January 12, 2015
The following small summary on a protein complex called EJC was inspired by a lecture given by Hervé Le Hir (ENS, Paris) at the Friedrich Miescher Institute in Basel in November 2014:
After transcription an mRNA becomes processed, exported, stored or transported, translated and degraded. Several multimeric protein complexes carry out these tasks and readily transform the initially naked mRNA into a large messenger ribonucleoprotein (mRNP) complex. For a long time it was believed that the described functional steps are occurring sequentially and relatively independent of each other. However, more recently it became clearer that many events during the life of an mRNA leave permanent protein marks which can influence the efficiency or occurrence of subsequent functional events and which are dependent on the sequence context. One of the first mRNPs that forms in the nucleus after transcription is the splicing machinery. It splices introns out of the pre-mRNA molecule, thereby creating the mature mRNA. The splicing reaction, however, leaves a relatively stable mark on the newly created spliced mRNA: The Exon Junction Complex (EJC).
What is an EJC and where is it formed?
The EJC is a multiprotein complex that forms as a consequence of splicing upstream of exon-exon junctions. Although the EJC’s composition is dynamic it contains four core proteins: The RNA helicase and eukaryotic initiation factor 4A3 (eIF4A3), metastatic lymph node 51 (MLN51), and the heterodimer Magoh/Y14. eIF4A3 possesses two ATP-dependent RecA domains which bind RNA in a “clamp-like” fashion. Magoh/Y14 seems to prevent conformational changes of eIF4A3, while the conserved SELOR domain of MLN51 also binds to the RNA and in addition stabilizes the RecA clamps further (1). This tetrameric core now serves as a platform allowing for the binding of other factors that catalyze different regulative processes during export, transport and translation of the mRNP. By using both fluorescence and electron microscopy approaches it became possible to narrow down the assembly zone of the tetrameric EJC core to nuclear punctuate regions termed perispeckles (periphery of nuclear speckles). All EJC subunits are enriched and fully assembled in these structures while MLN51, Magoh, and Y14 mutants fail to localize to the perispeckle region. Furthermore, perispeckles seem to contain polyA mRNAs and transcripts which are actively undergoing splicing (2). These nuclear compartments had earlier already been described as storage and assembly cites for splicing factors which highlights the possibility that EJC proteins join in a co- and post-splicing manner.
Which processes does the EJC catalyze?
Splicing of certain long intron containing mRNAs is affected by EJCs and the complex also seems to be responsible for the catalysis of one form of alternative splicing. Furthermore, the EJC is implicated in mRNA transport and plays an important role during nonsense-mediated decay (NMD) of transcript possessing a premature stop-codon. When such an erroneous codon is present, some EJCs remain bound to the mRNA because they are not displaced by the progressing ribosome and become bound by the up-frameshift factors Upf1, Upf2, and Upf3. Together these proteins trigger mRNA decay (3). For a long time it has been known that the presence of introns enhances the translation of a construct when compared to a similar construct that is lacking introns. Another
important task of EJCs therefore seems to be the enhancement of translational efficiency of spliced mRNAs. This has mainly been demonstrated by tethering all four EJC components artificially to mRNAs in Xenopus oocytes (4). The molecular details of this process have, however, remained elusive until recently.
How does the EJC influence translation?
It has been described that the EJC is the functional linker between splicing and an enhanced translation efficiency. Recently it emerged that the EJC component MLN51 might mediate this relationship by interacting with the translation initiation factor eIF3 (5). First of all it was observed that overexpression of MLN51 enhances translation of spliced luciferase reporters versus identical non-spliced reporters. Furthermore, MLN51 also enhances translation if the remaining three EJC components are not present. Immunoprecipitations then showed that several translation initiation factors and ribosomal subunits can bind EJC components, but only MLN51 binds via its SELOR domain to the initiation factor eIF3. This interaction might lead to a stabilization of the mRNP complex so that translation can initiate successfully. One problem, however, persists: Several studies have described that the ribosome displaces the EJC from the mRNP complex during the first round of translation. The question whether an upregulation of the first round of translation is sufficient to explain the observed positive effect on translation efficiency by the EJC is therefore still open. One explanation could be that EJCs increase the absolute pool of translated mRNAs via MLN51. Alternatively, MLN51 might increase the total number of initiating ribosomes on the single mRNA before the EJCs become displaced. It might also be possible that MLN51 survives on the mRNA after displacement, and thereby is able to initiate subsequent rounds of translation. This hypothesis seems probable since the other three EJC components are not required for an increased translation efficiency. Since a large number of factors have been described that peripherally bind EJCs (1) the molecular mechanism of translation enhancement is likely be more complex and more functional interactions of MLN51 need to be identified. The past years of research have, however, shown that the sequence context and all lifecycle steps of an mRNA are closely linked and the EJC serves as an interesting example for the complexity of an mRNAs life.
