Archive for April, 2011

Conference on modelling the immune system in Dresden, part 3

April 8, 2011

In my second ever post on this blog I quoted a celebrated paper of Ho et. al. on HIV therapy. One of the other authors of that paper was Avidan Neumann and on Wednesday I had the opportunity to hear him giving a talk. His subjects were HIV, HBV and HCV, with the greatest emphasis on the last of these. He did briefly mention the case of the man who is apparently the only person ever to be cured of HIV. This took place in Berlin in 2006. The man had both HIV and leukemia and as therapies for both of these he was given radiation treatment and a bone marrow transplant. The transplant was a very special one since the donor was an HIV controller. Since then the patient has not had any treatment against HIV and despite very thorough tests it has been impossible to find any trace of HIV in his body.

Coming now to HCV, this virus causes hepatitis C, a liver disease which is often chronic. It often has few or no symptoms but the liver is progressively damaged, frequently resulting in cirrhosis or even liver cancer. In the worst case a liver transplant is required and after the transplant the virus always infects the new liver. This disease affects about 300 million people and no vaccine is available. The standard treatment is to give interferon \alpha and an antiviral drug ribavirin over many months and this can be very hard on patients due to side effects. A new treatment, a protease called telaprevir, may soon be approved by the FDA. It is much more effective in getting rid of the virus than the standard treatment. The reasons why it is effective have been understood using mathematical modelling. Listening to this talk gave me the impression how close medicine and mathematics can be.

Arup Chakraborty gave a talk on targets for HIV vaccines which had an essential connection to HIV controllers. He has done statistical analysis of HIV viral genomes looking for a certain type of pattern. He explained the idea by an analogy with the fluctuations of share prices. If the share prices of different companies are examined for positive correlations then it is discovered that they can be grouped into certain sectors. These are the companies which are strongly related to certain activities, for instance those which have some close connection to car production. The genome of HIV virions can be analysed for correlations in an analogous way. This results in the identification of positively correlated groups which may again be called sectors. It is not a priori clear what these groups really mean. Interestingly the group with the strongest correlations (Sector 3 if I remember correctly) contains sequences related to HIV controllers. It turns out that these sequences have to do with the activity of building the viral capsid. A problem with vaccines against HIV is that if a vaccine targets a particular peptide a mutation may change that peptide and destroy the recognition without damaging the virus too much. Thus the virus can escape the immune attack. The special sequences in Sector 3 are such that mutations which affect them are likely to affect the stability of the capsid and hence compromise the reproduction of the virus. An important role is also played by those MHC molecules which can present the special peptides. The MHC molecules which do this optimally, and which occur in controllers are rare in the general population. They are, however, presented in a subleading way by more common MHC molecules. This may be enough to form an element of designing a good vaccine. In analysing this problem Chakraborty is using sophisticated mathematics, in particular the theory of random matrices.

To sum up my impressions of the conference, it has convinced me that mathematical immunology is an exciting and dynamic field which I want to be a part of.


Conference on modelling the immune system in Dresden, part 2

April 7, 2011

Here I continue with my presentation of themes from the conference. On Tuesday there was a talk by Thomas Höfer. One of the main themes was the stochastic variability of the behaviour of cells. For instance the production of IL-4 by Th2 cells is subject to considerable variation among cells. Modelling was used to try to understand if individual cells change their secretion rates with time. Might they cycle between states of higher and lower production? This appears not to be the case – they probably only change their behaviour once. I had a chance to talk about this subject in some more detail with Michael Flossdorf at the poster session on Monday. Another case is that of the production of interferon \beta by cells infected by a virus. There is a large variability and it seems that this has little to do with the details of the behaviour of the virus. Instead it is intrinsic to the cells producing the interferon.

Rob de Boer talked about experiments to study the dynamics of lymphocyte populations by labelling. In one type of experiments volunteers were given deuterated water for a certain period and during and after that period the amount of deuterium in the DNA of lymphocytes was measured. The only way in deuterium can be built into the cells is by being incorporated into DNA during cell division. Thus it is a signature of division. Interpreting the results required quite a bit of mathematical modelling. A useful comparison is provided by labelling using BrdU (bromodeoxyuridine). Deuterium has the advantage that it is not toxic.

