Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Diversification of molecularly defined myenteric neuron classes revealed by single-cell RNA sequencing

Nature Neuroscience volume 24, pages 34–46 (2021)Cite this article

Subjects

Abstract

Autonomous regulation of the intestine requires the combined activity of functionally distinct neurons of the enteric nervous system (ENS). However, the variety of enteric neuron types and how they emerge during development remain largely unknown. Here, we define a molecular taxonomy of 12 enteric neuron classes within the myenteric plexus of the mouse small intestine using single-cell RNA sequencing. We present cell–cell communication features and histochemical markers for motor neurons, sensory neurons and interneurons, together with transgenic tools for class-specific targeting. Transcriptome analysis of the embryonic ENS uncovers a novel principle of neuronal diversification, where two neuron classes arise through a binary neurogenic branching and all other identities emerge through subsequent postmitotic differentiation. We identify generic and class-specific transcriptional regulators and functionally connect Pbx3 to a postmitotic fate transition. Our results offer a conceptual and molecular resource for dissecting ENS circuits and predicting key regulators for directed differentiation of distinct enteric neuron classes.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Molecular definition of 12 enteric neuron classes in the mouse small intestine myenteric plexus.
Fig. 2: Gene categories conferring functional characteristics in enteric neuron classes.
Fig. 3: Immunohistochemical validation of marker genes for enteric neuron classes.
Fig. 4: Assessment of IPAN characteristics in ENCs 6, 7 and 12.
Fig. 5: Single-cell transcriptome analysis of the developing ENS reveals transcriptional programs of generic cell states.
Fig. 6: ENC identities emerge through binary branching followed by postmitotic neuronal diversification.
Fig. 7: Loss of PBX3 expression impairs the ENC8/9 to ENC12 transition.
Fig. 8: Schematic of the major principle of neuronal diversification in the developing CNS versus ENS.

Data availability

Raw sequence and processed data for Wnt1Cre;R26R-Tomato (E15.5 and E18.5) and for Baf53bCre;R26R-Tomato (P21) are available on the Gene Expression Omnibus database under the identifier GSE149524 and accession number SRP258962 at http://ncbi.nlm.nih.gov/sra/SRP258962. Raw sequencing data from Wnt1Cre;R26R-Tomato P21 and P23 animals is available under accession SRP135960 at https://www.ncbi.nlm.nih.gov/sra/SRP135960.

References

  1. Furness, J. B. The enteric nervous system and neurogastroenterology. Nat. Rev. Gastroenterol. Hepatol. 9, 286–294 (2012).

    CAS  PubMed  Google Scholar 

  2. Veiga-Fernandes, H. & Pachnis, V. Neuroimmune regulation during intestinal development and homeostasis. Nat. Immunol. 18, 116–122 (2017).

    CAS  PubMed  Google Scholar 

  3. Furness, J. B. Types of neurons in the enteric nervous system. J. Auton. Nerv. Syst. 81, 87–96 (2000).

    CAS  PubMed  Google Scholar 

  4. Sang, Q. & Young, H. M. Chemical coding of neurons in the myenteric plexus and external muscle of the small and large intestine of the mouse. Cell Tissue Res. 284, 39–53 (1996).

    CAS  PubMed  Google Scholar 

  5. Sang, Q., Williamson, S. & Young, H. M. Projections of chemically identified myenteric neurons of the small and large intestine of the mouse. J. Anat. 190, 209–222 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Qu, Z. D. et al. Immunohistochemical analysis of neuron types in the mouse small intestine. Cell Tissue Res. 334, 147–161 (2008).

    CAS  PubMed  Google Scholar 

  7. Furness, J. B., Jones, C., Nurgali, K. & Clerc, N. Intrinsic primary afferent neurons and nerve circuits within the intestine. Prog. Neurobiol. 72, 143–164 (2004).

    CAS  PubMed  Google Scholar 

  8. Knowles, C. H., Lindberg, G., Panza, E. & De Giorgio, R. New perspectives in the diagnosis and management of enteric neuropathies. Nat. Rev. Gastroenterol. Hepatol. 10, 206–218 (2013).

