Relacin - a novel antibacterial targeting the stringent response, maybe

The stringent response is a promising target for novel antibacterials: it is involved in virulence and antibiotic insensitivity, and inhibiting the stringent response would disarm the bug, making is both less evil and easier to kill.

A new study is came out in PLoS Pathogens describing a novel Rel inhibitor, relacin (Fig. 1). Wexselblatt and colleagues are following up their earlier work on derivatizing ppGpp into a Rel inhibitor  and are now testing the compound not only in vitro, but also in vivo.

Fig 1: the chemical structure of relacin.

They show that relacin efficiently inhibits sporulation of Bacillus subtilis. Sporulation in this organism is driven by ppGpp, and inhibitory effect of relacin is a strong indication that it actually works. However, really high concentrations are needed to achieve significant effects: 0.5 - 2 mM. At these concentrations one would expect that in addition to hitting RelA, relacin will affect all the other ppGpp targets, i.e. translational GTPases, GTP biosynthesis enzymes etc. The authors do not test these effects. It would be easy to do it in an in vitro translational lysate... but, unfortunately, this is not done.  By using a GFP-fusion reporter, they do show that relacin inhibits translation of mid-sporulation protein SpoIIQ, but they do not check that it does not inhibit translation in general. A simple test of GFP expression would do.

With this (potential) absence of specificity relacin is unlikely to be the 'magic bullet' inhibiting just the stringent response and making bacterial less pathogenic, but still viable. However, relacin is just the first step. There is a hope that the derivatives to come will work at more in vivo-relevant concentrations and will be highly Rel-specific.

References:

Wexselblatt et al. Biomed Org Chem (2010) PIMD: 20483622

Wexselblatt et al. PLoS Pathogens (2012) 

ppGpp regulates GTP synthesis by inhibiting Gmk and HprT

Another role for ppGpp was discovered by Allison Kriel and colleagues: it directly regulates GTP levels by interfering with GTP biosynthetic pathway. It is worth saying that inhibitory effects of (p)ppGpp on IMP dehydrogenase and anenylosuccinate synthetase, first enzymes of the guanylate and adenylate pathways, respectively, were discovered by Gallant and colleagues as early as in 1971, so the connection between (p)ppGpp and metabolism of G nucleotides was known long ago.

The cool thing about the paper is the approach they use. There can be loads of potential targets of ppGpp, and loads of proteins will be inhibited by it in vitro. Which ones are the relevant ones? Kriel and colleagues usa a top-down approach: first they get a birds-eye view of starvation by running metabolic and transcriptomic analysis of starved wt and ppGpp⁰ (i.e. devoid of ppGpp) strains, then identify the ppGpp targets by clustering and pathway analyses, and then follow their predictions up in vitro and an vivo. This is a really powerful approach.

The net result is that (p)ppGpp inhibits several enzymes in the GTP biosynthesis pathway, and by doing quantitative experiments, Kriel et al. identify the primary targets, Gmk and HprT (Fig. 1). All the experiments are done in B. subtilis, and in this bug pppGpp is the major magic spot nucleotide. It is made of GTP, so inhibition of GTP synthesis results in a negative feedback control loop. This loop turns out to be a key component for the control of the GTP levels in the cell.

In  B. subtilis, unlike E. coli, ppGpp does not regulate RNA polymerase directly: the regulation goes via effects on the GTP level. And indeed, a genetic screen performed by Kriel et al. showed that regulation of GTP metabolises by ppGpp, not of polymerase is crucial for the bacterial survival under stress. The have found 37 suppressor mutations leading to survival of the ppGpp⁰ strain - and most of these turned out to be in the GTP biosynthesis pathway. In the E. coli case, the supressor mutations are usually in the RNA polymerase.

 The negative control of GTP synthesis by ppGpp turned out to be crucial for bacterial well-being - in the ppGpp⁰ cells high levels of GTP caused cell death, though the mechanism is still unclear (Fig. 1). Kriel et al. proposed several possible explanations: inhibition with ATP-consuming enzymes, excessive up-regulation of the rRNA transcription, effects on dGTP synthesis etc.

Fig. 1: ppGpp's role in B. subtilis survival via regulation of GTP biosynthesis. Figure from Kriel et al.

