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  • richardmitnick 11:33 am on March 5, 2017 Permalink | Reply
    Tags: , , , , Genetic Engineering, , Hamilton Smith, , Methylation, Restriction enzyme, The Man Who Kicked Off the Biotech Revolution   

    From Nautilus: “The Man Who Kicked Off the Biotech Revolution” Hamilton Smith 

    Nautilus

    Nautilus

    3.5.17
    Carl Zimmer

    It’s hard to tell precisely how big a role biotechnology plays in our economy, because it infiltrates so many parts of it. Genetically modified organisms such as microbes and plants now create medicine, food, fuel, and even fabrics. Recently, Robert Carlson, of the biotech firm Biodesic and the investment firm Bioeconomy Capital, decided to run the numbers and ended up with an eye-popping estimate. He concluded that in 2012, the last year for which good data are available, revenues from biotechnology in the United States alone were over $324 billion.

    “If we talk about mining or several manufacturing sectors, biotech is bigger than those,” said Carlson. “I don’t think people appreciate that.”

    1
    Matchmaker Biotech pioneer Hamilton Smith chose to study recombination in a species of bacteria called Haemophilus influenza (above), which can take up foreign DNA fragments and integrate them into its own DNA. Media for Medical/UIG via Getty Images

    What makes the scope of biotech so staggering is not just its size, but its youth. Manufacturing first exploded in the Industrial Revolution of the 19th century. But biotech is only about 40 years old. It burst into existence thanks largely to a discovery made in the late 1960s by Hamilton Smith, a microbiologist then at Johns Hopkins University, and his colleagues, that a protein called a restriction enzyme can slice DNA. Once Smith showed the world how restriction enzymes work, other scientists began using them as tools to alter genes.

    “And once you have the ability to start to manipulate the world with those tools,” said Carlson, “the world opens up.”

    The story of restriction enzymes is a textbook example of how basic research can ultimately have a huge impact on society. Smith had no such grand ambitions when he started his work. He just wanted to do some science. “I was just having a lot of fun, learning as I went,” Smith, now 85, said.

    In 1968, when Smith was a new assistant professor at Johns Hopkins University, he became curious about how cells cut DNA into pieces and shuffle them into new arrangements—a process known as recombination. “It’s a universal thing,” Smith said. “Every living thing has recombination systems. But at the time, no one was sure how it worked, mechanically.”

    Smith chose to study recombination in a species of bacteria called Haemophilus influenza. Like many other species, H. influenzae can take up foreign DNA, either sucking in loose fragments from the environment or gaining them from microbial donors. Somehow, the bacterium can then integrate these fragments into its own DNA.

    Bacteria gain useful genes in this way, endowing them with new traits such as resistance to antibiotics. But recombination also has a dark side for H. influenzae. Invading viruses can hijack the recombination machinery in bacteria. They then insert their own genes into their host’s DNA, so that the microbes make new copies of the virus.

    To understand recombination, Smith produced radioactive viruses by introducing viruses into bacteria that had been fed radioactive phosphorus. New viruses produced inside the bacteria ended up with radioactive phosphorus in their DNA. Smith and his colleagues could then unleash these radioactive viruses on other bacteria. The scientists expected that during the infection, the bacteria’s genes would become radioactive as the viruses inserted their genetic material into their host’s DNA.

    At least that was they thought would happen. When Smith’s graduate student Kent Wilcox infected bacteria with the radioactive viruses, the radioactivity never ended up in the bacteria’s own genome.

    Trying to make sense of the failure, Wilcox suggested to Smith that the bacteria were destroying the viral DNA. He based his suggestion on a hypothesis proposed a few years earlier by Werner Arber, a microbiologist at the University of Geneva. Arber speculated that enzymes could restrict the growth of viruses by chopping up their DNA, and dubbed these hypothetical molecules “restriction enzymes.”

    Arber recognized that if restriction enzymes went on an unchecked rampage, they could kill the bacteria themselves by chopping up their own DNA. He speculated that bacteria were shielding their own DNA from assault, and thus avoiding suicide, by covering their genes with carbon and hydrogen atoms—a process known as methylation. The restriction enzymes couldn’t attack methylated DNA, Arber proposed, but it could attack the unprotected DNA of invading viruses.

