“Mitofusin 2 emerges as a possible therapeutic target to tackle fatty liver, a disease for which no treatments are available. Early diagnosis of this disease is difficult and physicians are currently only recommending weight loss to alleviate the condition,” explains Antonio Zorzano, head of the Complex Metabolic Diseases and Mitochondria laboratory at IRB Barcelona.

One of the most serious forms of fatty acid is non-alcoholic steatohepatitis (NASH), in which the accumulation of fat is accompanied by inflammation. In this study published in the journal Cell, the researchers have observed a decrease in the levels of Mitofusin 2 in patients with NASH, even in early stages of the disease.

Like humans, mice also develop this disease when the levels of Mitofusin 2 decreases. By injecting a mouse model of NASH with an adenovirus enconding Mitofusin 2 protein — a virus modified to artificially express proteins — the team headed by Zorzano, senior professor at the University of Barcelona and researcher of the CIBERDEM Programme, has observed the amelioration of NASH.

“We are now studying different approaches that will allow us to enhance the levels of Mitofusin 2, without producing side effects, and that could be relevant in the treatment of non-alcoholic fatty liver disease,” says María Isabel Hernández-Alvarez, postdoctoral fellow at IRB Barcelona and first author of the study.

This work has been supported by funding from the Ministry of Science, Innovation and Universities (previously known as MINECO), the Catalan Government, the Instituto de Salud Carlos III, CIBERDEM, “la Caixa” Foundation and the Pere Virgili Institute (IISPV).

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The method relies on unique sample-handling, signal-extraction, and data-assembly approaches, and a beamline capable of focusing intense x-rays at Brookhaven’s National Synchrotron Light Source II (NSLS-II) — a DOE Office of Science user facility — to a millionth-of-a-meter spot, about one-fiftieth the width of a human hair.

“Our technique really opens the door to dealing with microcrystals that have been previously inaccessible, including difficult-to-crystallize cell-surface receptors and other membrane proteins, flexible proteins, and many complex human proteins,” said Brookhaven Lab scientist Qun Liu, the corresponding author on the study, which was published on May 3, 2019, in IUCrJ, a journal of the International Union of Crystallography.

Deciphering protein structures

Protein crystallography has been a dominant method for solving protein structures since 1958, improving over time as x-ray sources have grown more powerful, allowing more precise structure determinations. To determine a protein structure, scientists measure how x-rays like those generated at NSLS-II diffract, or bounce off, the atoms in an ordered crystalline lattice consisting of many copies of the same protein molecule all arrayed the same way. The diffraction pattern conveys information about where the atoms are located. But it’s not sufficient.

“Only the amplitudes of diffracted x-ray ‘waves’ are recorded on the detector, but not their phases (the timing between waves),” said Liu. “Both are required to reconstruct a 3-D structure. This is the so-called crystallographic phase problem.”

Crystallographers have solved this problem by collecting phase data from a different kind of scattering, known as anomalous scattering. Anomalous scattering occurs when atoms heavier than a protein’s main components of carbon, hydrogen, and nitrogen absorb and re-emit some of the x-rays. This happens when the x-ray energy is close to the energy those heavy atoms like to absorb. Scientists sometimes artificially insert heavy atoms such as selenium or platinum into the protein for this purpose. But sulfur atoms, which appear naturally throughout protein molecules, can also produce such signals, albeit weaker. Even though these anomalous signals are weak, a big crystal usually has enough copies of the protein with enough sulfur atoms to make them measurable. That gives scientists the phase information needed to pinpoint the location of the sulfur atoms and translate the diffraction patterns into a full 3-D structure.

“Once you know the sulfur positions, you can calculate the phases for the other protein atoms because the relationship between the sulfur and the other atoms is fixed,” said Liu.

But tiny crystals, by definition, don’t have that many copies of the protein of interest. So instead of looking for diffraction and phase information from repeat copies of a protein in a single large crystal, the Brookhaven/Columbia team developed a way to take measurements from many tiny crystals, and then assemble the collective data.

Tiny crystals, big results

To handle the tiny crystals, the team developed sample grids patterned with micro-sized wells. After pouring solvent containing the microcrystals over these well-mount grids, the scientists removed the solvent and froze the crystals that were trapped on the grids.

“We still have a challenge, though, because we can’t see where the tiny crystals are on our grid,” said Liu. “To find out, we used microdiffraction at NSLS-II’s Frontier Microfocusing Macromolecular Crystallography (FMX) beamline to survey the whole grid. Scanning line by line, we can find where those crystals are hidden.”