References:

Kriel et al, Cell (2012) in press

Gallant et al. JBC (1971), 246 (18): 5812-5816, PIMD: 4938039

Krasny and Grouse, EMBO J. (2004), 23(22): 4473-83, PIMD: 15496987

Positive feedback control of E. coli RelA by its product ppGpp

ppGpp regulates numerous targets, and now we added one more: the stringent response factor RelA itself. Using an in vitro stringent response system we showed that ppGpp dramatically increases the turnover rate of RelA, both is the system where RelA is activated by the ribosomes (both naked and programmed with tRNA and mRNA) and in the system where RelA is activated by the ribosomal protein L11 alone.

Figure 1: RelA activation in the 70S-driven in vitro system upon addition of ppGpp

We did 70S and L11 tittrations and demonstrated that ppGpp increases RelA's kcat, making it a more efficient enzyme:

Figure 2. RelA activity as a function of the 70S concentration in presence and absence of ppGpp

What next? First off, we do not know where ppGpp binds and how it regulates RelA on the mechanistic level. Second, since there are at least 30 groups of the RSH proteins, we will figure out which are activated by this mechanism, and which are not. This will provide us some vital clues for understanding the computational properties of the stringent response system. Third, after this in vitro result it is instrumental to show the ppGpp-mediated activation in vivo. 

PS: and now our paper got covered as a Research Highlight in Nature Chemical Biology. Yay!

References:

Shyp et al., EMBO Reports (2012) doi: 10.1038/embor.2012.106.
PIMD: 22814757

iGEM2011: GFP-based readout for ppGpp concentration in vivo

Measuring ppGpp concentration in individual living cells with good temporal resolution would be great. I've been musing about a possibility of doing that using RNA aptamers, but that's just musing. It seems like am iGEM team from the University of Trondheim tried setting up a GFP-based reported system, and this system is, maybe, possibly, probably, working. Somewhat. 


Unfortunately there is no publication. However, there is a popular article about the whole affair, in Norwegian and there is a short report on the iGEM webpage. 


Apropos to the technical issues that are listed in the original report, such as dramatic leakage of the GFP reporter in the absence of stress stimuli, there are several conceptual concerns. First, the system is based on translation of the GFP reporter during the stringent response, and during the stringent response translation is strongly inhibited. Second, GFP (they use red version of it, mCherry) has to mature in order to become bringt, and that takes some time - from minutes to hours, depending on the conditions and what sort of GFP variant it is. For mCherry maturation time is 15-40 minutes, and this is comparable with E. coli generation time. Therefore, first, one would expect a very pronounced lag before the SR is engaged and the corresponding readout and, second, all the fluctuations in the ppGpp concentrations happening on the timescale below 10s of minutes will be averaged out. Third, GFP is very stable, so this reporter system will have severe memory effects - once the cell has committed to stringency, it will produce GFP, and even though stringency is reversed, GFP will stay. Maybe it is possible to turn this into a feature, but I am not sure how. And, lastly, brightness of the GFP depends on the pH and redox potential of the environment, and these things change in the stressed cells.

One more '-omics' analysis of the stringent response: BIBLIOMICS

The stringent response is confusing, no doubt about that. I personally get exceedingly confused when I read in vivo papers from the 80s. I somehow hope that there should be hidden gems there, and it is just my stupidity that stops me from discovering these.... so I try... and I get confused. In vivo data confuse me, and in vivo data from the 80s.... I am lost.

Importantly, I always try to read one paper at a time, maximum ten, rarely more then twenty. Imagine what happens if one would read them all? And how, I wonder, how would one call this sort of thing? Wonder no more; enter Carneiro and colleagues. What they did, they collected the whole bibliome about the E. coli stringent response and analyzed it in attempt to gain a birds-eye view, providing 'a more systematic understanding of this cellular response'. 

They summarize the nitty-gritty of the stringent response in the magnificent Figure 1.

 The sheer number of mistakes they make is owe-inspiring and truly shows the power of the high-throughput learning. It is OK that tRNAs have their anticodons on one the 3' (or is it 5'?) end and amino acids are attached where the anticodons should be. Fine, that the amino acid moieties are outside of the ribosome when the tRNAs are attached. Fine, that there is no way in hell one can figure out there are the A- , P- and E-sites of their ribosomes, and, surely, it would be nice to be able to know position of at least the A-site when we are talking about the stringent response. But what is truly fabulous, is that the ribosomal protein L11 is part of the small ribosomal subunit (L... the letter L is giving us a hint... large, maybe?...). Since RelA is interacting with L11, so this causes a bit of a trouble, and RelA ends up on the small subunit as well (ah, never mind this paper). In this awkward position RelA has no chances of inspecting the CCA of the A-site tRNA, but maybe it is for the best, given how messed up the tRNA already is and that we have no idea where the A-site could be...


