Multicellular signalling

I like studying bacteria. I find them fascinating, wonderful little creatures, able to do as much (and often more!) with a single cell as other organisms need whole multicellular bodies to achieve. I like exploring the places bacteria live, the things they can do, the ways they manage to exploit practically every niche on earth, and of course most importantly how I can exploit them.

But not everyone loves bacteria, and at heart I am a biochemist which means, among other things, that I get to teach younger biochemists. This means I do occasionally find myself venturing uncertainly into the world of the multicellular and while doing so recently I found an interesting paper on cell signalling (reference below) which I thought I would share.

All cells need to be able to communicate, but while bacteria know that everyone they communicate with is a competitor, multicellular organisms have cells that need to be able to cooperate in a strange and slightly twisted form of cellular-communism. Each cell needs to know when it can divide (usualy never), when to grow, when to release chemicals and, ultimatly,when to sacrifice itself for the Greater Good.

Cellular communication is mostly a chemical affair, with small molecules called ligands being sent from one cell to another and recognised by receptors on the cell surface. These receptors can take many forms, but one of the more common ones is the form of a seven-transmembrane spanning receptor, so called because it goes through the membrane seven times:

Picture (c)me and my dodgy art skills. The protein is in blue, the membrane in pink, and the ligand bound on the outer cell surface is the red blob.

Binding of a ligand causes a conformational change in the whole structure, most importantly in that long intracellular tail shown above. This can then activate other molecules inside the cell, with the end result that a specific gene is turned on or off. In the classical model of this process the intracellular tail interacted with a little molecule called the G protein which carried the message through to the genome. Another protein that featured in this model was B-arrestin, which was thought to desensitise the receptor and the G-protein by re-setting it back to its original state, i.e switching the thing off. This model is shown below:

Picture (c) me. This is a simplified diagram, in 'reality' there are a lot more different proteins involved, but these are the main ones, and the important ones for this paper.

New evidence is coming to light which modifies this model. Firstly, it's been found that the B-arrestin does more than just switch off the G-protein, it is also capible of sending its own signals, through a cascade of different proteins. Both the G protein and the B-arrestin can be used to pass on the message sent by the ligand. Secondly, it's been found that these two proteins are not activated equally, a bias can be displayed, sending the signal through one of these two intermediate proteins; either the G protein, or the B-agonist or a mixture of the two. This bias can be either due to the properties of the receptor, or those of the ligand binding to it. Experimentally you can generate a bias by altering either the receptor or the ligand to prefer binding to the B-agonist, and you can plot these on mathematical-looking graphs.

You can tell this is a biology graph because there are no actual numbers, just vague concepts :p (c) me.

The actual physiological effects of this are only starting to be explored, as it introduces an extra level of complexity to intracellular control. The use of several different ligands, all with varying degrees of bias at the same receptor, could produce more subtle cellular output responses. Within a multicellular organism, the better your intracellular communication is, the more likely your organism is to grow happily and survive.

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Rajagopal S, Rajagopal K, & Lefkowitz RJ (2010). Teaching old receptors new tricks: biasing seven-transmembrane receptors. Nature reviews. Drug discovery, 9 (5), 373-86 PMID: 20431569
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Lab Rat guide to Fourier Transformations

Protein crystallography is one of those mysterious things that I always feel I should know more about. It starts with protein crystals, fair enough, and then heads rapidly out beyond the Magical Event Horizon leaving me with a picture of set of small fuzzy dots which mysteriously resolve themselves into an electron density map. Somewhere in all this someone will mention the dreaded Fourier transformation, at which point I know all hope is lost and a might as well stop listening.

With the help of a good lecture and an utterly outstanding website though, I'm starting to get the hang of it. X-ray crystallography works by shooting X-rays at a protein crystal. As the crystal is in a regular lattice structure, the X-rays are scattered in a regular way. Each scattered ray can be characterised by the amplitude and the phase, as shown below:Each dot on the resulting image (which usually looks something like the figure shown on the right) corresponds to a scattered X-ray. The position of the dot gives (by way of a set of clever equations) the amplitude of the wavelength. However in order to calculate the position of an atom you need both the amplitude and the phase, and you can't get the phase from just the position of the dot. And here is where the dreaded Fourier transformation comes in, to help give information about the phase.

