Commercially viable biofuel crops are vital to reducing greenhouse gas emissions, and a new tool developed by the Center for Advanced Bioenergy and Bioproducts Innovation should accelerate their development -; as well as genetic editing advances overall.
CROPSR, the first open-source software tool for genome-wide design and evaluation of guide RNA (gRNA) sequences for CRISPR experiments, created by scientists at CABBI, a Department of Energy-funded Bioenergy Research Center (BRC). The genome-wide approach significantly shortens the time required to design a CRISPR experiment, reducing the challenge of working with crops and accelerating gRNA sequence design, evaluation, and validation, according to the study published in BMC Bioinformatics.
"CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments," said CROPSR developer Hans Müller Paul, a molecular biologist and Ph.D. student with co-author Matthew Hudson, Professor of Crop Sciences at the University of Illinois Urbana-Champaign. "We hope that the new software will accelerate discovery and reduce the number of failed experiments."
CROPSR developer Hans Müller Paul, a molecular biologist and Ph.D. student with co-author Matthew Hudson, Professor of Crop Sciences at the University of Illinois Urbana-Champaign. To better meet the needs of crop geneticists, the team built software that lifts restrictions imposed by other packages on design and evaluation of gRNA sequences, the guides used to locate targeted genetic material. Team members also developed a new machine learning model that would not avoid guides for repetitive genomic regions often found in plants, a problem with existing tools. The CROPSR scoring model provided much more accurate predictions, even in non-crop genomes, the authors said.
CROPSR is the first open source software tool for genome-wide design and evaluation of guide RNA (gRNA) sequences for CRISPR experiments, created by scientists at CABBI, a Department of Energy-funded Bioenergy Research Center (BRC). The genome-wide approach significantly shortens the time needed to design a CRISPR experiment, reducing the challenge of working with crops and speeding up the design, evaluation and validation of gRNA sequences, according to the study published in BMC Bioinformatics. To better meet the needs of crop geneticists, the team built software that lifts restrictions imposed by other packages on the design and evaluation of gRNA sequences, the guides used to locate targeted genetic material. Team members also developed a new machine learning model that would not avoid guides for repetitive genomic regions often found in plants, a problem with existing tools. The CROPSR scoring model provided much more accurate predictions, even in non-crop genomes. In the future, he hopes researchers will record their failures as well as their successes to help generate the data needed to train a non-specific model.
Computer engineers study the mathematics of how to optimize complex systems. In one example, they face a logistics challenge known as the "travelling salesman problem:" how can a hypothetical salesperson visit every city on their route in the shortest distance?
The algorithms developed to answer these sorts of questions are useful in many situations, such as reducing the costs of and pollution from a fleet of delivery trucks. But when engineers tried to optimize traffic on the internet, they found their methods wanting. Demand quickly rises and falls - for example, an oncoming hurricane drives traffic to a weather website, or a sports team's pageviews peak when there is a big play at a game - so the resources cannot be allocated systematically but must be continuously reorganized in response to a changing situation.
Honeybees don't study mathematics, but the demands of evolution reward those colonies that succeed in optimizing their resources. Fortunately, in the strange tale of how honeybees make the internet work. the scientists were smart enough to see that the honeybees knew better than they did.
Researchers are using astronomical techniques used to study distant stars to survey endangered species. The team of scientists is developing a system to automatically identify animals using a camera that has been mounted on a drone. It is able to identify them from the heat they give off, even when vegetation is in the way. Details of the system were presented at the annual meeting of the European Astronomical Society in Liverpool, UK.
The idea was developed by Serge Wich, a conservationist at Liverpool John Moores University, and Dr Steve Longmore, an astrophysicist at the same university. He says that the system has the potential to greatly improve the accuracy of monitoring endangered species and so help save endangered species.
"Conservation is not only about the numbers of animals but also about political will and local community supporting conservation. But better data always helps to move good arguments forward. Solid data on what is happening to animal populations is the foundation of all conservation efforts".
"Biological processes that make life happen and cause diseases largely take place inside cells, which can be studied with microscopes and other techniques, but not in enough detail," said Michael Feig, an MSU professor of biochemistry and molecular biology who led the research project. "Our research has revealed unprecedented details about what exactly takes place inside biological cells, and how proteins in particular behave in their natural environment."
The team set out to examine whether the crowding in biological cells alters the properties of biological molecules and their ability to carry out their function. Armed with access to the "K computer," a supercomputer housed at the RIKEN Advanced Institute for Computational Science in Kobe, Japan, the research team was able to conduct computer simulations that model the cellular interior of a bacterium, and show a detailed view of how the various molecular components interact in a very dense environment.
