Supercomputers help supercharge protein assembly

Using supercomputers, scientists are just starting to design proteins that self-assemble to combine and resemble life-giving molecules like hemoglobin.

Using proteins derived from jellyfish, scientists assembled a complex sixteen protein structure composed of two stacked octamers by supercharging alone. This research could be applied to useful technologies such as pharmaceutical targeting, artificial energy harvesting, 'smart' sensing and building materials, and more. Computational modeling through XSEDE allocations on Stampede2 (TACC) and Comet (SDSC) refined measurements of structure.

Red blood cells are amazing. They pick up oxygen from our lungs and carry it all over our body to keep us alive. The hemoglobin molecule in red blood cells transports oxygen by changing its shape in an all-or-nothing fashion. Four copies of the same protein in hemoglobin open and close like flower petals, structurally coupled to respond to each other. Using supercomputers, scientists are just starting to design proteins that self-assemble to combine and resemble life-giving molecules like hemoglobin. The scientists say their methods could be applied to useful technologies such as pharmaceutical targeting, artificial energy harvesting, 'smart' sensing and building materials, and more.

A science team did this work by supercharging proteins, which means that they changed the subunits of proteins, the amino acids, to give the proteins an artificially high positive or negative charge. Using proteins derived from jellyfish, the scientists were able to assemble a complex sixteen protein structure composed of two stacked octamers by supercharging alone, findings that were reported in January of 2019 in the journal Nature Chemistry.

The team then used supercomputer simulations to validate and inform these experimental results. Supercomputer allocations on Stampede2 at the Texas Advanced Computing Center (TACC) and Comet at the San Diego Supercomputer Center (SDSC) were awarded to the researchers through XSEDE, the Extreme Science and Engineering Discovery Environment funded by the National Science Foundation (NSF).

"We found that by taking proteins that don't normally interact with each other, we can make copies that are either highly positively or highly negatively charged," said study co-author Anna Simon, a postdoctoral researcher in the Ellington Lab of UT Austin. "Combining the highly positively and negatively charged copies, we can make the proteins assemble into very specific structured assemblies," Simon said. The scientists call their strategy 'supercharged protein assembly,' where they drive defined protein interactions by combining engineered supercharged variants.

"We exploited a very well-known and basic principle from nature, that opposite charges attract," added study co-author Jens Glaser. Glaser is an assistant research scientist in the Glotzer Group, Department of Chemical Engineering at the University of Michigan. "Anna Simon's group found that when they mix these charged variants of green fluorescent protein, they get highly ordered structures. That was a real surprise," Glaser said.

The stacked octamer structure looks like a braided ring. It's composed of 16 proteins -- two intertwined rings of eight that interact in very specific, discreet patches. "The reason why it's so hard to engineer proteins that interact synthetically is that making these interacting patches and having them all line up right such that they'll allow the proteins to assemble into bigger, regular structures is really hard," explained Simon. They got around the problem by adding many positive and negative charges to engineer variants of green fluorescent protein (GFP), a well-studied 'lab mouse' protein derived from the Aequorea victoria jellyfish.

The positively charged protein, which they called cerulean fluorescent protein (Ceru) +32, had additional opportunities to interact with the negatively charged protein GFP -17. "By giving these proteins all these opportunities, these different places where they could potentially interact, they were able to choose the right ones," Simon said. "There were certain patterns and interactions that were there, available, and energetically favored, that we didn't necessarily predict beforehand that would allow them to assemble into these specific shapes."

To get the engineered charged fluorescent proteins, Simon and co-authors Arti Pothukuchy, Jimmy Gollihar, and Barrett Morrow encoded their genes, including a chemical tag used for purification on portable pieces of DNA called plasmids in E. coli, then harvested the tagged protein that E. coli grew. The scientists mixed the proteins together. They initially thought the proteins might just interact to form large, irregularly structured clumps. "But then, what we kept on seeing was this weird, funny peak around 12 nanometers, that was a lot smaller than a big clump of protein, but significantly bigger than the single protein," Simon said.

