circular plastic recording chamber was secured to the skull with dental acrylic, along with a

metal head plate for restraint. A small metal post was implanted over bregma for stereotaxic

reference during recordings. After surgery, the mice were transferred to a warmed box chamber

until they returned to sternal recumbency, at which point they were returned to their home cages

to continue recovering. Recordings began after three or more days post-surgery recovery. Mice

were head-fixed on a foam running wheel, where they were free to make limb or whisking

movements, though higher speeds of walking or running were inhibited by a high coefficient of

friction of wheel rotation. Purkinje cells were recorded from 5.5-7.7 mm (median = 6.8 mm)

posterior and 0.5-2.0 mm (median = 1.1 mm) lateral to bregma, at 0.3-2.9 mm (median = 1.7

mm) deep from the surface of the brain. Cerebellar nuclei were targeted between 1.8-4.0 mm

(median = 2.8 mm) ventral from the brain surface, and below surface coordinates of 5.8-7.6 mm

(median = 6.2 mm) posterior and 0.5-2.0 mm (median = 1.4 mm) lateral to bregma. The precise

stereotaxic coordinates relative to bregma were used to reconstruct the recording sites post hoc.

Electrophysiology–spike properties and data analysis. Single-unit recordings were attained with

2-5 MΩ Tungsten electrodes (Thomas Recording, Germany) that are controlled by a motorized

micromanipulator (MP-225, Sutter Instrument). The signals were band-pass filtered at 0.3-13

kHz, amplified with an ELC-03XS (NPI, Tamm, Germany) amplifier, and digitized into Spike2

(CED, Cambridge, UK). Well-isolated units were analyzed over 200-300 seconds in anesthetized

animals (median = 200 s), and 40-120 seconds in awake animals (median = 71 s). The

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

anesthetized mice were secured in a stereotaxic unit during the recordings, whereas the awake

animals were recorded during quiet wakefulness while on a foam wheel (White et al., 2016b).

Analysis of the raw traces was performed with Spike2, Excel and MATLAB. Purkinje cells were

identified by the presence of both simple spikes and complex spikes. Simple spikes are generated

intrinsically within Purkinje cells and are modulated by mossy fiber to granule cell afferent

inputs whereas complex spikes are a Purkinje cell-specific action potential that result exclusively

from the excitatory climbing fiber input. Complex spikes cause a subsequent pause of ~20 ms in

simple spike firing. Simple spikes and complex spikes were sorted independently. Cerebellar

nuclear neurons were identified by their significant and characteristic depth within the

cerebellum, as well as their general firing profile that typically sounds distinct from Purkinje

cells when isolated with the aid of an audio amplifier. Based on the stereotaxic coordinates that

were used for targeting the electrodes, we predict that most cerebellar nuclear neurons were

recorded from the fastigial and interposed nuclei, with some potentially isolated from deeper

within the vestibular nuclei. The spike trains for both cell types were analyzed for frequency (Hz

= spikes/s). To quantify the average variability in their firing pattern, the interspike interval (ISI)

coefficient of variance (CV = (standard deviation of ISIs)/(mean of ISIs)) was calculated. To

measure the variability in firing patterns within a short period of two interspike intervals, the

CV2 (CV2 = 2*|ISIn+1 – ISIn|/(ISIn+1 + ISIn)) was calculated (Holt et al., 1996). Throughout the

study, numerical results are reported as mean ± standard error of the mean (SEM). Pairwise

statistical comparisons of the different firing properties were performed with the nonparametric

Wilcoxon rank sum test (Table S1). Significance was set at α = 0.05 threshold. Sample size was

not determined using a priori power analysis, but was based on the statistical criteria for

significance in observations. Animals were not randomized into analysis groups, and no animals

or samples were excluded. Data is available upon request.

Statistics of electrophysiological recordings (Table S1). We examined several different predictor

variables and their relationship to several response variables. Specifically, we tested the null

hypotheses that the predictor variables [genotype, days post-surgery at recording, and recorded

depth (also indicates the putative lobule)] had no significant effects on the means of the response

variables [mean firing rate, mean CV, and mean CV2]. We tested these hypotheses through an

initial omnibus MANOVA test for each predictor variable. If the MANOVA result showed

likelihood of p < 0.05 that the means of each response variable were equal between the levels of

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

the predictor variable, we rejected the null hypothesis and proceeded with pairwise comparisons

to determine which response variable(s) differed. Since we did not know the true underlying

variance levels for each response variable, we used nonparametric Wilcoxon rank sum tests

rather than Student’s t-tests, to avoid assuming equal variance. The significance levels of all

statistical tests were corrected for multiple comparisons with the Benjamini-Hochberg

correction. A p-value less than the Benjamini-Hochberg critical value with false discovery rate

set to 0.2 was interpreted to reject the null hypothesis of equal means in a given response

variable between the predictor groups.

Tissue preparation and cutting. For perfusion-fixation, animals were deeply anesthetized with

avertin (2, 2, 2-Tribromoethanol), and then perfused through the heart with 0.1 M phosphate-

buffered saline (PBS; pH 7.2), followed by 4% paraformaldehyde (4% PFA) diluted in PBS.

After incubation in 4% PFA overnight, the tissue was placed into 70% ethanol before embedding

in wax for paraffin tissue processing (Sillitoe et al., 2008). Paraffin tissue sections were cut at 10

µm on a microtome and ribbons collected on positively-charged glass slides from a warm water

bath. Alternatively, for free-floating tissue processing the brains were post-fixed in 4% PFA for

24-48 hours after perfusion, cryoprotected stepwise in sucrose solutions (15% and 30% diluted in

PBS), embedded in Tissue-Tek O.C.T. Compound (Sakura Finetek, Torrence, CA, USA), and

then frozen at -70 degrees. The tissue was cut at 40 µm on a cryostat, and tissue collected into

24-well plates.

Immunohistochemistry. Immunohistochemistry was carried out as described previously (Reeber

and Sillitoe, 2011; Sillitoe et al., 2003; Sillitoe et al., 2010; White and Sillitoe, 2013). Briefly,

tissue sections were thoroughly washed, blocked with 10% normal goat serum (NGS; Sigma, St.

Louis MO, USA) for 1 hour at room temperature and then incubated in 0.1M PBS containing

10% NGS, 0.1% Tween-20 and primary antibodies for 16-18 hours at room temperature, shaking

gently. The tissue sections were then washed three times in PBS and incubated in goat anti-

mouse horseradish peroxidase (HRP)-conjugated secondary antibodies (1:200; DAKO,

Carpinteria, CA, USA) for 2 hours at room temperature, and again shaking gently. The cerebellar

tissue was subsequently rinsed and immunoreactivity analyzed using SG substrate (Vector

Laboratories, Burlingame, CA, USA) as a chromogen. After mounting the tissue onto glass

slides, sections were coverslipped using Cytoseal mounting media (Richard-Allen Scientific, San

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Diego, CA, USA). We tested the specificity of the secondary antibodies by processing the tissue

sections without primary antibodies. No signal was detected in such control experiments

indicating that the staining we observed was not due to non-specific signals from the HRP

antibodies (data not shown). Please refer to our previous work for additional tests of reliable

signals from the antibodies used in this study (Reeber and Sillitoe, 2011; White and Sillitoe,

2017; White et al., 2014; White et al., 2016b).

