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U of Minnesota s Edgar Arriaga On Studying the Mitochondrial Proteome


At A Glance

Name: Edgar Arriaga

Position: Associate and assistant professor, department of chemistry, University of Minnesota, since 1998.

Background: Research associate and postdoc, department of chemistry, University of Alberta, 1992-1998.

PhD in analytical chemistry, Dalhousie University, Halifax, Nova Scotia, Canada, 1990.


Mitochondrial researcher Edgar Arriaga chaired a session on subcellular proteomics at last week’s PITTCON conference in Orlando, Fla. ProteoMonitor caught up with Arriaga after the session to find out more about his background and work on the mitochondrial proteome.

How did you end up combining proteomics with organelle research?

The integration of proteomics into my research has been recent. Before, I was an analytical chemist, mainly interested in unique approaches to solving biological problems. We were looking at individual organelles in the laboratory and at some point we realized it was important to understand more about them in terms of their proteomic content, so that’s how we started to get more involved in looking for proteomic strategies and looking for ways to combine proteomic strategies with subcellular analyses.

Where did you do your initial work, before you got into proteomics?

My initial background is in chemical spectroscopy, and then I got some background in electrophysiology and photobiology. These areas led me to bioanalytical separations and laser-induced fluorescence detection, and that led me to organelle analysis, and organelle analysis led me to proteomics.

The initial work in analytical chemistry was at Dalhousie University in Halifax, Nova Scotia, in Canada. The work in electrophysiology and photobiology was at the University of Kansas medical center in Kansas City. The work in bioanalysis separation and laser-induced fluorescence detection was in Edmonton, Alberta, at the University of Alberta. And the work on subcellular analysis, and now the work on subcellular proteomics is at the University of Minnesota.

What got you interested in subcellular components?

What happened was before going to Minnesota, when I was in Alberta, I was working on a project that was related to single-cell analysis. This approach was based on introducing an entire cell inside a capillary, and then fully disrupting the entire cell, so that basically we’re using the contents of the cell in solution. If one starts thinking about that concept, we are totally destroying the information that was originally encoded in the structure of the cell. So what seemed logical to me was finding new techniques that would take into consideration that structural composition of the cells. That’s why we figured that perhaps it was more important to not only analyze the contents of cells, but also analyze them according to the natural distribution that exists in the cells, which would be subcellular analysis.

Why did you decide to hone in on the mitochondria in particular?

Because at that time it seemed to be the simplest organelle to work with, but it’s not the simplest organelle to work with — it’s dynamic, it changes a lot, it varies from tissue to tissue, from cell to cell. It also responds to external stimulus such as oxidative stress, it changes with time, it changes with aging — so it’s not as simple as we thought. We initially thought it was going to be a very well-defined, membrane-bound organelle that was there, and it’s not like that. But that’s why we started to work on the mitochondria.

How did you end up combining proteomics with mitochondria?

One of the unique features of what we have been doing is that we can detect individual mitochondria. So this is the analytical component. The biological question that we wanted to address was related to the coexistence of two types of mitochondria within cells. This coexistence relates to the fact that some mitochondria contain mutations, and some mitochondria are normal — let’s call them normal for now. If there are 1,000 mitochondria in a cell, it is very difficult to figure out by any conventional techniques how to distinguish between the properties of the normal and the mutated mitochondria in the cell. So the way, or the approach that we thought we could use is to look at them one by one, and to see if we can separate them based on their mutation content, and then do a proteomic characterization after that separation. So it was important first to find a way of separating them, and then do the proteomic analysis on the two fractions so we can understand what the difference is between the proteomic content of the two kinds of mitochondria.

What is the clinical significance of mutated versus wild-type mitochondria?

The most straight-forward implication is that a lot of the age-related diseases contain mutated mitrochondrial DNA, or mutated mitochondria. For example, there is a disease called Lebers’ disease, and a lot of myopathies that are related to mutated mitochondria. If you check the databases, there are at least 300 diseases that are related to mutated mitochondrial DNA, and almost all of these mutations and diseases have similar features that one would see when people get old. So it has been postulated that a lot of these mutations are present in tissues of aged people, or aged animals. The implications are then for disease or age-related studies.

One of our first goals would be to be able to have reliable techniques that distinguish between a normal proteome and a mutated proteome, or a proteome that is associated with mutated mitochondria.

How far have you gotten in characterizing the differences between mutated and wild-type mitochondria?

We have got as far as characterizing differences in abundances of proteins that are highly expressed in mutated and wild-type mitochondrial DNA. The main difficulty is we have not done it with perfectly sorted mitochondria yet. Because what we have been doing to develop the techniques is to use an artificial cell line — a cybrid cell line — that contains a well-defined composition of mutated and wild-type mitochondria. Using these cell lines — they come from a collaborator, Carlos Moraes at the University of Florida — they have say 60 percent mutated mitochondrial DNA, and the other 40 percent is normal mitochondrial DNA. So if you compare that cell line with the original cell line that is 100 percent normal mitochondrial DNA, then we can start looking at the profile differences and similarities. And using iTRAQ technology, that is similar to ICAT technology, then it’s possible to start looking at differences in abundances between the proteins that are being detected. And if there are several peptides that are used to ID the protein, then it’s possible to assign an error and to determine if the difference is a significant difference or not.

That’s as far as we have gone as far as comparing the proteomes of the mutated and normal mitochondria.

What categories of proteins are different between the two types of mitochondria? Are they age-related proteins?

They are not per say clearly-defined age-related proteins. The proteins that are believed to be age related are usually related because of their mechanism — how they actually function within the cell. A lot of them have receptor mechanisms. The proteins could also be age related because they are subject to damage that happens with age, such as the damage caused by reactive oxygen species. In this particular project, we have not investigated the presence of damage with aging. What we have been seeing in this particular pool of proteins that we have identified are proteins that are related to oxidative phosphorylation, and also the mitochondrial machinery that are related to oxidative phosphorylation. So those are the main two types of families that we see that are being differentially affected by the presence of mutations.

I think that the proteins we’re seeing are more or less expected — they have to do with the respiration of mitochondria and oxidative phosphorylation, so I think it’s not that surprising that we saw that. I think what’s going to be very important is to be able to fully differentiate between totally mutated and totally normal mitochondrial DNA, so we can have a very clear and simple picture of what the difference is.

All of this is very preliminary — it’s something that needs to be more fully refined.

What are some of the things you’re looking to do in the future, and some of the ultimate goals you hope to accomplish?

The ultimate goal is probably beyond my scope, but ultimately all this research we hope is going to help us understand better what is happening when we age so that people have a better life. We don’t want people to live forever, but we want people to have a good time until they are old and it’s time to go.

Within our own research, we want to determine what are the proteins that are being affected or differentially expressed as we age, and to find out are they related to changes in mitochondria? Are they changing because mitochondria stop functioning? Or are they really changing because other factors that we still don’t understand are changing? It’s going to be a difficult task because working with mixtures is not the same as working with a purely homogeneous substance, and mitochondria are more complex than substances.

A final thought — it’s really important to develop techniques that allow us to elucidate these biological problems, as opposed to having a conformist attitude of saying, ‘This is what the techniques can do, and this is as far as we can go in understanding science.’


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