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My research assumes that
organisms that can cause disease manifestations are indeed
living organisms with there own ecologies and evolutionary
histories - similar to plants, animals, and fungi. Using
this as an intellectual foundation, I investigate the
ecology (interactions affecting distribution and abundance)
and evolution (change in geno- and phenotype due to neutral
or selected processes) of disease causing organisms and
their natural host populations. This approach is becoming
popular in the study of organisms that cause disease
in humans and agriculturally important species such as
West Nile virus, wheat rust, and Lyme disease. Understanding
the natural biology of these organisms is a crucial step
in the long-term control of diseases.
My primary research has
focused on the bacterium that causes Lyme disease, Borrelia
burgdorferi, in forest in the Northeastern United States.
B. burgdorferi is carried among vertebrate hosts by the
black-legged tick, Ixodes scapularis. These ticks occasionally
bite humans and, if infected, can transmit the bacteria,
resulting in human Lyme disease. For the majority of
time, B. burgdorferi is passed among feral vertebrates
such as mice, shrews, and chipmunks. I have focused on
the interactions between these host species and B. burgdorferi
genotypes that affect the fitness and dynamics of pathogen
population. The fitness of B. burgdorferi, as measured
by the number of new ticks that acquire the pathogen,
is equivalent to the human risk of contracting Lyme disease.
We recently discovered that each vertebrate species can
host only a subset of the B. burgdorferi genotypes, but
the genotype subset hosted differs among species. Thus,
all fifteen genotypes coexist in northeastern forests
as a multiple niche polymorphism where vertebrate species
act as niches - the genetic diversity of the pathogen
is maintained by the biodiversity of hosts (Brisson and
Dykhuizen, 2004). In addition, the abundance of each
genotype in ticks - equivalent to the human Lyme disease
risk - is directly related to the composition and relative
abundance of host species (Brisson and Dykhuizen, 2006). One of the most important
problems in population ecology and disease ecology involves
the development of theory that will allow prediction
of the dynamics of populations of disease causing organisms.
I have begun to address this area with a biologically
realistic mathematical model that predicts the frequency
of each B. burgdorferi genotype from empirical data on
the density of host species and the rate each genotype
is transmitted from hosts to ticks. Thus, by knowing
the densities of each host species, we can predict proportion
of ticks carrying each B. burgdorferi genotype, including
the four human infectious genotypes (Sienost et al.,
1999). This model can be used to predict the risk of
human Lyme disease in locales around the Northeastern
United States.
Work in my lab is not
limited to ecology or B. burgdorferi. Current projects
include data-based modeling, molecular evolution, experimental
evolution, and public health research. I am open to studies
of any sort that are hypothesis driven and involve the
interactions between a microbe and a eukaryote. These
interactions need not be pathogenic, mutualistic relationships
are equally interesting and often follow a similar theoretical
framework.
Dr. Brisson is a member of the Graduate Group in Cell and Molecular
Biology (CAMB) where he is involved in several areas of research:
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