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Amgen s Sumedha Jayasena on RNAi at the World s Biggest Biotech

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Name: Sumedha Jayasena

Position: Amgen, Research Scientist

Background: Gilead Sciences, director of proteomics — 1999; NeXstar, director of infectious diseases — 1995-1999; Nexagen, senior scientist — 1992-1995; PhD, biochemistry, Lehigh University — 1987; BS, chemistry, University of Colombo — 1983

Sumedha Jayasena currently works as a research scientist for Amgen, the world’s largest biotechnology company. Like most other big drugmakers, Amgen is using RNA interference to help it identify and validate drug targets, all the while keeping its eye on the direction the nascent technology is headed, if not actually exploring alternative uses. Jayasena recently took time to speak to RNAi News about how Amgen uses RNAi and possible applications of the technology down the road.

How did you first get started in RNAi?

In the year 2001, I was reading about what was going on in plants, and then I stumbled upon this paper by Bartel and Sharp … where they described the generation of short interfering RNA in Drosophila extracts. So I thought, since it’s present in Drosophila it should be found in mammals.

We were doing antisense research at that time for target validation and we had the platform already established. So what we did was take synthetic double-stranded RNA against three or four sites that we knew antisense oligos worked against a particular gene. Then, we transfected these molecules and in came the results — I think two sites were quite successful, but the other two sites didn’t work.

During that time I saw the [Nature] paper from [Thomas] Tuschl.

Can you talk a little bit about how RNAi is used at Amgen?

We are using RNAi technology for target validation, mainly in tissue cultures.

It’s very successful. There are difficult genes, but overall it’s very successful.

In terms of difficult genes or overall difficulties using the technology, what are some of the particular issues?

We have run into two genes … that have been difficult to have a successful knockdown in — more than 50 percent. So, we want to look at why these two genes are behaving differently. It could be an issue of compartmentalization of the message, restricting the access, or a technical issue. We don’t know.

Is Amgen looking into RNAi as therapeutics?

At the moment, no. We are basically applying this as a target validation tool. But Amgen is pretty open-minded and Amgen embraces new technologies.

Is it something that’s been on the table at Amgen — talking about possibly looking into or striking a collaboration?

Anything is possible, just like [with] any other big pharmaceutical company.

Amgen uses microRNAs to help its design of siRNAs. Could you talk a little about this?

Early on, in late 2001 or the beginning of 2002, we noticed that certain genes are easy to knock down and certain genes are more difficult. Difficult not in the sense of the two genes I mentioned, but in general by random choice of siRNA design. Then, we were wondering why — there’s no correlation between GC content of the mRNA and siRNA.

The best way to get some kind of handle on productive siRNA is to look in nature, what nature has done. At that time, three papers appeared in Science describing microRNA discovery, and we knew that they were also going through the Dicer processing and part of the RNAi pathway.

In detail, these two pathways may be different but it seems like they are identical. So we thought: well, Dicer is processing these molecules and they become functional — that’s why over millions of years these molecules are still present in highly developed organisms. So we thought we should look into these microRNA molecules and see whether we can [use them] to design siRNA molecules.

This is primarily what we use [to design siRNAs].

Are there any RNAi questions that you’d be interested in tackling in the future?

Yeah. Off-target effects are one of the most important things that we want to look into — what contributes and how to prevent [them]. By preventing the sense strand from becoming associated with the RISC complex, you can get 50 percent of the off- target effects taken care of. If there is the possibility of both strands being able to contribute to off-target effects, then having a good homology search, we’ll eliminate the potential [that] siRNAs have … to bind to other targets.

The problem becomes, now that it’s been demonstrated that you don’t need to have the mRNA cleavage to have protein knockdown — it goes along with the microRNA mechanism of action. Then, what kinds of mutations can be tolerated and still give a nice protein knockdown.

What kinds of approaches will be used to overcome these issues?

Chemical modifications will be the straightforward approach. … If you look at what has been published for chemical modifications based on antisense work and ribozymes and aptamers — all of these modifications will be useful to look into, but you have to screen out the modifications that won’t be acceptable for RISC. That may not be acceptable for RISC on the antisense strand, but on the sense strand it may be what we are looking for. …

Also, the identification of players within the RISC like helicase and other molecules. If you know the substrate specificities of, for example helicase, then you can design siRNAs so that the modifications can be placed in one end, not the other end — that would facilitate the preferred substrate for the helicase.

In terms of where the technology is going, some people have ambitious ideas. Where do you see …

I will take a very cautious attitude in that, because [RNAi] is going to hit the delivery issue when it comes to the siRNA becoming a therapeutic molecule. That will be most likely shared with what has been going on in the antisense field.

With two strands, there are good things and bad things — you can use one strand to decorate things so that a double-stranded molecule can be taken into cells rapidly. Then there should be a mechanism to get rid of them, whatever the decoration you put in, once it is in the cell.

So, delivery is a big issue [and] if someone can solve the issue, that’s going to be a huge breakthrough in the area for therapeutics.

People in the past … who have worked in ribozymes, in antisense did not pay very much attention to the delivery issue. They’ve missed the boat. But in this case, I think, everyone is focusing on delivery, because everything else [appears in order] — if you look at the efficacy, it’s there if you can deliver this molecule into the cell.

So efficacy is not an issue. Specificity may be an issue, but you can be smart enough to make siRNA molecules specific.

Then, in the application side for target validation, transgenic is going to be a huge [area]. That will slow down knockout animals. Most experiments can be done in tissue culture cells, with knockdown cell lines with RNAi. So, that may alleviate the burden of creating knockout [animals]. Knockout takes some time, certainly longer than [the time] an RNAi experiment can be done in tissue culture cells.

But, to give the credit to many people who have been working in the knockout area, they have also made technical advances, quantum leaps, in making knockouts faster.

So, lenti-mediate transgenics — putting this siRNA into lenti-vectors and creating transgenics — is a huge thing for target validation.

Is that something that’s going on at Amgen?

We are exploring all possibilities, without going into details.

Applications [may include] creating mosquitoes that are resistant to malaria by expressing siRNA against vital genes of the plasmodium. … There are a lot of other [uses]: pest-control, making transgenic plants that are resistant to being infected by pests. …

Then the microRNAs — they are just the tip of the iceberg. That’s going to be big for the future — by knowing what microRNA molecules are expressed in different pathogenic tissues versus normal tissue, that will pave the way for early diagnostics for a lot of diseases. By believing that microRNAs are involved in gene regulation, not only in the development stages but also in differentiated cells, then if you take a cancer tissue and look at the microRNA population, it should be different from normal tissue. By creating arrays for microRNAs, its going to be the future for diagnostics at the molecular level.

These are huge applications, but it takes time to come into reality.

It’s a no-brainer. It’s known that microRNAs are implicated in development, and we’re beginning to see that there are differences between normal and pathogenic tissue. …

But it’s a huge effort, and these kinds of efforts should be taken by NIH and NCI so that these chips and these validations can be done and be accessible to the public.

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