1. Le Hir H, Andersen GR. Structural insights into the exon junction complex. Curr Opin Struct Biol. 2008 Feb;18(1):112–9.
2. Daguenet E, Baguet A, Degot S, Schmidt U, Alpy F, Wendling C, et al. Perispeckles are major assembly sites for the exon junction core complex. Mol Biol Cell. 2012 May 1;23(9):1765–82.
3. Gehring NH, Kunz JB, Neu-Yilik G, Breit S, Viegas MH, Hentze MW, et al. Exon-junction complex components specify distinct routes of nonsense-mediated mRNA decay with differential cofactor requirements. Mol Cell. 2005 Oct 7;20(1):65–75.
4. Wiegand HL, Lu S, Cullen BR. Exon junction complexes mediate the enhancing effect of splicing on mRNA expression. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11327–32.
5. Chazal P-E, Daguenet E, Wendling C, Ulryck N, Tomasetto C, Sargueil B, et al. EJC core component MLN51 interacts with eIF3 and activates translation. Proc Natl Acad Sci. 2013 Apr 9;110(15):5903–8.
April 21, 2014
Is it possible to quantify the impact that a certain research project has on society? And is it beneficial to attach a societal relevance to research in general? In times of tight research budgets it becomes increasingly important that scientists and universities are able to demonstrate what the impact of their research is. A very important aspect is for example the ability to interact with “the society” in order to find out what current needs are or to convince the taxpayers that basic research is actually important for well-being. But how could this interaction between science and society be measured?
About a year ago I wrote a review paper in which I tried to answer some of the above mentioned questions. As it turns out social media can be a powerful partner to communicate your science while also being useful to assess the impact your research has made on others. An additional dimension social media has to offer is the possibility to actually create “societal relevance” through educating your followers and demonstrating that science can be understood and appreciated by many folks out there and not only a few in the ivory towers.
A very useful (and interesting!) way to measure how fast new research can spread in the digital age has been developed by the people at Altmetric. This tool is able to extract how and where published work is shared in social networks. In my small extracurricular project that I have mentioned above I applied this tool to assess how different scientific fields and universities differ in spreading their scientific results and how these results are perceived by the general public.
As participant of the GPP 2014 program you might be interested in the Altmetric tool and the question how researchers and universities can make their work more appealing to the public. Here is the link to my short paper: TheRelevanceOfResearch.
In case you are specifically interested in the Altmetric tool, there is also a more large-scale study and quantitative assessment of this topic which has been published last year and can be found here.
Feel free to discuss these science communication issues with me. Either by email or in person in a few weeks from now.