Antibodies. Anti-dystrophin antibody (1:20, Cat# NCL-DYS1) was purchased from Leica

Biosystems (Newcastle upon Tyne, UK) and was used to verify that full-length dystrophin was

eliminated in mdx mice. To account for the expression of the other dystrophin isoforms (i.e.,

Dp71, Dp116, Dp140, and Dp260) in control and mdx Purkinje cells, we used an anti-dystrophin

(MANDRA1) antibody (1:100, Cat # NB120-7164) from Novus Biologicals (Centennial, CO,

USA), targeted to the c-terminus. Mouse monoclonal anti-calbindin-D28K (calbindin; 1:10,000;

Cat# CD38), rabbit polyclonal anti-parvalbumin (1:1000; Cat# PV25) and rabbit polyclonal anti-

calretinin (1:500, Cat# CR7699/3H) were purchased from Swant (Marly, Switzerland). Calbindin

specifically labeled Purkinje cells, parvalbumin labeled Purkinje cells and GABAergic

interneurons, and calretinin labeled unipolar brush cells. We also used anti-CAR8 primary

antibodies (1:3,000; Santa Cruz Biotechnology, Santa Cruz, CA, USA) to label Purkinje cells

(Miterko et al., 2019a). To assess excitatory synapses, we used mouse monoclonal anti-vesicular

glutamate transporter 2 (VGLUT2; 1:500; Cat# MAB5504) purchased from Chemicon

(Millipore; Billerica, MA) for visualizing climbing and mossy fiber terminals (Gebre et al., 2012;

Hisano et al., 2002; Reeber and Sillitoe, 2011) and rabbit polyclonal anti-vesicular glutamate

transporter 1 (VGLUT1; 1:500; Cat# 135 302) purchased from Synaptic Systems (Goettingen;

Germany) for visualizing parallel fiber synapses and mossy fiber terminals (Gebre et al., 2012).

The granule cell layer was assessed by using the granule cell marker, rabbit anti-GABARα6,

which was purchased from Millipore (1:500; Cat# AB5610). Mouse monoclonal anti-NFH (also

called anti-SMI-32; 1:1500) was purchased from Covance (Princeton, NJ). Anti-SMI-32

recognizes the non-phosphorylated form of NFH (see manufacturer product datasheet for

details), which on tissue sections labels the soma, dendrites, and axons of adult Purkinje cells,

and also basket cell axons and pinceaux (Demilly et al., 2011). Rabbit anti-neurogranin (1:500)

was raised against full-length recombinant rat neurogranin protein (Chemicon, Temecula, CA;

Cat# AB5620). Neurogranin recognizes Purkinje cells in the perinatal cerebellum and Golgi cells

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

in the adult cerebellum (Larouche et al., 2006; Singec et al., 2003). Rabbit polyclonal anti-

cocaine- and amphetamine-related transcript peptide (CART 55-102; Cat # H-003-62) was used

at a concentration of 1:250 to detect climbing fibers (Reeber and Sillitoe, 2011) and was

purchased from Phoenix Pharmaceuticals, Inc. (Burlingame, CA). To fully visualize the fibers,

the CART signal was amplified using a biotinylated secondary antibody and the Vectastain Elite

ABC method from VectorLabs (Burlingame, CA; Reeber and Sillitoe, 2011).

Fluorescent Nissl histology. For dual staining of calbindin and NeuroTrace, 10 µm or 40 µm

tissue sections were immunolabeled with primary antibody as described above (calbindin;

1:10,000; Cat # CD38). We then added NeuroTrace fluorescent Nissl stain (Molecular Probes,

Eugene, Oregon), diluted to 1:1000, directly to the secondary antibody cocktail. Alexa Fluor®-

conjugated secondary antibodies (1:1500, Life Technologies, Cat # A31570) were used to

amplify and detect the calbindin signal. After 3 PBS rinses, we mounted the stained tissue

sections with FLUORO-GEL mounting media (Electron Microscopy Sciences, Hattfield, PA)

onto glass slides before imaging.

Imaging and data analysis. Photomicrographs of tissue sections were captured with a Zeiss

AxioCam MRc5 camera mounted on a Zeiss Axio Imager.M2 microscope. Images of tissue

sections were acquired with the Zeiss Apotome.2 system and analyzed using Zeiss ZEN software

(2012 edition). After imaging, the raw data was imported into Adobe Photoshop CS5 and

corrected for brightness and contrast levels. Schematics were drawn in Adobe Illustrator CS5.

Quantification of anatomical features. Cerebellar size, molecular layer thickness, Purkinje cell

number, and cerebellar nuclei areas and densities were quantified from 3 control and 3 mdx mice

using ImageJ software. Cerebellar size and Purkinje cell numbers were determined by

calculating, then averaging, the areas or the soma numbers of 3-8 sections of tissue, per animal,

respectively. All of the cerebellar tissue used in these calculations were previously stained with

calbindin and/or Nissl and were taken from within 200 µm from the midline. We used the tissue

area, inclusive of all ten vermal lobules, measured from sagittal sections, as a proxy for

examining cerebellar size. The number of Purkinje cells was calculated for the whole sagittal

cerebellum (lobules I-X), the anterior zone of the cerebellum (lobules I-V), the central zone of

the cerebellum (lobules VI-VIII), and the posterior/nodular zones of the cerebellum (lobules IX-

X). To complement our quantification of Purkinje cell number, molecular layer thickness and

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

cerebellar nuclei areas and densities were additionally measured. Molecular layer thickness was

measured in regions of cerebellar cortex flanking the fissure between lobules III and IV, on

sagittal sections that were co-stained with calbindin and Nissl. We chose to quantify these

specific regions because the cerebellar cortex in these lobules has substantial stretches without

curves, which makes quantification more systematic when comparing between mice. For each

mouse, the molecular layer thickness measurements were averaged from 4-8 sections separated

by ~200 μm around the midline. For additional details on the quantification of molecular layer

thickness please see Brown et al. (2019). Lastly, we quantified the areas and densities of the

fastigial and interposed cerebellar nuclei in 3 control and 3 mdx mice, each using 3 sagittal tissue

sections stained with calbindin (the Purkinje cell axons in the cerebellar nuclei provide an ideal

outline for assessing general nuclei anatomy) and Nissl. The fastigial nuclei measurements were

calculated from sagittal tissue sections that were 0.48 μm to 1.08 μm from the midline

whereas the interposed nuclei measurements were calculated from sagittal tissue sections that

were 1.08 μm to 1.92 μm from the midline. We did not quantify the area of the dentate nuclei

since our recordings in this study are predicted to be from the fastigial and interposed cerebellar

nuclei. Nuclear densities were determined in ImageJ software by first converting the TIFF

images containing the cerebellar nuclei to a 16-bit resolution, then adjusting the threshold so that

the Nissl staining of the nuclei was accurately detected by the “Analyze Particles” plug-in. The

subsequent nuclear counts were then divided by 50 μm to get the average number of cell nuclei

present in any given 50-μm area. For all of the anatomical features quantified, numerical results

are reported as the mean ± standard error of the mean (SEM). Sample size was determined based

on the statistical criteria for significance in observations. As previous reports have described

morphological features of cells in the cerebellum as being well approximated by normal

distributions (Ristanović et al., 2011), pairwise comparisons of the quantifications of these

anatomical features were performed with two-tailed Student’s t-tests.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

ACKNOWLEDGEMENTS

We thank all the members of the Sillitoe Lab for helpful discussions and critical reading of the

manuscript. We also thank the IDDRC Neuropathology Core for helping with the tissue staining

and histology experiments, and for providing advice and microcopy expertise during the project.

FUNDING

This work was supported by funds from Baylor College of Medicine (BCM) and Texas

Children’s Hospital to R.V.S.; a grant to R.V.S. from The Mrs. Clifford Elder White Graham

Endowed Research fund; The Hamill Foundation; a BCM IDDRC Project Development Award;

a BCM IDDRC grant [U54HD083092] from the Eunice Kennedy Shriver National Institute Of

Child Health & Human Development; by the National Center For Research Resources

[C06RR029965]; and by the NIH National Institute of Neurological Disorders and Stroke [R01

NS089664] and [R01 NS100874] (R.V.S.). T.L.S. was supported by Ruth L. Kirschstein

National Research Service Award [F31 NS095491] from the National Institute of Neurological

Disorders and Stroke. M.A. was supported by a postdoctoral award from the National Ataxia

Foundation (NAF).

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

REFERENCES

Amoasii, L., Hildyard, J. C. W., Li, H., Sanchez-Ortiz, E., Mireault, A., Caballero, D.,

Harron, R., Stathopoulou, T. R., Massey, C., Shelton, J. M., et al. (2018). Gene editing

restores dystrophin expression in a canine model of duchenne muscular dystrophy. Science.

362, 86–91.

