We describe the practical implementation of a new RP (pH 10 - pH 2) 2D HPLC-ESI/MS scheme for large-scale bottom-up analysis in proteomics. When compared to the common SCX-RP approach, it provides a higher separation efficiency in the first dimension and increases the number of identified peptides/proteins. We also employed the methodology of our sequence-specific retention calculator (SSRCalc) and developed peptide retention prediction algorithms for both LC dimensions. A diverse set of approximately 10,000 tryptic peptides from the soluble protein fraction of whole NK-type cells gave retention time versus hydrophobicity correlations, with R (2) values of 0.95 for pH 10 and 0.945 for pH 2 (formic acid) separation modes. The superior separation efficiency and the ability to use retention prediction to filter out false-positive MS/MS identifications gives promise that this approach will be a method of choice for large-scale proteomics analyses in the future. Finally, the "semi-orthogonal" separation selectivity permits the concatenation of fractions in the first dimension of separation before the final LC-ESI MS step, effectively cutting the analysis time in half, while resulting in a minimal reduction in protein identification.
BackgroundClostridium thermocellum produces H2 and ethanol, as well as CO2, acetate, formate, and lactate, directly from cellulosic biomass. It is therefore an attractive model for biofuel production via consolidated bioprocessing. Optimization of end-product yields and titres is crucial for making biofuel production economically feasible. Relative protein expression profiles may provide targets for metabolic engineering, while understanding changes in protein expression and metabolism in response to carbon limitation, pH, and growth phase may aid in reactor optimization. We performed shotgun 2D-HPLC-MS/MS on closed-batch cellobiose-grown exponential phase C. thermocellum cell-free extracts to determine relative protein expression profiles of core metabolic proteins involved carbohydrate utilization, energy conservation, and end-product synthesis. iTRAQ (isobaric tag for relative and absolute quantitation) based protein quantitation was used to determine changes in core metabolic proteins in response to growth phase.ResultsRelative abundance profiles revealed differential levels of putative enzymes capable of catalyzing parallel pathways. The majority of proteins involved in pyruvate catabolism and end-product synthesis were detected with high abundance, with the exception of aldehyde dehydrogenase, ferredoxin-dependent Ech-type [NiFe]-hydrogenase, and RNF-type NADH:ferredoxin oxidoreductase. Using 4-plex 2D-HPLC-MS/MS, 24% of the 144 core metabolism proteins detected demonstrated moderate changes in expression during transition from exponential to stationary phase. Notably, proteins involved in pyruvate synthesis decreased in stationary phase, whereas proteins involved in glycogen metabolism, pyruvate catabolism, and end-product synthesis increased in stationary phase. Several proteins that may directly dictate end-product synthesis patterns, including pyruvate:ferredoxin oxidoreductases, alcohol dehydrogenases, and a putative bifurcating hydrogenase, demonstrated differential expression during transition from exponential to stationary phase.ConclusionsRelative expression profiles demonstrate which proteins are likely utilized in carbohydrate utilization and end-product synthesis and suggest that H2 synthesis occurs via bifurcating hydrogenases while ethanol synthesis is predominantly catalyzed by a bifunctional aldehyde/alcohol dehydrogenase. Differences in expression profiles of core metabolic proteins in response to growth phase may dictate carbon and electron flux towards energy storage compounds and end-products. Combined knowledge of relative protein expression levels and their changes in response to physiological conditions may aid in targeted metabolic engineering strategies and optimization of fermentation conditions for improvement of biofuels production.
Introduction Although the clinical effects of infliximab therapy in rheumatoid arthritis have been documented extensively, the biological effects of this intervention continue to be defined. We sought to examine the impact of infliximab therapy on the serum proteome of rheumatoid arthritis patients by means of a mass spectrometry-based approach.
The wide dynamic range of proteins in biological samples poses a challenge for the detection of low-abundance proteins. Recently, combinatorial hexapeptide peptide libraries have been suggested as an approach to normalization of proteins in such mixtures. We examined the reproducibility of a commercial hexapeptide ligand library for quantitative and comparative serum proteomic analysis. We also compared this technology with IgY-based affinity depletion.
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