Macrophages were infected with virulent B. abortus strain 2308 or attenuated strain 19. Intracellular bacteria were recovered at different times after infection and their proteomes compared. The virulent strain initially reduced most biosynthesis and altered its respiration, adaptations reversed later in infection. The attenuated strain was unable to match the magnitude of the virulent strain’s adjustments. The results provide insight into mechanisms utilized by Brucella to establish intracellular infections.

The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34–80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics.

No abstract

Chromatographic protein and peptide separation technologies enable comprehensive proteomic analysis of plasma and other complex biological samples by mass spectrometry. However, as the number of separations and/or fractions increases, so does the number of peptides split across fraction boundaries. Irreproducibility of peptide chromatographic separation results in peptides on or near the boundary moving partially or entirely into adjacent fractions. Peptide shifting across fraction boundaries increases the variability of measured peptide abundance, and so there is a trade-off between proteomic comprehensiveness using separation technologies and accurate quantitative proteomic measurements. In this paper, a method for detecting and correcting split peptides, called Peptide Shifter, is introduced and evaluated. An essential component of Peptide Shifter is a global peptide expression profile analysis that allows the inference of the underlying peptide shift pattern without the use of peptide labeling or internal standards. A controlled proteomic analysis of plasma samples demonstrates a 34% decrease in peptide intensity variability after the application of Peptide

Figure 6. Expression profile correlation heatmap for all pairs of peptides from Fraction 2. Each point in the heatmap represents the Spearman correlation between the expression profiles of two peptides. Green is high correlation and red is low correlation. Peptides are highly correlated to themselvesthus, the diagonal green line. Hierarchical clustering has been applied to group highly correlated peptides. Framed in blue are the peptides corresponding to the two most frequently occurring expression profiles in Fraction 2, which appear in Figure 5. The upper left blue box corresponds to peptides shifted into Fraction 2, whereas the lower right blue box corresponds to peptides shifted out of Fraction 2. As expected, these two sets of peptides are highly negatively correlated (two yellow boxes).