Anderson, J. L., Head, S. I., Rae, C. and Morley, J. W. (2002). Brain function in Duchenne

muscular dystrophy. Brain 125, 4–13.

Anderson, J. L., Morley, J. W. and Head, S. I. (2010). Enhanced homosynaptic LTD in

cerebellar Purkinje cells of the dystrophic mdx mouse. Muscle and Nerve 41, 329–34.

Apps, R., Hawkes, R., Aoki, S., Bengtsson, F., Brown, A. M., Chen, G., Ebner, T. J., Isope,

P., Jörntell, H., Lackey, E. P., et al. (2018). Cerebellar Modules and Their Role as

Operational Cerebellar Processing Units: A Consensus paper. Cerebellum 17, 654–82.

Arancillo, M., White, J. J., Lin, T., Stay, T. L. and Sillitoe, R. V. (2015). In vivo analysis of

Purkinje cell firing properties during postnatal mouse development. J. Neurophysiol. 113,

578–591.

Barmack, N. H. and Yakhnitsa, V. (2008). Functions of interneurons in mouse cerebellum. J.

Neurosci. 28, 1140–52.

Benson, M. A., Newey, S. E., Martin-Rendon, E., Hawkes, R. and Blake, D. J. (2001).

Dysbindin, a novel coiled-coil-containing protein that interacts with the dystrobrevins in

muscle and brain. J. Biol. Chem. 276, 24232–41.

Birnkrant, D. J., Bushby, K., Bann, C. M., Alman, B. A., Apkon, S. D., Blackwell, A., Case,

L. E., Cripe, L., Hadjiyannakis, S., Olson, A. K., et al. (2018). Diagnosis and

management of Duchenne muscular dystrophy, part 2: respiratory, cardiac, bone health, and

orthopaedic management. Lancet. Neurol. 17, 347–61.

Blake, D. J., Hawkes, R., Benson, M. A. and Beesley, P. W. (1999). Different dystrophin-like

complexes are expressed in neurons and glia. J. Cell Biol. 147, 645–58.

Bostan, A. C., Dum, R. P. and Strick, P. L. (2013). Cerebellar networks with the cerebral

cortex and basal ganglia. Trends Cogn. Sci. 17, 241–54.

Brown, A. M., Arancillo, M., Lin, T., Catt, D. R., Zhou, J., Lackey, E. P., Stay, T. L., Zuo,

Z., White, J. J. and Sillitoe, R. V (2019). Molecular layer interneurons shape the spike

activity of cerebellar Purkinje cells. Sci. Rep. 9, 1742.

Buckner, R. L. (2013). The cerebellum and cognitive function: 25 years of insight from

anatomy and neuroimaging. Neuron 80, 807–15.

Burghes, A., Logan, C., Hu, X., Belfall, B., Worton, R. and Ray, P. (1987). A cDNA clone

from the Duchenne/Becker muscular dystrophy gene. Nature 328, 434–7.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Calderon, D. P., Fremont, R., Kraenzlin, F. and Khodakhah, K. (2011). The neural

substrates of rapid-onset Dystonia-Parkinsonism. Nat. Neurosci. 14, 357–365.

Carta, I., Chen, C. H., Schott, A. L., Dorizan, S. and Khodakhah, K. (2019). Cerebellar

modulation of the reward circuitry and social behavior. Science. 363, eaav0581.

Cendelin, J. (2014). From mice to men: lessons from mutant ataxic mice. Cerebellum & Ataxias

1, 4.

Chaussenot, R., Amar, M., Fossier, P. and Vaillend, C. (2019). Dp71-dystrophin deficiency

alters prefrontal cortex excitation-inhibition balance and executive functions. Mol.

Neurobiol. 56, 2670–84.

Chen, C. H., Fremont, R., Arteaga-Bracho, E. E. and Khodakhah, K. (2014). Short latency

cerebellar modulation of the basal ganglia. Nat. Neurosci. 17, 1767–75.

Crone, M. and Mah, J. K. (2018). Current and emerging treatment strategies for Duchenne

muscular dystrophy. Neuropsychiatr. Dis. Treat. 20, 31.

Cyrulnik, S. and Hinton, V. (2008). Duchenne muscular dystrophy: a cerebellar disorder?

Neurosci Biobehav Rev 32, 486–96.

D’Angelo, E. and Casali, S. (2013). Seeking a unified framework for cerebellar function and

dysfunction: from circuit operations to cognition. Front. Neural Circuits 6, 116.

Davie, J. T., Clark, B. A. and Hausser, M. (2008). The origin of the complex spike in

cerebellar Purkinje cells. J. Neurosci. 28, 7599–609.

De Zeeuw, C. I., Hoebeek, F. E., Bosman, L. W. J., Schonewille, M., Witter, L. and

Koekkoek, S. K. (2011). Spatiotemporal firing patterns in the cerebellum. Nat. Rev.

Neurosci. 12, 327-44.

Demilly, A., Reeber, S. L., Gebre, S. A. and Sillitoe, R. V. (2011). Neurofilament heavy chain

expression reveals a unique parasagittal stripe topography in the mouse cerebellum.

Cerebellum 10, 409–21.

Diño, M. R., Willard, F. H. and Mugnaini, E. (1999). Distribution of unipolar brush cells and

other calretinin immunoreactive components in the mammalian cerebellar cortex. J.

Neurocytol. 28, 99–123.

Falzarano, M. S., Scotton, C., Passarelli, C. and Ferlini, A. (2015). Duchenne muscular

dystrophy: From diagnosis to therapy. Molecules 20, 18168–84.

Fremont, R., Calderon, D. P., Maleki, S. and Khodakhah, K. (2014). Abnormal high-

frequency burst firing of cerebellar neurons in rapid-onset dystonia-Parkinsonism. J.

Neurosci. 34, 11723–32.

Fremont, R., Tewari, A. and Khodakhah, K. (2015). Aberrant Purkinje cell activity is the

cause of dystonia in a shRNA-based mouse model of Rapid Onset Dystonia-Parkinsonism.

Neurobiol. Dis. 82, 200–212.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Fremont, R., Tewari, A., Angueyra, C. and Khodakhah, K. (2017). A role for cerebellum in

the hereditary dystonia DYT1. Elife 6, e22775.

Gao, Z., Todorov, B., Barrett, C. F., van Dorp, S., Ferrari, M. D., van den Maagdenberg, A.

M. J. M., De Zeeuw, C. I. and Hoebeek, F. E. (2012). Cerebellar ataxia by enhanced

CaV2.1 currents is alleviated by Ca2+-dependent K+-channel activators in Cacna1aS218L

mutant mice. J. Neurosci. 32, 15533–46.

Gebre, S. A., Reeber, S. L. and Sillitoe, R. V. (2012). Parasagittal compartmentation of

cerebellar mossy fibers as revealed by the patterned expression of vesicular glutamate

transporters VGLUT1 and VGLUT2. Brain Struct. Funct. 217, 165-80.

Górecki, D. C., Monaco, A. P., Derry, J. M., Walker, A. P., Barnard, E. A. and Barnard, P.

J. (1992). Expression of four alternative dystrophin transcripts in brain regions regulated by

different promoters. Mol. Genet. 1, 505–10.

Grady, R. M., Wozniak, D., Ohlemiller, K. and Sanes, J. (2006). Cerebellar synaptic defects

and abnormal motor behavior in mice lacking alpha- and beta-dystrobrevin. J. Neurosci. 26,

2841–51.

Gravel, C., Eisenman, L. M., Sasseville, R. and Hawkes, R. (1987). Parasagittal organization

of the rat cerebellar cortex: Direct correlation between antigenic purkinje cell bands

revealed by mabQ113 and the organization of the olivocerebellar projection. J. Comp.

Neurol. 265, 294–310.

Guiraud, S. and Davies, K. (2019). Regenerative biomarkers for Duchenne muscular

dystrophy. Neural Regen. Res. 14, 1317–20.

Guiraud, S., Aartsma-Rus, A., Vieira, N. M., Davies, K. E., van Ommen, G.-J. B. and

Kunkel, L. M. (2015). The pathogenesis and therapy of muscular dystrophies. Annu. Rev.