The bird-eye view allows Carneiro and collegues to make some information-packed generalizations. I am not sure what we learn this way, but the figures speak for themselves:

Rrrright, the dashed line overtook the solid one and they never crossed, therefore the ratios between the blue and red bars changed with time... I want some error-bars, then it will be really, really nice and scientific.


But it is not only the figures that are great. The text is awesome as well. 'Later, in 1980, the ppGpp level was found to be controlled by the SpoT enzyme via GTP hydrolysis activity (PMID: 6159345)'. GTP hydrolysis! By SpoT! Yay! 'The 50S ribosomal subunit protein L11 has been indirectly implicated in the feedback inhibition of (p)ppGpp, because ribosomes lacking this protein are unable to stimulate the synthesis of these nucleotides (PMID:11673421; PMID:17095013) [39,61].' Feedback inhibition! This redefines the meaning of feedback... Wow! No wonder L11 migrated on the large subunit... 


Being subjected to such a monumental degree of confusion, the authors started expressing themselves in a most peculiar way; for the lack of a better word I would call it 'cautious': 'As a result, it was possible to perceive the relevance of specific translation GTPases known to be inhibited by (p)ppGpp nucleotides'. 'Studies showed that (p)ppGpp inhibits translation by repressing the expression of ribosomal proteins and also potentially inhibiting the activity of the particular proteins'. 


I certainly hope that soon the authors should take on the mighty ribosome. There are many more papers in the ribosomal bibliome, and the level of confusion might be even higher. I would also recommend some 3D plots!

 References:

Carneiro, S., Lourenço, A., Ferreira, E. C., & Rocha, I. (2011). Stringent response of Escherichia coli: revisiting the bibliome using literature mining. Microbial informatics and experimentation, 1(1), 14. doi:10.1186/2042-5783-1-14 PIMD: 22587779

One more crazy little thing

Stringent response is run by a family of proteins called RelA-SpoT Homologues, RSH, and these come in two flavors: the long ones and the short ones. The long ones have both ppGpp synthesizing and ppGpp hydrolyzing domains, and either both are active, with synthesizing being the dominant one (that would be the ancestral Rel) or both are active, with hydrolyzing being the dominant one (SpoT) or only the synthesizing one is active (RelA). The short RSHs are more variable. They have only one of the domains, so they can either synthesize (SAS, small alarmone synthetase) or hydrolyze (SAH, small alarmone synthetase) ppGpp. What is fun, is that in addition they can have other domains, sometimes with very peculiar functions.

A very peculiar SAS was characterized recently by Maya Murdeshwar and Dipankar Chatterji. They call it MS_RHII-RSD, or, using terminology proposed in our paper with Gemma Atkinson, actRelMsm. This SAS from Mycobacterium smegmatis in addition to the ppGpp synthetic activity has another one, quite unexpected. It has a dedicated domain capable of hydrolyzing DNA:RNA duplexes via its RNAse H domain.

Quite bizarre, quite.


References:


MS_RHII-RSD:  a dual function RNase HII - (p)ppGpp synthetase from Mycobacterium smegmatis. M. Murdeshwar and D. Chatterji. J. Bacteriology, 2012, in press PIMD: 22636779
 

ppGpp induces production of fruiting bodies in Myxococcus xanthus

E. coli is boring, admit it. At least in comparison with Myxococcus xanthus: a self-organized, predatory saprotrophic single-species biofilm called a swarm according to the Wikipedia. Now that sounds exciting! I wish one day somebody would call me "a self-organized, predatory biofilm called a swarm"! That would make a lovely email signature: "Vasili Hauryliuk, PhD,  self-organized, predatory biofilm called a swarm". Hell yes.

