In a paper published today in Nature Biotechnology, researchers led by Los Alamos National Laboratory and the U.S. Department of Energy Joint Genome Institute announced that the genetic sequence of the fungus Tricoderma reesei has uncovered important clues about how the organism breaks down plant fibers into simple sugars. The finding could unlock possibilities for industrial processes that can more efficiently and cost effectively convert corn, switchgrass and even cellulose-based municipal waste into ethanol. Ethanol from waste products is a more-carbon-neutral alternative to gasoline.

The fungus T. reesei rose to dubious fame during World War II when military leaders discovered it was responsible for rapid deterioration of clothing and tents in the South Pacific. Named after Dr. Elwyn T. Reese, who, with colleagues, originally isolated the hungry fungus, T. reesei was later identified as a source of industrial enzymes and a role model for the conversion of cellulose and hemicellulose — plant fibers — into simple sugars.

The organism uses enzymes it creates to break down human-indigestible fibers of plants into the simplest form of sugar, known as a monosaccharide. The fungus then digests the sugars as food.

Researchers decoded the genetic sequence of T. reesei in an attempt to discover why the deep green fungus was so darned good at digesting plant cells. The sequence results were somewhat surprising. Contrary to what one might predict about the gene content of a fungus that can eat holes in tents, T. reesei had fewer genes dedicated to the production of cellulose-eating enzymes than its counterparts.

“We were aware of T. reesei’s reputation as producer of massive quantities of degrading enzymes, however we were surprised by how few enzyme types it produces, which suggested to us that its protein secretion system is exceptionally efficient,” said Los Alamos bioscientist Diego Martinez (also at the University of New Mexico), the study’s lead author. The researchers believe that T. reesei’s genome includes “clusters” of enzyme-producing genes, a strategy that may account for the organism’s efficiency at breaking down cellulose.

On an industrial scale, T. reesei could be employed to secrete enzymes that can be purified and added into an aqueous mixture of cellulose pulp and other materials to produce sugar. The sugar can then be fermented by yeast to produce ethanol.

“The sequencing of the Trichoderma reesei genome is a major step towards using renewable feedstocks for the production of fuels and chemicals,” said Joel Cherry, director of research activities in second-generation biofuels for Novozymes, a collaborating institution in the study. “The information contained in its genome will allow us to better understand how this organism degrades cellulose so efficiently and to understand how it produces the required enzymes so prodigiously. Using this information, it may be possible to improve both of these properties, decreasing the cost of converting cellulosic biomass to fuels and chemicals.”

[James E. Rickman @ DOE/Los Alamos National Laboratory]

Professor Downing found that constructed ponds and lakes on farmland in the United States bury carbon at a much higher rate than expected; as much as 20-50 times the rate at which trees trap carbon. In addition, ponds were found to take up carbon at a higher rate than larger lakes.

“Aquatic ecosystems play a disproportionately large role in the global carbon budget,” Downing said. “Despite being overlooked in the past, it’s small bodies of water that are important because they take up carbon at a high rate and there are more of them than previously thought. The combined effect is that farm ponds could be burying as much carbon as the world’s oceans, each year.”

Ponds capture carbon in two main ways:

The research estimated there are 304 million natural lakes and ponds in the world, covering an area of 4.2 million square kilometers, twice the area previously thought. As many as 90 percent of these water bodies are one hectare (two acres) or less in area.

Downing’s research team published its most recent findings in the Feb. 15 issue of the journal Global Biogeochemical Cycles in a paper titled, “Sediment organic carbon burial in agriculturally eutrophic impoundments over the last century.” The team included members from Europe, the United States and Canada. The work was sponsored by the National Center for Ecological Analysis and Synthesis and the Iowa Department of Natural Resources.

Downing has presented invited seminars on this research to the International Society of Limnology, the American Society of Limnology and Oceanography, and at several major research institutions in North America and Europe. Most recently, he was invited to discuss his research by the Pond Conservation, a charity in the United Kingdom dedicated to creating and protecting ponds and the wildlife they support. He will spoke today at University College London. An upcoming presentation is scheduled for the annual meeting of the European Pond Conservation Network in Valencia, Spain.

