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Oxytocin improves behavioral and electrophysiological deficits in a novel Shank3-deficient rat

  1. Hala Harony-Nicolas
  2. Maya Kay
  3. Johann du Hoffmann
  4. Matthew E Klein
  5. Ozlem Bozdagi-Gunal
  6. Mohammed Riad
  7. Nikolaos P Daskalakis
  8. Sankalp Sonar
  9. Pablo E Castillo
  10. Patrick R Hof
  11. Matthew L Shapiro
  12. Mark G Baxter
  13. Shlomo Wagner
  14. Joseph D Buxbaum  Is a corresponding author
  1. Icahn School of Medicine at Mount Sinai, United States
  2. University of Haifa, Israel
  3. Albert Einstein College of Medicine, United States
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Cite this article as: eLife 2017;6:e18904 doi: 10.7554/eLife.18904

Abstract

Mutations in the synaptic gene SHANK3 lead to a neurodevelopmental disorder known as Phelan-McDermid syndrome (PMS). PMS is a relatively common monogenic and highly penetrant cause of autism spectrum disorder (ASD) and intellectual disability (ID), and frequently presents with attention deficits. The underlying neurobiology of PMS is not fully known and pharmacological treatments for core symptoms do not exist. Here, we report the production and characterization of a Shank3-deficient rat model of PMS, with a genetic alteration similar to a human SHANK3 mutation. We show that Shank3-deficient rats exhibit impaired long-term social recognition memory and attention, and reduced synaptic plasticity in the hippocampal-medial prefrontal cortex pathway. These deficits were attenuated with oxytocin treatment. The effect of oxytocin on reversing non-social attention deficits is a particularly novel finding, and the results implicate an oxytocinergic contribution in this genetically defined subtype of ASD and ID, suggesting an individualized therapeutic approach for PMS.

https://doi.org/10.7554/eLife.18904.001

eLife digest

Phelan-McDermid syndrome is a genetic disorder on the autism spectrum that affects how children develop in several ways, with additional symptoms including attention deficits, delays in learning to speak and motor problems. This syndrome is known to be caused by changes in a single gene known as SHANK3 that disrupt communication between brain cells involved in memory and learning. However, we do not know how these changes relate to the symptoms of Phelan-McDermid syndrome.

To understand how genetic changes affect the human brain, researchers often carry out experiments in rats or other small rodents because they have brains that are similar to ours. Harony-Nicolas et al. genetically modified rats to carry changes in the SHANK3 gene that reflect those found in people with Phelan-McDermid syndrome. The rats had disabilities related to those seen in Phelan-McDermid syndrome, including limits in long-term social memory and reduced attention span. They also showed changes in the connections between important parts of the brain. Therefore, studying these rats could help us to understand the link between molecular and cellular changes in the brain and how they affect people with Phelan-McDermid syndrome, and associated symptoms.

Previous studies have shown that a chemical called oxytocin, which is naturally produced by the brain, helps to form bonds between individuals and can cause positive feelings in relation to certain memories. Harony-Nicolas et al. found treating the rats with oxytocin boosted social memory and led to improvements in other symptoms of Phelan-McDermid syndrome. In particular, oxytocin treatment helped to increase the attention span of the rats.

Rats with changes in the SHANK3 gene will be a useful tool for future research into Phelan-McDermid syndrome, particularly in understanding how it affects the connections between brain cells, leading to the symptoms of Phelan-McDermid syndrome. A future challenge will be to find out whether oxytocin has the potential to be developed into a therapy to treat Phelan-McDermid syndrome in humans. Since there is evidence that SHANK3 is involved in other forms of autism, these rats will also be useful in understanding the other ways in which autism can develop.

https://doi.org/10.7554/eLife.18904.002

Introduction

Phelan McDermid syndrome (PMS) is a neurodevelopmental disorder characterized by intellectual disability (ID), absent or delayed speech, neonatal hypotonia, attention deficits and autism spectrum disorder (ASD). The neurobehavioral manifestations of PMS are caused by heterozygous mutations/deletions in the SHANK3 gene leading to a reduced expression of the SHANK3 protein. Shank3 is a key structural component of the glutamatergic postsynaptic density (PSD), and interacts with glutamate receptors and cytoskeletal elements to regulate glutamate signaling and synaptic plasticity (Kreienkamp, 2008). It has been estimated that more than 80% of individuals with PMS meet ASD diagnostic criteria and that ~0.5–1% of ASD cases, 1–2% of ID cases, and up to 2% of cases with both ASD and ID harbor a SHANK3 mutation, which makes it one of the more common single locus causes of ASD and ID (Gong et al., 2012; Soorya et al., 2013; Leblond et al., 2014). Despite its prevalence, PMS is less well studied than other single locus genetic disorders such as Fragile X or Rett syndromes. To date, no pharmaceutical compounds targeting core symptoms of PMS are available. To address this lack of effective therapeutics, several mouse lines with distinct Shank3 gene mutations have been developed to help understand the neurobiology of the syndrome and as a means of ultimately developing and assessing potential therapeutics (Bozdagi et al., 2010; Peça et al., 2011; Wang et al., 2011; Yang et al., 2012; Kouser et al., 2013; Kloth et al., 2015; Bidinosti et al., 2016; Mei et al., 2016; Wang et al., 2016). The various Shank3-deficient mouse models have displayed PMS and ASD-related behavioral phenotypes including impaired social behavior, increased repetitive behaviors, and motor deficits, as well as altered synaptic transmission and neuronal morphology in the brain (Bozdagi et al., 2010; Peça et al., 2011; Wang et al., 2011; Yang et al., 2012; Kouser et al., 2013; Drapeau et al., 2014Wang et al., 2016). Recently, the translational relevance of these mouse models has been highlighted by our observation that the hormone IGF-1 improves motor and synaptic deficits observed in a Shank3-deficient mouse line (Bozdagi et al., 2013), a result which directly led to a safety and preliminary efficacy clinical trial of IGF-1 in children with PMS (Kolevzon, 2014a).

Here, we report the generation and characterization of the Shank3-deficient rat, representing a novel genetic model of PMS, which demonstrates clear PMS-related behavioral and electrophysiological phenotypes that can be ameliorated by intracerebroventricular (ICV) oxytocin administration.

Results

Production and developmental phenotyping of the Shank3-deficient rat model

Founder Shank3-deficient rats were generated using zinc-finger nucleases (ZFN) technology, targeting exon 6 of the ankyrin repeat domain. This domain was targeted because five patients had been described with mutations in it (Figure 1A) (Durand et al., 2007; Moessner et al., 2007Hamdan et al., 2011; Boccuto et al., 2013; Yuen et al., 2015). Interestingly, the predicted truncated protein generated upon ZFN targeting of the rat Shank3 gene is quite similar to one of the human mutations that have been described (Hamdan et al., 2011) (Figure 1A, middle sequence). In rat, this mutation leads to a significant reduction in the number of Shank3 transcripts (Figure 1—figure supplement 1A) and reduces expression levels of the full-length Shank3a protein (Figure 1B and Figure 1—figure supplement 1B). We also observed that the levels of the PSD scaffolding protein Homer1 are decreased in the Shank3-deficient rats (Figure 1—figure supplement 1C), consistent with changes in the PSD and with well-replicated findings from Shank3-deficient mice. We noted that, at weaning, there was a modest reduction in the number of homozygous knockout (KO) animals from Heterozygous (Het) x Het matings, compared to expectation (292:555:200, corresponding to ratios of 0.53:1:0.36).

Figure 1 with 1 supplement see all
Gene-targeting of the rat Shank3 gene.

(A) The top schematic shows the Shank3 protein domains [ankyrin repeats domain (ANK), a Src homology 3 (SH3) domain, a PDZ domain, and a sterile α-motif (SAM) domain] and indicates the published de novo mutations observed within the ANK domain in PMS patients (light blue text, top schematic) (Durand et al., 2007; Moessner et al., 2007; Hamdan et al., 2011; Boccuto et al., 2013; Yuen et al., 2015). The 68 bp deletion that we introduced in exon 6 of the Shank3 rat gene (middle schematic) produces a stop codon in exon six that truncates the Shank3 protein. In a PMS patient, the c.601–1G>A mutation in intron 5 of the SHANK3 gene abolishes the normal acceptor site and leads to utilization of a cryptic acceptor site introducing a premature stop codon in exon 6 (red lines, bottom schematic), which also results in a similar truncated Shank3 protein (Hamdan et al., 2011). Lower-case letters, genomic sequence; upper-case letters, amino acids; *, premature stop codons. (B) Western blot showing anti-Shank3 staining, using antibodies targeted against the SH3 domain.

https://doi.org/10.7554/eLife.18904.003

To evaluate the impact of Shank3-deficiency in rats, basic developmental processes as well as early motor and sensory function were assessed. These assessments were carried out as previously described (Brunner et al., 2015) and included weight, stomach milk content, body temperature, locomotion, grooming, rearing, pup ultrasonic vocalization, geotaxis, and the righting reflex. We found no genotype-related deficits in these basic developmental or functional processes. In addition, when tested on the elevated plus maze, Shank3-Het and KO rats did not exhibit increased anxiety-like behaviors (See Materials and methods for details and Supplementary file 1 for results). These results enabled us to examine more complex PMS and ASD-relevant behaviors.

Social memory deficits in Shank3-deficient rats

We first measured preference for a social stimulus versus an object (Figure 2—figure supplement 1A), as well as juvenile social play (Figure 2—figure supplement 1B) and adult dyadic social interactions (Supplementary file 1) in freely interacting animals. We found no differences between Shank3-deficient and wildtype (WT) rats in any of these measures of social behavior or social preference.

Next, we used social habituation-dishabituation and social discrimination (SD) tests to examine social recognition memory (SRM). In the SD experiments, the subject rat was ultimately tested in its ability to discriminate between familiar and unfamiliar juvenile rats simultaneously introduced to it for 5 min. We used two versions of the SD test, in order to examine both short- and long-term SRM (with short and long referring to the interval between social memory acquisition and recall). To assess short-term SRM, the SD test was performed 30 min after the subject encountered the familiar rat for 5 min (Figure 2A), while, in the more challenging long-term SRM, which requires longer exposure to the social stimulus (Gur et al., 2014), the same test was performed 24 hr after a 1 hr encounter with the familiar rats (Figure 2B). We found that Shank3-deficiency does not impair short-term SRM as shown by the comparable findings between WT and Shank3-deficient rats on the social habituation-dishabituation (Figure 2—figure supplement 1C) and short-term SD tests (Figure 2A). In contrast, in two independent cohorts, we found that Shank3-Het and KO rats were unable to discriminate between novel and familiar social stimuli in the long-term SD test (Figure 2B) as they spent equal time investigating both the familiar and novel social stimuli. Notably, total investigation time (toward both familiar and unfamiliar rats) did not differ across genotypes in any of the SD tests (Figure 2—figure supplement 1D), indicating there is not a decreased interest in social exploration. Moreover, the fact that the Shank3-Het and KO rats performed well on the short-term SD test and were able to perceive and remember their conspecifics, even when only given 5 min for the first interaction, also ruled out perceptual deficits.

Figure 2 with 1 supplement see all
Shank3-deficient rats exhibit deficits in social memory.

