DOE News
    Doe Science news source
    The DOE Science News Source is a Newswise initiative to promote research news from the Office of Science of the DOE to the public and news media.
    • 2018-05-29 17:05:12
    • Article ID: 695268

    New Machine Learning Approach Could Accelerate Bioengineering

    Scientists use technique to automatically predict the amount of biofuel produced by microbes

    • Credit: Marilyn Chung , Berkeley Lab

      A new approach developed by Zak Costello (left) and Hector Garcia Martin brings the the speed and analytic power of machine learning to bioengineering.

    Scientists from the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a way to use machine learning to dramatically accelerate the design of microbes that produce biofuel.

    Their computer algorithm starts with abundant data about the proteins and metabolites in a biofuel-producing microbial pathway, but no information about how the pathway actually works. It then uses data from previous experiments to learn how the pathway will behave. The scientists used the technique to automatically predict the amount of biofuel produced by pathways that have been added to E. coli bacterial cells.

    The new approach is much faster than the current way to predict the behavior of pathways, and promises to speed up the development of biomolecules for many applications in addition to commercially viable biofuels, such as drugs that fight antibiotic-resistant infections and crops that withstand drought.

    The research is published May 29 in the journal Nature Systems Biology and Applications.

    In biology, a pathway is a series of chemical reactions in a cell that produce a specific compound. Researchers are exploring ways to re-engineer pathways, and import them from one microbe to another, to harness nature’s toolkit to improve medicine, energy, manufacturing, and agriculture. And thanks to new synthetic biology capabilities, such as the gene-editing tool CRISPR-Cas9, scientists can conduct this research at a precision like never before.

    “But there’s a significant bottleneck in the development process,” said Hector Garcia Martin, group lead at the DOE Agile BioFoundry and director of Quantitative Metabolic Modeling at the Joint BioEnergy Institute (JBEI), a DOE Bioenergy Research Center funded by DOE’s Office of Science and led by Berkeley Lab. The research was performed by Zak Costello (also with the Agile BioFoundry and JBEI) under the direction of Garcia Martin. Both researchers are also in Berkeley Lab’s Biological Systems and Engineering Division.

    “It’s very difficult to predict how a pathway will behave when it’s re-engineered. Trouble-shooting takes up 99% of our time. Our approach could significantly shorten this step and become a new way to guide bioengineering efforts,” Garcia Martin added.

    The current way to predict a pathway’s dynamics requires a maze of differential equations that describe how the components in the system change over time. Subject-area experts develop these “kinetic models” over several months, and the resulting predictions don’t always match experimental results. 

    Machine learning, however, uses data to train a computer algorithm to make predictions. The algorithm learns a system’s behavior by analyzing data from related systems. This allows scientists to quickly predict the function of a pathway even if its mechanisms are poorly understood — as long as there are enough data to work with.

    The scientists tested their technique on pathways added to E. coli cells. One pathway is designed to produce a bio-based jet fuel called limonene; the other produces a gasoline replacement called isopentenol. Previous experiments at JBEI yielded a trove of data related to how different versions of the pathways function in various E. coli strains. Some of the strains have a pathway that produces small amounts of either limonene or isopentenol, while other strains have a version that produces large amounts of the biofuels.

    The researchers fed this data into their algorithm. Then machine learning took over: The algorithm taught itself how the concentrations of metabolites in these pathways change over time, and how much biofuel the pathways produce. It learned these dynamics by analyzing data from the two experimentally known pathways that produce small and large amounts of biofuels. 

    The algorithm used this knowledge to predict the behavior of a third set of “mystery” pathways the algorithm had never seen before. It accurately predicted the biofuel-production profiles for the mystery pathways, including that the pathways produce a medium amount of fuel. In addition, the machine learning-derived prediction outperformed kinetic models.   

    “And the more data we added, the more accurate the predictions became,” said Garcia Martin. “This approach could expedite the time it takes to design new biomolecules. A project that today takes ten years and a team of experts could someday be handled by a summer student.”

    The work was part of the DOE Agile BioFoundry, supported by DOE’s Office of Energy Efficiency and Renewable Energy, and the Joint BioEnergy Institute, supported by DOE’s Office of Science. 


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    Missing gamma-ray blobs shed new light on dark matter, cosmic magnetism

    Scientists, including researchers from the Department of Energy's SLAC National Accelerator Laboratory, have compiled the most detailed catalog of such blobs using eight years of data collected with the Large Area Telescope (LAT) on NASA's Fermi Gamma-Ray Space Telescope. The blobs, including 19 gamma-ray sources that weren't known to be extended before, provide crucial information on how stars are born, how they die, and how galaxies spew out matter trillions of miles into space.

    Applying Auto Industry's Fuel-Efficiency Standards to Agriculture Could Net Billions in Corn Sector, Researchers Conclude

    Adopting benchmarks similar to the fuel-efficiency standards used by the auto industry in the production of fertilizer could yield $5-8 billion in economic benefits for the U.S. corn sector alone, researchers have concluded in a new analysis.

    How Animals Use Their Tails to Swish and Swat Away Insects

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    Research on Light-Matter Interaction Could Lead to Improved Electronic and Optoelectronic Devices

    A paper published in Nature Communications by Sufei Shi, assistant professor of chemical and biological engineering at Rensselaer, increases our understanding of how light interacts with atomically thin semiconductors and creates unique excitonic complex particles, multiple electrons, and holes strongly bound together.