The Fourier transformation is an equation, which gives reciprocal information about a molecule, for example if the molecule is a single small point, the Fourier transformation (i.e what it looks like after plugging its positional coordinates into the Fourier equation) will be a large fuzzy blob, as shown below (all pictures from now on are taken - with permission - from Kevin Cowtan's Book of Fourier) . Molecule is on the left and its Fourier transformation on the right:
For the more mathematically minded, what the Fourier transformation actually does is take a function and express it as the sum of a set of different sine and cosine waves. Apparently this can be done for any continuous function. By using this transformation you can get not only the amplitude, but also the phase of any given molecule inside an atom. You can also make the equation go backwards as well, turning the red fuzzy blob on the left back into the individual point. As most molecules contain many, many atoms there are various tricks you have to do in order to make this easier for large molecules, but first a quick proof of this concept using my favourite pictures on the Cowtan website.

Here is a picture of a duck:
And here is the Fourier transformation of the duck, with the amplitude represented by the brightness of the colour and the phase represented by the actual colour:
In order to show that the Fourier transformation really does show the phase, this transformation is mixed with the Fourier transformation of a picture of a cat. Rather than mix them both equally, the amplitude (brightness) of the duck transformation is mixed with the phase (actual colour) of the cat to give the following Fourier transformation:Performing the Fourier equation on this blob (to turn it back into an animal again) gives the following result, hopefully not unsurprising if I've managed to explain this alright:
It's a cat! A rather blotchy cat, true, with a fairly trippy background, but nevertheless the Fourier transformation has faithfully reproduced the phases, rather than the amplitudes.

So how does this help when looking at molecules? It turns out that the fuzzy black-and-gray-dots picture that is the end result of X-ray crystallography (shown above and reproduced here on the right) is the Fourier transform of the atomic electron clouds inside the protein crystal. That picture is like the fuzzy coloured blobs that the duck and cat images came out of. In the same way that those turned into animals, this picture can be turned into the approximate shape of the electron clouds surrounding a molecule. For low resolution images this can show the secondary structure of a protein, the positions of alpha helices and beta sheets and a general idea of protein shape. For high resolution images, individual amino-acid residues can be seen, allowing a much more detailed view of the structure to be generated.

It isn't always perfect. Sometimes you do get the equivalent of a blobby cat with a trippy background and have to play around with homologous comparisons and allowed bond-angles to get a meaningful structure. There are plenty of strategies that exist to help you get a better image as well, particuarly for larger molecules which need more help resolving phases. From what I've heard though, once you've actually got the crystal, the rest seems like childs play in comparison. I know people who have spent their whole PhD's, and longer, just trying to isolate and concentrate a single protein crystal...

Revision...

...would be a lot easier if the lecturers gave better notes. Notes that didn't leave me trying to work out colour-coded protein domains printed in greyscale with four very small slides to a page surrounded by unhelpful notes which turn into random squiggles when I drift off.

It's the option lectures that are scaring me at the moment. First terms stuff I've kind of got a hold on but I'm a bit lost with the options stuff, because I wasn't revising it as I went along. The reason I wasn't revising it? Because I was simultaneously trying to do an 8am-6pm five-days-a-week lab work project with a 5000 word write-up worth (wait for it) a whole 10% of my mark.

I swear this department is trying to kill me. Why I've agreed to do another year of it I don't know. (Except that the lab work was FUN. Just mental. Fun and mental. Like me :p )

But as soon as I get out of here, I am definitely going to make a headlong dash for the microbiology department and stay there. They will probably work me just as hard and just as crazily, but at least the scenery will be different.

Monoclonal antibodies

During my pathology course last year, monoclonal antibodies were one of those things I just couldn't 'get'. It was explained to me numerous times, by increasingly more irate and disappointed looking supervisors, but every time it was re-mentioned in lectures and supervisions I would sort of stare despairingly at whatever piece of paper was in front of me thinking 'what the hell are they again'.

