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.

Femtosecond laser microdissection for isolation of regenerating C. elegans neurons for single-cell RNA sequencing

Nature Methods volume 20, pages 590–599 (2023)Cite this article

Subjects

Abstract

Our understanding of nerve regeneration can be enhanced by delineating its underlying molecular activities at single-neuron resolution in model organisms such as Caenorhabditis elegans. Existing cell isolation techniques cannot isolate neurons with specific regeneration phenotypes from C. elegans. We present femtosecond laser microdissection (fs-LM), a single-cell isolation method that dissects specific cells directly from living tissue by leveraging the micrometer-scale precision of fs-laser ablation. We show that fs-LM facilitates sensitive and specific gene expression profiling by single-cell RNA sequencing (scRNA-seq), while mitigating the stress-related transcriptional artifacts induced by tissue dissociation. scRNA-seq of fs-LM isolated regenerating neurons revealed transcriptional programs that are correlated with either successful or failed regeneration in wild-type and dlk-1 (0) animals, respectively. This method also allowed studying heterogeneity displayed by the same type of neuron and found gene modules with expression patterns correlated with axon regrowth rate. Our results establish fs-LM as a spatially resolved single-cell isolation method for phenotype-to-genotype mapping.

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

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

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

Fig. 1: fs-LM isolates intact neuronal somas with reduced stress-related transcriptional artifacts for scRNA-seq.
Fig. 2: fs-LM facilitates profiling of transcriptional dynamics underlying axon regeneration in C. elegans.
Fig. 3: fs-LM facilitates the discovery of genetic programs underlying nerve regeneration in C. elegans.
Fig. 4: fs-LM facilitates the study of regeneration heterogeneity displayed neurons of the same type.
Fig. 5: GO analysis identifies genetic players with roles in C. elegans regeneration biology.

Data availability

The ChIP–seq datasets used for identifying potential regulators of nerve regeneration are publicly available at https://www.encodeproject.org/ (ENCODE Project75,76). The specific ChIP–seq data used in our study are listed in the Supplementary Table 8. The single-cell gene expression profiles of all six TRNs are used from the publicly available CeNGEN data at https://www.cengen.org/. All RNA-seq data involved in Figs. 1–5 are available on the NCBI SRA repository under study identifier SRP300789. The RNA-seq reads and counts are provided in the Supplementary Table 9. Source data are provided with this paper.

References

  1. Courtine, G. & Sofroniew, M. V. Spinal cord repair: advances in biology and technology. Nat. Med. 25, 898–908 (2019).

    CAS  PubMed  Google Scholar 

  2. Hutson, T. H. & Di Giovanni, S. The translational landscape in spinal cord injury: focus on neuroplasticity and regeneration. Nat. Rev. Neurol. 15, 732–745 (2019).

    PubMed  Google Scholar 

  3. Norsworthy, M. W. et al. Sox11 expression promotes regeneration of some retinal ganglion cell types but kills others. Neuron 94, 1112–1120.e1114 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Duan, X. et al. Subtype-specific regeneration of retinal ganglion cells following axotomy: effects of osteopontin and mTOR signaling. Neuron 85, 1244–1256 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Yanik, M. F. et al. Functional regeneration after laser axotomy. Nature 432, 822–822 (2004).

    CAS  PubMed  Google Scholar 

  6. Bourgeois, F. & Ben-Yakar, A. Femtosecond laser nanoaxotomy properties and their effect on axonal recovery in C. elegans. Opt. Express 16, 5963 (2008).

