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Indevr's Erica Dawson Talks About MChip, An Array-Based Screening Tool for Influenza


Erica Dawson
Research Scientist
Name: Erica Dawson
Title: Research Scientist, Indevr
Professional Background: 2006-present, research scientist, Indevr, Boulder, Colo.; 2003-2006, postdoctoral research associate, University of Colorado, Boulder.
Education: 2003 — PhD, analytical chemistry, University of North Carolina, Chapel Hill; BS, chemistry, Hartwick College, Oneonta, NY.                              

Erica Dawson is the lead author on two recent papers concerning the development of MChip, a microarray-based test created at Kathy Rowlen’s lab at the University of Colorado at Boulder that can be used to identify flu viruses, including avian influenza H5N1.
The first paper, published Nov. 15 in Analytical Chemistry, describes the design and characterization of a low-density microarray for subtyping influenza A, while the second paper, to be published in Analytical Chemistry this month, extends the description of MChip to include H5N1 [ Dawson E et al. MChip: A Tool for Influenza Surveillance. Analytical Chemistry. 2006 Nov 15;78(22):7610-7615.]
According to a statement from CU Boulder, the MChip has several advantages over the FluChip, a flu diagnostic previously developed by the same research team. While the FluChip is based on three influenza genes — hemagglutinin, neuraminidase, and matrix, — the MChip is based solely based on matrix. To learn more about the MChip, BioArray News spoke with Dawson last week.
You are currently employed at Indevr. What is the relationship between the FluChip, the MChip, and Indevr?
All of this work was conducted while I was a postdoctoral research associate in Kathy Rowlen’s lab at the University of Colorado, Boulder. I am the first author on both of the papers that came out.
I am now a research scientist at Indevr, which is a private company in Boulder where Kathy Rowlen is also the chief scientific officer. But the MChip and FluChip technology is wholly owned by the University of Colorado.
Indevr is a small start-up company focused on making instrumentation for the biomedical and diagnostic industries.
So the MChip was a microarray that was developed at the university.
We here at Indevr do a wealth of other things.
I understand that you have two papers out with regards to the MChip.
The first one of those papers details our analysis of a number of human influenza samples and the second one of those papers details our analysis of the Human H5N1 samples.
But what is the difference between the MChip and the FluChip that was developed one year ago?
The first chip we developed was called FluChip 55. This was a chip that targeted three different gene segments of influenza — both the two surface genes that are normally used to subtype the virus as well as an internal gene that we were normally using as an internal control to tell us whether or not influenza A was present.
That chip was developed around three gene segments and some of the difficulty with that [is] a lot of time you have difficulty amplifying all three gene segments and you just don’t get all of the information that you need. And through some of those experiments where we didn’t quite get all of the information, we realized that through these sequences that were designed to be a positive control, we were able to get full subtype information for the virus based on the pattern of hits.
And so this second crop of papers really explores that idea. We went from a three-gene microarray that is more challenging to focusing on a single-gene segment that no one uses to subtype influenza.
Although the chip is very different in that we are sort of inferring the antigenic subtype of the virus from this single, largely internal gene that no one uses to subtype the virus.
Is the MChip meant to complement the FluChip or replace it in use?
Well in many ways …. it is much more advantageous to use a single gene to subtype the virus. It is easier to amplify, and some of the technological challenges go away. But I think ultimately, we envision a chip that has some other functionalities associated with it that would sort of incorporate ideas from both chips.
How is it designed to be used and who would be the optimal user?
The complete assay time for the FluChip as it is now from patient sample through ‘here is an answer’ takes about seven hours. That is much more rapid than the typical sort of gold standard method of doing viral culture — growing the virus and determining what the subtype is through chemistry. That can take up to several days up to two weeks for more unique viruses.
So the first area we really see this chip being useful in is in clinical laboratories, at places like [the] Centers for Disease Control [and Prevention], whom we have an ongoing collaboration with, as well as a lot of these reference laboratories around the world that collect and analyze influenza samples. We would like to see this get used as an alternative by people who have an opportunity to increase and improve worldwide surveillance of influenza viruses.
Now, everyone always asks us, ’When is this going to be in my doctor’s office?’ It’s a great question, but the first thing we have to focus on is getting it in the hands of people that already analyze influenza samples to further validate it. In fact, Kathy Rowlen has started talks with some members of the Indonesian Ministry of Health to actually get a chip in some of their labs in Indonesia where, as you can imagine, many of these outbreaks actually happen.
Our first goal is the clinical lab market, but down the road we would like to see this turned into a more point-of-care type device.
Who is UC Boulder working with to manufacture and distribute the chips?
The only thing I can tell you now is that the university is currently involved in mature negotiations for the specific licensing of the technology to a diagnostics company in the US. We [think] the University of Colorado does not intend to distribute this, except for small-scale applications. We expect that the technology will be licensed and that that will be done by an outside entity.
How do you make the chips?
Basically, what happens is that we spot the chips, we wash them, we employ the standard techniques to spot and amplify the virus, and then apply it to the chip manually. The chips are made in-house and the data processing is done with a standard microarray-scanning instrument.
Are you aware of other companies that have developed microarrays for influenza? For example, CombiMatrix has an influenza chip.
Yes, I am aware of the other technologies. In the case of CombiMatrix’s technology, they are using a very high-density array. That array has 12,000 specific sequences on it. And some of the challenges that go along with that are the increased complexity of having to analyze that data, along with the increased cost of having to put that many sequences on a chip. I think CombiMatrix’s chip sells for about $500 or $600 a piece. The total material cost of our chip is about $10.
We are doing a very low-density chip, where we have at most a few hundred sequences on the chip. But that’s a real major difference.
But if both of you are looking at solving the same problem then why are you coming to different price points and density points?
Well, most of the things people are used to thinking microarrays are for are massively multiplexing thousands of sequences on a chip to do gene-expression analyses. And the way the sequences are designed is a fairly brute force approach: one sequence is used to target one particular strain or gene.
The way we decided to choose sequences was the opposite of that. What we did was design very few sequences that are broadly reactive with a wide range of different but related influenza viruses.
So, for example, on our first generation chip we had five or six sequences that were reactive for all H1 strains of influenza. And just with those five or six sequences, we were able to detect a wide variety of somewhat different H1 viruses. It is just sort of a different approach.
What would be the next logical step for this project?
The next step would be for a diagnostics company to turn this into a clinical assay. I really see this being first a clinical assay, and if we can get this into reference labs around the world, we can do a better job of surveying the influenza virus. In turn, that helps vaccine selection and it can also affect things like quarantine measures.
More long term than that, with improvements in sample processing and data, we would also love to see the time of this assay go down to an hour or less, where this could be a real, viable point-of-care diagnostic.
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