Regeneration in the absence of canonical neoblasts in an early branching flatworm.

The remarkable regenerative abilities of flatworms are closely linked to neoblasts - adult pluripotent stem cells that are the only division-competent cell type outside of the reproductive system. Although the presence of neoblast-like cells and whole-body regeneration in other animals has led to the idea that these features may represent the ancestral metazoan state, the evolutionary origin of both remains unclear. Here we show that the catenulid Stenostomum brevipharyngium, a member of the earliest-branching flatworm lineage, lacks conventional neoblasts despite being capable of whole-body regeneration and asexual reproduction. Using a combination of single-nuclei transcriptomics, in situ gene expression analysis, and functional experiments, we find that cell divisions are not restricted to a single cell type and are associated with multiple fully differentiated somatic tissues. Furthermore, the cohort of germline multipotency genes, which are considered canonical neoblast markers, are not expressed in dividing cells, but in the germline instead, and we experimentally show that they are neither necessary for proliferation nor regeneration. Overall, our results challenge the notion that canonical neoblasts are necessary for flatworm regeneration and open up the possibility that neoblast-like cells may have evolved convergently in different animals, independent of their regenerative capacity.

Adaptive robustness through incoherent signaling mechanisms in a regenerative brain.

Animal behavior emerges from collective dynamics of neurons, making it vulnerable to damage. Paradoxically, many organisms exhibit a remarkable ability to maintain significant behavior even after large-scale neural injury. Molecular underpinnings of this extreme robustness remain largely unknown. Here, we develop a quantitative pipeline to measure long-lasting latent states in planarian flatworm behaviors during whole-brain regeneration. By combining >20,000 animal trials with neural network modeling, we show that long-range volumetric peptidergic signals allow the planarian to rapidly restore coarse behavior output after large perturbations to the nervous system, while slow restoration of small-molecule neuromodulator functions refines precision. This relies on the different time and length scales of neuropeptide and small-molecule transmission to generate incoherent patterns of neural activity that competitively regulate behavior. Controlling behavior through opposing communication mechanisms creates a more robust system than either alone and may serve as a generalizable approach for constructing robust neural networks.