bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Reduced expression of the psychiatric risk DLG2 (PSD93) impairs

hippocampal synaptic integration and plasticity

Simonas Griesius1, Cian O’Donnell2, Sophie Waldron3,6, Kerrie L. Thomas3,5, Dominic M.

Dwyer3,6, Lawrence S. Wilkinson3,4,6, Jeremy Hall3,4,5, Emma S. J. Robinson1, Jack R. Mellor1*

1 Centre for , School of Physiology, Pharmacology and Neuroscience,

University of Bristol, University Walk, Bristol BS8 1TD, UK

2 Computational Neuroscience Unit, School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics, University of Bristol, Bristol BS8 1UB, UK

3 Neuroscience and Mental Health Research Institute, 4 MRC Centre for Neuropsychiatric

Genetics and Genomics, Schools of 5 Medicine and 6 Psychology, Cardiff CF24 4HQ, UK

* Corresponding author: [email protected], +44 117 331 1944

Running title

Low dosage DLG2 impairs synaptic plasticity

Keywords

Schizophrenia, autism spectrum disorder, dendritic integration, plateau potential, muscarinic

M1 receptor, phenotype rescue

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Abstract

Background: Genetic variations indicating loss of function in the DLG2 gene have been

associated with markedly increased risk for schizophrenia, autism spectrum disorder, and

intellectual disability. DLG2 encodes the postsynaptic scaffolding DLG2 (PSD93) that

interacts with NMDA receptors, potassium channels, and cytoskeletal regulators but the net

impact of these interactions on synaptic plasticity, likely underpinning cognitive impairments

associated with these conditions, remains unclear. Methods: Hippocampal CA1 neuronal

excitability and synaptic function were investigated in a novel clinically relevant heterozygous

Dlg2+/- rat model using ex vivo patch-clamp electrophysiology, pharmacology, and

computational modelling. Results: Dlg2+/- rats had increased NMDA receptor-mediated

synaptic currents and, conversely, impaired associative long-term potentiation. This

impairment resulted from an increase in function leading to a decrease in

input resistance and reduced supra-linear dendritic integration during induction of associative

long-term potentiation. Enhancement of dendritic excitability by blockade of potassium

channels or activation of muscarinic M1 receptors with selective allosteric agonist 77-LH-28-

1 reduced the threshold for dendritic integration and 77-LH-28-1 rescued the associative long-

term potentiation impairment in the Dlg2+/- rats. Conclusions: Despite increasing synaptic

NMDA receptor currents, the combined impact of reduced DLG2 impairs synaptic integration

in dendrites resulting in disrupted associative synaptic plasticity. This biological phenotype can

be reversed by compound classes used clinically such as muscarinic M1 receptor agonists

and is therefore a potential target for therapeutic intervention.

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Introduction

Genetic variations at the DLG2 gene are linked to multiple psychiatric disorders including

schizophrenia(1, 2), bipolar(3, 4), autism spectrum(5-7), attention deficit hyperactivity(8),

intellectual disability(9, 10), and Parkinson’s disease(11, 12). This clinical evidence indicates

the significance of DLG2 in the aetiology of psychopathologies common to a broad range of

disorders and suggests core underlying mechanisms and biological phenotypes. Many of the

genetic variations are predicted to produce a loss of function for DLG2 in one copy of the gene

but the resulting changes in neuronal function are poorly understood(13-16).

DLG2 is a member of a family of membrane-associated (MAGUK)

enriched at synaptic locations that encodes the scaffolding protein PSD93 (also referred to as

DLG2 or Chapsyn-110). DLG2 interacts directly with a number of other proteins in the

of excitatory synapses, such as NMDA receptor (NMDAR) subunit

GluN2B(17-20), AMPA receptor auxiliary subunit stargazin(21), potassium channels

Kir2.3(22), Kir2.2(23) and Kv1.4(24), as well as proteins involved in potassium channel

palmitoylation, cell adhesion, microtubule assembly, and cell signalling, palmitoyltransferase

ZDHHC14(25), neuroligin1-3(17), Fyn(26, 27), ERK2(28), GKAP(29), and MAP1A(30).

Uniquely to the MAGUK family, DLG2 is targeted to the axon initial segment where it regulates

neuronal excitability via its interactions with potassium channels(25, 31). At a functional level,

homozygous Dlg2-/- knockout mice have altered glutamatergic synapse function(32-35) and

impaired long-term potentiation (LTP) in the hippocampus(33). These synaptic perturbations

could underlie the common cognitive psychopathologies of the psychiatric disorders

associated with DLG2. Indeed, Dlg2-/- mice have been shown to have impaired performance

in the object-location paired associates learning task(36). Homozygous Dlg2-/- mice also

exhibit increased grooming behaviour(35) and altered social interaction but without consistent

effects in negative valence tasks such as the open field test(35, 37).

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Impaired synaptic plasticity resulting from the loss of DLG2 is a potential biological phenotype

underpinning trans-diagnostic cognitive psychopathologies but the mechanism by which

reduced DLG2 expression leads to impaired synaptic plasticity is unclear. Furthermore,

mechanistic understanding for the impact of DLG2 loss may reveal new targets for therapeutic

intervention. Most animal models for DLG2 loss have employed full knockouts of the gene but

these do not accurately represent the heterozygous nature of DLG2 genetic variants in patient

populations and potentially engage compensatory expression by other MAGUK proteins(32)

(38) that is not present in heterozygous reduced gene dosage models (Fig 1A-C). Therefore,

here we investigate the combined impact of low gene dosage DLG2 on synaptic function,

neuronal excitability and morphology using a novel CRISPR-Cas9 engineered heterozygous

Dlg2+/- (het) rat model to understand the interactions that lead to impaired synaptic plasticity

and cognitive function.

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Methods and materials

Animals and husbandry

All procedures were carried out under local institutional guidelines, approved by the University

of Bristol Animal Welfare and Ethical Review Board, and in accordance with the UK Animals

(Scientific procedures) Act 1986. The experiments employed a novel Dlg2+/- heterozygous

rat model generated on a Hooded Long Evans background using CRISPR-Cas9 genomic

engineering that targeted a 7bp deletion to exon 5 of the rat Dlg2 gene, resulting in a

downstream frame shift in exon 6 and the production of a premature stop codon that led to a

reduction in Dlg2 protein levels in the hippocampus (Fig 1). Full details of the creation, quality

control and off-target assessment of the Dlg2+/- model can be found in Supplement 1. Male

Dlg2+/- rats were bred with wild type (wt) female rats, generating mixed litters of Dlg2+/- and

wt littermate offspring. The Dlg2+/- animals were viable and showed no signs of ill health, with

normal litter sizes containing the expected Mendelian ratio of positive to wt genotypes and

normal sex ratios, there were no effects in survival of the Dlg2+/- rats to adulthood and no

effects on general morbidity, including fertility, or mortality throughout the lifespan. Further

details of animal husbandry, breeding strategy and viability are described in Supplement 1.

Approximately equal numbers of each sex rats aged P50-75 were used, with experimenter

blind to genotype during experiments and data analysis.

Brain slice preparation, electrophysiology, protein quantification and computational modelling

These procedures are described in Supplement 1.

Statistical analysis

3-way and 2-way ANOVA, 3-way repeated measures ANOVA, Komolgorov-Smirnov test, as

well as paired and unpaired t-tests were used as appropriate, with full statistical results

available in Supplement 2. Genotype, sex, and dorsal-ventral aspects of the hippocampus, as

well as repeated measurements, were factored into all analyses, as appropriate. Genotype

was viewed as the primary output factor shown in the figures but where effects of other factors

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were found, the data are presented in Supplement 1 (Figs S6, S10, S12, S13, S15, S16).

Inclusion of animals in the analysis of a subset of experiments using multi-level general linear

mixed modelling did not affect the statistical results indicating that the major source of

variability arose between cells rather than animals. Therefore, cell was defined as the

experimental unit and we report numbers of cells and animals in figure legends. α = 0.05 was

applied for all tests, except the Kolmogorov-Smirnov test where α = 0.01 was applied. The

degrees of freedom, F, and P values are presented in the text, figures, and Supplement 2.