(A–B) Above each figure are schematics of the short- and long-term social discrimination (SD) paradigms. The examined adult subject is shown in white, and the juveniles are shown in black and grey. Bar plots show behavior in short-term (WT, n = 12; Het, n = 13; KO, n = 9) and long-term (WT, n = 31; Het, n = 37: KO, n = 25) SD tests. For long-term SD, similar results were observed in two independent cohorts, therefore the results were pooled and presented here as a single cohort. Bars ± SEM at left show test subjects average investigation time of a familiar and unfamiliar juvenile rat. The light overlaid gray lines in A and B show the corresponding individual subject data that comprise each bar. Right scatter plots, presented with mean ± SEM, show the ratio of the investigation time (RDI= (Unfamiliar-Familiar)/(Unfamiliar+Familiar) for individual subjects. (C) Above the figure is a schematic of the long-term object location memory paradigm. The same plotting conventions as bar plots in A and B are used, but here they quantify investigation times of an object (WT, n = 12; Het, n = 12; KO, n = 12) in a novel or familiar location. (D) Above, Contextual fear conditioning paradigm schematic. Scatter plots (mean ± SEM) represent percent time freezing during retrieval of a 1-day-old conditioned fear memory (WT, n = 12; Het, n = 12; KO, n = 6). *, p<0.05, **, p<0.01, ***, p<0.001; see Supplementary file 1 for detailed statistical results.

https://doi.org/10.7554/eLife.18904.005

To determine whether this observed impairment is selective to social memory or if it also involves more general memory processes, we tested the rats on two long-term non-social memory paradigms that, similarly to the SD test, are known to be hippocampal-dependent, specifically, the object location memory test and the contextual fear conditioning memory test. In contrast to the impaired behavior in the long-term SD test, Shank3-Het and KO rats performed similarly to their WT littermates in the object location memory and contextual fear conditioning memory tests (Figure 2C and D). These results indicate that Shank3 deficiency selectively impairs long-term social memory, but leaves intact both short-term social memory and non-social long-term memory.

Attention deficits in Shank3-deficient rats

Attention deficits are often associated with PMS. Thus, we assessed performance in the attentionally demanding 5-choice serial reaction time (5-CSRT) task in which rats must respond quickly to briefly presented light cues (Figure 3) (Mar et al., 2013). This task requires training the rats in stages where the duration of the light stimulus is slowly decreased from 32 to 1 s by halving the stimulus duration across sessions once performance criteria are met (i.e. accuracy rates higher than 80% for two consecutive days with omission rates lower than 20%). Shank3-Het and KO rats learned the task and were able to reach baseline, similar to WT controls. However, both the Shank3 Het and KO rats had lower accuracy and lower omission rates, when compared to WT rats, even after extensive training. Moreover, after reaching baseline criterion Shank3-deficient rats did not maintain even this level of performance across the 10-day test period, during which they performed significantly fewer correct trials (Figure 3A), made more errors (Figure 3B), and exhibited higher omission rates than WT rats (Figure 3C). Even on trials with a correct response, Shank3-deficient rats responded more slowly and with more variable latencies than WT rats (Figure 3D).

Figure 3 with 1 supplement see all
Shank3-deficient rats exhibit deficits in attention.

(A) Traces and clouds indicate mean percentage of trials with a correct response ± SEM (WT, n = 10; Het, n = 13; KO, n = 12) across 10 5-CSRT sessions. The right side in all panels is the cross-rat median (dot) and middle quartiles (vertical lines). (B) Traces represent mean percentage of trials where an incorrect response was made. (C) Mean percentage of trials with no cued response. (D) Average reaction times on trials with a correct response. Results were observed in two independent cohorts; therefore, the results were pooled.

https://doi.org/10.7554/eLife.18904.007

Slow, inaccurate and omitted responses to very brief visual stimuli are commonly interpreted as reflecting an attention deficit (Robbins, 2002). While changes in accuracy might also be attributed to deficits in sensory perception, we excluded this possibility by carrying out studies with less bright visual cues and Shank3-deficient rats performed at WT levels (not shown). It was only when the duration of the light cues was shortened that the deficits were manifested, which indicates impaired vigilance and/or spatial attention. Furthermore, these deficits were not due to decreased motivation for food, because the latency of Shank3-deficient rats to collect reward after a correct response was similar to WT rats (Figure 3—figure supplement 1A), as was task performance when light cues were of a longer duration (Figure 3—figure supplement 1B). In summary, these results indicate that Shank3-deficient rats are impaired in an attentionally demanding task, which, when considered together with the deficits in long-term social memory, indicates this model demonstrates face validity for some features of PMS.

Synaptic plasticity deficits in Shank3-deficient rats

Memory deficits, while not considered core symptoms of autism, have been associated with ASD (Boucher et al., 2012). Both impaired working (Barendse et al., 2013) and episodic memory (Maister et al., 2013) have been observed in human subjects with ASD, which has been attributed to aberrant connectivity of the hippocampus and medial prefrontal cortex (mPFC) (Ben Shalom, 2003). The behavioral deficits we observe in Shank3-deficient rats are consistent with dysfunction in these circuits. The hippocampus and mPFC are both important for SRM (Watson et al., 2012; Harvey and Lepage, 2014; Jacobs and Tsien, 2014). Moreover, performance in the 5-CSRT task depends on mPFC function (Rogers et al., 2001) and attention, working memory, and decision-making require intact hippocampal-prefrontal functional connectivity (Jones and Wilson, 2005). We therefore evaluated the effect of Shank3 deficiency on synaptic function and plasticity in hippocampal-PFC circuitry. Extracellular field excitatory postsynaptic potential (fESPs) recordings at Schaffer collateral-CA1 synapses were similar between genotypes, with no differences in paired-pulse facilitation (Supplementary file 1) or the input-output relationship (Figure 4—figure supplement 1). These results suggest that basal synaptic transmission is generally intact in Shank3-deficient rats.

We found, however, in independent cohorts, that plasticity at these synapses was not intact. Long-term potentiation (LTP) induced by high-frequency stimulation (HFS) was reduced in both Shank3-Het and KO rats (Figures 4A and 6A, and Figure 6—figure supplement 1A), while mGluR-dependent long-term depression (LTD) was reduced only in KO rats (Figure 4B).

Figure 4 with 1 supplement see all
Synaptic plasticity is impaired in Shank3-deficient rats.

(A) High-frequency stimulation (HFS, arrow)-induced long-term potentiation (LTP) at hippocampal Schaffer collateral-CA1 synapses (n = 6 rats/genotype, 1–2 slices per rat). (B) Long-term depression induced by the mGluR agonist DHPG (50 µM, 5 min) is indicated by the horizontal line (n = 6 rats/genotype, six slices per rat). (C) HFS-induced LTP in the prelimbic PFC after stimulation of ipsilateral CA1 in ventral hippocampus of intact anesthetized WT (n = 5), Shank3 Het (n = 6) and KO (n = 6) rats. Inset shows a schematic of the target location of the stimulating and recording electrodes in vivo. Summary data are presented as mean ± SD. *p<0.05, ***p<0.001; See Supplementary file 1 for detailed statistical results.

https://doi.org/10.7554/eLife.18904.009

Innervation of the mPFC by the hippocampus (Marquis et al., 2006) is important for attention and working memory, both of which we have shown here are impaired in Shank3-deficient rats. We therefore assessed hippocampal-PFC synaptic transmission in vivo by stimulating hippocampal CA1/subicular regions and recording fEPSPs in the prelimbic area of the PFC in anesthetized rats. We found that LTP was reduced in both Shank3-Het and KO rats (Figure 4C). We also observed that there were no genotype associated differences in the input-output relationship of evoked local field potentials in coronal PFC slices, which demonstrates that these changes were specific to hippocampal-prefrontal circuitry (Supplementary file 1). In summary, these results suggest that Shank3-deficiency impairs plasticity in both the projections from hippocampus to the PFC and within intrinsic hippocampal circuits.

Oxytocin improves behavior and synaptic plasticity deficits in Shank3-deficient rats

Oxytocin has a central role in SRM formation (Ferguson et al., 2000; Gur et al., 2014) and hence we reasoned that it may underly some of the altered behaviors we observed; in addition and more broadly, oxytocin modulates mammalian social behavior and may be dysregulated in ASD (Harony and Wagner, 2010). To determine whether the behavioral deficits we observed in Shank3-deficient rats could be improved with a pharmacological intervention strategy, we tested Shank3-deficient rats on long-term SD and 5-CSRT tasks following an injection of either oxytocin or saline into the left lateral ventricle. We observed that oxytocin improved both the long-term social memory and attention deficits in Shank3-Het and KO rats (Figure 5A and B). Notably, in WT animals, oxytocin had no effect on long-term SRM (Figure 5—figure supplement 1A) or 5-CSRT task performance (Figure 5—figure supplement 1B).

Figure 5 with 1 supplement see all
Oxytocin improves social memory and attentional deficits in Shank3-deficient rats.

Above each figure is a schematic depicting the sequence of oxytocin administration and behavioral testing on the long-term social discrimination (SD) paradigm (in A) or 5-CSRT task (in B). In A, the test subject is shown in white and the juveniles are shown in black and grey. (A) Left bars (± SEM) show the test subject’s average investigation time of a familiar and unfamiliar juvenile rat on long-term SD test following treatment with oxytocin or vehicle for Shank3 Het (n = 15) and KO (n = 8) rats. The light overlaid gray lines show the corresponding individual subject data that comprise each bar. Bars on right show the ratio of the investigation time (RDI= (Unfamiliar-Familiar)/(Unfamiliar+Familiar) for individual subjects with the light overlaid gray lines representing the corresponding individual subject data. (B) Bars (± SEM) represent the percentage of correct (left), omitted (middle), and incorrect (right) trials in saline (solid bars) and oxytocin (open bars) of Shank3 Het (n = 7) and KO (n = 6) rats. Color conventions are identical to those used in Figure 3A–C. The light overlaid gray lines show the corresponding individual subject data that went into each bar. *p<0.05, **p<0.01, ***p<0.001; See Supplementary file 1 for detailed statistical results.

https://doi.org/10.7554/eLife.18904.011

Since oxytocin reversed the behavioral deficits in Shank3-deficient rats and has been previously shown to enhance the induction of synaptic plasticity in several systems (Benelli et al., 1995; Tomizawa et al., 2003; Fang et al., 2008; Ninan, 2011; Lin et al., 2012; Gur et al., 2014), we also examined the effect of oxytocin on LTP both in vitro and in vivo. As previously reported, in acute hippocampal slices derived from WT rats, oxytocin enhanced LTP induction after a weak stimulation of one train of 100 Hz pulses (Tomizawa et al., 2003; Lin et al., 2012) but we did not observe this oxytocin-dependent enhancement in Shank3-deficient rats (Figure 6—figure supplement 1A). In WT slices, oxytocin had no effect on LTP induced by stronger stimulation (4 × 100 Hz stimulation trains), but it greatly enhanced LTP in slices prepared from Shank3-deficient rats (in independent cohorts, Figure 6A and Figure 6—figure supplement 1B). In vivo, oxytocin also reversed the impaired LTP at hippocampal-prefrontal synapses in Shank3-deficient rats (Figure 6B). These results indicate that oxytocin treatment restores LTP induction at hippocampal and hippocampal-prefrontal synapses in Shank3-deficient rats and is consistent with a mechanism whereby deficits in synaptic plasticity across hippocampal-prefrontal circuitry underly PMS-relevant behavioral deficits we observed in these animals.

Figure 6 with 1 supplement see all
Oxytocin improves synaptic plasticity deficits in Shank3-deficient rats.

(A) Traces depict Hippocampal HFS-induced LTP (4 × 100 Hz) in WT and Shank3-deficient rats (n = 4 rats/genotype, six slices per rat). Application of 1 µM of oxytocin is indicated by the horizontal line. (B) LTP in the hippocampal to prefrontal synaptic pathway recorded in vivo in WT (n = 3), Shank3 Het (n = 4) and KO (n = 4) rats. Oxytocin (2 ng) or saline was administered in the lateral ventricle 5 min before LTP induction. ***p<0.001. See Supplementary file 1 for detailed statistical results.

https://doi.org/10.7554/eLife.18904.013

Discussion

Deficits in attention and the presence of ASD-related behaviors are common in PMS. In our genetically modified rat model of PMS, we found that Shank3 deficiency impairs social memory and attention. These impairments are accompanied by attenuated synaptic plasticity within the hippocampus and in the monosynaptic pathway connecting the hippocampus to the PFC. Hippocampal synaptic plasticity deficits have also been reported in Shank3-mouse models and were associated with impairments in actin cytoskeleton remodeling and with changes in the levels of glutamatergic receptors and other PSD scaffolding components including Homer, which we also found to be decreased in the Shank3-deficient rat (Figure 1—figure supplement 1C) (Bozdagi et al., 2010; Wang et al., 2011; Duffney et al., 2013; Kouser et al., 2013; Wang et al., 2016). The fact that long-term social memory was selectively impaired, in contrast to more general memory processes, may reflect the complexity of the information involved in social memory (Adolphs, 2010; Wiley, 2013), which may require more elaborate synaptic mechanisms than simpler forms of memory. These results may also relate to previous findings that correlate ASD-associated episodic memory deficits with the complexity of the memoranda (Lind, 2010), which suggests that sub-optimal thresholds for synaptic plasticity interfere with the ability of complex stimuli, such as social stimuli, to activate memory formation. Deficits in attentionally demanding tasks, like the 5-CSRT task, may also result from blunted synaptic plasticity, where brief events must be rapidly encoded and reliably stored by neural circuits to promote appropriate and timely behavior.

