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Reduced sociability and social agency encoding in adult Shank3-mutant mice are restored through gene re-expression in real time

Nature Neuroscience volume 24, pages 1243–1255 (2021)Cite this article

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Abstract

Despite a growing understanding of the molecular and developmental basis of autism spectrum disorder (ASD), how the neuronal encoding of social information is disrupted in ASD and whether it contributes to abnormal social behavior remains unclear. Here, we disrupted and then restored expression of the ASD-associated gene Shank3 in adult male mice while tracking the encoding dynamics of neurons in the medial prefrontal cortex (mPFC) over weeks. We find that Shank3 disruption led to a reduction of neurons encoding the experience of other mice and an increase in neurons encoding the animal’s own experience. This shift was associated with a loss of ability by neurons to distinguish other from self and, therefore, the inability to encode social agency. Restoration of Shank3 expression in the mPFC reversed this encoding imbalance and increased sociability over 5–8 weeks. These findings reveal a neuronal-encoding process that is necessary for social behavior and that may be disrupted in ASD.

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Fig. 1: Neuronal encoding of social information in the mPFC and its relation to Shank3 expression.
Fig. 2: Diminished Shank3 expression leads to diminished neuronal encoding of other experience and diminished distinction between other and self.
Fig. 3: Neuronal encoding of the other’s experience is social-context-specific.
Fig. 4: Increase in Shank3 expression is associated with increased sociability.
Fig. 5: Restoration of social behavior is dependent on the neuronal encoding of self and other.
Fig. 6: Controls for time progression and familiarity using Shank3fx/+; creER−/− mice.
Fig. 7: Restoration of sociability is dependent on social agency encoding in the mPFC.

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Data availability

The behavioral and neuronal data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

All software used in this study are listed in the Reporting Summary along with their versions. The primary MATLAB code used to perform the statistical and data analyses in this study is available from the corresponding author upon reasonable request.

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Acknowledgements

We thank A. Aristarkhova, B. Burcescu, J. Grondin, E. Mastrobattista, C. Ortega, J. St Fleur and M. Mejdell for assisting in the experimentation and data preprocessing. G.F. is funded by HHMI, S.W.L. is funded by the Autism Science Foundation Fellowship and Z.M.W. is supported by NIH R01HD059852, NIH R01NS091390, the Presidential Early Career Award for Scientists and Engineers and the Whitehall Foundation.

Author information

Author notes

  1. These authors contributed equally: Daniel K. Lee, S. William Li, Firas Bounni, Gabriel Friedman.

Authors and Affiliations

  1. Harvard-MIT Division of Health Sciences and Technology, Boston, MA, USA

    Daniel K. Lee & Ziv M. Williams

  2. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Daniel K. Lee, S. William Li, Firas Bounni, Gabriel Friedman, Mohsen Jamali, Michael A. Stankovich & Ziv M. Williams

  3. Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA

    S. William Li

  4. Northeastern University, Boston, MA, USA

    Leah Strahs, Omer Zeliger & Jack Demaree

  5. Harvard University, Cambridge, MA, USA

    Pauline Gabrieli

  6. Program in Neuroscience, Harvard Medical School, Boston, MA, USA

    Ziv M. Williams

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Contributions

S.W.L., F.B., L.S., O.Z., P.G., M.A.S. and J.D. performed the experiments. D.K.L., S.W.L., G.F., M.J. and P.G. analyzed the data. S.W.L. developed the conditional gene knockout studies. D.K.L., G.F. and S.W.L. edited the manuscript. Z.M.W. conceived and designed the study, wrote the manuscript and supervised all aspects of the research.

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Correspondence to Ziv M. Williams.