Jeremy Biggs, Pond Conservation director of policy and research, said the research has exciting implications. “It may be that ponds will be the modern equivalent of the swamps that formed coal in the past. But before we all rush into making ponds to trap carbon we need to do some basic research here in the UK. If the rate of carbon uptake in ponds in Europe is the same as that found in the USA study, we may well have discovered an important new natural way of trapping carbon,” he said.

Downing’s ongoing research, partnering with the United States Geological Survey, and his contributions to the Iowa Lakes Survey will investigate the role of small Iowa lakes in the absorption of atmospheric carbon dioxide and other important gases such as methane.

[John Downing @ Iowa State University]

Berkeley Lab has signed a collaboration agreement with Tensilica, Inc. to explore the use of Tensilica’s Xtensa processor cores as the basic building blocks in a massively parallel system design. Tensilica’s Xtensa processor is about 400 times more efficient in floating point operations per watt than the conventional server processor chip shown here.

In a paper published in the May issue of the International Journal of High Performance Computing Applications, Michael Wehner and Lenny Oliker of Berkeley Lab’s Computational Research Division, and John Shalf of the National Energy Research Scientific Computing Center (NERSC) lay out the benefit of a new class of supercomputers for modeling climate conditions and understanding climate change. Using the embedded microprocessor technology used in cell phones, iPods, toaster ovens and most other modern day electronic conveniences, they propose designing a cost-effective machine for running these models and improving climate predictions.

In April, Berkeley Lab signed a collaboration agreement with Tensilica, Inc. to explore such new design concepts for energy-efficient high-performance scientific computer systems. The joint effort is focused on novel processor and systems architectures using large numbers of small processor cores, connected together with optimized links, and tuned to the requirements of highly-parallel applications such as climate modeling.

Understanding how human activity is changing global climate is one of the great scientific challenges of our time. Scientists have tackled this issue by developing climate models that use the historical data of factors that shape the earth’s climate, such as rainfall, hurricanes, sea surface temperatures and carbon dioxide in the atmosphere. One of the greatest challenges in creating these models, however, is to develop accurate cloud simulations.

Although cloud systems have been included in climate models in the past, they lack the details that could improve the accuracy of climate predictions. Wehner, Oliker and Shalf set out to establish a practical estimate for building a supercomputer capable of creating climate models at 1-kilometer (km) scale. A cloud system model at the 1-km scale would provide rich details that are not available from existing models.

To develop a 1-km cloud model, scientists would need a supercomputer that is 1,000 times more powerful than what is available today, the researchers say. But building a supercomputer powerful enough to tackle this problem is a huge challenge.

Historically, supercomputer makers build larger and more powerful systems by increasing the number of conventional microprocessors — usually the same kinds of microprocessors used to build personal computers. Although feasible for building computers large enough to solve many scientific problems, using this approach to build a system capable of modeling clouds at a 1-km scale would cost about $1 billion. The system also would require 200 megawatts of electricity to operate, enough energy to power a small city of 100,000 residents.

In their paper, Towards Ultra-High Resolution models of Climate and Weather, the researchers present a radical alternative that would cost less to build and require less electricity to operate. They conclude that a supercomputer using about 20 million embedded microprocessors would deliver the results and cost $75 million to construct. This “climate computer” would consume less than 4 megawatts of power and achieve a peak performance of 200 petaflops.

“Without such a paradigm shift, power will ultimately limit the scale and performance of future supercomputing systems, and therefore fail to meet the demanding computational needs of important scientific challenges like the climate modeling,” Shalf said.

The researchers arrive at their findings by extrapolating performance data from the Community Atmospheric Model (CAM). CAM, developed at the National Center for Atmospheric Research in Boulder, Colorado, is a series of global atmosphere models commonly used by weather and climate researchers.

The “climate computer” is not merely a concept. Wehner, Oliker and Shalf, along with researchers from UC Berkeley, are working with scientists from Colorado State University to build a prototype system in order to run a new global atmospheric model developed at Colorado State.