    The week before Wilcox had carried out his baffling experiment, Smith had assigned his lab a provocative new paper supporting Arber’s hypothesis. Matthew Meselson and Robert Yuan at Harvard University reported in the paper how they had discovered a protein in E. coli that cut up foreign DNA—in other words, an actual restriction enzyme. With that paper fresh in his mind, Wilcox suggested to Smith that they had just stumbled across another restriction enzyme in Haemophilus influenzae.

    Smith tested the idea with an elegant experiment. He poured viral DNA into a test tube, and DNA from H. influenza into another. To each of these tubes, he then added a soup of proteins from the bacteria. If indeed the bacteria made restriction enzymes, the enzymes in the soup would chop up the viral DNA into small pieces.

    Scientists were decades away from inventing the powerful sequencers that are used today to analyze DNA. But Smith came up with a simple way to investigate the DNA in his test tubes. A solution containing large pieces of DNA is more viscous—more syrupy, in effect—than one with small pieces. So Smith measured the solution in his two test tubes with a device called a viscometer. As he had predicted, the virus DNA quickly became far less viscous. Something—some H. influenzae protein, presumably—was cutting the virus DNA into little pieces.

    “So I immediately knew this had to be a restriction enzyme,” Smith said. “It was a wonderful result—five minutes, and you know you have a discovery.”

    That instant gratification was followed by months of tedium, as Smith and his colleagues sorted through the proteins in their cell extracts until at last they identified a restriction enzyme. They also discovered a methylation enzyme that protected H. influenzae’s own DNA from destruction by shielding it with carbon and hydrogen.

    Once Smith and his colleagues published the remarkable details of their restriction enzymes, other scientists began to investigate them as well. They didn’t just study the enzymes, though—they began employing them as a tool. In 1972, Paul Berg, a biologist at Stanford University, used restriction enzymes to make cuts in the DNA of SV40 viruses, and then used other enzymes to attach the DNA from another virus to those loose ends. Berg thus created a single piece of DNA made up of genetic material from two species.

    A pack of scientists followed Berg’s lead. They realized that they could use restriction enzymes to insert genes from many different species into bacteria, which could then churn out proteins from those genes. In effect, bacteria could be transformed into biological factories.

    In 1978, Hamilton Smith got a call from Stockholm. He learned that he was sharing that year’s Nobel Prize in Medicine with Werner Arber and Daniel Nathans, another Johns Hopkins scientist who had followed up on Smith’s enzyme research with experiments of his own. Smith was as flummoxed as he was delighted.

    “They caught me off-guard,” Smith said. “I always looked up to the Nobelists as being incredibly smart people who had accomplished some world-shaking thing. It just didn’t seem like I was in that league.”

    But already the full impact of his work was starting to become clear. Companies sprouted up that were dedicated to using restriction enzymes to modify DNA. The first commercial application of this technology came from Genentech, a company founded in 1976. Genentech scientists used restriction enzymes to create a strain of E. coli that carried the gene for human insulin. Previously, people with diabetes could only purchase insulin extracted from the pancreases of cows and pigs. Genentech sold insulin produced by swarms of bacteria reared in giant metal drums.

    Over the years, scientists have built on Smith’s initial successes by finding new tools for manipulating DNA. Yet even today, researchers make regular use of restriction enzymes to slice open genes. “They’re still absolutely crucial,” said Carlson. “If you want to put a specific sequence of DNA in another sequence, it’s still most often restriction enzymes that you use to do that.”

    And as Smith has watched restriction enzymes become powerful and versatile, he has slowly overcome his case of Nobel imposter syndrome. “It probably was okay to get it,” he admitted.

    See the full article here .

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  • richardmitnick 8:57 am on September 9, 2016 Permalink | Reply
    Tags: , , , Genetic Engineering, Genetic Engineering to Clash With Evolution,   

    From Quanta: “Genetic Engineering to Clash With Evolution” 

    Quanta Magazine
    Quanta Magazine

    September 8, 2016
    Brooke Borel

    In a crowded auditorium at New York’s Cold Spring Harbor Laboratory in August, Philipp Messer, a population geneticist at Cornell University, took the stage to discuss a powerful and controversial new application for genetic engineering: gene drives.