"Our computer simulations were not too far away from simulating an entire cell in full atomistic detail," Feig said. "These simulations exceeding 100 million atoms are the largest simulations of this kind and are several orders of magnitude larger than what is typical research work today."
The powerful computer simulation led to a discovery that some proteins may not be as stable in very dense environments, losing the structures necessary for biological function. The research also found that this cellular environment might bring proteins involved in related biological processes closer to each other, which would enhance the overall efficiency of the cell in converting food to energy.
"Proteins in cells are squeezed together like people in the Tokyo subway during rush hour, where the crush violates personal space. But for proteins this is sometimes more welcome than we thought," Feig said.
A third major finding is that smaller molecules, such as those providing food and carrying energy, appear to be distracted by the many opportunities to interact with the larger proteins, affecting their biological function. "This is a breakthrough achievement in understanding how the molecules that biochemists normally study interact in real life conditions," said Thomas Sharkey, chair of the Department of Biochemistry and Molecular Biology at MSU. "It will provide critical insights that will be used by people working to cure cancer and other diseases that depend on the cellular processes that are now much better understood."
Nearly 25,000 species of fish live on our planet, and a University of Washington professor wants to scan and digitize them all. That means each species will soon have a high-resolution, 3D visual replica online, available to all and downloadable for free. Scientists, teachers, students and amateur ichthyologists will be able to look at the fine details of a smoothhead sculpin’s skeleton, or 3-D print an exact replica of an Arctic alligatorfish.
“These scans are transforming the way we think about 3-D data and accessibility,” said Adam Summers, a UW professor of biology and aquatic and fishery sciences who is spearheading the project.
Summers, who is based at the UW’s Friday Harbor Laboratories, uses a small computerized tomography (CT) scanner in the back room of a lab to churn out dozens of fish scans from specimens gathered around the world. The machine works like a standard CT scanner used in hospitals: A series of X-ray images is taken from different angles, then combined using computer processing to create three-dimensional images of the skeleton.
The goal is to make it possible for scientists to examine the morphology of a particular species, or try to understand why a group of fish all have similar physical characteristics such as bony head “armor” or the ability to burrow into the sand. “It’s been so fun to throw this data up on the web and have people actually use it,” Summers said.
Sequencing unsampled fungal diversity. Efforts to sequence 1000+ fungal genomes. Also see the Google+ site for more discussion opportunities.
This project is in collaboration with the work of the JGI and you can find links on this site to the nomination page for submitting candidate species to the project.
Four leading botanical gardens from around the world want to make it easier for researchers to identify plants in the field.
When plant biologists and field researchers come across a species they’ve never seen before, they turn to thick encyclopedia-like volumes called monographs with titles such as Flora Braseliensis that characterize each species in a region in great detail. But not every species has been well-described in this literature. Thomas estimates that only 10 percent of species in the American tropics have been properly characterized. And the reference materials that do exist sometimes don’t match, or are inaccessible to anyone who doesn’t have access through a university.
Four of the world’s leading botanical gardens would like to change that. Since 2012, they have been working toward building a free online database called World Flora Online of the world’s plant species – all 350,000 of them – so that scientists can more easily identify plants and share information about them. Thomas calls it “the WebMD” for plant biology. With a fresh new round of funding this spring including a $1.2 million grant from the Alfred P. Sloan Foundation and a $600,000 commitment from Google accompanied by a pledge to provide cloud storage for the project, the consortium has expanded to include 35 affiliates from around the world.
“Plants are hugely, hugely important for us,” says Doron Weber, vice president at the Sloan Foundation. “Plant research is very promising -- it's necessary for food, for medicines, for various materials. It's also the basis of healthy ecosystems and habitats. You can be completely bottom line about this.”
For the first time, researchers have reproduced the results of the Miller-Urey experiment in a computer simulation, yielding new insight into the effect of electricity on the formation of life's building blocks at the quantum level.
In 1953, American chemist Stanley Miller had famously electrified a mixture of simple gas and water to simulate lightning and the atmosphere of early Earth. The revolutionary experiment—which yielded a brownish soup of amino acids—offered a simple potential scenario for the origin of life's building blocks. Miller's work gave birth to modern research on pre-biotic chemistry and the origins of life.
For the past 60 years, scientists have investigated other possible energy sources for the formation of life's building blocks, including ultra violet light, meteorite impacts, and deep sea hydrothermal vents.
In this new study, Antonino Marco Saitta, of the Université Pierre et Marie Curie, Sorbonne, in Paris, France and his colleagues wanted to revisit Miller's result with electric fields, but from a quantum perspective.
Saitta and study co-author Franz Saija, two theoretical physicists, had recently applied a new quantum model to study the effects of electric fields on water, which had never been done before. After coming across a documentary on Miller's work, they wondered whether the quantum approach might work for the famous spark-discharge experiment.