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Peer review information Nature Neuroscience thanks Camilla Bellone and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Animal preparation and electrophysiological recordings.

a, Illustration depicting the Cre-lox system and its use in restoring Shank3 expression in adult mice. Cre-dependent FLEx switch constructs capable of controlling Shank3 expression are made by creating Shank3fx/+:CreER± mice in which Cre recombinase (CRE) is fused to an estrogen receptor (ER) protein. Here, an inverted PDZ domain (the membrane anchoring portion of SHANK3) is ‘floxed’ by two lox sites and, therefore, renders the mice heterozygous Shank3. CRE-ER is expressed constitutively. Normal Shank3 expression is restored by either delivering systemic TMX or local endoxifen to the mice. Binding of endoxifen to the ER receptor leads to dislodgement of the associated heat shock protein (HSP) from CRE which then allows it to enter the nucleus. Once in the nucleus, CRE leads the floxed PDZ sequence, flanked by two loxP sites, to be inverted through recombinase-mediated cassette exchange. Finally, inversion of the PDZ sequence leads to normal production of SHANK3. b, Representative waveform morphologies and recording locations. Displayed left is a histological section with bilateral electrolytic lesions indicating the microelectrode recording locations from the medial prefrontal cortex (mPFC). Right are representative waveform morphologies from six putative neurons recorded each from the mPFC of WT and HET mice. c, Shank3fx/+:CreER± mice were created by crossing CAGG-Cre-ER± with Shank3fx/fx mice. Shank3fx/+:CreER−/− mice were created for control comparison. Only littermates were used for comparisons and all were male mice.

Extended Data Fig. 2 Neuronal responses to experience valence, agency, and identity.

a, Neurons that responded to other’s experiences based on variations in the recorded animal’s own enclosure. Overlap in encoding across neurons is displayed on the left and their total numbers are shown to the right. Overall, only a few neurons (n = 7) displayed a difference in response to the other’s experience based on which specific enclosure the recorded animal was simultaneously placed in (three-way ANOVA, p < 0.0125 with post-hoc comparisons). b, Neuronal responses based on the other’s social identity. Breakdown of neurons that responded to the other’s identity (familiar and non-familiar) and their relation to neurons that responded to the other’s experience. On the left are the distribution of neurons that responded to the other’s experience. While many of the neurons that responded to the other’s experience also responded to the other’s identity (11.6%), some neurons responded to the other’s identity alone (5.4%; that is, irrespective of the other’s experience). On the right are the distribution of neurons that responded to the other’s identity based on whether the other animals were specifically familiar or non-familiar to recorded mouse. c, Relative proportions of all task modulated neurons using a three-way ANOVA that accounted for all terms describing experience valence (positive vs. negative), social agency (self vs. other) and social context/identity (familiar vs. non-familiar vs. totem) with post-hoc comparisons and correction for multiple comparisons at a p < 0.0125. To the left are the numbers of neurons that responded to self- or other-experience valences. To the right are the remaining top six most common feature combinations. For example, while many neurons responded to another’s aversive vs. appetitive experience, some neurons only responded to the other’s experience when they were familiar to the recorded animal. Other neurons, by comparison, only responded to differences between familiar vs. non-familiar animals while displaying little modulation to their specific experience. In total, 112 neurons and 131 neurons displayed task-related modulation in the WT and Shank3 mice, respectively.

Extended Data Fig. 3 Neural modulation over the course and within the trials.

a, Absolute difference in activity (Z-score) for other experience per cell over the time course of the trial. Here, neuronal responses are broken down into 5 second intervals in order to illustrate the time progression of neural modulation. While there was a slightly lower degree of modulation at the very end of the trial, this difference was not significant (repeated measures ANVOA, p > 0.2). Similarly, we find no difference in the total number of neurons that displayed significant modulation over the course of the trial (Chi-square, p > 0.5). The directions of the arrows indicate whether responses were stronger for the aversive (point up) compared to appetitive (point down) other experiences. To evaluate the effect that the animal’s own prior experience may have had on neuronal encoding of the other’s experience, we also compared all possible transitions combinations between self- followed by other-experience valence (for example, self-appetitive followed by other-aversive, self-aversive followed by other-aversive, etc.). Here, we find that only 2 neurons in the WT mice that responded to other-experience were also affected by specific past self-experience (three-way ANOVA, p < 0.0125). In other words, the animal’s own experience in one trial influenced neuronal responses the following trial in only 1.8% of the neurons. Similarly, we find only 1 neuron in the WT mice whose response to self-experience was also affected by past other-experience; together suggesting that the past trial condition did not influence neuronal response under this task. b, This Figure follows the same convention as in Fig. 3d. Here, however, neural activity (Z-score) are divided into successive, non-overlapping 5 second windows over the 20 second trial-span.