Ramit Mehr talked about natural killer cells. These have been studied a lot less than their relatives, the T and B cells. NK cells cannot specifically recognize antigens like the other cells and so the question immediately arises how they know which cells to kill. An answer to this question which was at first controversial but now seems to be generally accepted is the ‘missing self hypothesis’ of Klas Kärre. The idea is that the MHC type I molecules on the surface of host cells can repress the activity of NK cells. If the MHC molecules are not there, and thus ‘self’ is missing, the NK cell attacks. When a virus affects a cells it may be in its interest to suppress MHCI molecules to avoid attracting the attention of cytotoxic T cells. Then it may just get out of the CD8 frying pan into the NK fire. Not so much is known about where and how NK cells develop. It seems that although NK cells do not undergo selection like T cells they nevertheless need to go through a period of education in order to do their job optimally.

Gregoire Altan-Bonnet discussed the influence of Treg cells on effector T cells. IL-2 stimulates T cells to proliferate. Treg cells can rapidly bind IL-2 and internalize it. Under certain circumstances this can deplete the amount of IL-2 and thus limit the proliferation of effector T cells. A mathematical model of this process has been studied by a group of people including several participants of this conference. (See Busse et. al. PNAS 107, 3058). As explained by Altan-Bonnet, it has been argued due to experiments with cells kept in separate wells that cell contact was necessary for the action of Tregs but this argument is not conclusive. The wells can simply act as a hindrance to diffusion of the IL-2.

Conference on modelling the immune system in Dresden

April 5, 2011

On Sunday I travelled to the Max Planck Institute for the Physics of Complex Systems in Dresden to attend a conference on modelling the immune system. Before coming here I knew almost none of the participants personally although quite a few of them were known to me by name and by their papers. It seems to me that this conference is bringing together a lot of the leading figures in the area of mathematical immunology. I find the atmosphere at the conference very pleasant and friendly. There is a high percentage of the participants who have changed fields.

In what follows I will summarize some of the most interesting things I heard. There is so much information to absorb that many deserving topics will get left out. In his talk Antonio Freitas presented experimental evidence for how the number of B cells in a mouse is controlled by a quorum sensing mechanism. In particular this involved the technique of parabiosis which I mentioned in a previous post. In fact he went further than standard parabiosis and joined three mice together rather than just two. According to the picture he presented the number of B cells is not determined by production rate but by something else, a soluble substance. Through a series of experiments this substance was identified as IgG antibody. More specifically, there is more than one population of B cells present and it is a population of cells secreting IgM which is held in check by the concentration of IgG. The IgG binds to a receptor on the B cells causing a repression. Mice where this mechanism fails suffer from a lupus-like syndrome.

Robin Callard talked about T cell homeostasis. He works at the Institute of Child Health and in his presentation the development of the immune system in children played an important role. With age the thymic production of T cells decreases but the number of T cells remains relatively constant. Due to the volume change of the body it is not the same thing to look at the number of T cells as to look at their density.  He mentioned the concept of TRECs (T cell receptor excision circles) which may be used as an indicator that T cells have recently come from the thymus. The origin of these is as follows. During the development of the T cell receptor DNA rearrangement takes place and some pieces of DNA which have been excised survive as closed loops in the cell. Due to other processes going on it is rather hard to interpret the significance of measurements of TRECs for T cell dynamics. Callard and his collaborators have produced a mathematical model in order to provide better insights into this question (J. Immunology, 183, 4329). In the last part of his talk Callard explained some ideas (which he described as speculation) about the dynamics of the long asymptomatic phase in HIV infection. The main idea was that HIV slowly damages the lymph nodes (or other lymphatic tissues). This proposed process is irreversible, which means that interrupting therapy in HIV (for instance in children) could have lasting negative effects.

Andreas Radbruch gave a talk about the ways in which modelling and experiment can be combined to obtain a better understanding of the immune system. He discussed three examples. The cytokine IL2 is responsible for the proliferation of T cells. In situations where certain T cells should not proliferate their growth must be held in check by other factors. The first example in the talk concerned a system responsible for this control which was only recently discovered. Key players are the transcription factor Foxo1 and the microRNA miR-182. The original work is in Nature Immunology 11, 1057. The second example concerned work on the way in which a T cell which has differentiated in the direction of Th1 then becomes committed to that state. The underlying work has already been mentioned in a previous post and since I had already studied this paper in some detail this was rather familiar ground for me. The third example was about memory B cells. There is a class of cells of this type which reside in the bone marrow with each one being attached to its own stromal cell. I did not understand the details of this story and had the impression that it was not so easy to follow for even some of the expert members of the audience.

I have just finished writing about the talks from yesterday and I will stop here for now. I hope to continue with my extracts from the conference in the near future.