Name: Martin Grumet
Position: Professor, cell biology/neuroscience, Rutgers University; director, WM Keck Center for Collaborative Neuroscience
Background: Associate professor, New York University 1990-2000
Assistant professor, Rockefeller University 1984-1990
PhD, Rockefeller University 1980-1984
PhD, biophysics, Johns Hopkins University 1980
BS, physics, Cooper Union 1976
Name: Ron Hart
Position: Professor, cell biology/neuroscience, Rutgers University
Background: Assistant professor, Rutgers University 1985-1996
Postdoc, Rockefeller University 1981-1985
PhD, molecular biology, University of Michigan Medical School 1981
BS, biology, University of Connecticut 1977
Though they both had stints as postdoctoral fellows at Rockefeller University, it wasn't until they landed at Rutgers University's cell biology and neuroscience department that Martin Grumet and Ron Hart met.
Now they are collaborating on a National Institutes of Health-funded project to explore the expression and function of microRNAs in neural stem cells with the hopes of uncovering how these small non-coding RNAs affect neuronal and glial cell development.
Recently, Grumet and Hart took time to speak with RNAi News about the effort.
Let's start with the lab and the focus.
MG: I'm currently director of the WM Keck Center for Collaborative Neuroscience, and one of the things we focus on at the center is spinal cord injury. At the same time, I've been focusing a lot on stem cells because we think they will be very useful therapeutically for spinal cord injury.
I came to RNAi from the point of view of being interested in studying the development of stem cells, how to turn them into neural stem cells, [and] how to make those neural stem cells take on certain functions.
Ron [Hart] is coming at it from a different point of view. He has a long history of experience in molecular biology and RNA, and he has been developing reagents and technology to study RNAs and microRNAs.
In the course of studying stem cells, when did you start to think that microRNAs would be playing a role?
MG: Ron has been starting the microRNA work over the last couple of years. It became very interesting right away to look at microRNAs because of their potential as master regulators of RNAs, and as soon as the first papers came out on RNAi controlling development, even in worms and lower organisms, we started to predict that you'd see the same types of things in mammalian cells.
After working for a couple of months, we started to gain evidence that there are microRNAs and they do have interesting properties. One of the things that was very useful was, in our stem cell work we devised cells that give rise to neurons … and [ones that] give rise to glia the two major types of cells in the nervous system. When we get a microRNA comparison between those, it was really striking that there were differences in certain microRNAs it was like day and night between the two cell lines.
Once we started to see that, we realized that this might be a great way to analyze differences between closely related cells, [see] how they change with differentiation, and [see] how the microRNAs change.
Where are you at this point?
MG: [The work involves] two closely related neural stem cell lines [that] express different patterns of certain microRNAs. Those microRNAs change in different patterns as the neural or glial cells differentiate.
In terms of the application of the technology, we're doing this on cells we can grow in the lab, but Ron Hart has also developed technology to use laser capture, and he's been able to laser capture as few as 30 cells [for] microRNA analysis. There are regions in the developing brain that are near one another but give rise to very different types of cells. Part of what we propose in the [NIH] grant is … using laser capture to look at the microRNAs in one region versus the microRNAs in an adjacent region, and that might provide us with a signature for the different types of cells, as well as some ideas about how they were going to develop and develop differently over time.
Could you give some detail about the laser capture technology?
RH: We use the PALM/Zeiss system. It's a second-generation system that seems to be a little more accurate at selecting than the initial Arcturus systems that we looked at. We worked out amplification strategies for messenger RNA some time ago, and worked very hard on that. We've been working very closely with a group at Genisphere on amplification strategies and on microRNA-detection strategies. Working with them, we've modified their amplification system to be able to amplify microRNAs, as well.
That seems to be working well, but it's very much in the experimental stage.
How do you approach microRNA analysis?
RH: We developed a chip that was based on an algorithm we designed to balance melting temperatures and sequence conservation among microRNAs. We developed the chip and the design algorithm, and Genisphere developed a labeling system that requires no nucleic acid amplification, but is instead a signal-amplification system that is very sensitive.
That we've just licensed to Invitrogen, and they've started to sell it as their N-Code arrays.
Can you give a breakdown of how you plan to do the microRNA research the steps involved?
MG: One line of research will be to work with the clones of cells we made from the neural stem cells. We can isolate large amounts of messenger RNA and microRNAs from those cells. We've started to look at expression of the messenger RNAs and microRNAs. We're doing correlations to see which messenger RNAs negatively correlate to which microRNAs because the microRNAs, by one of several mechanisms, cause either the messenger RNAs to be degraded or not be translated. We're also beginning to consider doing 2D gels to look at the proteins that differ in the different cells.
So one approach is starting from the cells in culture that are models for different types of neural stem cells. The other approach will be to go to the embryos and capture cells from different regions, look at their microRNAs and RNAs to see how closely they match different types of cells we have and can grow in culture, and use that as a way to bridge between the culture models we have and what we can laser capture from small numbers of cells in vivo.
Is the idea that you guys want to find what microRNAs are at play, or take it one step further and use it as a point of intervention to treat disease?
MG: Ron is starting to design ways of interfering with the microRNAs, and we want to … use siRNA to knock down microRNAs. We should therefore be able to change cell phenotype and cell function. He's in the process of trying to validate those approaches, and we should be applying those approaches pretty soon.
RH: There've been a number of labs that have used the 2' O-methyl modified RNA that acts like an antisense on the microRNA. We have tried it to make sure we were able to get it to work and it looks like it is. But we certainly didn't develop that it was out there in the literature.
We've [also] worked on a couple of strategies for controlled over-expression of microRNAs. Originally, we just transfected in a precursor we bought from Ambion, but now we've got clones we've built and clones we've modified from Invitrogen to more efficiently control increased microRNA expression in a particular cell type also.
All this is being done in mice and rats?
RH: It's primarily in rats and rat cells, but we've done some work in parallel in mice as well. Our goal, of course, is that we get the rodent cells to tell us all the tricks [and] then turn our attention immediately to human cells, which are available to us.
[Right now,] we've finished a thorough mapping of neurogenesis and gliagenesis using the cell lines that [Grumet's] group developed. We want to go in with the laser capture system to confirm that the cell lines reflect true cortical development in vivo. We just stated that work and it should go very quickly.
At the same time, we've mapped messenger RNAs using the new Applied Biosystems microarrays. What that has done has allowed us to correlate microRNA levels and mRNA levels during changing differentiation, and that gives us computational predictions of genes regulating microRNAs and microRNAs regulating genes, basically.