Systems biology approach to stringent response

Bacterial cells constantly need to monitor their environment and act accordingly.

The trouble is, bacteria are very small and when you are so very small, all the effects of being quantized in terms of molecule numbers are becoming very strong: number of mRNA molecules for a certain gene is an integer value, and not a very high at that, events of receptor getting activated or RNA polymerase binding to the promoter are stochastic in nature, and since not too many of the individual events occur at a time, they are not averaged out due to the law of large numbers.

All this results in bacteria gambling all the time: some react to stimulus, some don't, some produce more proteins in response to it, some less. This leads to so called phenotypic heterogeneity, when otherwise (genetically) identical bacteria become very different in terms of their responses.

This could be a good thing and also could be a bad thing. Having a collection of different bugs instead of a clone army will provide certain versatility: some are ready for one conditions, and some are ready for others. For instance, some are ready to grow and divide right away and some are slower and more cautious. Both types of cells can be beneficial in different conditions: the active ones will drive the population growth, but will be sensitive to the antibiotic treatment, and the passive ones will wait until the treatment is over and then they will come to life. Sounds like a good strategy (and it has a name, this strategy - "bed hedging") and I guess it is exactly the reason why clone armies never caught on.

On the other hand, this noise makes it really hard for bacteria to make an educated guess and respond to a stimulus in the best possible way - there is simply too much background to filter through!

One of the widely used cellular response systems used by bacteria is so called stringent response. This one is mediated by a family of proteins called RSH (RelA SpoH Homologue, with RelA and SpoT being the first members to be discovered). These proteins sense different cues (aminoacid starvation, fatty acid starvation, heat shock and so on) and translate these input signals into modulation of the intracellular concentration of ppGpp - a modified G nucleotide which acts as a second messenger modulating numerous cellular processes, such as transcription, translation, replication and lots more.

The RSH-mediated system in M. tuberculosis was shown to be  vital for prolonged life in the host, linking it to the phenotypic heterogeneity. This bug has one RSH protein, Rel, which is capable of both producing and degrading ppGpp. The logical question is then - how is Rel activity and abundance regulated, and what is its distribution in the bacterial population?

In the recent two papers (1 and 2) exactly that was done using M. smegmatis as a non-pathogenic model for M. tuberculosis. Rel promotor was fused with a GFP ORF so that its activity can be monitored on the single cell level using flow cytometry. And indeed, they saw that cells are very strongly heterogeneous in respect to the GFP level, which reflects activity of the rel promoter. This heterogeneity turned out to be brought about by the positive feedback loop feeding Rel expression back to its promoter via activity of the MprAB and SigE proteins.

Positive feed back loops are a common way of creating this sort of bistability in the biological systems and is a very common motif in the gene networks. What would be interesting is to see how common is this positive feedback among different bacteria, especially the ones that have different RSH system, such as the most commonly studied E. coli, which has two RSH proteins instead of one in M. tuberculosis: RelA, which is mostly producing ppGpp, and SpoT, which is mostly degrading it.

Effects of noise in protein expression are also different in E. coli: here synthetic and hydrolytic components are split into two independently produced proteins, thus resulting in a system with more degrees of freedom. Sure enough, it is well documented that intrinsic noise in protein expression (that would be roughly variation in the protein expression between the two independent genes in one bacterial cell) is much less than extrinsic one (roughly - variation between different cells), but still - two genes is more than one!

And what about bugs having more RSHs? Streptococcus mutans has three! From classic microbiological studies it seems that similar regulation could be present there as well, linking stress tolerance and genetic competence.

However fruitful, systems biology investigations of the stringent response are suffering from one big limitation: using current approaches, only a few readouts can be followed in the same cell at the same time. Stringent response, however, involves many different systems being rewired, and microarrays in the combination with metabolomics can follow many, many things happening in the cell (though lacking in the single cell resolution!).