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    Ancient Pigment Can Boost Energy Efficiency

    Egyptian blue, derived from calcium copper silicate, was routinely used on ancient depictions of gods and royalty. Previous studies have shown that when Egyptian blue absorbs visible light, it then emits light in the near-infrared range. Now a team led by researchers at Lawrence Berkeley National Laboratory has confirmed the pigment's fluorescence can be 10 times stronger than previously thought.

    Expanding Fungal Diversity, One Cell at a Time

    Reported October 8, 2018, in Nature Microbiology, a team led by U.S. Department of Energy Joint Genome Institute researchers developed a pipeline to generate genomes from single cells of uncultivated fungi. The approach was tested on several uncultivated species representing early diverging fungi.

    Columbia Engineers Build Smallest Integrated Kerr Frequency Comb Generator

    Optical frequency combs can enable ultrafast processes in physics, biology, and chemistry, as well as improve communication and navigation, medical testing, and security. Columbia Engineers have built a Kerr frequency comb generator that, for the first time, integrates the laser with the microresonator, significantly shrinking the system's size and power requirements. They no longer need to connect separate devices using fiber--they can now integrate it all on compact and energy efficient photonic chips.

    Scientists Present New Clues to Cut Through the Mystery of Titan's Atmospheric Haze

    Experiments at Berkeley Lab helped scientists zero in on a low-temperature chemical mechanism that may help to explain the complex molecular compounds that make up the nitrogen-rich haze layer surrounding Titan, Saturn's largest moon.


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    Prototype Solar Energy, Battery Systems to Fuel Commercialization

    Designing, building and testing prototype systems that show how renewable energy can power devices, such as a weather and soil sensor station, can help bridge the gap between basic science research and commercialization.

    Argonne to Advance High Performance Computing in Manufacturing

    Argonne awarded funding to partner with Industry to advance the use of high performance computing in manufacturing.

    "Invisible Glass" Wins 2018 Create the Future Design Contest Grand Prize

    Scientists from the Center for Functional Nanomaterials developed a technique for making nonreflecting glass, silicon, and plastic surfaces.

    Missouri S&T researchers win multimillion dollar grant to build fast-charging stations for electric cars

    Researchers from Missouri S&T and three private companies will combine their expertise to create charging stations for electric vehicles that could charge a car in less than 10 minutes - matching the time it takes to fill up a conventional vehicle with gasoline."The big problem with electric vehicles is range, and it's not so much range as range anxiety.

    Making batteries store more energy, last longer

    A new solid polymer electrolyte may help make cell phone batteries store more energy and last longer.

    Three Brookhaven Lab Scientists Named Fellows of American Physical Society

    The American Physical Society (APS), the world's largest physics organization, has elected three scientists from the U.S. Department of Energy's (DOE) Brookhaven National Laboratory as 2018 APS fellows.

    Southern Research first to win accreditation under ISO 14034

    Southern Research has become the first organization in the United States to earn accreditation under ISO 14034, a new international standard for evaluating and verifying environmental technologies that was recently adopted by the American National Standards Institute.

    Kawtar Hafidi to head Physical Sciences and Engineering directorate at Argonne

    Physicist Kawtar Hafidi has been appointed Associate Laboratory Director, Physical Sciences and Engineering at the U.S. Department of Energy's (DOE) Argonne National Laboratory.

    Argonne researchers honored by Energy Secretary's awards program

    A select group of researchers from the U.S. Department of Energy's (DOE) Argonne National Laboratory was recently recognized for their contributions to infrastructure security and nuclear nonproliferation at the Secretary's Honor Awards ceremony in Washington, D.C., on August 29.

    PPPL's Sam Cohen earns award at meeting of U.S. government-funded laboratories hosted by PPPL

    PPPL physicist Sam Cohen and a local company win a Federal Laboratory Consortium award for a rocket propulsion technology.


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    How to Make Soot and Stardust

    Scientists unlock mystery that could help reduce emissions of fine particles from combustion engines and other sources.

    Breaking the Symmetry Between Fundamental Forces

    Scientists improve our understanding of the relationship between fundamental forces by re-creating the earliest moments of the universe.

    Water Plays Unexpected Role in Forming Minerals

    Water molecules line up tiny particles to attach and form minerals; understanding how this happens impacts energy extraction and storage along with waste disposal.

    Heavy Particles Get Caught Up in the Flow

    First direct measurement show how heavy particles containing a charm quark get caught up in the flow of early universe particle soup.

    Seeing Between the Atoms

    New detector enables electron microscope imaging at record-breaking resolution.

    Scaling Up Single-Crystal Graphene

    New method can make films of atomically thin carbon that are over a foot long.

    Discovered: Optimal Magnetic Fields Suppress Instabilities in Tokamak Plasmas

    U.S. and Korean scientists show how to find and use beneficial 3-D field perturbations to stabilize dangerous edge-localized modes in plasma.

    New Electron Glasses Sharpen Our View of Atomic-Scale Features

    A new approach to atom probe tomography promises more precise and accurate measurements vital to semiconductors used in computers, lasers, detectors, and more.

    Getting an Up-Close, 3-D View of Gold Nanostars

    Scientists can now measure 3-D structures of tiny particles with properties that hold promise for advanced sensors and diagnostics.

    Small, Short-Lived Drops of Early Universe Matter

    Particle flow patterns suggest even small-scale collisions create drops of early universe quark-gluon plasma.


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