麻豆淫院

September 22, 2010

Sandia using pathogen detection technology for understanding algal pond collapse

Sandia post-doc Hanyoup Kim gazes through the center of the Automated Molecular Biology Platform used to process complex DNA samples for detecting rare pathogen sequences. Such tools are being used by Sandia researchers to quantify the 鈥渦nknown unknowns鈥 at the root of pond crashes. (Photo by Randy Wong)
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Sandia post-doc Hanyoup Kim gazes through the center of the Automated Molecular Biology Platform used to process complex DNA samples for detecting rare pathogen sequences. Such tools are being used by Sandia researchers to quantify the 鈥渦nknown unknowns鈥 at the root of pond crashes. (Photo by Randy Wong)

(麻豆淫院Org.com) -- Armed with a pathogen detection technology honed through internal investments, as well as a recent $800K grant secured through the Department of Energy's Biomass Program, researchers at Sandia National Laboratories are tackling algal pond collapse, an issue that may be preventing some companies from producing the amount of algae it will take to make algal biofuels a cost-effective form of alternative energy.

Algae are widely viewed as a potential source of , but the technology to mass-produce fuel-grade algae is still in the early stages. A major roadblock is the inability to produce large amounts of the greenish, chlorophyll-containing organisms.

Algae are commonly grown in raceway ponds, large, shallow, artificial ponds that serve as fields for algae crops. But when water is constantly re-used, mixed or blended (a common practice at multi-acre algae production facilities), the ponds are prone to attack by agents such as fungi, viruses or predators like zooplankton.

鈥淭he organisms fall into these ponds and can crash a pond overnight,鈥 said Todd Lane, a molecular biologist and algae researcher at Sandia鈥檚 California site. 鈥淢any of the agents that are causing these pond crashes have not been identified, and you can鈥檛 develop countermeasures without understanding why something is happening.鈥 Pond crashes, Lane said, are often characterized by a sudden emergence of infection followed by rapid loss of algal biomass.

Sandia鈥檚 winning DOE proposal, titled 鈥淧ond Crash Forensics,鈥 will use pathogen detection and characterization technologies developed through the lab鈥檚 Rapid Threat Organism Recognition, or RapTOR, project. RapTOR was originally developed for homeland security purposes.

The RapTOR program seeks to solve the 鈥渦nknown unknowns鈥 problem - lethal agents that could be weaponized from ordinary viruses or disguised to look harmless - by developing a tool to rapidly characterize a biological organism with no pre-existing knowledge. Sandia鈥檚 researchers, Lane says, are taking advantage of rapidly evolving molecular biology technology and the advent of ultra-high-throughput DNA sequencing in order to re-engineer time-intensive benchtop methods to be faster, easier and automated.

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That same tool, he says, can be used to quantify the 鈥渦nknown unknowns鈥 at the root of pond crashes. Sandia鈥檚 researchers will obtain samples of water from 鈥渇reshly鈥 crashed ponds and unaffected ponds grown in parallel at the same facility under similar conditions. They鈥檒l focus on common production strains such as Nannochloropsis and Neochloris in primarily open pond architectures.

Sandia鈥檚 technical approach will combine modern methods of metagenomic analysis, advanced imaging and field microbiology / virology to identify, characterize and, when possible, isolate the agent causing a pond crash.

Sandia's RapTOR technology will tackle the problem of algal pond crashes, which occur in raceway ponds such as this one. (Photo courtesy RFE Renewable Fuel & Energy B.V.)
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Sandia's RapTOR technology will tackle the problem of algal pond crashes, which occur in raceway ponds such as this one. (Photo courtesy RFE Renewable Fuel & Energy B.V.)

The project will also employ Sandia鈥檚 unique capabilities in hyperspectral fluorescence imaging to characterize stress-induced fluctuations in algal photosynthetic pigments in both experimental and field systems. The project鈥檚 first year will focus on the identification and isolation of those agents causing pond crashes, while during the second year of the project researchers will create pond crashes 鈥渙n demand鈥 for laboratory analysis and experimentation leading to countermeasure development.

According to Lane, the goal is to develop a method for rapid characterization of the responsible predatory agents and either a device or service for companies that will help make their algae ponds more productive.

鈥淔or the commercial sector involved in producing , this will save money since those companies will maintain better control over their ponds and experience less impact on their production schedules,鈥 Lane said. 鈥淲e feel that we鈥檙e in a good position to address this particular roadblock. It鈥檚 a good niche for Sandia, and something that allows us to provide a service that will be of great benefit to the algal biofuel industry that will in turn greatly benefit the nation.鈥

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