April 1, 2014
Yes, forgetting is essential! In order not to overload your brain with “useless” information from the past you need to be able to forget. But how does forgetting work? Synapses connect neurons in the brain and it is thought that an altered neuronal structure (read: different wiring or less wiring) leads to forgetting. While a lot of time, money and careers are invested into the question how synaptic networks are formed, it is not very clear how the complexity can actually decrease. Assuming that a reduced synaptic “landscape” is equal to the well-known process of forgetting, it is therefore not very much known about this process. Although not te first of its kind, a recent paper addresses this issue and proposes a molecular mechanism which is mainly based on the regulation of the actin cytoskeleton via a post-transcriptional mechanism. And the evidence seems strong! The model organism used here are the C. elegans worms that can actually be trained to avoid a certain taste because they were starved of food when they were in contact with it for the first time. Remembering and forgetting this Pavlovian training by the worms can then be used as a proxy for memory function. As already mentioned, the major player in the competition between memory formation and forgetting is the rate at which synapses are formed and degraded. An already previously described and neuronal active protein called MSI-1 is proposed here to be responsible for the degradation part by inhibiting the translation of at least three mRNA types (arx-1, 2 and 3) who´s protein products would normally from the Arp2/3 complex. This complex is normally responsible for remodeling the actin skeleton of the synapses by the induction of actin branching. MSI-1 therefore prevents the Arp2/3 complex formation and thereby leads to decreased synaptical structure retention. In other words: MSI-1 increases the tendency for synapses to disappear, which might be one factor to answer the question why we forget things. This interplay is further strengthened by the authors finding that the deletion of the add-1 gene (responsible for actin capping and therefore stabilization) leads to memory loss. However, this phenotype could be reversed when msi-1 is deleted at the same time. As a consequence, add-1 and msi-1 must both be involved in memory formation and retention, but with opposing functions.
An unresolved question, however, remains how MSI-1 is “activated” to suppress arx mRNA translation. It is likely that forgetting is a neuronally regulated and controlled process, just like memory formation. The authors propose that the glutamate receptor GLR-1 might play a role in this process because it´s expression is exclusively increased in the MSI-1 positive neurons during learning. On the contrary GLR-1 is also required for MSI-1 function and therefore memory loss. How the upstream regulator GLR-1 can influence these two opposing events at the same time therefore remains an open question for future studies. Another interesting and open question is the link between the AVA neurons in which MSI-1 was predominantly found and neurons in the gut of the worms in which MSI-1 was also found. Can this link be explained by the food/starvation related setup of the experiment? And do other forms of training/memory acquisition and the resulting forgetting mechanism work differently? Furthermore, what are the effects of MSI-1 on the other numerous actin remodeling factors?
Despite these open questions, the paper presents compelling evidence for an additional molecular mechanism explaining neuronal information retention and loss. In summary and interestingly, memories seem to be regulated in a balanced way that is deeply influenced by the synaptical actin skeleton which is actively constructed, and passively degraded by the inhibition of its formation through the translation repressor MSI-1.
October 18, 2013
September 27, 2013
Life from single molecules to entire populations takes place in four dimensions. Three of which are spatial dimensions and last, but not least, the dimension of time. Interestingly, researchers ignored these hard realities for quite some time. During my PhD project on translational regulation within cells, we would like to master the four dimensions as good as we can. Live-cell imaging is a good method to monitor a single cell over time and to observe what is changing. However, live-cell imaging requires sharp and crisp images in order to be able to track single molecules over longer time spans. The biggest problem with conventional light microscopes are in fact the three spatial dimensions (x, y, z), because all the light from the specimen that you are observing is collected. This means not only the light of a single plane (x,y dimensions) is collected (and later observed), but also the light originating from all other planes above or below (z dimension) (see also Figure 1). Collecting a lot of this so-called “out of focus” light leads to blurred pictures, which means that fine details cannot be distinguished from each other anymore. A powerful tool to circumvent this problem is a variation of classical light microscopy called CONFOCAL MICROSCOPY. Here, I would like to give a short introduction into this extremely powerful and widely used microscope technique.
Figure 1: A cell that is observed under a microscope has three dimensions (x, y, z). However, the optics of a microscope dictate that only one z-plane can be “in focus” and not all planes at the same time. A standard microscope collects the light of all planes and therefore often produces blurred images when larger objects such as cells are observed.
In order to make sense of the confocal technique (con-focal = “having the same focus”) I would like to draw your attention to Figure 2. With the help of the steps 1 to 5 I will guide you through the figure. First of all a confocal microscope needs a strong light source. This role is often fulfilled by a short-wavelength laser (Step 1). The laser light is then reflected in a 45° angle by a so-called dichroic mirror (Step 2). This special mirror reflects short wavelengths (such as the green excitation laser), but is permissive for longer wavelengths (such as the emitted red light). The reflected green laser light is focused by the objective lens onto the specimen. Unfortunately, it is impossible to focus the light on only one single z-plane. As a consequence, a number of z-planes are excited by the green light and depending on the fluorescent molecule emit longer wavelength light, here depicted as red, orange, and purple (Step 3). Partly, this emitted light will later form the image that you can observe, but first it needs to travel to your eye: As explained above, the dichroic is permissive for the emitted longer wavelength light. Therefore, the light originating from all z-planes can pass. Since the light is originating from different planes, it also hits the so-called focal lens at different positions resulting in different focal points of this light. And now a small slit, called pinhole comes into play (Step 4): Most light (based on its origin) cannot pass this tiny opening because it is either focused in front of or behind the pinhole. The reason why a confocal microscope produces crisp images is that only light from a single z-plane is able to pass since its focal point is exactly within the pinhole (in this example the red light). Consequently, this light can reach the detector (Step 5) where it is converted into a visible image.
