Tip of the Week: MitoCheck, a human functional genomics database
As much as I love computational aspects of biology, there are times when the sort of flat and binary nature of the discipline leaves me craving some more three-dimensional, real live cellular work. My background was in cell biology and microtubule-associated proteins before I moved to the computational side of biology. And there are days when I would love to see more linkage between the digital and the dimensional. And days when I’d love to look around in the scope at mitosis and mitotic spindles again.
Today I saw it. And I’m going to show you where. We’ll be looking at the MitoCheck database. Below I’ll offer some discussion of the associated research papers, and in the movie I’ll show you how to navigate around the MitoCheck site a bit to find their data online.
It was actually coverage on the BBC* that tipped me off to this resource. And then I went looking for more. A press release on the work provided details and links. And then the Nature News article added additional information.
In short, this group of researchers used a couple of different genomics approaches to examine what happens to HeLa cells when you mess with the mitotic apparatus and processes. They transform cells with either RNA interference constructs, or GFP-tagged proteins, and film what happens to the cells over time. They analyze the movies, and make all this data available in the MitoCheck resource. As we say here in Boston–this is wicked cool.
But now, on to the papers: these researchers have 2 articles out that talk about the work, one focused more on the RNAi approach, and a separate one on the tagged proteins. I’ll address them separately below.
RNA interference experiments:
In this series of experiments, the MitoCheck team started with over 20,000 protein coding genes in humans, transformed HeLa cells with the siRNAs, and let the cells divide over a couple of days. The nuclei of the cells could be illuminated by a GFP-histone protein that they had already placed in the cells. They could light up the cells and film them, and monitor whether cell division looked normal or not. They were able to identify a number of cases where things were going awry. And they were going wrong in various ways. Sometimes there was cell death. Other times they could see a variety of phenotypes such as delayed mitosis, binuclear, poly-lobed, or “grape” looking aberrations. Some cells were too large. These could all be categorized, and compared, quantified, and are now stored as movies, processed data, and phenotypic assignment in the MitoCheck database.
I have some minor concerns about how knocked-down the transcripts are–they say that the values of the target mRNAs drop a lot, but these numbers vary quite a bit (the amount of supplemental data with the paper is excruciating….). It’s also hard to be sure what that means for the protein levels at this point. Also, HeLa cells have some characteristics that may not be average. But that said–as a general method and a hunting license to find genes to assess in more detail, I think this is a very excellent strategy. If I was still in the lab, I’d try the same thing with the cell system I used to study: C2C12 cells for muscle development. You could track whether cell fusion and myotube formation was disrupted….man, sometimes I do crave the lab still….
Tagged protein experiments:
In a second paper from the research teams, they use a similar strategy of monitoring the behavior of cells during mitosis via movies. But this time instead of knocking down a gene, they put a GFP tag on some selected proteins (mostly mouse proteins) that they put into the HeLa cells. These are stably-transfected tagged proteins on BACs, and they call this BAC TransgeneOmics (ahem, another -omics?). They look for where these proteins end up in dividing cells. Again, they have movies of this available now in their database. They also pull down protein complexes and look at them in more detail with other techniques.
Again, I have minor questions about the approach: mouse proteins in HeLa cells, and the bulky GFP tag affecting interactions, expression levels, etc. But again, as a hunting-license sort of effort, I think this is a very neat way to move downstream from digital genomics to real cells. And it’s worth it. The team demonstrates that you can begin to characterize the functions of unknown proteins with this strategy.
So, for this week’s tip of the week I show you MitoCheck. I’ll show how to access this data so you can take it further if you like. One technical note: I did have all of the issues that they talked about in their “troubleshooting” document (PDF) on my Windows machine. I had to do all 4 of the things they recommend in there to get the movies to run. FYI.
MitoCheck site: http://mitocheck.org/
Nature paper with RNAi data:
Neumann, B., Walter, T., Hériché, J., Bulkescher, J., Erfle, H., Conrad, C., Rogers, P., Poser, I., Held, M., Liebel, U., Cetin, C., Sieckmann, F., Pau, G., Kabbe, R., Wünsche, A., Satagopam, V., Schmitz, M., Chapuis, C., Gerlich, D., Schneider, R., Eils, R., Huber, W., Peters, J., Hyman, A., Durbin, R., Pepperkok, R., & Ellenberg, J. (2010). Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes Nature, 464 (7289), 721-727 DOI: 10.1038/nature08869
Sciencexpress article with protein and complexes data:
Hutchins, J., Toyoda, Y., Hegemann, B., Poser, I., Heriche, J., Sykora, M., Augsburg, M., Hudecz, O., Buschhorn, B., Bulkescher, J., Conrad, C., Comartin, D., Schleiffer, A., Sarov, M., Pozniakovsky, A., Slabicki, M., Schloissnig, S., Steinmacher, I., Leuschner, M., Ssykor, A., Lawo, S., Pelletier, L., Stark, H., Nasmyth, K., Ellenberg, J., Durbin, R., Buchholz, F., Mechtler, K., Hyman, A., & Peters, J. (2010). Systematic Localization and Purification of Human Protein Complexes Identifies Chromosome Segregation Proteins Science DOI: 10.1126/science.1181348
*Tip of the hat to Alex who heard the BBC story and told me about it. I owe you a cider.