"Something to do with mice, and antibodies, and making them human, or something" was usually the best I could do.

So when the subject appeared yet again during this years course, I decided to finally look it up properly and work out just what was going on.

Antibodies look like this:
The two variable regions recognise bind to antigen (parts of invading bacteria) leading to the invading bacteria being destroyed. Antibodies produced in the body are polyclonal, because each one has a different variable region and can target a different antigen (until a threat is realised in which case they massively overproduce the relavent antibody).

The idea of monoclonal antibody therapy is to produce a large number of essentially the same antibody, that can find and potentially destroy a specific target. The idea was to produce a kind of 'magic bullet' that went through the body picking out the specifically ill parts and removing them. And antibodies are very specific, and can be targeted to lots of different proteins.

The problem with producing them is that a single B cell (antibody-producing cell) will only last a few generations before dying. Not long enough to produce the large amounts of specifically-target antibody needed for therapy. The original solution to this problem was to use a technique known as hybridoma. Individual B cells that had been grown in mice and produced antibodies that destroyed whatever target the therapy was being designed to remove were fused with immortal myeloma cell lines. The B cell could then propagate for much longer, secreting monoclonal antibodies. The main problems with this technique were that is was slow and laborious and created problems for purifying the antigen.

The most modern technique I know of (although others are being developed) is called SLAM, which stands for Selected Lymphocyte Antibody Method. B cells are isolated from mice (or rabbits, other animals can potentially be used as well) and grown in little plastic wells until they start secreting antibodies. Single B cells are then isolated, and screened for activity. The relevant antibody genes are then cloned through PCR and expressed as recombinant antibodies. This technique is a lot faster and produces high affinity antibodies from a number of species.

Monoclonal antibodies are used in various drugs currently on the market. Lymphomas (cancerous B cells) can be treated with Zevalin (R) or Bexxar (R). Apparently on 3 February 2005, the New England Journal of Medicine reported that 59% of patients with a B-cell lymphoma were disease-free 5 years after a single treatment with Bexxar.

The thing is though, I'm being taught this as a biochemist student/researcher, not as a medical researcher. Which means that I have very little idea how useful, common, or applicable most of these techniques and products are. Academic researchers and medical researchers seem to live a world apart, something that hit me particularly hard during the conference. You could almost always tell, about half way through a talk, whether the speaker was a medical or academic researcher. There doesn't seem to be a whole lot of cross-talk between them either, which is a pity because academic research does often come up with the odd useful medical application, but of course they aren't in any position to implement it.

Translocon structure

Well, I'm still busy with revision but, miraculously, I seem to have almost achieved my crazy aim of writing all of first terms lectures notes in a week *dies theatrically*. I still don't actually know any of the stuff, but at least I now have notes to work from, and I understand it all, which is important.

Topic of the day today was protein targeting within cells, specifically targeting secreted proteins to the inside of the endoplasmic reticulum; a network of internal membranes which modifies secreted proteins and then exports them out of the cell.

Best story in all this is about the discovery of the structure of the translocon; the channel the protein goes through to get into the endoplasmic reticulum (through a membrane). When they first started looking at the structure of the translocon, they saw it was usually found in the form of four proteins very close together, so the first idea was that these formed a ring, with a nice wide hole in the centre for the protein to travel down. It made sense; but unfortunately it only made sense in that specific biological way where the idea is nice but it doesn't fit in with biology.

Because from the cells point of view (if it has one) a large channel like that is a very unhelpful thing to create. You can't regulate it; it needs a filter, or a cap, or some mechanism to prevent just anything going through. Also, a closer look at the translocon showed that it wasn't always found with four proteins close together; sometimes there were three, or two, which would make the channel even less specific or (in the case of only two) almost non-existent.