    PubMed  Google Scholar 

  7. Hammarlund, M., Nix, P., Hauth, L., Jorgensen, E. M. & Bastiani, M. Axon regeneration requires a conserved MAP kinase pathway. Science 323, 802 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Ghosh-Roy, A., Wu, Z., Goncharov, A., Jin, Y. & Chisholm, A. D. Calcium and cyclic AMP promote axonal regeneration in Caenorhabditis elegans and require DLK-1 kinase. J. Neurosci. 30, 3175 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Nix, P., Hisamoto, N., Matsumoto, K. & Bastiani, M. Axon regeneration requires coordinate activation of p38 and JNK MAPK pathways. Proc. Natl Acad. Sci. USA 108, 10738 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. El Bejjani, R. & Hammarlund, M. Notch signaling inhibits axon regeneration. Neuron 73, 268–278 (2012).

    CAS  PubMed  Google Scholar 

  11. Zou, Y. et al. Developmental decline in neuronal regeneration by the progressive change of two intrinsic timers. Science 340, 372–376 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Byrne, A. B. et al. Insulin/IGF1 signaling inhibits age-dependent axon regeneration. Neuron 81, 561–573 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Chuang, M. et al. The microtubule minus-end-binding protein patronin/PTRN-1 is required for axon regeneration in C. elegans. Cell Rep. 9, 874–883 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen, L. et al. Axon injury triggers EFA-6 mediated destabilization of axonal microtubules via TACC and doublecortin like kinase. eLife 4, e08695 (2015).

    PubMed  PubMed Central  Google Scholar 

  15. Li, C., Hisamoto, N. & Matsumoto, K. Axon regeneration is regulated by Ets-C/EBP transcription complexes generated by activation of the cAMP/Ca2+ signaling pathways. PLoS Genet. 11, e1005603 (2015).

    PubMed  PubMed Central  Google Scholar 

  16. Neumann, B. et al. EFF-1-mediated regenerative axonal fusion requires components of the apoptotic pathway. Nature 517, 219–222 (2015).

    CAS  PubMed  Google Scholar 

  17. Alam, T. et al. Axotomy-induced HIF-serotonin signalling axis promotes axon regeneration in C. elegans. Nat. Commun. 7, 10388 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Byrne, A. B. et al. Inhibiting poly(ADP-ribosylation) improves axon regeneration. eLife 5, e12734 (2016).

    PubMed  PubMed Central  Google Scholar 

  19. Chung, S. H. et al. Novel DLK-independent neuronal regeneration in Caenorhabditis elegans shares links with activity-dependent ectopic outgrowth. Proc. Natl Acad. Sci. USA 113, E2852–E2860 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Han, S. M., Baig, H. S. & Hammarlund, M. Mitochondria localize to injured axons to support regeneration. Neuron 92, 1308–1323 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Abay, Z. C. et al. Phosphatidylserine save-me signals drive functional recovery of severed axons in Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 114, E10196 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Cartoni, R. et al. The mammalian-specific protein Armcx1 regulates mitochondrial transport during axon regeneration. Neuron 94, 689 (2017).

    CAS  PubMed  Google Scholar 

  23. Hisamoto, N. et al. Phosphatidylserine exposure mediated by ABC transporter activates the integrin signaling pathway promoting axon regeneration. Nat. Commun. 9, 3099 (2018).

    PubMed  PubMed Central  Google Scholar 

  24. Kim, K. W. et al. A neuronal piRNA pathway inhibits axon regeneration in C. elegans. Neuron 97, 511–519.e516 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Linton, C. et al. Disruption of RAB-5 increases EFF-1 fusogen availability at the cell surface and promotes the regenerative axonal fusion capacity of the neuron. J. Neurosci. 39, 2823–2836 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Tang, N. H. et al. The mRNA Decay Factor CAR-1/LSM14 regulates axon regeneration via mitochondrial calcium dynamics. Curr. Biol. 30, 865–876.e867 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Yan, D., Wu, Z., Chisholm, A. D. & Jin, Y. The DLK-1 kinase promotes mRNA stability and local translation in C. elegans synapses and axon regeneration. Cell 138, 1005–1018 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Bounoutas, A. et al. Microtubule depolymerization in Caenorhabditis elegans touch receptor neurons reduces gene expression through a p38 MAPK pathway. Proc. Natl Acad. Sci. USA 108, 3982–3987 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Li, C. et al. The growth factor SVH-1 regulates axon regeneration in C. elegans via the JNK MAPK cascade. Nat. Neurosci. 15, 551–557 (2012).

