in

Caenorhabditis elegans populations shape their microbial environment


Abstract

Nematodes represent one of the most abundant and ecologically significant taxonomic groups on earth, playing diverse roles in the cycling of organic matter. However, little is known about their effects on their microbial environment. To explore such effects, we took advantage of the bacteriovore free-living nematode Caenorhabditis elegans, which has been shown to assemble a characteristic gut microbiome from different microbial environments. Worm populations (initially germ-free) were raised in several microbially-distinct natural-like environments emulating the environment from which C. elegans are often isolated, allowing worms to go through four generations encompassing the typical boom-to-bust population growth cycle. Samples from worms, their environments, and from control environments without worms were analyzed using next-generation 16S rRNA gene sequencing. Data analysis showed that microbial diversity increased in the environment, either when worms were present or not, but that trajectories of change were different depending on the presence of worms. Importantly, the presence of worms led with time to convergence in the composition of their microbial environments, particularly affecting the abundance of members of bacterial families that are part of the C. elegans gut microbiome. Our findings reveal that C. elegans not only responds to environmental microbial changes but also shapes them, suggesting new roles for nematodes in modulating environmental microbial diversity and ecosystems.

Similar content being viewed by others

Caenorhabditis elegans microbiome members have combinatorial effects on host survival and fitness

Host and microbiome jointly contribute to environmental adaptation

Caenorhabditis elegans foraging patterns follow a simple rule of thumb

Data availability

Raw data is available in the NCBI SRA database with accession number PRJNA1116742.

Code availability

R-scripts used to generate figures are available at https://rpubs.com/MicroRB/Boom_Bust.

References

  1. Steel, H. et al. Nematode succession during composting and the potential of the nematode community as an indicator of compost maturity. Pedobiologia (Jena). 53, 181–190 (2010).

    Google Scholar 

  2. Hodda, M. Phylum Nematoda: a classification, catalogue and index of valid genera, with a census of valid species. Zootaxa. 5114, 1–289 (2022).

    Google Scholar 

  3. Zhang, C., Wright, I. J., Nielsen, U. N., Geisen, S. & Liu, M. Linking nematodes and ecosystem function: a trait-based framework. Trends Ecol. Evol. 39, 644–653 (2024).

    Google Scholar 

  4. Vlaar, L. E. et al. On the role of dauer in the adaptation of nematodes to a parasitic lifestyle. Parasit. Vectors 14, https://doi.org/10.1186/S13071-021-04953-6 (2021).

  5. Hu, P. J. Dauer. in WormBook: The Online Review of C. elegans Biology.(WormBook, 2007) 1–19. https://doi.org/10.1895/wormbook.1.144.1.

  6. Hand, S. C., Denlinger, D. L., Podrabsky, J. E. & Roy, R. Mechanisms of animal diapause: recent developments from nematodes, crustaceans, insects, and fish. Am. J. Physiol. Regul. Integr. Comp. Physiol. 310, R1193–R1211 (2016).

    Google Scholar 

  7. van den Hoogen, J. et al. Soil nematode abundance and functional group composition at a global scale. Nature 572, 194–198 (2019).

    Google Scholar 

  8. Brenner, S. The genetics of Caenorhabditis elegans. Genetics 77, 71–94 (1974).

    Google Scholar 

  9. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282, 2012–2018 (1998).

  10. Kiontke, K. & Sudhaus, W. Ecology of Caenorhabditis species. WormBook https://doi.org/10.1895/wormbook.1.37.1 (2006).

  11. Petersen, C. et al. Travelling at a slug’s pace: possible invertebrate vectors of Caenorhabditis nematodes. BMC Ecol. 15, 19 (2015).

    Google Scholar 

  12. Reed, E. M. & Wallace, H. R. Leaping locomotion by an Insect-parasitic Nematode. Nature. 206, 210–211 (1965).

    Google Scholar 

  13. Cassada, R. C. & Russell, R. L. The dauerlarva, a post-embryonic developmental variant of the nematode Caenorhabditis elegans. Dev. Biol. 46, 326–342 (1975).

    Google Scholar 

  14. Androwski, R. J., Flatt, K. M. & Schroeder, N. E. Phenotypic plasticity and remodeling in the stress-induced Caenorhabditis elegans dauer. Wiley Interdiscip. Rev Dev. Biol. 6, e278 (2017).

    Google Scholar 

  15. Félix, M. A. & Duveau, F. Population dynamics and habitat sharing of natural populations of Caenorhabditis elegans and C. briggsae. BMC Biol. 10, 59 (2012).

    Google Scholar 

  16. Dallière, N., Holden-Dye, L., Dillon, J., O’Connor, V. & Walker, R. J. Caenorhabditis elegans feeding behaviors. Oxf. Res. Encycl. Neurosci. https://doi.org/10.1093/acrefore/9780190264086.013.190 (2017).

  17. Pérez-Carrascal, O. M. et al. Host preference of beneficial commensals in a microbially-diverse environment. Front. Cell. Infect. Microbiol. 12, 795343 (2022).

    Google Scholar 

  18. Siddiqui, R. et al. Olfactory basis for essential amino acid perception during foraging in Caenorhabditis elegans. Elife 13, RP101936 (2024).

    Google Scholar 

  19. García-González, A. P. et al. Bacterial metabolism affects the C. elegans response to cancer chemotherapeutics. Cell 169, 431–441.e8 (2017).

    Google Scholar 

  20. Berg, M. et al. Assembly of the Caenorhabditis elegans gut microbiota from diverse soil microbial environments. ISME J. 10, 1998–2009 (2016).

    Google Scholar 

  21. Meyer, J. M. et al. Succession and dynamics of Pristionchus nematodes and their microbiome during decomposition of Oryctes borbonicus on La Réunion Island. Environ. Microbiol. 19, 1476–1489 (2017).