Figure 2: The setup of a confocal microscope can be described in five simple steps (see text). The pinhole is the central element because it blocks all “out of focus” light originating from non-desired z-planes.
Unfortunately, the seemingly simplistic confocal approach also has two important side effects. First of all, a lot of light is lost because it is shielded by the pinhole. This in turn requires a very strong light source which can damage the sample if applied for a long time. In order to prevent this from happening, the specimen is scanned point-for-point in the x,y dimension. This leads us to the second side effect: Scanning takes a lot of time and this is kind of impractical if you want to observe a live cell. But: Both problems can be (partly) resolved by a variation of confocal microscopy called “spinning-disc confocal microscopy”.
More on this technique in my next post!
September 9, 2013
Traditionally single-molecule experiments are performed in vitro and therefore in a reduced environment. Recently, it has become possible to combine this single-molecular accuracy with a living single cell and to observe what happens in real time (“live”). For biologists the combination of these three technological ideas creates a lot of possibilities to answer a number of currently unanswered questions. I am very happy to be able to be part of this adventure. In the following I would like to address some aspects of my work:
What am I doing?
Currently I am working on the intriguing and big question how cells translate their DNA into protein. Interestingly, many important sub-questions of this problem still remain unanswered, especially when focusing on the fate of mRNA molecules once they have left the nucleus and are present in the cytoplasm. The quantification of the translation process in time and space, characterization of its steps and major molecular players is our focus area. In order to elucidate what happens to mRNAs in the cellular context we mark them with fluorescent proteins and apply single- and live-cell imaging. In addition, new labeling and detecting technologies allow to study mRNAs at the single-molecular level.
Why study translation live and in single cells?
The so-called central dogma of biology, namely the conversion of information stored in the DNA into proteins, has been dissected by a large number of scientists. However, in most traditional approaches the mRNAs as the central information carriers are isolated from large numbers of cells and therefore removed from their natural cellular context. This results in functional deficits and loss of spatio-temporal information (“Why is this mRNA at this place in this cell at this time?”). In contrast, the combination of single- and live-cell imaging allows to study the fate of mRNAs during translation in their physiologic environment, over a longer period of time and with a minimum of disturbing factors. The use of only single cells also allows to detect differences between cells of the same kind (for example neurons or muscle cells). An organ represents a very heterogeneous environment, so cells have to be different in order to be able to adapt to their local environment. Even 150 years ago Charles Darwin already noted that observable traits can vary widely within a species. Why couldn’t this also be the case for individual cells?
Why single-molecular accuracy?
Next to the advantages that live single-cell analysis has to offer, it is important to keep in mind that most biological processes can be reduced to the level of molecules. When, however, a larger number of molecules is observed (even within a single cell) this automatically leads to an averaging effect. A complicated biological process, like the mRNA translation into protein, involving a number of molecules during specific stages might therefore only be recognized as single event with a “before” and “after” without knowing what really happened in between. By visualizing single molecules it becomes possible to track their role as a puzzle piece within the big picture.
Nice. And how is this done?
There are two major tools. The first one is a microscope (more specific: a light microscope called confocal spinning disc microscope) to observe the single cell with its mRNA molecules. However, the resolution of a light microscope is limited to about 220 nm (1 nm = 1 m / 1,000,000,000). Even though a RNA molecule might be longer, it is also about 1,000 times thinner and therefore not detectable. In order to be able to still detect them we label them with fluorescent proteins. The emitted light results in a so-called “diffraction limited spot” which can be detected by the cameras of our microscope. For the RNA labeling we apply the MS2 and PP7 systems which use specific bacteriophage proteins that are again fused to fluorescent proteins and can bind to specific regions within the mRNA molecule of interest. Importantly, the MS2/PP7 labeling does not harm the biological processes within the observed cell. With this system it is also possible to label a single mRNA molecule in two colors (for example red and green). During the mRNA translation process different parts of the mRNA are targeted by the translation machinery in a sequential manner which has an influence on the binding of the green and red proteins. The appearance of both colors at the same time (yellow), first green and then red, or the other way around, the speed at which this change occurs, and the location within the cell can tell us a lot about the translation process.
In case I could spark your interest for single-molecule live cell imaging please also see our website or check out the following three articles on mRNA labeling and detection:
- Hocine et al., Single-molecule analysis of gene expression using two-color RNA labeling in live yeast. Nat Methods. 2013 Feb;10(2):119-21.
- Wu et al., Fluorescence fluctuation spectroscopy enables quantitative imaging of single mRNAs in living cells. Biophys J. 2012 Jun 20;102(12):2936-44.
- Larson et al., Real-time observation of transcription initiation and elongation on an endogenous yeast gene. Science. 2011 Apr 22;332(6028):475-8.
- the Spinning-disc microscope
- the MS2 and PP7 labeling systems
- and “diffraction limited spots”
will follow later.
August 30, 2013
August 1, 2013
Presentation time. In order to attract a few people to my talk I designed this poster with the freely available GIMP software. It takes a while, but the possibilities that GIMP has to offer are astonishing. The software is great for creative outbursts. And wouldn’t it be nice if scientific posters could become more appealing to the eye in the future? The Biology Department of the University of North Carolina at Chapel Hill is already quite good at it: http://www.flickr.com/photos/biologyposters/.
April 13, 2013
Partly painted walls – Boston
Enjoying some liquid sugar – Boston
Winter swimming (no pictures) – Somewhere in the woods
The Atlantic – Rockport
Freeclimbing or something like that – Rockport
Gone fishing – The Atlantic
Mont Royal – Montréal
A house in Montréal
A factory in Montréal
More houses in Montréal (it’s a beautiful city though, photos are selective)
Montréal at night (on top of Mont Royal)
Québec and its frozen river/part of the sea
White Mountains hiking
Since form follows function, the visualization of protein structures is vital for understanding biological complexity. Several ways of producing images that are not just beautiful, but also address certain research questions and help to elucidate protein function exist. Here I briefly want to talk about the program PyMOL which was originally created by Warren Lyford DeLano in 2000. My current project deals with the single-molecule characterization of bacterial translesion DNA polymerases. The polymerase I am working with the most is Pol II and therefore it is very interesting for me to picture this molecule in a way that allows me to understand how Pol II interacts with its DNA substrate (polymerases replicate DNA). However, translesion polymerases such as Pol II are not only capable of binding regular DNA, but also damaged DNA in order to prevent a stalling of the entire replication process which would otherwise lead to cell death. But why is Pol II DNA damage tolerant?
Now we are at the point were structural protein information is required. In this case this information was created by Wang and Yang in a very elegant and interesting crystallization study of Pol II (1). Even though the authors do a great job to visualize their findings, it might be helpful to do this yourself in order to create for example a different perspective view or even a short video that shows the protein from different angles. In addition you might also want to highlight certain amino acid residues by a specific color and thereby state the importance of certain functional proteins domains. All this can elegantly be performed by PyMOL. For my purposes I created the following view of Pol II containing a DNA helix with a tetrahydrofuran (THF) lesion which can not be processed by a regular polymerase.
For protein structure visualization the Protein Data Bank is the place to go. Just search for the protein structure you are interested in (hopefully it exists) and download the so-called PDB file which contains all the 3D data that is necessary to visualize the protein. Here I used the PDB file 3K5M which contains information on Pol II bound to a THF lesion DNA.
I assume you have downloaded PyMOL by now and know how to load a PDB file into it. What I like about PyMOL is its command line which allows to rapidly change what you want to see and achieve with your protein. The downside is that you need to know the syntax of the commands and also need to memorize the important commands because looking them up all the time is time consuming. The PyMOL user guide on pages 17 to 37 is a great introduction to the most essential commands. However, I used the following command sequence to produce the picture above. This is the foundation, but it can bring you quite far.
