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Supplementary Materials for
Deconstructing behavioral neuropharmacology with cellular specificity
Brenda C. Shields, Elizabeth Kahuno, Charles Kim, Pierre F. Apostolides, Jennifer Brown,
Sarah Lindo, Brett D. Mensh, Joshua T. Dudman, Luke D. Lavis, Michael R. Tadross*
*Corresponding author. Email: [email protected]
Published 7 April 2017, Science 356, aaj2161 (2017)
DOI: 10.1126/science.aaj2161
This PDF file includes:
Figs. S1 to S7
Synthesis methods
Captions for movies S1 to S3
References
Other supplementary material for this manuscript includes the following:
Movies S1 to S3
Fig. S1 │ Feature set of DART. Columns: the minimum ‘alphabet’ of features needed to causally link specific
molecules in defined cells to behavioral roles. Rows: available manipulations. Plusses (+) indicate features
demonstrated in the literature. At present, DART uniquely provides all four features, as follows:
(A) Acute onset: DART takes effect within minutes, averting most compensatory changes. In contrast, gene
editing (70) and genetically encoded toxin (32) approaches take days for protein turnover or toxin expression,
with potential for up- or down-regulation of compensatory genes (33). DART is notably slower than methods
with optical control. Future implementations could provide faster onset or rapid reversibility (see Discussion).
(B) Behaving-animal utility enables causal links to behavior to be drawn, but represents a technical challenge.
(C) Cell-type specificity is critical given the cellular diversity of the brain.
(D) Endogenous-protein specificity refers to manipulation of native receptors expressed from their endogenous
gene locus. This is distinct from the production of ectopic signals via non-mammalian actuators such as ChR2
(23). Actuators constructed from engineered mammalian proteins (71) (including OptoXR (72), LOV-Rac (30),
DREADD (25, 26), PSAM (24) and the SPARK/LiGluR family of actuators (27-29, 31, 73)) may, in principle, provide
similar utility, but typically require viral overexpression, which can disrupt the underlying biology (39) or
imperfectly reflect endogenous function. In principle, endogenous expression could be achieved by grafting an
engineered mammalian receptor into an endogenous genomic locus. However, germline knock-in would lack
cell-type specificity (31), whereas gene editing in a cell-type-specific manner has not been demonstrated for
these actuators in the literature, and is technically difficult. For example, TALEN or CRISPR/Cas9 (70)-mediated
`
editing require homologous recombination, which lacks the desired efficiency for cell-type-specific genomic
editing in mature brain tissue (74). Alternately, cre-based conditional knock-ins (75) typically involve exon
duplication, which can have deleterious effects on expression (76). Finally, cre-dependent expression from a
separate genomic locus (e.g., ROSA26) may poorly recapitulate endogenous-locus expression—a particular
concern in models of disease, wherein complex changes in gene regulation often play a central role in the
pathophysiology (8, 9, 77).
In contrast to engineered receptors, light-sensitive toxins (LOV-peptides, lumitoxins) (36, 37) and cell-typespecific enzymatic unmasking of prodrugs (PLE + masked MK801) (34, 35) have shown promise in acutely
manipulating endogenous proteins, but utility in vivo remains to be demonstrated. In particular, light-sensitive
toxins may require further optimization of contrast between dark and illuminated toxin potency (36, 37).
Conversely, toxic prodrugs (LacZ + Daun02) (78) can ablate cells, but lack protein specificity; whereas nontoxic
prodrugs will require optimization of drug solubility and cell permeability (34, 35), and would be limited to drugs
that act intracellularly.
Of note, the protein specificity of DART is specified by that of the original drug which was tethered, and thus
cannot distinguish AMPAR subtypes, for example. Likewise, the current implementation of DART is slower than
methods with optical control. Thus, whereas many tools excel and/or outperform DART in a given capacity,
achieving the four-fold ‘alphabet’ of features with a single technique has been technically challenging. DART
uniquely combines these four features, however, further refinement of its temporal and/or molecular precision
may be needed in future endeavors.
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Fig. S2 │ Design of YM90K-DART. (A) Site of drug conjugation on the 1-position of the quinoxaline ring (arrow)
guided by SAR and crystal structure of AMPAR bound to competitive antagonist DNQX (42). (B) Model of
YM90K-DART bound to AMPAR. (C) Chemical structures of DNQX (1), YM90K (2) and a known YM90K derivative
(40, 41) (3) containing a butyric acid on the 1-position. (D) Chemical synthesis scheme: compound 3 was amide2
conjugated to amino-PEG36-acid, followed by amide conjugation to amino-HTL (Methods). (E) HaloTagTM
contains the following: SSnlg-HA-mHT-ΔECD.TM.CTnlg-ERXL (Methods). (F) Packaging HaloTagTM with dTomato
marker of expression into cre-independent (top) and cre-dependent (DIO, bottom) recombinant adenoassociated virus (rAAV; Methods). (G) Characterization of rundown in cultured-neuron assays (as in Fig. 1E-H).
Assays were repeated for six rounds without any antagonist (including mock wash), followed by traditional
antagonist (NBQX or CPP, respectively). Each symbol is the per-coverslip mean from HT‒ (black) and HT+
(colored) cells; error bars are mean ± SEM over 24 coverslips.
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Fig. S3 │ YM90K-DART linker optimization and specificity characterization. (A-B) Cultured-neuron AMPAR assay
(as in Fig. 1F) for YM90K and YM90K conjugates. Each symbol is the per-coverslip mean from HT‒ (black) and
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HT+ (colored) cells; error bars are mean ± SEM. Dashed line accounts for rundown in the assay (Fig. S2G), and
solid curves are binding-relation fits with IC50 as indicated. PEG conjugation lowers diffusible drug potency by
~30-fold on HT‒ cells (compare black curve in panel B to those in panel A). Drug potency on HT+ cells increases
as a function of increasing PEG length. The combination of these two factors produces a 75-fold difference in
YM90K-DART (PEG36) potency on HT+ vs HT‒ cells. (C) Tethered drug potency as a function of HaloTagTM
expression level. One symbol per neuron, plotting the fraction of residual AMPAR activity following drug
tethering and washout (vertical axis), as a function of dTomato intensity (proxy for HaloTagTM expression,
horizontal axis). Error bars, mean ± SEM of data binned according to dTomato expression. (D) Test for bystander
effects of HT+ tethered drug on adjacent HT‒ cells. One symbol per HT‒ neuron, plotting the fraction of residual
AMPAR activity following drug tethering and washout (vertical axis), as a function of proximity to the closest
HT+ cell (horizontal axis). Error bars, mean ± SEM of data binned according to proximity (10 cells per bin).