    CAS  PubMed  Google Scholar 

  30. Yan, D. & Jin, Y. Regulation of DLK-1 kinase activity by calcium-mediated dissociation from an inhibitory isoform. Neuron 76, 534–548 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Malinow, R. A. et al. Functional dissection of C. elegans bZip-protein CEBP-1 reveals novel structural motifs required for axon regeneration and nuclear import. Front Cell Neurosci. 13, 348 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Kaletsky, R. et al. The C. elegans adult neuronal IIS/FOXO transcriptome reveals adult phenotype regulators. Nature 529, 92–96 (2016).

    CAS  PubMed  Google Scholar 

  33. Spencer, W. C. et al. Isolation of specific neurons from C. elegans larvae for gene expression profiling. PLoS ONE 9, e112102 (2014).

    PubMed  PubMed Central  Google Scholar 

  34. van den Brink, S. C. et al. Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations. Nat. Methods 14, 935–936 (2017).

    PubMed  Google Scholar 

  35. O’Flanagan, C. H. et al. Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses. Genome Biol. 20, 210 (2019).

    PubMed  PubMed Central  Google Scholar 

  36. Emmert-Buck, M. R. et al. Laser capture microdissection. Science 274, 998–1001 (1996).

    CAS  PubMed  Google Scholar 

  37. Schwarz, E. M., Kato, M. & Sternberg, P. W. Functional transcriptomics of a migrating cell in Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 109, 16246–16251 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Nath, R. D., Chow, E. S., Wang, H., Schwarz, E. M. & Sternberg, P. W. C. elegans stress-induced sleep emerges from the collective action of multiple neuropeptides. Curr. Biol. 26, 2446–2455 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Lockhead, D. et al. The tubulin repertoire of C. elegans sensory neurons and its context-dependent role in process outgrowth. Mol. Biol. Cell 27, 3717–3728 (2016).

  40. Cadwell, C. R. et al. Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nat. Biotechnol. 34, 199–203 (2016).

    CAS  PubMed  Google Scholar 

  41. Barrett, A. et al. Integrating bulk and single cell RNA-seq refines transcriptomic profiles of specific C. elegans neurons. Preprint at bioRxiv https://doi.org/10.1101/2022.04.05.487209 (2022).

  42. Gökçe, S. K. et al. A fully automated microfluidic femtosecond laser axotomy platform for nerve regeneration studies in C. elegans. PLoS ONE 9, e113917 (2014).

    PubMed  PubMed Central  Google Scholar 

  43. Gokce, S. K. et al. A multi-trap microfluidic chip enabling longitudinal studies of nerve regeneration in Caenorhabditis elegans. Sci. Rep. 7, 9837 (2017).

    PubMed  PubMed Central  Google Scholar 

  44. Ben-Yakar, A. & Bourgeois, F. Ultrafast laser nanosurgery in microfluidics for genome-wide screenings. Curr. Opin. Biotechnol. 20, 100–105 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Spaeth, C. S., Boydston, E. A., Figard, L. R., Zuzek, A. & Bittner, G. D. A model for sealing plasmalemmal damage in neurons and other eukaryotic cells. J. Neurosci. 30, 15790–15800 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Wu, A. R. et al. Quantitative assessment of single-cell RNA-sequencing methods. Nat. Methods 11, 41–46 (2014).

    CAS  PubMed  Google Scholar 

  47. Ziegenhain, C. et al. Comparative analysis of single-cell RNA sequencing methods. Mol. Cell 65, 631–643.e634 (2017).

    CAS  PubMed  Google Scholar 

  48. Yosef, N. & Regev, A. Impulse control: temporal dynamics in gene transcription. Cell 144, 886–896 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Bahrami, S. & Drabløs, F. Gene regulation in the immediate-early response process. Adv. Biol. Regul. 62, 37–49 (2016).

