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Harvard s Kenneth Kosik On RNAi and the Emergence of MicroRNAs

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At A Glance

Name: Kenneth Kosik

Position: Professor of Neurology and neuroscience, Harvard Medical School

Background: Associate professor, neurology, Harvard Medical School — 1988-1996; Assistant professor, neurology, Harvard Medical School — 1985-1988; Postdoc, McLean Hospital — 1980-1982; Medical residency, neurology, Tufts University — 1977-1980; MD, Medical College of Pennsylvania — 1976; BA/MA, English literature, Case Western Reserve University — 1972

Despite having received degrees in English literature, Kenneth Kosik was pulled by a strong interest in the life sciences to shift the course of his education toward medicine. After receiving his MD and completing his residency work, Kosik ended up teaching medicine rather than practicing it, and is now a full professor at Harvard Medical School.

Recently, Kosik spoke with RNAi News about his work and how it relates to RNA interference.

How did you get involved with RNAi?

I came from several directions to RNAi. One is that my lab is very, very oriented toward neurobiology. Almost all the work we do is with various neuronal systems, neuronal cultures — a number of different questions that range from issues related to neurodegeneration all the way to more fundamental questions like neural plasticity.

I’ve been doing that for years, and clearly, when RNAi burst on the scene, it was something that we longed to do in neurons, as well. However, it was generally believed, at that time — we’re not talking very long ago, just maybe two years ago — that neurons somehow did not have an RNAi processing system or that they were resistant; neurons seemed like a very problematic target.

But the technique is just so extraordinary that we thought we would give it a try. In my lab, a very talented postdoc named Anna Krichevsky worked out a technique to deliver siRNAs to neurons in culture. That was a small paper we did in PNAS.

So, that really whetted the appetite, and we really wanted to then think, now that we could deliver them, [of] some of the interesting directions to go in. Among the various neurological diseases, I’ve had a very long-standing interest in Alzheimer’s disease. A very large portion of my work over the years has been related to Alzheimer’s

It’s widely acknowledged in the field that a particular enzyme, BACE, technically BACE-1, is an extremely good target [for Alzheimer’s disease] — this is acknowledged by the pharmaceutical industry, by academics, [and] it’s something that is really considered really excellent because it’s an enzyme that cleaves the parent molecule to form [amyloid-beta peptide] and it does it quite specifically; if you knock it out, the animal has almost no phenotype, really minimal phenotype, so it seems like it’s something that an organism could tolerate being suppressed, and it’s clearly going have effects on reducing Abeta, which should impact the disease.

But there’s one huge sticking point, and that’s that the approach of most of the industry, when they identify an excellent target, is to search for small molecule inhibitors. As attractive as [BACE] is as a biological target, it is not particularly druggable. The reasons for that are two: One is that its structure is very open, so to get small molecules to the active site is difficult. The second is that it has a very close ortholog called BACE-2 [and] if you inhibit that, you actually increase the Abeta.

So, the design of small molecules that would be specific for one enzyme over another one [when both] are structurally so similar would be very, very difficult. Therefore, it makes a difficult small molecule target.

On the other hand, it makes an ideal RNAi target because you don’t have to worry about the protein structure and you can design RNAis that are specific for BACE-1 but not for BACE-2. That’s been our approach, and our work in that area has now been recently published in the JBC, showing that certain siRNAs show efficacy in neuronal culture — by efficacy I mean that they not only lower BACE-1 and lower it specifically, but they also reduce the amount of Abeta. I think this looks like it’s on the right track.

That was in vitro work. So, what’s going on right now? Have you moved into animals?

That’s what we’re doing as we speak; we’re moving the particular siRNAs that we found to be effective into a number of different delivery vehicles to try to get efficacy in animals. There are some very good animals for Alzheimer’s disease that we’re using.

These are [mouse] models in which the parent molecule for the Abeta that’s called APP, or the amyloid precursor protein, is over-expressed. Those animals go on to get the senile plaques; they have elevated Abeta levels; they have behavioral problems — we have a whole repertoire of phenomena that can be tested to show improvement with the RNAi: Is there a reduction in the Abeta? Is there a reduction in plaques? Is there an effect on behavior? There’s a lot of very potent readouts.

What sort of delivery vehicles are you looking at?

Mostly viral, but we have some other interesting directions [to go in]. For the most part, we’re thinking now that we first want to demonstrate efficacy using viral delivery methods.

Is there anything particular about viral vectors that make them appealing, or is there anything about them that makes you think that, in the long run, you’ll have to use something else?

I think, in the long run, we may have to go somewhere else, but I say that while at the same time thinking that viral vectors may take us quite a distance — some of these introductions of genes with viral vectors in cells that are undergoing mitosis could be problematic. But remember, the neuron is a post-mitotic cell and you may therefore circumvent the problem of any kind of malignant transformation that you have in other types of gene therapy.

So, I think that while everybody would rather swallow a pill than get a virus, I think the viruses can take us quite a distance.

[When you spoke] at the BIO-CEO conference, you got a good response from the industry people there (see RNAi News, 2/27/2004). Are you in discussions, at this point, with anybody about collaborations?

Yeah. Almost everyone on the panel has been [contacting me]. We’ve been talking to a number of companies on the panel from that meeting.

Still early-stage kinds of discussions?

That’s right.

What about other aspects of your work? Is there anything else that RNAi has extended into?

The other thing that we’ve very interested in — which is the other half of this field that has gotten a little bit less attention from industry so far, but has absolutely captivated academics and will soon be of interest to industry — are the microRNAs. As you know, [these] you might think of as the biological counterpart to everything that we’re talking about here — the very small non-coding transcripts that are quite abundant in the genome. They represent an entire new cluster of interesting targets for a number of conditions.

This whole field is going to have another area it’s going to give birth to — that is, the microRNAs as targets for certain conditions.

Have you begun work with microRNAs?

We sure have. We recently published the first array of all the microRNAs. What I mean by that is that we took a large number of microRNAs that are in the database — their sequences are known, but their targets and functions are unknown — and we spotted them all on a nylon filter and then used that as an array the same why you would use an array to look at the transcriptome from messenger RNAs.

But this is a very specialized array with only microRNAs and this was extremely revealing. The first thing that fell out of this study was how highly regulated many of the micro[RNAs] are as cells pass through different stages of differentiation. We saw extraordinary changes in the level of expression of microRNAs during brain development, for instance. This work was also published recently in a journal called RNA.

What sort of ongoing projects do you have in this area?

We’ve identified some clusters of microRNAs that are expressed in certain cells and we’re looking at how we can manipulate their expression to actually drive cells in certain directions.

You said that the microRNA hasn’t gotten much interest from industry. What will it take?

I think it will take the recognition of some work that, for instance, is already out there in the public domain. I’ll give you an example: There was a beautiful paper recently published in Science by Harvey Lodish and David Bartel showing that they can use microRNAs to drive hematopoietic stem cells along certain lineages. It’s increasing awareness of work like that that will capture the attention of industry.

 

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