(E) Model of tethered-drug diffusion. We first applied a classic formula developed by Flory (79, 80) for polymerchain statistics to specify the local concentration (in µM) produced by a drug linked to a single HaloTag:
RxConcFromOneHT(d); where d is the distance from HaloTag (in nm); NAvogadro (= 6.02 × 10-7 µM-1nm-3) is the
number of molecules comprising a 1 µM solution in a volume 1 nm3; and the length constant β is determined by
the number of PEG repeats (nPEG) where each PEG is 0.36 nm in length (see Flory Eqn. below diagram) (79, 80).
We integrated RxConcFromOneHT( r 2 + h 2 ) over all values of r for a fixed value of h (see diagram), thus allowing
HaloTag to laterally diffuse over all radial distances (r, in nm) from a receptor which is vertically displaced a
height (h, in nm) from the membrane. This yielded RxConc(h) which provides the effective surface concentration
felt by an AMPAR at a given height (Eqn. to the right of diagram; #HT/nm2 accounts for surface density of
HaloTag expression). Assuming h = 0 for AMPARs on an HT+ cell, the ratio RxConc(h) / RxConc(0) = exp(-β2 ·h2)
represents the relative drug concentration felt by an AMPAR on an HT‒ vs HT+ cell. For nPEG = 36, this relative
concentration drops steeply over a ~2 nm length scale (red curve). Thus, the PEG36 linker rarely adopts the fully
extended (14 nm) configuration, making it very unlikely that transcellular effects would occur, even for
intermembrane distances well below the ~20 nm estimate (44). (F) Tethered drug has no detectible effects on
NMDAR activity, even at the highest HaloTagTM expression levels. (G) Primary binding screen using 10 µM
YM90K and 300 µM YM90K-DART in 30 radioligand displacement assays, performed by the NIMH Psychoactive
Drug Screening Program. Data are mean displacement from four determinations; +50% is the standard
threshold for significance. Negative displacement represents nonspecific enhancement of radioligand binding,
sometimes seen when screening at high doses.
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Fig. S4 │ Supporting data for Fig. 3. (A) Pilot dosing experiments. HT‒ mice received a unilateral striatal infusion
with 1 µL saline containing the specified YM90K-DART dose, and were monitored in an open-field arena.
Behavioral effects did not appear until 300 µM YM90K-DART. (B) Characterization of surface HaloTagTM protein
6
turnover. Cultured neurons expressing HaloTag-2A-dTomato were incubated with HTL488 cell-impermeant dye
(1 µM for 10 min), washed and returned to the incubator for a specified interval, then incubated with HTL660
cell-impermeant dye (3.5 µM for 10 min), washed and imaged on a widefield fluorescence microscope. Top
insets show plots of surface dye labeling as a function of dTomato (a proxy for HaloTagTM expression), which
were normalized to 100 arbitrary florescence units for both HTL488 and HTL660 color channels. Bottom-right
inset shows plots of HTL488 vs HTL660 in individual cells, which were fit with straight-lines constrained through
the origin via regression-slope analysis. This slope ±SEM provided the fraction of surface HaloTagTM bound to
HTL488 as a function of interval duration (large graph). Turnover was fit with a bi-exponential relationship
(dashed green curve) with 30% fast (4 hr) and 70% slow (5 day) time constants. (C) Redosing behavioral
experiments. Mice infused while awake (arrow), and placed in an open field arena for several 1 hr sessions.
Infusions were performed once per week; first with saline, then 30 µM YM90K-DART (Rx), then 30 µM
YM90K-DART (repeat). Net number of 360° turns per 1 hr session (left minus right turns) for HT‒ (black) and HT+
(red) animals. One thin line per animal; thick lines and shading represent mean ± SEM across animals. Top graph
for D1-, bottom for D2-cre mice. Right: summary of effects for HT+ mice. Each connected symbol pair represents
one animal; error bars mean ± SEM; p values Wilcoxon signed rank test. The magnitude of behavioral effects in
D1-cells was similar upon repeated dosing, whereas manipulation of D2-cells produced diminished behavioral
effects (~half the rotation rate) on the second dose. Thus, whereas the acute onset of the first dose averts
compensatory phenomena, the ~1 day duration of the manipulation may have triggered more pronounced
compensatory phenomena in D2- vs D1-cells. (D) Additional behavioral metrics from D1-cre and D2-cre openfield sessions. All data corresponds to day-one sessions, and symbol color, format, and statistical tests are as in
Fig. 3C. See Methods for analysis details. From left to right: (1) Frequency of 360° turns per hr, binned by turn
diameter (HT+ animals only), left turns positive, right turns negative. (2) Tortuosity; a measure of trajectory
curviness that is independent of velocity. (3) Velocity. (4) Akinesia; percent of time immobilized. Each connected
symbol pair represents one animal (saline, Rx); error bars mean ± SEM; p values Wilcoxon signed rank test.
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Fig. S5 │ Supporting data for Fig. 4. (A) Histological penetrance of DART manipulation (see Methods). Data from
healthy mice reproduced from Fig. 3D; p values, Wilcoxon rank sum test. (B) Timecourse and stability of
6-OHDA-induced behavioral deficits. (C-E) Additional behavioral metrics corresponding to open-field sessions in
Fig. 4. From left to right: (1) narrow turns / hr (net number of 360° turns (left - right) with diameter ≤ 10 cm);
(2) all turns / hr (net number of 360° turns (left - right) with any diameter); (3) tortuosity, a measure of curviness
of trajectories which is independent of velocity (Methods); (4) velocity (meters per hour). Connected symbols
represent one animal (see key in panel C); error bars mean ± SEM; p values Wilcoxon signed rank test.
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Fig. S6 │ Additional supporting data for Fig. 4. (A-B) Behavioral metrics corresponding to open-field sessions of
A2A-cre and ChAT-cre animals. Format as in Fig. S5.
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Fig. S7 │ Additional data for atropine-DART. (A) Design guided by crystal structure of mAchR bound to the
competitive antagonist, QNB (53) (left). Homology-based docking of the related antagonist, atropine, indicated
that a primary hydroxyl was positioned near a narrow opening (middle), suggesting that tether-addition to this
site would permit linker exit (right). (B) Synthesis scheme: (i) dehydration of atropine to apoatropine; (ii)
Michael addition of thiol-PEG6-acid; (iii) amide conjugation to amino-PEG36-acid; (iv) amide conjugation to
amino-HTL. (C) Cultured neuron assay of mAchR signaling confirmed the known IC50 ~2 nM for atropine, and
established that YM90K-DART has no effect on mAchR signaling for HT‒ or HT+ cells (format as in Fig. 5C).