They measured the size of the particles that formed using a Zetasizer instrument at the Texas Materials Institute of UT Austin, and verified that the particles contained both cerulean and GFP proteins Förster Resonance Energy Transfer (FRET), which measures the energy transfer between different colored fluorescent proteins produce fluorescence in response to different energies of light to see if they are close together. Negative stain electron microscopy identifed the specific structure of the particles, conducted by the group of David Taylor, assistant professor of molecular biosciences at UT Austin. It showed that the 12 nm particle consisted of a stacked octamer composed of sixteen proteins. "We found that they were these beautifully shaped flower-like structures," Simon said. Co-author Yi Zhou from Taylor's group of UT Austin increased the resolution even further using cryo-electron microscopy to reveal atomic-level details of the stacked octamer.

Computational modeling refined the measurements of how the proteins were arranged into a clear picture of the beautiful, flower-like structure, according to Jens Glaser. "We had to come up with a model that was complex enough to describe the physics of the charged green fluorescent proteins and present all the relevant atomistic details, yet was efficient enough to allow us to simulate this on a realistic timescale. With a fully atomistic model, it would have taken us over a year to get a single simulation out of the computer, however fast the computer was," Glaser said.

They simplified the model by reducing the resolution without sacrificing important details of the interactions between proteins. "That's why we used a model where the shape of the protein is exactly represented by a molecular surface, just like the one that's measured from the crystallographic structure of the protein," Glaser added.

"What really helped us turn this around and improve what we were able to get out of our simulations was the cryo-EM data," said Vyas Ramasubramani, a graduate student in chemical engineering at the University of Michigan. "That's what really helped us find the optimal configuration to put into these simulations, which then helped us validate the stability arguments that we were making, and hopefully going forward make predictions about ways that we can destabilize or modify this structure," Ramasubramani said.

The scientists required lots of compute power to do the calculations on the scale that they wanted.

"We used XSEDE to basically take these huge systems, where you have lots of different pieces interacting with each other, and calculate all of this at once so that when you start moving your system forward through some semblance of time, you could get an idea for how it was going to evolve on somewhat real timescales," Ramasubramani said. "If you tried to do the same kind of simulation that we did on a laptop, it would have taken months if not years to really approach understanding whether or not some sort of structure would be stable. For us, not being able to use XSEDE, where you could use essentially 48 cores, 48 compute units all at once to make these calculations highly parallel, we would have been doing this much slower."

The Stampede2 supercomputer at the TACC contains 4,200 Intel Knights Landing and 1,736 Intel Skylake X compute nodes. Each Skylake node has 48 cores, the basic unit of a computer processor. "The Skylake nodes of the Stampede2 supercomputer were instrumental in achieving the performance that was necessary to compute these electrostatic interactions that act between the oppositely-charged proteins in an efficient manner," Glaser said. "The availability of the Stampede2 supercomputer was at just the right point in time for us to perform these simulations."

Initially, the science team tested their simulations on the Comet system at the SDSC. "When we were first figuring out what kind of model to use and whether this simplified model would give us reasonable results, Comet was a great place to try these simulations," Ramasubramani said. "Comet was a great testbed for what we were doing."

Looking at the bigger scientific picture, the scientists hope that this work advances understanding of why so many proteins in nature will oligomerize, or join together to form more complex and interesting structures.

"We showed that there doesn't need to be a very specific, pre-distinguished set of plans and interactions for these structures to form," Simon said. "This is important because it means that maybe, and quite likely we can take other sets of molecules that we want to make oligomerize and generate both positively charged and negatively charged variants, combine them, and have specifically ordered structures for them."

Natural biomaterials like bone, feathers, and shells can be tough yet lightweight. "We think supercharged protein assembly is an easier way to develop the kind of materials that have exciting synthetic properties without having to spend so much time or having to know exactly how they're going to come together beforehand," Simon said. "We think that will accelerate the ability to engineer synthetic materials and for discovery and exploration of these nanostructured protein materials."

The Serengeti-Mara squeeze -- One of the world's most iconic ecosystems under pressure

The migration of wildebeest is being disrupted.

Increased human activity around one of Africa's most iconic ecosystems is 'squeezing the wildlife in its core', damaging habitation and disrupting the migration routes of wildebeest, zebra and gazelle, an international study has concluded.

The Serengeti-Mara ecosystem is one of the largest and most protected ecosystems on Earth, spanning 40,000 square kilometres and taking in the Serengeti National Park and Maasai Mara National Reserve in East Africa.

