In collaboration with Dr. Vincent Melfi and the undergraduate
participants of the UBM project we will use DNA microarrays to 1) investigate
gene expression changes when the probiotic bacterium Lactobacillus reuteri is
exposed to stress. Undergraduates
currently in the lab have made significant contributions to the microarray
projects in the lab. Downstream analysis
of microarray data, including statistical and computational mining of the data,
is deeply rooted in mathematics.
Therefore students trained in both mathematics and biology will be
ideally prepared to tackle the large datasets that arise from genomic
technologies such as DNA microarrays.
Project -
Characterization of the it Lactobacillus reuteri stress response. Probiotics are live microbial supplements
that when ingested improve the overall health of the host. We are investigating the mechanisms by which
the probiotic bacterium Lactobacillus reuteri exerts these beneficial effects,
which are mostly unknown. One proposed
characteristic of probiotics that is believed to be important for their
function is the ability to survive various stresses, including acid stress in
the stomach and bile stress in the small intestine. Using DNA microarrays generated based on the L. reuteri
genome sequence we are studying the gene expression profiles of cells treated
with physiological concentrations of bile.
Undergraduates from the UBM program will have the opportunity to
participate in the project at all stages of the project, from the execution of
the experiment to data analysis. Often
there is a disconnect between the biologists that are performing genomic
experiments and the statisticians that are analyzing the data. By allowing undergraduates the opportunity to
participate in all phases of the project they will learn to bridge the gap that
so often affects the work in a negative way.
Mathematics undergraduates will have a real opportunity to make a
contribution in this project by helping us to apply several new statistical
models for identifying differentially expressed genes. In addition, computational biology software
programs will be applied to identify promoters in the L. reuteri genome and the
prediction of regulatory networks based on comparative genomic approaches. UBM math students comfortable with the algorithms
used in these software programs will be able to utilize them to their fullest
capability.
Lab
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