    Gene drives can force a trait through a population, defying the usual rules of inheritance. A specific trait ordinarily has a 50-50 chance of being passed along to the next generation. A gene drive could push that rate to nearly 100 percent. The genetic dominance would then continue in all future generations. You want all the fruit flies in your lab to have light eyes? Engineer a drive for eye color, and soon enough, the fruit flies’ offspring will have light eyes, as will their offspring, and so on for all future generations. Gene drives may work in any species that reproduces sexually, and they have the potential to revolutionize disease control, agriculture, conservation and more. Scientists might be able to stop mosquitoes from spreading malaria, for example, or eradicate an invasive species.

    The technology represents the first time in history that humans have the ability to engineer the genes of a wild population. As such, it raises intense ethical and practical concerns, not only from critics but from the very scientists who are working with it.

    Messer’s presentation highlighted a potential snag for plans to engineer wild ecosystems: Nature usually finds a way around our meddling. Pathogens evolve antibiotic resistance; insects and weeds evolve to thwart pesticides. Mosquitoes and invasive species reprogrammed with gene drives can be expected to adapt as well, especially if the gene drive is harmful to the organism — it’ll try to survive by breaking the drive.

    “In the long run, even with a gene drive, evolution wins in the end,” said Kevin Esvelt, an evolutionary engineer at the Massachusetts Institute of Technology. “On an evolutionary timescale, nothing we do matters. Except, of course, extinction. Evolution doesn’t come back from that one.”

    Gene drives are a young technology, and none have been released into the wild. A handful of laboratory studies show that gene drives work in practice — in fruit flies, mosquitoes and yeast. Most of these experiments have found that the organisms begin to develop evolutionary resistance that should hinder the gene drives. But these proof-of-concept studies follow small populations of organisms. Large populations with more genetic diversity — like the millions of swarms of insects in the wild — pose the most opportunities for resistance to emerge.

    It’s impossible — and unethical — to test a gene drive in a vast wild population to sort out the kinks. Once a gene drive has been released, there may be no way to take it back. (Some researchers have suggested the possibility of releasing a second gene drive to shut down a rogue one. But that approach is hypothetical, and even if it worked, the ecological damage done in the meantime would remain unchanged.)

    The next best option is to build models to approximate how wild populations might respond to the introduction of a gene drive. Messer and other researchers are doing just that. “For us, it was clear that there was this discrepancy — a lot of geneticists have done a great job at trying to build these systems, but they were not concerned that much with what is happening on a population level,” Messer said. Instead, he wants to learn “what will happen on the population level, if you set these things free and they can evolve for many generations — that’s where resistance comes into play.”

    At the meeting at Cold Spring Harbor Laboratory, Messer discussed a computer model his team developed, which they described in a paper posted in June on the scientific preprint site biorxiv.org. The work is one of three theoretical papers on gene drive resistance submitted to biorxiv.org in the last five months — the others are from a researcher at the University of Texas, Austin, and a joint team from Harvard University and MIT. (The authors are all working to publish their research through traditional peer-reviewed journals.) According to Messer, his model suggests “resistance will evolve almost inevitably in standard gene drive systems.”

    It’s still unclear where all this interplay between resistance and gene drives will end up. It could be that resistance will render the gene drive impotent. On the one hand, this may mean that releasing the drive was a pointless exercise; on the other hand, some researchers argue, resistance could be an important natural safety feature. Evolution is unpredictable by its very nature, but a handful of biologists are using mathematical models and careful lab experiments to try to understand how this powerful genetic tool will behave when it’s set loose in the wild.

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    Lucy Reading-Ikkanda for Quanta Magazine

    Resistance Isn’t Futile

    Gene drives aren’t exclusively a human technology. They occasionally appear in nature. Researchers first thought of harnessing the natural versions of gene drives decades ago, proposing to re-create them with “crude means, like radiation” or chemicals, said Anna Buchman, a postdoctoral researcher in molecular biology at the University of California, Riverside. These genetic oddities, she adds, “could be manipulated to spread genes through a population or suppress a population.”

    In 2003, Austin Burt, an evolutionary geneticist at Imperial College London, proposed a more finely tuned approach called a homing endonuclease gene drive, which would zero in on a specific section of DNA and alter it.

    Burt mentioned the potential problem of resistance — and suggested some solutions — both in his seminal paper and in subsequent work. But for years, it was difficult to engineer a drive in the lab, because the available technology was cumbersome.

    With the advent of genetic engineering, Burt’s idea became reality. In 2012, scientists unveiled CRISPR, a gene-editing tool that has been described as a molecular word processor. It has given scientists the power to alter genetic information in every organism they have tried it on. CRISPR locates a specific bit of genetic code and then breaks both strands of the DNA at that site, allowing genes to be deleted, added or replaced.