It is interesting, and important, to compare findings in different rodent models of PMS and relate them to symptoms observed in patients. In particular, while there is some overlap between the social communicative deficits observed in PMS and those observed in what is considered more classical autism, there are important differences. In contrast to the more typical conception of ASD (whether accurate or not), PMS-associated ASD is not associated with a social aversion or lack of social approach (Soorya et al., 2013; Kolevzon, 2014b). A recent study of functional neuroimaging showed that differential fMRI changes in response to social versus non-social sounds are preserved in PMS, in contrast to studies of idiopathic autism (iASD) (Wang et al., 2016). These findings, together with the fact that not all individuals with PMS are diagnosed with ASD, indicate that animal models for PMS should not necessarily present with social behavioral deficits and imply that behavioral phenotypic diversity in PMS patients may reflect additional processes.

This may explain some of the discrepancies that have been reported across distinct Shank3-mouse models (Harony-Nicolas et al., 2015), and those that we report here in the Shank3-deficient rat. These discrepancies could be attributed to (1) mutations/deletions in existing rodent models were targeted to different parts of the Shank3 gene, (2) varying genetic background, (3) different behavioral paradigms, (4) varying age and sex, (5) a focus on heterozygotes or knockouts, or other factors. Beyond these methodological issues, from an evolutionary perspective, mice and rats are separated by millions of years, which likely explain many of the observed discrepancies in behavioral repertoires between the two species. Just as mice and rats differ, so do mice and rats greatly differ from human, and thus one should be careful not to overly anthropomorphize these model systems or look for perfect overlap across species.

Further investigation of the mechanisms underlying synaptic plasticity deficits and the molecular pathways affected by Shank3 mutation and the consequent synaptic changes in rat and mouse Shank3 models will likely provide new targets for therapeutic treatments and allow comparison between two different species, thus providing more reliable molecular targets for future drug development studies. Although all the mutations that have been studied, including the one we introduced to the rat model, lead to the deletion of the longest Shank3 isoform, most leave intact other shorter isoforms, whose role is still unclear. Because many patients lack the entire SHANK3 gene, understanding the role of different Shank3 isoforms is of great interest, and contrasting existing rodent models will be useful in clarifying this important question.

To date, treatment strategies for PMS are non-specific and do not address key issues of cognition, language, motor development, etc. There are approaches that are applied in PMS that are adopted from the general population. For example, when ASD is present, one might make use of behavioral interventions (Kolevzon et al., 2014b), but these strategies need to be improved and designed for the specific needs of PMS patients. Recently, the field has begun to translate basic neurobiological findings gleaned from rodent models into promising pharmacological treatments for a host of genetic disorders such as Fragile X syndrome, Tuberous sclerosis, Rett syndrome, and PMS (Bear et al., 2004; Ehninger and Silva, 2009; Tropea et al., 2009; Kolevzon et al., 2014a).

The peptide oxytocin is a powerful regulator of mammalian social behavior, which has been shown to improve various aspects of social cognition and social behavior in human and non-human primates, by increasing social memory, enhancing social reward, and modulating social attention (Chang et al., 2012; Guastella et al., 2012; Parr et al., 2016). Oxytocin has been also studied in clinical trials as a potential therapeutic for iASD-associated social impairments, yet these efforts have led to equivocal results (Guastella et al., 2016). Hitherto, the effect of oxytocin has not been investigated in PMS or in animal models of PMS, and its effect on non-social ASD and PMS-associated deficits has not been evaluated. Given the evidence for a key role for oxytocin in SRM, we tested this compound and observed important effects on both behavioral and electrophysiological deficits. Interestingly, an ameliorative effect of oxytocin treatment on autism-like behaviors has recently been reported in other genetically defined mouse models of ASD (Tyzio et al., 2014; Peñagarikano et al., 2015).

Our results show, for the first time to our knowledge, a beneficial effect of oxytocin on attention to non-social stimuli. Social and attention deficits are often co-morbid in PMS (Soorya et al., 2013; Kolevzon, 2014b), which is perhaps reflective of a shared etiology and may explain why oxytocin improved both deficit types in Shank3 deficient rats. The ameliorative effect of oxytocin treatment on the long-term social memory, attention and synaptic plasticity deficits in Shank3-deficient rats, support a mechanism whereby deficits in synaptic plasticity across hippocampal-prefrontal circuitry may underly the behavioral deficits we observed. These results also imply that exogenous oxytocin administration might have therapeutic potential in human PMS patients.

In our view, genetically modified rat models are especially valuable for behavioral and functional studies. They have several species-specific advantages over mouse models, including a more complex behavioral repertoire and larger brains that readily facilitate high-density electrophysiological recordings. Moreover, rats remain the primary choice of the pharmaceutical industry for studying the pharmacokinetic properties of novel drugs that may have therapeutic potential in human. Our production of a Shank3-deficient rat model, which demonstrates both construct and face validity, will pave the way for future studies that investigate the mode by which Shank3 mutations alter brain activity during behavior and to further study the effects of oxytocin and other potential therapeutics for PMS. Our findings open new avenues of research to study the effect of Shank3-deficiency on the development and function of oxytocin neurons. Future studies should investigate if Shank3-deficiency affects hypothalamic processes that regulate oxytocin production and secretion (Brownstein et al., 1980) or whether it perturbs pathways further downstream. Additionally, it would be important to determine if oxytocin treatments during critical developmental windows could ameliorate PMS-associated behavioral deficits, and whether other forms of ASD, defined either etiologically or by the presence of specific biomarkers, may show such broad response to oxytocin. These, and other experiments, would support the use of oxytocinergic agonists for multiple forms of ASD, including additional genetically defined forms of ASD.

Materials and methods

Generation of Shank3-deficient rats

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Shank3-deficient rats were generated using zinc-finger nucleases (ZFN) on the outbred Sprague-Dawley background. The design, cloning, and validation of the ZFN, as well as embryonic microinjection and screening for positive founder rats was performed by SAGE Labs (Boyertown, PA). Briefly, sixteen pairs of ZFN were designed targeting exons 4, 5 and 6 of the Shank3 gene to disrupt the Shank3 ANK domain. These pairs were assembled by PCR and sub cloned into the pZFN expression plasmid. ZFN were then transfected into the rat C6 cell line and tested for disruption activity using the Surveyor endonuclease (CEL-1) assay (Kulinski et al., 2000). The best performing ZFN pair GACGCCCCTGTACCATAGTgccctaGGGGGCGGGGATGCC (recognizing the GACGCCCCTGTACCATAGT and the GGGGGCGGGGATGCC sequences located between 130163213–130163231 and 130163238–130163252, respectively, in the Shank3 gene (NCBI reference sequence NC_005106.3), were used for embryo microinjection. Positive Sprague-Dawley founder animals were mated to produce F1 heterozygous breeder pairs. Genomic DNA sequencing using the ZFN Primer F (GGAGGGACTCAATGCAGAAA) identified a 68 bp deletion in exon six leading to a premature stop codon, as shown in Figure 1A.

Animal care and husbandry

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All rats were kept under veterinary supervision in a 12 hr light/dark cycle at 22 ± 2°C. Unless otherwise indicated, animals were pair-caged with food and water available ad libitum. All animal procedures were approved by the Institutional Animal Care and Use Committees at the Icahn School of Medicine at Mount Sinai, the University of Haifa, and the Albert Einstein College of Medicine.

Animal selection and inclusion criteria

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Age-matched males were used in all tests unless otherwise noted. Minimal group sample sizes were decided in advance of the described experiments based on the standards in the field and using on-line sample size/power calculation tools, specifically the ‘biomath’ online tool; (http://biomath.info/power/). Any animals excluded from analysis or testing due to poor performance or for any other reason are noted in the appropriate Methods section.

Molecular analysis

Isolation of postsynaptic density (PSD)

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PFC tissues were dissected from 8 week old rats as previously described (Spijker, 2011). PSDs were prepared as follows; tissue samples from WT and Shank3 KO rats were homogenized in 2-[4-(2-hydroxyethyl)piperazin-1-yl]-ethanesulfonic acid (HEPES)-A containing 4 mM HEPES, pH 7.4, 0.32 M sucrose, Protease Inhibitor Cocktail and PhoSTOP Phosphatase Inhibitor Cocktail (both from Roche). Nuclear fractions were then precipitated by centrifuging twice at 700 g for 15 min, and the resulting supernatants were further centrifuged at 21,000 g for 15 min. The precipitates were re-suspended in HEPES-B containing 4 mM HEPES, pH 7.4, Protease Inhibitor Cocktail and PhoSTOP Phosphatase Inhibitor Cocktail, homogenized and rotated at 4°C for 1 hr. These lysates were centrifuged at 32,000 g for 20 min and washed twice with HEPES-C containing 50 mM HEPES, pH 7.4, 0.5% Triton X-100, Protease Inhibitor Cocktail and PhoSTOP Phosphatase Inhibitor Cocktail. Finally, postsynaptic density fractions were resuspended in HEPES-C containing 1.8% sodium dodecyl sulfate (SDS) and 2.5 M urea. Protein concentrations were determined using the Pierce BCA protein assay.

Immunoblotting

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The immunoblotting experiments, presented in Figure 1B and Figure 1—figure supplement 1B and C, were performed using a standard protocol (Bozdagi et al., 2010). Briefly, 10 μg of each PSD fraction were loaded onto a 4–12% SDS-polyacrylamide gel electrophoresis (PAGE gel, Invitrogen; Carlsbad, CA), which was then transferred to a polyvinylidene fluoride membrane for immunoblotting. For Shank3 protein, beta III tubulin, and Homer detection, anti-Shank3 (1:100, NeuroMab; clone N69/46, BRID:AB_10698031 targeted against amino acids 840–857), anti-Shank3 (1:100, NeuroMab; clone N367/62, BRID:AB_2315920 targeted against the SH3 domain), anti beta III tubulin (1:2000, Abcam; ab18207, RRID:AB_444319), and Homer-1b/c (1:100, Santa Cruz; sc-25271, RRID:AB_675652) antibodies were used. HRP-conjugated anti-rabbit (1:5,000), BRID:AB_2337910 HRP-conjugated anti-mouse antibodies (1:5,000), BRID:AB_2340031 were purchased from Jackson ImmunoResearch Laboratories (West Grove, PA). ECL substrate (Pierce; Thermo Scientific, Rockford, IL) or SuperSignal West Femto (Thermo Scientific, Rockford, IL) substrates were used to produce the signal that was detected on a G:Box Chemi-XT4 GENESys imager (Syngene; Cambridge, UK). Blots were quantified using the software GeneTools (SynGene, version 4.02).

RNA sequencing and analysis

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RNA was extracted from mPFC tissues from 8 week old WT and Shank3-KO littermate rats using the RNeasy Mini Kit (Qiagen, CA) according to the manufacturer's instructions. One µg was then used for the preparation of the seq library using TruSeq mRNA Seq Kit supplied by Illumina (Cat # RS-122–2001), following the manufacturer’s instruction. Before starting the seq library preparation, a Poly-A-based mRNA enrichment step was carried out and cDNA was synthesized and used for library preparation using the Illumina TruSeqTM RNA sample preparation kit as previously described (Tariq et al., 2011), except for the following steps: adapter-ligated DNA fragments were size-selected by gel-free size selection using appropriate concentration of SPRI AMPure beads to get an average 200 bp peak size in adaptor-ligated DNA. The size selected adaptor-ligated DNA fragments were amplified by LM-PCR. Then, Illumina recommended 6 bp barcode bases were introduced at one end of the adaptors during PCR amplification step. The amplified PCR products were then purified with SPRI AMPure XP magnetic beads to get the final RNA-seq library, which was used for high-throughput RNA-seq. Size and concentration of the RNA-seq library were measured by Bioanalyzer and Qubit.