The method would also allow them to follow individual atoms and molecules through space and time—and perhaps yield new insight into the role of electricity in Miller's work.
"The spirit of our work was to show that the electric field is part of it," Saitta said, "without necessarily involving lightning or a spark." Another key insight from their study is that the formation of some of life's building blocks may have occurred on mineral surfaces, since most have strong natural electric fields.
"The electric field of mineral surfaces can be easily 10 or 20 times stronger than the one in our study," Saitta said. "The problem is that it only acts on a very short range. So to feel the effects, molecules would have to be very close to the surface." "I think that this work is of great significance," said François Guyot, a geochemist at the French Museum of Natural History.
"Regarding the mineral surfaces, strong electric fields undoubtedly exist at their immediate proximity. And because of their strong role on the reactivity of organic molecules, they might enhance the formation of more complex molecules by a mechanism distinct from the geometrical concentration of reactive species, a mechanisms often proposed when mineral surfaces are invoked for explaining the formation of the first biomolecules."
One of the leading hypotheses in the field of life's origin suggests that important prebiotic reactions may have occurred on mineral surfaces. But so far scientists don't fully understand the mechanism behind it.
"Nobody has really looked at electric fields on mineral surfaces," Saitta said. "My feeling is that there's probably something to explore there."
Computer program crudely predicts a facial structure from genetic variations.
Researchers have now shown how 24 gene variants can be used to construct crude models of facial structure. Thus, leaving a hair at a crime scene could one day be as damning as leaving a photograph of your face. Researchers have developed a computer program that can create a crude three-dimensional (3D) model of a face from a DNA sample.
Using genes to predict eye and hair color is relatively easy. But the complex structure of the face makes it more valuable as a forensic tool — and more difficult to connect to genetic variation, says anthropologist Mark Shriver of Pennsylvania State University in University Park, who led the work, published today in PLOS Genetics1.
Shriver and his colleagues took high-resolution images of the faces of 592 people of mixed European and West African ancestry living in the United States, Brazil and Cape Verde. They used these images to create 3D models, laying a grid of more than 7,000 data points on the surface of the digital face and determining by how much particular points on a given face varied from the average: whether the nose was flatter, for instance, or the cheekbones wider. They had volunteers rate the faces on a scale of masculinity and femininity, as well as on perceived ethnicity.
Next, the authors compared the volunteers’ genomes to identify points at which the DNA differed by a single base, called a single nucleotide polymorphism (SNP). To narrow down the search, they focused on genes thought to be involved in facial development, such as those that shape the head in early embryonic development, and those that are mutated in disorders associated with features such as cleft palate. Then, taking into account the person’s sex and ancestry, they calculated the statistical likelihood that a given SNP was involved in determining a particular facial feature.
This pinpointed 24 SNPs across 20 genes that were significantly associated with facial shape. A computer program the team developed using the data can turn a DNA sequence from an unknown individual into a predictive 3D facial model (see 'Face to face'). Shriver says that the group is now trying to integrate more people and genes, and look at additional traits, such as hair texture and sex-specific differences.
Synthesis and assembly of DNA powerfully enables reverse genetics-based approaches to scientific discovery. I'll present recent and unpublished work on genome refactoring and redesign, focusing on identification of cryptic genetic elements and genome decompression. Next, I'll summarize work published over the past year in which we reported the first non-volatile and rewritable digital genetic data storage systems, amplifying genetic logic gates, and programmed cell-cell communication via arbitrary DNA messages. These experiences will be used to frame ten years of research in synthetic biology, by which the foundational engineering ideas of abstraction and standardization have finally been shown as not impossible to make true, and that when made true enable our designer DNA systems to work reliably the first time.
The internet connects people all over the world. But could the internet also connect us with dolphins, apes, elephants and other highly intelligent species? In a bold talk in Session 10 of TED2013, four incredible thinkers come together to launch the idea of the interspecies internet. Each takes four minutes to talk, then passes the metaphorical baton, building the narrative in parts.
The talk begins with Diana Reiss, a cognitive psychologist who studies intelligence in animals. She shows us a video of an adorable dolphin twirling in the water. But the dolphin isn’t spinning playfully for the camera — the dolphin is watching itself in a two-way mirror.
“A dolphin has self-awareness,” says Reiss. “We used to think this was a uniquely human quality, but dolphins aren’t the only non-human animals to show self-recognition in a mirror. Great apes, our closest relatives, also show this ability.” Ditto for elephants and even magpies.
Reiss shares her work with dolphins — she’s been teaching them to communicate through an underwater keyboard of symbols that correspond to whistles and playful activities. Through this keyboard, the dolphins learned to perform activities on demand, and also to express their desire for them.