Genomics Hum. Genet. 16, 281–308.

Hakim, C. H. and Duan, D. (2012). Gender differences in contractile and passive properties of

mdx extensor digitorum longus muscle. Muscle Nerve 45, 250–6.

Hansen, S. T., Meera, P., Otis, T. S. and Pulst, S. M. (2013). Changes in Purkinje cell firing

and gene expression precede behavioral pathology in a mouse model of SCA2. Hum. Mol.

Genet. 22, 271–83.

Hara, K. and Harris, R. A. (2002). The anesthetic mechanism of urethane: The effects on

neurotransmitter-gated ion channels. Anesth. Analg. 94, 313–18.

Heiney, S. A., Kim, J., Augustine, G. J. and Medina, J. F. (2014). Precise control of

movement kinematics by optogenetic inhibition of Purkinje cell activity. J. Neurosci. 34,

2321–30.

Hisano, S., Sawada, K., Kawano, M., Kanemoto, M., Xiong, G., Mogi, K., Sakata-Haga, H.,

Takeda, J., Fukui, Y. and Nogami, H. (2002). Expression of inorganic

phosphate/vesicular glutamate transporters (BNPI/VGLUT1 and DNPI/VGLUT2) in the

cerebellum and precerebellar nuclei of the rat. Brain Res Mol Brain Res 107, 23–31.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Hoebeek, F. E., Khosrovani, S., Witter, L. and De Zeeuw, C. I. (2008). Purkinje cell input to

cerebellar nuclei in tottering: Ultrastructure and physiology. Cerebellum 7, 547–58.

Hoffman, E. P., Brown, R. H. and Kunkel, L. M. (1987). Dystrophin: The protein product of

the duchenne muscular dystrophy locus. Cell 51, 919–28.

Holt, G. R., Softky, W. R., Koch, C. and Douglas, R. J. (1996). Comparison of discharge

variability in vitro and in vivo in cat visual cortex neurons. J. Neurophysiol. 75, 1806–1814.

Hoogland, G., Hendriksen, R. G. F., Slegers, R. J., Hendriks, M. P. H., Schijns, O. E. M. G.,

Aalbers, M. W. and Vles, J. S. H. (2019). The expression of the distal dystrophin isoforms

Dp140 and Dp71 in the human epileptic hippocampus in relation to cognitive functioning.

Hippocampus 29, 102–10.

Horn, K. M., Pong, M. and Gibson, A. R. (2010). Functional relations of cerebellar modules of

the cat. J. Neurosci. 30, 9411–23.

Hourdé, C., Joanne, P., Noirez, P., Agbulut, O., Butler-Browne, G. and Ferry, A. (2013).

Protective effect of female gender-related factors on muscle force-generating capacity and

fragility in the dystrophic mdx mouse. Muscle Nerve 48, 68–75.

Imbornoni, L., Price, E. T., Andrews, J., Meaney, F. J., Ciafaloni, E. and Cunniff, C. (2014). Diagnostic and clinical characteristics of early-manifesting females with Duchenne

or Becker muscular dystrophy. Am. J. Med. Genet. Part A 164, 2769–74.

Inoue, T., Lin, X., Kohlmeier, K. A., Orr, H. T., Zoghbi, H. Y. and Ross, W. N. (2001).

Calcium dynamics and electrophysiological properties of cerebellar Purkinje cells in SCA1

transgenic mice. J. Neurophysiol. 85, 1750–60.

Kostadinov, D., Beau, M., Pozo, M. B. and Häusser, M. (2019). Predictive and reactive

reward signals conveyed by climbing fiber inputs to cerebellar Purkinje cells. Nat.

Neurosci.

Koziol, L. F., Budding, D., Andreasen, N., D’Arrigo, S., Bulgheroni, S., Imamizu, H., Ito,

M., Manto, M., Marvel, C., Parker, K., et al. (2014). Consensus paper: The cerebellum’s

role in movement and cognition. Cerebellum 13, 151–77.

Krasowska, E., Zabłocki, K., Górecki, D. C. and Swinny, J. D. (2014). Aberrant location of

inhibitory synaptic marker proteins in the hippocampus of dystrophin-deficient mice:

Implications for cognitive impairment in Duchenne muscular dystrophy. PLoS One 9,

e108364.

Kueh, S. L. L., Dempster, J., Head, S. I. and Morley, J. W. (2011). Reduced postsynaptic

GABAA receptor number and enhanced gaboxadol induced change in holding currents in

Purkinje cells of the dystrophin-deficient mdx mouse. Neurobiol. Dis. 43, 558–64.

Kuo, S.-H., Louis, E., Faust, P., Handforth, A., Chang, S.-Y., Avlar, B., Lang, E., Pan, M.-

K., Miterko, L., Brown, A., et al. (2019). Current opinions and consensus for studying

tremor in animal models. Cerebellum.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Lalonde, R. and Strazielle, C. (2007). Brain regions and genes affecting postural control. Prog

Neurobiol 81, 45–60.

Landis, D. and Landis, S. (1978). Several mutations in mice that affect the cerebellum. Adv

Neurol 21, 85–105.

Larouche, M., Che, P. M. and Hawkes, R. (2006). Neurogranin expression identifies a novel

array of Purkinje cell parasagittal stripes during mouse cerebellar development. J. Comp.

Neurol. 494, 215–27.

Lidov, H. G. W., Byers, T. J., Watkins, S. C. and Kunkel, L. M. (1990). Localization of

dystrophin to postsynaptic regions of central nervous system cortical neurons. Nature 348,

725–8.

Lidov, H. G. W., Byers, T. J. and Kunkel, L. M. (1993). The distribution of dystrophin in the

murine central nervous system: An immunocytochemical study. Neuroscience 54, 167–87.

Long, C., Amoasii, L., Mireault, A. A., McAnally, J. R., Li, H., Sanchez-Ortiz, E.,

Bhattacharyya, S., Shelton, J. M., Bassel-Duby, R. and Olson, E. N. (2016). Postnatal

genome editing partially restores dystrophin expression in a mouse model of muscular

dystrophy. Science (80-. ). 351, 400–403.

Luna-Cancalon, K., Sikora, K. M., Pappas, S. S., Singh, V., Wulff, H., Paulson, H. L.,

Burmeister, M. and Shakkottai, V. G. (2014). Alterations in cerebellar physiology are

associated with a stiff-legged gait in Atcayji-hes mice. Neurobiol. Dis. 67, 140–148.

Marek, S., Siegel, J. S., Gordon, E. M., Raut, R. V., Gratton, C., Newbold, D. J., Ortega,

M., Laumann, T. O., Adeyemo, B., Miller, D. B., et al. (2018). Spatial and temporal

organization of the individual human cerebellum. Neuron 100, 977–93.e7.

McAfee, S. S., Liu, Y., Sillitoe, R. V. and Heck, D. H. (2019). Cerebellar lobulus simplex and

crus I differentially represent phase and phase difference of prefrontal cortical and

hippocampal oscillations. Cell Rep. 27, 2328–34.

Mercer, A. A., Palarz, K. J., Tabatadze, N., Woolley, C. S. and Raman, I. M. (2016). Sex

differences in cerebellar synaptic transmission and sex-specific responses to autism-linked

Gabrb3 mutations in mice. Elife 5, pii:e07596.

Mercier, S., Toutain, A., Toussaint, A., Raynaud, M., De Barace, C., Marcorelles, P.,

Pasquier, L., Blayau, M., Espil, C., Parent, P., et al. (2013). Genetic and clinical

specificity of 26 symptomatic carriers for dystrophinopathies at pediatric age. Eur. J. Hum.

Genet. 21, 855.

Min, Y. L., Li, H., Rodriguez-Caycedo, C., Mireault, A. A., Huang, J., Shelton, J. M.,

McAnally, J. R., Amoasii, L., Mammen, P. P. A., Bassel-Duby, R., et al. (2019).