    CRISPR provides a relatively easy way to release a gene drive. First, researchers insert a CRISPR-powered gene drive into an organism. When the organism mates, its CRISPR-equipped chromosome cleaves the matching chromosome coming from the other parent. The offspring’s genetic machinery then attempts to sew up this cut. When it does, it copies over the relevant section of DNA from the first parent — the section that contains the CRISPR gene drive. In this way, the gene drive duplicates itself so that it ends up on both chromosomes, and this will occur with nearly every one of the original organism’s offspring.

    Just three years after CRISPR’s unveiling, scientists at the University of California, San Diego, used CRISPR to insert inheritable gene drives into the DNA of fruit flies, thus building the system Burt had proposed. Now scientists can order the essential biological tools on the internet and build a working gene drive in mere weeks. “Anyone with some genetics knowledge and a few hundred dollars can do it,” Messer said. “That makes it even more important that we really study this technology.”

    Although there are many different ways gene drives could work in practice, two approaches have garnered the most attention: replacement and suppression. A replacement gene drive alters a specific trait. For example, an anti-malaria gene drive might change a mosquito’s genome so that the insect no longer had the ability to pick up the malaria parasite. In this situation, the new genes would quickly spread through a wild population so that none of the mosquitoes could carry the parasite, effectively stopping the spread of the disease.

    A suppression gene drive would wipe out an entire population. For example, a gene drive that forced all offspring to be male would make reproduction impossible.

    But wild populations may resist gene drives in unpredictable ways. “We know from past experiences that mosquitoes, especially the malaria mosquitoes, have such peculiar biology and behavior,” said Flaminia Catteruccia, a molecular entomologist at the Harvard T.H. Chan School of Public Health. “Those mosquitoes are much more resilient than we make them. And engineering them will prove more difficult than we think.” In fact, such unpredictability could likely be found in any species.

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    A sample of malaria-infected blood contains two Plasmodium falciparum parasites. CDC/PHIL

    The three new biorxiv.org papers use different models to try to understand this unpredictability, at least at its simplest level.

    The Cornell group used a basic mathematical model to map how evolutionary resistance will emerge in a replacement gene drive. It focuses on how DNA heals itself after CRISPR breaks it (the gene drive pushes a CRISPR construct into each new organism, so it can cut, copy and paste itself again). The DNA repairs itself automatically after a break. Exactly how it does so is determined by chance. One option is called nonhomologous end joining, in which the two ends that were broken get stitched back together in a random way. The result is similar to what you would get if you took a sentence, deleted a phrase, and then replaced it with an arbitrary set of words from the dictionary — you might still have a sentence, but it probably wouldn’t make sense. The second option is homology-directed repair, which uses a genetic template to heal the broken DNA. This is like deleting a phrase from a sentence, but then copying a known phrase as a replacement — one that you know will fit the context.

    Nonhomologous end joining is a recipe for resistance. Because the CRISPR system is designed to locate a specific stretch of DNA, it won’t recognize a section that has the equivalent of a nonsensical word in the middle. The gene drive won’t get into the DNA, and it won’t get passed on to the next generation. With homology-directed repair, the template could include the gene drive, ensuring that it would carry on.

    The Cornell model tested both scenarios. “What we found was it really is dependent on two things: the nonhomologous end-joining rate and the population size,” said Robert Unckless, an evolutionary geneticist at the University of Kansas who co-authored the paper as a postdoctoral researcher at Cornell. “If you can’t get nonhomologous end joining under control, resistance is inevitable. But resistance could take a while to spread, which means you might be able to achieve whatever goal you want to achieve.” For example, if the goal is to create a bubble of disease-proof mosquitoes around a city, the gene drive might do its job before resistance sets in.

    The team from Harvard and MIT also looked at nonhomologous end joining, but they took it a step further by suggesting a way around it: by designing a gene drive that targets multiple sites in the same gene. “If any of them cut at their sites, then it’ll be fine — the gene drive will copy,” said Charleston Noble, a doctoral student at Harvard and the first author of the paper. “You have a lot of chances for it to work.”

    The gene drive could also target an essential gene, Noble said — one that the organism can’t afford to lose. The organism may want to kick out the gene drive, but not at the cost of altering a gene that’s essential to life.