Almost 30 years ago, Harold J. Morowitz, who was then at Yale, set forth a bold plan for molecular biology. He outlined a campaign to study one of the smallest single-celled organisms, a bacterium of the genus Mycoplasma. The first step would be to decipher its complete genetic sequence, which in turn would reveal the amino acid sequences of all the proteins in the cell. In the 1980s reading an entire genome was not the routine task it is today, but Morowitz argued that the analysis should be possible if the genome was small enough. He calculated the information content of mycoplasma DNA to be about 160,000 bits, then added: Alternatively, this much DNA will code for about 600 proteins—which suggests that the logic of life can be written in 600 steps. Completely understanding the operations of a prokaryotic cell is a visualizable concept, one that is within the range of the possible.
There was one more intriguing element to Morowitz’s plan: At 600 steps, a computer model is feasible, and every experiment that can be carried out in the laboratory can also be carried out on the computer. The extent to which these match measures the completeness of the paradigm of molecular biology.
Looking back on these proposals from the modern era of industrial-scale genomics and proteomics, there’s no doubt that Morowitz was right about the feasibility of collecting sequence data. On the other hand, the challenges of writing down “the logic of life” in 600 steps and “completely understanding” a living cell still look fairly daunting. And what about the computer program that would simulate a living cell well enough to match experiments carried out on real organisms?
As it happens, a computer program with exactly that goal was published last summer by Markus W. Covert of Stanford University and eight coworkers. The program, called the WholeCell simulation, describes the full life cycle of Mycoplasma genitalium, a bacterium from the genus that Morowitz had suggested. Included in the model are all the major processes of life: transcription of DNA into RNA, translation of RNA into protein, metabolism of nutrients to produce energy and structural constituents, replication of the genome, and ultimately reproduction by cell fission. The outputs of the simulation do seem to match experimental results. So the question has to be faced: Are we on the threshold of “completing” molecular biology?
Our knowledge of the tree of life—a phylogenetic tree summarizing the evolutionary relationships among all life on Earth—is expanding rapidly. “Mega-trees” with millions of tips (species) are expected to appear imminently ( for example, see http://www.opentree.wikispaces.com ). Unfortunately, there has so far been no practical and intuitive way to explore even the much smaller trees with thousands of tips that are now being routinely produced. Without a way to view megatrees, these wondrous objects, representing the culmination of decades of scientific effort, cannot be fully appreciated. The field really needs a solution to this problem to enable scientists to communicate important evolutionary concepts and data effectively, both to each other and to the general public. Just like Google Earth changed the way people look at geography, a sophisticated tree of life browser could really change the way we look at the life around us. Our advances in understanding evolution are moving really fast now, but the tools for looking at these big trees are lagging behind. Displaying large trees is a hard problem that has so far resisted solution. We are still waiting for the equivalent of a Google Maps. However, trees with millions of tips, richly embellished with additional data, can now be easily explored within the web browser of any modern hardware with a zooming user interface similar to that used in Google Maps.
Researchers from the University of Cambridge used a numerical experiment to determine the limits of matt structural color – a phenomenon which is responsible for some of the most intense colors in nature – and found that it extends only as far as blue and green in the visible spectrum. The results, published in PNAS, could be useful in the development of non-toxic paints or coatings with intense color that never fades.
Structural color, which is seen in some bird feathers, butterfly wings or insects, is not caused by pigments or dyes, but internal structure alone. The appearance of the color, whether matt or iridescent, will depending on how the structures are arranged at the nanoscale.
Ordered, or crystalline, structures result in iridescent colors, which change when viewed from different angles. Disordered, or correlated, structures result in angle-independent matt colors, which look the same from any viewing angle. Since structural color does not fade, these angle-independent matt colors would be highly useful for applications such as paints or coatings, where metallic effects are not wanted. “In addition to their intensity and resistance to fading, a matt paint which uses structural color would also be far more environmentally-friendly, as toxic dyes and pigments would not be needed,” said first author Gianni Jacucci from Cambridge’s Department of Chemistry. “However, we first need to understand what the limitations are for recreating these types of colors before any commercial applications are possible.”
“Most of the examples of structural color in nature are iridescent – so far, examples of naturally-occurring matt structural color only exist in blue or green hues,” said co-author Lukas Schertel. “When we’ve tried to artificially recreate matt structural color for reds or oranges, we end up with a poor-quality result, both in terms of saturation and color purity.”
The researchers, who are based in the lab of Dr Silvia Vignolini, used numerical modeling to determine the limitations of creating saturated, pure and matt red structural color. The researchers modeled the optical response and color appearance of nanostructures, as found in the natural world. They found that saturated, matt structural colors cannot be recreated in the red region of the visible spectrum, which might explain the absence of these hues in natural systems.