CRISPR-Cas9 corrects Duchenne muscular dystrophy exon 44 deletion mutations in mice

and human cells. Sci. Adv. 5, eaav4324.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Miranda, R., Nagapin, F., Bozon, B., Laroche, S., Aubin, T. and Vaillend, C. (2015). Altered

social behavior and ultrasonic communication in the dystrophin-deficient mdx mouse model

of Duchenne muscular dystrophy. Mol. Autism 6, 60.

Miranda, R., Laroche, S. and Vaillend, C. (2016). Reduced neuronal density in the CA1

anterodorsal hippocampus of the mdx mouse. Neuromuscul. Disord. 26, 775–81.

Mirski, K. T. and Crawford, T. O. (2014). Motor and cognitive delay in Duchenne muscular

dystrophy: Implication for early diagnosis. J. Pediatr. 165, 1008–10.

Miterko, L. N., White, J. J., Lin, T., Brown, A. M., O’Donovan, K. J. and Sillitoe, R. V. (2019a). Persistent motor dysfunction despite homeostatic rescue of cerebellar

morphogenesis in the Car8 waddles mutant mouse. Neural Dev. 14, 6.

Miterko, L. N., Sillitoe, R. V. and Hawkes, R. (2019b). Zones and stripes: Development of

cerebellar topography. In Handbook of the Cerebellum and Cerebellar Disorders (ed.

Manto, M, Gruol D, Schmahmann J, Koibuchi N, S. R.), pp. 1–23. Cham: Springer.

Monaco, A. P., Neve, R. L., Colletti-Feener, C., Bertelson, C. J., Kurnit, D. M. and Kunkel,

L. M. (1986). Isolation of candidate cDNAs for portions of the Duchenne muscular

dystrophy gene. Nature.

Moser, H. and Emery, A. E. H. (1974). The manifesting carrier in Duchenne muscular

dystrophy. Clin. Genet. 5, 271–84.

Muntoni, F., Torelli, S. and Ferlini, A. (2003). Dystrophin and mutations: One gene, several

proteins, multiple phenotypes. Lancet Neurol. 2, 731–40.

Norman, A. and Harper, P. (1989). A survey of manifesting carriers of Duchenne and Becker

muscular dystrophy in Wales. Clin. Genet. 1, 466–8.

Papa, R., Madia, F., Bartolomeo, D., Trucco, F., Pedemonte, M., Traverso, M., Broda, P.,

Bruno, C., Zara, F., Minetti, C., et al. (2016). Genetic and early clinical manifestations of

females heterozygous for Duchenne/Becker muscular dystrophy. Pediatr. Neurol. 55, 58–

63.

Paukert, M., Huang, Y. H., Tanaka, K., Rothstein, J. D. and Bergles, D. E. (2010). Zones of

enhanced glutamate release from climbing fibers in the mammalian cerebellum. J. Neurosci.

30, 7290–9.

Paxinos, G. and Franklin, K. (2001). The mouse brain in stereotaxic coordinates. Elsevier

Academic Press.

Pereira da Silva, J. D., Campos, D. V., Nogueira-Bechara, F. M., Stilhano, R. S., Han, S.

W., Sinigaglia-Coimbra, R., Lima-Landman, M. T. R., Lapa, A. J. and Souccar, C. (2018). Altered release and uptake of gamma-aminobutyric acid in the cerebellum of

dystrophin-deficient mice. Neurochem. Int. 118, 105–114.

Person, A. L. and Raman, I. M. (2011). Purkinje neuron synchrony elicits time-locked spiking

in the cerebellar nuclei. Nature 481, 502–5.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Pilgram, G. S. K., Potikanond, S., Baines, R. A., Fradkin, L. G. and Noordermeer, J. N. (2010). The roles of the dystrophin-associated glycoprotein complex at the synapse. Mol.

Neurobiol. 41, 1–21.

Rae, M. G. and O’Malley, D. (2016). Cognitive dysfunction in Duchenne muscular dystrophy:

a possible role for neuromodulatory immune molecules. J. Neurophysiol. 116, 1304–15.

Reeber, S. L. and Sillitoe, R. V. (2011). Patterned expression of a cocaine- and amphetamine-

regulated transcript peptide reveals complex circuit topography in the rodent cerebellar

cortex. J. Comp. Neurol. 519, 1781–1796.

Reeber, S. L., Otis, T. S. and Sillitoe, R. V. (2013). New roles for the cerebellum in health and

disease. Front. Syst. Neurosci. 7, 83.

Ristanović, D., Milošević, N. T. and Marić, D. L. (2011). On the classification of normally

distributed neurons: An application to human dentate nucleus. Biol. Cybern. 104, 175083.

Ruigrok, T. J. H., Hensbroek, R. A. and Simpson, J. I. (2011). Spontaneous activity

signatures of morphologically identified interneurons in the vestibulocerebellum. J.

Neurosci. 31, 712–24.

Rybalka, E., Timpani, C. A., Cooke, M. B., Williams, A. D. and Hayes, A. (2014). Defects in

mitochondrial ATP synthesis in dystrophin-deficient mdx skeletal muscles may be caused

by complex I insufficiency. PLoS One 9, e115763.

Ryder-Cook, A. S., Sicinski, P., Thomas, K., Davies, K. E., Worton, R. G., Barnard, E. A.,

Darlison, M. G. and Barnard, P. J. (1988). Localization of the mdx mutation within the

mouse dystrophin gene. EMBO J. 7, 3017–21.

Salimena, M. C., Lagrota-Candido, J. and Quírico-Santos, T. (2000). Gender dimorphism

influences extracellular matrix expression and regeneration of muscular tissue in mdx

dystrophic mice. Histochem. Cell Biol. 122, 435–44.

Schmahmann, J. D. (2019). The cerebellum and cognition. Neurosci. Lett. 688, 62–75.

Schmahmann, J. D., Guell, X., Stoodley, C. J. and Halko, M. A. (2019). The theory and

neuroscience of cerebellar cognition. Annu. Rev. Neurosci.

Schmolesky, M., Weber, J., De Zeeuw, C. and Hansel, C. (2002). The making of a complex

spike: ionic composition and plasticity. Ann N Y Acad Sci 978, 359–90.

Schonewille, M., Belmeguenai, A., Koekkoek, S. K., Houtman, S. H., Boele, H. J., van

Beugen, B. J., Gao, Z., Badura, A., Ohtsuki, G., Amerika, W. E., et al. (2010). Purkinje

cell-specific knockout of the protein phosphatase PP2B impairs potentiation and cerebellar

motor learning. Neuron 67, 618–28.

Sesay, A. K., Errington, M. L., Levita, L. and Bliss, T. V. (1996). Spatial learning and

hippocampal long-term potentiation are not impaired in mdx mice. Neurosci Lett 211, 207–

10.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Shakkottai, V. G., Batla, A., Bhatia, K., Dauer, W. T., Dresel, C., Niethammer, M.,

Eidelberg, D., Raike, R. S., Smith, Y., Jinnah, H. A., et al. (2017). Current opinions and

areas of consensus on the role of the cerebellum in dystonia. Cerebellum 16, 577–94.

Shipman, M. and Green, J. (2019). Cerebellum and cognition: Does the rodent cerebellum

participate in cognitive functions? Neurobiol Learn Mem S1074-7427, 30027–9.

Sicinski, P., Geng, Y., Ryder-Cook, A. S., Barnard, E. A., Darlison, M. G. and Barnard, P.

J. (1989). The molecular basis of muscular dystrophy in the mdx mouse: A point mutation.

Science. 244, 1578–80.

Sillitoe, R. V., Benson, M. A., Blake, D. J. and Hawkes, R. (2003). Abnormal dysbindin

expression in cerebellar mossy fiber synapses in the mdx mouse model of Duchenne

muscular dystrophy. J. Neurosci. 23, 6576–85.

Sillitoe, R. V, Stephen, D., Lao, Z. and Joyner, A. L. (2008). Engrailed homeobox genes

determine the organization of Purkinje cell sagittal stripe gene expression in the adult

cerebellum. J. Neurosci.

Sillitoe, R. V., Vogel, M. W. and Joyner, A. L. (2010). Engrailed homeobox genes regulate

establishment of the cerebellar afferent circuit map. J. Neurosci. 30, 10015–10024.

