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The embryo assembles itself

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The embryo assembles itself


Biological processes depend on puzzle pieces coming together and interacting. Under specific conditions, these interactions can create something new without external input. This is called self-organization, as seen in a school of fish or a flock of birds. Interestingly, the mammalian embryo develops similarly. In PNAS, David Brückner and Gašper Tkačik from the Institute of Science and Technology Austria (ISTA) introduce a mathematical framework that analyzes self-organization from a single cell to a multicellular organism.

When an embryo develops, many types of cells with different functions need to be generated. For example, some cells will become part of the eye and record visual stimuli, while others will be part of the gut and help digest food. To determine their roles, cells are constantly communicating with each other using chemical signals.

Thanks to this communication, during development, everything is well synchronized and coordinated, and yet there is no central control responsible for this. The cell collective is self-organized and orchestrated by the interactions between the individuals. Each cell reacts to signals of its neighbors. Based on such self-organization, the mammalian embryo develops from a single fertilized egg cell into a multicellular organism.

David Brückner and Gašper Tkačik from the Institute of Science and Technology Austria (ISTA) have now established a mathematical framework that helps analyze this process and predict its optimal parameters. Published in PNAS, this approach represents a unifying mathematical language to describe biological self-organization in embryonic development and beyond.

The self-assembling embryo

In nature, self-organization is all around us: we can observe it in fish schools, bird flocks, or insect collectives, and even in microscopic processes regulated by cells. NOMIS fellow and ISTA postdoc David Brückner is interested in getting a better understanding of these processes from a theoretical standpoint. His focus lies on embryonic development — a complex process governed by genetics and cells communicating with each other.

During embryonic development, a single fertilized cell turns into a multicellular embryo containing organs with lots of different features. “For many steps in this developmental process, the system has no extrinsic signal that directs it what to do. There is an intrinsic property of the system that allows it to establish patterns and structures,” says Brückner. “The intrinsic property is what is known as self-organization.” Even with unpredictable factors — which physicists call “noise” — the embryonic patterns are formed reliably and consistently. In recent years, scientists have gained a deeper understanding of the molecular details that drive this complex process. A mathematical framework to analyze and quantify its performance, however, was lacking. The language of information theory provides answers.

Bridging expertise

“Information theory is a universal language to quantify structure and regularity in statistical ensembles, which are a collection of replicates of the same process. Embryonic development can be seen as such a process that reproducibly generates functional organisms that are very similar but not identical,” says Gašper Tkačik, professor at ISTA and expert in this field. For a long time, Tkačik has been studying how information gets processed in biological systems, for instance in the fly embryo. “In the early fly embryo, patterns are not self-organized,” he continues. “The mother fly puts chemicals into the egg that instruct the cells on what actions to take.” As the Tkačik group had already developed a framework for this system, Brückner reached out to develop one for the mammalian embryo as well. “With Gašper’s expertise in information theory, we were able to put it together,” Brückner adds excitedly.

Beyond embryo development?

During embryonic development, cells exchange signals and are constantly subject to random, unpredictable fluctuations (noise). Therefore, cellular interactions must be robust. The new framework measures how these interactions are possibly optimized to withstand noise. Using computer simulations of interacting cells, the scientists explored the conditions under which a system can still have a stable final result despite introducing fluctuations.

Although the framework has proven to be successful on three different developmental models that all rely on chemical and mechanical signaling, additional work will be required to apply it to experimental recordings of developmental systems. “In the future, we want to study more complex models with more parameters and dimensions,” Tkačik says. “By quantifying more complex models, we could also apply our framework to experimentally measured patterns of chemical signals in developing embryos,” adds Brückner. For this purpose, the two theoretical scientists will team up with experimentalists.



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Prying open the AI black box

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Prying open the AI black box


Artificial intelligence continues to squirm its way into many aspects of our lives. But what about biology, the study of life itself? AI can sift through hundreds of thousands of genome data points to identify potential new therapeutic targets. While these genomic insights may appear helpful, scientists aren’t sure how today’s AI models come to their conclusions in the first place. Now, a new system named SQUID arrives on the scene armed to pry open AI’s black box of murky internal logic.