    CAS  PubMed  Google Scholar 

  9. Rivera, L. R., Poole, D. P., Thacker, M. & Furness, J. B. The involvement of nitric oxide synthase neurons in enteric neuropathies. Neurogastroenterol. Motil. 23, 980–988 (2011).

    CAS  PubMed  Google Scholar 

  10. Fattahi, F. et al. Deriving human ENS lineages for cell therapy and drug discovery in Hirschsprung disease. Nature 531, 105–109 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Burns, A. J. et al. White paper on guidelines concerning enteric nervous system stem cell therapy for enteric neuropathies. Dev. Biol. 417, 229–251 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Obermayr, F., Hotta, R., Enomoto, H. & Young, H. M. Development and developmental disorders of the enteric nervous system. Nat. Rev. Gastroenterol. Hepatol. 10, 43–57 (2013).

    CAS  PubMed  Google Scholar 

  13. Uesaka, T., Nagashimada, M. & Enomoto, H. Neuronal differentiation in schwann cell lineage underlies postnatal neurogenesis in the enteric nervous system. J. Neurosci. 35, 9879–9888 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Le Dréau, G. & Martí, E. Dorsal-ventral patterning of the neural tube: a tale of three signals. Dev. Neurobiol. 72, 1471–1481 (2012).

    PubMed  Google Scholar 

  15. Pham, T. D., Gershon, M. D. & Rothman, T. P. Time of origin of neurons in the murine enteric nervous system: sequence in relation to phenotype. J. Comp. Neurol. 314, 789–798 (1991).

    CAS  PubMed  Google Scholar 

  16. Bergner, A. J. et al. Birthdating of myenteric neuron subtypes in the small intestine of the mouse. J. Comp. Neurol. 522, 514–527 (2014).

    CAS  PubMed  Google Scholar 

  17. Memic, F. et al. Transcription and signaling regulators in developing neuronal subtypes of mouse and human enteric nervous system. Gastroenterology 154, 624–636 (2018).

    CAS  PubMed  Google Scholar 

  18. Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhan, X. et al. Generation of BAF53b-Cre transgenic mice with pan-neuronal Cre activities. Genesis 53, 440–448 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Paul, A. et al. Transcriptional architecture of synaptic communication delineates GABAergic neuron identity. Cell 171, 522–539 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Cardoso, V. et al. Neuronal regulation of type 2 innate lymphoid cells via neuromedin U. Nature 549, 277–281 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Klose, C. S. N. et al. The neuropeptide neuromedin U stimulates innate lymphoid cells and type 2 inflammation. Nature 549, 282–286 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Muller, P. A. et al. Cross-talk between muscularis macrophages and enteric neurons regulates gastrointestinal motility. Cell 158, 300–313 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Neureither, F., Stowasser, N., Frings, S. & Möhrlen, F. Tracking of unfamiliar odors is facilitated by signal amplification through anoctamin 2 chloride channels in mouse olfactory receptor neurons. Physiol. Rep. 5, e13373 (2017).

    PubMed  PubMed Central  Google Scholar 

  25. Alcaino, C. et al. A population of gut epithelial enterochromaffin cells is mechanosensitive and requires Piezo2 to convert force into serotonin release. Proc. Natl Acad. Sci. USA 115, E7632–E7641 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Born, G. et al. Modulation of synaptic function through the α-neurexin-specific ligand neurexophilin-1. Proc. Natl Acad. Sci. USA 111, E1274–E1283 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Creutz, C. E. et al. The copines, a novel class of C2 domain-containing, calcium-dependent, phospholipid-binding proteins conserved from Paramecium to humans. J. Biol. Chem. 273, 1393–1402 (1998).

    CAS  PubMed  Google Scholar 

  28. Gerke, V., Creutz, C. E. & Moss, S. E. Annexins: linking Ca2+ signalling to membrane dynamics. Nat. Rev. Mol. Cell Biol. 6, 449–461 (2005).