Singec, I., Knoth, R., Ditter, M., Frotscher, M. and Volk, B. (2003). Neurogranin expression

by cerebellar neurons in rodents and non-human primates. J. Comp. Neurol. 459, 278–89.

Snow, W. M., Anderson, J. E. and Fry, M. (2014). Regional and genotypic differences in

intrinsic electrophysiological properties of cerebellar Purkinje neurons from wild-type and

dystrophin-deficient mdx mice. Neurobiol. Learn. Mem. 107, 19–31.

Solinas, S. M., Maex, R. and De Schutter, E. (2006). Dendritic amplification of inhibitory

postsynaptic potentials in a model Purkinje cell. Eur. J. Neurosci. 23, 1207–18.

Stay, T., Laurens, J., Sillitoe, R. V. and Angelaki, D. E. (2019). Genetically eliminating

Purkinje neuron GABAergic neurotransmission increases their response gain to vestibular

motion. Proc Natl Acad Sci USA 116, 3245–50.

Stoodley, C. (2012). The Cerebellum and cognition: Evidence from functional imaging studies.

Cerebellum 11, 352–365.

Sugihara, I. and Quy, P. N. (2007). Identification of aldolase C compartments in the mouse

cerebellar cortex by olivocerebellar labeling. J. Comp. Neurol. 500, 1076–92.

Suzuki, Y., Higuchi, S., Aida, I., Nakajima, T. and Nakada, T. (2017). Abnormal distribution

of GABAAreceptors in brain of duchenne muscular dystrophy patients. Muscle and Nerve

55, 591–95.

Tang, T., Blenkinsop, T. A. and Lang, E. J. (2019). Complex spike synchrony dependent

modulation of rat deep cerebellar nuclear activity. Elife 8, pii: e40101.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Taylor, P. J., Maroulis, S., Mullan, G. L., Pedersen, R. L., Baumli, A., Elakis, G., Piras, S.,

Walsh, C., Prósper-Gutiérrez, B., De La Puente-Alonso, F., et al. (2007). Measurement

of the clinical utility of a combined mutation detection protocol in carriers of Duchenne and

Becker muscular dystrophy. J. Med. Genet. 44, 368–72.

Thach, W. T. (2014). Does the cerebellum initiate movement? Cerebellum 13, 139–50.

Todorov, B., Kros, L., Shyti, R., Plak, P., Haasdijk, E. D., Raike, R. S., Frants, R. R., Hess,

E. J., Hoebeek, F. E., De Zeeuw, C. I., et al. (2012). Purkinje cell-specific ablation of

CaV2.1 Channels is sufficient to cause cerebellar ataxia in mice. Cerebellum 11, 246–58.

Tsai, P. T., Hull, C., Chu, Y., Greene-Colozzi, E., Sadowski, A. R., Leech, J. M., Steinberg,

J., Crawley, J. N., Regehr, W. G. and Sahin, M. (2012). Autistic-like behaviour and

cerebellar dysfunction in Purkinje cell Tsc1 mutant mice. Nature 488, 647–51.

Vaillend, C., Billard, J. M. and Laroche, S. (2004). Impaired long-term spatial and recognition

memory and enhanced CA1 hippocampal LTP in the dystrophin-deficient Dmdmdx mouse.

Neurobiol. Dis. 17, 10–20.

Wadiche, J. I. and Jahr, C. E. (2005). Patterned expression of Purkinje cell glutamate

transporters controls synaptic plasticity. Nat. Neurosci. 8, 1329–34.

Wagner, M. J., Kim, T. H., Savall, J., Schnitzer, M. J. and Luo, L. (2017). Cerebellar granule

cells encode the expectation of reward. Nature 544, 96–100.

Wagner, M. J., Kim, T. H., Kadmon, J., Nguyen, N. D., Ganguli, S., Schnitzer, M. J. and

Luo, L. (2019). Shared cortex-cerebellum dynamics in the execution and learning of a

motor task. Cell 177, 669–82.e24.

Waite, A., Tinsley, C. L., Locke, M. and Blake, D. J. (2009). The neurobiology of the

dystrophin-associated glycoprotein complex. Ann. Med. 41, 344–59.

Welsh, J. P., Lang, E. J., Suglhara, I. and Llinás, R. (1995). Dynamic organization of motor

control within the olivocerebellar system. Nature 374, 453–7.

White, J. J. and Sillitoe, R. V. (2013). Postnatal development of cerebellar zones revealed by

neurofilament heavy chain protein expression. Front. Neuroanat. 7, 9.

White, J. J. and Sillitoe, R. V. (2017). Genetic silencing of olivocerebellar synapses causes

dystonia-like behaviour in mice. Nat. Commun. 8, 1–16.

White, J. J., Arancillo, M., Stay, T. L., George-Jones, N. A., Levy, S. L., Heck, D. H. and

Sillitoe, R. V. (2014). Cerebellar zonal patterning relies on Purkinje cell neurotransmission.

J. Neurosci. 34, 8231–8245.

White, J. J., Arancillo, M., King, A., Lin, T., Miterko, L. N., Gebre, S. A. and Sillitoe, R. V. (2016a). Pathogenesis of severe ataxia and tremor without the typical signs of

neurodegeneration. Neurobiol. Dis. 86, 86–98.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

White, J. J., Lin, T., Brown, A. M., Arancillo, M., Lackey, E. P., Stay, T. L. and Sillitoe, R.

V. (2016b). An optimized surgical approach for obtaining stable extracellular single-unit

recordings from the cerebellum of head-fixed behaving mice. J. Neurosci. Methods 262,

21–31.

Xiao, J., Cerminara, N. L., Kotsurovskyy, Y., Aoki, H., Burroughs, A., Wise, A. K., Luo,

Y., Marshall, S. P., Sugihara, I., Apps, R., et al. (2014). Systematic regional variations in

Purkinje cell spiking patterns. PLoS One 9, e105633.

Xu-Wilson, M., Chen-Harris, H., Zee, D. S. and Shadmehr, R. (2009). Cerebellar

contributions to adaptive control of saccades in humans. J. Neurosci. 29, 12930–39.

Xu, L., Lau, Y. S., Gao, Y., Li, H. and Han, R. (2019). Life-long AAV-mediated CRISPR

genome editing in dystrophic heart improves cardiomyography without causing serious

lesions in mdx mice. Mol. Ther. 27, 1407–14.

Yoon, S. H., Grynpas, M. D. and Mitchell, J. (2019). Growth hormone increases bone

toughness and decreases muscle inflammation in glucocorticoud-treated mdx mice, model

of Duchenne muscular dystrophy. J. Bone Miner. Res. 34, 1473–86.

Zhou, H., Lin, Z., Voges, K., Ju, C., Gao, Z., Bosman, L. W. J., Ruigrok, T. J., Hoebeek, F.

E., De Zeeuw, C. I. and Schonewille, M. (2014). Cerebellar modules operate at different

frequencies. Elife 3, e02536.

Zwergal, A., La Fougère, C., Lorenzl, S., Rominger, A., Xiong, G., Deutschenbaur, L.,

Schöberl, F., Linn, J., Dieterich, M., Brandt, T., et al. (2013). Functional disturbance of

the locomotor network in progressive supranuclear palsy. Neurology 80, 634–41.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Figures

Fig. 1. The molecular expression profile of cerebellar neurons is similar in mdx and control

mice. A. Control mice express dystrophin in Purkinje cells, while mdx mice do not. B-J. Control

and mdx mice have similar expression patterns for markers of Purkinje cells (B), inhibitory

neurons (C-E), and excitatory cells and inputs (F-J). B. CAR8 labels Purkinje cell somata and

dendrites (axons are also labeled with CAR8 but are not seen in this tissue orientation). C.

Parvalbumin (PV) labels inhibitory Purkinje cells, molecular layer interneurons and granular

layer interneurons. D. Neurofilament heavy (NFH) labels Purkinje cells and basket cell axons. E.