We used standard approaches with 40 million 100 nt paired end sequences to reliably assess expression for each sample using the Genome Analyzer IIx (Illumina). The design of the experiment was as follows: 12 barcoded samples, 6 of each genotype, were pooled and loaded on two lanes, so that each sample was spread over two lanes to further minimize confounds, specifically those associated with lane effects. RNAseq analysis was carried out as previously described (Tariq et al., 2011), although with some modifications. Briefly, following the removal of sequences that mapped to ribosomal RNA sequencing, the remaining reads were mapped to the rat reference genome rn4, using TopHat 2.0.9 (Trapnell et al., 2009) and Bowtie 2.1.0 (Langmead et al., 2009), using default values. The mean insert sizes, as determined by bioanalyzer, were employed in TopHat mapping. Only uniquely mapped reads were considered and used in downstream analysis. Transcript abundance was determined using the HTSeq tool. For quality control, we used the Fastqc and the RNA-seqQC tools, to assess the quality of the raw data and the mapped reads, respectively.

To visualize the deletion in exon 6 of the Shank3 gene, we used the Integrated Genome Browser (IGB), available online (http://bioviz.org/igb/). The Rattus norvegicus reference genome version Nov_2004 was selected, and the BAM alignment file, from each rat, was loaded separately (Figure 1—figure supplement 1A).

Developmental studies

Pregnant Shank3-Het rats were shipped to PsychoGenics (Tarrytown, NY) where they were checked daily for litters. On the day of birth (defined as postnatal day 0 [P0]), the dam and her litter were left undisturbed. On P2, pups were tattooed using non-toxic ink applied under the skin of their paw and a tail snip sample was taken for genotyping. All pups were weighed daily from P2 to P21. Some animals were assessed for milk content score from P2 until their abdomen was covered by fur (around P10) to look for genotypic differences in the ability to breast-feed. The milk score for each pup within a litter is dependent on the overall level of milk in all pups from that litter at the time of observation: 3, normal milk content, normal milk level is defined in relation to littermates' milk content; 2, stomach not full, but milk is easily detected; 1, trace amounts of milk; 0, absence of milk. Additionally, the age at which the animals’ eyes open was documented. Animals were checked for survival once per day and survival rates were recorded. Neonatal phenotyping assessments, including body temperature, isolation tests (measuring frequencies of square crossing, pivot, grooming, rearing, ultrasonic vocalization, sniffing, geotaxis, and righting reflex were conducted at either P7 or P15 as previously described (Brunner et al., 2015). All tests took place between 10:00 AM and 3:00 PM and were performed by an examiner blind to subject genotype (Supplementary file 1). At P15, animals were tested in the geotaxis and righting reflex tests.

Negative geotaxis

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Animals were placed on an inclined platform (approximately 35° incline) with their head facing down slope. The latency to reorient the head toward the higher end of the platform was recorded (Supplementary file 1). This test measures motor coordination and vestibular system function. Animals had a maximum of 60 s to complete the test.

Pre-righting reflex and righting reflex

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These motor coordination assays measure the ability of a rat to right itself (reorient itself back onto its feet) when placed on its back. The pre-righting reflex assessment scores the time (from 0 to 30 s) it takes for the animal to right itself. Immediately after the pre-righting reflex test, 10 consecutive righting reflex trials (30 s each) were conducted and the number of successful righting trials (out of ten 30 s trials) was recorded (see Supplementary file 1).

Behavioral tests

Elevated plus maze

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Anxiety levels of the rats were assessed at 6–8 weeks of age using the elevated plus maze (EPM) apparatus by PsychoGenics. The EPM apparatus (Kinder Scientific, Poway, CA) consists of four arms of equal dimensions at a 90o angle, connected via a 6 × 6 cm square area. Two of the arms (50 × 10.8 cm) have high walls (15.75 cm) on all sides except the central entry area (‘closed arms’), and the other two arms have no walls (‘open arms’). All surfaces visible to the experimental subjects are made of black acrylic. The whole apparatus is elevated approximately 85 cm above the floor and is surrounded by black vinyl curtains. Appropriate padding was placed underneath the EPM apparatus in the rare event that an animal fell when in the open arms of the maze. On test days, rats were habituated to the experimental room at least 1 hr prior to being exposed to the EPM. After this habituation period, the animals were placed in the center area of the EPM apparatus facing an open arm and allowed to freely explore for 5 min. We measured total distance traveled, time spent in and number of entries into both the open and closed arms of the EPM (see Supplementary file 1 for a summary of these results). Testing and measurements were performed by an examiner blind to subject genotype.

Adult dyadic social interaction

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At 6–8 weeks of age, animals were tested for social behaviors by PsychoGenics. The adult dyadic social interaction test chamber is made of white Plexiglas (60.96 cm x 43.8 cm x 20.32 cm). Prior to measuring social behavior, all rats were habituated to the test room for at least 30 min. After this habituation period, test rats were placed in the chamber with strain-, sex-, and age-matched controls. Social interactions were recorded for the duration of the 6-min test session. Interactions were scored as social if they included sniffing, climbing over or under, following or exploring the anogenital area of the conspecific rat. Passive or aggressive contacts were not considered social interactions. Total social interaction time was measured and each pair of rats was treated as a single unit in order to avoid false inflation of group size (Supplementary file 1). Interactions were scored by an experienced observer who was blind to genotype.

Social preference

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We used a modified version of the widely used social preference paradigm by Moy et al., (Moy et al., 2004). Briefly, following 1 hr of habituation in the experimental cage, 9–11 week old rats were exposed simultaneously to a non-social object (e.g., hole puncher, paperclip, Rubik's cube) and to a juvenile rat confined to a transparent plastic corral. The total amount of time that the subjects spent investigating the social and non-social stimuli was measured by an experienced observer who was blind to genotype and the results are show in Figure 2—figure supplement 1A.

Juvenile social play

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Social play behavior, in WT and Shank3-KO rats, was measured at 26–30 days of age, in a manner similar to what has been previously described (Hamilton et al., 2014). Briefly, after weaning at 21 days of age, rats were pair-housed. Prior to the juvenile social play test each rat was individually habituated to the test cage for 10 min for three consecutive days. After this third habituation session, rats were socially isolated for 24 hr before the juvenile social play test began. On test days, two non-littermate rats, of the same gender, were placed into the 45×45 × 40 cm test arena for 10 min. The play partner was always a WT rat with no more than 10 g difference in body weight when compared to the test subject. The behavior of the animals was videotaped and analyzed post hoc using video tracking software (Ethovision XT, Noldus). Several aspects of social play were assessed, including approaching, chasing, crawling, nape attacking, pinning, and boxing of the conspecific rat. Other forms of social, but non-play behaviors, were also measured such as licking, grooming, and body or anogenital sniffing of the play partner. Approaching was included in both play and non-play social behaviors as it cannot be considered solely as part of the play sequelae. Behaviors were scored independently by two trained observers who were blind to the test animal’s genotype (Figure 2—figure supplement 1B and Supplementary file 1).

Habituation-dishabituation social recognition memory

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The habituation-dishabituation social recognition memory test was also carried out as previously described (Spiteri and Agmo, 2009), but with several modifications. Briefly, following 1 hr habituation to the experimental cage (60 × 40 × 20 cm), 9–11 week old male test rats were exposed for 5 min to the same social stimulus over four consecutive sessions separated by intervals of 30 min. In a fifth session they were exposed to a novel social stimulus of a different strain. In each session, the duration of investigation was measured, including any contact between the subject’s nose and the juvenile’s body or any other investigatory behavior displayed by the adult subject was measured by a trained observer, who was blind to genotype. Juveniles (3 week old , 30–35 g) male Wistar-Hanover or Wistar-Hola rats were used as social stimuli (Figure 2—figure supplement 1C).

Long- and short-term social discrimination tests

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Long- and short-term social discrimination tests were performed as previously described (Gur et al., 2014). Briefly, in the long-term SRM, the test rat (9–11 week old) was unrestrictedly exposed to a novel juvenile (3 week old, 30–35 g) of a different strain (Wistar Hannover/Hola) for 1 hr in an experimental cage (60 × 40 × 20 cm). The test rat was placed alone, 24 hr later, in the same test cage, but which now contained two transparent plastic corrals (9 cm in diameter). These corrals contain five horizontal slots per side (1 × 13 cm each), which allow physical contact between test subjects and rats that are subsequently placed in the corrals. After a 1 hr habituation period to the plastic corrals inserted in the chamber, the test animal was simultaneously exposed to the same juvenile that it encountered the day before and to a novel juvenile of a different strain for 5 min. In this encounter, each of the juvenile rats was confined to one of the two transparent plastic corrals. The duration of investigatory behavior of the adult test subject toward each juvenile was measured as previously described (Figure 2B) (Gur et al., 2014). The short-term social memory test, was carried out similarly to the long-term social discrimination test except for three differences: (1) the time between the first and second encounter was 30 min (compared to 24 hr in the long-term social discrimination test), (2) the test rat was habituated to the corrals for 1 hr before the first encounter (instead of the second encounter) to prevent the novelty of the environment from interfering with the expression of social behaviors, and (3) The first encounter was conducted for 5 min while the juvenile was held in one of the corrals (Figure 2A). Investigation time was scored by an experienced observer who was blind to genotype.

Object location memory

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Test rats (9–11 week old) were placed for 1 hr in a chamber (60 × 40 × 20 cm), which contained two identical LEGOs. The locations of the LEGOs were fixed by being firmly magnetized to the chamber. The same animals were placed 24 hr later in the same chamber for 1 hr for habituation and then exposed for 5 min to the same LEGOs they encountered the day before. However, during this session the location of one of the LEGOs was different than during the first session. The duration of investigatory behavior toward each of the LEGOs was measured, including any contact between the subject’s nose and the object or any intended touch of the object by the adult test subject (Figure 2C). These subject-object interactions were scored by an experienced observer who was blind to genotype.

Contextual fear memory

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The contextual fear memory test was carried out as previously described (Kritman and Maroun, 2013). Briefly, adult rats (9–11 week old) were placed in fear conditioning chambers (Panlab, Harvard Apparatus; Holliston, MA), which are outfitted with electrified floor-grids, black methacrylate walls, and a transparent front door. On conditioning days, the rats received three 0.5 s foot-shocks delivered through the grid at an intensity of 0.8 mA. The three shocks were administered 90, 210, and 330 s after the subjects were placed in the chamber. After delivery of the third shock, freezing behavior was measured for 2 min to evaluate the success of the fear conditioning protocol. 24 hr after fear conditioning, the rats were placed in the same chamber for 5 min without being subjected to foot-shock. Freezing behavior during a 5 min test period was quantified offline, averaged and presented as a percentage of the total session time spent freezing (Figure 2D). Testing and quantification were performed by an examiner blind to subject genotype.

5-Choice serial reaction time (5-CSRT) task

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Eight-week-old rats were habituated to being handled by the experimenter and were food deprived to achieve ~85% of free feeding weight. 5-CSRT task training occurred in a manner similar to what has previously been described (Mar et al., 2013). Briefly, rats were trained to touch the location of an illuminated white square that is presented at 1 of 5 locations on a Bussey-Saksida capacitive touchscreen system (Lafayette Instrument Company; Lafayette, IN, USA). If a capacitive screen touch occurred at the illuminated location during or up to 1 s after stimulus presentation a sugar pellet was delivered in the reward receptacle located across the chamber from the touch screen. Training occurred in stages where the duration of the light stimulus was slowly decreased from 32 to 1 s by halving the stimulus duration across sessions once criterion performance was met (~80% accuracy and less than 20% of trials omitted). 4 WT, 5 Het, and 3 KO rats were unable to reach performance criterion at 1 s and therefore were excluded from analysis of 5-CSRT task performances. Analysis of these data was performed with custom routines written in the R statistical programming environment (R Development Core Team, 2006) and the results are presented in Figure 3A–D and Figure 3—figure supplement 1. Training, testing, and analyses were performed blind to subject genotype.