    The third biorxiv.org paper, from the UT Austin team, took a different approach. It looked at how resistance could emerge at the population level through behavior, rather than within the target sequence of DNA. The target population could simply stop breeding with the engineered individuals, for example, thus stopping the gene drive.

    “The math works out that if a population is inbred, at least to some degree, the gene drive isn’t going to work out as well as in a random population,” said James Bull, the author of the paper and an evolutionary biologist at Austin. “It’s not just sequence evolution. There could be all kinds of things going on here, by which populations block [gene drives],” Bull added. “I suspect this is the tip of the iceberg.”

    Resistance is constrained only by the limits of evolutionary creativity. It could emerge from any spot along the target organism’s genome. And it extends to the surrounding environment as well. For example, if a mosquito is engineered to withstand malaria, the parasite itself may grow resistant and mutate into a newly infectious form, Noble said.

    Not a Bug, but a Feature?

    If the point of a gene drive is to push a desired trait through a population, then resistance would seem to be a bad thing. If a drive stops working before an entire population of mosquitoes is malaria-proof, for example, then the disease will still spread. But at the Cold Spring Harbor Laboratory meeting, Messer suggested the opposite: “Let’s embrace resistance. It could provide a valuable safety control mechanism.” It’s possible that the drive could move just far enough to stop a disease in a particular region, but then stop before it spread to all of the mosquitoes worldwide, carrying with it an unknowable probability of unforeseen environmental ruin.

    Not everyone is convinced that this optimistic view is warranted. “It’s a false security,” said Ethan Bier, a geneticist at the University of California, San Diego. He said that while such a strategy is important to study, he worries that researchers will be fooled into thinking that forms of resistance offer “more of a buffer and safety net than they do.”

    And while mathematical models are helpful, researchers stress that models can’t replace actual experimentation. Ecological systems are just too complicated. “We have no experience engineering systems that are going to evolve outside of our control. We have never done that before,” Esvelt said. “So that’s why a lot of these modeling studies are important — they can give us a handle on what might happen. But I’m also hesitant to rely on modeling and trying to predict in advance when systems are so complicated.”

    Messer hopes to put his theoretical work into a real-world setting, at least in the lab. He is currently directing a gene drive experiment at Cornell that tracks multiple cages of around 5,000 fruit flies each — more animals than past studies have used to research gene drive resistance. The gene drive is designed to distribute a fluorescent protein through the population. The proteins will glow red under a special light, a visual cue showing how far the drive gets before resistance weeds it out.

    Others are also working on resistance experiments: Esvelt and Catteruccia, for example, are working with George Church, a geneticist at Harvard Medical School, to develop a gene drive in mosquitoes that they say will be immune to resistance. They plan to insert multiple drives in the same gene — the strategy suggested by the Harvard/MIT paper.

    Such experiments will likely guide the next generation of computer models, to help tailor them more precisely to a large wild population.

    “I think it’s been interesting because there is this sort of going back and forth between theory and empirical work,” Unckless said. “We’re still in the early days of it, but hopefully it’ll be worthwhile for both sides, and we’ll make some informed and ethically correct decisions about what to do.”

    See the full article here .

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    Formerly known as Simons Science News, Quanta Magazine is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
  • richardmitnick 12:44 pm on August 13, 2016 Permalink | Reply
    Tags: , , Genetic Engineering, ,   

    From Science Node: “Opening the spigot at XSEDE” 

    Science Node bloc
    Science Node

    09 Aug, 2016
    Ken Chiacchia

    A boost from sequencing technologies and computational tools is in store for scientists studying how cells change which of their genes are active.

    Researchers using the Extreme Science and Engineering Discovery Environment (XSEDE) collaboration of supercomputing centers have reported advances in reconstructing cells’ transcriptomes — the genes activated by ‘transcribing’ them from DNA into RNA.

    The work aims to clarify the best practices in assembling transcriptomes, which ultimately can aid researchers throughout the biomedical sciences.

    1
    Digital detectives. Researchers from Texas A&M are using XSEDE resources to manage the data from transcriptome assembly. Studying transcriptomes will offer critical clues of how cells change their behavior in response to disease processes.

    “It’s crucial to determine the important factors that affect transcriptome reconstruction,” says Noushin Ghaffari of AgriLife Genomics and Bioinformatics, at Texas A&M University. “This work will particularly help generate more reliable resources for scientists studying non-model species” — species not previously well studied.