Extended Data Fig. 4 Proportional contribution of neurons across animals.

To allow for comparison across animals, the relative contribution of each mouse to the overall group ratio for self vs. other encoding are shown in percentages. Thus, a larger percentage means that they contributed relatively more to the proportion of other-encoding neurons whereas a smaller percentage means that they contributed relatively more to the proportion of self-encoding neurons. Additionally, we performed a within-group vs. between-group comparison to evaluate more directly whether differences in the proportions of neurons could be explained by potential dissimilarities in recording quality or variations in anatomical localization between animals. For example, if recordings were indeed made from slightly different areas or subpopulations of cells, then we should observe a similar variance between individual animals that belonged to the same genotype (that is, HET) compared to between individual animals that belonged to the different genotypes (that is, HET vs. WT). In other words, variability in the proportions of neurons found between one WT animal and another WT animal should be similar to that found between one WT animal and another HET animal. Examining the proportion of neurons that responded to other-aversive vs. other-appetitive experience, however, we find that the difference between animals within the WT group was significantly smaller than that between the WT and HET group (two-sample F-test for equality of variance; f-stat = 0.20, p = 0.0076). These observations therefore support the main findings and controls further below that those differences in encoding properties between animals were due to differences in Shank3 expression rather than a systematic variation in subpopulations sampled.

Extended Data Fig. 5 Robustness of neuronal encoding within the population across different statistical methodologies.

a, To validate our results and further delineate the response characteristics of the neurons, we repeated the ANOVA analyses at different statistical thresholds from p = 0.05 to 0.0025. Across conditions, other-to-self ratio was relatively stable, with HET and WT results ranging from 1:2.3 to 1:4.6, and 1.1:1 to 1:1.7, respectively. At all significance thresholds, the other-to-self ratio of HET was significantly smaller than that of WT (chi-square, p < 0.05). b, Support vector machines (SVMs) with nonlinear kernels were used to decode neural population activity on validation trials not used for model training. The temporal dynamic of neural population predictions is presented in relation to the beginning, middle and end of the trials and are broken down into the three primary features that described the animals’ social interactions during the task; their experience valence, social agency and identity. Using neural population activity from validation trials not used for model fitting, we find that activity from the neural population could accurately predict the social agency of the animals’ experience with an accuracy of 70.9 ± 5% at trial onset (permutation test, p < 0.001). In other words, the neural population could be used to reliably distinguish one’s own experience from that of another. We also found that the neural population could predict the specific valence of the animals’ experience with an accuracy of 76.8 ± 3% (permutation test, p < 0.001), suggesting that they reliably distinguished whether the experience was appetitive or aversive. Last, the neural population predicted the social context with an accuracy of 78.2 ± 2% (permutation test, p < 0.001). Overall, all three primary task features (agency, experience valence and social context/identity) were most accurately decoded from the population’s response at the beginning of the trials (that is, within the first 1–6 seconds; permutation test, ** p < 0.001). Prediction accuracy then gradually dropped over the middle to end of the trial. While decoding accuracy was significant during the middle of the trial for valence and social identity (permutation test, * p < 0.01), decoding performance for all three features was at chance by the end of the trial. Representation of these task features was therefore most prominent at the start of the trials (that is, at which time these conditions were most salient), and then gradually diminished by the end of the trial. To determine significance and error, this process was repeated 1000 times and compared to models trained on neuronal data that was randomly shuffled. Error bars indicate 95% confidence interval.

Extended Data Fig. 6 WT animals differentiate between others’ aversive and appetitive experiences.