Electrophysiology

Hippocampal slice preparation

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Rats were deeply anesthetized with isoflurane and then sacrificed by decapitation. The brain was removed and quickly placed in ice-cold cutting solution containing the following (in mM): 215 sucrose, 20 glucose, 26 NaHCO3, 4 MgCl2, 4 MgSO4, 1.6 NaH2PO4, 1 CaCl2, and 2.5 KCl. Hippocampi were mounted on an agar block, and transverse slices 400 μm thick were prepared with a DTK-2000 microslicer (Dosaka EM). Slices were placed in a hot water bath at 30°C, in a holding chamber containing 50% cutting solution and 50% artificial CSF (ACSF) recording solution, which contained the following (in mM): 124 NaCl, 26 NaHCO3, 10 glucose, 2.5 KCl, 1 NaH2PO4, 2.5 CaCl2, and 1.3 MgSO4. After 30 min, the 1:1 solution was switched to ACSF at 30°C and the holding chamber was removed from the water bath. Slices recovered in ACSF at room temperature for at least 1 hr, and then were transferred to a submersion-type, temperature-controlled recording chamber (TC-344B, Warner Instruments) and perfused with ACSF at 2 ml/min using a peristaltic pump (Dynamax RP-1, Rainin). Experiments were performed at 28°C. All solutions were equilibrated for at least 30 min with 95% O2 and 5% CO2, pH 7.4. Conventional field recordings were performed using a MultiClamp 700B amplifier (Molecular Devices). For field experiments, a recording electrode fabricated on a two-step micropipette puller (PP-830 or PC-10, Narishige) filled with a solution containing 5 M NaCl. This electrode was placed ∼150 μm deep in the stratum radiatum. To elicit synaptic responses, paired, monopolar square-wave voltage or current pulses (100–200 µs pulse width) were delivered through a stimulus isolator (Isoflex, AMPI) connected to a broken tip (∼20–40 μm) stimulating patch-type micropipette filled with ACSF. In some experiments, a bipolar stimulating electrode was used. As both stimulations produced comparable results, the results were averaged together in the final analysis. Typically, stimulating electrodes were placed in the middle of CA1 stratum radiatum. Stimulus intensity was adjusted to give comparable magnitude synaptic responses across experiments (∼1 mV for extracellular field recordings). Baseline stimulation was delivered at 0.1 Hz, before and after the induction of long-term plasticity. All neurophysiological data were acquired and analyzed blind to genotype.

Extracellular recordings

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Hippocampal slices (350 µm, Cohort 1; 400 µm, cohort 2) were prepared from 4-6 week old (cohort 1) and 6-8 week old (cohort 2) Het and KO rats and their wild-type littermate controls. As previously described, stimulation electrodes were placed in CA3 of stratum radiatum and field excitatory postsynaptic potentials (fEPSPs) were recorded from CA1 of stratum radiatum (Bozdagi et al., 2000; Klein et al., 2015). Test stimulus intensity was adjusted to obtain fEPSPs with amplitudes that were one-half of the maximal response. The EPSP initial slope (mV/ms) was determined from the average waveform of four consecutive responses (Figure 4—figure supplement 1). Paired-pulse responses were measured with inter-stimulus interval (ISI) of 50 ms, and are expressed as the ratio of the average responses to the second stimulation pulse (FP2) to the first stimulation pulse (FP1) (see Supplementary file 1). Long-term potentiation (LTP) was induced by either a high-frequency stimulus (four trains of 100 Hz, 1 s stimulation separated by 5 min, Figure 4A) or a single 100 Hz stimulation (Figure 6—figure supplement 1A) . (S)−3,5-dihydroxyphenylglycine (DHPG, 50 µM) was used to induce mGluR-dependent LTD (Figure 4B and Supplementary file 1). Oxytocin (1 µM) (Tomizawa et al., 2003; Lin et al., 2012) was bath-applied, for 20 min in the baseline as indicated in Figure 6A and Figure 6—figure supplement 1A and in the figure legends.

Whole-cell recordings

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For mPFC recordings, 300-µm-thick coronal brain slices were prepared. Recording methods were similar to previously published protocols (Bozdagi et al., 2000; Li et al., 2011; Wang et al., 2011). Acute slices were prepared from 4- to 6-week-old Shank3 Het and KO rats or WT littermates. All recordings were conducted in layer five pyramidal cells in slices kept at 32°C (Supplementary file 1).

In vivo field recordings in anesthetized rats

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Shank3 Het or KO rats and WT littermate controls were anesthetized with urethane (1.5 g/kg, i.p.) and placed in a stereotaxic frame and prepared for recordings as previously described (Bozdagi et al., 2007). For mPFC recordings, unilateral craniotomies were drilled over mPFC and glass recording microelectrodes were positioned according to stereotaxic coordinates (AP = 3 mm, ML = 0.6 mm, DV = 5 mm). To stimulate hippocampal projections, a stimulation electrode was placed in hippocampal CA1 (AP = 6.3 mm, ML = 5.2 mm lateral, DV = 8 mm). After baseline responses were recorded for 30 min, LTP was induced using 4 trains of 100 Hz stimulation applied every 5 min (Figure 4C). Oxytocin (2 ng/4 μl with a rate of 1 μl/min) was injected ICV (AP = −0.3 mm, ML = 1.3 mm, DV = −3.5 mm) using a precision syringe (Hamilton), 0–5 min prior to HFS (Figure 6B). All neurophysiological data were acquired and analyzed blind to genotype.

Surgical implantation of guide cannula

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For the SRM experiments, a guide cannula was implanted in naïve rats at 8.5–9.5 weeks of age. For the 5-CSRT task, surgery occurred after baseline performance was measured for 10 sessions (after criterion performance was first met on with a 1 s cue duration). For surgery, rats were deeply anesthetized by subcutaneous injection of 10% ketamine (0.09 ml/100 g) and Dormitor (0.05 ml/100 g) or with isoflurane. Anesthetized animals were fixed in a stereotaxic apparatus with the head flat, and a small hole was drilled in the skull to facilitate implantation of guide cannula. The cannula was inserted 0.1 mm (SRM task) or 1.25 mm (5-CSRT task) above the left lateral ventricle. The coordinates were AP = −1 mm, ML = 1.5 mm, DV = −3.6 mm (SRM experiments) or AP = −0.75 mm, ML = 1.75 mm, DV = −4 mm (5-CSRT task) both targeting the left lateral ventricle. Cannula were secured in position with acrylic dental cement and stabilized by at least two bone screws. A dummy cannula was placed in the guide cannula to prevent the tube from clogging. Antibiotics (amoxicilin 15%, 0.07 ml/100 g) and a pain killer (Calmagin 0.03 ml/100 g) were administered directly before and immediately following surgery and one day post-surgery. Animals were allowed to recover for at least 7 days before experimentation began. Post-surgery, 5-CSRT task rats were retrained to stable performance before being subjected to microinjections. In the oxytocin 5-CSRT experiments, two implanted KOs, 1 Het and WT were not subjected to microinjections because they failed to achive pre-surgery performance levels. In the long-term SRM task, 1 WT and 2 KOs lost their caps, 1 Het and 1 KO died during surgery, and 1 Het was extremely stressed and thus was not subjected to oxytocin injection. All experiments were run and analyzed blind to genotype.

Oxytocin administration

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The injectate for intracranial microinjections was prepared fresh daily by dissolving oxytocin (American Peptide Company) in 0.9% saline to achieve a final concentration of 250 nM (0.25 ng/µl) (Benelli et al., 1995).

On test days, the fluid line and the microinjector were filled with mineral oil before drawing up the drug or saline control. Prior to microinjection, animals were gently restrained while the dummy cannula was removed and the microinjectors loaded with injectate were placed into the animal’s guide cannula. The injectate was administered at a rate of 1 µl/min for 4 min (in total 1 ng of oxytocin was injected). Concentration was chosen based on published studies of the effect of ICV oxytocin injection on behavior (Ferguson et al., 2000; Gur et al., 2014). After injection, the microinjector remained in the guide cannula for 1 min to allow for diffusion. In the SRM task, microinjections occurred 10–20 min before the first social encounter (Figure 5A and Figure 5—figure supplement 1A). In the 5-CSRT task, animals were immediately placed in the operant chamber after oxytocin administration and testing started 10 min after (Figure 5B and Figure 5—figure supplement 1B). The order of saline and oxytocin injections was randomized across rats.

Histology

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At the end of each of experiment rats were sacrificed with an overdose of isoflurane, brains were removed and placed in 4% paraformaldehyde overnight, and 200-µm-thick sections were prepared. Correct positioning of the cannula over the left lateral ventricles was confirmed visually in each rat.

Statistical analysis

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SPSS (SPSS 19; IBM) or the R environment were used for statistical analyses. Parametric approaches such as t-tests or analysis of variance were used if data was found to be normally distributed by the Kolmogorov-Smirnov test. When the condition of normality was not met, non-parametric approaches for statistical comparisons were used such as Kruskal-Wallis or the Wilcoxon signed rank test. A threshold of p<0.05 was used to test statistical hypotheses. A detailed description of the results of all analyses, including the test used, sample size, mean or median, SEM or SD, and p values can be found in Supplementary file 1.

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Decision letter

  1. Peggy Mason
    Reviewing Editor; University of Chicago, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

[Editors’ note: this article was originally rejected after discussions between the reviewers, but the authors were invited to resubmit after an appeal against the decision.]

Thank you for submitting your work entitled "Oxytocin improves social and attentional deficits in a novel genetically modified rat model of autism" for consideration by eLife. Your article has been favorably evaluated by a Senior Editor and three reviewers, one of whom, Peggy Mason (Reviewer #1), is a member of our Board of Reviewing Editors, and another one is Karen Bales (Reviewer #2).

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

Obtaining mechanistic insight into autism and related conditions through the analysis of rodent models of this disease is of major importance. Thus, the topic of this manuscript, that the Shank3-KO rat is a model of PMS, is of great interest and timeliness. Unfortunately, the reviewers were not convinced that the Shank3 rat has face validity with PMS. The deficits that were explored appear to be in memory and possibly perception more so than in social behavior. Additional concerns that we hope will aid the authors are detailed in the reviews appended below.

Reviewer #1:

This manuscript shows that oxytocin ameliorates several of the differences between Shank3-Het and KO rats and WT rats. Several issues concern this reviewer.

The short-term vs. long-term SD tasks are termed in a confusing or even misleading fashion. In the short-term SD, rats interact for 5 mins and then are tested 30 mins later. In the long-term SD, they interact for 60 mins and then are tested a day later. Which of the changes is relevant – the time of exposure or the interval before testing? And which change – both of which lengthen – does the short vs. long refer to? This is not a trivial point as the Het/KO rats are fine at the short-term and not at the long-term. And this is interpreted as a difference in memory. It could be due to a difference in exploration or perception.

The perception vs. memory difference is potentially important. The fact that they do better after a 5 s light CSRT than a 1 s one suggests that there may be a deficit in perception. 1 s is too short for them to interpret correctly. In the last paragraph of the subsection “Social memory and attentional deficits in Shank3-deficient rats”, it is unclear how this result is interpreted as it is lumped with an unrelated finding that speaks to the motivation for food reward.

The object location task is not exactly parallel to the SD task. Location rather than identity is tested. Why? Why not make the tasks entirely parallel?

Figure 4A. Is there enough power (6 rats per genotype) to say that there is no difference? Of note the rank order is WT> Het> KO for both NMDA and AMPA. In contrast it looks as though the n per group for LTP is as much as 60 (6 rats and 10 slices /rat). The actual number of data points in 4B should be stated.

