Consistency of a two clinical site sample collection: a proteomics study.

PURPOSE: We investigated the ability to perform a clinical proteomic study using samples collected at different times from two independent clinical sites. EXPERIMENTAL DESIGN: Label-free 2-D-LC-MS proteomic analysis was used to differentially quantify tens of thousands of peptides from human plasma. We have asked whether samples collected from two sites, when analyzed by this type of peptide profiling, reproducibly contain detectable peptide markers that are differentially expressed in the plasma of disease (advanced renal cancer) patients relative to healthy normals. RESULTS: We have demonstrated that plasma proteins enriched in disease patients are indeed detected reproducibly in both clinical collections. Regression analysis, unsupervised hierarchical clustering and PCA detected no systematic bias in the data related to site of sample collection and processing. Using a genetic algorithm, support vector machine classification method, we were able to correctly classify disease samples at 88% sensitivity and 94% specificity using the second site as an independent validation set. CONCLUSIONS AND CLINICAL RELEVANCE: We conclude that multiple site collection, when analyzed by label-free 2-D-LC-MS, generates data that are sufficiently reproducible to guide reliable biomarker discovery.

The discovery of biaryl acids and amides exhibiting antibacterial activity against Gram-positive bacteria.

Solid-phase synthetic methods for biaryl-based compounds were developed resulting in the construction of two 1000-member libraries. Numerous compounds were identified by high-throughput screening using whole cell screens to exhibit anti-microbial activity against Gram-positive bacteria. A series of biaryl compounds containing natural and unnatural amino acids were made to explore the SAR of the amino acid functionality.

Differential fluorescence induction analysis of Streptococcus pneumoniae identifies genes involved in pathogenesis.

Differential fluorescence induction (DFI) technology was used to identify promoters of Streptococcus pneumoniae induced under various in vitro and in vivo conditions. A promoter-trap library using green fluorescent protein as the reporter was constructed in S. pneumoniae, and the entire library was screened for clones exhibiting increased gfp expression under the chosen conditions. The in vitro conditions used were chosen to mimic aspects of the in vivo environment encountered by the pathogen once it enters a host: changes in temperature, osmolarity, oxygen, and iron concentration, as well as blood. In addition, the library was used to infect animals in three different models, and clones induced in these environments were identified. Several promoters were identified in multiple screens, and genes whose promoters were induced twofold or greater under the inducing condition were mutated to assess their roles in virulence. A total of 25 genes were mutated, and the effects of the mutations were assessed in at least two different infection models. Over 50% of these mutants were attenuated in at least one infection model. We show that DFI is a useful tool for identifying bacterial virulence factors as well as a means of elucidating the microenvironment encountered by pathogens upon infection.