Today we had an auditioning for the Master students (potential Master students that is). Something like that:

Shall see. Looked promising! They both knew what IF3 is... unexpected!

+1: An ancient family of SelB elongation factor-like proteins with a broad but disjunct distribution across archaea

Yay, one more paper is accepted: An ancient family of SelB elongation factor-like proteins with a broad but disjunct distribution across archaea. Gemma C Atkinson, Vasili Hauryliuk and Tanel Tenson, BMC Evolutionary Biology 2011, 11:22.

The nitty-gritty: we found a SelB relative which is not likely to bind and deliver selenocysteinyl-tRNA. It does something else, and we do not know what. tRNA binding domain and ribosome-binding interfaces are intact, but the G domain is messed up, so it might be a translational GTPase with no GTPase activity! For more details check out Gem's blog or... just read the paper, it is open access!

All ribosomes are equal, but some ribosomes are more equal than others

There are many ways of regulating translation - different mRNA structures, modifications of the canonical set of translation factors, specialized factors and so on. Well, you can also have different ribosomes and they may have different functions.

Here is a review about different ribosomal flavors. Main points:

1. rRNA can be modified differently under different conditions, thus resulting in ribosomes with different properties, such as thermal stability, affinity between 30S and 50S, etc. Here it an example of ITC used for studying these rRNA-modified ribosomes.

2. Ribosomes can have different rRNA and proteins when produced under different conditions. The most striking example is Haloarcula marismortui with 3 rRNA operones, out of which one codes extremely divergent copy which is expressed at high temperatures. You mess with it and bug becomes temperature sensitive.

3. Profs of functional differences of these ribosomes - here we do not have much. Stability - yes, see above. But function...

Well, we do have a bunch of proteomics data showing that in Saccharomyces cerevisiae different paralogues of r-proteins localize differently and are specifically involved in translation of some mRNAs.

A quick reminder - Saccharomyces cerevisiae had a whole genome duplication (WGD), thus they generally have loads of paralogues and thus are used to study evolution of proteins after duplication. Apart from yeast, WGD has happend in many other lineages (bony fish, plants), and it would be interesting to see what happens to r-proteins during WGD...

Back to the functionality of different ribosomes. One interesting possible functional regulation is discussed. Knocking out non-essential ribosomal protein Rps25 makes ribosomes incapable of translating some IRESes, though no effect on normal cap-dependent translation. Is expression of Rps25 regulated during viral invasion? No evidence of that as yet.

4. There are two possible ways of using different ribosomes:

First it can be that when the cell changes its ribosomal set, changes one flavor for another, no mixing - a global rewiring of the translational machinery. This seems to be the case for rRNA modification in bacteria - appropriate enzyme is induced  under certain conditions and all the ribosomes are modified, viola. Same for different rRNA genes in archaea.

Alternative approach is to have many different ribosomes for different mRNAs. This is seemingly what we have in yeast (see above). Specific localization of different ribosomes and use of different mRNA-specific factors would then ensure proper coupling of appropriate ribosome with the right mRNA. Different localization of different paralogues of r-proteins in Saccharomyces cerevisiae is shown experimentally, and these proteins have different requirements for assembly into the 80S.

PS: what all the ribosomes have in common is their color. They all are yellow.

References:

1. Gilbert VW. Functional specialization of ribosomes? (2011) Trends. Biochem. Sci. 2011 PIMD 21242088

2. Lopez-Lopez at al. Intragenomic 16S rDNA divergence in Haloarcula marismortui is an adaptation to different temperatures. (2007) J. Mol. Evol. 65, 687–696

3. Esguerra J. et al. Functional importance of individual rRNA 20-O-ribose methylations revealed by high-resolution phenotyping. (2008) RNA 14, 649–656

4. Komilli at al. Functional specificity among ribosomal proteins regulates gene expression. (2007) Cell PIMD 17981122

4. Kellis at al. Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae (2007) Nature v. 131 pp 557-571

Single Particle Tracking (SPT) in vivo: interpretation of trajectories

Using a single particle tracking approaches it is possible to approach diffusion trajectories with millisecond time resolution. Analyzing these and figuring out what exactly is happening in the cell is a rather complex undertaking. Here are two papers discussing analysis of particle diffusion in vivo:

1. van den Wildenberg et al. Biopolimers 2011 PIMD 21240922

Use of tensors for describing asymmetry of diffusion in the cell (i.e. along the long axis we have less confinement than along the short axis, thus mean square displacement (MSD) plateau is different). Modeling of different confinement geometries (tube, cube, sector) + adding repulsive or attractive potentials describing interactions between the particle and environment.

2. Hall and Hoshino Biophys Rev 2010 PIMD 21088688

Focuses on protein diffusion in the bacterial membrane, comparing experimental data for TatA diffusion with modeling. Again, confinement effects are discussed - SPT data are 2D projection of the 3D diffusion. They model random walk on the surface of bacterial cell was in the same way as Deich at al. PNAS 2004 PIMD 15522969.

Geometric constraints and 2D-to-3D projection affect MSD and CPD (cumulative probability distributions), but not enough to explain thir experimental data.

In order to account for the experimental deviations unexplainable by geometry effects they assume existence of slow and fast particles and add an estimate of the localization precision, and now they get a nice agreement with the experimental data. Roughly 50 / 50 slow and fast.

Effect of localization precision on SPT was earlier discussed in Martin et al. Biophys J. 2002 PIMD 12324428 story: "Apparent subdiffusion inherent to single particle tracking".