“What we have demonstrated is that in the exascale computing regime, it makes more sense to target machine design for specific applications,” Wehner said. “It will be impractical from a cost and power perspective to build general-purpose machines like today’s supercomputers.”

Under the agreement with Tensilica, the team will use Tensilica’s Xtensa LX extensible processor cores as the basic building blocks in a massively parallel system design. Each processor will dissipate a few hundred milliwatts of power, yet deliver billions of floating point operations per second and be programmable using standard programming languages and tools. This equates to an order-of-magnitude improvement in floating point operations per watt, compared to conventional desktop and server processor chips. The small size and low power of these processors allows tight integration at the chip, board and rack level and scaling to millions of processors within a power budget of a few megawatts.

Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California. Visit our Website at www.lbl.gov.

[Ucilia Wang @ DOE/Lawrence Berkeley National Laboratory]

Engineers at Duke University believe that the results of feasibility studies conducted in their laboratory represent the first concrete steps toward achieving this space age vision of the future. Also, on a more immediate level, the technology developed by the engineers could make certain contemporary medical procedures safer for patients, they said.

For their experiments, the engineers started with a rudimentary tabletop robot whose “eyes” used a novel 3-D ultrasound technology developed in the Duke laboratories. An artificial intelligence program served as the robot’s “brain” by taking real-time 3-D information, processing it, and giving the robot specific commands to perform.

“In a number of tasks, the computer was able to direct the robot’s actions,” said Stephen Smith, director of the Duke University Ultrasound Transducer Group and senior member of the research team. “We believe that this is the first proof-of-concept for this approach. Given that we achieved these early results with a rudimentary robot and a basic artificial intelligence program, the technology will advance to the point where robots — without the guidance of the doctor — can someday operate on people.”

The results of a series of experiments on the robot system directing catheters inside synthetic blood vessels was published online in the journal IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. A second study, published in April in the journal Ultrasonic Imaging, demonstrated that the autonomous robot system could successfully perform a simulated needle biopsy.

Advances in ultrasound technology have made these latest experiments possible, the researchers said, by generating detailed, 3-D moving images in real-time.

The Duke laboratory has a long track record of modifying traditional 2-D ultrasound — like that used to image babies in utero — into the more advanced 3-D scans. After inventing the technique in 1991, the team also has shown its utility in developing specialized catheters and endoscopes for real-time imaging of blood vessels in the heart and brain.

In the latest experiment, the robot successfully performed its main task: directing a needle on the end of the robotic arm to touch the tip of another needle within a blood vessel graft. The robot’s needle was guided by a tiny 3-D ultrasound transducer, the “wand” that collects the 3-D images, attached to a catheter commonly used in angioplasty procedures.

“The robot was able to accurately direct needle probes to target needles based on the information sent by the catheter transducer,” said John Whitman, a senior engineering student in Smith’s laboratory and first author on both papers. “The ability of the robot to guide a probe within a vascular graft is a first step toward further testing the system in animal models.”

While the research will continue to refine the ability of robots to perform independent procedures, the new technology could also have more direct and immediate applications.

“Currently, cardiologists doing catheter-based procedures use fluoroscopy, which employs radiation, to guide their actions,” Smith said. “Putting a 3-D ultrasound transducer on the end of the catheter could provide clearer images to the physician and greatly reduce the need for patients to be exposed to radiation.”

In the earlier experiments, the tabletop robot arm successfully touched a needle on the arm to another needle in a water bath. Then it performed a simulated biopsy of a cyst, fashioned out of a liquid-filled balloon in a medium designed to simulate tissue.

“These experiments demonstrated the feasibility of autonomous robots accomplishing simulated tasks under the guidance of 3-D ultrasound, and we believe that it warrants additional study,” Whitman said.

The researchers said that adding this 3-D capability to more powerful and sophisticated surgical robots already in use at many hospitals could hasten the development of autonomous robots that could perform complex procedures on humans.

[Richard Merritt @ Duke University]