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New video tool peers deeply into growing embryos

The approach can detect heartbeat changes earlier than the human eye.
Shraddha Chakradhar is associate news editor for Nature Medicine in Boston.

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For Oliver Tills, it was all about timing. As a doctoral student at the University of Plymouth in the UK, he was interested in learning when along an embryo’s developmental timeline the different changes associated with growth—changes such as size, shape and movement—happen. Tills was working with snail embryos, but this question of timing has also intrigued other scientists, especially human embryologists, since human embryos aren’t easy to procure and observe during development. “What we know about early development is almost nothing,” says Tills, who is now a marine biologist at the University of Plymouth.

But a new tool that Tills began developing nearly a decade ago could finally let scientists see when and how embryos go through various changes as they slowly morph into larger beings. Tills and his coauthors at the University of Plymouth recently shared their findings in a December study1 published in PLoS Biology.

The technology, which the authors call EmbryoPhenomics, is capable of detecting changes that would go unnoticed by a researcher who is simply looking through a microscope. These changes include slowing down of the heartbeat and the development of gut muscles. Some changes happen so slowly, according to Tills, that the only way to observe them is by capturing successive images of the embryo’s growth and speeding up playback of the images so that the changes are discernible.

Tills’ tool captures millions of images of the growing embryo, and the accompanying software converts the traits within the images into pixelated graphs so that Tills and his team can look for changes in the traits. “We’re beginning to understand biology in a way others haven’t been able to do,” Tills says.

In the study, for instance, the authors were able to manipulate the temperature in which these embryos grew and found that at 30 °C, the overall energy—measured through qualities such as heartrate, movement and growth—of the embryos was low compared with snail and shrimp embryos grown under temperatures that were about 10 °C cooler. “We’re interested in how climate change affects these creatures,” Tills says, so it makes sense that increasingly warming waters will negatively affect these cold-blooded freshwater and marine species.

He sees the technology as also having translational value for human embryos. “What we’re learning is that not only are embryos sensitive to environmental changes, but they might be actually be more sensitive to environmental factors in this early stage of development,” Tills says. This technology could similarly be used to test the effects of outside influences, including specific drugs or toxicants, on model organisms that serve to inform us about human biology. Andreas Vogt, a systems biologist at the University of Pittsburgh School of Medicine, uses zebrafish—an essential model organism for human biology—for drug-discovery work and says that the technology described in the study could supplement the work he does. For instance, “I’d be interested in measuring the heart rate of an embryo in order to see how it responds to a drug,” Vogt says.

Automated process

In 2009, when Tills was a doctoral student, the methodology at the time required him to stay next to the microscope in a really cold lab for hours on end taking manual measurements of snail embryos. If he left the research bench, it meant that he would potentially miss an important moment in the embryos’ development. “If you took a call or went out to lunch, and it happened to be when embryos were going through changes, then you’d find you had large gaps in your understanding,” he says.

So he set out to build something that wouldn’t need constant attention. The EmbryoPhenomics platform is almost fully automated. The only human involvement occurs when a scientist loads the embryos into a tray full of little wells and sets the tray into the incubation chamber. Here, the embryos can stay for as long as the scientists choose. In the study, Tills and his team demonstrated that the system was capable of running for anywhere from a day-long experiment to a two-week time span, but according to Tills, there really is no limit on how long the system can keep going.

Current technology that is able to capture early embryonic development is used in the setting of in vitro fertilization, where clinicians are interested in seeing whether an embryo is viable. But these technologies stop chronicling the development after the first day or two, and are largely used to investigate surrogate measures of health, such as the symmetry of new cells within the embryo (asymmetry is thought to be an indicator that the embryo may be in poor health2). Other technologies are also not capable of handling the massive amount of data generated from millions of images captured over several days. For one of the experiments described in the study, the technology took 18 million images, which amounted to over 20 terabytes of data. The images and graphs were generated by the computer within a day or two of the experiment, according to Tills, rather than weeks.

“The information from these video images is complex,” says Stewart Owen, an environmental toxicologist at AstraZeneca. “Extracting detailed information from images is technically the bottleneck that holds up many fields,” Owen says, adding the fact that Tills’s system manages to do this is where his work takes a “step forward” from other technologies.

The next step, according to Tills, is to use deep-learning algorithms to help unpack all the data being generated. “What we know about biology is that things don’t work in isolation,” Tills says. By putting things together in an algorithm that can look at all the data and pick up on trends, “It’s going to tell us something fundamental about the nature of embryonic development.”

doi: 10.1038/d41591-019-00006-9
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References

  1. 1.

    Tills, O. et al. PLoS Biology 16, e3000074 (2018).

  2. 2.

    Yumoto, K., Sugishima, M. & Mio, Y. Fertil. Steril. 104, e151 (2015).

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