Z-RNA–binding domain Zα as ribosomal inhibitor: fishing for ribosomes

Feng at al. in NSMB show that Z-RNA (or DNA) binding domain Zα inhibits ribosomal function. Binds to the ribosome and inhibits it! Basically does what ribosome-binding antibiotics do - they bind, freeze the ribosome in some particular conformation and thus inhibit it. Viomycin can be a gerat example of that.

Better still, Zα seems to bind ribosomes nondiscriminantly (both bacterial and mammalian), so using a column with immobilized Zα you could purify ribosomes from whatever cells you have. Sounds fun, and, as I learned from the PI behind the paper - they are working on it, though this practical application is not mentioned in the original paper.

References:

Feng S, Li H, Zhao J, Pervushin K, Lowenhaupt K, Schwartz TU, & Dröge P (2011). Alternate rRNA secondary structures as regulators of translation. Nature structural & molecular biology PMID: 21217697

Ermolenko DN, Spiegel PC, Majumdar ZK, Hickerson RP, Clegg RM, & Noller HF (2007). The antibiotic viomycin traps the ribosome in an intermediate state of translocation. Nature structural & molecular biology, 14 (6), 493-7 PMID: 17515906

Using isothermal titration calorimetry for following subunit association

We use Isothermal Titration Calorimetry (ITC) for studying translational GTPases for quite some time now, and it turnes out one can do one more translation-related things with it: measure thermodynamics of subunit association with it (Osterman Biochimie 2011).

Quite amazing, actually. Sample is mixed at 200 rpm, ∼2 μM 50S are titrated with ∼11 μM 30S subunits, and yet seemingly there are no problems with precipitation and heat generated by it.

I would suspect that this means that one can follow initiation complex formation too...

References:

Ilya A Osterman, Petr V Sergiev, Philipp O Tsvetkov, Alexander A Makarov, Alexey A Bogdanov, Olga A Dontsova. Methylated 23S rRNA nucleotide m(2)G1835 of Escherichia coli ribosome facilitates subunit association. Biochimie 2011 PIMD 21237242

Darwin meets Gibbs: making a temperature-resistant protein

In order to perform its function, a protein should be properly folded. Therefore stability of this protein's native state is crucial for its function. Denatured protein can be toxic for the cell and requires specialised machinery to degrade it, thus compromising the cell's fitness. Having a denatured protein is not equal to just not having a functional one, it is equal to not having a functional one and having some costly junk.

Since stability is so crucial for protein function, it must leave its trace in the patterns of amino acid conservation. Bioinformatic studies show that there is a strong correlation between the Surface Accessible Area (SAA) of the residue and its conservation, or, simply speaking, conserved residues are mostly buried inside the protein. That sounds logical – the core should be more important for protein stability than its outer shell. The outer residues, on the other hand, can be rearranged in order to change the protein's binding selectivity and evolve new function. But lets get back to the core.

Basic thermodynamics relationships link protein stability to parameters like Gibbs free energy (ΔG), enthalpy (ΔH), entropy (ΔS), heat capacity (C, or, to be specific heat capacity at constant pressure, C_p) and absolute temperature (T). And adaptation to extreme temperatures gives us a striking example of thermodynamics shaping protein evolution. But first let us start with some basic theory - I know that sounds painful, but please stay with me for a moment!

Gibbs free energy is divided into enthaplic and entropic components (ΔG = ΔH - TΔS). By the definition of Gibbs energy, in order for the protein to be stable, ΔG of folding should be negative, and when it is positive, the protein unfolds.

Both of the components of ΔG change with temperature. Enthalpy changes linearly, with the proportionality coefficient being heat capacity (ΔC_p, ΔH(T) = ΔH(T₀) + ΔC_p(T-T₀)). Heat capacity is the amount of heat needed to change the temperature of protein by one degree.

Entropy also changes with temperature, though in a bit more complex way (ΔS = ΔS(T₀) + ΔC_pln(T/T₀)). When we combine the two components of ΔG, we get this:

ΔG(T) = ΔG(T₀) + ΔC_p(T-T₀) - ΔC_pTln(T/T₀)

This is a very interesting relationship. It gives ΔG(T) its characteristic shape with a maximum corresponding to the T of maximums stability, and two denaturation temperatures (on the graph below I plot –ΔG, rather than ΔG just so that the plot looks nicer).

We are all familiar with protein denaturation at high temperatures (we all boiled eggs!), but at lower temperatures? Well, this one happens as well, but very, very slowly, as all the reactions tend to at low temperatures, so we do not notice it that much. However, indeed, some proteins are better off when stored at -20C^o, than at -80C^o.

Heat capacity is intimately linked to the above-mentioned solvent accessible area (SAA). The reason for that is that it is the water surrounding the protein that gives it its heat capacity. Water molecules next to the protein are restricted in their freedom; they are essentially frozen, and ice, as we know, has tremendous heat capacity. When the protein denatures, its SAA increases, and so does the heat capacity. Heat capacity change upon denaturation in turn is determining the shape of folding ΔG dependence on temperature (see equation above).

And now we are primed to discuss how the extrermophylic proteins cope with high temperatures. One can imagine two obvious solutions. First, they could increase their stability (ΔG) (curve A). However, this would result in a bit too stable proteins that will be very hard to degrade, and this is not good for metabolism. Also, they will be too rigid, and flexibility is necessary for protein function. Second, they could move their temperature of maximum stability (curve B).

In reality they do something completely different! They decrease the ΔC_p instead, flattening the ΔG curve.

So how do they decrease the ΔC_p? Well this is all about the nature of the denatured state. ΔC_p is proportional to ΔSAA of protein unfolding, but proportionality is different for hydrophobic residues (these freeze water well, thus proportionality coefficient is high) and hydrophilic ones (these are similar to water in their nature, and thus do not restrict its movement too much, and the proportionality coefficient is lower).