References:

Potrykus K, & Cashel M (2008). (p)ppGpp: still magical? Annual review of microbiology, 62, 35-51 PMID: 18454629

Seaton K, Ahn SJ, Sagstetter AM, & Burne RA (2011). A transcriptional regulator and ABC transporters link stress tolerance, (p)ppGpp, and genetic competence in Streptococcus mutans. Journal of bacteriology, 193 (4), 862-74 PMID: 21148727

Mittenhuber G (2001). Comparative genomics and evolution of genes encoding bacterial (p)ppGpp synthetases/hydrolases (the Rel, RelA and SpoT proteins). Journal of molecular microbiology and biotechnology, 3 (4), 585-600 PMID: 11545276

Lemos JA, Lin VK, Nascimento MM, Abranches J, & Burne RA (2007). Three gene products govern (p)ppGpp production by Streptococcus mutans. Molecular microbiology, 65 (6), 1568-81 PMID: 17714452

Dahl JL, Kraus CN, Boshoff HI, Doan B, Foley K, Avarbock D, Kaplan G, Mizrahi V, Rubin H, & Barry CE 3rd (2003). The role of RelMtb-mediated adaptation to stationary phase in long-term persistence of Mycobacterium tuberculosis in mice. Proceedings of the National Academy of Sciences of the United States of America, 100 (17), 10026-31 PMID: 12897239

Sureka K, Ghosh B, Dasgupta A, Basu J, Kundu M, & Bose I (2008). Positive feedback and noise activate the stringent response regulator rel in mycobacteria. PloS one, 3 (3) PMID: 18335046

Ghosh S, Sureka K, Ghosh B, Bose I, Basu J, & Kundu M (2011). Phenotypic heterogeneity in mycobacterial stringent response. BMC systems biology, 5 PMID: 21272295

Elowitz MB, Levine AJ, Siggia ED, & Swain PS (2002). Stochastic gene expression in a single cell. Science (New York, N.Y.), 297 (5584), 1183-6 PMID: 12183631

Larson DR, Singer RH, & Zenklusen D (2009). A single molecule view of gene expression. Trends in cell biology, 19 (11), 630-7 PMID: 19819144

Alon U (2007). Network motifs: theory and experimental approaches. Nature reviews. Genetics, 8 (6), 450-61 PMID: 17510665

Ingolia NT, & Murray AW (2007). Positive-feedback loops as a flexible biological module. Current biology : CB, 17 (8), 668-77 PMID: 17398098

Raj A, & van Oudenaarden A (2009). Single-molecule approaches to stochastic gene expression. Annual review of biophysics, 38, 255-70 PMID: 19416069

Lidstrom ME, & Konopka MC (2010). The role of physiological heterogeneity in microbial population behavior. Nature chemical biology, 6 (10), 705-12 PMID: 20852608

Taniguchi Y, Choi PJ, Li GW, Chen H, Babu M, Hearn J, Emili A, & Xie XS (2010). Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science (New York, N.Y.), 329 (5991), 533-8 PMID: 20671182

Balaban NQ, Merrin J, Chait R, Kowalik L, & Leibler S (2004). Bacterial persistence as a phenotypic switch. Science (New York, N.Y.), 305 (5690), 1622-5 PMID: 15308767

Mendeley group on stringent response

Photoactivatable organic fluorophores for in vivo imaging

Imaging techniques heavily rely on the fluorophores they use. GFP was a great breakthrough because it allowed labeling specific targets, photoconvertable GFP variants were a great breakthrough because they allowed generation of single fluorescent molecules and this lead to development of a whole array of tracking and superresolution techniques.

However, GFP variants were always pretty bad fluorophores as compared to organic dyes due to their low quantum yield, pH and redox-potential sensitivity. Organic dyes, good as they are, had issues with selective labeling and thus were mostly used in vitro.

It seems that it might be about to change.  Lee at al. report a novel strategy for labeling proteins of interest in vivo with organic dyes. They use HaloTag technology by Promega and label a whole bunch of proteins both in mammalian cells and bacteria with photoactivatable azido DCDHF labels.

And it works beautifully. The only problem is that HaloTag is even bigger than GFP - 33 kD. That's a lot.

References:

Lee at al. Superresolution imaging of targeted proteins in fixed and living cells using photoactivatable organic fluorophores. JACS 2010 vol. 132 (43) pp. 15099-15101 PIMD 20936809

Lord at al. Azido push-pull fluorophores photoactivate to produce bright fluorescent labels. J Phys Chem B 2010 vol. 114 (45) pp. 14154-14167 PIMD 19860443

Antibiotics vs the ribosome

Ok, now it is official: this summer in Tartu there will be a conference on antibiotics inhibiting protein synthesis organized by Tanel Tenson.