    CAS  PubMed  Google Scholar 

  50. Taylor, S. R. et al. Molecular topography of an entire nervous system. Cell 184, 4329–4347.e4323 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Neumann, B. & Hilliard, M. A. Loss of MEC-17 leads to microtubule instability and axonal degeneration. Cell Rep. 6, 93–103 (2014).

    CAS  PubMed  Google Scholar 

  52. Savage, C. et al. Mutations in the Caenorhabditis elegans beta-tubulin gene mec-7: effects on microtubule assembly and stability and on tubulin autoregulation. J. Cell Sci. 107, 2165–2175 (1994).

    CAS  PubMed  Google Scholar 

  53. Duan, H. et al. Transcriptome analyses reveal molecular mechanisms underlying functional recovery after spinal cord injury. Proc. Natl Acad. Sci. USA 112, 13360 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Teoh, J.-S., Wong, M. Y.-Y., Vijayaraghavan, T. & Neumann, B. Bridging the gap: axonal fusion drives rapid functional recovery of the nervous system. Neural Regen. Res. 13, 591–594 (2018).

    PubMed  PubMed Central  Google Scholar 

  55. Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Tedeschi, A. et al. The calcium channel subunit Alpha2delta2 suppresses axon regeneration in the adult CNS. Neuron 92, 419–434 (2016).

    CAS  PubMed  Google Scholar 

  57. Celniker, S. E. et al. Unlocking the secrets of the genome. Nature 459, 927–930 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Kudron, M. M. et al. The ModERN resource: genome-wide binding profiles for hundreds of Drosophila and Caenorhabditis elegans transcription factors. Genetics 208, 937 (2018).

    CAS  PubMed  Google Scholar 

  59. Wu, Z. et al. Caenorhabditis elegans neuronal regeneration is influenced by life stage, ephrin signaling, and synaptic branching. Proc. Natl Acad. Sci. USA 104, 15132–15137 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Ma, T. C. & Willis, D. E. What makes a RAG regeneration associated? Front Mol. Neurosci. 8, 43 (2015).

    PubMed  PubMed Central  Google Scholar 

  61. Schmitt, A. B. et al. Identification of regeneration-associated genes after central and peripheral nerve injury in the adult rat. BMC Neurosci. 4, 8 (2003).

    PubMed  PubMed Central  Google Scholar 

  62. Chandran, V. et al. A systems-level analysis of the peripheral nerve intrinsic axonal growth program. Neuron 89, 956–970 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Chen, B. K. et al. Axon regeneration through scaffold into distal spinal cord after transection. J. Neurotrauma 26, 1759–1771 (2009).

    PubMed  PubMed Central  Google Scholar 

  64. Kadoya, K. et al. Spinal cord reconstitution with homologous neural grafts enables robust corticospinal regeneration. Nat. Med. 22, 479–487 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinf. 9, 559 (2008).

    Google Scholar 

  66. Lovatt, D. et al. Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue. Nat. Methods 11, 190–196 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Reynoso, M. A. et al. Translating Ribosome Affinity Purification (TRAP) followed by RNA sequencing technology (TRAP-SEQ) for quantitative assessment of plant translatomes. Methods Mol. Biol. 1284, 185–207 (2015).

    CAS  PubMed  Google Scholar 

  68. Lee, J. H. et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nat. Protoc. 10, 442–458 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361, eaat5691 (2018).

