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Atypical behaviour and connectivity in SHANK3-mutant macaques

Nature volume 570, pages 326–331 (2019)Cite this article

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Abstract

Mutation or disruption of the SH3 and ankyrin repeat domains 3 (SHANK3) gene represents a highly penetrant, monogenic risk factor for autism spectrum disorder, and is a cause of Phelan–McDermid syndrome. Recent advances in gene editing have enabled the creation of genetically engineered non-human-primate models, which might better approximate the behavioural and neural phenotypes of autism spectrum disorder than do rodent models, and may lead to more effective treatments. Here we report CRISPR–Cas9-mediated generation of germline-transmissible mutations of SHANK3 in cynomolgus macaques (Macaca fascicularis) and their F1 offspring. Genotyping of somatic cells as well as brain biopsies confirmed mutations in the SHANK3 gene and reduced levels of SHANK3 protein in these macaques. Analysis of data from functional magnetic resonance imaging revealed altered local and global connectivity patterns that were indicative of circuit abnormalities. The founder mutants exhibited sleep disturbances, motor deficits and increased repetitive behaviours, as well as social and learning impairments. Together, these results parallel some aspects of the dysfunctions in the SHANK3 gene and circuits, as well as the behavioural phenotypes, that characterize autism spectrum disorder and Phelan–McDermid syndrome.

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Fig. 1: Generation and germline transmission of macaques with SHANK3 mutations.
Fig. 2: Sleep disturbances and altered home-cage activity in SHANK3-mutant macaques.
Fig. 3: Impaired social interaction and reduced vocalization in SHANK3 mutants.
Fig. 4: Eye-tracking properties in SHANK3-mutant macaques.
Fig. 5: Dysregulated global and local connectivity in SHANK3-mutant macaques.

Data availability

All data are available in the main text or the Supplementary Information. All sequencing data, images, code, and materials used in the analysis are available to researchers for the purpose of reproducing or extending the analyses.

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Acknowledgements

We thank L. Harp McGovern and the late P. J. McGovern for their vision and support; F. Zhang for advice and reagents for CRISPR; D. G. Amaral for sharing image resources for creating eye-tracking stimuli; J. Bachevalier for advice on behavior testing; E. A. Murray for guidance on the Wisconsin General Test Apparatus assay; G. Genovese and R. Rosario for support with statistical and bioinformatics analysis; S. Sharma, S. Lall and S. Krol for critical reading of the manuscript; L. Dennis, N. Nien-Chu Espinoza, S. Yang, A. Chakrabarti, N. Joshi and Y. Fukumura for behavioral scoring; X. Wu, X. Ding, L. Cheng and X. Liu for technical support; the veterinary team of Blooming-Spring for excellent colony management and technical support; and S. E. Hyman (Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard), N. Sanjana (NYU) and L. Cong (Stanford University) and members of the Feng laboratory at MIT for critical discussion on this project. This work was supported by National Key R&D Program of China (2017YFC1307500); Shenzhen Overseas Innovation Team Project (KQTD20140630180249366); Guangdong Innovative and Entrepreneurial Research Team Program (2014ZT05S020). S.Y. and Q.K. was supported by Frontier and Innovation of Key Technology Project in Science and Technology Department of Guangdong Province (2014B020225007 and 2019B020235002); and Program for New Century Excellent Talents in University of Ministry of Education of the People’s Republic of China (NCET-12-1078). This work was also supported by the National Key R&D Program of China (2018YFA0107203 and 2017YFA0103802 to A.P.X., 2017YFA0103802 to W.L.); the External Cooperation Program of Chinese Academy of Sciences (172644KYSB20160026); International Partnership Program of Chinese Academy of Sciences (172644KYS820170004 to L.W., 172644KYSB20160175 to H.Z.); the Patrick J. McGovern Foundation; Hundred Talent Program of Chinese Academy of Sciences to H.Z.; the National Natural Science Foundation of China (81425016 to A.P.X., 31671119 to Z.L.); Shenzhen Science and Technology Innovation Commission grants (JCYJ20151030140325151 to H.Z.; GJHZ20160229200136090, JCYJ20170413165053031 to T.Y.; JCYJ20170413162938668 to Z.L.). Y. Zhou was supported by postdoctoral fellowships from the Simons Center for the Social Brain at MIT and Nancy Lurie Marks Family Foundation. G.F. is supported by the McGovern Institute for Brain Research at MIT, James and Patricia Poitras Center for Psychiatric Disorders Research at MIT, the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, and Edward and Kay Poitras. L.W. is also supported by Guangdong Provincial Key Laboratory of Brain Connectome and Behavior 2017B030301017, Shenzhen Discipline Construction Project for Neurobiology DRCSM [2016]1379, and Shenzhen-Hong Kong Institute of Brain Science.

