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2017 ; 8
(ä): 645
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Multiplicity of Mathematical Modeling Strategies to Search for Molecular and
Cellular Insights into Bacteria Lung Infection
#MMPMID28912729
Cantone M
; Santos G
; Wentker P
; Lai X
; Vera J
Front Physiol
2017[]; 8
(ä): 645
PMID28912729
show ga
Even today two bacterial lung infections, namely pneumonia and tuberculosis, are
among the 10 most frequent causes of death worldwide. These infections still lack
effective treatments in many developing countries and in immunocompromised
populations like infants, elderly people and transplanted patients. The
interaction between bacteria and the host is a complex system of interlinked
intercellular and the intracellular processes, enriched in regulatory structures
like positive and negative feedback loops. Severe pathological condition can
emerge when the immune system of the host fails to neutralize the infection. This
failure can result in systemic spreading of pathogens or overwhelming immune
response followed by a systemic inflammatory response. Mathematical modeling is a
promising tool to dissect the complexity underlying pathogenesis of bacterial
lung infection at the molecular, cellular and tissue levels, and also at the
interfaces among levels. In this article, we introduce mathematical and
computational modeling frameworks that can be used for investigating molecular
and cellular mechanisms underlying bacterial lung infection. Then, we compile and
discuss published results on the modeling of regulatory pathways and cell
populations relevant for lung infection and inflammation. Finally, we discuss how
to make use of this multiplicity of modeling approaches to open new avenues in
the search of the molecular and cellular mechanisms underlying bacterial
infection in the lung.