    PubMed  PubMed Central  Google Scholar 

  70. Hammarlund, M., Hobert, O., Miller, D. M. 3rd & Sestan, N. The CeNGEN Project: the complete gene expression map of an entire nervous system. Neuron 99, 430–433 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Chen, L. et al. Axon regeneration pathways identified by systematic genetic screening in C. elegans. Neuron 71, 1043–1057 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Jin, Y., Jorgensen, E., Hartwieg, E. & Horvitz, H. R. The Caenorhabditis elegans gene unc-25 encodes glutamic acid decarboxylase and is required for synaptic transmission but not synaptic development. J. Neurosci. 19, 539–548 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Schuske, K., Beg, A. A. & Jorgensen, E. M. The GABA nervous system in C. elegans. Trends Neurosci. 27, 407–414 (2004).

    CAS  PubMed  Google Scholar 

  74. Nass, R., Hall, D. H., Miller, D. M. 3rd & Blakely, R. D. Neurotoxin-induced degeneration of dopamine neurons in Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 99, 3264–3269 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Davis, C. A. et al. The encyclopedia of DNA elements (ENCODE): data portal update. Nucleic Acids Res. 46, D794–D801 (2017).

    PubMed Central  Google Scholar 

  76. Consortium, E. P. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Institutes of Health (NIH) grant nos. R21-NS109821 (A.B.-Y.) and RO1-NS060129 (A.B.-Y.), by the training grant no. EB007507 (C.M.), and by a grant from The University of Texas System Neuroscience and Neurotechnology Research Institute (A.B.-Y. and R.O.M.). We are grateful to B. Zemelman, L. Kreeger and N. Golding (The University of Texas at Austin) for sharing insights and brain slice samples from PV-Cre;Ai14 mice and gerbils injected with two adeno-associated viruses during the early-stage development of this method. We acknowledge A. Battenhouse (The University of Texas at Austin) for ChIP–seq analysis, Y. Li (Dell Pediatric Research Institute) for assistance during FACS experiments, Y. Jin (University of California San Diego) for C. elegans strains used in this study (CZ10175 and CZ11327), C. Williams (The University of Texas at Austin) for preparing micropipette and E. Hegarty (The University of Texas at Austin) for help with animal maintenance and insights in experimental design. Bioinformatics analysis support was provided by the Bioinformatics Consulting Group at UT Austin, Center for Biomedical Research Support (grant no. RRID:SCR_022688). We thank the ENCODE Consortium, in particular M. Snyder, V. Reinke and K. White for providing the ChIP–seq datasets. Some strains were provided by the Caenorhabditis Genetic Center, which is funded by the NIH Office of Research Infrastructure Programs (grant no. P40 OD010440).

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA

    Peisen Zhao & Adela Ben-Yakar

  2. Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA

    Sudip Mondal & Adela Ben-Yakar

  3. Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA

    Chris Martin, Andrew DuPlissis, Ning Jiang & Adela Ben-Yakar

  4. Deparment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    Shahab Chizari & Ning Jiang

  5. Interdisciplinary Life Sciences Graduate Programs, The University of Texas at Austin, Austin, TX, USA

    Ke-Yue Ma & Ning Jiang

  6. Department of Neuroscience, The University of Texas at Austin, Austin, TX, USA

    Rajani Maiya & Robert O. Messing

  7. Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX, USA

    Rajani Maiya & Robert O. Messing

  8. Institute of Neuroscience, The University of Texas at Austin, Austin, TX, USA

    Rajani Maiya, Robert O. Messing & Adela Ben-Yakar

  9. Department of Physiology, LSU Health Sciences Center, New Orleans, LA, USA

    Rajani Maiya

Authors
  1. Peisen Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sudip Mondal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chris Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andrew DuPlissis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shahab Chizari
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ke-Yue Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rajani Maiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Robert O. Messing
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ning Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Adela Ben-Yakar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.B.-Y. conceived the method and supervised the overall direction of the research. P.Z., C.M., S.M. and A.B.-Y. designed the experiments. P.Z., S.M. and C.M. further developed the method to bring it into practice, the optical setup and the automated LabView program. P.Z. maintained animal strains, performed laser axotomy experiments and isolated neurons used in all RNA-seq studies. S.M. isolated neurons from different strains to demonstrate the use of the fs-LM method with multiple strains and confirmed using RT–PCR. P.Z. performed RNA-seq and initial data analysis with inputs from K.-Y.M. Further data analysis was carried out by S.C., A.D. and S.M. during the revision with inputs from N.J. and A.B.-Y. Experimental setup and protocol for fs-LM isolation of neurons from mice brain slices were developed and performed by P.Z. with inputs from R.M. and R.O.M. P.Z., S.M. and A.B.-Y. prepared the paper with inputs from all authors.

Corresponding author

Correspondence to Adela Ben-Yakar.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Methods thanks Itai Yanai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Nina Vogt, in collaboration with the Nature Methods team.

Additional information

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

Extended data

Extended Data Fig. 1 Schematic of the fs-LM setup for single-cell microdissection of C. elegans neurons.

a, Schematic of the optical setup. The diagram shows a femtosecond laser (fs-laser), beam splitter (BS), mirror (M), shutter (S), flip mirror (FM), neutral density filter (ND), photodetector (PD), hot mirror, tube lens (TL), filter set, fluorescence source (FL Lamp), motorized stage, condenser, and bright-field light source (BF Lamp). The microdissection is performed with a 60× 1.0 NA water dipping objective. The sample manipulation is performed with a 10× 0.3NA air objective with a 10 mm working distance. A glass microneedle is mounted on a 3-axis manipulator and suction pressure is controlled using a precise pneumatic puller. The pi-chart shows the isolation of n = 123 PLM neurons (32.0% out of n = 384 total PLM neurons). The pie chart also depicts the unsuccessful situations and classifies them under different categories based on the step at which we lost the neuron. Most failures (incomplete resection, n = 88 neurons) occurred primarily when the neurons were torn into pieces during the release process through the cuticle (Extended Data Fig. 2e-l). b, Priming steps for the glass micropipette before it can be used for cell manipulation. c, fs-LM isolation steps including C. elegans immobilization, single-cell dissection, cell collection in the glass micropipette, and cell lysis for single-cell transcriptomic analysis.

Extended Data Fig. 2 Successful and unsuccessful fs-LM isolation of C. elegans PLM neurons.

a-d, Example of successful fs-LM isolation of neurons. The resected neuron was released through the incision smoothly without damage, as evidenced by consistent volume and cytoplasmic GFP intensity (n = 123 out of total 384 attempts). e-h, Incomplete resection of neuron causing it to remain in place after the incision was made (n = 88 out of total 384 attempts). As a result, the neuron was torn by the outflow of surrounding tissue. i-l, A resected neuron was fragmented when migrating through a small cuticle incision. In this case, the neuron was moving towards the incision, which indicated complete resection. Scale bar, 50 μm.

Extended Data Fig. 3 Quantification of amplified cDNA libraries from fs-LM isolated single C. elegans neurons.

a, Example of libraries of good quality. Inset: the isolated neurons retained GFP intensity until being deposited into the lysis buffer. b, Example of libraries that failed quality check, and were thus excluded from this study. Inset: the isolated neuron lysed before being deposited into the lysis buffer. Although the cellular content of the neuron supposedly remained in the micropipette, degradation, and attachment to the inner wall of the micropipette affected reverse transcription (RT)-PCR, resulting in libraries dominated by short fragments that were mostly primer dimers. c, Example of NTC controls.

Extended Data Fig. 4 Isolation of C. elegans touch receptor neurons by the dissociation-FACS method.

a-d, FACSAria II gate settings for isolating living GFP-labeled C. elegans touch receptor neurons from dissociated animals. Prior to FACS, the cell suspension was filtered through a 5 μm syringe filter to prevent clogging. SSC-A, SSC-W, and FSC gates were set up to exclude debris and clusters of cells. We stained the dead neurons with propidium iodide. GFP + PI- events were sorted into 96 well plates or 1.5 mL conical tubes containing lysis buffer. The GFP threshold was determined in reference to the autofluorescence of cells from dissociated N2 worms. The PI threshold was determined by test sorting a small number of PI-stained cells and observing two distinct populations of live/dead cells. e, Histogram of GFP levels of the isolated neurons. f, Cell suspension prior to sorting and g, example of a collected neuron. Green: GFP. Red: PI. Multiple locations were imaged to confirm GFP + neurons using the fluorescent microscope (confirmed with 3 independent sample preparation). Scale bar: 5 μm. h, Quantification of cDNA library prepared from one of the GFP + sorted cells using FACS method.