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Results

Dlg2+/- heterozygous knockout rats were generated by CRISP-Cas9 targeting of the Dlg2

gene (Supplement 1). In this model, DLG2 protein expression levels were reduced by ~50%

in hippocampus without effects on expression of other components of the postsynaptic

density, including the closely related MAGUK DLG4 (PSD95) and the GluN1 NMDAR subunit

(Fig 1A-C).

NMDAR currents

Protein-protein interaction studies have reported DLG2 to interact directly with NMDAR

subunits(17-19) and with AMPAR indirectly(21). Further, DLG2 has also been shown to affect

glutamatergic function in homozygous Dlg2-/- models, albeit with variable results in

AMPA/NMDA ratio(32-34). To investigate whether glutamatergic function was affected in

Dlg2+/- rats, the AMPA/NMDA ratio was measured in the CA1 region of hippocampal slices

(Fig 2A). Dlg2+/- hets had a reduced AMPA/NMDA ratio in the SC pathway, with no effect in

the TA pathway (Fig 2B-D). AMPAR-mediated miniature excitatory postsynaptic currents

(mEPSCs, Supplement 1 Fig S3) resulting from the activity of single synapses were recorded

to probe which component of the AMPA/NMDA ratio was affected. mEPSCs from synapses

on apical dendrites are more detectable than those from more distal synapses due to signal

attenuation(39) so mEPSCs are assumed to arise from synapses in the SC pathway. There

was no difference in the distributions of mEPSC amplitude, interevent interval, or decay tau

across genotype (Fig 2E-I). Paired-pulse facilitation, measured in the AMPA/NMDA ratio

experiment, was also not different across genotype in either pathway (Supplement 1 Fig S5).

Together, these results show no change in postsynaptic AMPAR function and presynaptic

glutamate release probability in the SC pathway. It follows that the AMPA/NMDA ratio effect

in the SC pathway was due to an increase in NMDAR function. This could result from either

an increase in NMDAR number or a change in subunit composition between GluN2A and

GluN2B. To test subunit composition, NMDAR currents were isolated (Fig 2J) and the

selective GluN2B negative allosteric modulator RO256981 was applied. RO256981

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decreased EPSC amplitude (Fig 2J-L) and increased the EPSC decay time in both the SC

and the TA pathways (Fig 2M-N). There was a trend toward a genotype x drug interaction in

the EPSC amplitude measurement in the SC pathway but no genotype x drug interaction in

the EPSC decay kinetics. Together, these results show similar NMDAR subunit composition

across genotype and therefore the enhancement in NMDAR function likely arises from

increased receptor numbers at SC synapses.

Synaptic integration and aLTP

NMDARs contribute to dendritic integration of spatiotemporally coherent inputs that can

summate supralinearily to drive associative LTP (aLTP) relevant to the learning of novel

representations(40-47). Given increased NMDAR function, it is predicted that dendritic

integration and plasticity would be facilitated in the Dlg2+/- hets. To test this, aLTP was

induced by stimulating SC and TA pathways simultaneously (Fig 3A-B). An additional

independent SC pathway was also stimulated as a negative control and a pathway check was

done to confirm pathway independence (Supplement 1 Fig S4). Despite the increased

NMDAR function in the Dlg2+/- hets, the induction protocol resulted in reduced aLTP in the

Dlg2+/- hets in both SC and TA test pathways but robust aLTP in the wts (Fig 3C-E). Critically,

baseline EPSC amplitudes were not different (Fig 3G), suggesting that all received

similar inputs. However, during induction (Fig 3F) the number of elicited action potential bursts

and single spikes was reduced in the Dlg2+/- hets (Fig 3H,J) and there was a trend suggesting

reduced overall depolarisation in response to synaptic stimulation (Fig 3I). Both spike number

and depolarisation during induction correlated with LTP in the SC pathway but not the TA

pathway (Supplement 1 Fig S7). There was no effect of genotype on the after-

hyperpolarisation (Fig 3K). This suggests that although synaptic receptor numbers are

increased in the Dlg2+/- hets, the integration of synaptic inputs from the SC and TA pathways

is impaired, reducing dendritic depolarisation and action potential spiking which are the drivers

of aLTP.

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To test the necessity of action potentials for aLTP, a paired theta burst LTP induction protocol

was used, where action potentials were driven by somatic current injection to bypass dendritic

integration, and spikes were paired with simultaneous SC pathway stimulation (Fig 3L). Under

these conditions, robust LTP was induced in the SC pathway in both genotypes, with the TA

pathway acting as negative control (Fig 3M-O). Similarly, when aLTP was tested using

baseline EPCSs doubled in amplitude, maximal LTP was induced and there was no effect of

genotype (Supplement 1 Figs S8&S9). This indicates that the hets are fundamentally able to

undergo LTP but their ability to integrate inputs is impaired.

To directly test synaptic integration, the number of activated synapses required to generate

supra-linear summation of EPSPs was assessed, which is a measure of the ability for

synapses to integrate within dendrites(44, 45, 47). To activate increasing numbers of

synapses, the SC pathway was stimulated with increasing intensity. The number of activated

synapses was measured by the slope of a single EPSP and the integration of synapses

assessed by the amplitude and duration of a compound summated EPSP (area under the

curve – AUC) elicited by repetitive high frequency synaptic stimulation (Fig 4A). As stimulation

intensity was increased the number of active synapses increased in a linear relationship with

the amplitude and durations of the summated compound EPSP until a “change point” was

reached (see methods) after which the relationship became supra-linear because the duration

of the compound EPSP increased (Fig 4B), indicative of activation of regenerative or plateau

potentials within the dendrites(44, 45, 47). The inhibition of these regenerative potentials by

D-APV demonstrated their dependence on NMDAR activation (Fig 4A-B). The change point

was increased in the Dlg2+/- hets (Fig 4B-C), indicating that het neurons required more

synaptic inputs to undergo the transition to supra-linear integration. Additionally, the maximum

duration of the compound EPSP as a ratio to the corresponding slope of the single EPSP was

reduced in the Dlg2+/- hets (Fig 4D). This again indicates that Dlg2+/- hets require more

synaptic input to integrate dendritic inputs and produce the supra-linear regenerative

potentials important for aLTP.

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Mechanism for impaired synaptic integration and plasticity

Reduced synaptic integration in dendrites could arise from multiple mechanisms. Based on

previous findings in CA1 pyramidal neurons the three most likely are: i) Reduced expression

of hyperpolarisation-activated cyclic nucleotide-gated (HCN) channels that regulate neuronal

excitability and contribute to dendritic integration(48-50), ii) Increased expression of small

conductance calcium-activated potassium (SK) channels that inhibit NMDARs at synapses,

reducing dendritic integration and LTP(51-53), iii) Reduced input resistance by increased

potassium channel expression particularly in dendritic locations to reduce dendritic integration

and LTP(44, 45, 54-58). Although blocking HCN channels produced robust effects on neuronal

excitability (including spiking, sag, and input resistance) there were no differential effects

across genotype (Fig 5A-F). There were also no genotype-specific effects on cellular

resonance or impedance that are directly dependent on HCN channels(59-63) (Supplement 1

Fig S11). As previously described, the SK channel blocker apamin produced an increase in

EPSP duration in the SC and TA pathways (Fig 5G-I) indicating increased NMDAR activation

during synaptic stimulation(51-53). However, the regulation of synaptic NMDAR function by

SK channels was similar between genotypes indicating no change in SK channel expression.

Therefore, differential HCN or SK channel function is unlikely to explain the difference in

synaptic integration between genotypes.

To assess input resistance, measurements were analysed from voltage clamp experiments

(using identical conditions to the LTP experiments in Fig 3) and in current clamp experiments.

