Current understanding of how antibiotics induce bacterial cell death is centered on the essential bacterial cell function that is inhibited. However, antibiotic-mediated cell death is a complex, multi-factorial process that begins with the physical interaction between a drug molecule and its specific target, and involves alterations to the affected bacterium at the biochemical, molecular, regulatory and structural levels. A deeper understanding of the complexity of interactions between the drug, the target and the rest of the genome, and thus of the specific underlying mechanisms that lead up to antibiotic resistance, is essential for the successful development of new treatment strategies to kill multi-drug resistant bacteria as well as strategies to prevent the emergence and spread of antibiotic resistance.
We utilize cutting edge genome-wide, experimental and bioinformatical systems approaches, of which we have recently developed several ourselves, in order to construct drug/gene interaction networks that mediate the bacterial antibiotic responses. These networks are subsequently used to direct the development of new therapeutic treatments.
Microbes are extremists, being found on the most inhospitable places on earth; they live on the slopes of the highest mountains; the edges of volcanoes; in deep-sea ocean vents; and they can even survive solitarily deep under ground. Living on and inside the human body they outnumber human cells 10:1, raising the philosophical question of what defines a human being. The robustness and impressive evolutionary potential of bacteria gives them the amazing ability to deal with almost any environment they are confronted with. In the lab we uncover the capabilities of different bacterial species in order to create a biological toolbox that is filled with components that can be used to engineer bacteria with new traits and novel applicability.
An important goal in modern biology is to understand the relationship between genotype and phenotype; what constitutes a phenotype, which genes are involved and how do they interact to provide an efficient yet robust response to environmental change. With respect to pathogenic microorganisms, the goal of uncovering genotype-phenotype relationships is especially relevant, because the lack of understanding about the function of a significant part of the (pan-)genome currently hampering the design of novel strategies to battle infectious diseases. Developing high-throughput approaches for non-model (pathogenic) organisms that can match genotypes to phenotypes under in vitro and in vivo (infection) conditions is therefore crucial.
We recently developed the now widely used massively parallel sequencing technique, Tn-seq (van Opijnen et al., 2009), and have drawn up a detailed roadmap to link genotypes to phenotypes (Van Opijnen and Camilli 2012). New work in the lab focuses on developing strategies that automate the discovery of genotype-phenotype links and the placement of genes in their pathways.
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