Neurogranin labels Golgi cells in the adult mouse. F. Gamma-amino-butyric-acid receptor alpha

6 (GABAaRα6) labels granule cells and their parallel fiber axons. G. Calretinin labels a subset of

unipolar brush cells. H. Vesicular glutamate transporter 1 (VGLUT1) labels parallel fiber and

mossy fiber terminals. I. Vesicular glutamate transporter 2 (VGLUT2) labels climbing fiber and

mossy fiber terminals. J. Cocaine- and amphetamine-related transcript peptide (CART) labels

climbing fiber axons and terminals mainly in lobules IX and X. Scale bar, 200 µm. Molecular

layer (ml). Purkinje cell layer (pcl). Granular layer (gl). N = 3 mice of each genotype.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Fig. 2. Gross cerebellar morphology does not differ between mdx mice and controls. A-B.

Representative mid-sagittal sections showing Purkinje cells stained with calbindin (magenta) and

granule cells stained with fluorescent Nissl (green). C. No significant difference was found

between genotypes for cerebellar size (Cerebellar size: control = 30.1 x 106 ± 2.8 x 106 μm2, mdx

= 29.2 x 106 ± 1.9 x 106 μm2, , two-tailed Student’s t-test, N = 3 mice of each genotype, n = 3-8

sections per animal, t(4) = 0.280, p = 0.79). D-E. Higher-power images from lobules III-IV

illustrate how molecular layer thickness was measured perpendicular to the Purkinje cell

monolayer adjacent to the primary fissure. F. No significant difference was found between

genotypes for molecular layer thickness (control mean = 152.3 ± 3.7 μm, mdx mean = 155.7 ±

4.0 μm, two-tailed Student’s t-test, N = 3 mice of each genotype, n = 4-8 sections per animal,

t(4) = -0.623, p = 0.57). Scale bar (A-B), 500 µm; (C-D), 50 µm. Molecular layer (ml). Purkinje

cell layer (pcl).

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Fig. 3. Extracellular spontaneous firing properties of Purkinje cells in ketamine-

dexmedetomidine anesthetized mdx and control mice. A. Schematic showing the recording

approach. B. Schematic illustrating the electrode placement for targeting the Purkinje cells. C.

Example raw voltage trace from a control Purkinje cell, with complex spikes noted with green

asterisks. D. As in C, for mdx mice. E. Average simple spike waveform for the cell shown in C.

F. Average complex spike waveform for the cell in C. G-H. Simple spike and complex spike

waveforms for the mdx cell shown in D. I. Mean simple spike firing rate (y-axis) was not

significantly lower in mdx mice (red) compared to the control mice (blue) when corrected for

multiple comparisons. No statistically significant difference was found in mean CV (x-axis),

though there was a trend toward lower variability in the mdx mice. J. No significant differences

were found for either mean firing rate or mean CV for complex spikes. Circles are individual

data points, crosses represent mean values ± SEM. n = 48 control cells, n = 46 mdx cells, N = 12

mice of each genotype. Please refer to Table S1 for a list of the statistical tests used in this

figure.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Fig. 4. Awake extracellular spontaneous firing properties of Purkinje cells in mdx and

control mice. A. Schematic showing the recording approach. B. Schematic illustrating the

electrode placement for targeting the Purkinje cells. C. Example raw voltage trace from a control

Purkinje cell, with complex spikes noted with green asterisks. D. As in C, for mdx mice. E.

Average simple spike waveform for the cell shown in C. F. Average complex spike waveform

for the cell in C. G-H. Simple spike and complex spike waveforms for the mdx cell shown in D.

I. Mean simple spike firing rate (y-axis) was significantly lower in mdx mice (red) compared to

controls (blue). No statistically significant difference was found in mean CV (x-axis). J.

Complex spikes in mdx mice have significantly lower complex spike firing variability compared

to controls, but firing rates do not differ between the genotypes. Circles are individual data

points, crosses represent mean values ± SEM. n = 24 cells of each genotype, N = 4 mice of each

genotype. Please refer to Table S1 for a list of the statistical tests used in this figure. D

isea

se M

ode

ls &

Mec

hani

sms

• D

MM

• A

ccep

ted

man

uscr

ipt

Fig. 5. Spontaneous firing properties of mdx and control cerebellar nuclear neurons in

awake behaving mice. A. Schematic showing the recording approach. B. Schematic illustrating

the electrode placement for targeting the cerebellar nuclear neurons. C. Example raw voltage

trace from a control cerebellar nuclear neuron. D. Example raw voltage trace from an mdx

cerebellar nuclear neuron. E. In awake mice, mean simple spike firing rate was not significantly

different in the mdx mice (red) compared to the controls (blue), but mdx CV2 (variability) was

higher than controls. Circles are individual data points, crosses represent mean values ± SEM. n

= 28 control cells, n = 23 mdx cells, N = 4 mice of each genotype. Please refer to Table S1 for a

list of the statistical tests used in this figure.

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Fig. S1. The anatomy of cerebellar circuits is grossly intact in mdx mice. A. The total number

of Purkinje cells (PC) in the whole mdx cerebellum (Cb) does not differ statistically from the

number of Purkinje cells (PC) in the whole control cerebellum (counted in all lobules/per sagittal

section; Control = 569.2 ± 32.7, mdx= 578.7 ± 6.7, two-tailed Student’s t-tests, N = 3 animals per

genotype, n = 3-8 sections per animal, t(4) = -0.286, p = 0.79). B-D. The total number of Purkinje

cells (PC) in the mdx cerebellum does not differ from that of controls when analyzed by zone

(Control = 256.0 ± 12.9 (anterior), 169. ± 7.4 (central), 143.8 ± 14.3 (posterior/nodular), mdx=

260.6 ± 3.6 (anterior), 181. ± 5.1 (central), 136.7 ± 2.3 (posterior/nodular), two-tailed Student’s t-

tests, N = 3 animals per genotype, n = 3-8 sections per animal; t(4) = -0.340, p = 0.75, t(4) = -

1.345, p = 0.25, t(4) = 0.489, p = 0.65, respectively). E-F. The fastigial (FN) and interposed (IN)

nuclear densities (no = number) are comparable between the genotypes (Control = 17.36 ± 1.61

(FN), 36.11 ± 3.12 (IN), mdx = 21.26 ± 1.20 (FN), 33.19 ± 1.14 (IN), two-tailed Student’s t-tests,

N = 3 animals per genotype, n = 3 sections per animal; t(4) = -1.9646, p = 0.12, t(4) = 0.880, p =

0.43, respectively). G-J. The areas of the fastigial (FN) and interposed (IN) cerebellar nuclei are

comparable between control and mdx mice (Control = 1,242.5 ± 154.9 µm2 (FN), 4,051.9 ± 385.4

µm2 (IN), mdx = 1,483.5 ± 287.7 µm2 (FN), 3,015.8 ± 567.9 µm2 (IN), two-tailed Student’s t-tests,

N = 3 animals per genotype, n = 3 sections per animal, t(4) = -0.737, p = 0.50, t(4) = 1.510, p =

0.21, respectively). The distances of the fastigial and interposed nuclei from bregma are +0.72 mm

(FN) and +1.56 mm (IN), respectively. Calbindin staining (green) labels Purkinje cell soma, axons

and terminals whereas Nissl (blue) is a general stain for cell nuclei. Scale bar, 50 µm.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Fig. S2. Purkinje cells in control and mdx mice express multiple isoforms of dystrophin. A.

Schematic detailing the different isoforms of dystrophin. Gray asterisks indicate the isoforms that

are expressed in the mammalian brain. The dystrophin antibody used in Fig. 1 targets the rod

domain (red) while the MANDRA1 antibody used in this supplemental figure targets the c-

terminus (teal), which is present in all of the isoforms. B. The MANDRA1 antibody detects

dystrophin isoforms that are located near the plasma membrane since the c-terminus of the

dystrophin protein interacts with glycoproteins embedded in the plasma membrane. C. The

hippocampus expresses MANDRA1 in the control brain, demonstrating the expected pattern of

expression. D-E. MANDRA1 expression in control (D) and mdx (E) Purkinje cells is identical.