In both these data sets Dlg2+/- hets had reduced input resistance (Fig 6A-D). This increase in

electrical leak in the Dlg2+/- hets is predicted to reduce cross-talk between synapses and their

integration leading to a reduced spike output but it is also expected to reduce the spike output

in response to somatic current injection. However, despite reduced input resistance in the

Dlg2+/- hets, there was no effect of genotype on spike output to current injection (rheobase)

(Fig 6E-F). This could be explained by a depolarised resting membrane potential (Fig 6G) and

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a trend towards hyperpolarised action potential spike threshold (Fig 6H) in the Dlg2+/- hets

indicating that smaller membrane potential depolarisations were required to initiate spikes.

There was no effect of genotype on spike half-width, maximum spike slope, spike amplitude,

or capacitance, and a slight decrease in latency to spike in the Dlg2+/- hets (Supplement 1

Fig S14).

Reduced input resistance in the Dlg2+/- hets could be explained via two mechanisms: i)

increased membrane area through greater dendritic branching and extent(45, 64) or ii)

increased membrane conductance, most likely caused by increased potassium channel

expression. To test the first mechanism, a subset of neurons from the intrinsic excitability

experiments were filled with neurobiotin to allow post hoc morphological analysis. Analysis of

these neurons revealed that het neurons were smaller than wt neurons (Fig 6I) and had

reduced dendritic branch number and total dendritic branch length but had similar mean

dendritic branch lengths (Fig 6J-L). Scholl analysis demonstrated that Dlg2+/- het neurons

had reduced dendritic arborisation overall, with the most striking differences in the basal and

proximal apical regions (Fig 6M). Contrary to the predicted neuronal size – input resistance

relationship, there was no correlation between total dendritic branch length and input

resistance (Fig 6N). Therefore, reduced neuronal arborisation in the Dlg2+/- hets cannot

explain the observed reduced input resistance and instead increased potassium channel

expression is the most likely explanation.

To explore which potassium channels were most likely to reduce input resistance and enhance

synaptic integration, a computational approach was employed where 6 representative

reconstructed pyramidal neurons (3 wt, 3 het) were populated with voltage dependent sodium

(NaV) and potassium (Ka, Kir, Kdr, and Km, A-type, inward rectifier, delayed rectifier and M-

type respectively) channels as well as a voltage independent leak conductance. Computer

simulations of these het reconstructed neurons showed consistently increased input

resistance relative to wt (Fig 7A-B). This result was expected from the reduced dendritic

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arborisation and supports the conclusion that the Dlg2+/- hets have increased ionic

conductances. DLG2 interacts with potassium inward rectifier Kir2.3(22) and Kir2.2(23) as well

as A-type Kv1.4(24) channels which therefore represented the most likely channels to

underpin decreased input resistance and increased synaptic integration. In order to probe the

effects of these channels on input resistance, the wt reconstruction was populated with either

Kir or Ka channels and channel conductances were scaled systematically over a ten-fold

range (Fig 7C). The inclusion of Ka channels reduced input resistance with greater channel

density causing greater reductions in input resistance. In contrast, the inclusion of Kir channels

had no effect across the conductance ranges explored (Fig 7C). These potassium channel

selective effects on input resistance map onto the voltage-dependent activation curves of

these channels (Supplement 1 Fig S17). Based on these results, an increase in Ka channel

expression or function is a good candidate to underly the decrease in input resistance in the

Dlg2+/- hets. Next, to test the effects of input resistance, as well as Ka and Kir channels, on

dendritic integration, a series of simulations were executed (Fig 7D). Dendrites were randomly

activated in a cumulative manner, with increasing numbers of proximal apical and tuft

dendrites being activated at any one time. Reminiscent of the dendritic integration experiment

in slices (Fig 4), change points were observed where the relation between activated dendrite

number and summated EPSP amplitude and duration transitioned from linear to supra-linear

(Fig 7E). This change point shifted leftward with increasing numbers of activated tuft dendrites,

indicating the facilitation of dendritic integration in the presence of more synaptic inputs.

Similar to slice experiments, simulation of proximal apical dendrite activation alone was also

able to generate supra-linear summation (Fig 7E). Following the inclusion of Ka channels into

the simulation, supra-linear summation was abolished (Fig 7F) whereas the inclusion of Kir

channels had no effect (Fig 7G) again reflecting the respective voltage-dependent activation

curves for Ka and Kir channels (Supplement 1 Fig S17). Doubling the leak conductance, which

approximately halved input resistance, considerably attenuated EPSP summation and shifted

the change point to the right indicating reduced synaptic integration and supra-linearity (Fig

7H). Of the potassium channels interacting with DLG2, these results suggest that A-type

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potassium channels are the most likely candidates upregulated in the Dlg2+/- hets to underly

the dendritic integration deficits.

Rescue of synaptic integration and plasticity

The aLTP, theta burst LTP, and dendritic integration results from Figures 2 and 3 suggest that,

given enough synaptic input, Dlg2+/- hets can express LTP despite their reduced input

resistance. It follows that by increasing input resistance in the Dlg2+/- hets, dendritic

integration and aLTP could be effectively rescued. Three separate methods to increase input

resistance were tested for their effectiveness in rescuing dendritic integration. The first was

the relatively broad-spectrum voltage-sensitive potassium channel blocker, 4-aminopyridine

(4-AP)(65), the second was the selective Kv1.3, Kv1.4 blocker CP339818(66) and the third

was activation of muscarinic M1 receptors(51, 67). 4-AP caused an increase in input

resistance, a reduction in the supra-linearity change point, a trend toward increased maximum

duration of the compound EPSP as a ratio to the corresponding slope of the single EPSP, and

a repolarisation in resting membrane potential (Fig 8A-E). The effects of 4-AP were not

genotype-specific, as there were no drug x genotype interactions. These results support the

computational modelling predictions that voltage-sensitive potassium channels attenuate

dendritic integration and blocking them facilitates it. Since DLG2 interacts with Kv1.4, the

selective blocker CP339818 was used to test whether the upregulation of these channels was

responsible for reduced dendritic integration. However, CP339818 had no effect on input

resistance or dendritic integration (Supplement 1 Fig S18) indicating that upregulation of these

specific A-type potassium channels does not underpin the reduction in dendritic integration in

the Dlg2+/- hets.

These results demonstrate, as predicted, that blocking a subset of potassium channels

activated around the resting membrane potential facilitates dendritic integration. However, due

to the considerable heterogeneity of potassium channels and their ability to compensate for

one another coupled with limited availability of selective pharmacological tools, identifying and

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targeting the precise channels that cause reduced input resistance in the Dlg2+/- hets is

challenging. An alternative approach, and one with greater therapeutic potential, is to rescue

the input resistance reduction indirectly, for example by activation of cholinergic muscarinic

M1 receptors that inhibit potassium channel function and increase dendritic excitability(44, 45,

54-58). Support for this approach was found using the highly selective muscarinic M1 receptor

allosteric partial agonist 77-LH-28-1(68) which increased input resistance, reduced the change

point, increased the maximum duration of the compound EPSP as a ratio to the corresponding

slope of the single EPSP, and depolarised the resting membrane potential (Fig 8F-J).

However, there were no significant drug x genotype interactions. Similar results were found

for the broad-spectrum non-hydrolysable acetylcholine analogue carbachol (Supplement 1 Fig

S19).

These results suggest that pharmacological enhancement of dendritic excitability and

integration may be sufficient to rescue aLTP in the Dlg2+/- hets. Therefore, the aLTP

experiment was repeated in the presence of 77-LH-28-1. This rescued aLTP in the Dlg2+/-

hets with robust aLTP in SC and TA pathways (Fig 9A-C). In addition, unlike in the absence

of 77-LH-28-1, there was no effect of genotype and no pathway x genotype interaction (Fig

9C), indicating 77-LH-28-1 selectively rescues aLTP in the Dlg2+/- hets. Importantly, baseline

EPSC amplitude did not differ among pathways and across genotype (Fig 9E), indicating that

the amount of synaptic input received was similar in all conditions. Analysis of the aLTP

induction phase revealed that 77-LH-28-1 rescued synaptic summation and the resulting

action potential spiking (Fig 9F-H) as well as plateau potential generation (Supplement 1 Fig

S20), with the genotypic differences for number of bursts, EPSP summation, and spike

number disappearing. Taken together, Figures 8&9 show 77-LH-28-1 reduced the threshold

for dendritic integration in both wts and Dlg2+/- hets but selectively facilitated aLTP in the

Dlg2+/- hets indicating induction of synaptic plasticity in the Dlg2+/- hets is more sensitive to

increased dendritic excitability and synaptic integration.