Thermophilic proteins enrich the normally hydrophobic protein core with polar residues, forming salt bridges and dipole-dipole pairs. This results in a more rigid structure, thus you still pay in flexibility somewhat, therefore if there is no need for extreme temperatures, hydrophobic core is better.

Modifying the protein core is not an easy task since you need to compensate for one substitution with another (say, you have a positively charged residue, and now in order to compensate it you need a negatively charged one). Moving in the other direction (thermophilic to mesophilic) would be equally tricky. Therefore keeping your temperature stable – just like we do! – allows avoiding all these complicated thermodynamic matters altogether.

References:

Fu H, Grimsley G, Scholtz JM, & Pace CN (2010). Increasing protein stability: importance of ΔC_p and the denatured state. Protein science : a publication of the Protein Society, 19 (5), 1044-52 PMID: 20340133

Franzosa EA, & Xia Y (2009). Structural determinants of protein evolution are context-sensitive at the residue level. Molecular biology and evolution, 26 (10), 2387-95 PMID: 19597162

Drummond DA, & Wilke CO (2008). Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell, 134 (2), 341-52 PMID: 18662548

Geiler-Samerotte KA, Dion MF, Budnik BA, Wang SM, Hartl DL, & Drummond DA (2011). Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast. Proceedings of the National Academy of Sciences of the United States of America, 108 (2), 680-5 PMID: 21187411

Loladze VV, Ermolenko DN, & Makhatadze GI (2001). Heat capacity changes upon burial of polar and nonpolar groups in proteins. Protein science : a publication of the Protein Society, 10 (7), 1343-52 PMID: 11420436

DePristo MA, Weinreich DM, & Hartl DL (2005). Missense meanderings in sequence space: a biophysical view of protein evolution. Nature reviews. Genetics, 6 (9), 678-87 PMID: 16074985

Methicillin-resistant S. aureus (MRSA) JKD6229, freaking out and deadly

Stringent response, as I wrote here, here, and here, and here, is a central regulator of bacterial physiology, which decides whether to grow happily churning out new proteins without a care or to shut down all of the unnecessary systems, relocate all  resources to amino acid production and put up a fight. So what happens if a mutation hyper-activates it in Staphylococcus aureus? Wonder no more - the pathogen goes berserk!

The strain in question is called JKD6229 and it was reported in the resent paper by Gao at al. in PloS Pathogens. It was discovered among the clinical isolates, and rigorous analysis showed that it has continuously activated stringent response with elevated levels of ppGpp alarmone. Previous studies implicated stringent response in bacterial virulence, demonstrating that inhibition of this mechanism renders bacteria inapt for any sort of shenanigans (for review see Dalebroux et al. 2010).

Digging deeper, authors discovered that JKD6229 had a whole set of mutations making it nasty.

First was a set of mutations rendering it resistant to several antibiotics. Modified topoisomerase IV gave it resistance to cyproflaxacin, RNA polymerase was altered to give it resistance to rifampin and ribosomal large subunit methyltransferase RlmN had an insertion making it insensitive to linezolid. It short - this bug was really, really hard to kill. 

Second, authors report that the bug had mutated RelA, which had low activity in ppGpp hydrolysis, leading to accumulation of high ppGpp levels. High ppGpp level inhibits ribosome synthesis and results in slow growth, so the strain was dubbed as "Small Colony Variant". At the very same time, all the defense mechanisms were on high alert, and JKD6229 was not expecting anything good from the world around it. It was not growing fast, but it was hard to kill and it was fighting back. 

One very, very pissed off bacterium. 

And there are several ways to deal with it.

First, you can kill it (see my earlier account on the development of antibacterials). Surely, JKD6229 will be trying hard to survive, accumulating even more resistance markers.

Second, you can try calm it down, make it non-virulent. This approach is an emerging strategy in development of antibacterials - inhibiting virulence, but not killing the bug. There are two potential benefits. First, lower selective pressure for resistance mutants since in most of the tissues virulence is not needed for survival. Second, potentially higher selectivity - only the bad bugs perish, and the good ones live. However, there are problems with this approach. Virulence mechanisms are very diverse, and therefore drugs targeting them will have a very narrow spectrum. And usually you do not know exactly what sort of bug is causing the problem. Development of rapid diagnostic methods can fix this, and then 'narrow spectrum' becomes 'selectivity', and this is a good thing.

PS: Wait! Mutations in Staphylococcus aureus RelA? Well, surely not. Staphylococcus aureus does not have RelA. The protein authors refere to is Rel, a bi-functional protein capable of both producing and hydrolyzing ppGpp, as opposed of RelA, which is able only of ppGpp syntheses. For more information on phylogenetic relationships between RelA, Rel and SpoT see Mittenhuber 2001.

References:

Gao W, Chua K, Davies JK, Newton HJ, Seemann T, Harrison PF, Holmes NE, Rhee HW, Hong JI, Hartland EL, Stinear TP, & Howden BP (2010). Two novel point mutations in clinical Staphylococcus aureus reduce linezolid susceptibility and switch on the stringent response to promote persistent infection. PLoS pathogens, 6 (6) PMID: 20548948

Dalebroux ZD, Svensson SL, Gaynor EC, & Swanson MS (2010). ppGpp conjures bacterial virulence. Microbiology and molecular biology reviews : MMBR, 74 (2), 171-99 PMID: 20508246

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

Escaich S (2010). Novel agents to inhibit microbial virulence and pathogenicity. Expert opinion on therapeutic patents, 20 (10), 1401-18 PMID: 20718591

Mendeley group on stringent response

Ribosome-assisted protein UN-folding

"Stand still, do not move! I gave you life, I will also kill you!" said Taras, and, retreating a step backwards, he brought his gun up to his shoulder. Andrii was white as a sheet; his lips moved gently, and he uttered a name; but it was not the name of his native land, nor of his mother, nor his brother; it was the name of the beautiful Pole. Taras fired.

