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Quantitative analysis of variability and robustness in spatial pattern formation

Periodic Reporting for period 4 - SPACEVAR (Quantitative analysis of variability and robustness in spatial pattern formation)

Reporting period: 2021-07-01 to 2022-12-31

During embryonic development a single cell turns into a complex organism. This process is characterized by an antagonism between variation and stability. On the one hand, development is a tightly controlled process; tissues need to be specified at the right time, at the correct spatial position, and with a defined size. On the other hand, regulation should not be too rigid, since embryos need to adjust to environmental perturbations and correct errors caused by noisy gene expression. Furthermore, it remains unclear to which extent vertebrate embryos can tolerate perturbations of cell lineages. This project was focused on studying variation and stability during pattern formation in the zebrafish heart. We sought to understand the origin of embryo-to-embryo variability as well as robustness against perturbation.

The zebrafish heart is a powerful model system for studying variability, since heart positioning is inverted along the left/right axis in 5-10% of wildtype embryos. Here, we combined light microscopy and gene expression analysis to reveal the mechanisms and principles underlying variability in heart positioning. To expand our study of embryo-to-embryo variability, we further developed a method for high-throughput single-cell lineage tracing based on CRISPR-Cas9. This novel approach allows us to study embryo-to-embryo variability in developmental lineage specification systematically and on a massively parallel level. Finally, we used this strategy to explore the regenerative capacity of the zebrafish heart upon injury, which allowed us to reveal the origin and function of pro-regenerative fibroblasts. In summary, these quantitative experiments provided unprecedented insights into variability and robustness during development as well as regeneration of adult organs upon injury.

The concepts developed here can help us understand variable outcomes in human genetic disease, and one of our long-term goals is to develop strategies for regenerative therapies in humans. Furthermore, the methods established in this project will be useful for understanding mechanisms of disease in a broad range of systems.
In WP1, we set out to determine the source of stochastic heart laterality fluctuations in the zebrafish. We discovered that this phenomenon is linked to global left/right signaling in the zebrafish embryo, and we could show that fluctuations in the number of dorsal forerunner cells, a small cell population specified at gastrulation stages, is responsible for stochastic heart inversion. Specifically, we could show by live microscopy that those embryos in which the number of dorsal forerunner cells is smallest develop laterality defects with much higher probability (Fig. 1). We found that these fluctuations are largely stochastic, with only a minor genetic component (Moreno-Ayala et al., Cell Reports, 2021).

In WP2, we proposed to develop a method for simultaneous cell type identification and lineage tracing in thousands of single cells. This project progressed exceedingly well and led to a high-level publication early in the funding period (Spanjaard et al., Nature Biotech, 2018). Specifically, we developed experimental approaches for generating lineage barcodes in zebrafish embryos by CRISPR/Cas9 and for detecting these barcodes by single cell transcriptomics (Fig. 2). Importantly, we characterized the diversity of the barcodes and the dynamics of cell labeling. Furthermore, we developed computational methods for lineage tree reconstruction based on this data. In summary, we now have a method that allows simultaneous cell type identification and lineage tracing in thousands of single cells. We continued to further improve the experimental technology throughout the funding period (manuscript in preparation).

In WP3, we used high-throughput lineage tracing to systematically identify the origin of transient cell types in the adult zebrafish heart that arise during regeneration after injury. By combining this data with functional experiments for targeted cell type depletion, we identified the origin and function of a transient population of pro-regenerative fibroblasts (Hu et al., Nat Genet, 2022). This work included improved computational analysis of high-throughput lineage data (compared to our earlier publication from WP2) as well as spatial transcriptomics analysis of the heart using tomo-seq.
WP1 led to the identification of a remarkable phenomenon: Fluctuations in cell numbers at an early developmental stage are not buffered or corrected, but instead manifest themselves by a macroscopic phenotype – a laterality defect (Moreno-Ayala et al., Cell Reports, 2021). This is an important conceptual novelty, which may have profound consequences also for human genetics, since similar phenomena might underlie incomplete penetrance of mutations in the human population.

In WP2, we developed a method for high-throughput lineage tracing (Spanjaard et al., Nat Biotech, 2018), which allows to identify the lineage origin of thousands of single cells from the same animal. Together with several other papers, this manuscript was selected by Science as the "Breakthrough of the Year 2018". We continue to improve this method on the experimental and computational level by e.g. introducing additional barcodes, extending the period of lineage recording, optimizing barcode recovery during single-cell RNA-seq, and by improving algorithms for lineage tree reconstruction.

In WP3, we studied how the zebrafish heart reacts to injury, by focusing on understanding the origin of transient cell types that arise during regeneration in the adult heart. We identified the origin and function of a previously uncharacterized population of pro-regenerative fibroblasts (Hu et al., Nat Genet, 2022) by combining the methodology developed in WP2 with functional experiments for targeted cell type depletion.
Fig. 1. The probability for heart inversion is higher in embryos with less dorsal forerunner cells.
Fig. 2. Experimental strategy for high-throughout lineage tracing.