    Ghaffari is principal investigator in an ongoing project whose preliminary findings and computational aspects were presented at the XSEDE16 conference in Miami in July. She is leading a team of students and supercomputing experts from Texas A&M, Indiana University, and the Pittsburgh Supercomputing Center (PSC).

    The scientists sought to improve the quality and efficiency of assembling transcriptomes, and they tested their work on two real data sets from the Sequencing Quality Control Consortium (SEQC) RNA-Seq data: One of cancer cell lines and one of brain tissues from 23 human donors.

    What’s in a transcriptome?

    The transcriptome of a cell at a given moment changes as it reacts to its environment. Transcriptomes offer critical clues of how cells change their behavior in response to disease processes like cancer, or normal bodily signals like hormones.

    Assembling a transcriptome is a big undertaking with current technology, though. Scientists must start with samples containing tens or hundreds of thousands of RNA molecules that are each thousands of RNA ‘base units’ long. Trouble is, most of the current high-speed sequencing technologies can only read a couple hundred bases at one time.

    So researchers must first chemically cut the RNA into small pieces, sequence it, remove RNA not directing cell activity, and then match the overlapping fragments to reassemble the original RNA molecules.

    Harder still, they must identify and correct sequencing mistakes, and deal with repetitive sequences that make the origin and number of repetitions of a given RNA sequence unclear.

    While software tools exist to undertake all of these tasks, Ghaffari’s report was the most comprehensive yet to examine a variety of factors that affect assembly speed and accuracy when these tools are combined in a start-to-finish workflow.

    Heavy lifting

    The most comprehensive study of its kind, the report used data from SEQC to assemble a transcriptome, incorporating many quality control steps to ensure results were accurate. The process required vast amounts of computer memory, made possible by PSC’s high-memory supercomputers Blacklight, Greenfield, and now the new Bridges system’s 3-terabyte ‘large memory nodes.’

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    Blacklight supercomputer at the Pittsburgh Supercomputing Center.

    3
    Bridges HPE/Intel supercomputer

    4
    Bridges, a new PSC supercomputer, is designed for unprecedented flexibility and ease of use. It will include database and web servers to support gateways, collaboration, and powerful data management functions. Courtesy Pittsburgh Supercomputing Center.

    “As part of this work, we are running some of the largest transcriptome assemblies ever done,” says coauthor Philip Blood of PSC, an expert in XSEDE’s Extended Collaborative Support Service. “Our effort focused on running all these big data sets many different ways to see what factors are important in getting the best quality. Doing this required the large memory nodes on Bridges, and a lot of technical expertise to manage the complexities of the workflow.”

    During the study, the team concentrated on optimizing the speed of data movement from storage to memory to the processors and back.

    They also incorporated new verification steps to avoid perplexing errors that arise when wrangling big data through complex pipelines. Future work will include the incorporation of ‘checkpoints’ — storing the computations regularly so that work is not lost if a software error happens.

    Ultimately, Blood adds, the scientists would like to put the all the steps of the process into an automated workflow that will make it easy for other biomedical researchers to replicate.

    The work promises a better understanding of how living organisms respond to disease, environment and evolutionary changes, the scientists reported.

    See the full article here .

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  • richardmitnick 1:38 pm on October 22, 2015 Permalink | Reply
    Tags: , Genetic Engineering, ,   

    From MIT: “Quantum physics meets genetic engineering” 


    MIT News

    October 14, 2015
    David L. Chandler | MIT News Office

    1
    Rendering of a virus used in the MIT experiments. The light-collecting centers, called chromophores, are in red, and chromophores that just absorbed a photon of light are glowing white. After the virus is modified to adjust the spacing between the chromophores, energy can jump from one set of chromophores to the next faster and more efficiently. Courtesy of the researchers and Lauren Aleza Kaye

    Researchers use engineered viruses to provide quantum-based enhancement of energy transport.


    download the mp4 video here.

    Nature has had billions of years to perfect photosynthesis, which directly or indirectly supports virtually all life on Earth. In that time, the process has achieved almost 100 percent efficiency in transporting the energy of sunlight from receptors to reaction centers where it can be harnessed — a performance vastly better than even the best solar cells.