    CAS  PubMed  Google Scholar 

  29. Chan, K. Y. et al. Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci. 20, 1172–1179 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Nurgali, K., Stebbing, M. J. & Furness, J. B. Correlation of electrophysiological and morphological characteristics of enteric neurons in the mouse colon. J. Comp. Neurol. 468, 112–124 (2004).

    PubMed  Google Scholar 

  31. Furness, J. B., Robbins, H. L., Xiao, J., Stebbing, M. J. & Nurgali, K. Projections and chemistry of Dogiel type II neurons in the mouse colon. Cell Tissue Res. 317, 1–12 (2004).

    CAS  PubMed  Google Scholar 

  32. Spencer, N. J. & Smith, T. K. Mechanosensory S-neurons rather than AH-neurons appear to generate a rhythmic motor pattern in guinea pig distal colon. J. Physiol. 558, 577–596 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Lasrado, R. et al. Lineage-dependent spatial and functional organization of the mammalian enteric nervous system. Science 356, 722–726 (2017).

    CAS  PubMed  Google Scholar 

  34. Rhee, J. W. et al. Pbx3 deficiency results in central hypoventilation. Am. J. Pathol. 165, 1343–1350 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Okamoto, T. et al. Extensive projections of myenteric serotonergic neurons suggest they comprise the central processing unit in the colon. Neurogastroenterol. Motil. 26, 556–570 (2014).

    CAS  PubMed  Google Scholar 

  36. Hao, M. M. & Young, H. M. Development of enteric neuron diversity. J. Cell. Mol. Med. 13, 1193–1210 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Arenas, E., Denham, M. & Villaescusa, J. C. How to make a midbrain dopaminergic neuron. Development 142, 1918–1936 (2015).

    CAS  PubMed  Google Scholar 

  38. Young, H. M. et al. Colonizing while migrating: how do individual enteric neural crest cells behave? BMC Biol. 12, 23 (2014).

    PubMed  PubMed Central  Google Scholar 

  39. Young, H. M., Jones, B. R. & McKeown, S. J. The projections of early enteric neurons are influenced by the direction of neural crest cell migration. J. Neurosci. 22, 6005–6018 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Laranjeira, C. et al. Glial cells in the mouse enteric nervous system can undergo neurogenesis in response to injury. J. Clin. Invest. 121, 3412–3424 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Panman, L. et al. Transcription factor-induced lineage selection of stem-cell-derived neural progenitor cells. Cell Stem Cell 8, 663–675 (2011).

    CAS  PubMed  Google Scholar 

  42. Rivetti Di Val Cervo, P. et al. Induction of functional dopamine neurons from human astrocytes in vitro and mouse astrocytes in a Parkinson’s disease model. Nat. Biotechnol. 35, 444–452 (2017).

    PubMed  Google Scholar 

  43. Taniguchi, H. et al. A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex. Neuron 71, 995–1013 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Danielian, P. S., Muccino, D., Rowitch, D. H., Michael, S. K. & McMahon, A. P. Modification of gene activity in mouse embryos in utero by a tamoxifen-inducible form of Cre recombinase. Curr. Biol. 8, 1323–1326 (1998).

    CAS  PubMed  Google Scholar 

  45. Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010).

    CAS  PubMed  Google Scholar 

  46. Bialkowska, A. B., Ghaleb, A. M., Nandan, M. O. & Yang, V. W. Improved swiss-rolling technique for intestinal tissue preparation for immunohistochemical and immunofluorescent analyses. J. Vis. Exp. 113, e54161 (2016). (2016).

  47. Memic, F. et al. Ascl1 is required for the development of specific neuronal subtypes in the enteric nervous system. J. Neurosci. 36, 4339–4350 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhang, A. W. et al. Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling. Nat. Methods 16, 1007–1015 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Crow, M., Paul, A., Ballouz, S., Huang, Z. J. & Gillis, J. Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor. Nat. Commun. 9, 884 (2018).