Every year a million wildebeest, half a million gazelle and 200,000 zebra make the perilous trek from the Serengeti national park in Tanzania to the Maasai Mara reserve in Kenya in their search for water and grazing land.

Now, an international team of scientists have discovered that increased human activity along the boundaries is having a detrimental impact on plants, animals, and soils.

The findings are published in the journal Science.

The study looked at 40 years of data, and revealed that some boundary areas have seen a 400 per cent increase in human population over the past decade, while larger wildlife species in key areas in Kenya have declined by more than 75 per cent.

The study reveals how population growth and an influx of livestock in the buffer zones of the parks has squeezed the area available for migration of wildebeest, zebra and gazelles, causing them to spend more time grazing less nutritious grasses than they did in the past. This has reduced the frequency of natural fires, changing the vegetation and altering grazing opportunities for other wildlife in the core areas.

The study shows that the impacts are cascading down the food chain, favouring less palatable plants and altering the beneficial interactions between plants and microorganisms that enable the ecosystem to capture and utilize essential nutrients.

The effects could potentially make the ecosystem less resilient to future shocks such as drought or further climate change, the scientists warn.

The authors conclude that, even for reasonably well-protected areas like the Serengeti and Mara, alternative strategies may be needed that sustain the coexistence and livelihood of local people and wildlife in the landscapes surrounding protected areas. The current strategy of increasingly hard boundaries may be a major risk to both people and wildlife.

The study was led by the University of Groningen with collaborators at 11 institutions around the world, including the universities of York, Glasgow and Liverpool.

Dr Colin Beale, from the University of York's Department of Biology, said: "Protected areas across East Africa are under pressure from a wide range of threats. Our work shows that encroachment by people should be considered just as serious a challenge as better known issues such as poaching and climate change."

Dr Michiel Veldhuis, lead author of the study from the University of Groningen, said: "There is an urgent need to rethink how we manage the boundaries of protected areas to be able to conserve biodiversity. The future of the world's most iconic protected area and their associated human population may depend on it."

Dr Simon Mduma, Director of the Tanzanian Government's Wildlife Research Institute added: "These results come at the right time, as the Tanzanian government is now taking important steps to address these issues on a national level."

"This paper provides important scientific evidence of the far ranging consequences of the increased human pressures around the Serengeti-Mara ecosystem, information that is now urgently needed by policy makers and politicians."

Galápagos islands have nearly 10 times more alien marine species than once thought

The bryozoan Amathia verticillata. Known in other parts of the world for fouling pipes and fishing gear and killing seagrasses, its discovery in the Galapagos is especially concerning for scientists.

Over 50 non-native species have found their way to the Galápagos Islands, almost 10 times more than scientists previously thought, reports a new study in Aquatic Invasions published Thursday, March 28.

The study, a joint effort of the Smithsonian Environmental Research Center, Williams College, and the Charles Darwin Foundation, documents 53 species of introduced marine animals in this UNESCO World Heritage Site, one of the largest marine protected areas on Earth. Before this study came out, scientists knew about only five.

"This increase in alien species is a stunning discovery, especially since only a small fraction of the Galápagos Islands was examined in this initial study," said Greg Ruiz, a co-author and marine biologist with the Smithsonian Environmental Research Center.

"This is the greatest reported increase in the recognition of alien species for any tropical marine region in the world," said lead author James Carlton, an emeritus professor of the Maritime Studies Program of Williams College-Mystic Seaport.

The Galápagos lie in the equatorial Pacific, roughly 600 miles west of Ecuador. Made famous by Charles Darwin's visit in 1835, the islands have long been recognized for their remarkable biodiversity. But with their fame, traffic has spiked. In 1938, just over 700 people lived on the Galápagos. Today, more than 25,000 people live on the islands, and nearly a quarter-million tourists visit each year.

Carlton and Ruiz began their study in 2015, with Inti Keith of the Charles Darwin Foundation. They conducted field surveys on two of the larger Galápagos Islands: Santa Cruz and Baltra, where they hung settlement plates from docks one meter underwater to see what species would grow on them. They also collected samples from mangrove roots, floating docks and other debris and scoured the literature for previous records of marine species on the islands.

The team documented 48 additional non-native species in the Galápagos. Most of them (30) were new discoveries that could have survived on the islands for decades under the radar. Another 17 were species scientists already knew lived on the Galápagos but previously thought were native. One final species, the bryozoan Watersipora subtorquata, was collected in 1987 but not identified until now.

