EteRNA is an online game designed to let gamers help scientists figure out how to design and manipulate new ribonucleic acid (RNA) molecules.
RNAs are single strands of nucleotides that can fold into molecules that perform various functions in the body. Creating RNA molecules that perform certain tasks (for example, turning off genes related to a certain genetic disorder) can help researchers abolish rare diseases, create new therapies and possibly cures for neurological disorders, cancers, etc. However, predicting what shape a specific RNA sequence will fold into is a difficult equation to figure out, so that’s what EteRNA is trying to do.
Jeff Anderson-Lee, a computer systems manager who has no biology training, is actually helping researchers understand the building blocks of life by playing an online game. EteRNA is a two-dimensional puzzle game that requires players to fold strands of RNA into complex molecular shapes. It’s performed with the four bases: adenine, guanine, uracil and cytosine. Players are supposed to fill in the individual nucleotides and create stable designs in order to advance to the next puzzle. Once this is done, they design molecules that can solve biochemical problems.
Every week the best designs created by gamers and chosen as the best by the gaming community will be synthesized at Stanford.
The science behind this is quite complicated, but that doesn’t mean that you need to have academic knowledge in order to play. In fact, pretty much everyone can make valuable biochemistry contributions by playing this game, even publish the results.
Jeff Anderson Lee, Eli Fisker, Vineet Kosaraju and Michelle Wu are the first gamers who published research as lead authors – in a peer reviewed scientific journal. This scientific paper will appear in March in a special print issue of the journal devoted to RNA.
DNA structure is the building block of our everyday life. It holds most of the instructions our body needs to perform in a cyclical manner. Researchers and scientist at the University of Washington, in corporation with Microsoft and the University of Illinois have found out that if data is stored in DNA structures, then they can be secured for not just decades but centuries.
The DNA molecules can be used as part of an archival system, which can store almost all of the world’s data in less than nine liters’ worth of the solution. It can help store data for more than millenniums. Currently, magnetic disks such as DVDs and current forms of hard disks can save data for decades at max. An Exabyte of data that we can store in more than 200 million DVDs can be done more efficiently using DNAs. The data that is being generated and stored is costing more than the hardware that is developed to make it store. Hence, the use of DNA to edit and code data in it will make it easier to store vast amounts of information while making them secure for years to come. However, as DNA technology advances, the cost to enable sequencing and creating DNA that is synthetic would fall. Researchers at Microsoft and University of Washington stored four image files in a DNA structure and returned the data easily, with a single error.
Computer storage also uses a form of navigation like our cars do. The same mechanism works for DNA too, which have all data centralized, while monitoring changes in them through processes. If a picture is broken into thousands of pieces and stored in DNA, it is easier to help it be used in thousands of different other pictures, while making the single image formed after centuries. According to a Microsoft computer architect Karin Strauss, DNA can be the best medium to save data, we only need to keep it dry and cold.
Bioengineers at the Rice University have developed a fast computational method to model tissue-specific metabolic pathways. Their computational method may help researchers find new therapeutic targets for various diseases.
Immense networks of biochemical reactions, or metabolic pathways, keep organisms functioning but are also implicated in many diseases. They are challenges that “big data” projects can best address. For example, a pathway in the liver might not act the same way as an identical chain in the muscle. To help overcome this issue, bioengineer Amina Qutub developed an algorithm called Cost Optimization Reaction Dependency Assessment (CORDA), which can model metabolic pathways specific to their home tissues.
In the new CORDA algorithm, metabolic reactions not backed by experimental data are assigned a high “cost” that gives them less importance. This cost is then minimized in a method that depends on flux balance analysis, which is a standard method for simulating metabolism in a network.
“Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions,” said the authors of the article which appeared in PLOS Computational Biology. “These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation.”
The researchers expect their new method will become a broad tool to model cell- and tissue-specific metabolism. They looked at 271 metabolites known to be present in all of the models and found that two (both essential to fatty acid and glycerophospholipid pathways) stood out as essential selectively for cancer models. “Interestingly, although cancer metabolism has often been thought of collectively, CORDA was able to capture key differences between different cancer types,” Qutub said. “In the future, the fast computational approach introduced by CORDA will allow for the high-throughput generation of patient-specific models of metabolism.”
Researchers at Florida Atlantic University led a study that for the first time identified a gene responsible for sleep loss, diabetes, obesity and blood glucose levels. The study is published in the journal Current Biology.
The study authors discovered that a gene called translin integrates the sleep and metabolic state, with important implications for understanding the neural mechanism underlying sleep loss in response to environmental challenges.
Sleep deprivation is associated with increased appetite and insulin insensitivity, while chronically sleep-deprived people are more likely to develop obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease.
Dr. Alex C. Keene, corresponding author of the study explained: “In humans, sleep and feeding are tightly interconnected, and pathological disturbances of either process are associated with metabolism-related disorders. Despite the widespread evidence for interactions between sleep loss and metabolic dysfunction, little is known about the molecular basis of this interaction and how these processes integrate within the brain.”
The sleep cycles of fruit flies are remarkably similar to humans: they get most of their sleep at night, caffeine can negatively affect their sleep and poor sleep can affect their memory performance the next day. They also tend to sacrifice sleep for their quest to search for food. So Keene and his team used fruit flies in their study, putting them on specific diets in order to measure their sleep, pressure levels and blood sugar. They designed various scenarios for the fruit flies, and carried out a nervous system-specific RNAi screen to distinguish the genes required to keep hungry flies awake. What they found is that translin, when knocked down in neurons, causes hungry flies to sleep just as they would on a full stomach.
“While many genes have been identified as genetic regulators of sleep or metabolic state, mounting evidence from our study indicates that translin functions as a unique integrator of these processes,” said co-first author, Kazuma Murakami. “We also have been able to show that this gene is not required for general modulation of sleep. Furthermore, we now know that the energy stores in mutant flies are normal and that the starvation-induced sleep suppression phenotype is not due to increased nutrient storage.”