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Discussion

NMDAR currents are increased in the Dlg2+/- heterozygous rat model. Additionally, dendritic

arborisation is reduced. These observations would be expected to combine to enhance

neuronal excitability, dendritic integration and synaptic plasticity. Instead, the effects are

entirely offset, and indeed reversed, by a concomitant reduction in input resistance caused by

an increase in potassium channel expression, most likely A-type potassium channels. This

increase in electrical leak is the dominant effect, resulting in a final phenotype where dendritic

integration and aLTP are impaired. Crucially, dendritic integration can be rescued by

potassium channel block or activation of muscarinic M1 receptors, the latter of which can also

rescue synaptic plasticity. These phenotypes are potentially particularly relevant since the

Dlg2+/- rat model relates to human single copy genetic variants.

The direct interaction between DLG2 and GluN2b NMDAR subunits suggest the most

important effects of DLG2 perturbations are on NMDAR function – synaptic integration and

plasticity. However, previous studies on Dlg2-/- full knockout models have either reported no

changes in the AMPA/NMDA ratio or a reduction in the AMPA/NMDA ratio due to reduction in

AMPAR function(32-34). Here, AMPAR function was unchanged and instead we found an

unexpected increase in NMDAR currents, likely caused by increased expression. On its own,

this finding predicts enhanced aLTP, but we found the converse with aLTP impairment. This

is similar to previous reports in Dlg2-/- mice but with important differences. In homozygous

Dlg2-/- mice CA1 LTP was reduced in response to the strong TBS induction protocol(33), but

in our study using heterozygous Dlg2+/- rats TBS-induced LTP was normal. An LTP deficit

only became apparent in the Dlg2+/- model when neurons were required to integrate

converging inputs suggesting a more nuanced but potentially more behaviourally relevant

phenotype in the clinically relevant Dlg2+/- model. Furthermore, synaptic integration and the

initiation of non-linear dendritic events are key determinants of feature detection and selectivity

in neuronal networks(46, 69, 70) and a deficit in detecting events and giving appropriate

salience are important features of many psychiatric disorders(71).

15 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

The dichotomy between enhanced NMDA currents and reduced NMDAR function in Dlg2+/-

rats during aLTP highlights the dominant role played by changes to intrinsic neuronal

excitability; in this instance reduced input resistance caused by increases in potassium

channel function. Interestingly, in a Dlg2-/- full knockout model no changes in input resistance

were reported(72) highlighting again the importance of using clinically relevant models. In our

Dlg2+/- model this increase in potassium channel function does not appear to be caused by a

direct interaction with DLG2 but instead as a homeostatic regulatory mechanism perhaps to

compensate for increased synaptic currents. A similar compensatory mechanism is found in

other models of psychiatric disorders such as Fmr1-/y mice where changes in intrinsic

neuronal excitability dominate the resulting perturbations in network processing including

dendritic integration and synaptic plasticity(60, 73, 74). This raises the intriguing possibility

that genetic disruptions to synaptic function may generally cause homeostatic compensations

in intrinsic neuronal excitability that dominate neuronal function and present a common

biological phenotype across multiple psychiatric disorders(75).

We have demonstrated in this study that the compensatory mechanisms affecting neuronal

excitability can be ameliorated pharmacologically with the administration of selective agonists

such as 77-LH-28-1 rescuing impairments in synaptic integration and plasticity, a proof of

principle that may be applicable to other psychiatric disorder risk variants. For example, an

increase in input resistance due to the administration of 77-LH-28-1 could facilitate spike

backpropagation, potentially rescuing the plasticity impairment reported in the Cacna1c+/-

model of genetic vulnerability to schizophrenia(76). Highly selective muscarinic M1 receptor

agonists have efficacy clinically with negligible side effects(77-80) making them attractive

pharmaceutical tools. It remains to be seen whether behavioural impairments in DLG2 models

can be rescued using similar pharmacological strategies.

16 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A B C ) ) ) H H DLG2 DLG4 H GluN1 D D D P P 300 P A 300 300 A A G G G

o o o t t t

. . . m m *** m r r 200 r

o 200 200 o o n n n ( ( (

s s s e e e i i i t t t i i i s s 100 s

n 100 100 n n e e e d d d

d d d e e e t t t a a a r r 0 0 r 0 g g g e e e t t Wt Het Wt Het t Wt Het n n n I I I

17 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 1 DLG2 expression is reduced in Dlg2+/- hets, with no change in DLG4 or GluN1

expression. Expression of DLG2 (unpaired t-test: P < 0.001) (A), DLG4 (unpaired t-test: P =

0.784) (B), and GluN1 (unpaired t-test: P = 0.163) (C) in the hippocampus of Dlg2+/- het and

wt rats. Data from 23 (DLG2), 24 (DLG4), and 21 (GluN1) rats. Summary values depicted as

mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001 (unpaired t-test)

18 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A B C Data 3 D Data 3 Wt SC SC TA 8 20 100 pA o 300 Wt TA o i i t t * a a r 200 50 ms He2t0 S0C r

6 15 C Het TA C S 100 S P P E E

0 0 A A 4 10 D -100 0.50 0.55 0.60 0.65 0.70 0.5 0.6 0.7 D M 300 M N N / -200 -200 / A 200 A 2 5 P 200 P -300 M M A 100 A -400 -400 0 0 0 0 Wt Het Wt Het 50 -100 0.5 0.6 0.7 0.5 0.6 0.7 40 -200 -200 20 -300 5 5 E -400 -400 F 0 0 0 0 0.02 0.04 0.06 0.02 0.04 0.06 -20 -5 Wt-5 20 pA Het Wt Het 5 pA -40 100 ms -10 -10 10 ms -50 2.2 2.3 2.4 2.5 2.6 2.7 -15 -15 G H Histogram of m-2E0PSC intervaHlistogIram-2 0of mEPSC tau decay cum. frequency 100 100 100 y y y c c c n n n e e 75 75 e 75 u u u q Wt q Wt Wt q e e e r r r f f f

Het Het Het

e 50 e 50 e 50 v v v i i i t t t a a a l l l u u 25 25 u m m 25 m u u u C C C 0 0 0 0 25 50 75 100 0 10 20 30 40 0 20 40 Amplitude (pA) Interevent interval (s) Decay tau (ms) J SC TA SC TA

Ctrl Wt + RO256981 1 µM Ctrl Het 150 + D-APV 50 µM 150 150 150 + RO256981 1 µM (scaled) + RO256981 1 µM + D-APV 50 µM 100 100 100 + RO256981 1 µM (1s0c0aled) 50 pA 50 50 50 50 100 ms

0 0 0 0 0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4 K SC L TA M SC N TA o o i 400 400 i 2.0 4.5 t t a a r r

2 2

4.0 u u ) ) a 300 300 a 1.5 1.5 A A t t

p p ( ( y y

a a e e c c d d e e u u 200 200 1.0 1.0 d d t t

i i / / l l

p p 1 1

m m u u a a A A 100 100 0.5 t t 0.5

y y a a c c e e D 0 0 D 0.0 0.0 l l l l l l l l r M M r M M r M M r M M r M r M r M r M t µ µ t µ µ t µ µ t µ µ t µ t µ t µ t µ c µ µ c µ µ c µ µ c µ µ c c c c t 1 0 t 1 0 t 1 0 t 1 0 t 1 t 1 t 1 t 1 W 1 5 e 1 5 W 1 5 e 1 5 W 1 e 1 W 1 e 1 8 H 8 8 H 8 8 H 8 8 H 8 9 V 9 V 9 V 9 V 9 9 9 9 6 P 6 P 6 P 6 P 6 6 6 6 5 A 5 A 5 A 5 A 5 5 5 5 2 - 2 - 2 - 2 - 2 2 2 2 D D D D O + O + O + O + O O O O R R R R R R R R + + + + + + + +

19 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 2 Glutamatergic function is altered in the Dlg2+/- hets due to an increase in NMDAR

current, with no change in AMPAR current or GluN2b subunit expression. A) Schematic

representation of the hippocampal slice recording setup, with the CA3 removed and

stimulating electrodes in the stratum radiatum and in the stratum lacunosum moleculare. B)

AMPA/NMDA EPSC ratio example traces. The primarily AMPAR-mediated EPSCs were

recorded at a holding potential of -70 mV, whilst the AMPA- and NMDA-mediated EPSCs were

recorded at a holding potential of 40 mV. The AMPA/NMDA ratio was derived by dividing the

peak EPSC amplitude at -70 mV by the EPSC amplitude 45 ms after stimulation at 40 mV.