“Because of the complex interplay between single scattering and multiple scattering, and contributions from correlated scattering, we found that in addition to red, yellow and orange can also hardly be reached,” said Vignolini. Despite the apparent limitations of structural color, the researchers say these can be overcome by using other kinds of nanostructures, such as network structures or multi-layered hierarchical structures, although these systems are not fully understood yet.
Computational method helps scientists examine microbes at a larger, more comprehensive scale than previously possible.
During the Zika virus outbreak of 2015–16, public health officials scrambled to contain the epidemic and curb the pathogen’s devastating effects on pregnant women. At the same time, scientists around the globe tried to understand the genetics of this mysterious virus. The problem was, there just aren’t many Zika virus particles in the blood of a sick patient. Looking for it in clinical samples can be like fishing for a minnow in an ocean.
A new computational method developed by Broad Institute scientists helps overcome this hurdle. Built in the lab of Broad Institute researcher Pardis Sabeti, the “CATCH” method can be used to design molecular “baits” for any virus known to infect humans and all their known strains, including those that are present in low abundance in clinical samples, such as Zika. The approach can help small sequencing centers around the globe conduct disease surveillance more efficiently and cost-effectively, which can provide crucial information for controlling outbreaks.
The new study was led by MIT graduate student Hayden Metsky and postdoctoral researcher Katie Siddle, and it appears online in Nature Biotechnology.
Synthetic biologists are converting microbial cells into living devices that are able to perform useful tasks ranging from the production of drugs, fine chemicals and biofuels to detecting disease-causing agents and releasing therapeutic molecules inside the body. To accomplish this, they fit cells with artificial molecular machinery that can sense stimuli such as toxins in the environment, metabolite levels or inflammatory signals. Much like electronic circuits, these synthetic biological circuits can process information and make logic-guided decisions. Unlike their electronic counterparts, however, biological circuits must be fabricated from the molecular components that cells can produce, and they must operate in the crowded and ever-changing environment within each cell.
Similar to how computer scientists use logical language to have their programs make accurate AND, OR and NOT decisions towards a final goal, “Ribocomputing Devices” (stylized here in yellow) developed by a team at the Wyss Institute can now be used by synthetic biologists to sense and interpret multiple signals in cells and logically instruct their ribosomes (stylized in blue and green) to produce different proteins.
So far, synthetic biological circuits can only sense a handful of signals, giving them an incomplete picture of conditions in the host cell. They are also built out of several moving parts in the form of different types of molecules, such as DNAs, RNAs, and proteins, that must find, bind and work together to sense and process signals. Identifying molecules that cooperate well with one another is difficult and makes development of new biological circuits a time-consuming and often unpredictable process.
As reported in Nature, a team at Harvard’s Wyss Institute for Biologically Inspired Engineering is now presenting an all-in-one solution that imbues a molecule of ‘ribo’ nucleic acid or RNA with the capacity to sense multiple signals and make logical decisions to control protein production with high precision. The study’s approach resulted in a genetically encodable RNA nano-device that can perform an unprecedented 12-input logic operation to accurately regulate the expression of a fluorescent reporter protein in E. coli bacteria only when encountering a complex, user-prescribed profile of intra-cellular stimuli. Such programmable nano-devices may allow researchers to construct more sophisticated synthetic biological circuits, enabling them to analyze complex cellular environments efficiently and to respond accurately.
“We demonstrate that an RNA molecule can be engineered into a programmable and logically acting “Ribocomputing Device,” said Wyss Institute Core Faculty member Peng Yin, Ph.D., who led the study and is also Professor of Systems Biology at Harvard Medical School. “This breakthrough at the interface of nanotechnology and synthetic biology will enable us to design more reliable synthetic biological circuits that are much more conscious of the influences in their environment relevant to specific goals.”
Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm scientists found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo.
Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules.
This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.
EVE Online isn't just a game about internet spaceships and sci-fi politics. Since March, developer CCP Games has been running Project Discovery – an initiative to help improve scientific understanding of the human body at the tiniest levels. Run in conjunction with the Human Protein Atlas and Massively Multiplayer Online Science, the project taps into EVE Online'sgreatest resource – its player base – to help categorise millions of proteins.
"We show them an image, and they can change the colour of it, putting green or red dyes on it to help them analyse it a little bit better," Linzi Campbell, game designer on Project Discovery, tells WIRED. "Then we also show them examples – cytoplasm is their favourite one! We show them what each of the different images should look like, and just get them to pick a few that they identify within the image. The identifications are scrambled each time, so it's not as simple as going 'ok, every time I just pick the one on the right' – they have to really think about it."