SQUID, short for Surrogate Quantitative Interpretability for Deepnets, is a computational tool created by Cold Spring Harbor Laboratory (CSHL) scientists. It’s designed to help interpret how AI models analyze the genome. Compared with other analysis tools, SQUID is more consistent, reduces background noise, and can lead to more accurate predictions about the effects of genetic mutations.

How does it work so much better? The key, CSHL Assistant Professor Peter Koo says, lies in SQUID’s specialized training.

“The tools that people use to try to understand these models have been largely coming from other fields like computer vision or natural language processing. While they can be useful, they’re not optimal for genomics. What we did with SQUID was leverage decades of quantitative genetics knowledge to help us understand what these deep neural networks are learning,” explains Koo.

SQUID works by first generating a library of over 100,000 variant DNA sequences. It then analyzes the library of mutations and their effects using a program called MAVE-NN (Multiplex Assays of Variant Effects Neural Network). This tool allows scientists to perform thousands of virtual experiments simultaneously. In effect, they can “fish out” the algorithms behind a given AI’s most accurate predictions. Their computational “catch” could set the stage for experiments that are more grounded in reality.

“In silico [virtual] experiments are no replacement for actual laboratory experiments. Nevertheless, they can be very informative. They can help scientists form hypotheses for how a particular region of the genome works or how a mutation might have a clinically relevant effect,” explains CSHL Associate Professor Justin Kinney, a co-author of the study.

There are tons of AI models in the sea. More enter the waters each day. Koo, Kinney, and colleagues hope that SQUID will help scientists grab hold of those that best meet their specialized needs.

Though mapped, the human genome remains an incredibly challenging terrain. SQUID could help biologists navigate the field more effectively, bringing them closer to their findings’ true medical implications.



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Iron meteorites hint that our infant solar system was more doughnut than dartboard

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Iron meteorites hint that our infant solar system was more doughnut than dartboard


Four and a half billion years ago, our solar system was a cloud of gas and dust swirling around the sun, until gas began to condense and accrete along with dust to form asteroids and planets. What did this cosmic nursery, known as a protoplanetary disk, look like, and how was it structured? Astronomers can use telescopes to “see” protoplanetary disks far away from our much more mature solar system, but it is impossible to observe what ours might have looked like in its infancy — only an alien billions of light years away would be able to see it as it once was.

Fortunately, space has dropped a few clues — fragments of objects that formed early in solar system history and plunged through Earth’s atmosphere, called meteorites. The composition of meteorites tells stories of the solar system’s birth, but these stories often raise more questions than answers.

In a paper published in Proceedings of the National Academy of Sciences, a team of planetary scientists from UCLA and Johns Hopkins University Applied Physics Laboratory reports that refractory metals, which condense at high temperatures, such as iridium and platinum, were more abundant in meteorites formed in the outer disk, which was cold and far away from the sun. These metals should have formed close to the sun, where the temperature was much higher. Was there a pathway that moved these metals from the inner disk to the outer?

Most meteorites formed within the first few million years of solar system history. Some meteorites, called chondrites, are unmelted conglomerations of grains and dust left over from planet formation. Other meteorites experienced enough heat to melt while their parent asteroids were forming. When these asteroids melted, the silicate part and the metallic part separated due to their difference in density, similar to how water and oil don’t mix.

Today, most asteroids are located in a thick belt between Mars and Jupiter. Scientists think that Jupiter’s gravity disrupted the course of these asteroids, causing many of them to smash into each other and break apart. When pieces of these asteroids fall to Earth and are recovered, they are called meteorites.

Iron meteorites are from the metallic cores of the earliest asteroids, older than any other rocks or celestial objects in our solar system. The irons contain molybdenum isotopes that point toward many different locations across the protoplanetary disk in which these meteorites formed. That allows scientists to learn what the chemical composition of the disk was like in its infancy.

Previous research using the Atacama Large Millimeter/submillimeter Array in Chile has found many disks around other stars that resemble concentric rings, like a dartboard. The rings of these planetary disks, such as HL Tau, are separated by physical gaps, so this kind of disk could not provide a route to transport these refractory metals from the inner disk to the outer.

The new paper holds that our solar disk likely didn’t have a ring structure at the very beginning. Instead, our planetary disk looked more like a doughnut, and asteroids with metal grains rich in iridium and platinum metals migrated to the outer disk as it rapidly expanded.

But that confronted the researchers with another puzzle. After the disk expansion, gravity should have pulled these metals back into the sun. But that did not happen.

