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!

Transcripts are not perfect markers of change

Source: Daran-Lapujade, P., Jansen, M.L.A., Daran, J., van Gulik, W., de Winde, J.H., and Pronk, J.T. Role of transcriptional regulation in controlling fluxes in central carbon metabolism of Saccharomyces cerevisiae. 2004. Journal of Biological Chemistry, 279(10): 9125-38

The authors grew yeast in chemostats under carbon-limitation on one of four carbon sources: glucose, maltose, acetate, and ethanol. They used flux balance analysis to come up with metabolic fluxes through key proteins and also measured transcript abundances across the genome for all four conditions. They found that there was not a great difference found (as compared to Kresnowati et al) except in 117 transcripts, between fermentable sugars and C2-carbon sources, though fluxes differed significantly at many steps in carbon metabolism. The difference between maltose and glucose was limited mainly to maltose transporters, both in flux and transcript abundance. Similarly, there was not a great difference between acetate and ethanol. Looking at the transcript abundance, the authors saw that the 117 transcript profiles clustered into six clusters relating to difference between glucose/maltose and acetate/ethanol, as well as within the carbon sources (ie, between glucose and maltose), the expected genes were in the expected clusters. Looking at the MIPS classification of the genes, 40% are still unknown, while 29% relate to carbon metabolism. The authors then looked at the upstream sequences for clustered genes, discovering conserved sequences for transcription factors. Of these transcription factors a few were predicted while unknown factors seem to play a role in more. Noting the discrepancy between changes in flux and changes in transcript abundance, even the magnitude changes, the authors suggest that most carbon-metabolism is altered via post-transcriptional regulation, and that transcript regulation is only used for rate-limiting steps in pathways. Finally, the authors hypothesize reasons their changed transcript dataset is so small compared to others who have looked at carbon source change and suggest it is due to the chemostat. The authors strongly feel the chemostat keeps a more constant environment, allowing changes to single perturbations, as opposed to stress, growth, and overabundance that is seen in batch.

Other notes:
-180 total transcripts change in response to carbon source
=33 between glucose and maltose
=16 between ethanol and acetate
=117 between sugars and C2-compounds
-complete data set found at www.bt.tudelft.nl/carbon-source
-maltose uptake requires energy-dependent proton-symport mechanism as opposed to glucose’s simple diffusion
-biomass yields for C2 lower due, respiration rates higher due to lower ATP yield
-higher fluxes in TCA, glyoxylate cycle, gluconeogenesis for C2
-lower fluxes in glycolysis, oxidative-PPP, NADP-dependent acetaldehyde and/or isocitrate dehydrogenases for C2
-79 upregulated, 38 downregulated in cultures limited by C2
=79 : 21 carbon metabolism, 7 for TCA, 5 acetyl-CoA metabolism and trafficking, 3 transcriptional regulation, 8 for transport, 7 for nitrogen metabolism and transport (SAM3), only 1 in respiration
=38 : 20 no clear role, 10 carbon metabolism, 4 PPP, 3 transport, 1 signaling
-previous studies on diauxic shift 400 transcripts shown to change 2-fold, 600 in glucose vs ethanol in batch
=225 genes are transcriptionally regulated by glucose, but not in glucose-limited chemostat with low glucose concentrations
=acetate as a byproduct for glucose batch, alters pH gradient, causes stress response
-in chemostat glucose is too low to encourage ethanol/acetate production
=growth rate decreases in batch, held steady in chemostat
-magnitude of changes does not match up, requires more than transcription regulation
=glycolysis and pyruvate showed no correlation
=“during carbon-limited cultivation, fluxes through these central metabolic pathways in S. cerevisiae are not primarily controlled at the transcriptional level”
=DNA microarrays “have limited value as indicators for in vivo activity for proteins”


Metabolites at right, transcript at left; significant decreases between carbon sources underlined, increases highlighted. Many more metabolites differ significantly than their corresponding enzyme's transcript, and magnitudes rarely match!


This has been a pet peeve of mine for a while: the multitude of studies that do some experiment, slap a microarray around and claim: "Aha! Look how many genes change! THIS is quite important!" Research should mature to look deeper at phenotypes: proteomics and metabolomics come to mind. Plus, this opens up a huge field of importance for genomicists: post-transcriptional regulation.