The analysis project is worked into EVE Online as a minigame, and works within the context of the game's lore. "We have this NPC organisation called the Drifters – they're like a mysterious entity in New Eden [EVE's interplanetary setting]," Campbell explains. "The players don't know an awful lot about the Drifters at the minute, so we disguised it within the universe as Drifter DNA that they were analysing. I think it just fit perfectly. We branded this as [research being done by] the Sisters of Eve, and they're analysing this Drifter DNA."
The response has been tremendous. "We've had an amazing number of classifications, way over our greatest expectations," says Emma Lundberg, associate professor at the Human Protein Atlas. "Right now, after six weeks, we've had almost eight million classifications, and the players spent 16.2 million minutes playing the minigame. When we did the math, that translated – in Swedish measures – to 163 working years. It's crazy."
"We had a little guess, internally. We said if we get 40,000+ classifications a day, we're happy. If we get 100,000 per day, then we're amazed," Lundberg adds. "But when it peaked in the beginning, we had 900,000 classifications in one day. Now it's stabilised, but we're still getting around 200,000 a day, so everyone is mind-blown. We never expected it."
HIV spreads throughout the body in a similar way to some computer worms, according to a new model, which also suggests that early treatment is key to finding a cure to the disease.
HIV specialists and network security experts at University College London (UCL) have found that HIV progresses both via the bloodstream and directly between cells – akin to computer worms spreading themselves through two routes to infect as many computers as possible.
Prof Benny Chain, from UCL’s infection and immunity division, the co-senior author of the research, said: “I was involved in a study looking in general at spreading of worms across the internet and then I realised the parallel. They have to consistently find another computer to infect outside. They can either look locally in their own networks, their own computers, or you could remotely transmit out a worm to every computer on the internet. HIV also uses two ways of spreading within the body.”
The model was inspired by similarities between HIV and computer worms such as the highly damaging “Conficker” worm, first detected in 2008, which has infected military and police networks across Europe and is still active today.
The researchers’ findings, published on Thursday, told them that just as computer worms spread most efficiently by a combination of two routes, so must HIV – enabling the researchers to create a model for this “hybrid spreading”, which accurately predicted patients’ progression from HIV to Aids.
Detailed sample data from 17 HIV patients from London were used to verify the model, suggesting that hybrid spreading provides the best explanation for HIV progression and highlighting the benefits of very prompt treatment.
Chain said the model provided strong evidence of cell-to-cell spread, which he said some HIV scientists remained sceptical about, as it is difficult to observe in human beingsbecause it occurs in tissue.
Scientists are using previously top-secret technology to zoom through the human body down to the level of a single cell. Scientists are also using cutting-edge microtome and MRI technology to examine how movement and weight bearing affects the movement of molecules within joints, exploring the relationship between blood, bone, lymphatics and muscle.
UNSW biomedical engineer Melissa Knothe Tate is using previously top-secret semiconductor technology to zoom through organs of the human body, down to the level of a single cell.
A world-first UNSW collaboration that uses previously top-secret technology to zoom through the human body down to the level of a single cell could be a game-changer for medicine, an international research conference in the United States has been told.
The imaging technology, developed by high-tech German optical and industrial measurement manufacturer Zeiss, was originally developed to scan silicon wafers for defects.
UNSW Professor Melissa Knothe Tate, the Paul Trainor Chair of Biomedical Engineering, is leading the project, which is using semiconductor technology to explore osteoporosis and osteoarthritis.
Using Google algorithms, Professor Knothe Tate -- an engineer and expert in cell biology and regenerative medicine -- is able to zoom in and out from the scale of the whole joint down to the cellular level "just as you would with Google Maps," reducing to "a matter of weeks analyses that once took 25 years to complete."
Her team is also using cutting-edge microtome and MRI technology to examine how movement and weight bearing affects the movement of molecules within joints, exploring the relationship between blood, bone, lymphatics and muscle. "For the first time we have the ability to go from the whole body down to how the cells are getting their nutrition and how this is all connected," said Professor Knothe Tate. "This could open the door to as yet unknown new therapies and preventions."
Professor Knothe Tate is the first to use the system in humans. She has forged a pioneering partnership with the US-based Cleveland Clinic, Brown and Stanford Universities, as well as Zeiss and Google to help crunch terabytes of data gathered from human hip studies. Similar research is underway at Harvard University and Heidelberg in Germany to map neural pathways and connections in the brains of mice.
A newly developed website catalogs more than 1,300 specimens of extinct flying reptiles called pterosaurs, thus enabling users to map out the ancient creatures on Google Earth. The goal is to help researchers find trends in the evolution and diversity of theseancient winged reptiles.
"Having a very specific database like this, which is just for looking at individual fossil specimens of pterosaurs, is very helpful, because you can ask questions that you couldn't have answered with bigger databases [of more animals]," said Matthew McLain, a doctoral candidate in paleontology at Loma Linda University in California and one of the three developers of the site. McLain and his colleagues call their database PteroTerra.