But I digress. Stringent response (or, to be more specific, RelA-mediated production of alarmone molecule ppGpp) regulates loads of things in bacterial physiology: it turns on bacterial survival mode and shuts down production of ribosomes, it induces virulence (cornered bacteria are deadly) and makes bugs more resistant to antibiotics. Now let us just imagine for a moment what stringent response can do to a "a self-organized, predatory biofilm called a swarm"! Exactly that was investigated in recent paper by Konovalova and colleagues (Konovalova et al. Mol Microbiology 2012).

Unlike boring E. coli, Myxococcus xanthus has a life cycle (Fig. 1). It can swarm happily gobbling up other bacteria, or, if food supply is low, it can form a fruiting body (a life-stile similar to that of slime molds who are not bacteria but eucaryotes).

Fig. 1. Life cycle of a self-organized, predatory biofilm called a swarm (AKA Myxococcus xanthus).

Formation of the fruiting bodies depends on the functionality of the stringent response system (Harris et al. Gens Dev. 1998). How Konovalova and colleagues fill in the molecular details presenting an example of post-translational activation of secretion by regulated proteolysis.  Here is how it works.

Formation of the fruiting bodies depends on the cell-to-cell signaling, and this process, obviously, happens outside of the cell. It involves proteolysis of several extracellular target proteins by a subtilisin-like protease PopC, which needs to be exported outside of the cell in order to do its job. So now it turns out that RelA, working together with PopD protein, regulates PopC export, which is activated during starvation (and, therefore, production of ppGpp). The PopD:PolC complex formation is not affected by ppGpp, suggesting that regulation of export by RelA is using some indirect mechanism. And indeed, PopD turned out to be degraded during starvation in a FtsH-dependent manner, releasing PopC - a story somewhat similar to regulation of toxin:antitoxin pairs via antitoxin degradation by Lon protease during nutritional stress.

All this brings us to the question of importance of the regulated proteolysis during the stringent response. One known example of ppGpp-mediated control via protein degradation is degradation of ribosomal proteins by Lon protease induced by accumulation of polyphosphate. Unfortunately, usually stringent response on the whole-cell level is studied on the mRNA level, by, say, microarrays. It would be most educational to compare the changes on the mRNA level with changes on the proteome level and to pick up the protein degradation-mediated regulation pathways.

References:

Harris BZ, Kaiser D, & Singer M (1998). The guanosine nucleotide (p)ppGpp initiates development and A-factor production in Myxococcus xanthus. Genes & Development, 12 (7), 1022-35 PMID: 9531539

Konovalova A, Löbach S, & Søgaard-Andersen L (2012). A RelA-dependent two-tiered regulated proteolysis cascade controls synthesis of a contact-dependent intercellular signal in Myxococcus xanthus.  Molecular Microbiology  PMID: 22404381

Active role of the stringent response in antibiotic tolerance

From time to time we try killing bacteria with antibiotics. Most of the bugs die, but not all. These survivors fall into two categories: resistant bugs and tolerant bugs. Resistant bugs have specific mechanisms counteracting the drug: mutations in the target site, enzymes destroying the antibiotic, etc. Tolerant bugs are not getting killed using some more general approach, such as forming a biofilm efficiently shielding them from contact with the drug or shutting down its biosynthetic activity and waiting for the better days to come.

The stringent response is a mechanism rewiring the bacterial physiology under stress. It changes many things simultaneously, and, not surprisingly, functionality of the stringent response is linked to antibiotic tolerance. However, the big question here is the nature of this link: do bugs need functional stringent response in order to tolerate the drug just because relaxed bugs do not shut down their growth when needed and die, or does the stringent response induce production of certain specific enzymes protecting from the drug?

Recent report by Nguyen and colleagues seems to settle this question. Using series of in vivo experiments with E. coli knock-out strains deficient either in stringent response per se (knock-outs of RelA and SpoT) or in down-stream stringent response-regulated targets they show that the main source of antibiotic tolerance is not a general biosynthetic shut-down. Specifically, they identify two genes induced during the stringent response - superoxide dismutase (SOD) and catalase - to be crucial for bacterial survival in the presence of antibacterials.  What these do, they protect the bug from the hydroxyl radical. And build-up the latter was recently identified as a common mechanism causing the cell death during treatment by different unrelated antibacterials. 

References:

Nguyen at al., Science (2011) 334, pp. 982-986 PIMD 22096200

Kohanski et al. Cell (2007) 130, pp. 797-810 PIMD 17803904

DksA and ppGpp regulate transcription of both rRNA and r-proteins

During the stringent response ppGpp together with a small protein DksA bind to the RNA polymerase and down-regulate transcription of the rRNA genes. It makes sense - there is no need for more ribosomes if there are not enough amino acids. However, ribosomes consist not only of rRNA but also of ribosomal proteins, and if the cell stops making rRNA it would make sense to stop making the ribosomal proteins as well.

And it turnes out that ppGpp and DksA do that too. Makes total sense, again. It is quite rare that something about the stringent response makes total sense, but there you are.

References:

Lemke, J. J., Sanchez-Vazquez, P., Burgos, H. L., Hedberg, G., Ross, W., & Gourse, R. L. (2011). Direct regulation of Escherichia coli ribosomal protein promoters by the transcription factors ppGpp and DksA. Proceedings of the National Academy of Sciences of the United States of America, 108(14), 5712–5717.

The RelA/SpoT Homolog (RSH) Superfamily: Distribution and Functional Evolution of ppGpp Synthetases and Hydrolases across the Tree of Life

Stringent response is run by the RSH (RelA / SpoT Homologue) proteins, but there are more RSHs then just these two. Usually researchers were finding them using an ad hoc approach: take your favorite bug you worked with for 10 years, blast its genome with RelA gene, find anything that looks like RelA, test  it.

Finally there is a proper analysis of RSHs across the tree of life: The RelA/SpoT Homolog superfamily: distribution and functional evolution of ppGpp synthetases and hydrolases across the tree of life by Atkinson GC, Tenson T, Hauryliuk V, PLoS ONE, 6(8): e23479. 

Here is the take home message:

• there are loads of different RSHs out there: we identified 30 subgroups! 
• all the RSHs out there are now are classified (for now, that is. New genomes are coming out every day, damn the progress!).
• Archaea, Bacteria, Eucaryotes: they all have RSHs. I repeat: Archaea too.
• there are the long RSHs (i.e. Rel, RelA and SpoT) and there are the short ones. 
• The short ones have either ppGpp synthesis or ppGpp hydrolysis domain. The long ones have both, but not always both are functional.
• by comparing the long ones vs the short ones we identified residues potentially involved in the inter-domain cross-talk in the long ones (the short ones have only one domain thus there is no cross talk there!).

The bottom line: if you work on a strange RSH protein from a strange bug, do check out our paper. 

Fig. 1.  Maximum likelihood phylogeny of the ppGpp hydrolase domain.  Subgroups are labeled and shading behind the branches shows the most common domain structure observed for those groups, as per the legend in the inset box. Symbols on branches indicate bootstrap support, as per the inset box.

Hurray to Gem! 

Single-molecule investigations of the stringent response machinery in living bacterial cells

Wikipedia: "reductionism, an approach to understanding the nature of complex things by reducing them to the interactions of their parts, or to simpler or more fundamental things". This approach was very successful in unrevealing the basic mechanisms of biological systems. Modern biochemistry is reductionism in its pure form: we purify individual components, mix them together in a test tube and make this in vitro system jump through the hoops and this way we learn how it works. Then we extrapolate what we learned from the in vitro system to the cell, and test our model in vivo: overexpress some components, knock-out the other, introduce mutations etc.

However, sometimes producing in vitro system is not feasible, either because it is to laborious or because we simply do not know what are the components. A good solution would be then to do biochemistry, but... inside the living cell. This approach became technically feasible in the recent decades, and was highly successful in cracking these hard problems for which in vitro investigations are just not cutting it. In vivo biochemistry relies on labeling the protein (proteins) of interest with a fluorescent tag, usually a GFP derivative, and then following its movement inside the living cell on the single molecule level. Movement of the protein can tell us about its functional cycle: binding to a partner will slow its diffusion, for instance.

Now this approach was applied to investigation of the stringent response (I have discussed this fascinating bacterial adaptation system quite at length here). In short, when bacteria are starving for amino acids, they accumulate deacylated tRNAs. These bind to the ribosomal A-site, and this situation is sensed by a protein called RelA, which starts producing alarmone molecule ppGpp. One important thing about RelA functional cycle is that it has two states with distinctly different difusion properties: ribosome bound and free.

This was taken advantage of in the recent paper by English at al. RelA was labelled with a fluorescent GFP variant and its diffusion was followed at ms time resolution. Indeed, inactive RelA turned out to be tightly associated with the ribosomes and diffusing slowly (Fig. 1). However, when stress was induced, either by amino acid limitation or by the heat shock, RelA fell off the ribosome and started moving about much, much faster (Fig. 1).

It is known that under these conditions RelA is enzymatically active and produces ppGpp. Since active RelA seems to spend its time off, rather than on the ribosome, it was suggested that ppGpp production is happening off the ribosome as well. And this is a rather unique mechanism for a ribosome-associated factor. Usually on the ribosome is when the protein is active: RelE binds to the ribosome and cuts the mRNA, EF-G binds, hydrolyses GTP and translocates A and P site tRNAs, ricin binds and cuts the ribosomal RNA.

Fig. 1. MSD (Mean Square Displacement) analysis of the RelA diffusion in vivo. Diffusive behavior of active and inactive RelA is compared to that of ribosomes carrying fluorescent label on L25 protein (green triangles) and freely diffusing protein mEos2. Insert shows the difference in the individual trajectories of active (right trajectory) and inactive (left trajectory) RelA.

Now, of course, this mechanism of RelA has to be tested by other methods. As any approach, single molecule tracking in its current form has its limitations, and the biggest one is the labels used, GFP in this case. RelA fused with GFP is not RelA, it can behave somewhat different.

PS: and now this story was covered in the news! HFSP and UppsalaBio (in Swedish). Also it is covered as a Research highlight in Biopolymers.

PPS: a great review of the single molecule investigations in vivo just came out in Nature: Gene-Wei Li and Sunney Xie (2011). Central dogma at the single-molecule level in living cells. Nature, 475, 308-315 PIMD 21776976. Too bad, we are not mentioned!

PPPS: this blog post is covered in The MolBio Carnival #13!

PPPPS: and now our paper made it to F1000.

References:

Xie XS, Choi PJ, Li GW, Lee NK, & Lia G (2008). Single-molecule approach to molecular biology in living bacterial cells. Annual review of biophysics, 37, 417-44 PMID: 18573089

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

Gallant J, Palmer L, & Pao CC (1977). Anomalous synthesis of ppGpp in growing cells. Cell, 11 (1), 181-5 PMID: 326415

Brian P. English, Vasili Hauryliuk, Arash Sanamrad, Stoyan Tankov, Nynke H. Dekker, and Johan Elf (2011). Single-molecule investigations of the stringent response machinery in living bacterial cells PNAS 108(31), E359-364 PIMD: 21730169 and the PNAS Author Summary

Mendeley group on stringent response

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

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

Kinetics of stringent response revealed by microarray analysis

Stringent response is immensely complex and many different proteins are targeted by ppGpp. Different targets have different susceptibility to ppGpp - K_D of binding or K_i of inhibition. Therefore as stringent response progresses and ppGpp concentration changes, different targets will be engaged sequentially, in this way orchestrating changes in the cellular physiology.

Studying the development of stringent response in time is a tricky business. Temporal resolution in one key component, ability following many parameters (many targets) is the other one. Microarrays seem to be the way (Traxler 2006, Traxler 2008, Durfee 2008, Traxler 2011 and Balsalobre 2011).

Here are the main points from Traxler 2011. They did microarray analysis of four strains: wt E. coli K-12-derivative MG1655, ppGpp⁰, Lrp- and RpoS- in MG1655 background. The nature of the wt is important - L12 derivatives are special in that sense that they exhibit stringent response upon L-Valine and L-isolucine overdose, and the latter is used to induce the stringent response in Traxler 2011.

In these strains they follow the effects of two global regulators, Transcription factor Lrp (leucine responsive protein) and RpoS AKA Sigma 38, a specialized σ-factor.

It turnes out that ppGpp regulates both the feed-back loop regulated by Lrp and the feed-forward loop regulated by RpoS (for discussion of how these motifs work see Alon 2007). Moreover, Lrp regulon is induced much earlier than RpoS.

So how is one molecule - ppGpp - evokes two temporally separated responses (early Lrp and late RpoS)? The obvious idea is that these two regulons have different sensitivity to ppGpp, thus the more sensitive one is induced earlier (Lrp) and the less sensitive one is induced later (RpoS). Combining microarray data with measurements of ppGpp concentrations in vivo confirmed this hypothesis.