Reviewer information

Nature thanks Thomas Bourgeron, Michael Platt and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

  1. Yang Zhou

    Present address: Montreal Neurological Institute & Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada

  2. These authors contributed equally: Yang Zhou, Jitendra Sharma, Qiong Ke, Rogier Landman

Authors and Affiliations

  1. Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yang Zhou, Minqing Jiang, Ting Yan, Ying Zou, Dongdong Xu, Yanyang Bai, Wenjing Ji, Zhonghua Lu, Liping Wang & Huihui Zhou

  2. McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    Yang Zhou, Rogier Landman, William Menegas, Tomomi Aida, Shivangi Parmar, Julia B. Hyman, Adrian Fanucci-Kiss, Olivia Meisner, Dongqing Wang, Sheeba A. Anteraper, Robert Desimone & Guoping Feng

  3. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jitendra Sharma, Shivangi Parmar, Julia B. Hyman, Adrian Fanucci-Kiss, Olivia Meisner, Dongqing Wang, Sheeba A. Anteraper, Mriganka Sur, Robert Desimone & Guoping Feng

  4. Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jitendra Sharma & Mriganka Sur

  5. Simons Center for the Social Brain, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jitendra Sharma & Mriganka Sur

  6. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA

    Jitendra Sharma

  7. Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-Sen University, Guangzhou, China

    Qiong Ke, Hong Chen, Xinqiang Lai, Weiqiang Li, Lihua Huang & Andy Peng Xiang

  8. Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China

    Qiong Ke, Weiqiang Li & Andy Peng Xiang

  9. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Rogier Landman & Guoping Feng

  10. College of Veterinary Medicine, South China Agricultural University, Guangzhou, China

    Jingli Yuan, Yan Huang, Yaqing Li & Shihua Yang

  11. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA

    David S. Hayden & John W. Fisher III

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Contributions

G.F., S.Y. and Y. Zhou conceived the study, and R.D., G.F. and H.Z. provided ongoing guidance on the design. S.Y. and A.P.X. oversaw the generation of mutant monkeys. H.Z. oversaw the characterization of mutant monkeys. Y. Zhou carried out CRISPR design and validation. S.Y., Q.K., H.C., Y. Zhou, J.Y., D.X., Y.H. and A.P.X. generated mutant monkeys. Y. Zhou and D.W. designed and performed molecular, protein, sequencing and off-target analyses. R.L., J.S., Y. Zhou, G.F. and R.D. designed and analysed behavioural experiments and MRI assays. H.Z., L.W., Z.L., T.Y., Y. Zou, M.J., W.J., Y.B., W.M., T.A., Y.L., X.L., W.L., L.H., S.A.A. and M.S. participated in the design or execution of some of the behavioural experiments. R.L., D.S.H., J.W.F. III, J.B.H., A.F.-K., O.M. and S.P. managed and performed behavioural scoring. Y. Zhou, R.L., R.D., J.S. and G.F. wrote the manuscript with input from all authors.

Corresponding authors

Correspondence to Huihui Zhou, Andy Peng Xiang, Guoping Feng or Shihua Yang.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Original images for western blots and DNA gel.

Original images for western blots and DNA gel electrophoresis corresponding to specific figure panels as indicated are presented without cropping or further processing, such as adjusting of brightness and contrast.

Extended Data Fig. 2 Summary of founder and germline-transmitted SHANK3 mutations.

a, Schematic showing the structure of the wild-type macaque SHANK3 gene and magnified panels with the annotated sequence of the gRNA and protospacer adjacent motif (PAM) for both strands within exon 21. b, SURVEYOR assay showing SpCas9-mediated indels in cultured cynomolgus monkey primary skin fibroblasts with indicated gRNAs. c, Genotyping PCR results of individual monkey embryos injected with a mixture of SpCas9 mRNA, SHANK3 gRNA no. 1 and gRNA no. 2. Asterisks indicate effectively edited embryos. d, Number of injected embryos, transferred recipients and newborn macaques in this study. e, SHANK3-mutant macaques have similar body weights to those of age-matched wild-type controls. f, Pie charts of genotype (indels) of DNA from semen from mutant macaques M2 and M3 show a similar pattern to their respective blood samples.

Source Data

Extended Data Fig. 3 Alignment of partial SHANK3 sequence genotyped from skin DNA.

a–e, Alignment of ten representative reads of SHANK3 sequence genotyped from a skin biopsy of each mutant monkey with reference SHANK3 sequence from wild-type monkey.