Pterosaurs were the first flying vertebrates. They lived between 228 million and 66 million years ago, and went extinct around the end of the Cretaceous period. During that time, this group evolved to be incredibly diverse. Some were tiny, like the sparrow-size Nemicolopterus crypticus, which lived 120 million years ago in what is now China. Others were simply huge, like Quetzalcoatlus, which was as tall as a giraffe and probably went around spearing little dinosaurs with its beak like a stork might snack on frogs.
Paleontological databases are common tools, because they allow researchers to navigate through descriptions of fossil specimens. One of the largest, the Paleobiology Database, has more than 50,000 individual entries.
McLain and his colleagues wanted something more targeted. They painstakingly built PteroTerra from the ground up. McLain, as the paleontologist on the project, read published papers on pterosaurs and visited museums to catalog specimens.
"I think we have every species represented, so in that sense, it's pretty complete," he told Live Science. The database does not contain every specimen of pterosaur material ever found — tens of thousands of fossil fragments have been discovered — but McLain hopes to get other paleontologists on board as administrators to upload their specimen data.
New insights into the behavior of photosynthetic proteins from atomic simulations could hasten the development of artificial light-gathering machines.
The protein complex known as photosystem II splits water molecules to release oxygen using sunlight and relatively simple biological building blocks. Although water can also be split artificially using an electrical voltage and a precious metal catalyst, researchers continue to strive to mimic the efficient natural process. So far, however, these efforts have been hampered by an incomplete understanding of the water oxidation mechanism of photosystem II. Shinichiro Nakamura from the RIKEN Innovation Center and colleagues have now used simulations to reveal the hidden pathways of water molecules inside photosystem II.
At the heart of photosystem II is a cluster of manganese, calcium and oxygen atoms, known as the oxygen-evolving complex (OEC), that catalyzes the water-splitting reaction. Recent high-resolution x-ray crystallography studies have revealed the precise positions of the atoms in the OEC and of the protein residues that contact the site. While this information has yielded important structural clues into photosynthetic water oxidation, the movements of water, oxygen and protons within the protein complex are still the subject of much speculation.
To resolve this problem, researchers have turned to molecular dynamics (MD) simulation, a technique that models the time-dependent behavior of biomolecules using thermodynamics and the physics of motion. While previous MD simulations of photosystem II have involved the use of approximate models that focus only on protein monomers or the main OEC components, Nakamura's team took a different approach. "Our hypothesis was that we cannot understand the mechanism of oxygen evolution just by looking at the manganese-based reaction center," he says. "Therefore, we carried out a total MD simulation, without any truncation of the protein or simplification."
In their simulation, the team embedded an exact model of photosystem II inside a thylakoid—a lipid and fatty-acid membrane-bound compartment found in the chloroplasts of plant cells. After initial computations confirmed the reliability of their model, the researchers performed a rigorous MD simulation of the protein—membrane system in the presence of more than 300,000 water molecules (Fig. 1). "The results indicated that water, oxygen and protons move through photosystem II not randomly but via distinct pathways that are not obviously visible," says Nakamura.
The pathways revealed by the simulations are delicately coupled to the dynamic motions of the photosystem II protein residues. While such intricate activity is currently impossible to reproduce artificially, the researchers suspect that combining quantum-chemical calculations with MD simulations could help to unlock the mysterious principles behind the highly efficient oxygen-evolution reactions of this remarkable biological factory.
The team, a collaboration between The University of Queensland and the Australian National University, believe their microscope could lead to a better understanding of the basic components of life and eventually allow quantum mechanics to be probed at a macroscopic level. Their world-first discovery has been published in Nature Photonics.
Team leader Associate Professor Warwick Bowen, of UQ’s ARC Centre of Excellence for Engineered Quantum Systems, said the study relied on quantum interactions between the photons of light to achieve measurement precision that surpassed conventional measurement. “This ‘quantum microscope’ is a pioneering step towards applications of quantum physics in technology,” Associate Professor Bowen said.
“In fundamental physics, it could be immediately applied towards observing phenomena in the microscopic motion of small particles that have yet to be observed and were predicted many decades ago.” In the study, the researchers used their quantum microscope to measure the cytoplasm of a live beer-brewing yeast cell and found they could achieve their measurements 64 per cent faster than with a conventional microscope.
Lead author and UQ PhD student Mr Michael Taylor said the results demonstrated for the first time that quantum light could provide a practical advantage in real-world measurements. “The measurements performed could aid in understanding the life-cycle of a cell, as its cytoplasm plays a crucial role in transferring nutrients into and around the cell,” he said.
