optogenetic and potassium channel gene therapy in a rodent model of focal neocortical epilepsy

8/12/2019 Optogenetic and Potassium Channel Gene Therapy in a Rodent Model of Focal Neocortical Epilepsy

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www.sciencetranslationalmedicine.org/cgi/content/full/4/161/161ra152/DC1

Supplementary Materials forOptogenetic and Potassium Channel Gene Therapy in a Rodent Model

of Focal Neocortical Epilepsy

Robert C. Wykes, Joost H. Heeroma, Laura Mantoan, Kaiyu Zheng, Douglas C.

MacDonald, Karl Deisseroth, Kevan S. Hashemi, Matthew C. Walker,* Stephanie

Schorge,* Dimitri M. Kullmann*

*To whom correspondence should be addressed. E-mail: [email protected] (M.C.W.);

[email protected] (S.S.); [email protected] (D.M.K.)

Published 21 November 2012, Sci. Transl. Med.4, 161ra152 (2012)DOI: 10.1126/scitranslmed.3004190

The PDF file includes:

Fig. S1. Correlation of EEG coastline length with increases in high-frequency

power.

Fig. S2. Correlation of burst counting by a blinded observer with high-frequencypower and coastline length.

Fig. S3. Electroclinical features of the tetanus toxin model.

Fig. S4. Automated event classification.

Fig. S5. Criteria used to identify adapting layer 5 pyramidal neurons.Fig. S6. Biophysical properties of type 2 pyramidal neurons in animals injected

tetanus toxin.

Fig. S7. Estimation of volume of tissue transduced with Kv1.1-GFP lentivirus.Fig. S8. Preferential transduction of excitatory neurons with Kv1.1 lentivirus.

Fig. S9. Identification of layer 5 neurons.

Fig. S10. Behavioral assessment in animals injected with Kv1.1-GFP lentivirus.Fig. S11. Immunohistochemical analysis of neuronal and glial markers after

Kv1.1-GFP lentivirus injection.

Fig. S12. Stable neuronal transduction with Kv1.1 lentivirus.


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Figure S2. Correlation of burst counting by a blinded observer with high-frequency power

and coastline length.(A) Representative EEG segments identified as seizure-like bursts. (B)

Scatter plots showing absence of correlation between beta (12 30 Hz) power and burst count

during one hour of EEG recording 7 days after TT (n = 19; red line, linear regression). ( C) as in(B) for 120 160 Hz band. (D) Correlation of coastline and burst count. (E) Coefficients of

determination obtained from plots as in (B D) (filled bar, coastline). **, P< 0.01; ***, P15 %

weight loss, or death following a severe seizure, were seen in a subset of animals which

exhibited especially high HF power (Fig. 1F). (A) Dystonic contralateral forelimb posture. (B)

EEG recording from an animal showing a buildup of electrographic seizure activity prior to

death.


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High Frequency Power

Intermittency

Library Events Plot Eating

Grooming

High Frequency High Amp

High Frequency Low Amp

High Frequency Spike

High Frequency Short

500 ms1mV

Left to right: File name, Second, Channel, Classif ication status, Baseline value, Metrics

M1310061660.ndf 3072.0 14 U 3.1 0.684 0.213 0.874 0.634 0.619 0.932a

b

Figure S4. Automated event classification.The program stepped through consecutive 1 s EEG

epochs, and updated a running estimate of the baseline power as the lowest power between 4 and

160 Hz in any 1 s epoch during the preceding 20 minutes. Epochs whose power exceeded 5 x

baseline were defined as putative events. For each such event, 6 parameters were estimated:

Power (in the 4 160 Hz band), Transient Power (power in the 1 4 Hz band), High Frequency

Power (60 160 Hz), Spikiness (voltage range/standard deviation), Voltage Asymmetry (balance

of points exceeding 2 standard deviations either side of the mean), and Intermittency (low-

frequency power of the rectified high-frequency signal). We applied a sigmoidal function to

these 6 characteristics so as to obtain metrics bounded between zero and one. (A) Example of a

metrics processor output line. The last 6 numbers are the metrics. The event is thus represented

as a point in a 6-dimensional hypercube. (B) Two-dimensional projection of the metric space,


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showing High Frequency Power and Intermittency selected as the X and Y axes, with colors

corresponding to different classes of normal behavior-related and epileptiform events. The event

library was constructed by an operator who, with reference to synchronized video recordings,

classified events as no event (no obvious electrographic or behavioral event), short high

frequency bursts (250 ms, event power >6 x

baseline), long high frequency bursts of low amplitude (>250 ms, event power 5 6 x

baseline), high frequency spikes, eating-related or grooming-related. The archetypical

epileptiform EEG event exemplars are shown on the right. Other classes of events, which bore

no relation to seizures in either behavior or EEG signature, such as head-shake and other/non-

specified, are not illustrated (such events occurred at similar frequencies in TT-injected and

control animals). As the algorithm stepped through subsequently identified events these were

provisionally identified as belonging to one or other category according to its Euclidean distance

to previously classified neighbors. The identity of each new event proposed by the algorithm was

overruled by the observer if necessary until it reached a false allocation rate


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Figure S5. Criteria used to identify adapting layer 5 pyramidal neurons.Type 1 non-