As Martin Fuchs, the lead beamline scientist at FMX, explained, “The FMX beamline can focus the full intensity of the x-ray beam down to a size of one micron, or millionth of a meter. We can finely control the beam size to match it to the size of the crystals — five microns in the case of the current experiment. These capabilities are crucial to obtain the best signal,” he said.

Wuxian Shi, another FMX beamline scientist, noted that “the data collected in the grid survey contains information about the crystals’ location. In addition, we can also see how well each crystal diffracts, which allows us to pick only the best crystals for data collection.”

The scientists were then able to maneuver the sample holder to place each mapped out microcrystal of interest back in the center of the precision x-ray beam for data collection.

They used the lowest energy available at the beamline — tuned to approach as closely as possible sulfur atoms’ absorption energy — and collected anomalous scattering data.

“Most crystallographic beamlines could not reach the sulfur absorption edge for optimized anomalous signals,” said co-author Wayne Hendrickson of Columbia University. “Fortunately, NSLS-II is a world-leading synchrotron light source providing bright x-rays covering a broad spectrum of x-ray energy. And even though our energy level was slightly above the ideal absorption energy for sulfur, it generated the anomalous signals we needed.”

But the scientists still had some work to do to extract those important signals and assemble the data from many tiny crystals.

“We are actually getting thousands of pieces of data,” said Liu. “We used about 1400 microcrystals, each with its own data set. We have to put all the data from those microcrystals together.”

They also had to weed out data from crystals that were damaged by the intense x-rays or had slight variations in atomic arrangements.

“A single microcrystal does not diffract x-rays sufficiently for structure solution prior to being damaged by the x-rays,” said Sean McSweeney, deputy photon division director and program manager of the Structural Biology Program at NSLS-II. “This is particularly true with crystals of only a few microns, the size of about a bacterial cell. We needed a way to account for that damage and crystal structure variability so it wouldn’t skew our results.”

They accomplished these goals with a sophisticated multi-step workflow process that sifted through the data, discarded outliers that might have been caused by radiation damage or incompatible crystals, and ultimately extracted the anomalous scattering signals.

“This is a critical step,” said Liu. “We developed a computing procedure to assure that only compatible data were merged in a way to align the individual microcrystals from diffraction patterns. That gave us the required signal-to-noise ratios for structure determination.”

Applying the technique

This technique can be used to determine the structure of any protein that has proven hard to crystallize to a large size. These include cell-surface receptors that allow cells of advanced lifeforms such as animals and plants to sense and respond to the environment around them by releasing hormones, transmitting nerve signals, or secreting compounds associated with cell growth and immunity.

“To adapt to the environment through evolution, these proteins are malleable and have lots of non-uniform modifications,” said Liu. “It’s hard to get a lot of repeat copies in a crystal because they don’t pack well.”

In humans, receptors are common targets for drugs, so having knowledge of their varied structures could help guide the development of new, more targeted pharmaceuticals.

But the technique is not restricted to just small crystals.

“The method we developed can handle small protein crystals, but it can also be used for any size protein crystals, any time you need to combine data from more than one sample,” Liu said.

The first-of-its-kind report, which tracked several dozen male collegiate water polo players over three seasons, was published today in PLOS One, a peer-reviewed, open-access scientific journal.

“For years, water polo’s head trauma risks have been downplayed or overshadowed by football-related brain injuries,” said study co-author James Hicks, professor and chair of UCI’s Department of Ecology & Evolutionary Biology. “Our data quantifies the extent of the problem and sets the stage for additional research and possible rule changes or protective gear to improve water polo safety.”

During the study, players wore caps embedded with electronic sensors. Over time, every participant got bopped in the head by balls or rival players, but some fared worse -occasionally far worse — than others.

Offensive players were more likely to get battered than defensive and transition positions (60 percent versus 23 percent and 17 percent, respectively). And swimmers attacking from the left side of the goal suffered more head hits than players on the right, possibly because right-handed athletes commonly throw shots from the left zone, so there’s more activity in that area, researchers theorized.

The most unsafe position, according to the study, was offensive center. On average, those players endured nearly seven blows to the skull per game, which amounted to 37 percent of all head impacts recorded by UCI scientists. In contrast, the second-most vulnerable position, defensive center, averaged two head strikes a game, the study found.

Overall, researchers counted an average of 18 head hits per game. Although no concussions were diagnosed, the force of the blows was “similar to those observed in collegiate soccer, another sport that is commonly studied for the risks associated with repeated head impact exposure,” Hicks said.

Next up, UCI researchers are preparing a manuscript that details how water polo head shots affect brain function.

Hicks got interested in the subject while watching his three sons play the sport. “People who’ve never seen a game may not realize how physical it is,” he said. “Head-butts and elbows. Balls flying up to 50 mph. I’ve witnessed players get dragged out of the pool in a daze after a blow to the head, and I’ve sat in an emergency room while my kid received stitches from being struck in the face. I began to wonder what the concussion rate was.”