AMPA/NMDA EPSC ratio across genotype in the SC (3-way ANOVA: genotype main effect:

F 1, 68 = 4.791, P = 0.033) (C) and the TA (3-way ANOVA: genotype main effect: F 1, 34 = 0.583,

P = 0.452) (D) pathways. 68 cells from 32 animals for the SC data set and 34 cells from 16

animals for the TA data set. Example mEPSC traces (E) and mean mEPSCs (F) across

genotype. Cumulative frequency plots of amplitude (Kolmogorov–Smirnov Test: P = 0.028)

(G), interevent interval (Kolmogorov–Smirnov Test: P = 0.999) (H), and decay tau

(Kolmogorov–Smirnov Test: P = 0.067) (I). 45 cells from 14 animals. J) GluN2b example

EPSC traces. The traces following RO256981 1µM administration were also peak scaled to

better illustrate changes in decay kinetics. EPSC amplitude in the SC (3-way repeated-

measures ANOVA: drug main effect: F 2, 88 = 260.603, P < 0.001. Genotype x drug interaction:

F 2, 88 = 2.952, P = 0.057) (K) and TA (3-way repeated-measures ANOVA: drug main effect: F

2, 56 = 42.076, P < 0.001. Genotype x drug interaction: F 2, 56 = 1.738, P = 0.185) (L) pathways.

Decay tau 1 / decay tau 2 ratio in SC (3-way repeated-measures ANOVA: drug main effect: F

1, 45 = 9.715, P = 0.003. Genotype x drug interaction: F 1, 45 = 0.272, P = 0.605) (M) and TA (3-

way repeated-measures ANOVA: drug main effect: F 1, 27 = 3.410, P = 0.076. Genotype x drug

interaction: F 1, 27 = 0.831, P = 0.370) (N) pathways. 53 cells from 14 animals (SC), 38 cells

from animals 14 (TA). Summary values depicted as mean ± SEM. * P < 0.05, ** P < 0.01, ***

P < 0.001 (3-way ANOVA between subject effect)

20 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A B 100 Hz

Pre (SC) Pre (TA) x 3 Post Time 2 s

C Wt D Het 100 100 100 100 100 100 SCS Cctrl ctrl TATA SSCC SCS Cctrl ctrl TATA SSCC 0 0 0 0 0 0 1 2 3 4 -100 .5 .5 .5 .5 -100 -100 0 10000 pA0 -100 -100 -100 -200 20 -m20s0 Pre LT-P200 -200 -200 -200 E Post LTP *** -300500 -300 -300 -35000 -300 -300 500 -400 Wt SC-400 -400 -400 Het- 4SC00 -400 ) ) ) ) l l l l

r 400 r 400 r 400 Wt TA r 400 Het TA t t -500t -500 t c c c -500 c -500

Wt SC ctrl - 500 Het SC ctrl -500 % % % %

-600 300 -600 -600 300 -600 300 C C

C -C 600 -600 S S S S P P P P E E E 200 E 200 200 ( ( ( (

P P P P T T T T L L L 100 L 100 100

0 0 0

0 10 20 30 0 10 20 30 rl A C rl A C t T S t T S c t c t t Time (min) Time (min) C T C e e S W W S H H 20 t t 20 e F G W H 0 0 ) A 200

0.5 1.0 1.5 2.0 p

0.5 1.0 1.5 2.0 (

e

-20 ) l -20 d r u t

t 150 i c l

p

-40 % -40 m C a

S 100 C P

-60 S -60 E ( P

20 mV E

-40 -40 P e 250 ms T 50 n L i l e s a 0 -50 Wt-50 B Het rl A C rl A C 10 mV t T S t T S c t t c t t C C e e S W W S H H t t -60 50 ms -60 e W H 0.45 0.50 0.55 0.60 0.65 H0.45 0.50 0.55 ILT0P.6 0EPSP0 A.6U5 C (whoJle) KLTP EPSP AUC (whLole) 2.0 3 10 20 100 Hz )

) 10 # 8 # s

1.5 s V P

0.067 P V S S m 2 Pre (SC)

** m (

P *** ( P

6 0 E E C

C /

/ x 1

U 1.0 Post U # # A

A t

e 4 -10 s P P k r Time i

S 1 u H p P

B 0.5 A 2 s S E 2 -20

0.0 0 0 -30 Wt Het Wt Het Wt Het Wt Het

M TA SC N TA SC O 0 0 0 0 1 2 3 4 1 2 3 4 400 100 pA 1 2 3 4 1 2 3 4 400 1 1 1 1 1 1 1 1 400 .1 .1 .1 .1 .1 .1 .1 .1 ...... 400 ) ) 0 0 0 0 0 0 0 0 ) ) l 0 0 0 0 0 0 0 0 l l l r r r r

t 20 ms t t -200 -200 t

c -200 c -200 c c

300 Pre LTP 300 300 % % % %

Post LTP C C C C S S S S P P P 200 -400 -400 200 -400 -400 P 200 E E E E ( ( ( (

P P P P T T T 100 100 T

L L 100 L -600 -600 -600 -600 L

0 0 0 0 10 20 30 0 10 20 30 rl C rll C t S t S Time (min) Time (min) c c tt A T A e T W T H t t e W H

21 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 3 Attenuated aLTP in the Dlg2+/- hets despite normal TBS LTP. A) Schematic

representation of the hippocampal slice recording setup, with the CA3 removed and

stimulating electrodes in two separate areas of the stratum radiatum and in the stratum

lacunosum moleculare. B) aLTP induction protocol, where one SC pathway and one TA

pathway were tested and where the second SC pathway acted as a negative control. There

was no induced somatic depolarisation. This induction protocol was repeated thrice at an

interval of 10 seconds. aLTP over time in wts (C) and Dlg2+/- hets (D). Example traces pre-

and post-induction are displayed for the wt and het groups above their corresponding plots of

LTP over time. E) aLTP at the 25-30 minute mark post induction across genotype and pathway

(3-way repeated-measures ANOVA: pathway effect: F 2, 54 = 7.300, P = 0.002. Genotype main

effect: F 1, 27 = 15.687, P < 0.001. Genotype x pathway interaction: F 2, 54 = 7.376, P = 0.001).

F) Example traces of LTP induction, with example EPSPs following post hoc spike truncation.

G) Baseline EPSC amplitude across genotype (3-way repeated-measures ANOVA: pathway

effect: F 2, 54 = 1.227, P = 0.301. Genotype main effect: F 1, 27 = 0.553, P = 0.463. Genotype x

pathway interaction: F 2, 54 = 0.344, P = 0.711). Burst number (3-way ANOVA: genotype main

effect: F 1, 27 = 10.407, P = 0.003) (H), EPSP AUC (3-way ANOVA: genotype main effect: F 1,

27 = 3.63, P = 0.067) (I), total spike number (3-way ANOVA: genotype main effect: F 1, 27 =

15.877, P < 0.001) (J), and afterhyperpolarisation AUC (3-way ANOVA: genotype main effect:

F 1, 27 = 0.036, P = 0.85) (K) across genotype during LTP induction. 35 cells from 17 animals.

