Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias to some degree, assigned ranks among the techniques revealed that for most LC-FTICR-MS analyses linear regression normalization ranked either first or second. However, the lack of a definitive trend among the techniques suggested the need for additional investigation into adapting normalization approaches for label-free proteomics. Nevertheless, this study serves as an important step for evaluating approaches that address systematic biases related to relative quantification and label-free proteomics.

Implementation of uranium bioremediation requires methods for monitoring the membership and activities of the subsurface microbial communities that are responsible for reduction of soluble U(VI) to insoluble U(IV). Here, we report a proteomics-based approach for simultaneously documenting the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, aquifer. Three planktonic Geobacter-dominated samples were obtained from two wells down-gradient of acetate addition. Over 2,500 proteins from each of these samples were identified by matching liquid chromatography-tandem mass spectrometry spectra to peptides predicted from seven isolate Geobacter genomes. Genome-specific peptides indicate early proliferation of multiple M21 and Geobacter bemidjiensis-like strains and later possible emergence of M21 and G. bemidjiensis-like strains more closely related to Geobacter lovleyi. Throughout biostimulation, the proteome is dominated by enzymes that convert acetate to acetyl-coenzyme A and pyruvate for central metabolism, while abundant peptides matching tricarboxylic acid cycle proteins and ATP synthase subunits were also detected, indicating the importance of energy generation during the period of rapid growth following the start of biostimulation. Evolving Geobacter strain composition may be linked to changes in protein abundance over the course of biostimulation and may reflect changes in metabolic functioning. Thus, metagenomics-independent community proteogenomics can be used to diagnose the status of the subsurface consortia upon which remediation biotechnology relies.

The purple nonsulfur photosynthetic bacterium Rhodobacter capsulatus has been extensively studied for its metabolic versatility as well as for production of a gene transfer agent called RcGTA. Production of RcGTA is highest in the stationary phase of growth and requires the response regulator protein CtrA. The CtrA protein in Caulobacter crescentus has been thoroughly studied for its role as an essential, master regulator of the cell cycle. Although the CtrA protein in R. capsulatus shares a high degree of sequence similarity with the C. crescentus protein, it is nonessential and clearly plays a different role in this bacterium. We have used transcriptomic and proteomic analyses of wild-type and ctrA mutant cultures to identify the genes dysregulated by the loss of CtrA in R. capsulatus. We have also characterized gene expression differences between the logarithmic and stationary phases of growth. Loss of CtrA has pleiotropic effects, with dysregulation of expression of ϳ6% of genes in the R. capsulatus genome. This includes all flagellar motility genes and a number of other putative regulatory proteins but does not appear to include any genes involved in the cell cycle. Quantitative proteomic data supported 88% of the CtrA transcriptome results. Phylogenetic analysis of CtrA sequences supports the hypothesis of an ancestral ctrA gene within the alphaproteobacteria, with subsequent diversification of function in the major alphaproteobacterial lineages.The purple nonsulfur bacterium Rhodobacter capsulatus is a model organism for various aspects of bacterial physiology, such as bioenergetics and N 2 fixation, and also engages in an unusual mechanism of genetic exchange, carried out by a bacteriophage-like element called the R. capsulatus gene transfer agent (RcGTA) (34, 56). The production of RcGTA is maximal in the stationary phase of growth of R. capsulatus cultures (49) and is regulated by at least 2 distinct signaling systems, one through quorum sensing of a long chain acyl-homoserine lactone (43) and the other involving the response regulator protein CtrA (30).The CtrA protein was first characterized for Caulobacter crescentus (41), where it is essential for viability and acts as a master regulator of the cell cycle (reviewed in reference 45), controlling at least 25% (144 of 553) of the genes involved in cell cycle progression (31). Despite sharing remarkable sequence identity (71%) with the CtrA protein from C. crescentus, the R. capsulatus protein has a very different role because it is not essential and does not appear to be involved in cell cycle processes. One function of CtrA in common to the two species is the regulation of expression of genes that encode the flagellum (29, 41). The ctrA genes of Sinorhizobium meliloti (3), Brucella abortus (6), and Ruegeria sp. strain TM1040 (36) have also been studied. Similarly to C. crescentus and R. capsulatus CtrA, Ruegeria CtrA controls motility (36). A search of the GenBank database reveals that convincing homologs which share Ͼ50% identity with the C. crescen...

We describe the application of LC-MS without the use of stable isotope labeling for differential quantitative proteomic analysis of whole cell lysates of Shewanella oneidensis MR-1 cultured under aerobic and suboxic conditions. LC-MS/MS was used to initially identify peptide sequences, and LC-FTICR was used to confirm these identifications as well as measure relative peptide abundances. 2343 peptides covering 668 proteins were identified with high confidence and quantified. Among these proteins, a subset of 56 changed significantly using statistical approaches such as statistical analysis of microarrays, whereas another subset of 56 that were annotated as performing housekeeping functions remained essentially unchanged in relative abundance. Numerous proteins involved in anaerobic energy metabolism exhibited up to a 10-fold increase in relative abundance when S. oneidensis was transitioned from aerobic to suboxic conditions. Molecular & Cellular Proteomics 5:714 -725, 2006.Two of the most commonly used methods for quantitative proteomics are two-dimensional electrophoresis (2DE) 1 coupled to either MS or MS/MS and LC-MS/MS (1). In the 2DE-based approach, intact proteins are separated by 2DE, and the abundance of a protein is determined based on the stain intensity of the protein spot on the gel. The identity of the protein is now generally determined by MS analysis peptides after proteolysis of the protein spot. Since its inception in the mid-1970s, the 2DE-based approach has been routinely used for large scale quantitative proteomic analysis. Some of the disadvantages of this approach are that it is difficult to automate and has a limited detection capacity for proteins with extreme ranges in pI values, for hydrophobic proteins, and for low abundance proteins (1). It is generally believed that the intensity of an MS signal for a particular peptide does not always reflect its abundance due to ion suppression effects among co-eluting species. Thus, the LC-MS/MS-based approach often uses stable isotope labeling techniques, e.g. with 15 N, 18 O, stable isotope labeling by amino acids in cell culture (SILAC), and ICAT, to provide relative quantification (2-4). Although potentially providing the greatest accuracy, isotopic labeling has some disadvantages. Labeling with stable isotopes is expensive, and some labeling procedures involve complex processes and yield artifacts. It also can be computationally difficult to reliably define the isotopic "pairs" for relative quantification due to possible differences in the LC elution time of the labeled forms, incomplete mass spectrometric resolution of the isotopic pairs (5, 6), or the presence of other unresolved components.An alternative approach involves "label-free" methods that use relative peptide peak intensities that are generally performed in conjunction with a data normalization procedure. A linear correlation between the amount of an analyte and its peak area can be obtained by using a sufficiently low LC flow rate and a small amount of sample because ESI approach...