(D-E) Cultured neuron assays of AMPAR and NMDAR synaptic transmission were sensitive to their respective
antagonists (NBQX and CPP), but atropine-DART produced no evidence of AMPAR or NMDAR block for HT‒ or
HT+ cells (format as in Fig. 1E-H).
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Supplementary synthesis methods
YM90K-DART synthesis. The following two-step procedure was used (Fig. S2D):
(i) Compound 3 (0.021 g, 6 x 10-5 mol) was charged to a vial. DMF (1 mL) was added to generate a
heterogeneous mixture and stirred at room temperature. N,N,N′,N′-Tetramethyl-O-(N-succinimidyl)uronium
tetrafluoroborate (8.1 mg, 2.7 x 10-5 mol) was added followed by Hunig’s base (0.062 mL, 3.6 x 10-4 mol),
affording a clear solution. After stirring 10 min, Amino-PEGn-COOH (0.100 g, 6 x 10-5 mol for n = 36) was added.
This reaction was allowed to stir for 20 min, and then diluted with a 3:1 solution of ACN:H2O (2 mL) and purified
by reverse phase preparative chromatography. The desired fractions were collected, concentrated and kept
under vacuum overnight to afford compounds 4 to 6 (4: 92%; 5: 64%; 6: 0.095g, 79% yield) as slightly yellow
viscous oils:
• Compound 4: 1H NMR (400 MHz, Methanol-d4) δ 9.36 (t, J = 1.5 Hz, 1H), 8.10 (s, 1H), 7.96 (s, 1H), 7.88 (t, J =
1.8 Hz, 1H), 7.81 (dd, J = 2.0, 1.4 Hz, 1H), 4.23 – 4.05 (m, 2H), 3.63 (t, J = 6.2 Hz, 2H), 3.54 – 3.40 (m, 46H),
3.27 - 3.25 (m, 2H), 2.45 (t, J = 6.3 Hz, 2H), 2.29 (t, J = 6.7 Hz, 2H), 1.95 (p, J = 6.9 Hz, 2H).
• Compound 5: 1H NMR (400 MHz, Methanol-d4) δ 9.44 (t, J = 1.5 Hz, 1H), 8.19 (s, 1H), 8.06 (s, 1H), 7.98 (t, J =
1.8 Hz, 1H), 7.93 – 7.86 (m, 1H), 4.35 – 4.14 (m, 2H), 3.74 (t, J = 6.3 Hz, 3H), 3.64 – 3.56 (m, 103H), 3.51 (t, J =
5.4 Hz, 2H), 3.36 - 3.32 (p, J = 1.6 Hz, 2H), 2.55 (t, J = 6.3 Hz, 2H), 2.39 (t, J = 6.8 Hz, 2H), 2.14 – 1.97 (m, 2H).
• Compound 6: 1H NMR (400 MHz, Methanol-d4) δ 9.29 (s, 1H), 8.08 (s, 1H), 7.95 (s, 1H), 7.82 (d, J = 28.1 Hz,
2H), 4.21 – 4.06 (m, 2H), 3.64 (t, J = 6.3 Hz, 3H), 3.53 – 3.50 (m, 151H), 3.49 – 3.47 (m, 13H), 3.40 (t, J =
5.6Hz, 2H), 3.23 – 3.21 (m, 2H), 2.44 (t, J = 6.3 Hz, 2H), 2.28 (t, J = 6.8 Hz, 2H), 2.05 – 1.81 (m, 2H).
(ii) Compounds 4-6 (0.087 g, 4.3 x 10-5 mol, for n = 36) were charged to a vial. DMF (1 mL) was added and stirred
at room temperature. N,N,N′,N′-Tetramethyl-O-(N-succinimidyl)uronium tetrafluoroborate (0.013 g, 1eq.) was
added followed by Hunig’s base (0.045 mL, 6 eq.). After stirring 10 min, HaloTag ligand (0.010 g, 1 eq.) was
added and stirred for 20 min. The reaction mixture was taken up in a 3:1 solution of ACN:H2O (2 mL) and
purified by reverse phase preparative chromatography. The desired fractions were collected, concentrated and
kept under vacuum overnight to afford compounds 7 to 9 (7: 31%; 8: 41%; 9: 59.2mg, 62% yield) as viscous oils:
• Compound 7: 1H NMR (400 MHz, Methanol-d4) δ 9.36 (s, 1H), 8.10 (s, 1H), 7.96 (s, 1H), 7.88 (t, J = 1.8 Hz,
1H), 7.81 (t, J = 1.7 Hz, 1H), 4.22 – 4.07 (m, 2H), 3.63 (t, J = 6.2 Hz, 2H), 3.56 – 3.38 (m, 69H), 3.29 – 3.25 (m,
4H),2.37 (t, J = 6.2 Hz, 2H), 2.29 (t, J = 6.7 Hz, 2H), 1.95 (p, J = 6.9 Hz, 2H), 1.68 (dq, J = 8.0, 6.6 Hz, 2H), 1.55 –
1.46 (m, 2H), 1.43 – 1.35 (m, 2H), 1.34 – 1.26 (m, 2H).
• Compound 8: 1H NMR (400 MHz, Methanol-d4) δ 9.27 (s, 1H), 8.07 (s, 1H), 7.94 (s, 1H), 7.81 (d, J = 29.0 Hz,
2H), 4.23 – 4.03 (m, 2H), 3.73 – 3.66 (m, 1H), 3.63 (t, J = 6.2 Hz, 3H), 3.52 – 3.37 (m, 112H), 3.30 – 3.23 (m,
3H), 2.35 (t, J = 6.2 Hz, 2H), 2.28 (t, J = 6.8 Hz, 2H), 1.94 (p, J = 7.0 Hz, 2H), 1.74 – 1.59 (m, 2H), 1.56 – 1.44
(m, 2H), 1.42 – 1.34 (m, 2H).
• Compound 9 (YM90K-DART): 1H NMR (400 MHz, Methanol-d4) δ 9.44 (t, J = 1.5 Hz, 1H), 8.19 (s, 1H), 8.07 (s,
1H), 8.02 – 7.85 (m, 1H), 4.33 – 4.14 (m, 1H), 3.81 (dd, J = 5.8, 3.9 Hz, 1H), 3.73 (t, J = 6.2 Hz, 1H), 3.64 – 3.48
(m, 160H), 3.38 (t, J = 5.6 Hz, 2H), 3.34 – 3.33 (m, 2H), 2.46 (t, J = 6.2 Hz, 1H), 2.39 (t, J = 6.8 Hz, 1H), 2.11 –
1.98 (m, 1H), 1.84 – 1.72 (m, 1H), 1.67 – 1.55 (m, 1H), 1.55 – 1.44 (m, 1H), 1.48 – 1.34 (m, 1H). HRMS (ES+)
calculated for C100H182ClN7O44 [M+H]+2 = 1111.075, found 1111.6001.