It is not too late to register! And it has a very, very competitive registration fee - 0 USD!

Confirmed speakers:

James Williamson (Scripps Research Institute),
Alexander Mankin (University of Illinois at Chicago),
Steven Douthwaite (University of South Denmark),
Daniel Wilson (University of Munich),
Karen Shaw (Trius Therapeutics),
Ada Yonath (Weizmann Institute of Science).
Birte Vester (University of Southern Denmark)
Joyce Sutcliffe (Tetraphase Pharmaceuticals)
Mans Ehrenberg (Uppsala University)
Chaitan Khosla (Stanford University)
Markus Zeitlinger (Medical University of Vienna)

... and me and Gem Atkinson! That sold it, right?

Antibiotics affecting ribosome's protein composition

Antibiotics kill bugs; and about a half of them are doing so by messing up translation. That usually means that the ribosome is stalled at a certain step, be it initiation or elongation or ribosomal recycling.

But it is not always just that. Sometimes antibiotics also mess up the ribosome itself  and affect its composition.

Exhibit A: kasugamycin, an antibiotic that inhibits translation initiation in bacteria by interfering with binding of the the initiator tRNA. Amazingly enough, treatment with kasugamycin results in dramatic change in the ribosomal composition which is in turn changing ribosome's functional properties. Several proteins dissociate from the small ribosomal subunit (S1, S2, S6, S12, S18 and S21) which turns the 70S ribosome into a 61S kasugamycin particle. Ribosomal protein S1 is of particular interest here, because it is very important for the mRNA:ribosome interactions and is responsible for  A/U rich sequences acting as translational activators.

The S61 particle loses the ability to translate mRNAs with Shine-Dalgarno sequences, while being able to translate leaderless mRNAs, that is the ones starting directly with the initiation codon at the 5'. These leaderless mRNAs can be translated without the help of any initiation factors, by bacterial and eukaryotic ribosomes alike, so it is no surprise that S61 particles, even though compromised can still translate these messages.

What is particularly interesting in the kasugamycin story, it is that loss of the ribosomal proteins can be reconstituted in vitro by simply mixing the drug with the 70S. This means that the effect is direct rather than mediated by the assembly process (see below for an example of the latter effect).

Exhibit B: chloramphenicol and erythromycin. These antibiotics cause defects of the ribosomal assembly, and they seem to be doing so by interfering with the expresion levels of different ribosomal proteins. Here we have Liebig's barrel in action: you interfere with levels of many components you need to have and end up running out of one, the limiting one.

All of the above is highly relevant for people using antibiotics as tools, for instance in microscopy. Chloramphenicol and kasugamycin are widely used to inhibit translation (for instance here and here). It's worth remembering that they are doing much more than that while interpreting your results. Sometimes the tool you use can have much more complicated character than one would anticipate, as I discussed here.

References:

Wilson DN (2009). The A-Z of bacterial translation inhibitors. Critical reviews in biochemistry and molecular biology, 44 (6), 393-433 PMID: 19929179

Schluenzen F, Takemoto C, Wilson DN, Kaminishi T, Harms JM, Hanawa-Suetsugu K, Szaflarski W, Kawazoe M, Shirouzu M, Nierhaus KH, Yokoyama S, & Fucini P (2006). The antibiotic kasugamycin mimics mRNA nucleotides to destabilize tRNA binding and inhibit canonical translation initiation. Nature structural & molecular biology, 13 (10), 871-8 PMID: 16998488

Schuwirth BS, Day JM, Hau CW, Janssen GR, Dahlberg AE, Cate JH, & Vila-Sanjurjo A (2006). Structural analysis of kasugamycin inhibition of translation. Nature structural & molecular biology, 13 (10), 879-86 PMID: 16998486

Kaberdina AC, Szaflarski W, Nierhaus KH, & Moll I (2009). An unexpected type of ribosomes induced by kasugamycin: a look into ancestral times of protein synthesis? Molecular cell, 33 (2), 227-36 PMID: 19187763

