Spatial Aspects of HIV Infection - Mathematical Methods and Models in Biomedicine - page 22

dynamic behavior of immune cells in living tissue such as lymph nodes and the
spleen [ 1 , 17 , 67 , 119 ]. Other techniques besides two-photon microscopy such as
photoactivated localization microscopy or structured illumination microscopy allow
the visualization of immune cell activation processes even on a subcellular level [ 5 ].
The interaction of HIV-1 proteins with host cell molecules can be well addressed
using novel fluorescent imaging techniques [ 25 ]. Agent-based models can be used
to simply mimic the observed behavior of immune cells and virions by this kind of
experiments [ 10 , 15 ]. Using the resulting simulation frameworks and varying factors
such as susceptible cell density or vulnerability of mucosal and epithelial barriers
make these kinds of models suitable to address the questions mentioned above.
Spatially explicit models, such as agent-based models, will also help us to
address the question of under what conditions infected cells occur in clusters. What
role does cell-to-cell transmission play compared to diffusion of viral particles?
Does it vary during different stages of infection? These analyses can reveal whether
in a lymph node densely packed with susceptible target cells for HIV specific
immune responses might play a more important role for the containment of infection
than, for example, in blood where susceptible cells are more widely dispersed. The
detailed spatial structure of specific organs might also explain the different HIV
clearance dynamics observed in lymphoid tissue, blood, plasma, lung, and liver
[ 27 ]. It might help to explain why the CD4 + T cell population in mucosal tissue
is massively depleted during the first weeks of infection [ 107 ], while this loss is not
reflected in the peripheral blood [ 40 ].
Another advantage, and need, for agent-based models is the study of the
evolution of HIV while spreading through the host. Although current evidence
indicates that HIV infection can be founded by a single viral strain [ 112 ], the high
replication rate of HIV leads to tremendous variability of HIV viral strains inside a
single patient later during infection [ 62 ]. This diversity challenges the responding
immune system, leaving it unable to control viral replication at some point.
Agent-based models including spatial information allow one to follow individual
cells and virions, making it possible to observe the development of clusters of
infected cells containing the same viral variant. These models can be used to study
the evolutionary pressure of different kinds of immune responses (innate, cell-
mediated, and humoral) on HIV and, hence, on the overall disease progression and
development.
The spatial models presented in the previous sections, which have already been
applied to study HIV infection dynamics, have analyzed how HIV dynamics differ
in different compartments [ 27 ], how HIV infection spreads in solid tissue, and how
spatial patterns of infected cells change in relation to cell turnover [ 120 , 130 ]. They
showed that viral infectiousness can be much lower than estimated previously if
spatial structure is considered [ 120 ]. However, there is still a way to go to include all
the different aspects from the establishment of infection to the activation of immune
responses.
In summary, we would propose that spatially explicit models should be used: