Monthly Archives: March 2008

Live: Networks, noise and survival in stress

Gabor Balazsi has just finished a very interesting presentation on the interplay between molecular networks, gene expression noise, and evolutionary selection – here is the opening slide:

Garbor Balazsi’s opening slide

In the first part of his talk he gave a nice introduction to global network topology and network motifs – this should be nothing new to people familiar with the work of the Barabasi and Alon labs. He also explained the “Commander, Intermediate, Executor” model for hierarchical regulatory networks, which I had personally not heard about before, and the concept of “origons”, which seems quite use for understanding the response of large signaling networks to environmental cues.

The second part of his talk was about stochastic noise in gene expression. Genetically identical cells in a culture may express the same protein at different levels; this is a result of random noise influencing transcription, mRNA degradation, translation, and protein degradation. This is simply a consequence of low copy numbers giving rise to stochastic, as opposed to deterministic, behavior.

Finally, he talked about how noise at the level of gene expression can influence the survival of species in a changing environment. This part of his talk was kicked off with the funniest slide of his presentation:

Gabor Balazsi’s funniest slide

I guess it should be seen as a lesson on how not to do. He made some very good points about how noise plays hardly any role in multicellular organisms that reproduce sexually. By contrast, stochastic variation within clonal bacterial cultures provides much higher chance of survival when faced with sudden stress such treatment with anti-bacterial drugs. I would have liked to hear more about this, but unfortunately there was not much time left for this part of the presentation due to technical problems with the projectors. It looks like Guy Shinar picked the safe strategy for his presentation.

All in all, I found it to be a really inspiring talk. I have uploaded his slides in case if you want to take a look at it.

Live: Computational and Systems Biology Course

Fifteen minutes ago, Attila Csikasz-Nagy opened the Computational and Systems Biology Course at CoSBi in Trento, Italy:

CoSBi opening

Over the coming week, I will be covering the most interesting presentations and posters here on the blog and in the Picasa web album.

Analysis: The transcriptional response to growth rate is unrelated to cell-cycle regulation

David Botstein’s group at Princeton recently published a paper in Molecular Biology of the Cell with the title “Coordination of Growth Rate, Cell Cycle, Stress Response, and Metabolic Activity in Yeast”. As described in their abstract, they found interesting several correlations between the transcriptional responses to changes in growth rate and the regulation in response to stress and during the metabolic cycle:

We studied the relationship between growth rate and genome-wide gene expression, cell cycle progression, and glucose metabolism in 36 steady-state continuous cultures limited by one of six different nutrients (glucose, ammonium, sulfate, phosphate, uracil, or leucine). The expression of more than one quarter of all yeast genes is linearly correlated with growth rate, independent of the limiting nutrient. The subset of negatively growth-correlated genes is most enriched for peroxisomal functions, whereas positively correlated genes mainly encode ribosomal functions. Many (not all) genes associated with stress response are strongly correlated with growth rate, as are genes that are periodically expressed under conditions of metabolic cycling. We confirmed a linear relationship between growth rate and the fraction of the cell population in the G0/G1 cell cycle phase, independent of limiting nutrient. Cultures limited by auxotrophic requirements wasted excess glucose, whereas those limited on phosphate, sulfate, or ammonia did not; this phenomenon (reminiscent of the “Warburg effect” in cancer cells) was confirmed in batch cultures. Using an aggregate of gene expression values, we predict (in both continuous and batch cultures) an “instantaneous growth rate”. This concept is useful in interpreting the system-level connections among growth rate, metabolism, stress, and the cell cycle.

Because of my interest in cell cycle, their results regarding growth rate and cell-cycle regulation caught my attention. In Figure 6 of their paper, Brauer et al. show the slope distribution for the genes belonging to each of the phase-specific clusters defined by Spellman et al. (1998). The only trend they observe is that genes expressed at the G1/M transition.

I decided to redo the cell-cycle part of their analysis in a slightly different manner, hoping that I would be able to get a stronger signal than they did. Rather than using the 800 periodically expressed genes proposed by Spellman et al. (1998), I thus made use of the list of 600 periodically expressed genes from de Lichtenberg et al. (2005). Like Brauer et al., I found no difference in growth-rate response between cell-cycle-regulated genes and other genes. To analyze the phase-specific expression, I chose to plot the peak time distributions for genes that are up- and down-regulated in response to increasing growth rate:

Peak-time distribution for genes that are up- or down-regulated in response to increasing growth rate

In agreement with Brauer et al., genes that are down-regulated at high growth rates appear to have a striking preference for being expressed at the G1/M transition. However, manual inspection of these genes revealed that more than half of them belong to the Y’ family of DNA helicases, which are encoded by the sub-telomeric regions (striped blue bars). The trend observed by Brauer et al. is thus presumably not due to slower growing cells spending more time in M-G1 phase as suggested by the authors, Instead, it is likely an artifact of the many Y’ helicase genes found in the sub-telomeric regions of budding yeast, which are so highly homologous that they can cross hybridize on microarrays and hence all appear to be periodically expressed with identical peak times.

After correcting for this the down-regulated genes show a weak preference for being expressed during M phase whereas the up-regulated genes tend to be expressed in late G1 and S phase. However, the peak-time distributions of up- and down-regulated do not differ significantly from that of all cell-cycle-regulated genes (Kolmogorov-Smirnov test).

In summary, my reanalysis suggests that there is no correlation between the transcriptional response to changes in growth rate and transcriptional cell-cycle regulation. It also reiterates the importance of manually inspecting the results from statistical analyses – they may be highly significant for all the wrong reasons.

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Editorial: One month anniversary

When I launched this blog just a month ago, I wrote that it was an experiment and that I would later evaluate if it was worthwhile to continue. I am very happy to already now be able to declare the experiment a success. With over 2000 views during the first month and around 50 subscriptions to the RSS feed, Buried Treasure is certainly worthwhile writing – I hope you also find it worthwhile reading.

In the near future I plan to experiment with live blogging. The idea is to provide coverage of the conferences and meetings that I attend. To avoid polluting my blog with dozens of short posts consisting of just one or two sentences and a photo, I have setup an associated Picasa web album. This is where the main action will happen – I plan to post only highlights and summaries here on the blog. You can find the RSS feeds for the album and the blog in the sidebar.