AT A GLANCE
NAME: Sanjeev Krishna
POSITION: Professor of molecular parasitology and medicine, St. George's Hospital Medical School, London, since 2000.
Author on a paper in the April 24 issue of the Lancet describing a panel of biomarkers for African sleeping sickness.
BACKGROUND: Wellcome Trust senior research fellow in clinical science, St. George's Hospital Medical School, 1994-2001.
Researcher in tropical medicine, Wellcome-Mahidol University, Oxford, 1991-93.
Wellcome Clinical Lecturer, John Radcliffe Hospital, Oxford, 1990-94.
DPhil, Oxford University, 1990.
Bachelor of medicine/surgery, Oxford University, 1982.
BA in pathology, Cambridge University, 1979.
How did you get involved with proteomics and biomarker discovery?
A research fellow of mine came in one day to do a journal club, which we do every Wednesday morning — this is a couple years ago — and he pulled out the paper published in the Lancet by Emmanuel Petricoin and colleagues. We discussed it in journal club. It was actually Dan Agranoff who was the research fellow who pulled it out — he’s one of the authors on the paper that we published. The other one in the room was Marios Papadopoulos who was first author on the paper. There were others on the team. We thought about this and we thought, ‘well this does sound like a very exciting technique. We’re infectious disease physicians — what should we think about using this technique for?’ And I had just started becoming interested in sleeping sickness.
Why were you particularly interested in sleeping sickness?
Because it’s one of the world’s most neglected diseases. And [it’s] also one of the world’s most horrible diseases to die from. In tropical diseases, you’ve got a lot of money going into malaria, TB, [and] HIV for example. But sleeping sickness is the poor cousin.
So I just got involved in a project in Angola in sleeping sickness, and I thought that would be an excellent condition in which to consider using some of the approaches that Petricoin had published for ovarian cancer. And we did that.
Why did you think the biomarker discovery method would be appropriate for sleeping sickness in particular?
Sleeping sickness is caused by a single organism. While the disease spectrum that you see can vary clinically, it produces characteristic changes in the pattern of some blood proteins — immuno- globulins, for example. And it’s [also] really because I thought it would be a good model infection to look at. It’s chronic, [and] it’s hard to diagnose. So there’s a real need for a test. And it’s totally neglected.
So you started the research a couple of years ago?
Yes — that’s when we had the idea. And then you know what it’s like — you have to apply for funding, you have to get committee approval, and then develop the technology.
What instrumentation did you use in the study?
It’s a Ciphergen SELDI machine. We have a center here at St. George’s Medical School, which has just been built and opened. It’s called the Biomics center, and it has a lot of equipment which is useful for the sorts of approaches that we were taking, including the Ciphergen SELDI machine.
So you put the samples right on the Ciphergen ProteinChip?
That’s right. It’s a hydrophobic chip. We tried a couple of different chips, and then focused on this particular one, which gave more peaks than some of the other chips. And when you’re starting with a new technique, there’s a lot of playing around. So we did that. Really, it was Marios Papadopoulos who hands-on started to develop this for the conditions that we were interested in.
Where does your funding come from?
Our funding comes from a variety of different sources. We do have some funding from government — the UK equivalent of the NIH, the [Medical Research Council]. But we also have funding from the Wellcome Trust. And we got grants from the World Health Organization, for example. So they’re all competitive, peer-reviewed-type stuff.
So at what point in the project are you now?
We’re doing much larger studies, but also I’ve got it in mind very firmly that we’ve got to take this high-tech technology and start to use it to develop low-tech approaches. [That is,] stuff we can use in places where the patients actually have the disease, like in Angola, where conditions are very difficult.
I think what the proteomic signatures that we’ve got tell us is that there is information there that distinguishes whatever disease state you have from their controls. And if you can do that, the information is there on which to try and use alternative approaches to make the same distinctions.
Yeah, all the usual stuff — the stuff that’s easy to use.
I would not rule out a mass spec-based diagnostic. The technology moves very quickly — the hardware development, the ease of use and so on. So I’m not ruling anything out. All I’m saying is, right now, the approaches that look attractive and appropriate for our use — and I’m talking about the most hostile environment that you can imagine — would be conventional assays that use antibodies and a dipstick of some sort, for example.
Would your group develop the diagnostic, or will you turn it over to a company to do that?
There’s no money in the game that we’re playing. It’s not like cancer, it’s not like other chronic diseases that afflict those of us in Western countries. So we’re going to have to try to do it ourselves, I suspect. But we want funding for it — of course we do.
So you’re doing a larger study now?
It’s done in collaboration with the World Health Organization, and it’s going to a much larger data set. So with this study we had about 85 patients with sleeping sickness and just a few more controls. This would be something that’s probably 10 times as large.
So you get the samples shipped from Africa?
We collaborate — the WHO TDR section has built up a resource of banks of sera which are clinically validated and so on. They’ve done this for TB for example. That’s an invaluable collection of material, precisely for the sorts of questions we’d like to answer and the developments we’d like to make.
So are you thinking of applying this to other diseases?
Oh yes! Diseases that are difficult to diagnose and which are important to diagnose. So obviously we have mentioned TB in the paper. There are a lot of diseases out there that are far from being easily diagnosed. And the diagnosis is just an opening, isn’t it? The methodology is also a way of validating markers [for therapeutic development].
Whom do you collaborate with in Angola?
The work in Angola is done with Angolan doctors, [especially] Paulo Abel of Angotrip, and is done with a German group, [especially] August Stich of Wurzburg, that has been working with Angolan doctors and structures within Angola to actually deliver healthcare to the patients with sleeping sickness. You’ve got to imagine what it’s like. When I first started, the [country] was still in the longest running civil war in Africa — 27 years. There was no infrastructure. The only people who were giving healthcare in these remote areas were a [a few people] from the government organizations, but also NGOs [and] charities.
Given that difficult environment and the serum banks that you use for the samples, how do you deal with the risk of introducing artifacts during sample handling?
The way we have tried to deal with that is, you get samples from geographically different areas, which would go some way to align for systematic ethnic differences. We’ve also done the experiments in the lab to see what [effects] different methods of sample handling have on spectra, and the samples that we’ve collected ourselves have been very rigorously collected and stored and controlled. And then, as with all good science, you’ve got to have the right controls.
When you say sample-handling effects, what do you mean?
How many times you can freeze and thaw [the sample] before you start to lose information, the effects of hemolysis — this sort of stuff.