“Once Jupiter formed, it very likely opened a physical gap that trapped the iridium and platinum metals in the outer disk and prevented them from falling into the sun,” said first author Bidong Zhang, a UCLA planetary scientist. “These metals were later incorporated into asteroids that formed in the outer disk. This explains why meteorites formed in the outer disk — carbonaceous chondrites and carbonaceous-type iron meteorites — have much higher iridium and platinum contents than their inner-disk peers.”

Zhang and his collaborators previously used iron meteorites to reconstruct how water was distributed in the protoplanetary disk.

“Iron meteorites are hidden gems. The more we learn about iron meteorites, the more they unravel the mystery of our solar system’s birth,” Zhang said.



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Supermassive black hole appears to grow like a baby star

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Supermassive black hole appears to grow like a baby star


Supermassive black holes pose unanswered questions for astronomers around the world, not least “How do they grow so big?” Now, an international team of astronomers, including researchers from Chalmers University of Technology in Sweden, has discovered a powerful rotating, magnetic wind that they believe is helping a galaxy’s central supermassive black hole to grow. The swirling wind, revealed with the help of the ALMA telescope in nearby galaxy ESO320-G030, suggests that similar processes are involved both in black hole growth and the birth of stars.

Most galaxies, including our own Milky Way have a supermassive black hole at their centre. How these mind-bogglingly massive objects grow to weigh as much as millions or billions of stars is a long-standing question for astronomers.

In search of clues to this mystery, a team of scientists led by Mark Gorski (Northwestern University and Chalmers) and Susanne Aalto (Chalmers) chose to study the relatively nearby galaxy ESO320-G030, only 120 million light years distant. It’s a very active galaxy, forming stars ten times as fast as in our own galaxy.

“Since this galaxy is very luminous in the infrared, telescopes can resolve striking details in its centre. We wanted to measure light from molecules carried by winds from the galaxy’s core, hoping to trace how the winds are launched by a growing, or soon to be growing, supermassive black hole. By using ALMA, we were able to study light from behind thick layers of dust and gas,” says Susanne Aalto, Professor of Radio Astronomy at Chalmers University of Technology.

To zero in on dense gas from as close as possible to the central black hole, the scientists studied light from molecules of hydrogen cyanide (HCN). Thanks to ALMA’s ability to image fine details and trace movements in the gas — using the Doppler effect — they discovered patterns that suggest the presence of a magnetised, rotating wind.

While other winds and jets in the centre of galaxies push material away from the supermassive black hole, the newly discovered wind adds another process, that can instead feed the black hole and help it grow.

“We can see how the winds form a spiralling structure, billowing out from the galaxy’s centre. When we measured the rotation, mass, and velocity of the material flowing outwards, we were surprised to find that we could rule out many explanations for the power of the wind, star formation for example. Instead, the flow outwards may be powered by the inflow of gas and seems to be held together by magnetic fields,” says Susanne Aalto.

The scientists think that the rotating magnetic wind helps the black hole to grow.

Material travels around the black hole before it can fall in — like water around a drain. Matter that approaches the black hole collects in a chaotic, spinning disk. There, magnetic fields develop and get stronger. The magnetic fields help lift matter away from the galaxy, creating the spiralling wind. Losing matter to this wind also slows the spinning disk — that means that matter can flow more easily into the black hole, turning a trickle into a stream.

For Mark Gorski, the way this happens is strikingly reminiscent of a much smaller-scale environment in space: the swirls of gas and dust that lead up to the birth of new stars and planets.

“It is well-established that stars in the first stages of their evolution grow with the help of rotating winds — accelerated by magnetic fields, just like the wind in this galaxy. Our observations show that supermassive black holes and tiny stars can grow by similar processes, but on very different scales,” says Mark Gorski.

Could this discovery be a clue to solving the mystery of how supermassive black holes grow? In the future, Mark Gorski, Susanne Aalto and their colleagues want to study other galaxies which may harbour hidden spiralling outflows in their centres.

“Far from all questions about this process are answered. In our observations we see clear evidence of a rotating wind that helps regulate the growth of the galaxy’s central black hole. Now that we know what to look for, the next step is to find out how common a phenomenon this is. And if this is a stage which all galaxies with supermassive black holes go through, what happens to them next?,” asks Mark Gorski.



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