Taras Bulba, Nikolai Vasilievich Gogol

Ribosome makes proteins, we all know that. But producing a string of amino acids is just a half it. In order to be functional, nascent protein should fold correctly. And the ribosome takes care of that as well.

First, building blocks of the protein - alfa helices, for instance - are formed already in the ribosomal tunnel where they are protected from the hostile environment. When the protein emerges outside of the tunnel, it is greeted by the ribosome-associated chaperons, which help it to fold. Moreover, by cleverly fine-tuning translational rate, protein syntheses machinery allows protein domains to be produced one by one with pauses in between, ensuring that they fold correctly.

And here is a surprise. A fresh paper in JACS by O'Brian and colleagues suggest that the ribosome destabilizes unfinished proteins dangling out of the ribosome tunnel. Coarse-grain simulations allow dissecting the nature of this phenomenon.

Stability of the protein is reflected by the Gibbs free energy of folding (ΔG). Gibbs free energy in turn can be divided into and enthalpic (ΔH) and entropic components (TΔS), ΔG = ΔH - TΔS. When the protein is close to the ribosome, it pays for it in freedom (obviously, it can't move about freely any more), which means that the total number of available microstates is lower. And S is dependent on the total number of these microstates, thus it goes down, bringing down the Gibbs free energy. 

Moreover, it is not just thermodynamics, it is kinetics too: ribosome decreases folding rate, and unfolding rate increases. This is keeping with the basic definitions relating the equilibrium constant (K) with the rate ones (k₊₁,  k_-1), ΔG = - RTln(K), K = k₊₁ / k_-1.

So why is the ribosome so nasty to its progeny? Well, I guess the answer is - it just can't help it. The effects described above are simple consequences of the fact that nascent protein has to be attached to the ribosome during translation, and this results in loss in available microstates and so on (see above). And translational machinery is trying hard to be kinder to nascent proteins, cleverly designing the ribosomal tunnel, employing chaperones and waiting for the domains to fold before moving to the next one.

But is the ribosome doing anything good to the folding protein? And yes, it does. It stirs the folding pathway towards more native-like intermediates, guiding the direction of folding so that it starts from the N-terminus - the part that gets translated first. And again, this beneficial effect is done again by restricting proteins' freedom - freedom to sample configurations diverging from the productive folding path. 

Isn't it a great example of excellent parenting?  

References:

O'Brien EP, Christodoulou J, Vendruscolo M, & Dobson CM (2011). New Scenarios of Protein Folding Can Occur on the Ribosome. Journal of the American Chemical Society PMID: 21204555

Playing chicken, single molecule

Many things happen to DNA. Proteins bind, slide along, dissociate. Sometimes they bump into each other, and then... what happens then?

This was exactly the question adressed in Finkelstein at al., Nature 2010. They were particularly interested in a bacterial protein called RecBCD, which is a powerful helicase. Using single-molecule microscopy they
had a look at what happens when RecBCD rams into some other protein.

And they had several to look at. RNA polymerase was the first one, and this is a formidable roadblock, and yet - RecBCD pushed it off the DNA with ease. Here are the actual images:

RecBCD sliding RNA polymerase along the DNA (76.5 %):

RecBCD ejecting RNA polymerase (8.5 %):

And RecBCD being stalled by RNA polymerase (rare events!) (15 %):

Then they tried other proteins, EcoRI endonuclease and lac repressor, and again, RecBCD was victorious over and over. Only the mighty nucleosome (never mind that it is a eukaryotic protein and it never met RecBCD before!) managed to put up a fight - 24% of the head-on collisions resulted with RecBCD being stalled, 11% resulted in nuceosome ejection and in remaining 65% RecBCD was sliding the nucleosome along the DNA.

What next? Well, now authors are preparing for experiments on RecBCD head-on collisions with Higgs bosons in the LHC.  I bet on RecBCD.

PS: it is all very convenient that the authors happened to study RecBCD - neat story, their protein is stronger than all the others, yay! But wat if they would have started with some lame one, like PNA polumerase? But hey! I never write my results in the order I get them... do you? Did THEY?

References:

Finkelstein IJ, Visnapuu ML, & Greene EC (2010). Single-molecule imaging reveals mechanisms of protein disruption by a DNA translocase. Nature, 468 (7326), 983-7 PMID: 21107319

human vs yeast

I am reading loads of yeast genetics papers recently, and I wonder... Imagine yeast getting sapient, and starting doing science. Genetics, in particular. On humans, actually.

For instance they could do some screens for temperature-sensitive mutants (huge, massive saunas in action). Imagine the figures in the papers to go along with this sort of experiments. Some allele crossing experiments in search of synthetic lethality - that would be great as well. With photos of F0 and F1. Auxotrophic humans with plasmids complementing their deficiency as useful tools - complementation experiments will be particularly cruel - no complementation - well, tough luck!

I am really glad yeast are rather silly and not very proactive.

Stringent response - why are we still in the middle ages? Part II.

This is a continuation of my previous post on this subject, see here.

So here are some more reasons for investigation of stringent response being such a painful and slow-going venture. Let us go through the approaches we have.

Microbiology

Here we have a bunch of problems. Stringent response is very central and messing with it has very pleortopic effects which is not helping. Doing knock-outs of RelA and SpoT is a tricky business, and compensatory mutations can and do arise. However, I would say that microbiological data are the best part of the data available, especially since different model organisms were studied recently and work on different RSH proteins is done, linking RSH proteins to different targets (see Battesti 2005, Vinella 2005, Persky 2009,  Lemos 2007, Gatewood 1010, and Maciag 2010).

Definitely, all the best things in the stringent response field are done using the microbiological approach. Just as they were done 10 years ago. Or 20. This is a bit sad.

Structural methods

Here we have more serious problems and less succes stories. RSH proteins are horrible to work with, they tend to precipitate a lot. Therefore the only structural insight we have so far is x-ray of the truncated Rel protein (Hogg 2004) - but this is only one representative of the RSH family which is actually much bigger than what is presented in Mittenhuber 2001! we have no idea as to how RelA or SpoT look like, we can only guess using homology modeling using the Rel structure.

No cryoelecton reconstructions are available, and the reason is simple: in order to have a good cryoEM sample, you need to have high occupancy (high % of RelA-bound ribosomes in this case), and for that to happen RelA needs to bind really tight (working concentrations are roughly 50 nM 70S). Of course, one can hammer the ligand (RelA in our case) in just by increasing its concentration - it is simply a matter of  Le Chatelier's principle! - but again, you add loads of RelA and it precipitates. Bummer!

How about crosslinking? This is a bit more promising, but still - there are issues. RelA:tRNA crosslink is a hard one, since standart procedure of modifying the by oxidation tRNA CCA which was used for crosslinking with FMT (Hountondji 1980, Gite 1997) does not work for RelA: it does not want to interact with with the modified tRNA any more (Sprinzl 1976)!

Biochemistry

As I say, RelA is a nasty protein to work with. Rel seems to be a bit better, and considerable progress was done using it (Sajish 2009, Avarbock 2005). Some good stuff was done with E. coli protein too (Jenvert 2007), but unfortunately this lab has already folded. Actually that seems to be a trend - it seems to be unlikely for the lab to continue working on RSH proteins in vitro for a long time. Very nice proteins, yes.

The main problem here is that all biochemistry is done with greatly simplified in vitro systems - people use just 70S and mRNA, and tRNA; no initiation or pre-transclocation complexes which would be much more of a natural substrate. This is the direction where we are going.

As to SpoT, no one can purify nowadays, the only reports of people doing this (and we do not really know what they purified since no masspec of the SDS PAGE band was done) are dating from late 70s (Ma 1979). And this really hinders this direction.

Single molecule methods

Well, see this. SPT investigations of RelA are coming, but and the main problem here is - surprise! - microbiology. Getting the strains right is really hard and takes lots of effort and control, and it is very, very easy to end up working with some very strange mutant.

What we really need there is some sensor for in vivo concentrations of ppGpp in the individual cells so that we could combine RelA tracking data with ppGpp production. There is a sensor for ppGpp (Rhee 2008), but getting inside E. coli... that would be a tricky one.

Hight throughput approaches: microarrays, libraries...

They exist, and things are done (Traxler 2006, Traxler 2008, Durfee 2008, Traxler 2011 and Balsalobre 2011). This seems to be a very promising approach able to resolve kinetics of stringent response developing during starvation: which geners are affected, in which order. Combined with mutational analysis it really holds promise for in vivo investigations of stringent response (for more detailed discussion see here).

Mendeley group on stringent response

LUCA in pictures

If you still wonder how the last common ancestor (LUCA) looked like, wonder no more. There is a very good rendering of it made, I would guess, in paint and some text to go with it here.

You pay in ribosomes for proteins

Everything costs. When cell grows, it needs energy and in needs materials. By the end of the day it comes down to accounting: if you need to make N proteins, you will need X ATPs molecules, Y aminoacids and Z ribosomes to do the job. And of all these ribosomes are the most expensive to make: they are huge, made of RNA and if you want to make proteins fast, you need lots of ribosomes!

So research team led by famous systems biologist Uri Alon decided to quantify the cost of making a protein. In order to do so, they forced E. coli producing Green Fluorescent Protein (GFP) which is inert and easy to quantify. They figured out that early in the exponential phase the cost of GFP (that is decrease in growth rate associated with production of a given amount of GFP) is high, but later on it markedly recreases!

This observation makes immediate sense: first you need to produce the tools for producing GFP (ribosomes, energy in the form of ATP etc.) and if instead of this you make GFP this GFP comes at a high prise. Corroborating with this logic, they figured out that if you transfer bacteria from energy-reach media to energy-poor, the price for GFP is low: well, you accumulated all these ribosomes during the good times, so now you can make some GFP cheap.

There could be an interesting connection here with another resent paper where in yeast it was shown that the cost of GFP is dramatically different for stable and denaturation-prone variants (for brilliant discussion of this paper see this post in It Takes 30). Is GFP equally stable in E. coli during the early and late exponential phase? Could it be that the effects observed here are reflecting mere change in GFP stability? Intracellular conditions do change in E. coli under different conditions, so it is possible that GFP is not always equally stable, and this may affect its physiological cost. Surprisingly, another report claims that in E. coli aggregated and soluble LacZ have very similar cost, which to some extent dispels my worries about GFP stability and cost.

The read-out for GFP quantification could be affected by cellular milieu as well: judging from my experience, GFP is definitely not always equally bright, and this could affect estimates of GFP concentration and thus the estimates of its physiological cost.

