Changes in the Protein Expression of Yeast as a Function of Carbon Source

Abstract

Protein expression trends in yeast were monitored as a function of carbon source (glucose versus galactose) using multidimensional high performance liquid chromatography (HPLC) coupled to gas-phase fractionation, using relative intensity triggering (GPFri). Size exclusion HPLC was used to separate whole cell lysates, and following proteolysis of these fractions, each was separated by reversed phase HPLC, which was coupled on-line via electrospray to an ion trap mass spectrometer. The GPFri technique increased the dynamic range of proteins detected by increasing the number of peptide ions subjected to low energy collision induced dissociation to the 24 most intense ions in each of the survey scans. No protein or peptide labeling was used; instead, the number of SEQUEST identifications for each peptide (previously termed "hits") were used as a semiquantitative means of assessing both the direction (increase vs decrease) and significance of change in protein abundance. None of the traditional SEQUEST filters, e.g., Xcorr, DelCn, Sp, Rsp, etc., were employed in this study. Instead, a Student's t-test was used to distinguish those proteins that significantly and reproducibly changed between carbon sources from those that did not. This relied on the SEQUEST misassignments occurring in equal proportion between treatments and thereby negating each other; statistically significant changes in SEQUEST assignments were nonrandom events by definition and therefore reflective of correct identifications. This method of data analysis showed a large degree of concordance with results reported by other groups in similar transcriptional profiling and proteomic experiments. In all, 176 and 231 (fold-change > or = 1.1; p < or = 0.05) proteins were identified as being increased in peptide hit number when the yeast cells' source of carbon was changed between glucose and galactose, respectively.

Correlation of mRNA Expression and Protein Abundance Affected by Multiple Sequence Features Related to Translational Efficiency in Desulfovibrio vulgaris: A Quantitative Analysis

“…Peptide identification was performed using SEQUEST Version 2.7 (ThermoQuest) (Eng et al 1994;Yates et al 1995) to search the D. vulgaris protein sequence database (Heidelberg et al 2004). The relative protein abundance was estimated on the basis of the number of peptide hits (Gao et al 2003;Qian et al 2005). The peptide hits for a given protein were the average of three LC-MS/MS measurements.…”

Protein Expression in a Drosophila Model of Parkinson's Disease

“…34 In another study of protein expression changes in yeast as a function of carbon source, Opiteck and co-workers proposed a protein to be differentially expressed when the fold change in peptide hits was equal to or greater than 1.1 and the P value from a Student's t-test was equal to or less than 0.05. 33 In the present work, we have utilized a strict set of criteria that are designed to focus our attention to those proteins that have been identified by a large number of peptide hits and also appear to vary substantially in abundance (between the PD-model and control animals). The criteria used for selection are as follows.…”

Quantitative proteomics of intracellular Porphyromonas gingivalis

“…Therefore, an effective system was developed for measuring protein abundance change in P. gingivalis without the use of stable isotopes. A paper describing these quantitative methods based on spectral counting [19,20] and signal intensity measurements in MS 1 has been published [12]. We report our data here based on both types of calculation because it is not clear at present that either approach is better under all conditions.…”