    PubMed  PubMed Central  Google Scholar 

  54. Braschi, B. et al. Genenames.org: the HGNC and VGNC resources in 2019. Nucleic Acids Res. 47, D786–D792 (2019).

    CAS  PubMed  Google Scholar 

  55. Wolf, F. A. et al. PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Genome Biol. 20, 1–9 (2019).

    Google Scholar 

  56. Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).

    PubMed  PubMed Central  Google Scholar 

  57. Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F. & Theis, F. J. Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845–848 (2016).

    CAS  PubMed  Google Scholar 

  58. Stein-O’Brien, G. L. et al. Decomposing cell identity for transfer learning across cellular measurements, platforms, tissues and species. Cell Syst. 8, 395–411 (2019).

    PubMed  PubMed Central  Google Scholar 

  59. Stein-O’Brien, G. L. et al. PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF. Bioinformatics 33, 1892–1894 (2017).

    PubMed  PubMed Central  Google Scholar 

  60. La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Cell sampling was performed at the Eukaryotic Single-cell Genomics core facility at Science for Life Laboratory, Sweden, funded by the Swedish Research Council. The authors acknowledge support from Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council and Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. U.M. was supported by The Swedish Research Council (Vetenskapsrådet; 2016-03130), Swedish Medical Society, Ruth and Richard Julin Foundation, Ollie and Elof Ericssons Foundation, Magnus Bergvall Foundation, Brain Foundation (Hjärnfonden) and Åke Wiberg Foundation. A.M. was supported by Wenner-Gren Foundations. F.M. was supported by the Brain Foundation (Hjärnfonden). P.E. acknowledges the European Research Council (PainCells; 740491), the Swedish Research Council, a KAW Scholar and project grant, and the Wellcome Trust (200183). The imaging was performed in the Biomedicum Imaging Core with support from the Karolinska Institutet. We thank the Viral Vector Facility of the Neuroscience Center Zurich for excellent service and construction of AAV-virus vectors. We thank G. Tabacaru for laboratory assistance. We thank C. Villascusa (Karolinska Institutet) for sharing the Pbx3 mutant mice and J. Kaltschmidt (Stanford University) for antibodies. We acknowledge J. Frisén and S. Giatrellis for access and assistance with flow cytometry.

Author information

Author notes

  1. Rakesh Kumar

    Present address: Zoology Department, Ravenshaw University, Cuttack, India

  2. These authors contributed equally: Khomgrit Morarach, Anastassia Mikhailova.

Authors and Affiliations

  1. Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden

    Khomgrit Morarach, Anastassia Mikhailova, Viktoria Knoflach, Fatima Memic, Rakesh Kumar, Wei Li, Patrik Ernfors & Ulrika Marklund

Authors
  1. Khomgrit Morarach
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anastassia Mikhailova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Viktoria Knoflach
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fatima Memic
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rakesh Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Patrik Ernfors
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ulrika Marklund
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study concept and design: A.M., K.M., V.K. and U.M. Acquisition of data: A.M., F.M., K.M., V.K., R.K., W.L. and U.M. Analysis and interpretation of data: A.M., F.M., K.M., V.K., R.K., W.L. and U.M. Drafting of the manuscript: A.M., K.M., V.K., P.E. and U.M. Obtained funding: F.M., P.E. and U.M.

Corresponding author

Correspondence to Ulrika Marklund.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Supportive Data related to Fig. 1d–g.