Representative examples of Purkinje cells are outlined. F. Examples of control Purkinje cells (PC)

that express MANDRA1 (red arrows). G. Examples of mdx Purkinje cells (PC) that express

MANDRA1 (red arrows). Scale bar (C), 200 µm. Scale bar (D-E), 50 µm. Scale bar (F-G), 10

µm. Molecular layer (ml). Purkinje cell layer (pcl). N = 3 mice per genotype.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Fig. S3. The time between surgery and recording does not affect the Purkinje cell properties.

The session day following surgery in which analyzed awake Purkinje cells were recorded did not

affect simple spike (A) or complex spike (B) summary statistics when comparing neurons recorded

10 days or fewer following surgery (n = 25) versus those recorded more than 10 days after surgery

(n = 23). For days post-surgery as a predictor variable, recorded cells were divided into two groups,

high and low, both relative to the median value. The median value was 10, but with two cells

recorded exactly 10 days after surgery. Please refer to Table S1 for a list of the statistical tests

used in this figure.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Fig. S4. The depth of the recordings does not affect overall Purkinje cell properties. The depth

of recorded awake Purkinje cells did not affect simple spike (A) or complex spike (B) summary

statistics when comparing neurons recorded dorsal to 1650 µm (n = 24) and those recorded ventral

to 1650 µm (n = 24). The depth of recorded neurons was calculated based on where we found the

recording features at optimal signal to noise ratio with respect to the surface of the cerebellum at

the site of the craniotomy. The recorded cells were recorded into two groups, high and low, relative

to the median value. Therefore, as a population the dorsoventral depth indicates neurons that fall

in the upper half versus the lower half of the analyzed distance. Please refer to Table S1 for a list

of the statistical tests used in this figure.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Fig. S5. Potential predictor variables apart from genotype show no effect on spiking

characteristics in cerebellar nuclear neurons. A. The length of time between craniotomy

surgery and recording date did not significantly affect rate, CV, or CV2 (one-way MANOVA p =

0.79). B. Anteroposterior recording position showed no difference in spiking statistics between the

anterior and posterior half of recorded cells (p = 0.25). C. Mediolateral distance was not a

significant factor influencing cerebellar nuclear firing (p = 0.13). D. Dorsoventral recording depth

did not affect spiking statistics (p = 0.18). E. Putative recorded nuclei showed no significant effect

on spiking statistics (p = 0.18).

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Fig. S6. Dystrophin is weakly expressed in a subset of cells in the cerebellar nuclei of control

and mdx mice. A-B. A small number of cells in the fastigial (A) and interposed (B) cerebellar

nuclei are weakly immunoreactive for the Dp427 isoform in control mice. C-D. Anti-dystrophin

staining in the fastigial (C) and interposed (D) cerebellar nuclei of mdx mice reveals an identical

staining pattern to that of control mice. The expression of Dp427 is weaker in specific regions of

the interposed nuclei of both genotypes. In many cells within both cerebellar nuclei, the expression

of Dp427 is barely beyond the level of background staining. Scale bar (A-D), 200 µm. N = 3 mice

per genotype.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Comparison Statistical Test

N Statistic Degrees of

freedom

Likelihood BH-corrected

significance Overall cerebellar area by genotype

Two-tailed t-test

6 t = 0.280 4 p = 0.7936 0

Molecular layer thickness by genotype

Two-tailed t-test

6 t = -0.623 4 p = 0.5668 0

Purkinje cell number by genotype, whole cerebellum

Two-tailed t-test 6 t = -0.286 4 p = 0.7888 0

Purkinje cell number by genotype, anterior zone

Two-tailed t-test

6 t = -0.3401 4 p = 0.7509 0

Purkinje cell number by genotype, central zone

Two-tailed t-test

6 t = -1.3452 4 p = 0.2498 0

Purkinje cell number by genotype, posterior-nodular zones

Two-tailed t-test 6 t = 0.4894 4 p = 0.6502 0

Fastigial nucleus area by genotype

Two-tailed t-test

6 t = -0.7372 4 p = 0.5019 0

Fastigial nucleus density by genotype

Two-tailed t-test

6 t = -1.9457 4 p = 0.1236 0

Interposed nucleus area by genotype

Two-tailed t-test

6 t = 1.5096 4 p = 0.2056 0

Interposed nucleus density by genotype

Two-tailed t-test

6 t = 0.8796 4 p = 0.4287 0

Anesthetized simple spike response variables by genotype

One-way MANOVA 94 λ = 0.9028 1,92 p = 0.0261 1

Anesthetized simple spike firing rate by genotype

Wilcoxon rank sum

48/46 z = 1.99 93 p = 0.0471 0

Anesthetized simple spike CV by genotype

Wilcoxon rank sum

48/46 z = 1.76 93 p = 0.0787 0

Anesthetized simple spike CV2 by genotype

Wilcoxon rank sum

48/46 z = -1.48 93 p = 0.1392 0

Anesthetized complex spike response variables by genotype

One-way MANOVA 94 λ = 0.9929 1,92 p = 0.8859 0

Awake simple spike response variables by genotype

One-way MANOVA 48 λ = 0.8266 1,46 p = 0.0371 1

Awake simple spike firing rate by genotype

Wilcoxon rank sum

24/24 z = 2.53 47 p = 0.0115 1

Awake simple spike CV by genotype

Wilcoxon rank sum

24/24 z = -0.03 47 p = 0.9753 0

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n

Awaked simple spike CV2 by genotype

Wilcoxon rank sum

24/24 z = -0.13 47 p = 0.8934 0

Awake complex spike response variables by genotype

One-way MANOVA 48 λ = 0.7772 1,46 p = 0.0106 1

Awake complex spike firing rate by genotype

Wilcoxon rank sum

24/24 z = -0.55 47 p = 0.5848 0

Awake complex spike CV by genotype

Wilcoxon rank sum

24/24 z = 3.17 47 p = 0.0016 1

Awake complex spike CV2 by genotype

Wilcoxon rank sum

24/24 z = 0.75 47 p = 0.4517 0

Awake CN response variables by genotype

One-way MANOVA

51 λ = 0.7494 1,49 p = 0.0033 1

Awake CN firing rate by genotype

Wilcoxon rank sum

28/23 z = -1.47 50 p = 0.1424 0

Awake CN CV by genotype

Wilcoxon rank sum

28/23 z = -0.71 50 p = 0.4778 0

Awake CN CV2 by genotype

Wilcoxon rank sum

28/23 z = -2.36 50 p = 0.0184 1

Awake simple spike response variables by days post-surgery

One-way MANOVA

48 λ = 0.9613 1,46 p = 0.6250 0

Awake simple spike response variables by dorso-ventral position

One-way MANOVA 48 λ = 0.9943 1,46 p = 0.9954 0

Awake complex spike response variables by days post-surgery

One-way MANOVA

48 λ = 0.8533 1,46 p = 0.0701 0

Awake complex spike response variables by dorso-ventral position

One-way MANOVA 48 λ = 0.9943 1,46 p = 0.9682 0

Recording depth by genotype

Wilcoxon rank sum

24/24 z = 0.58 47 p = 0.56 0

Awake CN response variables by days post-surgery

One-way MANOVA 51 λ = 0.9785 1,49 p = 0.7933 0

Awake CN response variables by anterior-posterior position

One-way MANOVA 51 λ = 0.9174 1,49 p = 0.2515 0

Awake CN response variables by medio-lateral position

One-way MANOVA

51 λ = 0.8891 1,49 p = 0.1337 0

Awake CN response variables by dorso-ventral position

One-way MANOVA

51 λ = 0.9022 1,49 p = 0.1800 0

Awake CN response variables by putative lobule

One-way MANOVA 51 λ = 0.9019 1,49 p = 0.1791 0

Table S1. Post-hoc statistical analyses employed throughout the study. A tabulated version of the data showing the values that were reported for the post-hoc statistical analyses.

Disease Models & Mechanisms: doi:10.1242/dmm.040840: Supplementary information

Dis

ease

Mo

dels

& M

echa

nism

s •

Sup

plem

enta

ry in

form

atio

n