Date of Award


Degree Type


Degree Name

Doctor of Philosophy


Life Sciences

Major Professor

Robert L. Hettich, Frank W. Larimer

Committee Members

Jeffrey Becker, Loren Hauser, Steven W. Wilhelm


With the advent of whole genome sequencing, a new era of biology was ushered in allowing for “systems-biology” approaches to characterizing microbial systems. The field of systems biology aims to catalogue and understand all of the biological components, their functions, and all of their interactions in a living system as well as communities of living systems. Systems biology can be considered an attempt to measure all of the components of a living system and then produce a data-driven model of the system. This model can then be used to generate hypotheses about how the system will respond to perturbations, which can be tested experimentally. The first step in the process is the determination of a microbial genome. This process has, to a large extent, been fully developed, with hundreds of microbial genome sequences completed and hundreds more being characterized at a breathtaking pace. The developments of technologies to use this information and to further probe the functional components of microbes at a global level are currently being developed. The field of gene expression analysis at the transcript level is one example; it is now possible to simultaneously measure and compare the expression of thousands of mRNA products in a single experiment. The natural extension of these experiments is to simultaneously measure and compare the expression of all the proteins present in a microbial system. This is the field of proteomics.

With the development of electrospray ionization, rapid tandem mass spectrometry and database-searching algorithms, mass spectrometry (MS) has become the leader in the attempts to decipher proteomes. This research effort is very young and many challenges still exist. The goal of the work described here was to build a state-of-the-art robust MS-based proteomics platform for the characterization of microbial proteomes from isolates to communities. The research presented here describes the successes and challenges of this objective. Proteome analyses of the metal-reducing bacteria Shewanella oneidensis and the metabolically versatile bacteria Rhodopseudomonas palustris are given as examples of the power of this technology to elucidate proteins important to different metabolic states at a global level. The analysis of microbial proteomes from isolates is only the first step of the challenge. In nature, microbial species do not act alone but are always found in mixtures with other species where their intricate interactions are critical for survival. These studies conclude with some of the first efforts to develop methodologies to measure proteomes of simple controlled mixtures of microbial species and then present the first attempt at measuring the proteome of a natural microbial community, a biofilm from an acid mine drainage system. This microbial system illustrates life at the extreme of nature where life not only exists but flourishes in very acidic conditions with high metal concentrations and high temperatures. The technologies developed through these studies were applied to the first deep characterization of a microbial community proteome, the deciphering of the expressed proteome of the acid mine drainage biofilm.

The research presented here has led to development of a state-of-the-art robust proteome pipeline, which can now be applied to the proteome analysis of any microbial isolate for a sequenced species. The first steps have also been made toward developing methodologies to characterize microbial proteomes in their natural environments. These developments are key to integrating proteome technologies with genome and transcriptome technologies for global characterizations of microbial species at the systems level. This will lead to understanding of microbial physiology from a global view where instead of analyzing one gene or protein at a time, hundreds of genes/proteins will be interrogated in microbial species as the adapt and survive in the environment.

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