L) Theta burst LTP induction protocol, where the SC pathway was paired with somatic

depolarisation and where the TA pathway acted as a negative control. Theta burst LTP over

time in wts (M) and Dlg2+/- hets (N). O) Theta burst LTP at the 25-30 minute mark post

induction across genotype (3-way repeated-measures ANOVA: pathway effect: F 1, 33 =

18.979, P < 0.001. Genotype main effect: F 1, 33 = 0.04, P = 0.843. Genotype x pathway

interaction: F 1, 33 = 0.004, P = 0.950). 41 cells from 19 animals. Summary values depicted as

mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001 (3-way ANOVA between subject effect)

22 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Low stim A High stim Wt B Het 10 Wt Max stim intensity Het )

Sweep # P +D-APV 50 µM s

S Change point 100 100 V P m E (

d C n

U 5 u A o

p y a

10 mV m 50 50 c o e C 100 ms d

0 0 0 0 10 20 30 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Single EPSP rising subthreshold slope (mV/ms)

100 100 C D 30 1.0 ** *

o 0.8 i t t n 10 mV a i 50 20 r 50 o e

1 ms 10 mV p 0.6

p e o

100 ms l g s n

/

a 0.4 h 10 C C 0 0 U A 0.2 0.1010.1020.1030.1040.1050.1060.1070.1080.1090.110 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Single EPSP rising subthreshold slope Compound EPSP decay AUC 0 0.0 Wt Het Wt Het

23 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 4 Increased threshold for supra-linear dendritic integration in the Dlg2+/- hets in the SC

pathway. A) Example traces depicting a single EPSP followed by a compound EPSP at

increasing stimulation intensities (light to dark) over consecutive recording sweeps. The red

trace represents the response at maximal stimulation intensity in the presence of 50 µM D-

APV. The left inset depicts a zoomed-in view of the single EPSP, where rising subthreshold

slope was measured. The right inset depicts a zoomed-in view of the compound EPSP decay,

where the AUC was measured. B) Example relationships between the single EPSP rising

subthreshold slope and the compound EPSP decay AUC across genotype, with the change

points marked by black circles. Change point (EPSP rising subthreshold slope mV/mS) (3-

way ANOVA: genotype main effect: F 1, 34 = 12.625, P = 0.001) C) and AUC/slope ratio (3-way

ANOVA: genotype main effect: F 1, 34 = 8.003, P = 0.009) (D) across genotype. 38 cells from

23 animals. Summary values depicted as mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001

(3-way ANOVA between subject effect)

24 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

D´a´ta´ 7 ## 0 ) V m (

ZD7288 200109s1control 200109s1 ZD7288 200109sZ1D7288 200109s1 e -1 d

A u B

80 t i l Wt ctrl 10 p

60 m + ZD-7288 a 50 -2 50 50

g 0

a Het ctrl 40 0.5 1.0 1.5 2.0

S Wt 20 mV + ZD-7288 20 -10 + ZD-7288 -3 200 ms -150 -100 -50 0 0 0 0 0 -20 0.3 0.6 0.9 0.5 1.0Current step amplitude0 (.5pA) 1.0 0.5 1.0 -20 -30 10 -40 Data 7 Data 7 C D -40 0 Het Wt ctrl 0 + 0ZD.5 -7288 1.0 1.5 2.0 15 ) + ZD-7288 V -10 m (

Het ctrl e

# -1

d -20

e 10 u t k

+ ZD-7288 i i

l Wt ctrl 10 mV p p

S -30 m + ZD-7288 250 ms a 5 -2 g

a Het ctrl -40 S + ZD-7288 0 -3 0 100 200 -150 -100 -50 0 Current step amplitude (pA) Current step amplitude (pA)

delta input resistance delta input resistance E F G 15 40 250 15 SC TA

30 )

) Ctrl Wt l x 200 10 10 r a t

c + Apamin 100 nM m

%

% 20 ( + D-APV 50 µM (

i g R

150 5 5 a D S 10 2 mV 50 ms 100 0 0 0 0.50 0.55 0.60 0.65 0.70 Wt Het Wt Het 0.50 0.55 0.60 0.65 0.70

SC TA H SC I TA 15 150 150

10 ) ) ) ) 10 s s s s m m m 100 m 100 ( ( ( (

u u u u Ctrl Het a a a a t t t t

5 + Apamin 100 nM y y y y 5 a a a a c c c 50 c 50 + D-APV 50 µM e e e e D D D D

0 0 0.55 0.60 0.65 0.70 0 0 0.50 0.55 0.60 0.65 0.70 l l l l tr M M tr M M tr M M tr M M c n µ c n µ c n µ c n µ t 0 0 t 0 0 t 0 0 t 0 0 W 0 5 e 0 5 W 0 5 e 0 5 1 V H 1 V 1 V H 1 V in P in P in P in P m -A m -A m -A m -A a D a D a D a D p + p + p + p + A A A A + + + +

25 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 5 Unaltered HCN and SK channel function in the Dlg2+/- hets. A) Example voltage

traces in response to current steps (-150 to 250 pA) before and after application of ZD-7288

20 µM. B) Voltage traces in response to a hyperpolarising current step of -150 pA before and

after the application of ZD-7288 20 µM. Spike number (3-way repeated-measures ANOVA:

drug effect: F 1, 28 = 0.321, P = 0.576. Current step effect: F 10, 280 = 99.423, P < 0.001. Genotype

main effect: F 1, 28 = 0.272, P = 0.606. Drug x genotype interaction: F 1, 28 = 0.304, P = 0.586.

Drug x step interaction: F 10, 280 = 4.126, P < 0.001. Drug x step x genotype interaction: F 10, 280

= 0.134, P = 0.999) (C) and sag amplitude (3-way repeated-measures ANOVA: drug effect: F

1, 28 = 14.797, P = 0.001. Current step effect: F 6, 168 = 14.072, P < 0.001. Genotype main effect:

F 1, 28 = 0.03, P = 0.864. Drug x genotype interaction: F 1, 28 = 0.206, P = 0.654. Drug x step

interaction: F 10, 280 = 4.126, P < 0.001. Drug x step x genotype interaction: F 10, 280 = 0.564, P

= 0.758) (D) across genotype and before and after the application of ZD-7288 20 µM. Sag as

a percentage of max voltage deflection (3-way repeated-measures ANOVA: genotype main

effect: F 1, 50 = 0.182, P = 0.672) (E) and change in input resistance (3-way repeated-measures

ANOVA: genotype main effect: F 1, 37 = 0.351, P = 0.558) (F) following the application of ZD-

7288 20 µM. 37 cells from 18 animals. G) EPSPs before and after the application of apamin

100 nM. EPSP decay tau across genotype in SC (3-way repeated-measures ANOVA: drug

effect: F 2, 92 = 18.327, P < 0.001. Genotype main effect: F 1, 46 = 0.057, P = 0.812. Drug x

genotype interaction: F 2, 92 = 0.76, P = 0.471.) (H), and TA (3-way repeated-measures

ANOVA: drug effect: F 2, 86 = 29.346, P < 0.001. Genotype main effect: F 1, 43 = 0.391, P =

0.535. Genotype x drug interaction: F 2, 86 = 0.166, P = 0.847). (I) pathways. 55 cells from 17

animals (SC), 54 cells from animals 17 (TA). Summary values depicted as mean ± SEM. * P

< 0.05, ** P < 0.01, *** P < 0.001 (3-way ANOVA between subject effect)

26 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

RMP pooled aspect A B all experimentC1s0 D 15000 300 250 100 * 0 * )

50 pA 10 mV ) 0.5 1.0 1.5 2.0 m m 200 h 20 ms 250 ms h

O -10 200 Wt O

10000 M M ( ( 150

) 0 Het ) p -20 p 0.10 0.15 0.20 0.25 m Wt m a a 100 l l c c

5000 Het 100 -30 I ( V

( i -100 i 150 pA 50 R R -40 -100 250 ms 0 0 0 2 mV Wt Het 0.10 0.15 0.20 0.25 Wt Het-200 20 ms -300 Data 2 raw trace example -400 10E00 F RMP pooled aspect G RMP pooled aspect H RMP pooled aspect 900 -500 800 -30 -30 0.082 -600 700 Wt ** )