a, To understand whether animals recognized another animal’s experience and to allow for comparison with our main results, the animals performed a place preference/avoidance task where subjects were presented with two age and sex-matched familiar conspecific partners undergoing either an appetitive (food-baited enclosure) or aversive (confined tube enclosure) experience. The percent time spent by the animals investigating the aversive and appetitive enclosures when in the presence of another animal is shown here. While the WT displayed a significant difference the time spent investigating the specific enclosures when compared to HET animals (*two-tailed unpaired test; ts(15) = −2.79; p = 0.014), there was no difference in approach behavior when familiar conspecifics were replaced with inanimate totems in the enclosures (ANOVA, p > 0.5 post-hoc comparison). b, We confirmed that the WT animals differentiated the other’s experiences based on respiratory rate. Using a mouse jacket (Lomir Biomedical) and pulse sensor (World Famous Electronics; digitized at 500 Hz then band-passed at 1–5 Hz), we find a significant difference in the animal’ respiratory rate when the other animal was having an aversive vs. appetitive experience (*ANOVA, p = 0.0031). c, The panel above displays the sequence of behavioral testing, plasma collection and corticosterone analysis/quantification by ELISA. The panel below displays the plasma levels collected across all WT and HET animals. Here, the levels are given based on whether the animals observed the other having an appetitive vs. aversive experience (two-tailed unpaired t-tests; * p = 0.021, ** p < 0.01, n.s. p = 0.23).

Extended Data Fig. 7 Evaluating for Shank3 dependent differences in anxiety phenotype between the WT and HET mice.

Elevated zero-maze testing was performed on the WT and HET mice. Overall, HET mice displayed no evidence of elevated anxiety compared to WT based on the proportion of time spent in the open areas, number of visits to the open areas, or percent of time spent head-dipping (two-tailed unpaired t-tests; p > 0.5).

Extended Data Fig. 8 Shank3 dependent changes in proportion of neuronal encoding and sociability.

a, Each curve represents the raw proportions of other-encoding and self-encoding neurons at weekly intervals after TMX administration (rather than ratio; with the sum equaling one). Time points in which there was a significant difference are underlined in red (chi-square tests, p < 0.01). The proportion of neurons that were task-modulated or which responded to variations in familiarity did not significantly change in the weeks after TMX administration for Shank3fx/+:CreER± mice. Specifically, the percentage of task modulating neurons increased only marginally from 73% (n = 131 of 180, pre-tamoxifen) to 74% (n = 84 of 114, post TMX; chi-square, χ2(1) = 0.29, p = 0.86; Extended Data Fig. 3). Likewise, the percentage of neurons that responded to variations in the other’s familiarity remained almost identical (30%, n = 39 of 131, pre-tamoxifen to 29.8%, n = 25 of 84, post-tamoxifen; chi-square, χ2(1) = 2.0 × 10−6, p = 1.0). b, Above, the net amount of time spent with the other animal vs. inanimate object out of the 120 seconds for testing. Below, three-chamber testing was obtained from the same individual animals over the consecutive course of 8 weeks after TMX administration. Time points in which there was a significant difference are underlined in red (paired t-tests, * ts(19) = 3.01; p = 0.0046). c, To further validate results from the Shank3fx/+:CreER−/− mice and to confirm that changes in behavior after TMX was not explained by task familiarity or time-progression, HET mice also received corn oil (that is, vehicle) instead of TMX. Here, the HET (Cre±) mice displayed no change in behavior over time (one-sample t-tests, p > 0.5). d, In the top panel, the curve represents the proportion of time spent in the chamber of the other animal or inanimate object ± standard errors of the mean at weekly intervals. In the bottom panel, each curve represents the percentage of other-encoding and self-encoding neurons at weekly intervals. The horizontal line represents an equal proportion of neurons. No time point demonstrated a significant difference in either behavior or sociability when compared to all other points (one-sample t-tests, n.s.; p > 0.2). e, The proportion of time interacting with the other animal as defined by the amount of time at which the subject mouse was in proximity (within 3 cm) and oriented towards the other animal (within 20 degrees). HET mice displayed a gradual and significant increase in the amount of time spent interacting with the other animal after TMX (paired t-test, p < 1.0 × 10−4). These findings were not apparent when testing the Shank3fx/+:CreER−/− mice which lacked the Cre-lox system after TMX (unpaired t-test, p > 0.5). More remarkably, by 8 weeks after TMX administration, the amount of time spent interacting with the other by the HET mice was essentially indistinguishable from that of the WT mice (unpaired t-test, p > 0.5). All error bars indicate s.e.m.

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Lee, D.K., Li, S.W., Bounni, F. et al. Reduced sociability and social agency encoding in adult Shank3-mutant mice are restored through gene re-expression in real time. Nat Neurosci 24, 1243–1255 (2021). https://doi.org/10.1038/s41593-021-00888-4

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