    Google Scholar 

  22. Zhang, F. et al. Natural genetic variation drives microbiome selection in the Caenorhabditis elegans gut. Curr. Biol. 31, 2603–2618.e9 (2021).

    Google Scholar 

  23. Griem-Krey, H., Petersen, C., Hamerich, I. K. & Schulenburg, H. The intricate triangular interaction between protective microbe, pathogen and host determines fitness of the metaorganism. Proc. Biol. Sci. 290, 20232193 (2023).

    Google Scholar 

  24. Lo, W. S., Sommer, R. J. & Han, Z. Microbiota succession influences nematode physiology in a beetle microcosm ecosystem. Nat. Commun. 15, 5137 (2024).

    Google Scholar 

  25. Peters, L. et al. Polyketide synthase-derived sphingolipids mediate microbiota protection against a bacterial pathogen in C. elegans. Nat. Commun. 16, 5151 (2025).

    Google Scholar 

  26. Berg, M., Zhou, X. Y. & Shapira, M. Host-specific functional significance of Caenorhabditis gut commensals. Front. Microbiol. 7, 221536 (2016).

    Google Scholar 

  27. Johnke, J. et al. Caenorhabditis nematodes influence microbiome and metabolome characteristics of their natural apple substrates over time. mSystems 10, e0153324 (2025).

    Google Scholar 

  28. Bodkhe, R., Trang, K., Hammond, S., Jung, D. K. & Shapira, M. Emergence of dauer larvae in Caenorhabditis elegansdisrupts continuity of host-microbiome interactions. FEMS Microbiol. Ecol. 100, fiae149 (2024).

    Google Scholar 

  29. Rivera, D. E. et al. Dynamics of gut colonization by commensal and pathogenic bacteria that attach to the intestinal epithelium. NPJ Biofilms Microbiomes 11, 70 (2025).

    Google Scholar 

  30. Zhang, F. et al. Caenorhabditis elegans as a model for microbiome research. Front. Microbiol. 8, 241616 (2017).

    Google Scholar 

  31. Dirksen, P. et al. The native microbiome of the nematode Caenorhabditis elegans: gateway to a new host-microbiome model. BMC Biol. 14, 38 (2016).

    Google Scholar 

  32. Dirksen, P. et al. CeMbio—the Caenorhabditis elegans microbiome resource. G3 GenesGenomesGenetics 10, 3025 (2020).

    Google Scholar 

  33. Yun, J. H. et al. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl. Environ. Microbiol. 80, 5254 (2014).

    Google Scholar 

  34. Sullam, K. E. et al. Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol. Ecol. https://doi.org/10.1111/j.1365-294X.2012.05552.x (2012).

  35. Liukkonen, M. et al. Seasonal and environmental factors contribute to the variation in the gut microbiome: a large-scale study of a small bird. J. Anim. Ecol. 93, 1475–1492 (2024).

    Google Scholar 

  36. Trang, K., Bodkhe, R. & Shapira, M. Compost microcosms as microbially diverse, natural-like environments for microbiome research in Caenorhabditis elegans. J. Vis. Exp 187, 64393 (2022).

    Google Scholar 

  37. Choi, R. et al. An enterobacteriaceae bloom in aging animals is restrained by the gut microbiome. Aging Biol. 1, 20240024 (2024).

    Google Scholar 

  38. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Google Scholar 

  39. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).

    Google Scholar 

  40. McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).

    Google Scholar 

  41. Wright, E. S. Fast and flexible search for homologous biological sequences with DECIPHER v3. R. J. 16, 191–200 (2024).

    Google Scholar 

  42. Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592 (2010).

    Google Scholar 

  43. Knights, D. et al. Bayesian community-wide culture-independent microbial source tracking. Nat. Methods 8, 761–763 (2011).

    Google Scholar 

  44. Wickham, H. ggplot2. https://doi.org/10.1007/978-3-319-24277-4 (2016).

  45. Martin, B. D., Witten, D. & Willis, A. D. Modeling microbial abundances and dysbiosis with beta-binomial regression. Ann. Appl. Stat. 14, 94–115 (2019).

    Google Scholar 

  46. Martin, B. D., Witten, D. & Willis, A. D. corncob: Count Regression for Correlated Observations with the Beta-Binomial. CRAN: Contributed Packages https://doi.org/10.32614/CRAN.package.concorb (2021).

  47. Liu, Y. & Xie, J. Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures. J. Am. Stat. Assoc. 115, 393 (2019).

    Google Scholar 

  48. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300 (1995).

    Google Scholar 

Download references

Acknowledgements

We thank Dan Kim for assistance with DNA sequencing. Work described in this paper was supported by NIH grants R01AG061302 and R01ES034012.

Author information

Authors and Affiliations

Authors

Contributions

R.B. and M.S. conceived the project and wrote the paper. R.B. set up all the experiments and analyzed the data. K.S. contributed to microbiome analysis.

Corresponding authors

Correspondence to
Rahul Bodkhe or Michael Shapira.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

41522_2026_975_MOESM1_ESM (download PDF )

41522_2026_975_MOESM2_ESM (download ZIP )

41522_2026_975_MOESM3_ESM (download XLSX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Bodkhe, R., Sankaran, K. & Shapira, M. Caenorhabditis elegans populations shape their microbial environment.
npj Biofilms Microbiomes (2026). https://doi.org/10.1038/s41522-026-00975-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41522-026-00975-z


Source: Ecology - nature.com

Urban forests baseline and ecosystem benefits of a tropical metropolis: case of Dhaka, Bangladesh

The classification and determinants of the 15-minute city across 339 Chinese cities

Back to Top