How are the numbers of rats tested determined? E.g. for the oxt studies with CSRT, 15 HETs and 8 KOs were studied. Of concern was that the numbers were not pre-set.

Reviewer #2:

This paper behaviorally and neurobiologically characterizes the Shank3 rat, as a model for autism, and examines the effects of oxytocin administration on the behaviors. In addition, it examines LTP in hippocampal slices in the Shank3 rat and shows that oxytocin restores normal LTP in vitro. This paper makes a large contribution to the literature on oxytocin through its thorough behavioral characterization and also in that it showed a neural mechanism for oxytocin to ameliorate behavioral deficits.

I have two large concerns:

Whereas the main therapeutic use for oxytocin in humans is via intranasal administration, in this study it was via intracerebroventricular administration. This is not clear unless you look at the methods. Please modify the Results/Discussion to indicate this mode of administration, and that results might differ from intranasal administration.

Also:

The Methods say that the EPM was performed (subsection “Elevated plus maze”), but I could not find these results in the text.

Reviewer #3:

In this manuscript Harony-Nicolas et al. describe the successful generation of Shank3-deficient rats, modeling the Phelan-McDermid syndrome (PMS) in humans. They report that these rats show several behavioral impairments related to social memory and attention that are associated with PMS, and then go on to show that electrophysiological phenotypes in the hippocampus and prefrontal cortex are present in these rats that may serve as potential mechanisms for the observed behavioral deficits. These phenotypes were reversed by in vitro or in vivo administration of oxytocin. These novel findings are of high interest to the field as using rats as model organisms for ASD could be beneficial for translating potential treatment options. However, there is a disconnect between the presented findings and the authors' claims that these rats serve as an animal model of ASD – these rats do not show any of the core behavioral symptoms of ASD (repetitive behavior, social interaction deficits, etc.). The phenotypes are more related to learning and memory, which are affected in patients with Shank3 mutations. Thus, the title and Abstract are misleading. Overall, a more transparent and accurate assessment of the Results is necessary, rather than trying to fit this model into the "ASD box. " In fact, it is quite interesting that these animals do not mirror the mouse models, and do not have behavioral manifestations expected in a model of ASD, but rather a model of ID.

1) The title of the paper suggests that these rats display "social deficits" – this should be changed to "memory deficits" since these rats do not appear to have a generalized social deficit. This is a general theme throughout the paper that needs to be seriously addressed

2) Many of the behavioral phenotypes exhibited by several types of Shank3-deficient mouse models of ASD, for example elevated anxiety, repetitive behavior, reduced social interest (e.g. Peca et al., 2011 Nature; Mei et al., 2016 Nature; Wang et al., 2016 Nat. comm.) are not seen in these Shank3-deficient rats. Do these rats develop compensatory mechanisms that protect from these behavioral phenotypes associated with ASD? Does the function of corticostriatal circuits remain intact?

3) The presented dataset suggests that there is a specific impairment in hippocampal synaptic plasticity, and not areas involved in social cognition, such as frontal lobe – at the same time object location memory remains intact in the rats. Are other hippocampal plasticity-dependent tasks impaired in these mice? Given the uncertainty as to which circuits are involved, this needs to be presented clearly.

4) We have no real insight into mechanisms, which is the reason to use the model system. What are the mechanisms of impaired LTP in the hippocampus? Are there postsynaptic components, as expected from Shank3's role as a postsynaptic protein?

5) The recovery of behavioral impairments by i.c.v. oxytocin is an exciting finding. However, the authors have not addressed which receptor type, expressed in which brain region(s), is responsible. Oxytocin can activate both vasopressin and oxytocin receptors, and these receptors are widely expressed throughout the brain. Since the authors have shown that the synaptic plasticity in the hippocampus is impaired whereas it remains intact in the PFC, oxytocin is presumably acting on the hippocampus to recover the attentional deficits and memory. Is there any experimental evidence to support this?

Again, social memory and attention while sometimes disrupted in ASD are not core features of ASD. The hippocampal deficits that are suggested here speak more to learning and memory and therefore, ID, in humans.

[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]

Thank you for submitting your article "Oxytocin improves behavioral and electrophysiological deficits in a novel Shank3-deficient rat" for consideration by eLife. Your article has been favorably evaluated by a Senior Editor and two reviewers, one of whom, Peggy Mason (Reviewer #1), is a member of our Board of Reviewing Editors, and another one is Karen Bales (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

This manuscript reports a valuable description of a Shank3 mutant rat, its cognitive deficits and rescue of the deficits tested by ICV oxytocin.

The authors are asked to address the sample sizes one last time. The authors say that the samples were largely constrained by the 25-50-25 inheritance pattern of WT-Hets-KOs. Yet the samples don't show this 25-50-25 distribution. They are very close to 1:1:1 overall. In the early tests – where mortality does not figure and where the distribution should be closer to Mendelian – the rats are at 9-15-12 which is a ratio of 0.6-1-0.8. However, in the core social memory tests (conducted later) the distributions are 12-13-9, 22-20-11, 9-17-14, 31-37-25, averaging 0.9-1-0.7. Then in the oxytocin rescue experiments (which are if anything more time consuming and subject to loss), the ratio is again very close to 1:1:1.

These ratios close to one are not easy to understand and are not explained by the authors' letter. The reason that this is important is because of the need to set sample size targets for behavioral tests prior to conducting the tests in order to avoid unconscious bias to creep into the experiment.

It might be of help to discuss how many animals in each pool and of each type were lost to surgery or some other fatality.

Was the person conducting the e-phys blind to the rat's genotype? And the person that analyzed the e-phys’ results?

Given the history of this submission, we must reach a final decision on your next and last version.

Reviewer #2:

The authors have addressed all of my comments and I have no further concerns.

https://doi.org/10.7554/eLife.18904.016

Author response

[Editors’ note: the author responses to the first round of peer review follow.]

[…] Reviewer #1:

This manuscript shows that oxytocin ameliorates several of the differences between Shank3-Het and KO rats and WT rats. Several issues concern this reviewer.

The short-term vs. long-term SD tasks are termed in a confusing or even misleading fashion. In the short-term SD, rats interact for 5 mins and then are tested 30 mins later. In the long-term SD, they interact for 60 mins and then are tested a day later. Which of the changes is relevant – the time of exposure or the interval before testing? And which change – both of which lengthen – does the short vs. long refer to? This is not a trivial point as the Het/KO rats are fine at the short-term and not at the long-term. And this is interpreted as a difference in memory. It could be due to a difference in exploration or perception.

We thank the reviewer for raising this point. To avoid further confusion, we have now clarified in the Results section that the long- and short-term refer to the interval between exposures and not the exposure time (subsection “Social memory and attentional deficits in Shank3-deficient rats”, second paragraph). This is in addition to the diagrams that we included in the original manuscript (Figures 2A and 2B), which outlined the method schematically (including showing the timing of the exposure and the interval), and the Methods section that detailed both paradigms.

We understand the reviewer’s concern and agree that, under certain circumstances (that we don't think apply here) the difference in the time spent with the social stimuli may introduce confounds that relate to exploration or perception. However, this would only be of concern if the rats showed deficits in their short-term social recognition memory (with the short interaction time) while showing intact long-term social recognition memory (with the longer interaction time). The opposite is true. The Shank3 HET and KO rats show intact short-term memory on the short-term social discrimination test even with a short exploration time, indicating that their social exploration or perception is not affected. And they show an impaired behavior on the long-term social discrimination test thus suggesting that their long-term memory is affected, even when given enough time (1 hour) for exploration. Furthermore, the possibility of differences in exploration is addressed by the similarity in total exploration time between the genotypes and in their social preference. We have now added and discussed these points in the Results section (subsection “Social memory and attentional deficits in Shank3-deficient rats”, second paragraph).

Finally, it is noteworthy to mention that it is a common procedure in memory studies that a weaker stimulus is used to induce short-term memory, while a stronger stimulus are used (and often required)to produce long-term memory. As an example is the low and high doses of LiCl used in the conditioned taste aversion paradigm (Houpt&Berlin 1999, PMID:10355522). This, in fact, correlates with LTP procedures where short-term LTP can be achieved with one train of tetanic stimulation while long- term LTP requires several such trains. The idea behind using distinct procedures in our experiments is to apply a minimal exposure that generates a stable memory, so if indeed any of the genotypes exhibit impaired social memory it will be easily detected on the background of such a minimal procedure. For short-term memory, exposure of 5 minutes is enough, and hence used here, while a much longer exposure (1 h in our hands) is needed for long-term SRM (in rats).

The perception vs. memory difference is potentially important. The fact that they do better after a 5 s light CSRT than a 1 s one suggests that there may be a deficit in perception. 1 s is too short for them to interpret correctly. In the last paragraph of the subsection “Social memory and attentional deficits in Shank3-deficient rats”, it is unclear how this result is interpreted as it is lumped with an unrelated finding that speaks to the motivation for food reward.

We understand the concern of the reviewer and agree that changes in accuracy can be conceived as reflecting deficits in sensory perception, specifically those related to basic visual sensory function. However, it is important to note that the pattern of deficit we observe, and which is evoked by only changing the stimulus duration, is commonly interpreted as reflecting an attentional deficit, while deficits observed by changing the physical qualities of the light(brightness or illuminance) are those that reflect perceptual differences (Reviewed by Robbins TW, 2002, PMID: 12373437). In our experiment we used the same light stimulus in all sessions and found that the rats have no problem in seeing and responding to the light, implying that they have no issues with their sensory perception. We also did a decreased brightness challenge in one of the rat cohorts and did not observe any effect on performance, which further argues against the observed primary deficit being due to perceptual problems. Only when the duration of the light was shortened, the deficits were evoked and the rats had difficulties in detecting a more briefly presented light, indicating that the Shank3 Het and KO rats have difficulty in vigilance or spatial attention. We have now clarified this point in the Results section (subsection “Social memory and attentional deficits in Shank3-deficient rats”, last paragraph).

We have edited the sentence that the reviewer refers to (in the original file) to clarify this point, and want to note that the sentence that follows (“These deficits were not due to decreased motivation for food reward, because latency to collect reward after a correct response was similar among genotypes (Figure 2—figure supplement 1E), as was task performance when light cues were of a longer duration” is not unrelated, but rather is important because the observed attentional findings could be also related to motivational problem, which we rule out by examining the latency of the rats to collect reward, which we found to be unaffected in the Shank3-deficient rats.

Finally, as a side comment, we want to note that the reviewer’s comments: “The fact that they do better after a 5 s light CSRT than a 1 s one suggests that there may be a deficit in perception”, if thought about more generally, supports the second point we raised for the previous comment and emphasizes the notion that perception would be an issue if the rats perform worse on shorter stimuli vs. longer ones on the social recognition memory test and not vice versa.

The object location task is not exactly parallel to the SD task. Location rather than identity is tested. Why? Why not make the tasks entirely parallel?

The idea behind testing the Shank3 rats on the object location memory and the contextual fear conditioning tests was not to examine a paradigm that is exactly parallel to social discrimination. Instead, the aim was to examine whether the observed deficits in social recognition memory are specific to social stimuli or that the Shank3 rats have a general memory deficit. Obviously, the first choice one would think about to test non- social memory is the novel object recognition test, given the fact that it technicallyseems to be the best to parallel the social discrimination test that we applied. However, the reason we focused on the object location memory and contextual fear conditioning tests in our study is because social recognition memory is well known to be hippocampal- dependent and our findings demonstrate that the Shank3 rat model has hippocampal LTP deficits. Therefore, we aimed to examine other hippocampal-dependent memory paradigms. Both the object location and the fear conditioning tests are known to be hippocampal dependent, while the dependence of the object location memory test on the hippocampus is not clear (see for example Gaskin et al. 2003, PMID: 14750658). Since the object location memory and the contextual fear conditioning tests differ in their mode (the fear-conditioning task is a reinforcement-driven task while the object location memory test depends on the animal’s natural exploratory tendency when introduced in a new stimulus or stimulating environment), we decided to include both. We have further clarified this point in the Results section (subsection “Social memory and attentional deficits in Shank3-deficient rats”, third paragraph).