After discovering a dearth of studies, he launched his own. In the first, published three years ago in Frontiers in Neurology, Hicks and Dr. Steven Small, UCI professor of neurology, surveyed 1,500 USA Water Polo members and discovered that 36 percent recalled suffering at least one concussion during their playing career.

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“When given this tool, cells began to increase their firing rate beyond levels we have seen before, even with normal images pre-selected to elicit the highest firing rates,” explains co-first author Carlos Ponce, then a post-doctoral fellow in the laboratory of senior author Margaret Livingstone at Harvard Medical School and now a faculty member at Washington University in St. Louis.

“What started to emerge during each experiment were pictures that were reminiscent of shapes in the world but were not actual objects in the world,” he says. “We were seeing something that was more like the language cells use with each other.”

Researchers have known that neurons in the visual cortex of primate brains respond to complex images, like faces, and that most neurons are quite selective in their image preference. Earlier studies on neuronal preference used many natural images to see which images caused neurons to fire most. However, this approach is limited by the fact that one cannot present all possible images to understand what exactly will best stimulate the cell.

The XDREAM algorithm uses the firing rate of a neuron to guide the evolution of a novel, synthetic image. It goes through a series of images over the course of minutes, mutates them, combines them, and then shows a new series of images. At first, the images looked like noise, but gradually they changed into shapes that resembled faces or something recognizable in the animal’s environment, like the food hopper in the animals’ room or familiar people wearing surgical scrubs. The algorithm was developed by Will Xiao in the laboratory of Gabriel Kreiman at Children’s Hospital and tested on real neurons at Harvard Medical School.

“The big advantage of this approach is that it allows the neuron to build its own preferred images from scratch, using a tool that is not limited by much, that can create anything in the world or even things that don’t exist in the world,” says Ponce.

“In this way we have evolved a super-stimulus that drives the cell better than any natural stimulus we could guess at,” says Livingstone. “This approach allows you to use artificial intelligence to figure out what triggers neurons best. It’s a totally unbiased way of asking the cell what it really wants, what would make it fire the most.”

From this study, the researchers believe they are seeing that the brain learns to abstract statistically relevant features of its world. “We are seeing that the brain is analyzing the visual scene, and driven by experience, extracting information that is important to the individual over time,” says Ponce. “The brain is adapting to its environment and encoding ecologically significant information in unpredictable ways.”

The team believes this technology can be applied to any neuron in the brain that responds to sensory information, such as auditory neurons, hippocampal neurons, and prefrontal cortex neurons where memories can be accessed. “This is important because as artificial intelligence researchers develop models that work as well as the brain does — or even better — we will still need to understand which networks are more likely to behave safely and further human goals,” Ponce says. “More efficient AI can be grounded by knowledge of how the brain works.”

This work was supported by grants from the National Institutes of Health and the National Science Foundation.

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While the release of nutrients buried in the seabed ‘feeds’ coastal marine ecosystems, the latest research at Flinders University has found a new physical mechanism which erodes seabed sediment at depths up to 20 metres, well outside (between 10km and 20km) from the surf zone closer to shore.

This powerful natural process that is energetic enough to erode seabed sediment at up to 20 m, also adds to the nutrients stirred and moved by breaking surface waves nearer the beach, according to the new hydrodynamic modelling.

“This new knowledge has significant implications for coastal sediment management practices such as dredging,” says Flinders University oceanographer Associate Professor Jochen Kaempf.

The study reveals that major sediment erosion follows from coast-parallel winds in an oceanic situation known as downwelling.

“Such winds trigger a swift coastal current — left-bounded by the coast in the Southern Hemisphere — that is accompanied by a vigorous stirring zone in nearshore waters,” Associate Professor Kaempf says.

While this finding explains the high proportion of recycled nutrients in coastal ecosystems, it incidentally also points to a new mechanism of wind-driven sediment drift in coastal oceans that complements the well-known littoral drift in the surf zone.

“Along the Adelaide metropolitan coastline, for example, the wind-driven sediment drift tends to be predominantly southward and opposite to the northward sediment drift in the surf zone,” explains Dr Kaempf.

“On the other hand, high turbidity levels following a seabed erosion event negatively impact the health of seagrass beds, and the sudden nutrient release can also trigger potentially harmful toxic algae blooms,” says Dr Jochen Kaempf, who also is South Australian branch president of the Australian Meteorological and Oceanographic Society.

Dr Kaempf’s latest paper calls for more field research and the development of reliable ocean forecasting models to study and predict the occurrence of such erosion events.

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