a, Frequency distribution of the number of UMIs, detected genes and percent of mitochondrial genes per cell. Orange bars indicate proportion of cells passing the thresholding for each parameter. b, Box plots showing number of UMIs, detected genes and percent of mitochondrial genes per cell for each of the ENCs. Box-and-whisker plots indicate max-min (whiskers), 25-75 percentile (boxes) with median as a centre line. Points indicate outliers. c, UMAP depicting inferred female (Xist) and male (Eif2s3y, Ddx3y, Kdm5) cells. Pie-chart showing proportions of male and female cells (2:3 ratio). d, Bar-graph showing fraction of male and female cells in each ENC after normalized by total number of cells from each sex and scaled to 1. e, Label transfer relationship between previously proposed enteric neuron types (ENT)1-9 in Zeisel et al., 201818 and ENC1-12 presented in this study. Notably, ENC5 (Sst) and ENC11 (Npy/Th/Dbh) represent new clusters. ENT-clusters representing plausible excitatory (ENT4-6) and inhibitory (ENT2,3) motor neurons were not retained, but distributed into ENC1-4 and ENC8-9, respectively. UMI: Unique Molecular Identifier; ENT: Enteric Neuron Type; ENC: Enteric Neuron Class; UMAP: Uniform Manifold Approximation and Projection.

Extended Data Fig. 2 Supportive data related to Fig. 1h–j.

a, Feature plots related to Tac1+ clusters (ENC1-4). A gene set including Calb2 and stronger Ndufa4l2 demarcated ENC1-2 from ENC3-4, while Gda and Penk expression discriminated ENC2-4 from ENC1. ENC4 resembled ENC3, but displayed a unique expression of Fucosyltransferase 9 (Fut9) and the transcription factor Nfatc1. b, Feature plots related to Rprml+ clusters (ENC8-11). c, Heatmap representing CellAssign score for each cell (columns) to each functional type (rows). d, Rare cells assigned with maximum likelihood to interneuron 3 (IN_3, serotonin-producing), presented on UMAP. e, Feature plots displaying expression of genes correlated to serotonin production (Ddc) and re-uptake (Slc6a4) in ENC12.

Extended Data Fig. 3 Negative markers for ENC1-12, summary table of validated ENC markers and ENC proportions across the small intestine.

a–o, Immunohistochemical validation of negative marker proteins. Pictures show either myenteric peel preparations or transverse sections at P21-P90. white arrow: positive marker; yellow arrow: negative marker. Scale bars indicate 20 µm. p, Table summarizing ENC markers verified by immunohistochemistry (unique markers in bold) q) Graphs indicating proportions of ENCs at week 9-12 (n=3-4 mice) using HUC/D or PGP9.5 for total neuron counts. ENC1-2 was calculated by subtracting CALR+ ENC6, ENC5 and ENC11 percentages from the average total CALR+ neurons. Note the much higher proportion of ENC6 in tissue, than in scRNA-seq data, reflecting the difficulties in isolating big size neurons from tissue. Graph with all ENCs in ileum was normalized to 100% (absolute value 102,6%). Data are presented as mean values±SD.

Extended Data Fig. 4 Schematic tables summarizing marker and ligand/receptor gene expression in each ENC.

We combined information gained from RNA-sequencing (Fig. 1 and Supplementary Fig. 2), immunohistochemical analysis (Fig. 3) and transgenic mice (Fig. 4) to make a reasonable representation of gene expression patterns of (a) marker genes (b) ligand/receptors in the ENCs. (ligand): refers to genes required for the production of a ligand, including enzymes. ENC: Enteric Neuron Class.

Extended Data Fig. 5 Validation of Cre mouse lines for the investigation of ENC6 and ENC7.

a, Myenteric plexus peel from Nmu-Cre;R26R-Tom mouse showing TOM in HUC/D+ neurons (stars) and its exclusion from enteric glia (SOX2+). b, Myenteric plexus peel from Cck-IRES-Cre;R26-Tom mouse showing TOM in both neurons (stars) and enteric glia (stars). c, Myenteric plexus peel of Cck-IRES-Cre mouse injected with AAV-DIO-Ruby3 showing RUBY3 only in neurons and not in glia. d, Transverse sections showing that Nmu and Cck RNA expression correlate with reporter+ neurons in Nmu-Cre;R26R-Tom and Cck-IRES-Cre; AAV-DIO-EYFP/Ruby3 animals. e, Graph showing the percentage of reporter+ neurons expressing the reciprocal RNA. Data are presented as mean values±SD. A total of 638 reporter+ neurons were investigated in three Nmu-Cre;R26R-Tom mice, and 71 reporter+ neurons were investigated in three Cck-IRES-Cre;AAV-DIO-EYFP/Ruby3 mice. TOM: dtTomato. Scale bars indicate 50μm.