    One way plants achieve this efficiency is by making use of the exotic effects of quantum mechanics — effects sometimes known as quantum weirdness. These effects, which include the ability of a particle to exist in more than one place at a time, have now been used by engineers at MIT to achieve a significant efficiency boost in a light-harvesting system.

    Surprisingly, the researchers at MIT and Eni, the Italian energy company, achieved this new approach to solar energy not with high-tech materials or microchips — but by using genetically engineered viruses.

    This achievement in coupling quantum research and genetic manipulation, described this week in the journal Nature Materials, was the work of MIT professors Angela Belcher, an expert on engineering viruses to carry out energy-related tasks, and Seth Lloyd, an expert on quantum theory and its potential applications; research associate Heechul Park; and 14 collaborators at MIT, Eni, and Italian universities.

    Lloyd, a professor of mechanical engineering, explains that in photosynthesis, a photon hits a receptor called a chromophore, which in turn produces an exciton — a quantum particle of energy. This exciton jumps from one chromophore to another until it reaches a reaction center, where that energy is harnessed to build the molecules that support life.

    But the hopping pathway is random and inefficient unless it takes advantage of quantum effects that allow it, in effect, to take multiple pathways at once and select the best ones, behaving more like a wave than a particle.

    This efficient movement of excitons has one key requirement: The chromophores have to be arranged just right, with exactly the right amount of space between them. This, Lloyd explains, is known as the Quantum Goldilocks Effect.

    That’s where the virus comes in. By engineering a virus that Belcher has worked with for years, the team was able to get it to bond with multiple synthetic chromophores — or, in this case, organic dyes. The researchers were then able to produce many varieties of the virus, with slightly different spacings between those synthetic chromophores, and select the ones that performed best.

    In the end, they were able to more than double excitons’ speed, increasing the distance they traveled before dissipating — a significant improvement in the efficiency of the process.

    The project started at a workshop held at Eni’s laboratories in Novara, Italy. Lloyd and Belcher, a professor of biological engineering, were reporting on different projects they had worked on, and began discussing, along with Eni researchers, the possibility of a project encompassing their very different expertise. Lloyd, whose work is mostly theoretical, pointed out that the viruses Belcher works with have the right length scales to potentially support quantum effects.

    In 2008, Lloyd had published a paper demonstrating that photosynthetic organisms transmit light energy efficiently because of these quantum effects. When he saw Belcher’s report on her work with engineered viruses, he wondered if that might provide a way to artificially induce a similar effect, in an effort to approach nature’s efficiency.

    “I had been talking about potential systems you could use to demonstrate this effect, and Angela said, ‘We’re already making those,’” Lloyd recalls. Eventually, after much analysis, “We came up with design principles to redesign how the virus is capturing light, and get it to this quantum regime.”

    Within two weeks, Belcher’s team had created their first test version of the engineered virus. Many months of work then went into perfecting the receptors and the spacings.

    Once the team engineered the viruses, they were able to use laser spectroscopy and dynamical modeling to watch the light-harvesting process in action, and to demonstrate that the new viruses were indeed making use of quantum coherence to enhance the transport of excitons.

    “It was really fun,” Belcher says. “A group of us who spoke different [scientific] languages worked closely together, to both make this class of organisms, and analyze the data. That’s why I’m so excited by this.”

    While this initial result is essentially a proof of concept rather than a practical system, it points the way toward an approach that could lead to inexpensive and efficient solar cells or light-driven catalysis, the team says. So far, the engineered viruses collect and transport energy from incoming light, but do not yet harness it to produce power (as in solar cells) or molecules (as in photosynthesis). But this could be done by adding a reaction center, where such processing takes place, to the end of the virus where the excitons end up.

    “This is exciting and high-quality research,” says Alán Aspuru-Guzik, a professor of chemistry and chemical biology at Harvard University who was not involved in this work. The research, he says, “combines the work of a leader in theory (Lloyd) and a leader in experiment (Belcher) in a truly multidisciplinary and exciting combination that spans biology to physics to potentially, future technology.”

    “​Access to controllable excitonic systems is a goal shared by many researchers in the field,” Aspuru-Guzik adds. “This work provides fundamental understanding that can allow for the development of devices with an increased control of exciton flow.”

    The research was supported by Eni through the MIT Energy Initiative. In addition to MIT postdocs Nimrod Heldman and Patrick Rebentrost, the team included researchers at the University of Florence, the University of Perugia, and Eni.

    See the full article here .

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