This preliminary study suggests that TS repetitive-sequence polymorphisms are predictive for tumor downstaging. TR sequences in TS promoter may be useful as a novel means of predicting response to preoperative 5-FU-based chemoradiation.

The analysis of proteomes from aerobic and photosynthetic Rhodobacter sphaeroides 2.4.1 cell cultures by liquid chromatography-mass spectrometry yielded approximately 6,500 high confidence peptides representing 1,675 gene products (39% of the predicted proteins). The identified proteins corresponded primarily to open reading frames (ORFs) contained within the two chromosomal elements of this bacterium, but a significant number were also observed from ORFs associated with 5 naturally occurring plasmids. Using the accurate mass and time (AMT) tag approach, comparative studies showed that a number of proteins were uniquely detected within the photosynthetic cell culture. The estimated abundances of proteins observed in both aerobic respiratory and photosynthetic grown cultures were compared to provide insights into bioenergetic models for both modes of growth. Additional emphasis was placed on gene products annotated as hypothetical to gain information as to their potential roles within these two growth conditions. Where possible, transcriptome and proteome data for R. sphaeroides obtained under the same culture conditions were also compared.

The high-throughput accurate mass and time (AMT) tag proteomic approach was utilized to characterize the proteomes for cytoplasm, cytoplasmic membrane, periplasm, and outer membrane fractions from aerobic and photosynthetic cultures of the gram-nagtive bacterium Rhodobacter sphaeroides 2.4.1. In addition, we analyzed the proteins within purified chromatophore fractions that house the photosynthetic apparatus from photosynthetically grown cells. In total, 8300 peptides were identified with high confidence from at least one subcellular fraction from either cell culture. These peptides were derived from 1514 genes or 35% percent of proteins predicted to be encoded by the genome. A significant number of these proteins were detected within a single subcellular fraction and their localization was compared to in silico predictions. However, the majority of proteins were observed in multiple subcellular fractions, and the most likely subcellular localization for these proteins was investigated using a Z-score analysis of estimated protein abundance along with clustering techniques. Good (81%) agreement was observed between the experimental results and in silico predictions. The AMT tag approach provides localization evidence for those proteins that have no predicted localization information, those annotated as putative proteins, and/or for those proteins annotated as hypothetical and conserved hypothetical.

A variety of strategies now exist for the extracellular expression of recombinant proteins using laboratory strains of Escherichia coli . However, secreted proteins often accumulate in the culture medium at levels that are too low to be practically useful for most synthetic biology and metabolic engineering applications. The situation is compounded by the lack of generalized screening tools for optimizing the secretion process. To address this challenge, we developed a genetic approach for studying and engineering protein-secretion pathways in E. coli . Using the YebF pathway as a model, we demonstrate that direct fluorescent labeling of tetracysteine-motif-tagged secretory proteins with the biarsenical compound FlAsH is possible in situ without the need to recover the cell-free supernatant. High-throughput screening of a bacterial strain library yielded superior YebF expression hosts capable of secreting higher titers of YebF and YebF-fusion proteins into the culture medium. We also show that the method can be easily extended to other secretory pathways, including type II and type III secretion, directly in E. coli . Thus, our FlAsH-tetracysteine-based genetic assay provides a convenient, high-throughput tool that can be applied generally to diverse secretory pathways. This platform should help to shed light on poorly understood aspects of these processes as well as to further assist in the construction of engineered E. coli strains for efficient secretory-protein production.