So the current model (with a lot more supporting evidence) is that there is a little channel down the middle of each individual protein, shaped a bit like an hourglass, which secreted proteins travel through to enter the endoplasmic reticulum. This model works better, especially as the middle bit of the hourglass can expand and change shape; allowing protein folding inside the channel. This also allows for proteins that want to stay in the membrane to be released, there's a little exit space near the middle of the hourglass (alpha helix two of Sec61 for those who are interested) that allows the protein to escape from the translocon into the membrane before it enters the endoplasmic reticulum.

But of course every new model leaves questions behind that were answered by the old model. The thing now, is nobody is quite sure why the proteins cluster together in groups of (mostly) four. If they have a channel through each protein, why not be all separate? Why form specifically numbered groups? It has been suggested that one protein is used for recognition while the other is actually used for the channel but it's all a bit uncertain at the moment.

*sigh* I miss lab work. I miss blogging about lab work. Revision is like forcing yourself to eat when you're already full, I want to get onto some new stuff.

That Time Of The Year

Well, I am back now in the land of fast Internet, and doing that thing that happens when exams loom which is try to remember how the hell information is supposed to get from large numbers of bits of paper into your head.

I'm currently revising transcription, which I first encountered in AS level (aged 16 for those not familiar with the English schooling system). I've been taught it almost every year since as well, and over the years the process seems to have become more complex and less certain (along with everything else, strangely enough).

Transcription is the first step for making proteins inside the cell. The information for creating proteins is stored in DNA (...mostly..more on that maybe later), with every three base-pairs of the DNA coding for one protein amino-acid. DNA is made of a string of base pairs held in place by a sugar-phosphate backbone, and proteins are made of strings of amino-acids all folded up so it works quite well.

However the cell doesn't just make protein from the DNA template, it goes through an intermediate step first, making an RNA template of the DNA (known as messenger RNA, mRNA). This is the process of transcription (link leads to a nice animation). The RNA then leaves the nucleus and is used for a template to make the protein.

One thing you get taught in AS levels is about promoters. Promoters are regions of DNA that specify the start sites of transcription, the place all the transcription machinery binds too, before trundling off along the gene. You get told that they have a things called a TATA box, ten base pairs away from the start; essentially a conserved sequence of bases that bind to the transcription machinery very well; and conserved (ish) bases around the start site called the INR box. This makes sense (especially when they tell you how the machinery actually works) and specifies exactly where the mRNA should start being made from. Here's a paper.

Except it turns out that these TATA box promoters are a really rare form of promoter. Most promoters are a lot less precise, very fuzzy, and the start site can be anywhere within about 20 base pairs. The mRNA that comes out frequently has extra bases at the front end, because the start point is not well defined.

This is mentioned very briefly, and then they tell you everything and more about TATA box promoters all over again. This is because people know about TATA box sites, because most if not all of the research is done on them, and that is because all of the focus is on them. Also getting ideas out of scientists is a lot, lot harder than getting them in, and the nice preciseness of the TATA box promoter is a lovely idea. It's just not the one the cell uses the most.

Hehe. Science is crazy fun sometimes. Good luck to everyone else out there hitting exams as well. :)

How bacteria make antibiotics

There are many different types of antibiotics bacteria can make, but my lab project (now finished, alas) was concentrating mostly on a type called polyketides. These are not just antibiotics, some polyketides can also be antifungals and anticancer agents too, so it's not surprising that quite a lot of work has been done characterising their formation.

Here is the molecular structure of erythromycin. Like many polyketides it is circular, which at first appears to be a bit of a headache to synthesise. The way it's put together, though, is actually very clever. The backbone of the circular section is made up first, using a system of modular enzymes that pass the growing chain along like a conveyor belt, adding new residues at each stage. Then the straight chain is curled up into a ring, and finally the two side residues (the ones on the bottom right of the chemical structure, that look a bit like squashed rectangles with dents in them) are stuck on.