Atropine-DART synthesis. The following four-step procedure was used (Fig. S7B):
(i) Atropine (2.043g, 7.06 x 10-3mol) was charged to a round bottom flask and dissolved in CH2Cl2 (10mL). To this
stirring solution was added in sequential order: I2 (2.150g, 8.47 x 10-3 mol) PPh3 (2.222g, 8.47 x 10-3mol)and
imidazole (1.202g, 1.76 x 10-2mol) and stirred for 1h at ambient temperature. The reaction was quenched with
saturated NaHCO3(aq) and Na2S2O3(aq) and stirred for 10 minutes. The aqueous layer was extracted with CH2Cl2.
The combined organic layers were washed with brine, dried over Na2SO4, filtered and concentrated in vacuo.
11
The crude extract was purified by silica gel chromatography using a linear gradient of 0 – 10% CH3OH in CH2Cl2
containing 2M NH3 as a modifier to afford 11 as a white crystalline solid (1.148g, 77% yield).
• Compound 11: 1H NMR (400MHz, CDCl3) δ 7.29 – 7.26 (m, 5H), 6.28 (d, J = 1.2Hz, 1H), 5.81 (d, J = 5.1Hz, 1H),
5.13 (t, J = 5.1Hz, 1H), 3.39 (br. s, 2H), 2.55 (dt, J = 15.7, 4.2Hz, 2H), 2.40 (s, 3H), 1.97 – 1.94 (m, 2H), 1.85 –
1.79 (m, 4H).
(ii) An oven-dried flask was cooled to ambient temperature under an Ar atmosphere and charged with HS-PEG6CO2t-Bu (0.311 g, 0.73 mmol). Anhydrous THF (2 mL) was added and the solution was cooled to –78 °C. n-BuLi
(1.6 M, 0.456 mL) was added dropwise and the reaction was stirred for 15 min. Compound 11 (0.180 g, 0.66
mmol) dissolved in THF was added dropwise and the resulting reaction mixture was stirred for 20 minutes at –
78 °C and then quenched with excess 1N HCl. The reaction mixture was stirred overnight, concentrated and
purified directly by reverse phase HPLC on a C-18 column using a 10-90% gradient of CH3CN in H2O containing
0.1% v/v TFA as a modifier to afford 12 in 47% yield (0.198g).
• Compound 12: 1H NMR (400MHz, Methanol-d4) δ 7.37 - 7.29 (m, 5H), 5.03 (t, J = 4.76Hz, 1H), 3.96 – 3.92 (m,
1H), 3.84 (br. s, 1H), 3.73 (t, J = 6.2Hz, 3H), 3.66 – 3.60 (m, 24H), 3.01 (dd, J = 13.4, 6.04Hz, 1H), 2.74 – 2.71
(m, 5H), 2.54 (t, J = 6.2Hz, 2H), 2.39 – 2.25 (m, 2H), 2.23 – 2.19 (m, 1H), 2.18 – 2.12 (m, 1H), 2.06 – 1.98 (m,
1H), 1.92 – 1.89 (m, 1H), 1.70 – 1.62 (m, 1H).
(iii) Compound 12 (99 mg, 0.154 mmol) was dissolved in DMF (3 mL). N,N,N′,N′-Tetramethyl-O-(Nsuccinimidyl)uronium tetrafluoroborate (46 mg, 0.154 mmol, 1 equiv) was added followed by Hunig’s base (60
mg, 0.46 mmol, 3 equiv). H2N-PEG36-CO2H (249 mg, 0.154 mol, 1 equiv) was added to afford a heterogeneous
mixture, which was sonicated for 5 minutes and then stirred at ambient temperature for 30 min. The reaction
mixture was purified directly by reverse phase HPLC on a C-18 column using a 10-60% gradient of CH3CN in H2O
containing 0.1% v/v TFA to afford the desired product 13 (108 mg, 31% yield).
• Compound 13: 1H NMR (400MHz, Methanol-d4) δ 7.41 – 7.29 (m, 5H), 5.03 (t, J = 4.56Hz, 1H), 3.98 – 3.93 (m,
1H), 3.86 (br. s, 1H), 3.85 – 3.80 (m, 2H), 3.74 – 3.70 (m, 10H), 3.63 – 3.59 (m, 241H), 3.54 (t, J = 5.6Hz, 3H),
3.46 – 3.44 (m, 1H), 3.38 – 3.34 (m, 3H), 3.01 (dd, J = 13.4, 6.0Hz, 1H), 2.74 – 2.71 (m, 4H), 2.54 (t, J = 6.2Hz,
3H), 2.45 (t, J = 6.2Hz, 2H), 2.40 – 2.30 (m, 2H), 2.26 – 2.13 (m, 3H), 2.06 – 1.97 (m, 1H), 1.93 – 1.89 (m, 1H),
1.69 – 1.62 (m, 1H).
(iv) Compound 13 (108 mg, 47 μmol) was dissolved in DMF (3 mL). Tetramethyl-O-(N-succinimidyl)uronium
tetrafluoroborate (14 mg, 47 μmol, 1 equiv) was added followed by Hunig’s base (30 mg, 0.23 mmol, 4 equiv).
HaloTag amine (O2) ligand (17 mg, 47 μmol, 1.1 equiv) was added portion-wise until starting material 13 was
consumed. The reaction mixture was purified directly by reverse phase HPLC on a C-18 column using a 20-60%
gradient of CH3CN in H2O containing 0.1% v/v TFA to afford the desired product 14, a clear viscous oil (75 mg,
64% yield).
• Compound 14 (atropine-DART): 1H NMR (400MHz, Methanol-d4) δ 7.41 – 7.29 (m, 5H), 5.04 – 5.02 (m, 1H),
3.97 – 3.93 (m, 1H), 3.85 (br. s, 1H), 3.83 – 3.80 (m, 1H), 3.72 (dt, J = 6.16, 2.0Hz, 6H), 3.64 – 3.57 (m, 172H),
3.56 – 3.52 (m, 7H), 3.50 – 3.47 (m, 4H), 3.36 (t, J = 5.4Hz, 5H), 3.25 – 3.18 (m, 3H), 3.01 (dd, J = 13.5, 6.0Hz,
1H), 2.45 (t, J = 6.0Hz, 5H), 2.40 – 2.12 (m, 5H), 2.06 – 2.00 (m, 1H), 1.93 – 1.89 (m, 1H), 1.80 – 1.73 (m, 2H),
1.69 – 1.65 (m, 1H), 1.63 – 1.56 (m, 2H), 1.51 – 1.35 (m, 1H). HRMS (ES+) calculated for C117H220ClN3O48S
[M+H]+2 = 2505.03, found 2505.4417.
