How viruses hijack cellular transport systems

Even in the world of the very small, there are significant differences in size. A eukaryote cell (i.e a human cell) for example is relatively big, in microscopic terms. Most other things that interact with the cell at the microscopic level, are far smaller than it, such as bateria, viruses and signalling molecules.

A virus isn't much more than a small capsule of proteins with a little bit of DNA inside. Once it gets inside a eukaryote cell, it's very much in the position of a small child wandering into a big city. In front of it lies the vast interior of the cell, full of reactions, enzymes, proteins scurrying too and fro, mRNA being translated, proteins being folded and other busy bustling cellular processes. Surrounding it are large organelles (larger than the virus particle!) with strange and mysterious procedures going on inside them...

That sort of view, stretching across to both horizons

From here, the virus has to make its way to the nucleus, pushing its way through the crowded and complex cellular interior without being spotted as an intruder. Fortunately it has some help here, because it's facing the same problem faced by every molecule and organelle already in the cell. Transport mechanisms are already in place so that things can move around the large intracellular space with relative ease. The viruses simply hijack these transport systems and get a free ride all the way too the nucleus.

Work on the herpes simplex virus helped to produce a model of how the viral particles move around the cell. After entering the cell through the cell surface membrane, the virus is picked up by dynein which carries it along microtubes towards the nucleus. The microtubules form a network within the cell (like train rails) which the dynein motors along (using ATP energy). This is shown pictorally below:

Dynein moves in one direction along the microtubule while kinesin moves in the other direction. Together they move molecules all around the cell.

Once at the nucleus, the viral DNA enters through the nuclear membrane and is replicated inside the nucleus (entering the nucleus is a critical step for DNA-viruses; for those viruses that contain RNA this step is not so vital). The replicated DNA then comes back out of the nucleus and is transcribed into protein in the cytoplasm, which leads to the formation of new viral particles. These new viruses then have to travel back down the microtubule (carried by kinesin) to the outer membrane of the cell where they can be released into the surrounding environment and go on to infect more cells.

One interesting question is what exactly the dynein (and kenesin) bind to on the virus cell surface. As well as being an interesting point, answering this comes with the usual funding bait that if you find how viruses move inside the cell you may be able to find ways of stopping them from moving which would leave them at a severe disadvantage. To examine this the virus was isolated and the parts of the surrounding protein coat that bound to cellular factors further separated. These separated capsid proteins were then tested for their ability to bind to mammalian intracellular proteins. They found that several of the capsid proteins could bind to important transporter molecules, and furthermore that several different transporter molecules could sometimes bind to the same capsid protein.

Drawing showing the site of attachment of the motor transport proteins to the (green) virus capsule. The other end of the motor proteins is used to move along the microtubule.

As I'm in a fairly syntheticly-biological mood, I couldn't help but notice the mention at the end of the paper that this could have implications beyond virus treatment or vaccinations. The ability to create a little molecule that the cell can carry to the nucleus could have implications for both future genetic treatments and nanotechnology. The ability to get a little capsule of treatment right to the nucleus of cells could even have the potential for treating cancer cells, as it utilizes the cells own transport mechanisms to deliver treatment to the intracellular place it is needed.

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Kerstin Radtke, Daniela Kieneke, André Wolfstein, Kathrin Michael, Walter Steffen, Tim Scholz, Axel Karger, Beate Sodeik (2010). Plus- and Minus-End Directed Microtubule Motors Bind Simultaneously to Herpes Simplex Virus Capsids Using Different Inner Tegument Structures PLoS Patholgens, 6 (7) : e1000991

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Modelling Virotherapy for Cancer

Most cancer-related research, particularly medical cancer-related research tends for rather obvious reasons to involve animal research, and while I'm more than willing to agree that it's a necessary sacrifice it does always make me feel a bit squeamish on a personal level. Which was why the first thing that struck me when a certain jazz-playing poetry-writing philosopher-doctor sent this paper my way was that it was involved in developing a mathematical model for treatments. Not to replace animal testing, obviously, but to cut the tests down to those that were more likely to work, reducing the need for animal use.

The paper is exploring glioma virotherapy, which uses synthetic viral capsules to target cancer cells and kill them, while not harming the surrounding normal cells. These viruses are known as ontolytic viruses and while they may originate from harmful strains they've had almost all of their own DNA knocked out, turning them into little balls of protein designed to target cancer cells only. This approach has several problems associated with it, but one of the main ones is that the human body generally doesn't like having virus's inside it. Any injected cancer-targeting virus capsids are in danger or being effectively destroyed by the bodies immune system.

One solution to this is to use immunosuppressants, which naturally comes with problems of its own, including the question of dosage. How much immunosuppressant do you give the patient, depending on the corresponding number of viruses used, and the size of the cancer. In order to explore this without having to kill huge numbers of rats, Friedman and colleagues developed a model to explore the effects of differing virus and immunosuppressant concentrations.

