Using Electroactive Bacteria, Students Design Toxin Sensor
News Oct 12, 2012
Cornell University Genetically Engineered Machines (CU GEM) is trying to help the oil industry develop sound environmental safety practices. Bolstered by a $20,000 grant from the Oil Sands Leadership Initiative, the team has designed and built a biosensor that uses the electroactive bacterial species Shewanella oneidensis MR-1 to detect the toxic substances arsenic and naphthalene in water.
They will enter their design in the 2012 iGEM North American East Jamboree competition, Oct. 12-14, at Duquesne University in Pittsburgh.
Abundant in Canada and Russia, oil sand, or tar sand, is a petroleum deposit that requires specialized, energy-intensive refining techniques to extract hydrocarbons from a muddy substance that resembles tar. Left over in this process is a pool of chemicals, called tailings, that are deposited into holding ponds, causing environmental safety concerns due to their potential for leaking into water sources.
The students' device would help refineries monitor levels of potentially hazardous substances in water sources. The technology they are using involves genetic manipulation of S. oneidensis MR-1 to generate direct current output in a whole-cell, autonomous biosensor. Core to the idea is a "biobrick" -- a DNA sequence with a specific biological function -- in which they will link the bacteria's metal-reduction pathway with a promoter protein that is turned on in the presence of either arsenic or naphthalene.
Biosensors today often use fluorescence as their output, which introduces the need for a cumbersome photodiode and the potential for light contamination -- problems that would be eliminated by the students' design.
"Tools currently available for things like detecting naphthalene and arsenic are time consuming and expensive," said Jim Mathew '14, co-team leader of CU GEM. "There is a definite need for a device like this."
Their prototype works by placing Shewanella bacteria into a small bioreactor. Water samples continuously pump into the chamber, and the bacteria's genetic circuitry is turned on only in the presence of the metallic compounds. This causes production of a protein complex that allows the bacteria to create an electric current. A readout of the levels of current are sent to a field station, providing a reliable and continuous monitoring system.
Making the biosensor comes with all kinds of engineering problems, the students said: getting the pumping system to pump at very low, controlled flow rates, finding a robust battery pack light enough to float in water, and making sure the bacteria don't die inside the chambers by providing them with food. What's more, the students concerned themselves with ethical questions -- making sure, for example, that their system would keep genetically modified bacteria from backwashing out of the reactor.
Their goal is not just to prove a concept, but to build a device that actually works and is eventually self-sustaining, added co-team leader Claire Paduano '13.
The interdisciplinary nature of the team, which has 22 members representing almost every engineering major, enables people of different expertise to work together. There's the "wet lab" side -- working with the biological samples, that has to integrate seamlessly with the "dry lab" -- led by co-team leader Dan Levine '14, whose multidisciplinary team is responsible for the design and integration of all electrical and mechanical systems.
Mechanism Controlling Multiple Sclerosis Risk IdentifiedNews
Researchers at Karolinska Institutet have now discovered a new mechanism of a major risk gene for multiple sclerosis (MS) that triggers disease through so-called epigenetic regulation. They also found a protective genetic variant that reduces the risk for MS through the same mechanism.
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.
Ancient Syphilis Genomes Decoded for First TimeNews
Researchers recovered three genomes of the bacterium Treponema pallidum from skeletal remains from colonial-era Mexico, and were able to distinguish the subspecies that causes syphilis from the subspecies that causes yaws. It was not previously thought possible to recover DNA from this bacterium from ancient samples.