Sea squirts, marine worms and moss animals (bryozoans) made up the majority of the non-native species. Almost all of the non-natives likely arrived inadvertently in ships from tropical seas around the world. Some of the most concerning discoveries include the bryozoan Amathia verticillata -- known for fouling pipes and fishing gear and killing seagrasses -- and the date mussel Leiosolenus aristatus, which researchers have already seen boring into Galápagos corals.

"This discovery resets how we think about what's natural in the ocean around the Galápagos, and what the impacts may be on these high-value conservation areas," Carlton said.

To reduce future invasions, the Galápagos already have one of the most stringent biosecurity programs in the world. International vessels entering the Galápagos Marine Reserve may anchor in only one of the main ports, where divers inspect the vessel. If the divers find any non-native species, the vessel is requested to leave and have its hull cleaned before returning for a second inspection.

Still, the authors say, the risks remain high. The expansion of the Panama Canal in 2015 may bring the Indo-Pacific lionfish -- a major predator in the Caribbean -- to the Pacific coast of Central America. Once there, it could make its way to the Galápagos, where the likelihood of its success would be very high. Another possible arrival is the Indo-Pacific snowflake coral, which has already caused widespread death of native corals on the South American mainland.

Seeds inherit memories from their mother

This is a seed of Arabidopsis thaliana at the beginning of germination.

Seeds remain in a dormant state -- a temporary blockage of their germination -- as long as environmental conditions are not ideal for germination. The depth of this sleep, which is influenced by various factors, is inherited from their mother, as researchers from the University of Geneva (UNIGE), Switzerland, had previously shown. Today, they reveal in the journal eLife how this maternal imprint is transmitted through small fragments of so-called 'interfering' RNAs, which inactivate certain genes. The biologists also reveal that a similar mechanism enables to transmit another imprint, that of the temperatures present during the development of the seed. The lower this temperature was, the higher the seed's dormancy level will be. This mechanism allows the seed to optimize the timing of its germination. The information is then erased in the germinated embryo, so that the next generation can store new data on its environment.

Dormancy is implemented during seed development in the mother plant. This property allows the seeds to germinate during the appropriate season, to prevent all the offspring of a plant from developing in the same place and competing for limited resources, and to promote plant dispersal. Seeds also lose their dormancy at variable times. "Subspecies of the same plant can have different levels of dormancy depending on the latitudes at which they are produced, and we wanted to understand why," explains Luis Lopez-Molina, Professor at the Department of Botany and Plant Biology of the UNIGE Faculty of Science.

The paternal gene is silenced

Like all organisms with sexual reproduction, the seed receives two versions of each gene, a maternal and a paternal allele, which may have different levels of expression. The UNIGE biologists had shown in 2016 that the dormancy levels of Arabidopsis thaliana, a model organism used in laboratories, are inherited from the mother. Indeed, in the seed, the level of expression of a dormancy regulating gene called allantoinase (ALN) is the same as that of the maternal allele. This implies that it is the maternal allele of ALN that is mainly expressed, to the detriment of the paternal allele.

In the current study, the researchers show that this maternal imprint is transmitted by an epigenetic mechanism, which influences the expression of certain genes without altering their sequence. The paternal allele of ALN is 'silenced' by biochemical modifications called methylations, which are carried out in the promoter region of the gene in order to inactivate it.

"These methylations are themselves the result of a process in which different enzymatic and factor complexes are involved, as well as small fragments of so-called 'interfering' RNA. This is a unique example of genomic imprinting, because it is made in the absence of the enzyme usually responsible for methylation," says Mayumi Iwasaki, researcher in the Geneva group and the first author of the article.

The imprint of past cold prevents the seed from awakening

The environmental conditions present during the seed formation also leave their mark, as its dormancy level increases with decreasing temperatures. "We have discovered that, in this case, both alleles of the ALN gene are strongly repressed in the seed. This is due to a similar epigenetic mechanism, but not all of the actors are the same as those used to silence the paternal allele," says Luis Lopez-Molina.

This imprint of the cold enables the seed to keep information on past temperatures, in order to include them in the choice of the optimal time of germination. After germination, the ALN gene is reactivated in the embryo. The memory of the cold will then be cleared, allowing the counters to be reset for the next generation.