Extended Data Fig. 6 Morphological characterization of ENC6, 7, 12 and 5-HT+ ENC12.

Related to Fig. 4e–g. a, Representative examples of each morphological type found within ENC6, 7 and 12 and their size. b, Representative examples of each morphological type and their relative proportion (n=90 neurons from 5 animals) within jejunum and ileum of 5-HT+ ENC12. Scale bars indicates 20μm. Data are presented as mean values±SD.

Extended Data Fig. 7 Supportive data related to Fig. 5a,b.

a, b, Frequency distribution of the number of UMIs, detected genes and percent of mitochondrial genes per cell in E15.5 (a) and E18.5 (b) datasets. Orange bars represent cells that pass the thresholding for each parameter. c-d) Boxplots showing normalized expression (log scale) of known cell state genes: Sox10 (progenitor), Ascl1 (neuroblast), Elavl4 (enteric neuron), Plp1 (Enteric glia) and Dhh (SCP), grouped by Louvian clusters for E15.5 (c) and E18.5 (d). Box-and-whisker plots indicate max-min (whiskers), 25-75 percentile (boxes) with median as a centre line. Points indicate outliers. e, f, Refined clusters on UMAP for E15.5 (e) and E18.5 (f). Clusters in the same state were merged to obtain the generic ENS state clusters shown in Fig. 5a,b. UMI: Unique Molecular Identifier; SCP: Schwann cell precursor; E: Embryonic day; UMAP: Uniform Manifold Approximation and Projection; MT: Mitochondrial.

Extended Data Fig. 8 Feature plots displaying expression of Notch signaling genes at E18.5.

Related to Fig. 5. a, Ligands; note the predominant expression of Dll1 and Dll3 in neuroblasts. b, Receptors; note the predominant expression of Notch1,2 in progenitors. c, Downstream transcription factor; note the enriched expression of Hes6 in neuroblasts, Hes1 in progenitors and Hes5, Heyl and Hey2 in enteric glia. d, Regulator of activity; note the enriched expression of Mfng in neuroblasts and Lfng in progenitors. Color bar indicate expression level with maximum cut off at the 90th percentile.

Extended Data Fig. 9 Feature plots displaying transcription factors associated with generic cell states of the ENS at E15.5.

Related to Fig. 5f–h. a, progenitors, b) neuroblasts and c) neurons. Color bar indicate expression level with maximum cut-off at the 90th percentile.

Extended Data Fig. 10 Supportive data related to Fig. 6f.

a, TFs expressed in one or few ENCs that correlated well with juvenile expression (exception in a’). b, TFs with broad ENC-specific expression that correlated well with juvenile expression (exception in b’). c, TFs only expressed at embryonic stages, and not maintained in juvenile ENCs. d, TFs with wide expression, including bona fide ENS markers Hand2 and Phox2b. See Supplementary Fig. 2c to compare with the gene expressions in juvenile ENCs. Color bar indicate expression level with maximum cut off at the 90th percentile.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Supplementary Table 3.

Reporting Summary

Supplementary Table 1

Enriched genes in ENC1–12.

Supplementary Table 2

Table showing average and individual AUROC scores for HGNC gene families in ENCs.

Supplementary Table 4

Enriched genes in generic cell clusters at E15.5 and E18.5.

Supplementary Table 5

Coordinated gene patterns at E15.5.

Supplementary Table 6

Enriched genes in refined clusters at E15.5 and E18.5.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Morarach, K., Mikhailova, A., Knoflach, V. et al. Diversification of molecularly defined myenteric neuron classes revealed by single-cell RNA sequencing. Nat Neurosci 24, 34–46 (2021). https://doi.org/10.1038/s41593-020-00736-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-020-00736-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing