The microbial community, or microbiome, of the gut is known to influence human health. Previous studies have focused on determining the types of microbes that are present. Unfortunately, this information is not enough to understand the microbiome.

“The gut environment is shaped by small molecules known as metabolites, which are excreted by the microbial community,” said Sergei Maslov (BCXT/CABBI), a professor of bioengineering and Bliss faculty scholar. “Although it is possible to measure these metabolites experimentally, it is cumbersome and expensive.”

The researchers had previously published a study where they used experimental data from other studies to model the fate of metabolites as they pass through the gut microbiome. In the new study, they have used the same model to predict new microbial processes that have not been determined before.

“What we eat passes into our gut, and there is a cascade of microbes which release metabolites,” said Akshit Goyal, a postdoctoral fellow at MIT and a collaborator of the Maslov lab. “Biologists have measured these molecules in human stools, we have shown that you can use computational models to predict the levels of some.”

Measuring every metabolite and trying to understand which microbe might be releasing it can be challenging. “There is a large universe of possible cross-feeding interactions. Using this model, we can aid experiments by predicting which ones are more likely to occur in the gut,” Goyal said.

The model was also supported by genomic annotations, which explain which microbial genes are responsible for processing the metabolites. “We are confident of our modelling predictions because we also checked whether the microbes contain the genes necessary for carrying out the associated reactions. About 65% of our predictions were supported by this information,” said Veronika Dubinkina, a PhD student in bioengineering.

The researchers are now working to improve the model by including more experimental data. “Different people have different strains of gut microbes. Although these different strains have many genes in common, they differ in their capabilities,” Dubinkina said. “We need to collect more data from patients to understand how different microbial communities behave in different hosts.”

“We are also interested in determining how fast the microbes consume and secrete the metabolites,” said Tong Wang, a PhD student in physics. “Currently the model assumes that all the microbes consume metabolites at the same rate. In reality, the rates are different and we need to understand them to capture the metabolite composition in the gut.”

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Materials provided by Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign. Original written by Ananya Sen. Note: Content may be edited for style and length.

In a paper publishing today in the SIAM Journal on Imaging Sciences, Matan Leibovich (New York University), George Papanicolaou (Stanford University), and Chrysoula Tsogka (University of California, Merced) introduce a new method for taking high-resolution images of fast-moving and rotating objects in space, such as satellites or debris in LEO. They created an imaging process that first utilizes a novel algorithm to estimate the speed and angle at which an object in space is rotating, then applies those estimates to develop a high-resolution picture of the target.

Leibovich, Papanicolaou, and Tsogka used a theoretical model of a space imaging system to construct and test their imaging process. The model depicts a piece of fast-moving debris as a cluster of very small, highly reflective objects that represent the strongly reflective edges of an item in orbit, such as the solar panels on a satellite. The cluster of reflectors all move together with the same speed and direction and rotate about a common center. In the model, multiple sources of radiation on the Earth’s surface — such as the ground control stations of global navigation satellite systems — emit pulses that are reflected by target pieces of space debris. A distributed set of receivers then detects and records the signals that bounce off the targets.

The model focuses on sources that produce radiation in the X-band, or from frequencies of 8 to 12 gigahertz. “It is well known that resolution can be improved by using higher frequencies, such as the X-band,” Tsogka said. “Higher frequencies, however, also result in distortions to the image due to ambient fluctuations from atmospheric effects.” Signals are distorted by turbulent air as they travel from the target to receivers, which can make the imaging of objects in LEO quite challenging. The first step of the authors’ imaging process was thus to correlate the data taken at different receivers, which can help reduce the effects of these distortions.

The diameter of the area encompassed by the receivers is called the physical aperture of the imaging system — in the model, this is about 200 kilometers. Under normal imaging conditions, the physical aperture’s size determines the resolution of the resulting image; a larger aperture begets a sharper picture. However, the quick movement of the imaging target relative to the receivers can create an inverse synthetic aperture, in which the signals that were detected at multiple receivers as the target moved throughout their field of view are synthesized coherently. This configuration can effectively improve the resolution, as if the imaging system had a wider aperture than the physical one.

Objects in LEO can spin on timescales that range from a full rotation every few seconds to every few hundred seconds, which complicates the imaging process. It is thus important to know — or at least be able to estimate — some details about the rotation before developing the image. The authors therefore needed to estimate the parameters related to the object’s rotation before synthesizing the data from different receivers. Though simply checking all of the possible parameters to see which ones yield the sharpest image is technically feasible, doing so would require a lot of computational power. Instead of employing this brute force approach, the authors developed a new algorithm that can analyze the imaging data to estimate the object’s rotation speed and the direction of its axis.

After accounting for the rotation, the next step in the authors’ imaging process was to analyze the data to develop a picture of the space debris that would hopefully be as accurate and well-resolved as possible. One method that researchers often employ for this type of imaging of fast-moving objects is the single-point migration of cross correlations. Though atmospheric fluctuations do not usually significantly impair this technique, it does not have a very high resolution. A different, commonly-used imaging approach called Kirchhoff migration can achieve a high resolution, as it benefits from the inverse synthetic aperture configuration; however, the trade-off is that it is degraded by atmospheric fluctuations. With the goal of creating an imaging scheme that is not too heavily affected by atmospheric fluctuations but still maintains a high resolution, the authors proposed a third approach: an algorithm whose result they call a rank-1 image. “The introduction of the rank-1 image and its resolution analysis for fast-moving and rotating objects is the most novel part of this study,” Leibovich said.

To compare the performance of the three imaging schemes, the authors gave simulated data of a rotating object in LEO to each one and compared the images that they produced. Excitingly, the rank-1 image was much more accurate and well-resolved than the result of single-point migration. It also had similar qualities to the output of the Kirchhoff migration technique. But this result was not entirely surprising, given the problem’s configuration. “It is important to note that the rank-1 image benefits from the rotation of the object,” Papanicolaou said. Though a rotating object generates more complex data, one can actually incorporate this additional information into the image processing technique to improve its resolution. Rotation at certain angles can also increase the size of the synthetic aperture, which significantly improves the resolution for the Kirchhoff migration and rank-1 images.

Further simulations revealed that the rank-1 image is not easily muddled by errors in the new algorithm for the estimation of rotation parameters. It is also more robust to atmospheric effects than the Kirchhoff migration image. If receivers capture data for a full rotation of the object, the rank-1 image can even achieve optimal imaging resolution. Due to its good performance, this new imaging method could improve the accuracy of imaging LEO satellites and space debris. “Overall, this study shed light on a new method for imaging fast-moving and rotating objects in space,” Tsogka said. “This is of great importance for ensuring the safety of the LEO band, which is the backbone of global remote sensing.”

These reconstructions are important for understanding how and when oxygen became available in Earth’s atmosphere and ultimately increased to the levels that support life as we know it today.

Yet reconstructions that rely on signals from sedimentary rocks but ignore the impact of local sedimentary processes do so at their own peril, according to geoscientists including David Fike in Arts & Sciences at Washington University in St. Louis.

Their new study published Feb. 26 in Science Advances is based on analyses of a mineral called pyrite (FeS₂) that is formed in the presence of bacteria. With its chemical-reduced iron (Fe) and sulphur (S), the burial of pyrite in marine sediments is one of the key controls on oxygen levels in Earth’s atmosphere and oceans.

The researchers compared pyrite in sediments collected in a borehole drilled in the shelf just off the eastern coast of New Zealand with sediments drilled from the same ocean basin but hundreds of kilometers out into the Pacific.

“We were able to get a gradient of shallow to deep sediments and compare the differences between those isotopic compositions in pyrite between those sections,” said Fike, professor of Earth and planetary sciences and director of environmental studies at Washington University.

“We demonstrate that, for this one basin in the open ocean, you get very different signals between shallow and deep water, which is prima facie evidence to argue that these signals aren’t the global fingerprint of oxygen in the atmosphere,” said Fike, who also serves as director of Washington University’s International Center for Energy, Environment and Sustainability (InCEES).

Instead of pointing directly to oxygen, the same signals from pyrite could be reinterpreted as they relate to other important factors, Fike said, such as sea level change and plate tectonics.

Fike and first author Virgil Pasquier, a postdoctoral fellow at the Weizmann Institute of Sciences in Israel, first questioned the way that pyrite has been used as a proxy in a study published in PNAS in 2017 using Mediterranean Sea sediments. For his postdoctoral research, Pasquier has been working with professor Itay Halevy at the Weizmann Institute to understand the various controls on the isotopic composition of pyrite. Their results raise concerns about the common use of pyrite sulfur isotopes to reconstruct Earth’s evolving oxidation state.

“Strictly speaking, we are investigating the coupled cycles of carbon, oxygen and sulfur, and the controls on the oxidation state of the atmosphere,” Pasquier said.

“It’s much more sexy for a paper to reconstruct past changes in ocean chemistry than to focus on the burial of rocks or what happened during the burial,” he said. “But I find this part even more interesting. Because most microbial life — especially back when oxygen was initially accumulating in the atmosphere — occurred in sediments. And if our ultimate goal is to understand oxygenation of the oceans, then we have to understand this.”

For this study, the team conducted 185 sulfur isotope analyses of pyrite along the two boreholes. They determined that changes in the signals in pyrite from the nearshore borehole were more controlled by sea level-driven changes in local sedimentation, rather than any other factor.

In contrast, sediments in the deeper borehole were immune to the sea-level changes. Instead, they recorded a signal associated with the long-term reorganization of ocean currents.

“There is a water depth threshold,” said Roger Bryant, a co-author and PhD graduate of Fike’s laboratory at Washington University, now a postdoctoral fellow at the University of Chicago. “Once you go below that water depth, sulfur isotopes apparently are not sensitive to things like climate and environmental conditions in the surface environment.”

Fike added: “The Earth is a complicated place, and we need to remember that when we try to reconstruct how it has changed in the past. There are a number of different processes that impact the kinds of signals that get preserved. As we try to better understand Earth’s long-term evolution, we need to have a more nuanced view about how to extract information from those signals.”

Led by scientists who collaborate as part of the International Research Network for Nuclear Astrophysics (IReNA)  and the Joint Institute for Nuclear Astrophysics — Center for the Evolution of the Elements (JINA-CEE), the study is published in the latest issue of the journal Science.

Heavy elements we encounter in our everyday life, like iron and silver, did not exist at the beginning of the universe, 13.7 billion years ago. They were created in time through nuclear reactions called nucleosynthesis that combined atoms together. In particular, iodine, gold, platinum, uranium, plutonium, and curium, some of the heaviest elements, were created by a specific type of nucleosynthesis called the rapid neutron capture process, or r process.

The question of which astronomical events can produce the heaviest elements has been a mystery for decades. Today, it is thought that the r process can occur during violent collisions between two neutron stars, between a neutron star and a black hole, or during rare explosions following the death of massive stars. Such highly energetic events occur very rarely in the universe. When they do, neutrons are incorporated in the nucleus of atoms, then converted into protons. Since elements in the periodic table are defined by the number of protons in their nucleus, the r process builds up heavier nuclei as more neutrons are captured.

Some of the nuclei produced by the r process are radioactive and take millions of years to decay into stable nuclei. Iodine-129 and curium-247 are two of such nuclei that were pro-duced before the formation of the sun. They were incorporated into solids that eventually fell on the earth’s surface as meteorites. Inside these meteorites, the radioactive decay generat-ed an excess of stable nuclei. Today, this excess can be measured in laboratories in order to figure out the amount of iodine-129 and curium-247 that were present in the solar system just before its formation.

Why are these two r-process nuclei are so special? They have a peculiar property in common: they decay at almost exactly the same rate. In other words, the ratio between iodine-129 and curium-247 has not changed since their creation, billions of years ago.

“This is an amazing coincidence, particularly given that these nuclei are two of only five radioactive r-process nuclei that can be measured in meteorites,” says Benoit Côté from the Konkoly Observatory, the leader of the study. “With the iodine-129 to curium-247 ratio being frozen in time, like a prehistoric fossil, we can have a direct look into the last wave of heavy element production that built up the composition of the solar system, and everything within it.”

Iodine, with its 53 protons, is more easily created than curium with its 96 protons. This is because it takes more neutron capture reactions to reach curium’s higher number of protons. As a consequence, the iodine-129 to curium-247 ratio highly depends on the amount of neutrons that were available during their creation.

The team calculated the iodine-129 to curium-247 ratios synthesized by collisions between neutron stars and black holes to find the right set of conditions that reproduce the composition of meteorites. They concluded that the amount of neutrons available during the last r-process event before the birth of the solar system could not be too high. Otherwise, too much curium would have been created relative to iodine. This implies that very neutron-rich sources, such as the matter ripped off the surface of a neutron star during a collision, likely did not play an important role.

So what created these r-process nuclei? While the researchers could provide new and insightful information regarding how they were made, they could not pin down the nature of the astronomical object that created them. This is because nucleosynthesis models are based on uncertain nuclear properties, and it is still unclear how to link neutron availability to specific astronomical objects such as massive star explosions and colliding neutron stars.

“But the ability of the iodine-129 to curium-247 ratio to peer more directly into the fundamental nature of heavy element nucleosynthesis is an exciting prospect for the future,” said Nicole Vassh from the University of Notre Dame, coauthor of the study.

With this new diagnostic tool, advances in the fidelity of astrophysical simulations and in the understanding of nuclear properties could reveal which astronomical objects created the heaviest elements of the solar system.

“Studies like this are only possible when you bring together a multidisciplinary team, where each collaborator contributes to a distinct piece of the puzzle. The JINA-CEE 2019 Frontiers meeting provided the ideal environment to formalize the collaboration that led to the current result,” Côté said.

This work was supported in part by JINA-CEE a U.S. National Science Foundation (NSF) Physics Frontiers Center operating under grant No. PHY- 1430152, and by IReNA, an NSF AccelNet Network of Networks operating under grant OISE-1927130.