Source Data

Extended Data Fig. 4 Statistical analysis of western blots using brain lysates prepared from V1 biopsy of macaques.

a, b, Quantification of blots was based on five technical repeats using the same V1 protein sample with N-terminal (a) and C-terminal (b) antibodies. Values were normalized to those of the C1 control monkey. α-Tubulin, as loading control, was run on the same gel. Data are presented as mean ± s.e.m., n = 5 technical repeats using sample for the 2 controls and 5 SHANK3 mutants, *P < 0.05, **P < 0.01, ***P < 0.001; ns, not significant; one-way analysis of variance (ANOVA) with Bonferroni post hoc test.

Source Data

Extended Data Fig. 5 Representative traces of overall activity.

a–l, Representative and enlarged traces of overall activity recorded by motion watches across multiple days from a control macaque and all five SHANK3 mutants. A.U, arbitrary units.

Source Data

Extended Data Fig. 6 Behavioural parameters of monkeys during the first and second five minutes of interaction.

a, Schematic showing the two interconnected cages used for habituation of individual macaques and subsequent paired social-interaction assay. b–l, Separate behavioural parameters of monkeys in control and SHANK3-mutant groups during the first five minutes of interaction. m, No difference in social behaviours (including chasing, following, circling, fleeing and play) during the second five minutes of interaction. In all panels, n = 6 macaques for control group; n = 5 macaques for the SHANK3-mutant group. Data are presented as mean ± s.e.m., two-tailed Mann–Whitney U-test.

Extended Data Fig. 7 Behavioural parameters of probe macaques when paired with wild-type or SHANK3-mutant monkeys during the first five minutes of interaction.

a–k, Total durations of chasing (a), following (b), circling (c), fleeing (d), play (e), attacking (f), anogenital inspection (g), rump presentation (h), mounting (i), receiving grooming (j) and giving grooming (k). In all panels, n = 10 probe monkeys paired individually with 6 wild-type macaques from the control group and 5 macaques from the SHANK3-mutant group. Data are presented as mean ± s.e.m., *P < 0.05, **P < 0.01; two-tailed Mann–Whitney U-test.

Extended Data Fig. 8 Performance of control and mutant monkeys in the discrimination and reversal tasks using WGTA.

a, Task design. b, c, Total days (b) and total trials (c) required for macaques to pass the black–white discrimination test of the WGTA. d, e, Total days (d) and total trials (e) required for macaques to pass the black–white reversal test of the WGTA (>75%-correct trial). f, A graphical model for Bayesian nonparametric multitarget tracking. Priors omitted for brevity. Arrows pointing to ellipses indicate continuation to the next time step. g, Diagram of the eye-tracking box. In b–e, n = 6 macaques for control group; n = 3 macaques for the SHANK3-mutant group. Data are presented as mean ± s.e.m.; Mann–Whitney U-test. Coloured squares indicate individual macaques with SHANK3 mutations.

Extended Data Fig. 9 Performance of controls and SHANK3 mutants in the Hamilton search task.

a, Schematic and flow chart of the Hamilton search task. b, Performance of macaques in the ‘set-breaking’ test of the Hamilton search task. M3 showed no improvement (delta value = 0). ‘Delta’ is set to measure the learning of the monkey across five test days, calculated by increase of the number of trials in which the monkey opened the correct well on the first try. c, Percentage of correct trials on the ‘forced set-breaking’ test of the Hamilton search task, from monkeys across five test days. d, Number of monkeys that reached a 75%-correct rate on the fifth day of the forced set-breaking test. *P < 0.05, Two-tailed χ2 test (P = 0.023) was applied to determine the statistical difference between groups.

Extended Data Fig. 10 Structural MRI and seed-based functional MRI analysis of macaque brains.

a–c, No difference in white matter volume (a) and cerebrospinal fluid volume (b), but a reduced volume of grey matter (c), in SHANK3 mutants, relative to control macaques. In a–c, n = 6 macaques for control group; n = 5 macaques for SHANK3-mutant group. Data are presented as mean ± s.e.m., **P < 0.01, Mann–Whitney U-test. Coloured squares indicate individual mutant macaques. d, e, Sagittal, coronal and axial views of averaged functional MRI image from six control macaques (d) and five SHANK3 mutants (e), using the putative posterior cingulate cortex as seed region. f, Sagittal, coronal and axial views of averaged functional MRI image show blood-oxygen-level-dependent signals in the posterior cingulate cortex that are greater in mutants than in controls. In d –f, the putative posterior cingulate cortex regions are highlighted by arrows.

Supplementary information

Supplementary Tables

This file contains Supplementary Tables 1-3. Supplemental Table 1: Off target analysis of SHANK3 gRNA #1 and gRNA #2. Supplemental Table 2: Ethogram example from the mutant monkey M5. Supplemental Table 3: Power analysis of data sets with statistical significance.

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Zhou, Y., Sharma, J., Ke, Q. et al. Atypical behaviour and connectivity in SHANK3-mutant macaques. Nature 570, 326–331 (2019). https://doi.org/10.1038/s41586-019-1278-0

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