Discovering differences in the GFP cost in early and late exponential phase prompted the authors to try figuring out what cellular system is behind it. And they had a very good initial guess. In bacteria adaptation to changes in availability of food are regulated by the stringent response mechanisms, with RelA and SpoT proteins doing the job (see my previous posts on that subject, see 1 and 2). RelA produces ppGpp molecule that compels the cell to stop producing ribosomes and concentrate on aminoacid production, and SpoT mostly degrades ppGpp: too much of it would lead to complete inhibition of ribosomal production and eventually - death.

Therefore it is only logical that in the paper in question different knock-out strains missing RelA and SpoT were tested, and indeed, stringent response machinery turned out to the the key to radical changes of the protein cost during different stages of bacterial growth.

And here is the catch.

One of the strains they used was SpoT(-) RelA(+) strain, that is one having NO SpoT and allegedly INTACT RelA. As we discussed above this bug should be very much dead, and as yet no one managed to produce this strain. So what's about the strain presented in the paper then?

Well, there are many options. When you want, really want to knock out a gene, you finally succeed. However, bacteria want to live, and you select the ones with mutations that compensate for the knock-out of the gene you have. For instance, you can mutate main target of ppGpp, the RNA polymerase and make it insensitive to regulation. Aslo, you can mutate RelA and make it inactive. And there are several other possible compensatory mutations... In order to notice these changes in the strain you made you really need to run a lot of tests, and the authors did not.

So here is another example how bacteria are cleverly trying to fool systems biology approach (another example is here).

Update: the SpoT knock-out strain used in the original paper indeed was iffy, it had compensatory mutations in RelA and an erratum was published, which I discuss here.

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), 758-67 PMID: 20434381

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

Geiler-Samerotte KA, Dion MF, Budnik BA, Wang SM, Hartl DL, & Drummond DA (2010). Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast. Proceedings of the National Academy of Sciences of the United States of America PMID: 21187411

Plata G, Gottesman ME, & Vitkup D (2010). The rate of the molecular clock and the cost of gratuitous protein synthesis. Genome biology, 11 (9) PMID: 20920270

Mendeley group on stringent response

Viral nature of the mitochondrial RNA polymerase

Mitochondria contain their own genome, and they transcribe it. Since mitochondria are of bacterial origin, one would expect that their polymerase would be similar to that of bacteria. And it is so the case for chloroplasts, which are also of bacterial origin.

However, mitochondrial polymerase not homologous to that of bacteria, or, for that matter, to cytosolic eukariotic polymerases. It is homologous to... polymerases of T phages, T3 and T7!

However, it is slightly modified. It has an extension at the N-terminus, and this extension is highly variable. Using this extension yeast mitochondrial polymerase interacts with protein Nam1p, which is involved in mRNA stabilization. Nam1p in turn interacts with the whole bunch of mitochondrial membrane proteins which organise translation and following assembly of the proteins constituting the core of cytochrome c oxidase complex (COX).

In this way all the steps of COX formation are connected in the mitochondria: polimerase binds to Nam1p, Nam1p binds to membrane-bound translational enhancers, enhancers bind mRNA and the ribosome, the ribosome itself binds to membrane, and translated protein is inserted in the membrane. There is even a special term for this sort of coupled transcription, translation and insertion - transertion. Very neat system!

Amazingly, different eukaryotes reinvent this system in different ways. Most of the components are clade-specific, and since the system is so very interconnected, it is is very, very different in different eucaryotes. Therefore when yeast geneticists say that they are studying Saccharomyces cerevisiae as a model system in order to understand human mitochondrial translation they are... well... how should I say it? well, they are being over-optimistic.

PS: and phages and mitochondria are trading polymerases both ways! A cyanophage was discovered that has an ex-mitochondrial DNA (not RNA) polymerase!

References:

Masters BS, Stohl LL, & Clayton DA (1987). Yeast mitochondrial RNA polymerase is homologous to those encoded by bacteriophages T3 and T7. Cell, 51 (1), 89-99 PMID: 3308116

Rodeheffer MS, Boone BE, Bryan AC, & Shadel GS (2001). Nam1p, a protein involved in RNA processing and translation, is coupled to transcription through an interaction with yeast mitochondrial RNA polymerase. The Journal of biological chemistry, 276 (11), 8616-22 PMID: 11118450

Naithani S, Saracco SA, Butler CA, & Fox TD (2003). Interactions among COX1, COX2, and COX3 mRNA-specific translational activator proteins on the inner surface of the mitochondrial inner membrane of Saccharomyces cerevisiae. Molecular biology of the cell, 14 (1), 324-33 PMID: 12529447

Gagliardi D, Stepien PP, Temperley RJ, Lightowlers RN, & Chrzanowska-Lightowlers ZM (2004). Messenger RNA stability in mitochondria: different means to an end. Trends in genetics : TIG, 20 (6), 260-7 PMID: 15145579

Yi-Wah Chan, Remus Mohr, Andrew D. Millard, Antony B. Holmes, Anthony W. Larkum, Anna L. Whitworth, Nicholas H. Mann, David J. Scanlan, Wolfgang R. Hess and Martha R. J. Clokie. Discovery of cyanophage genomes which contain mitochondrial DNA polymerase. Mol Biol Evol (2011) doi: 10.1093/molbev/msr041

GppCp (GMPPCP) Jena Bioscience NU-402-25 / NU-402-5

GTPases can be inhibited by non-hydrolizable GTP analogues, such as GDPNP or GDPCP, and these are commercially avaliable. So here is my question:

Does it count as a citation if you get cited in the product description leaflet? I guess it does not... but can I get a discount, please?

See ref 1 here.