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Movie S1. Example cultured‐neuron AMPAR assay corresponding to Fig. 1D‐E. Initial image depicts GCaMP
(green) and dTomato (red) expression. Subsequent frames depict ΔF/F0 Ca2+ imaging. Cells are subjected to
repetitive FITC‐cube illumination (50 ms exposure, 3‐Hz, 16 frames), which is repeated 6 times for each
dose (2 min between repetitions). Experimental drugs were added by manual pipetting (~5 min between
doses). See Methods for assay details.
Movie S2. Example open‐field recordings corresponding to Fig. 3. D1‐ and D2‐cre HT+ animals turn in
opposite directions following YM90K‐DART infusion into the left striatum.
Movie S3. Example open‐field recordings for D2‐cre HT+ Parkinsonian animal. The animal exhibits
pronounced akinesia and narrow turns to the left (13 days after 6‐OHDA). In the same animal, following D2‐
cell‐restricted AMPAR antagonism, these symptoms are significantly ameliorated.
13
References
1. C. I. Bargmann, How the new neuroscience will advance medicine. JAMA 314, 221–222
(2015). doi:10.1001/jama.2015.3298 Medline
2. L. M. Monteggia, R. C. Malenka, K. Deisseroth, Depression: The best way forward. Nature
515, 200–201 (2014). doi:10.1038/515200a Medline
3. H. A. Whiteford, L. Degenhardt, J. Rehm, A. J. Baxter, A. J. Ferrari, H. E. Erskine, F. J.
Charlson, R. E. Norman, A. D. Flaxman, N. Johns, R. Burstein, C. J. Murray, T. Vos,
Global burden of disease attributable to mental and substance use disorders: Findings
from the Global Burden of Disease Study 2010. Lancet 382, 1575–1586 (2013).
doi:10.1016/S0140-6736(13)61611-6 Medline
4. H. Bergman, T. Wichmann, M. R. DeLong, Reversal of experimental parkinsonism by lesions
of the subthalamic nucleus. Science 249, 1436–1438 (1990).
doi:10.1126/science.2402638 Medline
5. C. R. Gerfen, T. M. Engber, L. C. Mahan, Z. Susel, T. N. Chase, F. J. Monsma Jr., D. R.
Sibley, D1 and D2 dopamine receptor-regulated gene expression of striatonigral and
striatopallidal neurons. Science 250, 1429–1432 (1990). doi:10.1126/science.2147780
Medline
6. V. Gradinaru, M. Mogri, K. R. Thompson, J. M. Henderson, K. Deisseroth, Optical
deconstruction of parkinsonian neural circuitry. Science 324, 354–359 (2009).
doi:10.1126/science.1167093 Medline
7. A. V. Kravitz, B. S. Freeze, P. R. Parker, K. Kay, M. T. Thwin, K. Deisseroth, A. C. Kreitzer,
Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia
circuitry. Nature 466, 622–626 (2010). doi:10.1038/nature09159 Medline
8. A. B. Nelson, A. C. Kreitzer, Reassessing models of basal ganglia function and dysfunction.
Annu. Rev. Neurosci. 37, 117–135 (2014). doi:10.1146/annurev-neuro-071013-013916
Medline
9. D. J. Surmeier, S. M. Graves, W. Shen, Dopaminergic modulation of striatal networks in
health and Parkinson’s disease. Curr. Opin. Neurobiol. 29, 109–117 (2014).
doi:10.1016/j.conb.2014.07.008 Medline
10. W. Shen, M. Flajolet, P. Greengard, D. J. Surmeier, Dichotomous dopaminergic control of
striatal synaptic plasticity. Science 321, 848–851 (2008). doi:10.1126/science.1160575
Medline
11. J. D. Peterson, J. A. Goldberg, D. J. Surmeier, Adenosine A2a receptor antagonists attenuate
striatal adaptations following dopamine depletion. Neurobiol. Dis. 45, 409–416 (2012).
doi:10.1016/j.nbd.2011.08.030 Medline
12. T. Fieblinger, S. M. Graves, L. E. Sebel, C. Alcacer, J. L. Plotkin, T. S. Gertler, C. S. Chan,
M. Heiman, P. Greengard, M. A. Cenci, D. J. Surmeier, Cell type-specific plasticity of
striatal projection neurons in parkinsonism and L-DOPA-induced dyskinesia. Nat.
Commun. 5, 5316 (2014). doi:10.1038/ncomms6316 Medline
13. T. Klockgether, L. Turski, T. Honoré, Z. M. Zhang, D. M. Gash, R. Kurlan, J. T.
Greenamyre, The AMPA receptor antagonist NBQX has antiparkinsonian effects in
monoamine-depleted rats and MPTP-treated monkeys. Ann. Neurol. 30, 717–723 (1991).
doi:10.1002/ana.410300513 Medline
14. P. A. Löschmann, K. W. Lange, M. Kunow, K. J. Rettig, P. Jähnig, T. Honoré, L. Turski, H.
Wachtel, P. Jenner, C. D. Marsden, Synergism of the AMPA-antagonist NBQX and the
NMDA-antagonist CPP with L-dopa in models of Parkinson’s disease. J. Neural Transm.
Park. Dis. Dement. Sect. 3, 203–213 (1991). doi:10.1007/BF02259538 Medline
15. M. S. Starr, Glutamate/dopamine D1/D2 balance in the basal ganglia and its relevance to
Parkinson’s disease. Synapse 19, 264–293 (1995). doi:10.1002/syn.890190405 Medline
16. F. Blandini, R. H. Porter, J. T. Greenamyre, Glutamate and Parkinson’s disease. Mol.
Neurobiol. 12, 73–94 (1996). doi:10.1007/BF02740748 Medline
17. K. W. Lange, J. Kornhuber, P. Riederer, Dopamine/glutamate interactions in Parkinson’s
disease. Neurosci. Biobehav. Rev. 21, 393–400 (1997). doi:10.1016/S01497634(96)00043-7 Medline
18. K. A. Johnson, P. J. Conn, C. M. Niswender, Glutamate receptors as therapeutic targets for
Parkinson’s disease. CNS Neurol. Disord. Drug Targets 8, 475–491 (2009).
doi:10.2174/187152709789824606 Medline
19. F. Gardoni, M. Di Luca, Targeting glutamatergic synapses in Parkinson’s disease. Curr.
Opin. Pharmacol. 20, 24–28 (2015). doi:10.1016/j.coph.2014.10.011 Medline
20. K. Eggert, D. Squillacote, P. Barone, R. Dodel, R. Katzenschlager, M. Emre, A. J. Lees, O.
Rascol, W. Poewe, E. Tolosa, C. Trenkwalder, M. Onofrj, F. Stocchi, G. Nappi, V.
Kostic, J. Potic, E. Ruzicka, W. Oertel, Safety and efficacy of perampanel in advanced
Parkinson’s disease: A randomized, placebo-controlled study. Mov. Disord. 25, 896–905
(2010). doi:10.1002/mds.22974 Medline
21. O. Rascol, P. Barone, M. Behari, M. Emre, N. Giladi, C. W. Olanow, E. Ruzicka, F.
Bibbiani, D. Squillacote, A. Patten, E. Tolosa, Perampanel in Parkinson disease
fluctuations: A double-blind randomized trial with placebo and entacapone. Clin.
Neuropharmacol. 35, 15–20 (2012). doi:10.1097/WNF.0b013e318241520b Medline
22. A. Lees, S. Fahn, K. M. Eggert, J. Jankovic, A. Lang, F. Micheli, M. M. Mouradian, W. H.
Oertel, C. W. Olanow, W. Poewe, O. Rascol, E. Tolosa, D. Squillacote, D. Kumar,
Perampanel, an AMPA antagonist, found to have no benefit in reducing “off” time in
Parkinson’s disease. Mov. Disord. 27, 284–288 (2012). doi:10.1002/mds.23983 Medline
23. E. S. Boyden, F. Zhang, E. Bamberg, G. Nagel, K. Deisseroth, Millisecond-timescale,
genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268
(2005). doi:10.1038/nn1525 Medline
24. C. J. Magnus, P. H. Lee, D. Atasoy, H. H. Su, L. L. Looger, S. M. Sternson, Chemical and
genetic engineering of selective ion channel-ligand interactions. Science 333, 1292–1296
(2011). doi:10.1126/science.1206606 Medline
25. B. N. Armbruster, X. Li, M. H. Pausch, S. Herlitze, B. L. Roth, Evolving the lock to fit the
key to create a family of G protein-coupled receptors potently activated by an inert
ligand. Proc. Natl. Acad. Sci. U.S.A. 104, 5163–5168 (2007).
doi:10.1073/pnas.0700293104 Medline
26. E. Vardy, J. E. Robinson, C. Li, R. H. Olsen, J. F. DiBerto, P. M. Giguere, F. M. Sassano, X.
P. Huang, H. Zhu, D. J. Urban, K. L. White, J. E. Rittiner, N. A. Crowley, K. E. Pleil, C.
M. Mazzone, P. D. Mosier, J. Song, T. L. Kash, C. J. Malanga, M. J. Krashes, B. L. Roth,
A new DREADD facilitates the multiplexed chemogenetic interrogation of behavior.
Neuron 86, 936–946 (2015). doi:10.1016/j.neuron.2015.03.065 Medline
27. M. Banghart, K. Borges, E. Isacoff, D. Trauner, R. H. Kramer, Light-activated ion channels
for remote control of neuronal firing. Nat. Neurosci. 7, 1381–1386 (2004).
doi:10.1038/nn1356 Medline
28. M. Volgraf, P. Gorostiza, R. Numano, R. H. Kramer, E. Y. Isacoff, D. Trauner, Allosteric
control of an ionotropic glutamate receptor with an optical switch. Nat. Chem. Biol. 2,
47–52 (2006). doi:10.1038/nchembio756 Medline
29. J. Broichhagen, A. Damijonaitis, J. Levitz, K. R. Sokol, P. Leippe, D. Konrad, E. Y. Isacoff,
D. Trauner, Orthogonal optical control of a G protein-coupled receptor with a SNAPtethered photochromic ligand. ACS Cent. Sci. 1, 383–393 (2015).
doi:10.1021/acscentsci.5b00260
30. Y. I. Wu, D. Frey, O. I. Lungu, A. Jaehrig, I. Schlichting, B. Kuhlman, K. M. Hahn, A
genetically encoded photoactivatable Rac controls the motility of living cells. Nature
461, 104–108 (2009). doi:10.1038/nature08241 Medline
31. W. C. Lin, M. C. Tsai, C. M. Davenport, C. M. Smith, J. Veit, N. M. Wilson, H. Adesnik, R.
H. Kramer, A comprehensive optogenetic pharmacology toolkit for in vivo control of
GABAA receptors and synaptic inhibition. Neuron 88, 879–891 (2015).
doi:10.1016/j.neuron.2015.10.026 Medline
32. I. Ibañez-Tallon, H. Wen, J. M. Miwa, J. Xing, A. B. Tekinay, F. Ono, P. Brehm, N. Heintz,
Tethering naturally occurring peptide toxins for cell-autonomous modulation of ion
channels and receptors in vivo. Neuron 43, 305–311 (2004).
doi:10.1016/j.neuron.2004.07.015 Medline
33. S. Incontro, C. S. Asensio, R. H. Edwards, R. A. Nicoll, Efficient, complete deletion of
synaptic proteins using CRISPR. Neuron 83, 1051–1057 (2014).
doi:10.1016/j.neuron.2014.07.043 Medline
34. L. Tian, Y. Yang, L. M. Wysocki, A. C. Arnold, A. Hu, B. Ravichandran, S. M. Sternson, L.
L. Looger, L. D. Lavis, Selective esterase-ester pair for targeting small molecules with
cellular specificity. Proc. Natl. Acad. Sci. U.S.A. 109, 4756–4761 (2012).
doi:10.1073/pnas.1111943109 Medline
35. Y. Yang, P. Lee, S. M. Sternson, Cell type-specific pharmacology of NMDA receptors using
masked MK801. eLife 4, e10206 (2015). doi:10.7554/eLife.10206 Medline
36. O. I. Lungu, R. A. Hallett, E. J. Choi, M. J. Aiken, K. M. Hahn, B. Kuhlman, Designing
photoswitchable peptides using the AsLOV2 domain. Chem. Biol. 19, 507–517 (2012).
doi:10.1016/j.chembiol.2012.02.006 Medline
37. D. Schmidt, P. W. Tillberg, F. Chen, E. S. Boyden, A fully genetically encoded protein
architecture for optical control of peptide ligand concentration. Nat. Commun. 5, 3019
(2014). doi:10.1038/ncomms4019 Medline
38. G. V. Los, L. P. Encell, M. G. McDougall, D. D. Hartzell, N. Karassina, C. Zimprich, M. G.
Wood, R. Learish, R. F. Ohana, M. Urh, D. Simpson, J. Mendez, K. Zimmerman, P. Otto,
G. Vidugiris, J. Zhu, A. Darzins, D. H. Klaubert, R. F. Bulleit, K. V. Wood, HaloTag: A
novel protein labeling technology for cell imaging and protein analysis. ACS Chem. Biol.
3, 373–382 (2008). doi:10.1021/cb800025k Medline
39. F. Wang, J. Zhu, H. Zhu, Q. Zhang, Z. Lin, H. Hu, Bidirectional control of social hierarchy
by synaptic efficacy in medial prefrontal cortex. Science 334, 693–697 (2011).
doi:10.1126/science.1209951 Medline
40. J. Ohmori, M. Shimizu-Sasamata, M. Okada, S. Sakamoto, Novel AMPA receptor
antagonists: Synthesis and structure-activity relationships of 1-hydroxy-7-(1H-imidazol1-yl)-6-nitro-2,3(1H,4H)-quinoxalinedione and related compounds. J. Med. Chem. 39,
3971–3979 (1996). doi:10.1021/jm960387+ Medline
41. J. I. Shishikura, H. Inami, S. Sakamoto, M. Fuji, S. I. Tsukamoto, M. Sasamata, M. Okada,
“1,2,3,4-tetrahydroquinoxalinedione derivative” (Google Patents,
2006; www.google.com/patents/CA2199468C?cl=enGo).
42. N. Armstrong, E. Gouaux, Mechanisms for activation and antagonism of an AMPA-sensitive
glutamate receptor: Crystal structures of the GluR2 ligand binding core. Neuron 28, 165–
181 (2000). doi:10.1016/S0896-6273(00)00094-5 Medline
43. P. D. Davis, E. C. Crapps, "Selective and specific preparation of discrete PEG compounds"
(2011); www.freepatentsonline.com/7888536.html.
44. B. Zuber, I. Nikonenko, P. Klauser, D. Muller, J. Dubochet, The mammalian central nervous
synaptic cleft contains a high density of periodically organized complexes. Proc. Natl.
Acad. Sci. U.S.A. 102, 19192–19197 (2005). doi:10.1073/pnas.0509527102 Medline
45. T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter,
R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Looger, K. Svoboda, D. S. Kim,
Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300
(2013). doi:10.1038/nature12354 Medline
46. F. Tecuapetla, S. Matias, G. P. Dugue, Z. F. Mainen, R. M. Costa, Balanced activity in basal
ganglia projection pathways is critical for contraversive movements. Nat. Commun. 5,
4315 (2014). doi:10.1038/ncomms5315 Medline
47. J. Brown, W. X. Pan, J. T. Dudman, The inhibitory microcircuit of the substantia nigra
provides feedback gain control of the basal ganglia output. eLife 3, e02397 (2014).
doi:10.7554/eLife.02397 Medline
48. R. Iancu, P. Mohapel, P. Brundin, G. Paul, Behavioral characterization of a unilateral 6OHDA-lesion model of Parkinson’s disease in mice. Behav. Brain Res. 162, 1–10 (2005).
doi:10.1016/j.bbr.2005.02.023 Medline
49. M. A. Cenci, M. Lundblad, Ratings of L-DOPA-induced dyskinesia in the unilateral 6OHDA lesion model of Parkinson’s disease in rats and mice. Curr. Protoc. Neurosci.
Chapter 9, Unit 9 25 (2007); 10.1002/0471142301.ns0925s41.
50. S. Taverna, E. Ilijic, D. J. Surmeier, Recurrent collateral connections of striatal medium
spiny neurons are disrupted in models of Parkinson’s disease. J. Neurosci. 28, 5504–5512
(2008). doi:10.1523/JNEUROSCI.5493-07.2008 Medline
51. A. Pisani, G. Bernardi, J. Ding, D. J. Surmeier, Re-emergence of striatal cholinergic
interneurons in movement disorders. Trends Neurosci. 30, 545–553 (2007).
doi:10.1016/j.tins.2007.07.008 Medline
52. N. Maurice, M. Liberge, F. Jaouen, S. Ztaou, M. Hanini, J. Camon, K. Deisseroth, M.
Amalric, L. Kerkerian-Le Goff, C. Beurrier, Striatal cholinergic interneurons control
motor behavior and basal ganglia function in experimental parkinsonism. Cell Rep. 13,
657–666 (2015). doi:10.1016/j.celrep.2015.09.034 Medline
53. K. Haga, A. C. Kruse, H. Asada, T. Yurugi-Kobayashi, M. Shiroishi, C. Zhang, W. I. Weis,
T. Okada, B. K. Kobilka, T. Haga, T. Kobayashi, Structure of the human M2 muscarinic
acetylcholine receptor bound to an antagonist. Nature 482, 547–551 (2012).
doi:10.1038/nature10753 Medline
54. A. J. Irving, G. L. Collingridge, A characterization of muscarinic receptor-mediated
intracellular Ca2+ mobilization in cultured rat hippocampal neurones. J. Physiol. 511,
747–759 (1998). doi:10.1111/j.1469-7793.1998.747bg.x Medline
55. W. M. Pardridge, Molecular Trojan horses for blood-brain barrier drug delivery. Curr. Opin.
Pharmacol. 6, 494–500 (2006). doi:10.1016/j.coph.2006.06.001 Medline
56. L. A. Banaszynski, L. C. Chen, L. A. Maynard-Smith, A. G. Ooi, T. J. Wandless, A rapid,
reversible, and tunable method to regulate protein function in living cells using synthetic
small molecules. Cell 126, 995–1004 (2006). doi:10.1016/j.cell.2006.07.025 Medline
57. K. Nishimura, T. Fukagawa, H. Takisawa, T. Kakimoto, M. Kanemaki, An auxin-based
degron system for the rapid depletion of proteins in nonplant cells. Nat. Methods 6, 917–
922 (2009). doi:10.1038/nmeth.1401 Medline
58. M. Iwamoto, T. Björklund, C. Lundberg, D. Kirik, T. J. Wandless, A general chemical
method to regulate protein stability in the mammalian central nervous system. Chem.
Biol. 17, 981–988 (2010). doi:10.1016/j.chembiol.2010.07.009 Medline
59. G. Leriche, L. Chisholm, A. Wagner, Cleavable linkers in chemical biology. Bioorg. Med.
Chem. 20, 571–582 (2012). doi:10.1016/j.bmc.2011.07.048 Medline
60. A. Damijonaitis, J. Broichhagen, T. Urushima, K. Hüll, J. Nagpal, L. Laprell, M.
Schönberger, D. H. Woodmansee, A. Rafiq, M. P. Sumser, W. Kummer, A. Gottschalk,
D. Trauner, Azocholine enables optical control of alpha 7 nicotinic acetylcholine
receptors in neural networks. ACS Chem. Neurosci. 6, 701–707 (2015).
doi:10.1021/acschemneuro.5b00030 Medline
61. L. Laprell, E. Repak, V. Franckevicius, F. Hartrampf, J. Terhag, M. Hollmann, M. Sumser,
N. Rebola, D. A. DiGregorio, D. Trauner, Optical control of NMDA receptors with a
diffusible photoswitch. Nat. Commun. 6, 8076 (2015). doi:10.1038/ncomms9076 Medline
62. E. M. Sletten, C. R. Bertozzi, Bioorthogonal chemistry: Fishing for selectivity in a sea of
functionality. Angew. Chem. 48, 6974–6998 (2009). doi:10.1002/anie.200900942
Medline
63. M. S. Starr, B. S. Starr, Facilitation of dopamine D1 receptor- but not dopamine D1/D2
receptor-dependent locomotion by glutamate antagonists in the reserpine-treated mouse.
Eur. J. Pharmacol. 250, 239–246 (1993). doi:10.1016/0014-2999(93)90387-W Medline
64. M. S. Starr, B. S. Starr, Glutamate antagonists modify the motor stimulant actions of D1 and
D2 agonists in reserpine-treated mice in complex ways that are not predictive of their
interactions with the mixed D1/D2 agonist apomorphine. J. Neural Transm. Park. Dis.
Dement. Sect. 6, 215–226 (1993). doi:10.1007/BF02260924 Medline
65. R. Schwyzer, ACTH: A short introductory review. Ann. N.Y. Acad. Sci. 297, 3–26 (1977).
doi:10.1111/j.1749-6632.1977.tb41843.x Medline
66. P. S. Portoghese, Bivalent ligands and the message-address concept in the design of selective
opioid receptor antagonists. Trends Pharmacol. Sci. 10, 230–235 (1989).
doi:10.1016/0165-6147(89)90267-8 Medline
67. E. T. Mack, P. W. Snyder, R. Perez-Castillejos, B. Bilgiçer, D. T. Moustakas, M. J. Butte, G.
M. Whitesides, Dependence of avidity on linker length for a bivalent ligand-bivalent
receptor model system. J. Am. Chem. Soc. 134, 333–345 (2012). doi:10.1021/ja2073033
Medline
68. J. Kim, T. Zhao, R. S. Petralia, Y. Yu, H. Peng, E. Myers, J. C. Magee, mGRASP enables
mapping mammalian synaptic connectivity with light microscopy. Nat. Methods 9, 96–
102 (2011). doi:10.1038/nmeth.1784 Medline
69. V. Gradinaru, F. Zhang, C. Ramakrishnan, J. Mattis, R. Prakash, I. Diester, I. Goshen, K. R.
Thompson, K. Deisseroth, Molecular and cellular approaches for diversifying and
extending optogenetics. Cell 141, 154–165 (2010). doi:10.1016/j.cell.2010.02.037
Medline
70. M. Jinek, K. Chylinski, I. Fonfara, M. Hauer, J. A. Doudna, E. Charpentier, A programmable
dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–
821 (2012). doi:10.1126/science.1225829 Medline
71. A. C. Bishop, J. A. Ubersax, D. T. Petsch, D. P. Matheos, N. S. Gray, J. Blethrow, E.
Shimizu, J. Z. Tsien, P. G. Schultz, M. D. Rose, J. L. Wood, D. O. Morgan, K. M.
Shokat, A chemical switch for inhibitor-sensitive alleles of any protein kinase. Nature
407, 395–401 (2000). doi:10.1038/35030148 Medline
72. R. D. Airan, K. R. Thompson, L. E. Fenno, H. Bernstein, K. Deisseroth, Temporally precise
in vivo control of intracellular signalling. Nature 458, 1025–1029 (2009).
doi:10.1038/nature07926 Medline
73. G. Sandoz, J. Levitz, R. H. Kramer, E. Y. Isacoff, Optical control of endogenous proteins
with a photoswitchable conditional subunit reveals a role for TREK1 in GABAB
signaling. Neuron 74, 1005–1014 (2012). doi:10.1016/j.neuron.2012.04.026 Medline
74. T. Mikuni, J. Nishiyama, Y. Sun, N. Kamasawa, R. Yasuda, High-throughput, highresolution mapping of protein localization in mammalian brain by in vivo genome
editing. Cell 165, 1803–1817 (2016). doi:10.1016/j.cell.2016.04.044 Medline
75. F. Schnütgen, N. Doerflinger, C. Calléja, O. Wendling, P. Chambon, N. B. Ghyselinck, A
directional strategy for monitoring Cre-mediated recombination at the cellular level in the
mouse. Nat. Biotechnol. 21, 562–565 (2003). doi:10.1038/nbt811 Medline
76. D. A. Fortin, S. E. Tillo, G. Yang, J. C. Rah, J. B. Melander, S. Bai, O. Soler-Cedeño, M.
Qin, B. V. Zemelman, C. Guo, T. Mao, H. Zhong, Live imaging of endogenous PSD-95
using ENABLED: A conditional strategy to fluorescently label endogenous proteins. J.
Neurosci. 34, 16698–16712 (2014). doi:10.1523/JNEUROSCI.3888-14.2014 Medline
77. M. Heiman, A. Heilbut, V. Francardo, R. Kulicke, R. J. Fenster, E. D. Kolaczyk, J. P.
Mesirov, D. J. Surmeier, M. A. Cenci, P. Greengard, Molecular adaptations of striatal
spiny projection neurons during levodopa-induced dyskinesia. Proc. Natl. Acad. Sci.
U.S.A. 111, 4578–4583 (2014). doi:10.1073/pnas.1401819111 Medline
78. E. Koya, S. A. Golden, B. K. Harvey, D. H. Guez-Barber, A. Berkow, D. E. Simmons, J. M.
Bossert, S. G. Nair, J. L. Uejima, M. T. Marin, T. B. Mitchell, D. Farquhar, S. C. Ghosh,
B. J. Mattson, B. T. Hope, Targeted disruption of cocaine-activated nucleus accumbens
neurons prevents context-specific sensitization. Nat. Neurosci. 12, 1069–1073 (2009).
doi:10.1038/nn.2364 Medline
79. C. R. Cantor, P. R. Schimmel, Biophysical Chemistry: Part III: The Behavior of Biological
Macromolecules (Macmillan, 1980).
80. M. X. Mori, M. G. Erickson, D. T. Yue, Functional stoichiometry and local enrichment of
calmodulin interacting with Ca2+ channels. Science 304, 432–435 (2004).
doi:10.1126/science.1093490 Medline