1 300 V

s 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 600 0.0 -400.5 1.0 1.5 -402.0 ) m

1 Het s 20 mV (

2 A 1 ) d

0 500 p 2 l ( V 1

0 100 ms -50 o -50 e 9

400 m 1

200 h ( s 1

9 s -50 a 1

300 e P b r o h 200 M -60 -60 t e

R h 100 100 e k R 100 pA i 0 -70 p -70 -1000.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 01.8000 m.9s1.0 S 0 -80 -80 Wt Het Wt Het Wt Het Wt L I J branch # K branch # branch # 15000 300 ) 150 )

*** m m µ ( µ

( *

h h t t g 200 g 10000 100 # n n

e e h l l

c h h n c a c r n n a B a r 5000

100 r 50 b

b l

a n t a o e T

0 0 M 0 Wt Het Wt Het Wt Het

M Sholl analysis genotype N total length vs Ri Het 20 200

* 2 15 R =0.015 # 150

) P=0.600 n m o Wt i h t c Het O e 10 100 M s ( r

i e t R n I 5 50

0 0 -200 0 200 400 600 800 0 5000 10000 Distance from soma (µm) Total branch length (µm)

100 μM

27 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 6 Reduced input resistance and dendritic arborisation in the Dlg2+/- hets. A) Current

traces in response to a 2 mV voltage step for wt and het. B) Input resistance (V clamp) across

genotype (3-way ANOVA: genotype main effect: F 1, 146 = 5.698, P = 0.018). 146 cells from 58

animals. C) Voltage traces in response to a -150 pA current step across genotype. D) Input

resistance (I clamp) across genotype (3-way ANOVA: genotype main effect: F 1, 78 = 4.209, P

= 0.044). E) Voltage deflections in response to a current step of equal size across genotype.

Rheobase (3-way ANOVA: genotype main effect: F 1, 90 = 0.011, P = 0.916) (F), resting

membrane potential (RMP) (3-way ANOVA: genotype main effect: F 1, 136 = 7.075, P = 0.009)

(G), and spike threshold (3-way ANOVA: genotype main effect: F 1, 89 = 3.105, P = 0.082) (H)

across genotype. ~136 cells from 38 animals. (I) Example morphological reconstructions

across genotype, cell bodies denoted with circles. Dendritic branch number (3-way ANOVA:

genotype main effect: F 1, 40 = 23.279, P < 0.001) (J), total dendritic branch length (3-way

ANOVA: genotype main effect: F 1, 40 = 7.002, P = 0.013) (K), and mean dendritic branch

length (3-way ANOVA: genotype main effect: F 1, 40 = 0.133, P = 0.718) (L) across genotype.

M) Scholl analysis across genotype (3-way ANOVA: genotype main effect: F 1, 31 = 5.532, P

= 0.025). 40 cells from 20 animals. N) Correlation between total dendritic branch length and

input resistance dataset (Pearson correlation: R2 = 0.015, P = 0.600). Summary values

depicted as mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001 (3-way ANOVA between

subject effect)

28 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Ri current step traces Ri current step traces Ri current step traces A -60B -60C -60

Wt Het -70 -70 -70

10 mV 10 mV -80 -80 -80 400 ms 400 ms -90 Ri summary Ri summary

300 -90 150 -90 0 1000 2000 03000 1000 2000 0 3000 1000 2000 3000 ) ) l r m t h c

O ) %

M 200 100 ( ( m

i i h R R

O

d d M e ( e t

t i a a l R l 100 50 u u m m i i S S

0 0 Wt Het k a a a a a r r r r r a i i i i i e K K K K K K K K K K L .5 1 .5 .0 .0 .5 1 .5 .0 .0 0 1 2 5 0 1 2 5 100 μm

D P5 P4 P2 P3 P1 P7

P6

T3 T1 T4 T2

100 μm -10 -10 -10 -10

-20 -20 -20 -20 E Leak F Leak + Ka G Leak + Kir H Leak x2 -30 -30 -30 -30 Change point -40 -40 -40 -40 10 mV -50 200 ms -50 -50 -50 -60 -60 -60 -60

-70 -70 -70 -70 1.0 1A.1rithm1.2etic 1s.u3m 1.4 1.0 1.1 1.2 1.3 1.4 1.0 1.1 1.2 1.3 1.4 1.0 1.1 1.2 1.3 1.4 Change point 10 10 10 10 0 tuft dends 8 1 tuft dend 8 8 8 ) ) ) 4 tuft dend ) s s s s V V V 6 6 V 6 6 m m m m ( ( ( (

C C C 4 4 C 4 4 U U U U A A A A 2 2 2 2

0 0 0 0 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 Proximal dend # Proximal dend # Proximal dend # Proximal dend #

29 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 7 With equal ionic conductance, simulated het neurons have higher input resistance.

Ka channels reduce input resistance and inhibit dendritic integration. A) Example

reconstructions used in simulations. B) Simulated voltage traces in response to a -150 pA

current step across genotype (top) and the corresponding input resistance (bottom). 6

neuronal reconstructions were populated with Ka, Kir, Km, Kdr, NaV channels. C) Voltage

traces in response to a -150 pA current step in a wt reconstruction populated either with the

Ka (pink) or the Kir (orange) channels (top). Channel conductance was scaled by a factor of

0.5-5 for each condition. Corresponding input resistance (bottom). D) Overview of the dendritic

integration simulations. Different proportions of proximal and tuft dendrites were activated in

a random, but consistent across experiments, sequence with 1 synapse per dendrite. AUC

was calculated to identify the change point to supralinearity, conditions were altered, and the

procedure was repeated. The first 7 proximal (P) (red) and first 4 tuft (T) (blue) activated

dendrites are shown on top of the wt reconstruction used in the dendritic integration

simulations, with the numbered dendrites indicating their relative activation sequence. EPSP

AUC as a function of different numbers of proximal and tuft dendrites and the corresponding

EPSPs under control conditions where only leak current is present (E), leak + Ka (F), leak +

kir (G), and leak x2 (H). Summary values depicted as mean ± SEM

30 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

100 100 A 50 50

10 mV 100 ms

100 100 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Wt Het +4AP 0.3 mM

50 50

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 B C D E 300 200 200

) 6000 d l d d d l l y y l l y y r ) t t t t t o

3000 o l i 3000 i o o i i r r r r r c h h h h

t a a a a s s s s c e e e e e

e e e ) 150 % 150 ) ) ) ) 300 r l n r n r ( n r n i i i

i s s r s s ) l l h % l l h h h t l 200 t ( t t t o n n n n m r

m m m i c / b / / b / b b t t t

o o o o u V u u V u c V V n a n n n n

i

s

%

r s s s f

f f

f

m ( m m m o 100

100 100 200 % o g o g o g o g e

e

(

e e e p n

n n n p i P d i p d d d i p i p i p l l l l e o s s o s s o o o R l i M o i l i i o l o l o l g r r

100 r r s s s h

s h s

h

h

R n

s / s s s P P P P a 50 50 e 100 50

e 100 e e S S S S r r r h r C P P P h h P h h C U T T E E T E T E ( ( ( ( A 0 0 0 0 l l rl l l l l l tr M tr M tr M tr M tr M tr M tr M tr M c c c c c c c c t m t m t m t m t m t m c m c m 3 e 3 3 e 3 3 e 3 t 3 t 3 W . . W . . W . . W . e . 0 H 0 0 H 0 0 H 0 0 H 0 P P P P P P P P A100 A A A 100 A A A A 4 4 4 4 4 4 4 4 + + + + + + + + F 50 50

100 100 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Wt Het + 77-LH-28-1 7 µM

