The catch in having renewable energy sources is they have to be renewable.
Algae is one of the up and coming potential renewable energy sources, so a suite of complementary technologies is under development to help the industry detect and quickly recover from algal pond crashes, an obstacle to large-scale cultivation for future biofuels, said researchers at Sandia National Laboratories.
The research, which focuses on monitoring and diagnosing algal pond health, draws upon Sandia’s longstanding expertise in microfluidics technology, its strong bioscience research program and significant internal investments.
Because of the way algae grows and ends up produced in most algal ponds, they are prone to attack by fungi, rotifers, viruses or other predators. Consequently, algal pond collapse is a critical issue that companies must solve to produce algal biofuels cost-effectively. The issue was a key component in the Department of Energy’s National Algal Biofuels Technology Roadmap.
Researchers are addressing the algal pond crash issue in three complementary ways:
• Developing a real-time monitoring tool for algal ponds that can detect indications of a problem days in advance of a crash
• Applying pathogen detection and characterization technologies honed through the lab’s Rapid Threat Organism Recognition (RapTOR) work
• Employing its SpinDx diagnostic device to dig deeper into problems after they’ve occurred and help to identify specific biological agents responsible for crashes
One of the ways researchers were able to find any potential problems was to develop an online algal reflectance monitor. Sandia’s Tom Reichardt, a researcher who works in the lab’s remote sensing unit, led development of the monitor through an internally funded project. These instruments typically set up alongside the algal pond and they continuously monitor and analyze the algae’s concentration levels, while examining its photosynthesis and performing other diagnostics.
“In real-time, it will tell you if things are going well with the growth of your algae or whether it’s beginning to show signs of trouble,” said Reichardt. However, while this real-time monitoring will warn pond operators when the ponds are under attack, it may not be able to identify the attacker, he said.
To help pinpoint the problems, a Sandia team led by researcher Todd Lane developed a process to quickly and accurately identify pond crash agents through ultra-high-throughput sequencing using RapTOR.
RapTOR, originally developed for homeland security purposes, is able to solve the “unknown unknowns” problem – lethal agents that could be weapons from ordinary viruses or disguised to look harmless. It was to serve as a tool to rapidly characterize a biological organism with no pre-existing knowledge.
Lane’s team also created a method for creating a field-ready assay for those agents, something that works quickly and is relatively inexpensive. They are applying SpinDx, a device developed by other Sandia/California researchers that can analyze important protein markers and process up to 64 assays from a single sample, all in a matter of minutes.
A Sandia team led by researcher Jeri Timlin, in collaboration with the University of Nebraska’s Van Etten lab, enhanced the RapTOR diagnostics by studying interactions of a certain virus with algal cells. Using hyperspectral imaging, they identified spectroscopic signatures of viral infections arising from changes in algal pigmentation. These signatures potentially could end up being able to provide early detection and subsequent mitigation of viral infections in algal ponds.
“It’s important for the growth of an algal industry to develop a method where algal pond operators can learn immediately when there’s a problem with their ponds from a biological agent standpoint,” Lane said. “It’s equally important that they learn – within a very short period of time, like 24 hours – what specific agent is eating away at their algae, and have a technology available that could develop an assay to combat the agent. Our tools come very close to accomplishing all of those things.
“We couldn’t really do an exhaustive characterization of all of the kinds of agents that could be at the root of pond crashes,” Lane said. “But we confirmed some that had been identified before, and we found some others that weren’t familiar to the research community. The important achievement was to develop the methodology, which hadn’t existed before.”