Figure 4A. Is there enough power (6 rats per genotype) to say that there is no difference? Of note the rank order is WT> Het> KO for both NMDA and AMPA. In contrast it looks as though the n per group for LTP is as much as 60 (6 rats and 10 slices /rat). The actual number of data points in 4B should be stated.

We thank the reviewer for raising this point and agree that we are underpowered to exclude a real change in I/O function for NMDA. We estimate that we need 15 data points to say that reliably. We have therefore removed this figure and repeated the I/O function assessment in an independent set of experiments on WT and KO rats, focusing on overall I/O and using larger n (n=5 rats per genotype/3 slices per rat). This data is now presented as Figure 4—figure supplement 1, and shows no significant differences in I/O function between genotypes. Understanding subtle impact of Shank3 deficiency on multiple aspects of synaptic function (including AMPA and NMDA receptors) is an important study that will require multiple different approaches and analyses. Altogether, the data suggest that change in I/O function is not likely to explain the clear LTP changes.

We apologize for the typographical error in the number of animals used for LTP recording. The correct numbers were n=6 rats/1-2 slices per rat. Those numbers have been corrected in the legend of the figure and in the supplementary file (Supplementary file 1).

How are the numbers of rats tested determined? E.g. for the oxt studies with CSRT, 15 Hets and 8 KOs were studied. Of concern was that the numbers were not pre-set.

The sample size was chosen based on the standards in the field and using on-line sample size/power calculation tools. Specifically, we followed the recommendation for the “Minimum Numbers of Mice” discussed by Professor Jacqueline N. Crawley, in her book entitled “What’s Wrong With My Mouse”, Second Edition and applied the “biomath” online tool; (http://biomath.info/power/) for targeted calculations. Following the book’s recommendation, we determined our minimal N following Figure 13.1 (contributed by Professor Douglas Wahlsten) in the above-mentioned book, which describes the number of animal/per group needed to obtain specific statistical power. In general, our N for behavioral studies ranged between 9-22, therefore we were 60-80% powered to detect large effect differences (δ=1 – 1.5). As noted, we also calculated the numbers for each experiment based on its design using the “biomath” online tool. For example, for the social discrimination test, we applied a paired t-test between the novel and familiar stimuli to determine SRM (this was also applied for the Oxt treatment experiments). Since in normal conditions rats spend on average at least 60% of their total investigation time exploring the novel stimulus, with SD of 12%, a sample size of n=6 is calculated for 80% power and confidence interval of 5%. However, we always try to double this sample size so we aim for 12 animals per group, beyond the predicted sample size. This was important because, in some cases, we lost some animals during the experiment, leaving us with 7-8 animals, which is still beyond the predicted sample size. Information about the exact N and statistical method used for each experiment were detailed in the supplementary file (Supplementary file 1).

We understand the question of the reviewer regarding the variability of the N between the different genotypes. In all our studies we use offspring of Het x Het breeding. This is to be able to study littermates, which is optimal when carrying out behavioral studies. The fact that the numbers varied between the genotypes is hence primarily because HET x HET breeding produces a distribution of 25% WTs, 25% KOs and 50% HETs. Therefore, for each WT and KO rats we have two HET littermates that we could use and include in our data, when available, without invalidating our experiment and analysis. The 5-CSRTT requires at least two months of training after which we do surgeries to inject the OXT (in the case of the 5-CSRTT-OXT experiment). During this period and the surgeries, there is always a chance of losing one or two animals, which cannot be replaced, together with its littermates, before 4 additional months (breeding, reaching the age of testing and then training). Therefore, we tried to include as many of the available rats as possible, given the limited number of testing chambers, even if this means that we will not start or end with precisely equal numbers of animals.

Reviewer #2:

This paper behaviorally and neurobiologically characterizes the Shank3 rat, as a model for autism, and examines the effects of oxytocin administration on the behaviors. In addition, it examines LTP in hippocampal slices in the Shank3 rat and shows that oxytocin restores normal LTP in vitro. This paper makes a large contribution to the literature on oxytocin through its thorough behavioral characterization and also in that it showed a neural mechanism for oxytocin to ameliorate behavioral deficits.

I have two large concerns:

Whereas the main therapeutic use for oxytocin in humans is via intranasal administration, in this study it was via intracerebroventricular administration. This is not clear unless you look at the methods. Please modify the Results/Discussion to indicate this mode of administration, and that results might differ from intranasal administration.

We thank the reviewer for raising this point and agree that this is an important issue that should be discussed and clarified in the manuscript. We agree with the reviewer that it is totally possible that when ICV injected, the effect of oxytocin may be different than when it is intranasally administered. This is mainly due to the fact that the percentage of oxytocin that reaches the brain following intranasal administration (using tolerable concentrations) is extremely small making the brain oxytocin concentration following intranasal administration incomparable to those detected following direct ICV injection into the brain. This reality implies that the delivery approach of oxytocin to the brain should be improved to allow better comparison between direct and indirect administrations in animal studies and to optimize treatment efficacy in human subjects. We have now added a paragraph to address this issue in the Discussion section (eighth paragraph).

Also:

The Methods say that the EPM was performed (subsection “Elevated plus maze”), but I could not find these results in the text.

We thank the reviewer for pointing out that EPM results were missing in the text. The approach was indeed discussed in the Methods section, and the results and statistical analysis were included in the supplementary file, but not in the main text. We have now added this information to the Results section (subsection “Production and developmental phenotyping of the Shank3-deficient rat model”, last paragraph).

Reviewer #3:

In this manuscript Harony-Nicolas et al. describe the successful generation of Shank3-deficient rats, modeling the Phelan-McDermid syndrome (PMS) in humans. They report that these rats show several behavioral impairments related to social memory and attention that are associated with PMS, and then go on to show that electrophysiological phenotypes in the hippocampus and prefrontal cortex are present in these rats that may serve as potential mechanisms for the observed behavioral deficits. These phenotypes were reversed by in vitro or in vivo administration of oxytocin. These novel findings are of high interest to the field as using rats as model organisms for ASD could be beneficial for translating potential treatment options. However, there is a disconnect between the presented findings and the authors' claims that these rats serve as an animal model of ASD – these rats do not show any of the core behavioral symptoms of ASD (repetitive behavior, social interaction deficits, etc.). The phenotypes are more related to learning and memory, which are affected in patients with Shank3 mutations. Thus, the title and Abstract are misleading. Overall, a more transparent and accurate assessment of the Results is necessary, rather than trying to fit this model into the "ASD box. " In fact, it is quite interesting that these animals do not mirror the mouse models, and do not have behavioral manifestations expected in a model of ASD, but rather a model of ID.

We appreciate and respect the reviewer’s point of view and agree that the phenotypes observed in the Shank3 rat model may relate more to those affected in patients with PMS and have changed the title and text accordingly.However, we still believe that the Shank3 rat is a valid model for important aspects of ASD, as mutations in this gene are associated with such high risk for ASD. As we and others have shown, not all patients with PMS have ASD, so there is no reason to expect that a specific rodent model will show ASD (see Soorya et al. 2013, PMID23758760). We added a paragraph that discusses this issue in the Discussion section (second paragraph).

But the broader point is that it has become quite clear that there are many ways to have a deficit in reciprocal social interactions and hence meet criteria in ASD, that have little to do with social aversion or lack of social approach. The simplest example is William Syndrome, known for hypersociability, where some 50 percent of individuals meet criteria for autism. They show excessive social approach but they are not able to carry out ‘typical’ reciprocal social interactions.

In the specific case of PMS, in our recent functional neuroimaging study we show quite clearly that differential fMRI changes in response to social versus non-social sounds are preserved in PMS (see Wang et al. 2016, PMID: 26909118), a difference that is absent in other studies of idiopathic autism. In addition, we show that social orientating is preserved in PMS, again, something reduced in studies of idiopathic autism. For this reason, others and we conclude that PMS-associated ASD is not associated with a social indifference or social aversion, in contrast to the more typical conception of ASD. In addition, we conclude that the primary, and most significant and pervasive deficits in PMS are cognitive and attentional, rather than social. And there is little doubt that there will be many subtypes of autism with preserved social interest. Hence we would argue that this is a good model for PMS and a reasonable model for some subtypes of ASD. However, as noted above, we have made the requested changes (Abstract; Introduction; Discussion, second paragraph).

1) The title of the paper suggests that these rats display "social deficits" – this should be changed to "memory deficits" since these rats do not appear to have a generalized social deficit. This is a general theme throughout the paper that needs to be seriously addressed

We agree with the reviewer and have now changed the titleto better reflect the findings. However, we did not use the term “memory deficits” as suggested by reviewer. This is because we believe this would be misleading given the fact that the Shank3- deficient rats showed no deficit on two non-social long-term memory paradigms, the object location memory and contextual fear conditioning tests, and that their deficits are only on tasks that implicate social-dependent memory. Therefore, in the same way that the reviewer emphasizes that the social deficits cannot be generalized, we believe that the observed memory (social memory) deficits cannot be generalized as well.

2) Many of the behavioral phenotypes exhibited by several types of Shank3-deficient mouse models of ASD, for example elevated anxiety, repetitive behavior, reduced social interest (e.g. Peca et al., 2011 Nature; Mei et al., 2016 Nature; Wang et al., 2016 Nat. comm.) are not seen in these Shank3-deficient rats. Do these rats develop compensatory mechanisms that protect from these behavioral phenotypes associated with ASD? Does the function of corticostriatal circuits remain intact?

We agree with the reviewer that the Shank3 rat model does not display all of the phenotypes observed in various Shank3-mouse models, and we thank the reviewer for raising this issue, and helping us realize the importance of discussing it in the paper. We have now included a brief discussion about this issue in the Discussion section (third paragraph).

Finding discrepancies between the rat and mouse models is not totally surprising since such discrepancies have been already reported even between Shank3 mouse models. We have previously summarized these discrepancies in detail (Harony-Nicolas et al., 2015; PMID: 26350728), including discrepancies in reported alterations in motor function, anxiety levels, social preference, interest for social novelty, and ultrasonic vocalizations, which exemplify how difficult it is to draw a unifying phenotype when dealing with different models even of the same species.

These discrepancies within the mice models and between the mice and rat model could be attributed to:

1) The fact that different models have mutations/deletions in different parts of the Shank3 gene. Although all mutations lead to the deletion of the longest Shank3 isoform, each leaves behind other shorter isoforms. The role of these shorter Shank3 isoforms is not clear. They can potentially play a compensatory and protective role or, contrary; increase the deleterious effect of the introduced mutation leading to the manifestation of different phenotypes in each model.

2) The use of different behavioral paradigms to assess what is identified as the same behavior.

3) The age of the tested animal on each paradigm.

4) The sex of the tested animals.

5) Genetic differences in background strains used in the mice.

Some of the findings in mice are made in homozygous but not heterozygous animals. Moreover, mice and rats are separated by 12-25 million years in evolution and differ in complex behaviors, thus generating different outcomes in behavioral paradigms. Whether we want to relate these different outcomes to compensatory mechanisms or to an added complexity in cognition and behavior, it is an open argument.

Finally, based on our findings showing that the Shank3-deficient rats do not exhibit motor deficits or show any impulsive behavior on the 5-CSRT test, we did not have a strong rationale to focus on the corticostriatal circuits in the current study. We chose to study the plasticity in the hippocampus and the hippocampal-PFC circuit because of their direct relevance to the observed attentional and social recognition memory deficits. However, one cannot exclude the possibility that other brain circuits are affected by the Shank3 mutation, especially corticostriatal circuits, which have been shown to be impaired by Shank3 mutation in the mouse. Therefore, we agree with the reviewer that the integrity of other circuits should be examined as well in the frame of future studies.

3) The presented dataset suggests that there is a specific impairment in hippocampal synaptic plasticity, and not areas involved in social cognition, such as frontal lobe – at the same time object location memory remains intact in the rats. Are other hippocampal plasticity-dependent tasks impaired in these mice? Given the uncertainty as to which circuits are involved, this needs to be presented clearly.