"Studying how maternal and environmental factors cause dormant seeds to awaken is of crucial importance for agriculture, especially to prevent early germination in an environment subject to climate change," concludes Mayumi Iwasaki. The ecological stakes are also high, because increasing temperatures could reduce the dormancy of the seed bank and thus modify the distribution of plant species under a given latitude. This would have multiple consequences, both direct and indirect, for native animal and plant species.

Biophysicists use machine learning to understand, predict dynamics of worm behavior

Caenorhabditis elegans 

Biophysicists have used an automated method to model a living system -- the dynamics of a worm perceiving and escaping pain. The Proceedings of the National Academy of Sciences (PNAS)published the results, which worked with data from experiments on the C. elegans roundworm.

"Our method is one of the first to use machine-learning tools on experimental data to derive simple, interpretable equations of motion for a living system," says Ilya Nemenman, senior author of the paper and a professor of physics and biology at Emory University. "We now have proof of principle that it can be done. The next step is to see if we can apply our method to a more complicated system."

The model makes accurate predictions about the dynamics of the worm behavior, and these predictions are biologically interpretable and have been experimentally verified.

Collaborators on the paper include first author Bryan Daniels, a theorist from Arizona State University, and co-author William Ryu, an experimentalist from the University of Toronto.

The researchers used an algorithm, developed in 2015 by Daniels and Nemenman, that teaches a computer how to efficiently search for the laws that underlie natural dynamical systems, including complex biological ones. They dubbed the algorithm "Sir Isaac," after one of the most famous scientists of all time -- Sir Isaac Newton. Their long-term goal is to develop the algorithm into a "robot scientist," to automate and speed up the scientific method of forming quantitative hypotheses, then testing them by looking at data and experiments.

While Newton's Three Laws of Motion can be used to predict dynamics for mechanical systems, the biophysicists want to develop similar predictive dynamical approaches that can be applied to living systems.

For the PNAS paper, they focused on the decision-making involved when C. elegans responds to a sensory stimulus. The data on C. elegans had been previously gathered by the Ryu lab, which develops methods to measure and analyze behavioral responses of the roundworm at the holistic level, from basic motor gestures to long-term behavioral programs.

C. elegans is a well-established laboratory animal model system. Most C. elegans have only 302 neurons, few muscles and a limited repertoire of motion. A sequence of experiments involved interrupting the forward movement of individual C. elegans with a laser strike to the head. When the laser strikes a worm, it withdraws, briefly accelerating backwards and eventually returning to forward motion, usually in a different direction. Individual worms respond differently. Some, for instance, immediately reverse direction upon laser stimulus, while others pause briefly before responding. Another variable in the experiments is the intensity of the laser: Worms respond faster to hotter and more rapidly rising temperatures.

The researchers fed the Sir Isaac platform the motion data from the first few seconds of the experiments -- before and shortly after the laser strikes a worm and it initially reacts. From this limited data, the algorithm was able to capture the average responses that matched the experimental results and also to predict the motion of the worm well beyond these initial few seconds, generalizing from the limited knowledge. The prediction left only 10 percent of the variability in the worm motion that can be attributed to the laser stimulus unexplained. This was twice as good as the best prior models, which were not aided by automated inference.

"Predicting a worm's decision about when and how to move in response to a stimulus is a lot more complicated than just calculating how a ball will move when you kick it," Nemenman says. "Our algorithm had to account for the complexities of sensory processing in the worms, the neural activity in response to the stimuli, followed by the activation of muscles and the forces that the activated muscles generate. It summed all this up into a simple and elegant mathematical description."

The model derived by Sir Isaac was well-matched to the biology of C. elegans, providing interpretable results for both the sensory processing and the motor response, hinting at the potential of artificial intelligence to aid in discovery of accurate and interpretable models of more complex systems.

"It's a big step from making predictions about the behavior of a worm to that of a human," Nemenman says, "but we hope that the worm can serve as a kind of sandbox for testing out methods of automated inference, such that Sir Isaac might one day directly benefit human health. Much of science is about guessing the laws that govern natural systems and then verifying those guesses through experiments. If we can figure out how to use modern machine learning tools to help with the guessing, that could greatly speed up research breakthroughs."