Wednesday, January 28, 2009

Noise propagation in transcription networks

Source: Dunlop et al (2008). Regulatory activity revealed by dynamic correlations in gene expression noise. Nature Genetics 40(12):1493-1498.

Biological events are stochastic in nature. Random fluctuations in protein concentration, expression and etc relays noise through the transcription network via the regulatory links. For example, a random decrease in the concentration of a repressor results in an increase in the expression of its target gene; however, only if the concentration of the repressor falls within an "active" range in which the expression of the target genes is sensitive to small chanages in the repressor content (see Fig. below).
Thus, observed correlations between the expression of different genes may be the result of a direct or indirect regulatory process. However, in addition to intrinsic noise (fluctuations in the expression of a given gene), we should also consider the extrinsic noise in which all the genes are uniformly affected by a given change (e.g. a random increase in the ribosome content of the cell increases the expression of all the genes). Extrinsic noise causes false positive correlation (see Fig. below).
Thus, any measurement of correlations must be normalized by the effect of extrinsic noises. In this paper, the authors use both stochastic modeling and experimental validation to make the case for this phenomenon.

Tuesday, January 13, 2009

MISSING: ATP!!

Source: Kresnowati, M.T.A.P., van Winden, W.A., Almering, M.J.H., ten Pierick, A., Ras, C., Knijnenburg, T.A., Daran-Lapujade, P., Pronk, J.T., Heijnen, J.J., and Daran, J.M. When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation. 2006. Molecular Systems Biology, 49

The authors subjected yeast held at steady-state low-glucose levels to a pulse of glucose and recorded their transcriptional and metabolic differences five minutes after the pulse. The most shocking discovery was the remarkable drop in AXP levels, led mainly by ATP. ATP was not simply converted to ADP, nor were AXPs converted for RNA incorporation, over 80% of AXP was unaccounted for after the pulse. Additionally, early-glycolytic metabolites climbed after the pulse but later-glycolytic metabolites sharply dropped. This was explained by the observed jump in NADH/NAD which would inhibit glyceraldehyde-3-phosphate dehydrogenase. With the switch from gluconeogenesis to glycolysis, these later compounds would flush into TCA or ethanol production but not be replenished until redox equilibrium in the cell was returned. On the transcriptome front, over 1000 genes were found to differ between at least two time points, differences didn’t begin until after 120s, though most until after 210s. The upregulated genes were enriched for ribosome biogenesis, amino acid metabolism and purine synthesis, all of the genes leading to adenine production through de novo synthesis, RNA degradation, sulfur metabolism, and conversion. The downregulated genes were enriched for C1-metabolism, energy reserves, and TCA. Additionally a number of genes in those pathways were found to have an order of magnitude lower half-lives for transcripts, from ~30 minutes to four! Looking at 3’, post-stop codon regions, the degraded genes nearly all shared in at least one of four regions that were abundantly found compared to chance.



Other notes:
-1154 genes significantly change
=K-means clustering into 5 groups
-CXP, UXP, and GXP levels also dipped but not on the same magnitude of AXP
-TCA intermediates increased, except citrate
=probably two separate branches: TCA and glyoxylate cycle
=TCA genes downregulated, glyoxylate genes upregulated


So yeah, it's cool that 1/6th of the genome changes its transcription. And yeah, it's interesting that there's an 8-fold difference in transcript half-lives. But WHERE DOES ALL THE ATP GO?!?! In case you're new to biology: ATP is one of the top 10 most used molecules (by number of reactions). This is like saying that upon the introduction to oxygen, humans lose 80% of their red blood cells and no one can see any dead red blood cells, they just vanish. If anyone knows any follow up studies that solved this conundrum, please send my way!