50 50

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 G H I J 300 200 300 200 ) l d d d d l l l l y y r y y ) t t t t t l o o o i i o i i r r r c r r h h h h

t a a a a s s s s c e e e e

e e % e e

150 ) 150 ) ) ) ) r ( r n n l r n r n i i

i i s s s s r ) l l % h l h l h h l 200 200 t t t ( o t t n n n n r m

m i m m c / / b b / / b t b t t o

o o o u u V V u c u V V a n n n n n

i

r s

s

% s s f f

f

f

m m ( m m o

100

100

% o g o g e o g o g

e ( e

e p e

n n

n p n i d d P i p i p d d i p i p l l l l e o s s o o s s o o R l i i o o l l i M i o l o l g r r 100 100 r r s s s h h

s s h

h

R n / s s s s P P P P

a e e 50 50 e e S S S r S r r h r C P P h h P P h h C U T T E E T E T E ( ( ( ( A 0 0 0 0 l l l l r M r M rl rl r M r M rl l t µ t µ t M t M t µ t µ t M tr M c c c µ c µ c c c µ c µ t 7 t 7 t 7 t 7 t 7 t 7 t t e e e 7 e 7 W -1 H -1 W 1 1 W -1 H -1 W 1 1 8 8 - H - 8 8 - H - 2 2 8 8 2 2 8 8 - - -2 -2 - - -2 -2 H H H H H H H H -L -L L L -L -L L L 7 7 - - 7 7 - - 7 7 7 7 7 7 7 7 7 7 7 7 7 7 + + + + + + + +

31 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 8 Potassium channel block and M1 agonism lowers dendritic integration thresholds in

the Dlg2+/- hets. A) Example traces depicting a single EPSP followed by a compound EPSP

at increasing stimulation intensities (light to dark) over consecutive recording sweeps before

and after 4-aminopyridine 0.3 mM across genotype. Input resistance (3-way repeated-

measures ANOVA: drug effect: F 1, 23 = 8.608, P = 0.007, genotype x drug interaction: F 1, 23 =

0.418, P = 0.524) (B), change point (3-way repeated-measures ANOVA: drug effect: F 1, 14 =

8.422, P = 0.012, genotype x drug interaction: F 1, 14 = 0.042, P = 0.841) (C), AUC/slope (3-

way repeated-measures ANOVA: drug effect: F 1, 23 = 3.988, P = 0.058, genotype x drug

interaction: F 1, 23 = 1.570, P = 0.223) (D), and resting membrane potential (RMP) (3-way

repeated-measures ANOVA: drug effect: F 1, 24 = 57.899, P < 0.001, genotype x drug

interaction: F 1, 24 = 0.230, P = 0.636) (E) as percent of control before and after the after 4-

aminopyridine 0.3 mM across genotype. 32 cells from 15 animals. F) Example traces depicting

a single EPSP followed by a compound EPSP at increasing stimulation intensities (light to

dark) over consecutive recording sweeps before and after 77-LH-28-1 7 µM across genotype.

Input resistance (3-way repeated-measures ANOVA: drug effect: F 1, 21 = 4.12, P = 0.055,

genotype x drug interaction: F 1, 21 = 1.270, P = 0.273) (G), change point (3-way repeated-

measures ANOVA: drug effect: F 1, 16 = 6.879, P = 0.018, genotype x drug interaction: F 1, 16 =

0.645, P = 0.434) (H), AUC/slope (3-way repeated-measures ANOVA: drug effect: F 1, 17 =

38.074, P < 0.001, genotype x drug interaction: F 1, 17 = 0.152, P = 0.701) (I), and resting

membrane potential (RMP) (3-way repeated-measures ANOVA: drug effect: F 1, 21 = 8.931, P

= 0.007., genotype x drug interaction: F 1, 21 = 1.412, P = 0.248) (J) as percent of control before

and after the after 77-LH-28-1 7 µM. 29 cells from 15 animals. Summary values depicted as

mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001 (3-way ANOVA between subject effect)

32 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A Wt B Het SC ctrl TA SC SC ctrl TA SC 0 0 0 0 0 0 1 2 3 4 1 2 3 4 1 2 3 4 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 1 2 3 4 1 2 3 4 1 2 3 4 0 0 0 0Pre LTP 0 0 0 0 0 0 0 0 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 100 pA 0 0 0 0 0 0 0 0 0 0 0 0 -200 -200 Pos-t2 L0T0P -200 -200 20 ms -200

-400 -400 -400 7 µM 77-LH-28-1 -4007 µM 77-L-H4-0208-1 -400 C

500 500 500 -600 -600 -600 Wt SC -600 Het SC-600 -600 ) ) l ) ) l l l

r 400

r 400 r r 400

t Wt TA Het TA t t t c c

c c

Wt SC ctrl Het SC ctrl % % % %

300 300 300 C C C C S S S S P P P P E E E 200 E ( 200

( 200 ( (

P P P P T T T T L

100 L L 100 L 100

0 0 0 0 10 20 30 0 10 20 30 rl A C rl A C t T S t T S Time (min) c t c t t Time (min) C T C e e S W W S H H t t e D E W H 20 20 )

A 300

0 0 p (

0.5 1.0 1.5 2.0 0.5 1.0 1.5 2.0 e ) d l r u t t i -20 -20 c l

p 200 %

m C a

-40 -40 S C P S E ( P

100 E

-60 -60 P e T n L i

20 mV l e

250 ms s

-20 a 0 -20 B rl A C rl A C t T S t T S Wt c t t c t t C C e e S W W S H H -40 t t 10 mV Het e -40 W H 50 ms

-60 -60 0.45 0.50 0.55 0.60 0.65 0.45 0.50 0.55 0.60 0.65 F G H 2.0 4 10

) 8 # s #

1.5 3 V P P m S S (

P P

6 E E C

/ /

1.0 U 2 # #

A

t

e 4 s P k r i S u p P

B 0.5 1 S E 2

0.0 0 0 Wt Het Wt Het Wt Het

33 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 9 Muscarinic M1 agonism rescues aLTP in the Dlg2+/- hets. aLTP over time in wts (A)

and Dlg2+/- hets (B). Example traces pre- and post-induction are displayed for the wt and het

groups above their corresponding plots of LTP over time. C) aLTP at the 25-30 minute mark

post induction across genotype (3-way repeated-measures ANOVA: pathway effect: F 2, 32 =

12.169, P < 0.001. Genotype main effect: F 1, 16 = 0.176, P = 0.680. Genotype x pathway

interaction: F 2, 32 = 0.09, P = 0.914). D) Example traces of LTP induction, with example EPSPs

following post hoc spike truncation E) Baseline EPSC amplitude across genotype (3-way

repeated-measures ANOVA: pathway effect: F 2, 32 = 1.297, P = 0.287. Genotype main effect:

F 1, 16 < 0.001, P = 0.985. Genotype x pathway interaction: F 2, 32 = 0.043, P = 0.958). Burst

number (3-way ANOVA: genotype main effect: F 1, 16 = 0.001, P = 0.974) (F), EPSP AUC (3-

way ANOVA: genotype main effect: F 1, 16 = 0.100, P = 0.755) (G), and total spike number (3-

way ANOVA: genotype main effect: F 1, 16 = 0.029, P = 0.867) (H) across genotype during LTP

induction. Summary values depicted as mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001

(3-way ANOVA between subject effect)

34 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Acknowledgements

We thank Jenny Carter for coordinating the initial generation and breeding of the Dlg2+/- rat

line, Rachel Humphries for computational modelling discussions and Aleks Domanski and all

members of the Robinson and Mellor groups for general discussions. We also thank Hannah

Jones and Estela Michail for their input in the study of morphology. The authors gratefully

acknowledge funding from Medical Research Council (UK) (CO’D, PhD studentship to SG),

Biotechnology and Biological Science Research Council (UK) (JRM), Wellcome Trust (UK)

(JRM, PhD studentship to SW). The Dlg2+/- rats were generated as part of a Wellcome Trust

Strategic Award ‘DEFINE’ (JH and LSW) and the Wellcome Trust Strategic Award and the

Neuroscience and Mental Health Research Institute, Cardiff University, UK provided core

support.

The data in this study was presented as poster and abstract at FENS (2020) and BAP (2021).

35 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Disclosures

The authors declare no conflict of interest. ER has received research funding from Boehringer

Ingelheim, Eli Lilly, Pfizer, Small Pharma Ltd. and MSD, and DD has received research funding

from Eli Lilly, but these companies were not associated with the data presented in this

manuscript.

36 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.02.454736; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

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