A single-cell multiomic approach in planarians to understand regeneration.

Lead Research Organisation: Oxford Brookes University
Department Name: Faculty of Health and Life Sciences

Abstract

Many animals are able to regenerate missing body parts and organs when they are injured. This ability, very reduced in humans and other mammals, is present in animals such as freshwater planarians. The planarian Schmidtea mediterranea can regenerate any body part in a matter of days. Thanks to its amenability for experimentation and ease of research use, S. mediterranea has become a powerful laboratory model where to study regeneration. Understanding this process is fundamental for regenerative medicine, as it seeks to recreate it with human cells in the laboratory, and ultimately in the clinic.

Planarians regenerate thanks to a stem cell population present in their adult stages, the so-called neoblasts. Years of research have revealed genes, signals, molecules and processes that are important for planarian regeneration. However, these studies have suffered from the lack of cellular resolution: we do not know in which cell types these signals are active and how the different cell types coordinate during the regeneration process to form a tissue as complex as a head or a tail. Partly this is because current techniques to dissect the process genetically typically blend all tissues and cell types into bulk samples. Other techniques with high cellular resolution suffer from low throughput, giving information of a few genes in each assay.

We have recently helped develop and used a very novel set of techniques that are revolutionising biology: single-cell analysis. It allows profiling the genetic information of thousands of individual cells by sequencing messenger RNAs and gene regulatory elements from each of them. With this, we can classify the major planarian cell types such as muscle, neurons, epidermis and dozens more and reconstruct their developmental processes. These methods have also been used in other developmental systems such as frogs, fish and newts, leading the way to a single-cell revolution of stem cell and developmental biology. The latest version of this method that we have already set up allow us to profile ~10-100 times more cells per experiment and makes feasible performing large sample sets with replicate experiments. This is a key modification to obtain statistically significant information.

Thus, to understand how planarian regeneration works at the level of the individual cells that participate in the process, we will obtain single cell analysis profiles of around half a million cells, from different regeneration times, body parts and in replicates. Analysing all this information will allow us to elucidate which genes are activated in each cell type and at what time points during the process. We will perturb the function of these genes using well-established planarian methods to obtain functional information about the role of these genes from the effects of the perturbation. We will analyse these by further single-cell transcriptomic experiments. All of these experiments will tell us how each individual cell type behaves in the regeneration process. With such technique and cell numbers, even the rarest cell types will be captured. We will elucidate the signals they use to instruct the regenerative cells to integrate in the new regenerating tissue, and the functional effects of these signals.

Altogether, these experiments will allow us to analyse planarian regeneration in an unprecedented quantitative way and at the single-cell level and with functional information. This will be a significant step towards understanding animal regeneration. Our data will spur novel studies on planarians to study the regulators and processes that we uncover and lead the way in the study of animal regeneration in other animals. The tools and methods that we will use for the first time will become standard in the study of regeneration and developmental processes, and key for single-cell biology. Understanding how animals regenerate is key to advance the agenda of human regenerative medicine.

Technical Summary

Regeneration is the ability to replace tissues and organs lost to injury. The planarian Schmidtea mediterranea is a convenient lab model that regenerates any body part in a matter of days. A pluripotent stem cell population underlies the process. Dozens of cell types have been described, present throughout the body intermingled in a complex pattern. Despite extensive studies, it is still unknown how each tissue instructs the regenerative cells to integrate in the blastema, what are the signals that they use, and how do regenerative cells respond to these signals. Partly, this is because common techniques such as RNA-sequencing lack cellular resolution. Recently, single-cell techniques have revolutionised biology as they offer unprecedented cellular resolution combined with a very high throughput and will therefore be key to answer these questions. We previously used these methods to reconstruct all differentiation trajectories of planarian stem cells into a single differentiation tree. We have already optimised a novel single-cell transcriptomic approach that will allow us to obtain many more cells, with replicates to obtain statistical power and knockdown samples to obtain mechanistic information. With this method we will then elucidate in each cell type a) the quantitative changes in abundance, b) the timing of differentiation in regeneration and c) the quantitative changes in gene expression. To obtain mechanistic information, we will perform knockdown experiments with regeneration regulators. Altogether, these experiments will allow us to analyse the contribution of each cell type to regeneration in an unprecedented quantitative way and at the single-cell level, allowing us to better understand planarian regeneration and lead the way in the study of animal regeneration in other animals. Understanding animal regeneration will provide key information that will inform the deployment of human regenerative medicine.

Publications

10 25 50