Rendering Lrp operon inactive in turn disrupts normal progression of the stringent response: both wt and Lpr- strains rapidly accumulate ppGpp, but during the later stage wt cells lower the ppGpp concentration and resume growth, whereas Lrp- strain retains high ppGpp concentration is unable to adapt to stringent conditions. Functional RpoS (which works on the later stages of stringent response) does not help - you have to come prepared, i.e. Lrp regulon should do its job.

However powerful, microarray-based techniques inherently average out the cell-to-cell variability which plays important role in the stringent response as shown by the systems biology investigations.

References:

Matthew F. Traxler, Vineetha M. Zacharia, Stafford Marquard, Sean M. Summers, Huyen-Tran Nguyen, S. Elizabeth Stark and Tyrrell Conway. Discretely calibrated regulatory loops controlled by ppGpp partition gene induction across the ‘feast to famine’ gradient in Escherichia coli. Molecular Microbiology (2011) doi:10.1111/j.1365-2958.2010.07498.x

Matthew F. Traxler, Sean M. Summers, Huyen-Tran Nguyen, Vineetha M. Zacharia, G. Aaron Hightower, Joel T. Smith and Tyrrell Conway. The global, ppGpp-mediated stringent response to amino acid starvation in Escherichia coli. Molecular Microbiology (2008) 68(5), 1128–1148

Carlos Balsalobre. Concentration matters!! ppGpp, from a whispering to astrident alarmone. Molecular Microbiology (2011) doi:10.1111/j.1365-2958.2010.07521.x

Matthew F Traxler, Dong-Eun Chang, Tyrrell Conway. Guanosine 3',5'-bispyrophosphate coordinates global gene expression during glucose-lactose diauxie in Escherichia coli. PNAS 2006 vol. 103 (7) pp. 2374-9

Tim Durfee, Anne-Marie Hansen, Huijun Zhi, Frederick R. Blattner and Ding Jun Jin. Transcription Profiling of the Stringent Response in Escherichia coli. J. of Bacteriol. 2008, p. 1084-1096, Vol. 190, No. 3

R. I. Leavitt, H. E. Umbarger. Isoleucine and valine metabolism in Escherichia coli. XI. Valine inhibition of the growth of Escherichia coli strain K-12. J. Bacteriol. 1962 vol. 83 pp. 624-30

Uri Alon. Network motifs: theory and experimental approaches. Nat Rev Genet. 2007 vol. 8 (6) pp. 450-61

Brinkman AB, Ettema TJ, de Vos WM, van der Oost J. The Lrp family of transcriptional regulators. Mol Microbiol. 2003 48(2) pp. 287-94

Mendeley group on stringent response

ppGpp mediates cross-talk between the stringent and acid stress responses

We know that stringent response alarmone ppGpp can do about anything, interacting with RNA Polymerase, translational GTPases, Obg GTPase, polynucleotide phosphorylase, DnaG primase, IMP dehydrogenase and adenylosuccinate synthetase to name a few. In net result is: production of ribosomes and tRNAs is halted, cell cycle is arrested, and amino acids are produced.

Well, now one more target was discovered, lysine decarboxylase Ldc1/CadA. Lysine decarboxylase is induced upon acid stress conditions and protects the cell catalyzing decarboxylation of L-lysine resulting in the polyamine cadaverine and carbon dioxide. CO₂ diffuses away and basic cadaverine keeps the intracellular pH, protecting from acidification.

Kanjee at al. solved the Lcd1 x-ray strucutre, and the protein turned out to be in complex with ppGpp. Enzymatic assays showed that ppGpp inhibits Lcd1, thus providing a link between the acid and stringent responses: these two are in a sense are mutually exclusive. During the stringent response ppGpp alters RNA Polymerase in such a way that genes involved in amino acid biosynthesis are predominantly transcribed, and during the acid stress response Lcd1 degrades lysine. Inhibition of Ldl1 by ppGpp stops amino acid degradation, shifting the balance even more towards the amino acid production.

References:

Kanjee U, Gutsche I, Alexopoulos E, Zhao B, El Bakkouri M, Thibault G, Liu K, Ramachandran S, Snider J, Pai EF, & Houry WA (2011). Linkage between the bacterial acid stress and stringent responses: the structure of the inducible lysine decarboxylase. The EMBO journal PMID: 21278708

Mendeley group on stringent response