At A Glance
Name: Yongchang Qiu
Position: Associate director of protein chemistry and proteomics group, Wyeth Research, since 1998.
Background: PhD in pharmaceutical chemistry with Al Burlingame and Leslie Benet, University of California, San Francisco, 1998.
How did you get involved with proteomics?
In the early days when I was at UCSF, I worked with Al Burlingame — he was my supervisor there. I basically started there learning mass spectrometry as well as biology, looking at drug-induced organ toxicity, using 2D gels plus mass spectrometry to look at these active metabolites’ covalent bonding to certain proteins, and basically separating those proteins using 2D gels and radiolabeled drugs as a detection method. We used imaging or film to record the spots that were hot, then used mass spectrometry to identify those spots. So it was very primitive proteomics technology. Everything was new —it was in 1994 or ‘95. So basically I was trained [in proteomics there], but not formally trained that way, because there was no such thing at that moment. Then the program over here [at Wyeth] liked what I did and hired me straight out of school.
Tell me about the group you lead at Wyeth.
The group that I’m leading here is called protein chemistry and proteomics. It’s the only group [doing these things] within discovery and research at Wyeth. We’re focusing on a number of areas. [One is] traditional protein chemistry support like Edman sequencing or individual protein characterization — say you always express those proteins as a target, then you need to characterize [them] looking at the primary structure [characteristics] like phosphorylation, sequence conformation. So this is a small part of what we do. But we’ve transformed into a much larger undertaking right now — so-called proteomics. But when I say proteomics, that’s not necessarily looking at quantitative protein expression changes — there’s a lot more to it, and that’s exactly what we do. So the major areas we’re working on right now is one, functional proteomics — basically the elucidation of protein complexes of interest from the drug development point of view. [That is] any given target that can be a potential target and you want to define its function in vivo — its biology, what pathway it’s involved in. [Our in vivo methods] have some unique advantages compared to other traditional methods like yeast-2-hybrid or other methods that you can’t do in vivo. So we’re using this as a tool for target validation, target prioritization as well as target identification. In some cases, it leads to other proteins of interest. Maybe that protein would be an even better intervention point than the original protein target that we sought for a particular indication.
So this is one of the main things that we do — basically using affinity purification methods [to isolate the protein complex]. To do so, sometimes we have to design a construct with a small tag on it or generate antibodies against the target. Downstream, we have a mass spectrometry-based platform, including automated MDLC as well as downstream software — the search engine as well as the back-end Oracle databases. So [you can] summarize it, analyze it, or even disseminate the data information to your collaborators. It’s a pretty comprehensive integrated system.
What mass spectrometers does your group use?
We have nine mass spectrometers: five ion traps, one conventional MALDI TOF, and a MALDI TOF/TOF. We also have two hybrid quadrupole TOF instruments from two different manufacturers — The Micromass Q-TOF and the [Applied Biosystems] Q-STAR. We also have the linear trap as well from Finnigan.
So what are the other major areas you’re working on?
The second type of analysis that we’ve been doing is more global expression proteomics, where we basically identify and quantify interesting protein mixtures looking at their expression changes in disease versus control or treatment versus non-treatment. And then we use that as a way to discover targets or validate targets, or to really understand the protein pathway — whatever pathway that’s being affected.
The third type of proteomic analysis is epitope mapping. We’re very interested in mapping the interface between two proteins when they bind to each other — in particular, antibody-antigen receptor-ligand interactions, because that has a lot of value in drug development.
There are a lot of other applications where we don’t do [it ourselves] but help [others at Wyeth] as a consultant, such as biomarker discovery, toxicity markers, markers for drug responses, patient selection, things like that. Those are huge undertakings and we have a small group, so resource constraints are the main issues here. I have, including myself, 11 people: Three or four people dedicated [to] protein chemistry support, two molecular biologists — they’re working on specific projects isolating interesting protein complexes using molecular biology or biochemical techniques like tagging — and one software engineer. Then we have the rest of the people basically concentrating on the analytical part, on the instrument and chromatography side.
Can you give me examples of particular projects you’ve worked on?
For example, there is a cytokine called GDF-8, also called myostatin. Knockout of GDF-8 in mice results in significant increase in muscle mass and reduction of fat. You can also inhibit the molecule in adult mice, and the mice will exhibit this double-muscling situation — basically they get really muscular, and fat content goes down. This can be a really useful potential treatment for diseases like muscular dystrophy or diabetes. So the thing is, in order to really block it in humans, you’ve got to confirm that this molecule exists in human blood. And not only that, if you want to generate therapy against it, then you need to know the composition of this complex — does it exist alone as a dimer or does it really bind to something else? Because there is a mechanism in vivo to regulate those molecules, right? They’re tightly regul-ated, otherwise humans are going to be out of control. So we want to know that.
Then we basically used antibodies to purify those complexes and then elucidate the complex successfully. [This was published] in the Journal of Biological Chemistry as well as Molecular Endocrinology. So that’s something that you can’t do using other traditional biochemical methods like yeast-2-hybrid — these are in vivo — we take human blood to do it.
The other example is that we were interested in receptors on the cell surface. Basically we wanted to know ‘what are the molecules that are involved in receptor signaling by pulling out the whole receptor complex?’ So one example would be the lymphotoxin beta receptor. We basically used the ligand — the ligand is called LIGHT — as the bait. LIGHT is expressed as a tagged ligand, and we incubate that molecule with the relevant cell line that expresses the LT beta receptor. So we know it’s really responsive to this ligand. Then we pull out the whole LT beta receptor complex by using this ligand. Then we basically run it on 1D gels and cut every piece of it, and identify all the proteins. Compared to the control experiment, we were able to identify a number of proteins that help us to understand the LT beta apoptotic pathways. That was also published in the Journal of Biological Chemistry last year. We have a number of similar studies that haven’t been published and I’m afraid I can’t talk to you about those.
So what’s was your ultimate goal in that last example?
The ultimate goal would be that by understanding the pathways, if you do want to target these receptors, you would know the further downstream pharmacological consequences. Maybe, for example, some of these receptors are involved in multiple pathways, and maybe you can inhibit one and not the other. Sometimes this is needed in order to avoid the toxicity but get the pharmacological responses that you need. Many of these receptors are involved in multiple pathways and things like that. In many ways you can find new targets that way. To give you another example, we identified the estrogen receptor complex that way as well.
In my opinion, MS-based functional proteomics is a maturing tool now for target identification and validation and prioritization. If you want to do it out of the blue, it’s probably hard because you need to have all those reagents available. But in a pharmaceutical comp-any, if you’re interested in a molecule, those reagents are often already there, because people are interested in the molecule, they’ve expressed it, [and] they have different constructs and all that stuff.
What would you say are some of the differences between academia and industry for a scientist?
In the academic environment, you can do some very interesting studies and publish some very interesting papers, but they can be useless — at least in the short term, from the drug development point of view. For example, when we do these receptor complex studies, even if we do a study and then get the composition and understand some of the things there, if we don’t find a new target or understand the new pathways or things like that related to that particular receptor, I would not call it a huge success. And particularly for proteomics, that’s even more obvious, like expression proteomics and things like that. To actually get a result that can be beneficial — to have a direct impact on drug development —[as opposed to] just getting some proteins that are differentially expressed and publish[ing] it, that’s a totally different story. So I think that there is a certain reality here. People in the pharmaceutical industry would generally be more critical of any proteomics technologies compared to people in academics.