Extended Data Fig. 5 RNA-sequencing of fs-LM and dissociation-FACS isolated neurons.

a, b, Number of genes detected at different sequencing depth obtained by subsampling 19 million total reads from bulk (each bulk sample has >5,000 cells) and single neuron samples. c, Cumulative distribution of sequencing depth among all single-neuron samples collected with fs-LM and verified using scRNA-seq library quality checks. Single-neuron samples below the red dotted line were discarded due to insufficient sequencing depth. d, Number of genes identified in fs-LM isolated single neurons (n = 46 uninjured PLM neurons) and single TRNs isolated using dissociation-FACS method (n = 23 single TRNs from WT animals). e, f, Top tissue enrichment analysis terms of fs-LM isolated single neurons (e) and dissociation-FACS isolated single neurons (f). Data presented as mean + standard error of mean (SEM). g, Correlation of gene expression profiles between the ensembles of single TRNs (isolated using FACS-dissociation method, n = 23) and the single PLM neurons (isolated using the fs-LM method, n = 40).

Extended Data Fig. 6 Gene expression profiles for the neurons collected using fs-LM and dissociation-FACS methods.

a, Expression levels of marker genes among fs-LM isolated single PLM neurons (n = 123 PLM neurons). b, Expression levels of marker genes among dissociation-FACS isolated TRNs (n = 23 single TRNs). c, Expression levels of marker genes among dissociation-FACS isolated bulk samples (n = 3 bulk samples each with >5,000 TRNs).

Extended Data Fig. 7 Examples of successful fs-LM isolation of single neurons from different locations in multiple C. elegans strains.

a, Isolation of one of the PLM neurons from the tail region in CZ10175 animal (we resected n = 14 PLM neurons out of 15 attempts over 6 independent batches). Scale bar, 50 μm. b, Isolation of VD7 neuron from the mid-body region (close to the vulva muscle and residing on the ventral cord region) in the CZ1200 animal (resected n = 3 VD7 neurons over 3 independent batches). c, Isolation of one of the CEP neurons from the head region (in the head ganglion) in the BY200 animal (resected n = 24 CEP neurons out of 30 attempts over 10 independent batches). d, Isolation of one of the RME neurons from the head region (in the head ganglion) in the CZ1200 animal (We resected n = 8 RME neurons out of 9 attempts over 4 independent batches). The top panel shows the neurons’ schematics. Below are the fluorescence images describing the steps for the axotomy of neuronal processes, neuron dissection, cuticle ablation, neuron extraction, and neuron collection. The lightening arrows indicate the locations of the laser spots for axotomy and fs-LM (light pink, indicating low pulse energies) and cuticle ablation (red, indicating higher pulse energies required to ablate the cuticle). The yellow arrows indicate the isolated neurons outside the animal body and as collected inside the micro-pipette tip. The bottom panel shows 2% agarose gel with PCR amplification products of single-cell lysates and visualized with ethidium bromide. Lanes are marked with the target genes or ladder used in the experiment.