As we have previously noted in our response to comment 3 of reviewer #1 and to our response to this reviewer for comment 1, we have examined two well-known hippocampal-dependent long-term memory paradigms, the object location memory and contextual fear conditioning tests. None of these tests showed a significant difference between genotypes. The fact that socialrecognition memory, which is well known to be hippocampal-dependent, was affected in the Shank3 rat model, while two other non- socialhippocampal-dependent memories were not, suggests that (1) the memory deficits are social specific and (2) social recognition memory is a more "frangible" type of memory that implicates more complex cues as compared to the non-social memory tested by us. Therefore, when the hippocampal circuitry is even partially impaired, the social recognition memory may be more vulnerable and more affected than other types of memory. Another possibility is that the PFC impairment is the most severe in our study and that this region is needed only for social memory.

4) We have no real insight into mechanisms, which is the reason to use the model system. What are the mechanisms of impaired LTP in the hippocampus? Are there postsynaptic components, as expected from Shank3's role as a postsynaptic protein?

We indeed use animal models to gain insight into underlying mechanism, and we do that with the ultimate goal of using them for drug discovery and for the evaluation of novel and existing (FDA approved) drugs. While understanding the mechanisms underlying the LTP deficits is highly important and would shed light on affected mechanisms or pathways that can be of interest for drug discovery, the focus of the current study was on producing, validating and studying a novel rat model and to see whether some deficits could be reversed. This latter study made use of an already existing and safe clinical compound, oxytocin, to ameliorate impaired behaviors. But the choice of oxytocin arose from the specific deficits we observed (in which oxytocin has a very direct role).

As noted by the reviewer and as expected from the role of Shank3 at the postsynapse, other postsynaptic components are likely to be affected by Shank3- deficiency. Indeed, findings from Shank3-mouse models support this notion and show changes in the levels of other PSD scaffolding components, subunits of glutamatergic receptors, as well as deficits in the synaptic actin cytoskeleton remodeling system, which is well associated with synaptic plasticity. Amongst the most reliable and reproducible findings from Shank3 mouse models is the decrease in the levels of Homer, a scaffolding protein that interacts with Shank3 at the PSD. In the Shank3-deficient rat model, we also found a significant decrease in Homer, in KO rat PFC samples, which validates the mouse models findings. We have added this finding to the Results section (subsection “Production and developmental phenotyping of the Shank3-deficient rat model”, first paragraph), Discussion, and to Figure 1—figure supplement 1 legend.

We have recently obtained preliminary data (not discussed in this paper) suggesting changes in the actin cytoskeleton components, similar to those reported in the Shank3-mouse models. While valuable, these findings are not informative by themselves and require further investigation to examine how such baseline changescontribute to the observed synaptic plasticitydeficits, so to be able to infer the direct relationship between both. This will be done by studying the dynamics of these and other synaptic components before and after in-vitro or in-vivo synaptic stimulation, and which is beyond the scope if the current study.

5) The recovery of behavioral impairments by i.c.v. oxytocin is an exciting finding. However, the authors have not addressed which receptor type, expressed in which brain region(s), is responsible. Oxytocin can activate both vasopressin and oxytocin receptors, and these receptors are widely expressed throughout the brain. Since the authors have shown that the synaptic plasticity in the hippocampus is impaired whereas it remains intact in the PFC, oxytocin is presumably acting on the hippocampus to recover the attentional deficits and memory. Is there any experimental evidence to support this?

We agree with the reviewer that oxytocin can activate both oxytocin and vasopressin receptors, which are widely spread across different brain regions and play and essential role in translating the oxytocin signal into cellular changes. We believe this question is important mainly because by discovering which receptors are activated by oxytocin and which downstream pathways are stimulated by this activation, we will be able to uncover new therapeutic targets for treatments. While highly important and significant to the field, we feel that addressing this question is best done in an independent study.

Regarding the second point raised by the reviewer, we respectfully disagree with the statement that “the synaptic plasticity in the hippocampus is impaired whereas it remains intact in the PFC”. PFC plasticity is not intact, as we clearly show that LTP in the PFC was reduced in both Shank3-Het and KO rats. Having that explained, one can’t conclude based on current available data as to which brain region is targeted and most benefited by the oxytocin administration. PFC would certainly be the more reasonable target of attention restoration by oxytocin, yet this has to be experimentally examined. As we stated for the first point, and as the reviewer implied, identifying the target receptor activated by oxytocin and the brain region targeted will help address this issue. In this regard, brain recording as well as imaging studies (e.g., fMRI) following oxytocin administrations can also be valuable tool to be considered. Yet as we noted above, while important and significant to the field, understanding the mechanisms by which oxytocin exerts its effect is, in our opinion, best left to an independent study.

Again, social memory and attention while sometimes disrupted in ASD are not core features of ASD. The hippocampal deficits that are suggested here speak more to learning and memory and therefore, ID, in humans.

This comment has been addressed at length in response to the reviewer’s general overview and in our response to his first and third comments.

[Editors’ note: the author responses to the re-review follow.]

[…] This manuscript reports a valuable description of a Shank3 mutant rat, its cognitive deficits and rescue of the deficits tested by ICV oxytocin.

The authors are asked to address the sample sizes one last time. The authors say that the samples were largely constrained by the 25-50-25 inheritance pattern of WT-Hets-KOs. Yet the samples don't show this 25-50-25 distribution. They are very close to 1:1:1 overall. In the early tests – where mortality does not figure and where the distribution should be closer to Mendelian – the rats are at 9-15-12 which is a ratio of 0.6-1-0.8. However, in the core social memory tests (conducted later) the distributions are 12-13-9, 22-20-11, 9-17-14, 31-37-25, averaging 0.9-1-0.7. Then in the oxytocin rescue experiments (which are if anything more time consuming and subject to loss), the ratio is again very close to 1:1:1.

These ratios close to one are not easy to understand and are not explained by the authors' letter. The reason that this is important is because of the need to set sample size targets for behavioral tests prior to conducting the tests in order to avoid unconscious bias to creep into the experiment.

It might be of help to discuss how many animals in each pool and of each type were lost to surgery or some other fatality.

Was the person conducting the e-phys blind to the rat's genotype? And the person that analyzed the e-phys’ results?

We thank the reviewer for raising these important questions, and we have divided our response into several sections.

Sample size:

We would like to begin by emphasizing that our minimum sample sizes for each experiment, chosen based on power analyses, were set before the experiments started, and that there were no intermediate analyses based on partial samples (and hence no alteration in sample sizes as the study progressed). Hence we do not think that there could be a source of unconscious bias that led to altered results.

We also want to apologize for the confusion that we introduced by the description of 1:2:1 ratios of WT, Hets, and KOs. This was meant to underscore that the breeding scheme, together with the focus on males, had impact on sample size because only one out of every eight pups was expected to be homozygous and male. In practice, we targeted a 1:1:1 ratio in these studies.

Mendelian ratios:

Based on this comment regarding Mendelian ratios, we have now reviewed a large series of serial litters (n=130 litters). We observed that there is a reduction in the number of homozygous knockout animals at weaning (292:555:200, corresponding to ratios of 0.53:1:0.36). It is for this reason that there are sometimes fewer animals in the KO group. This is now noted in the text.

Animal loss:

We do not think that animal loss played a biased role in the results. As we now note in the text, in the long-term SRM task, 1 WT and 2 KOs lost their caps, 1 Het and 1 KO died during surgery, and 1 Het was extremely stressed and thus was not subjected to oxytocin injection. For the 5-CSRT, 4 WT, 5 Het, and 3 KO rats were unable to reach performance criterion at 1 s and therefore were excluded from analyses. This is now noted in the text.

Binding of assessor:

Finally, we would like to also state that the electrophysiology experiments were done with the experimenter and data analyst blind to genotype. This is our standard approach for all studies and we had already noted this for some experiments but accidently omitted to note this for electrophysiology and in a few other places in the manuscript. We have now added this information to the Methods.

https://doi.org/10.7554/eLife.18904.017

Article and author information

Author details

  1. Hala Harony-Nicolas

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    HH-N, Conceptualization, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Methodology, Writing—original draft, Project administration
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8283-9093
  2. Maya Kay

    Sagol Department of Neurobiology, University of Haifa, Haifa, Israel
    Contribution
    MK, Conceptualization, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Contributed equally with
    Johann du Hoffmann
    Competing interests
    The authors declare that no competing interests exist.
  3. Johann du Hoffmann

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    JdH, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Contributed equally with
    Maya Kay
    Competing interests
    The authors declare that no competing interests exist.
  4. Matthew E Klein

    Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, United States
    Contribution
    MEK, Data curation, Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  5. Ozlem Bozdagi-Gunal

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    OB-G, Conceptualization, Data curation, Formal analysis, Methodology, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  6. Mohammed Riad

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    MR, Data curation, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  7. Nikolaos P Daskalakis

    Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    NPD, Data curation, Formal analysis, Methodology, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  8. Sankalp Sonar

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    SS, Data curation, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  9. Pablo E Castillo

    Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, United States
    Contribution
    PEC, Supervision, Funding acquisition, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  10. Patrick R Hof

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    3. Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    PRH, Conceptualization, Supervision, Funding acquisition, Investigation, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  11. Matthew L Shapiro

    1. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    MLS, Conceptualization, Resources, Supervision, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  12. Mark G Baxter

    1. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    MGB, Conceptualization, Resources, Data curation, Formal analysis, Supervision, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  13. Shlomo Wagner

    Sagol Department of Neurobiology, University of Haifa, Haifa, Israel
    Contribution
    SW, Conceptualization, Resources, Formal analysis, Funding acquisition, Investigation, Writing—original draft, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7618-0752
  14. Joseph D Buxbaum

    1. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, United States
    2. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, United States
    3. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    4. Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    5. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    6. The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    JDB, Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing—original draft, Writing—review and editing
    For correspondence
    joseph.buxbaum@mssm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8898-8313

Funding

Human Frontier Science Program (RGP0019/2015)

  • Hala Harony-Nicolas
  • Shlomo Wagner
  • Joseph D Buxbaum

National Institute of Mental Health (F31-NS073200)

  • Matthew E Klein

National Institute of Mental Health (T32-GM007288)

  • Matthew E Klein

National Institute of Mental Health (R01-MH081935)

  • Pablo E Castillo

National Institute of Mental Health (R01-DA17392)

  • Pablo E Castillo

Israel Science Foundation (1350/12)

  • Shlomo Wagner

National Institute of Mental Health (R01-MH093725)

  • Joseph D Buxbaum

National Institute of Mental Health (R01-MH101584)

  • Joseph D Buxbaum

Autism Speaks (8410)

  • Joseph D Buxbaum

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by the National Institutes of Health/National Institute of Mental Health grants R01 MH093725 and R01 MH101584 to JDB, R01 MH081935 and R01 DA017392 to PEC, F31 NS073200 and T32 GM007288 to MEK, the Seaver Foundation to HHN, the Human Frontier Science Program (HFSP) RGP0019/2015 to HHN, JDB and SW, Autism Speaks 8410 to JDB, and by the Israel Science Foundation (SFN) grant 1350/12 to SW. In addition, this study was supported by a generous gift from William G. Gibson and Paulina Rychenkova, PhD. We thank Dr. Mouna Maroun for her advice on the fear conditioning test, Dr. Jill Silverman for reviewing the manuscript, and Ms. Idil Ozturk, Ms. Ayesha Islam, and Ms. Deniz Bingul for their assistance in behavioral scoring.

Ethics

Animal experimentation: All animal procedures were approved by the Institutional Animal Care and Use Committees at the Icahn School of Medicine at Mount Sinai (protocol number: LA12-00270), at the University of Haifa (Protocol number: 194-10), and at the Albert Einstein College of Medicine (Protocol number: 20130506)

Reviewing Editor

  1. Peggy Mason, University of Chicago, United States

Publication history

  1. Received: June 17, 2016
  2. Accepted: January 2, 2017
  3. Version of Record published: January 31, 2017 (version 1)

Copyright

© 2017, Harony-Nicolas et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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