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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 gene 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 Synaptic Plasticity, 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 protein 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 potassium channel 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 locus 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 guanylate kinase (MAGUK) proteins
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
postsynaptic density 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).
3 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.
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.
6 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.
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 neurons 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.
8 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.
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
11 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.
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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