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adapting neurons have larger somata and thicker-tufted dendrites than type 2 neurons and exhibit

non-adapting trains of action potentials (APs) (30). (A) Sample traces showing APs at threshold

in both types of neurons. (B) Schematic showing measurement of AP waveform parameters. (C)

AP waveform parameters in type 1 and type 2 pyramidal neurons. (D) Biophysical properties and

location of type 1 and type 2 pyramidal neurons (left to right: resting membrane potential (RMP),

resting input resistance (RN), current threshold (IThresh), membrane time constant, capacitance,

distance from pia). (E)Firing patterns evoked by constant current injection (left, black trace,

type 1; right, gray trace, type 2). (F) Interspike interval normalized by the interval between the

second and third spikes. (G) Voltage threshold and waveform during trains of APs (left to right:

threshold plotted against AP number, peak AP voltage, halfwidth). (H) Expanded traces

showing representative AP trains from type 1 and type 2 neurons showing distinct

afterhyperpolarization shapes. (I) At sub-physiological temperatures type 1 neurons can exhibit

AP bursting behavior, consistent with previous reports in the rodent motor cortex (57). At 34

37 C neither type 1 nor type 2 neurons exhibited burst firing. Therefore, all recordings were

conducted at 36 C.


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Figure S6. Biophysical properties of type 2 pyramidal neurons in animals injected

tetanus toxin. (A)Sample traces showing action potentials at threshold from two control (black)

and two tetanus-injected animals (red). The proportion of neurons firing doublets was notsignificantly different between conditions. (B) Parameters measured as explained in figure S5.

Control (Ct) data are replotted for comparison. (C) Trains of action potentials in neurons from

both control animals and animals injected with tetanus toxin showed adaptation of firing

frequency. (D) Summary of inter-spike intervals. * P < 0.05 (not significant when corrected for

multiple comparisons).


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Figure S8. Preferential transduction of excitatory neurons with Kv1.1 lentivirus.

Immunofluorescence images obtained 3 weeks after injection of lentivirus encoding Kv1.1 and

GFP showing colocalization of GFP with the glutamatergic neuron marker CaMKII, and little

or no colocalization with either the GABAergic marker GAD67 or the glial marker GFAP. Kv1.1

lentivirus injection resulted in GFP expression in 678 121 neurons (avg s.e.m., n = 5 animals

tested). Of these, 72 8% (n = 3) were CaMKII-positive, corresponding to 53 19 % of the

local CaMKII-positive population; 1.5 1.5 % (n = 4) were GAD67-positive (6% of the local

population) and 0 cells (n = 4) were GFAP-positive.


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Action potential number Action potential number

Action potential number

Figure S9. Identification of layer 5 neurons.Cells included in Fig. 3 were adapting type 2

pyramidal cells (UI, uninjected animals; G, GFP-positive neurons from animals injected with

GFP-only lentivirus; UT, Kv, untransduced and transduced neurons from animals injected with

Kv1.1 lentivirus respectively; T1, type 1 neurons shown for comparison). Cell capacitance,

normalized inter-spike interval, and AP halfwidth were all clearly different from type 1 neurons.


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Figure S10. Behavioral assessment in animals injected with Kv1.1-GFP lentivirus. (A)

Number of ipsilateral (right) and contralateral (left) foot faults during 2 minutes of free

exploration on an elevated wire grid in animals injected with Kv1.1-GFP lentivirus (n = 5

animals, mean SEM). (B)Data from animals injected with GFP-only lentivirus (n = 5). The

performance improved with time non-significantly in both groups, consistent with motorlearning, but neither group showed a difference between left and right forelimb function.

Grooming and nesting behavior were also unaffected.


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Figure S11. Immunohistochemical analysis of neuronal and glial markers after Kv1.1-GFP

lentivirus injection. (A) GFP fluorescence (left) and NeuN immunofluorescence in a section

obtained 4 weeks after injection of lentivirus encoding Kv1.1 and GFP. (B)GFP and GFAP

immunofluorescence at 4 weeks.


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Figure S12. Stable neuronal transduction with Kv1.1 lentivirus.(A) GFP

immunofluorescence 6 months after injection, showing similar size and location of transduced

area. (B) High magnification of transduced neurons at 6 months, showing pyramidal cell

morphology. (C) Serial sections illustrating transduced volume, which was similar to data

sacrificed at 4 weeks.

optogenetic and potassium channel gene therapy in a rodent model of focal neocortical epilepsy

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