Source data

Extended Data Fig. 8 Correlation of gene expression profiles between fs-LM and dissociation-FACS methods.

a, Normalized expression of the selected 36 genes, obtained from CeNGEN feature lists, utilized to visualize and identify cell clusters that were assigned a predicted neuronal category. With this classification analysis, we obtained PLM (n = 6), PVM (n = 5), ALM (n = 8), and AVM (n = 3) subgroups with one remaining unclassified. The color panels show the four neuron categories and the normalized level of expression. b, Principal component analysis (PCA) on gene expression profiles in single PLM neurons isolated by fs-LM (fs-LM (PLM), n = 40) and dissociation-FACS (dissociation-FACS (PLM), n = 6) methods. The six dissociation-FACS isolated neurons were classified using the neuron-specific gene expression data available in CeNGEN data. c, Pearson correlation coefficients as calculated from 50 groups of 6 neurons isolated using the fs-LM method (n = 40), predicted-PLM method (dissociation-FACS, n = 6), and all TRNs (dissociation-FACS, n = 23). Shaded areas represent a 95% confidence interval around the mean. d, Box and whisker plot for the top 10 expressed genes. e, Box and whisker plot for all 1,000 ranked genes. The box extends from the 25th to 75th percentiles, the line is plotted at the median, the whiskers drawn down to the 10th percentile and up to the 90th percentile. Points below and above the whiskers are drawn as individual points. The statistical test used is a two-tailed unpaired Wilcoxon rank sum test. P-value = 0.024 (dissociation FACS and predicted PLM for top 10 genes, *) and P-value < 0.0001 (****).

Extended Data Fig. 9 Axon regeneration of PLM neurons in wild-type and dlk-1 (0) animals following fs-laser axotomy.

a, Regeneration status of axotomized PLM neurons at 24-hour post-axotomy examined over at least 3 independent batches. 1 out of 86 wild-type PLM neurons failed to initiate regrowth. b, Length of axon regrowth at various time points post-axotomy. At 2–4 hours post-axotomy, wild-type PLM neurons started to regrow at an average rate of 6.1 μm/hour. The ectopic regrowth rate of dlk-1 (0) neurons was found to be 1.2 μm/hour. Data presented as mean ± standard deviation (SD). c, d, Microscope images of regrowing wild-type (c) and dlk-1 (0) neurons (d). The regrowth lengths presented in (b) were measured from up to n = 16 wild-type and n = 14 dlk-1(0) animals, collected over at least 3 independent experiments. Asterisk, site of laser axotomy. Arrowhead, the tip of regrowing axon. Scale bar, 10 μm.

Extended Data Fig. 10 Differential gene expression between uninjured and axotomized neurons isolated from wild-type/dlk-1 (0) animals.

a, DEGs between uninjured wild-type (n = 21) and dlk-1 (0) (n = 24) neurons collected from at least 3 independent experiments. Red points in the volcano plot represent significant DEGs with adjusted P-value < 0.05, log2 fold change > 2, and tested using a one-sided Wilcoxon rank test. b, DEGs between uninjured (n = 21 control) and axotomized wild-type (n = 46) neurons collected over at least 3 independent batches. c, DEGs between uninjured (n = 24 control) and axotomized dlk-1 (0) (n = 13) neurons collected over at least 3 independent batches. Boxplots on the right show expression levels of the top 4 DEGs for each set. The box extends from the 25th to 75th percentiles, the line is plotted at the median, the whiskers drawn down to the 10th percentile and up to the 90th percentile. Points below and above the whiskers are drawn as individual points.

Supplementary information

Supplementary Information

Supplementary Notes 1–6 and Figs. 1–5.

Reporting Summary

Peer Review File

Time-lapse video of single-cell isolation and cell-lysate collection from an individual PLM neuron using the fs-LM method.

Time-lapse video of single-cell isolation and cell-lysate collection from an individual CEP neuron using the fs-LM method.

Supplementary Tables

Supplementary Tables 1–9.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 7

Unprocessed gel pictures for Extended Data Fig. 7a,c.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, P., Mondal, S., Martin, C. et al. Femtosecond laser microdissection for isolation of regenerating C. elegans neurons for single-cell RNA sequencing. Nat Methods 20, 590–599 (2023). https://doi.org/10.1038/s41592-023-01804-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-023-01804-3

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