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Drosophila embryonic development at single-cell resolution

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A new atlas charting the continuum of embryo development in fruit flies has gone further thanks to machine learning. Credit: Isabel Romero Calvo/EMBL

Scientists have created the most complete and detailed single-cell map of embryo development in any animal to date, using the fruit fly as a model organism.

Published in ScienceThis study, co-led by Eileen Furlong of EMBL and Jay Shendure of the University of Washington, uses data from more than one million embryonic cells spanning all stages of embryo development and represents significant progress on multiple levels. This fundamental research also helps scientists answer questions such as how mutations lead to various developmental defects. In addition, it provides a path to understand the huge non-coding portion of our genome that contains most disease-related mutations.

“Just capturing the whole of embryogenesis — all stages and all cell types — to get a more complete picture of the cell states and molecular changes that accompany development is an achievement in itself,” said Eileen Furlong, head of the Division of Genome Biology from EMBL. . “But what I’m really excited about is using deep learning to get a continuous picture of the molecular changes that drive embryonic development — down to the minute.”

Embryonic development begins with the fertilization of an egg, followed by a series of cell divisions and decisions that give rise to a highly complex multicellular embryo that can move, eat, perceive and interact with its environment. Researchers have been studying this process of embryonic development for more than a hundred years, but only in the last decade have new technologies enabled scientists to identify molecular changes associated with cell transitions at the single-cell level.

These single-cell studies have generated tremendous excitement as they have demonstrated the complexity of cell types in tissues, even identified new cell types, and revealed their developmental pathways alongside underlying molecular changes. However, attempts to profile entire embryo development with single-cell resolution have been unattainable due to the many technical challenges in sampling, cost, and technologies.

In this regard, the fruit fly (Drosophila melanogaster), an excellent model organism in developmental biology, gene regulation and chromatin biology, has some important advantages when it comes to developing new approaches to address this. The embryonic development of fruit flies is extremely fast; within just 20 hours of conception, all tissues are formed, including the brain, gut and heart, allowing the organism to crawl and eat. This, coupled with the many discoveries of fruit flies that have boosted understanding of how genes and their products work, encouraged the Furlong lab and their collaborators to take up this challenge.

“Our goal was to get a continuous picture of all stages of embryogenesis, to capture all the dynamics and changes as an embryo develops, not only at the level of RNA, but also the control elements that control this process.” regulate,” said co-author Stefano Secchia, a Ph.D. student in the Furlong group.

Preliminary work with ‘enhancers’

In 2018, the Furlong and Shendure groups demonstrated the feasibility of: profiling of “open” chromatin at single cell resolution in embryos and how these DNA regions often represent active developmental enhancers. Enhancers are segments of DNA that act as control switches to turn genes on and off. The data showed which cell types in the embryo use which enhancers at a given time and how this use changes over time. Such a map is essential for understanding what drives specific aspects of embryonic development.

“I got really excited when I saw those results,” Furlong said. “To go beyond RNA to look upstream at these regulatory switches in individual cells was something I didn’t think would be possible for a long time.”

Going beyond ‘snapshots’

The 2018 study was state-of-the-art at the time, profiling ~20,000 cells in three different windows of embryo development (at the beginning, middle and end). However, this work still only provided snapshots of the cellular diversity and regulation during specific discrete time points. The team therefore explored the potential of using examples from overlapping time windows, and applied the concept as a proof-of-principle to one specific line:the muscle.

This then set the stage to scale up dramatically using new technology developed in the Shendure lab. The team’s current work profiled open chromatin from nearly one million cells and RNA from half a million cells from overlapping time points spanning the entire development of fruit fly embryos.

Using a kind of machine learning, the researchers took advantage of the overlapping time points to predict time with a much finer resolution. Co-author Diego Calderon, a postdoctoral researcher in the Shendure lab, trained a neural network to predict the precise development time for each cell.

“Although the collected samples contained embryos with slightly different ages within a 2 or 4 hour time window, this method allows you to zoom in on any part of this embryogenesis timeline on a minute scale,” Calderon said.

Shendure added, “I was amazed at how well this works. We were able to capture molecular changes that occur very quickly in time, in minutes, that previous researchers had discovered by hand-picking embryos every three minutes.”

In the future, such an approach would not only save time, but could also serve as a reference for normal embryo development to see how things might change in different mutant embryos. This could indicate exactly when and in which cell type the phenotype of a mutant arises, as the researchers showed in the muscle. In other words, this work not only helps to understand how development normally proceeds, but also opens the door to understanding how different mutations can mess it up.

The new predictive potential this research predicts, based on samples from much larger time windows, could be used as a framework for other model systems. For example, the development of mammalian embryos, in vitro cell differentiation, or even post-drug treatment in diseased cells, where gaps in sampling times can be designed to allow optimal time prediction at a finder resolution.

In the future, the team plans to explore the atlas’ predictive powers.

“By combining all the new tools we have at our disposal in single-cell genomics, computation and genetic engineering, I would like to see if we can predict what will happen to the fate of individual cells. in vivo after a genetic mutation,” Furlong said. “…but we’re not there yet. But before this project, I also thought that the current work would not be possible anytime soon.”

Use of chromatin in individual cells reveals developmental pathways

More information:
Diego Calderon et al, The Drosophila Embryonic Development Continuum at Single Cell Resolution, Science (2022). DOI: 10.1126/science.abn5800. www.science.org/doi/10.1126/science.abn5800

Provided by European Molecular Biology Laboratory

Quote: Drosophila Embryonic Development at Single Cell Resolution (2022, Aug 4), retrieved Aug 5, 2022 from https://phys.org/news/2022-08-drosophila-embryonic-single-cell-resolution.html

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