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Purdue Researchers Develop Cell-Based Biosensor for Rapid, Onsite Tox Testing

Researchers at Purdue University have developed a cell-based biosensor technology that they said can screen thousands of samples of food or water for pathogenic Listeria or Bacillus in one to two hours. 
The multi-well plate-based biosensor contains a murine B-lymphocyte hybridoma, called Ped-2E9, that was encapsulated in a type I collagen matrix. The biosensor detected viable cells of pathogenic Listeria, the toxin listeriolysin O, and enterotoxin from the Bacillus organism. The sensor colorimetrically measured the alkaline phosphatase released from infected Ped-2E9 cells.
The investigators reported that pathogenic L. monocytogenes cells and toxin preparations from L. monocytogenes or B. cereus showed cytotoxicity ranging from 24 to 98 percent three to six hours post infection. However, nonpathopgenic L. innocua and B. subtilis induced minimal cytotoxicity, ranging from 0.4 to 7 percent.
Using laser scanning cytometry and cryo-nano scanning electron microscopy, the scientists confirmed the viability of the infected Ped-2E9 cells in the gel matrix.
Their work was published in the February issue of Laboratory Investigation.
Arun Bhunia, a professor of molecular food microbiology in the Department of Food Science at Purdue, spoke with CBA News recently about the assay, its applicability to testing pathogens in human cell lines, and its potential use in the food industry and as a weapon for fighting bioterrorism.  
How does this assay work?
We started with mammalian cells, in this case, a mouse cell line. In general, many pathogens produce toxins, and some of those toxins are capable of killing mammalian cells.
We grew the cells in 96-well plates and immobilized them in a collagen matrix, essentially to hold them in place so we could expose the cells to bacteria or toxin. Those toxins are going to cause damage to the cells.
One desirable property of these cells is that they have a large amount of an intracellular enzyme, called alkaline phosphatase. As soon as the cell membrane is damaged due to exposure to the toxin, the enzyme is released.
We added an ALP liquid substrate that is broken down by the enzyme to produce a color change. So if you observe a color change, you know that you have got some harmful agents in your sample.
The amount of toxin present directly correlates with the intensity of the color change observed. That change can be monitored by the naked eye, by comparison to standardized controls. You could also use a spectrophotometer to help you to quantify cytotoxicity.
What we were able to do was put this assay in a 96-well format, so that it could be used for rapid, on-site testing, for example for testing in a food science laboratory or a clinical setting. All you need is conventional laboratory equipment, and you can have answers in one to two hours.
In addition, the mammalian cell lines we are using happen to be more sensitive to the types of toxins we are testing, so the signal we get is very strong and observed very quickly. If you want to use a different type of cell, the signal may not be as strong.
Have you ever used this screen with human cell lines?
Yes, in the past we have used human cell lines. It works just as well. You get a similar response. We used human cells several years ago, however.
People may want to test cells’ response to different types of toxins. They could also do that using a cell-based biosensor.
Basically, researchers can adapt this technology to suit their own purposes. We are interested primarily in the food-borne pathogens, so that is where we started using this assay with Listeria monocytogenes and Bacillus cereus.
When did your group start doing this work?
This work goes back to the early ‘90s, when I was working as a postdoc at the University of Arkansas. I was looking at bacterial interaction with B-lymphocytes, while doing a different experiment. The B-lymphocytes we were using were supposed to produce antibodies, and I was looking to see if the cells producing antibodies can bind or interact with bacteria.
What I found out was that when we were using a pathogenic bacteria, it killed the B-lymphocytes, and when we were using nonpathogenic bacteria, it did not kill them.
So that was an accidental discovery, it was not part of the research. Since we found the potential application of these cells, we have now reached a point where we think we can use this cell-based biosensor assay in different configurations.
The goal is to come up with a kit or test method, along with the materials, that one can use on-site.
Do you have plans to commercialize this assay as a kit?   
It would be nice. Since we are in an academic setting, it limits how far we can go with this technology, unless some company wants to step in and market it.
I would say it definitely has commercial potential, but I am not in a position to pursue that at this time. Maybe some day, however, we will reach a point where it would be advantageous for a commercial company to manufacture and market it.
That would be the ultimate goal. Challenges such as keeping the mammalian cells viable for a long time must still be met, however.  
Is there a potential customer for this biosensor assay?  
The government, food processors, or the food industry could use it to test samples on-site. It all depends on whether the organization or agency in question does their own testing. If they plan to do in-house testing, they could potentially use it.
Cell-based biosensor assays could be expanded to clinical settings as well.
Does this have potential applications for fighting bioterrorism?
It is possible, yes. The platform and cells we are using can look for a pretty broad spectrum of toxins. Many times you do not know what you are looking for.
The first thing you want to know is if any hazardous materials or pathogens are present in your food or water samples. If the initial tests are positive, you can do subsequent tests to identify the specific pathogen.

So we would like to see this type of application, where you get a broad-based response to see if any pathogens are present in your samples.

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