So here is the picture that has appeared on every slide show in every lab meeting we've had this term, showing the formation of the straight-chain backbone before it gets curved into a circle:
Ignoring the little letters (which are just names of enzymes) it really does look a lot like a conveyor belt. At each stage the chain is lengthened, before finally being taken off and twisted around onto itself (to form a circular molecule called DEB). The modular nature of this system is fascinating to work with, but a real problem to sequence. DNA sequencing techniques work mainly by chopping the genome up, sequencing the bits, then trying to stick them back together and modular repeats tend to confuse them.

The last stage, going from DEB to erythromycin, is just a matter of decoration. Although the squashed-rectangle additions (glycosylases, added by glycosylation I believe) look complex, they are quite common molecules that get added onto things in the cell. Glycosylase residues and glycosylation enzymes are very common.
And that's how bacteria make polyketides :)

Lab Rat Working

Holidays are over :(

Image from here

I did not do the drawing, I hasten to add, but I do feel a bit like that. Sitting on top of seemingly impossible problems with a 'help meeee' sort of look.

At the moment I have decided to concentrate on revision because I am too tired (read lazy) to write my long essay. As my lever-arch file that contains the lecture notes is teetering on the brink of exploding, I've brought a book to write the revision notes in. So far I've filled in approximately half a page of it (NOT GOOD) but hopefully as it is a book rather than bits of paper I can do a NaNoWriMo thingy and try to fill up two pages a day.

Rather than, say, looking for pictures of rats on deviantart. heh.

Interesting Fact Of The Day: As there is now a large database of protein structures, many new structures can be determined by just looking at a DNA or protein structure and comparing it to the ones in the database. If you have the protein structure, you can also look at the individual amino-acids (the molecular building blocks that make up proteins) and using the knowledge of what kind of amino-acids they are (attracted to water, attracted to each other, acidic, polar, etc) make a reasonable guess as to the function.

This is one of those wonderful examples where science is very similar to trying to guess what the picture is on a half finished jigsaw puzzle (without looking at the box. In science there is no box). The more different techniques you use, the better you'll have an understanding of what the protein is, and of course some proteins are a lot easier to guess than others. A protein from a rat (say) with the exact same genetic code as a ribosome protein in a silverfish is easy. Another protein might have sections similar to the silverfish, but other bits that are more like bacterial membrane transporters, in whicch case you'll need a whole barrage of other techniques to figure it out.

Although if your DNA code is wrong to start with; due to contamination, procedural error, crossed communication wires or laziness, none of the fancy computer techniques will give any meaningful result. Nor will any of your experimental work, if you're recreated the protein from the genetic code you've been given.

And this does happen. There was a protein that developmental scientists were looking at a while back where (through no fault of the experimenter) the DNA mutated mid way through the growth-and-extraction process, which meant that everyone who was working on it (trying to find out where it migrated to in developing frog eggs) was working on a protein that didn't exist. Only one amino acid had changed, but it meant that this protein didn't migrate anywhere and all the researchers and poor little phD students were tearing their hair out about it.

Until someone finally decided to go back and check the sequence, essentially go through the whole tedious growing-frogs-and-taking-out-their-DNA-and-getting-the-right-bit-out all over again. They found that the bit of DNA they got the second time around was different to the one everyone else was working on. After that I think they did a couple more checks (well ... I hope they did. To be honest I wouldn't be surprised if they didn't) just to make sure they really had the right stuff, and yay! it migrated and some people wrote some papers and were happy about it.

Quick question: How long was the interval between the first attempt to get the correct DNA sequence and the second?

Answer: 20 years.

Oooops :)

To be fair to the scientific establishment though, there is a good reason for that. Science works on funding, and you just don't get funding for something that has Been Done Before. Another thing science works on is papers. The more papers you write, the more likely you are to get more jobs (and more funding) and you wouldn't realistically be able to publish a paper that just confirms someone else's work, not unless the work in question is starting to look very dodgy, and really needs conformation.

To be ever fairer to the scientists (especially as I am one), those twenty years working with the wrong protein were probably not an entire waste of time. They would have generated a lot of new techniques, and probably several people who were really good at tracking proteins by the end of it.

heh. still funny though. 20 years of the wrong thing...








Image from here