How to swap a gearbox for a new model right on the highway

Protein biosyntheses is central a hub for cellular physiology: proteins are essencial for all the cellular processes. Therefore changing something really important in translational machinery is really hard: you still need to continue producing proteins! Swapping an important translational factor for another one? That sounds impossible, but this is exactly what happend with eEF1A - eukaryotic factor that brings aminoacylated tRNA to the ribosome. Moreover, it happened several times!

It was indeed swapped for a similar, yet different protein EFL (EF-Like) several times during eukaryotic evolution. The main difference between EFL and eEF1A is in theis GTPase cycle. eEF1A, just like its bacterial counterpart EF-Tu, needs a specialized factor in order to regenerate it from the GDP to GTP-bound state (Guanine nucleotide Exchange Factor, GEF). EFL does not need a GEF, so it is in a sense simpler.

Loosing a GEF seems to be a common theme in the evolution of translational GTPases. Mitochondrial EF-Tu lost its GEF (EF-Ts) in Saccharomyces cerevisiae, though retained that in human and S. pombe! Moreover, it is possible to select mutants in yeast eEF1A which would confere GEF-independence, turning into something like EFL.

Sometimes regulating GTPases is just too much to ask for and Nature cuts corners.

References:

Keeling PJ, & Inagaki Y (2004). A class of eukaryotic GTPase with a punctate distribution suggesting multiple functional replacements of translation elongation factor 1alpha. Proceedings of the National Academy of Sciences of the United States of America, 101 (43), 15380-5 PMID: 15492217

Rosenthal LP, & Bodley JW (1987). Purification and characterization of Saccharomyces cerevisiae mitochondrial elongation factor Tu. The Journal of biological chemistry, 262 (23), 10955-9 PMID: 3301847

Chiron S, Suleau A, & Bonnefoy N (2005). Mitochondrial translation: elongation factor tu is essential in fission yeast and depends on an exchange factor conserved in humans but not in budding yeast. Genetics, 169 (4), 1891-901 PMID: 15695360

Ozturk SB, & Kinzy TG (2008). Guanine nucleotide exchange factor independence of the G-protein eEF1A through novel mutant forms and biochemical properties. The Journal of biological chemistry, 283 (34), 23244-53 PMID: 18562321

mitochondrial mRNA UTRs: insanity, lunacy and absurd

mRNA in general have 5'UTR (untranslated region) followed by ORF (open reading frame) and then comes 3'UTR. Both UTRs regulate mRNAs stability, localization, translational efficiency. In eukaryotes cytozolic mRNAs have 3'UTR polyA, which regulates mRNA stability and translational efficiency, and 5'UTR which regulates efficiency of translation.

Mitochondrial mRNAs... it's a mess.

1) 3'UTRs are regulating localization (i.e. transport into the mitochondria, (Pattini 2003 PIMD 15376913)) and in mRNA stability (Gagliardi 2004 PIMD 15145579). Mechanisms of mRNA stabilization seem to be very, very different in plants (polyA destabilizes, like it does in bacteria!), yeast (no polyA at all, just like it is in yeast cytozolic mRNAs!) and mammals (polyA stabilizes, just like it does in eukaryotic cytozolic mRNAs!). 3 different approaches?! It is about as insane as it gets, really.

In mammals 3'UTRs are short (Ojala 1981 PIMD 7219536), unlike in plants and yeast, where 3' UTRs are long.

2) 5'UTRs are regulating translation (mRNA-specific enhancers of translation bind to them and thus regulate translation initiation) and localization within the mitochondria, thus coupling translation and insertion of the mRNA into the membrane. Most of the proteins that are translated in yeast mitochondria are intermembrane proteins involved in respiration and ATP production (review Towpik 2005 PIMD 16341268), thus coupling translation and insertion is a must. And indeed, when multisubunit complexes are assembled, translation of the individual subunits is geometrically coordinated (Naithani 2003 PIMD 12529447).

All this is well and good, but there are issues. Somehow investigation of 3' and 5'UTRs is a big thing in plant mitochondria, and not much is done nowadays with yeast or mammals. Or at least it is not easy to find. Second, no one tried systematically comparing UTRs from different organisms.

What I have dug out by now is this: in plants 5'UTRs are long, and there is a lot of experimental material here using 5'-RACE (Froner 2007 PIMD 17488843, Kuhn 2005 PIMD 15653634). In yeast - long 5'UTRs as well (review Costanzo 1990 PIMD 2088182), though much less studied experimentally. In mammals 5'UTRs are claimed to be short, at least in humans (Montoya 1981 PIMD 7219535). Here signals for mRNA-specific initiation enhancers are located within the ORF.

Is plant and yeast mitochondria translation radically different? Why did mammalian mitochondrial mRNA loose 5'UTR regulation? If yes, where is the watershed? What are the differences in the yeast+plants mitochondirial machinery vs mammalian?

Mammalian mitochondrial genome is super-streamlined, cutting corners where possible (review Attardi 1985 PIMD 3891661), so that could be a reason for the loss of 3' and 5'UTR. But what drives this minimization? Why trying THAT hard?

Experiments on mitochondrial translation seem to be done on different systems in different areas of research: yeast are used for identifying initiation enhancers and studying genetics and molecular biology of translation regulation, in plants 3' and 5' UTRs are extensively mapped, and in mammals using very, very simplified translational system (tRNA, IF2, IF3, EF-Tu and EF-G) some rudimentary biochemistry is done. This does scitsofrenic devision of labor is in keeping with the mitochondrial spirit indeed.

PS: mitochondrial ribosomes are also very, very strange.

