Understanding the Immune System by Computer-Aided Modeling - Immunoinformatics - page 151

Fig. 2. We simulate the onset of an opportunistic disease by injecting a bacterium (e.g.,
Mycobacterium tuberculosis ) during the ninth year after the primal infection with HIV. While
the HIV count is still under control by means of a continuous cytotoxic activity (plot b) and by
a humoral response (plot d), the system that is weakened in its CD4 count (plot a) cannot cope
with the replication rate of the newly injected bacteria (plot c).
of output is shown in Fig. 2 that is produced by the simulation of a number of cells
contained in 10 μl of peripheral blood (about 20,000 immune cells with a repertoire of
4096 possible receptors fighting with an equivalent number of potential HIV strains).
Besides that, we can look at the HIV peptides that are expressed on the surface of
the antigen-processing cells, to determine if the wild-type virus undergoes mutations
able to escape MHC presentation. Likewise we can monitor any viral mutation to
check if there is a systematic behavior of the virus that allows it to escape the im-
mune system control (Bernaschi and Castiglione 2006).
An interesting feature of the model is the possibility to schedule the injection of
an arbitrary antigen at any time. For instance, at the beginning of a simulation, we
can infect the “virtual patient” with a wild-type HIV that weakens the immune sys-
tem. Then, during the simulation, it is possible to challenge again the immune system
by means of a fast-replicating bacterium like, for example, Mycobacterium tubercu-
losis (MTB). What we get, as depicted in Fig. 2, is the appearance of the expected
opportunistic disease. The MTB is injected 9 (simulated) years after the primal infec-
tion with HIV. At the time of the second antigenic challenge, the HIV is still under
control by means of a continuous anti-HIV cytotoxic activity (plot b) and by a spe-
cific humoral response (plot d). However, in the latent phase of the AIDS disease,
the system is weakened in its CD4 count (plot a) and eventually cannot cope with the
replication rate of the newly injected bacteria (plot c).
Note, however, that by injecting the same bacterium at the time the CD4
count is not too low, the immune system is able to defeat the challenge (not
shown), as it happens in reality for healthy immune systems. This demonstrates