Step 1: Know your protein domains. Pol II has five domains in total. I gave a distinctive color to each one of them. The N-terminal domain stretches form residues 1-146 and 366-388, the Exo domain from 147-365, and so on… From the literature you must figure out yourself which domains your protein has and where they are located. The following command is very important and lets you select your domains (here the example for the N-terminal domain):
PyMOL> select nterminal, resi 1-146,366-388
This command will name the indicated residues “nterminal”. Later you can use “nterminal” to address the entire domain instantaneously. Specify the residues of all your domains and give them a descriptive name. On the right side of the screen you can then see an overview of all your domains.
Step 2: Know how to hide. Proteins can be very confusing. Use the following commands to first hide everything and then only selectively display what you want to see in a style that you like.
PyMOL> hide all
PyMOL> show cartoon, nterminal
I personally like the alpha-helix and beta-sheet displaying style called “cartoon”. But please also play around with the following styles: ellipsoids, lines, ribbon, dashes, mesh, volume, sticks, and many more… In case you become confused or made a mistake just use “hide all” or “hide cartoon, nterminal” to get rid of your confusion. Now choose a fitting style for all your domains and do not worry about the colors yet.
Step 3: Colors are nice. Now it is time to further organize your residues not only by displaying style, but also by color. This command is very easy and works with all major colors like green, yellow, purple, blue, red, orange and so on…
PyMOL> color yellow, nterminal
So go ahead and color each of your domains in a clear, distinctive way.
Step 4: Size does matter. The “cartoon” view is very handy to see in which contexts residues are located without the confusion of all the side chains. However, a real protein is much bigger and the electrostatic forces and hydrophobic interactions determine which part of a protein is actually accessible by ligands or in the case of Pol II by DNA. The accessibility can be modeled in PyMOL by an algorithm displaying the surface that is available to water molecules.
PyMOL> show surface, nterminal
PyMOL> set transparency, 0.6
Use these commands for each of your domains and play around with the transparency (from 0 to 1) so that the surface depiction does not become overwhelming and the cartoon residue structure is still visible. The combination of two or more different styles at the same time such as “cartoon” and “surface” in this case is actually one of the strongest features of PyMOL!
Step 5: Make it nice. Most people’s aim is to create protein structure visualizations for presentation or publications. How to achieve a high-quality and clean file is therefore very important.
PyMOL> bg_color white
These commands set the background color to white which is most convenient for most applications. “Ray” creates a sharper (read: nicer) depiction of your protein. It is important to bear in mind that the “ray” command effects are lost once you perform other modifications to your protein. So only use “ray” at the finish line. Or just use it as many times as you want.
Step 6: Hold on to good things. In order to save your work go to the “File” menu located on the top of one of the PyMOL windows. There are a couple of options how to save your work. Most important is “Save Session as…” because it allows you to go back to your current state of the project. But you are probably also interested in just saving the current view of your protein (“Save Image as…”). If you want another view angle just turn your protein as desired and save again. A PNG image will be created that can be used in papers or presentations.
Step 7: Let’s move it. You can also make a video out of individual PNG pictures that show your protein form different angles. For Pol II the result looks like this. Luckily you do not have to turn your protein 60 times and save everything and than put it together as a movie. PyMOL does it for you.
PyMOL> mset 1 x60
PyMOL> util.mrock 1,60,180
Use these commands to make and test-view a movie of 60 frames that lets your protein structure rotate in a 180 degree space. If it gets boring after a while use “mstop” to stop. In order to save, go to the “File” menu again and choose “Save Movie as…”. Every major media player should now be able to display your moving protein.
By now you probably still have a number of unanswered questions. But there is relief. People who know much more about PyMOL have created a very convenient FAQ page which contains the answers to most questions that beginners have or that are just good to know.
And now go ahead and use structural biology research for your own purposes with PyMOL!
(1) Wang F., Yang W., Structural Insight into Translesion Synthesis by DNA Pol II, Cell 139, 1279-1289, 2009.