Siibak T, Peil L, Dönhöfer A, Tats A, Remm M, Wilson DN, Tenson T, & Remme J (2011). Antibiotic-induced ribosomal assembly defects result from changes in the synthesis of ribosomal proteins. Molecular microbiology, 80 (1), 54-67 PMID: 21320180

Nevo-Dinur K, Nussbaum-Shochat A, Ben-Yehuda S, & Amster-Choder O (2011). Translation-independent localization of mRNA in E. coli. Science (New York, N.Y.), 331 (6020), 1081-4 PMID: 21350180

Tzareva NV, Makhno VI, & Boni IV (1994). Ribosome-messenger recognition in the absence of the Shine-Dalgarno interactions. FEBS letters, 337 (2), 189-94 PMID: 8287975

Andreev DE, Terenin IM, Dunaevsky YE, Dmitriev SE, & Shatsky IN (2006). A leaderless mRNA can bind to mammalian 80S ribosomes and direct polypeptide synthesis in the absence of translation initiation factors. Molecular and cellular biology, 26 (8), 3164-9 PMID: 16581790

Montero Llopis P, Jackson AF, Sliusarenko O, Surovtsev I, Heinritz J, Emonet T, & Jacobs-Wagner C (2010). Spatial organization of the flow of genetic information in bacteria. Nature, 466 (7302), 77-81 PMID: 20562858

Yes we can't!

In a recent paper by Shachrai at al. (which I discussed in detail here) a SpoT knock-out E. coli strain was reported, even though it is known that this strain is lethal both in E. coli and in Legionella pheumophilia. The good news is that now it is all cleared up.

The authors of the original paper wrote an erratum saying that yes, their SpoT knock-out was not just a SpoT knock-out; it has compensatory mutations. More specifically, RelA (which makes the brunt of the ppGpp in the cell) was compromised by mutations involved in the auto-regulation of its ppGpp-producing activity.

This incident brings up a question of validity of various knock-out strains that are so easy to make using a PCR product homologous to the target sequence in the genomic DNA, and therefore are so widely used.

First are the compensatory mutations, as it happened in the Shachrai paper. Here they had compensatory mutation in RelA, but it is the only one? May be there are more? P1 phage transduction in the clean background is the way to go, and as prices go down, whole-genome sequencing of the resulting construct is a good control.

Second are the downstream effects of the gene you knocked-out. In bacteria genes are arranged in operones, and knocking out one you mess up expression of the following one. In the case of SpoT knock-out in Shachrai at al. knocking out the whole SpoT ORF results in messing with rpoZ, the omega subunit of the RNA polymerase. This surely can not be good. Therefore the common practice is to insert something inside the ORF rather than substitute the whole thing altogether.

Tricky business.

References:

Shachrai, I., Zaslaver, A., Alon, U., & Dekel, E. (2010). Cost of Unneeded Proteins in E. coli Is Reduced after Several Generations in Exponential Growth Molecular Cell, 38 (5), 758-767 DOI: 10.1016/j.molcel.2010.04.015

Xiao H, Kalman M, Ikehara K, Zemel S, Glaser G, & Cashel M (1991). Residual guanosine 3',5'-bispyrophosphate synthetic activity of relA null mutants can be eliminated by spoT null mutations. The Journal of biological chemistry, 266 (9), 5980-90 PMID: 2005134

Datsenko KA, & Wanner BL (2000). One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proceedings of the National Academy of Sciences of the United States of America, 97 (12), 6640-5 PMID: 10829079

Gropp M, Strausz Y, Gross M, & Glaser G (2001). Regulation of Escherichia coli RelA requires oligomerization of the C-terminal domain. Journal of bacteriology, 183 (2), 570-9 PMID: 11133950

Gentry DR, & Burgess RR (1989). rpoZ, encoding the omega subunit of Escherichia coli RNA polymerase, is in the same operon as spoT. Journal of bacteriology, 171 (3), 1271-7 PMID: 2646273

Zusman T, Gal-Mor O, & Segal G (2002). Characterization of a Legionella pneumophila relA insertion mutant and toles of RelA and RpoS in virulence gene expression. Journal of bacteriology, 184 (1), 67-75 PMID: 11741845

Mendeley group on stringent response