Among other things, the ‘quantum microscope’ could reveal the finer details within a cell – more than a regular microscope. Biological imaging is a particularly important application for quantum light as these fine details are typically only visible when a lot of light is used.
“Unfortunately, biological samples are grilled when the power is increased too far,” said Mr Taylor. “The ‘quantum microscope’, on the other hand, provides a way to improve measurement sensitivity without increasing the risk of optical damage to the sample.”
Take a walk through a human brain? Fly over the surface of Mars? Computer scientists at the University of Illinois at Chicago are pushing science fiction closer to reality with a wraparound virtual world where a researcher wearing 3-D glasses can do all that and more.
In the system, known as CAVE2, an 8-foot-high screen encircles the viewer 320 degrees. A panorama of images springs from 72 stereoscopic liquid crystal display panels, conveying a dizzying sense of being able to touch what's not really there.
As far back as 1950, sci-fi author Ray Bradbury imagined a children's nursery that could make bedtime stories disturbingly real. "Star Trek" fans might remember the holodeck as the virtual playground where the fictional Enterprise crew relaxed in fantasy worlds.
The Illinois computer scientists have more serious matters in mind when they hand visitors 3-D glasses and a controller called a "wand." Scientists in many fields today share a common challenge: How to truly understand overwhelming amounts of data. Jason Leigh, co-inventor of the CAVE2 virtual reality system, believes this technology answers that challenge.
"In the next five years, we anticipate using the CAVE to look at really large-scale data to help scientists make sense of that information. CAVEs are essentially fantastic lenses for bringing data into focus," Leigh said.
The CAVE2 virtual world could change the way doctors are trained and improve patient care, Leigh said. Pharmaceutical researchers could use it to model the way new drugs bind to proteins in the human body. Car designers could virtually "drive" their vehicle designs.
Imagine turning massive amounts of data – the forces behind a hurricane, for example – into a simulation that a weather researcher could enlarge and explore from the inside. Architects could walk through their skyscrapers before they are built. Surgeons could rehearse a procedure using data from an individual patient.
But the size and expense of room-based virtual reality systems may prove insurmountable barriers to widespread use, said Henry Fuchs, a computer science professor at the University of North Carolina at Chapel Hill, who is familiar with the CAVE technology but wasn't involved in its development.
While he calls the CAVE2 "a national treasure," Fuchs predicts a smaller technology such as Google's Internet-connected eyeglasses will do more to revolutionize medicine than the CAVE. Still, he says large displays are the best way today for people to interact and collaborate.
Turning vast amounts of genomic data into meaningful information about the cell is the great challenge of bioinformatics, with major implications for human biology and medicine. Researchers at the University of California, San Diego School of Medicine and colleagues have proposed a new method that creates a computational model of the cell from large networks of gene and protein interactions, discovering how genes and proteins connect to form higher-level cellular machinery.
"Our method creates ontology, or a specification of all the major players in the cell and the relationships between them," said first author Janusz Dutkowski, PhD, postdoctoral researcher in the UC San Diego Department of Medicine. It uses knowledge about how genes and proteins interact with each other and automatically organizes this information to form a comprehensive catalog of gene functions, cellular components, and processes.
"What's new about our ontology is that it is created automatically from large datasets. In this way, we see not only what is already known, but also potentially new biological components and processes – the bases for new hypotheses," said Dutkowski.
Originally devised by philosophers attempting to explain the nature of existence, ontologies are now broadly used to encapsulate everything known about a subject in a hierarchy of terms and relationships. Intelligent information systems, such as iPhone's Siri, are built on ontologies to enable reasoning about the real world. Ontologies are also used by scientists to structure knowledge about subjects like taxonomy, anatomy and development, bioactive compounds, disease and clinical diagnosis.
Knowledge about how genes and proteins interact with each other and automatically organizes this information to form a comprehensive catalog of gene functions, cellular components, and processes.
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CROPSR is the first open source software tool for genome-wide design and evaluation of guide RNA (gRNA) sequences for CRISPR experiments, created by scientists at CABBI, a Department of Energy-funded Bioenergy Research Center (BRC). The genome-wide approach significantly shortens the time needed to design a CRISPR experiment, reducing the challenge of working with crops and speeding up the design, evaluation and validation of gRNA sequences, according to the study published in BMC Bioinformatics. To better meet the needs of crop geneticists, the team built software that lifts restrictions imposed by other packages on the design and evaluation of gRNA sequences, the guides used to locate targeted genetic material. Team members also developed a new machine learning model that would not avoid guides for repetitive genomic regions often found in plants, a problem with existing tools. The CROPSR scoring model provided much more accurate predictions, even in non-crop genomes. In the future, he hopes researchers will record their failures as well as their successes to help generate the data needed to train a non-specific model.