First, they needed to specify the parameters they were using:

Number of tumour cells infected with virus = y

Number of tumour cells uninfected = x

Necrotic (dying) cells = n

Immune cells (destroying the viruses) = z

Free virus particles = v

Then some rates to take into account:

Proliferation of non-infected cells = λ

Infection rate of tumour cells = B

Diffusion coefficient of virus particles = D

Adding this all together with some mathematical magic (and a function to include immunosuppressant levels) leads to what is to me a totally incomprehensible series of mathematical squiggles (anyone whose desperate to read them can find them in the appendix of the reference paper below). But somewhere along the line the magic works, as seen when they compare it to experimental data:

The table above (from the reference) isn't remarkably clear, suffice to say that the blue bars are the actual experiment results (carried out in rats) while the red bars are the results of the model simulation. Graph A shows infected tumour cells (after 6 and 72 hours), graph B shows immune cells (after 6 hours 72 hours and just before the rat dies) while graph C shows the immune cells after addition of the immunosuppressant (after 6 hours, 72 hours, and just before the rat dies). The x-axis shows the percentage of cells.

Having got a model that shows a reasonable degree of accuracy, the experimenters can then play around with the parameters without any more rats having too be involved. For example they can explore the effects of adding more viruses. More viruses in the system increase the immune cell response, even in suppressed patients (although obviously the response is lessened). However as the numbers of viruses decrease, the immune cells start to leave the area, allowing any viruses that have survived to quickly recover the population and the immune cells rush back in again. This leads to a feedback loop which, with my knowledge of the effects of the immune system, can't be all that good for the patient.

The results below from the model show the effect of adding varying amounts of virus on the number of infected tumour cells.

The cyclical pattern can be clearly seen, especially for the larger numbers of viruses (the blue, red and green lines represent increasing numbers of virus's injected into the system - as the colours are rather faint the blue line is the mostly straight one, the red line is the bumpy one and the green 'line' is a series of peaks). The model was also used to explore different concentrations of immunosuppressant and different dosage schedules (one a week, twice a week etc.) for treatment.

There are limitations to the model, it only considers injections into the centre of spherical tumours, for example, and does nothing to model any potential problems caused by metastasis (bits of the tumour breaking off and moving away). However is does provide the framework of a system to explore different options for bench experimentation, to ensure that any work that is done on animals will be the useful and relevant for the development of this system into a working treatment for human cancers.

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Friedman, A. (2006). Glioma Virotherapy: Effects of Innate Immune Suppression and Increased Viral Replication Capacity Cancer Research, 66 (4), 2314-2319 DOI: 10.1158/0008-5472.CAN-05-2661

Motility of Cancer Cells

Cancer is a disease of multicellular organisms. In order to become multicellular, a certain amount of control needs to be exerted over each individual cell, cells can no longer move around, grow, and divide when they want too. Instead they must obey signals from the surrounding environment (including their fellow cells) which tell them what to do. Cancer, like anarchy, is what happens when the control breaks down, and individual cells start growing and dividing regardless.

Uncontrolled growth leads to a neoplasm, a large mass of abnormal tissue. These can be benign, and merely exist in the body without causing too many problems, or they can start to become cancerous, invading surrounding tissues, and sometimes entering the bloodstream and spreading to further locations within the body.

(Because of this, cancer is primarily a disease of deterministic multicellular organisms. Plants and other non-determinists can get tumours, but tend not to be so badly affected by them, as they are constantly growing anyway)

In order to break away from the neoplasm and spread the disease cancer cells must gain motility. Studying how cancer cells move can be difficult in vivo because the conventional method of immuno-histology (which involves taking slices out of a tumour during development then fixing and staining them) prevent movement all together. Newer work has been done using Intravital imaging (shown diagrammatically on the rather cute little picture on the right) , where a fluorescently-labelled tumour is generated in an animal and then observed while the animal is anaesthetised. This gives a perfect in vivo image of what is actually happening inside the living tumour cell, in these images you can see cells moving in real time, and examine how they act under the effects of internal mutations and changes in external conditions.

One of the things that this type of imaging revealed was that most of the cells in a tumour don't move (less than 0.1% tumour cells in vivo/hour). Furthermore, there were two types of movement. Firstly, individual cells, that darted around on their own, fairly quickly and in all directions. Secondly large clumps of cells, that moved relatively slowly, but in the same direction with a more ordered internal microtubular structure.

Single celled movementTwo types of movement were first described; mesenchymal and amoeboid. As the main difference between them lies in the speed and number of direction changes it has been suggested that the distinction may be an artifact of different experimental conditions, rather than actual physical difference. The movement (which has been studied extensively in mesenchymal cells as they can be stuck down onto 2D surfaces) is initiated by signals to receptor tyrosine kinases. These turn on the small G-protein, Rac which, among other things, activates Arp2/3 proteins, which control the nucleation of actin subunits. In the diagram above the actin is shown in red, and it is used to generate movement of the cell. As the cell is forcing it's way through a thick external extracellular matrix (EMC) it also secretes proteases and MMPs to break this down, allowing easier forward movement.

Collective cell movement
(All images are taken from the reference below, and I've included the key for those with an interest in how eukaryote cells hold themselves together)

Collective motility is the movement of whole groups of cells, either in clusters or chains. These cells can move between tissues, spreading the tumour (in particular they can get into the lymph system) but they are not normally found in the bloodstream. Interestingly, collective motility is seen when the conditions for single-cell motility have been blocked, suggesting that the rapid-moving single cells are a transient stage in order to get the tumour into the bloodstream. Once it finds a new environment, it reverts back to the less-motile stage, with large clumps of tissue still able to (very slowly) manoeuvre themselves into nearby tissues.

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SAHAI, E. (2005). Mechanisms of cancer cell invasion Current Opinion in Genetics & Development, 15 (1), 87-96 DOI: 10.1016/j.gde.2004.12.002