Reviews:

Mitochondrial evolution: Karlberg 2003 PIMD 12728281
Mitochondrial and chloroplast translation: Gillham 1994 PIMD 7893142
Mitochondrial translation and desease: Perez-Martinez 2008 18991722
Plant mitochondrial translation: Binder 2003 PIMD 12594926, Hoffmann 2001 PIMD 11642360
Yeast mitochondrial translation: Costanzo 1990 PIMD 2088182, Dieckmann 1994 PIMD 8206703
Mammalian mitochondrial translation: Spremulli 2004 PIMD 15196894

mitochondrial translation - complete mess

Mitochondria have their own genome, their own translational machinery and their own mRNAs which code a handful of proteins. Most of the proteins come from the cytoplasm, but some get translated inside the mitochondria. And this is done in amazingly weid way...

Bacteria - mitochondrial ancestors - have 3 initiation factors, IF1, 2 and 3, and all of these are absolutely necessary for the bacterial viability.

Mitochondria do not have IF1 (all mitochondria), and unlike mammals, yeast ones do not have IF3! Also they seem to use mitochondria-specific initiation factor AEP3. Do mammals have AEP3 homologue? Worth checking... To make things more complicated, mitochondria have their own special mRNA-specific factors... and again, there is a catch. Yeast mRNA have long 5' UTRs (untranslated regions), and mammals have short, they basically have leaderless mRNAs (I'd love to see a good reference for that! THIS is a little bit out of date...) - therefore I would expect that these mRNA-specific IFs work differently in yeast in mammals. So yeast and mammalian mitochondrial translation seems to have very, very different translational apparatus. Isn't is weird?

Another amazing thing is that translation and protein localization are tightly linked in mitochondria. mRNA-specific initiation factors (i.e. Pet111p) and above-mentioned AEP3 interact with the mitochondrial membrane (most of the mitochondrially-translated proteins are membrane proteins), so that translation is localized where the proteins should go.

stringent response... in Drosophila?

If you happened to be a bacteria, you must prepare for trouble: shortage of food, temperature changes and so on. And when the trouble comes, you should respond accordingly. Stringent response system does exactly that: it integrates several input sources (aminoacid, fat and carbon limitation, temperature upshift to name a few) and alters concentration of the alarmone molecule ppGpp (GDP with 2 extra phosphates attached to the sugar moiety).

ppGpp in turn regulates everything: transcription, translation, replication. Therefore it is a must to control ppGpp levels very precisely, and to that end bacteria have proteins which produce ppGpp (RelA), (mostly)degrade it (SpoT) and do both (Rel). All together these proteins are called RelA-SpoT homologues (RSH).

All this is in bacteria... how about eukaryotes? Well, organelles have RSH, with some of them being rather peculiar in terms of signals they respond to, such as Ca++ sensitive OsCRSH1 RSH from chloroplasts. But what about cytozolic proteins?

Exactly that was discovered in 2010 - cytozolic RSH Mesh1 in drosophila. It is a small protein, capable of only ppGpp hydrolysis, which it does specifically: it takes only this nucleotide among the variety of different ones tested. Knock-out has a strong and specific phenotype, suggesting that the Mesh1 is important and functional. Moreover, Mesh1 can substitute SpoT in bacteria. X-ray structure of the protein was solved, so the paper went into Nature Structural Biology.

The big question here is how did Mech1 end up in eukaryotes and why is it retained there? How do you transfer such a complex system as stringent response from bacteria to eukaryotes?

With RSH proteins one can not just have a ppGpp-producing one - in this case you produce ppGpp, it accumulates and the bug dies. Therefore usually bugs have Rel - it both makes and degrades ppGpp, so the whole system is in one protein. Mesh1 degrades ppGpp, and no cytozolic RSH capable of synthesis were identified in eukaryotes so far... so what is Mesh1 doing? what is it degrading?

May be there is some ppGpp-producing protein which is not homologous to RSH, and this s the source of ppGpp which Mesh1 degrades. However, attempts to spot ppGpp during aminoacid deprivation were invariably unsuccessful. So it may be Mesh1 actually does something else then ppGpp hydrolysis.

References:

Sun D, Lee G, Lee JH, Kim HY, Rhee HW, Park SY, Kim KJ, Kim Y, Kim BY, Hong JI, Park C, Choy HE, Kim JH, Jeon YH, & Chung J (2010). A metazoan ortholog of SpoT hydrolyzes ppGpp and functions in starvation responses. Nature structural & molecular biology, 17 (10), 1188-94 PMID: 20818390

Mitkevich VA, Ermakov A, Kulikova AA, Tankov S, Shyp V, Soosaar A, Tenson T, Makarov AA, Ehrenberg M, & Hauryliuk V (2010). Thermodynamic characterization of ppGpp binding to EF-G or IF2 and of initiator tRNA binding to free IF2 in the presence of GDP, GTP, or ppGpp. Journal of molecular biology, 402 (5), 838-46 PMID: 20713063

Maciag M, Kochanowska M, Lyzeń R, Wegrzyn G, & Szalewska-Pałasz A (2010). ppGpp inhibits the activity of Escherichia coli DnaG primase. Plasmid, 63 (1), 61-7 PMID: 19945481

Gralla JD (2005). Escherichia coli ribosomal RNA transcription: regulatory roles for ppGpp, NTPs, architectural proteins and a polymerase-binding protein. Molecular microbiology, 55 (4), 973-7 PMID: 15686546

Pollard JW, Lam T, & Stanners CP (1980). Mammalian cells do not have a stringent response. Journal of cellular physiology, 105 (2), 313-25 PMID: 7462330

Buckstein MH, He J, & Rubin H (2008). Characterization of nucleotide pools as a function of physiological state in Escherichia coli. Journal of bacteriology, 190 (2), 718-26 PMID: 17965154

Mendeley group on stringent response