Biomedical subjects

Eric F Strittmatter

Publications and source records attributed to Eric F Strittmatter.

22 records · Page 2Linked to original sources

PubMedDate not supplied

Characterization of purified c-type heme-containing peptides and identification of c-type heme-attachment sites in Shewanella oneidenis cytochromes using mass spectrometry.

We describe methods for mass spectrometric identification of heme-containing peptides from c-type cytochromes that contain the CXXCH (X=any amino acid) sequence motif. The heme fragment ion yielded the most abundant MS/MS peak for standard heme-containing peptides with one amino acid difference for both 2+ and 3+ peptide charge states; both sequence and charge affect the extent of heme loss. Application to Shewanella oneidenis demonstrated the utility of this approach for identifying c-type heme-containing peptides from complex proteome samples.

Amino Acid Motifs↗

PubMedDate not supplied

Probability-based evaluation of peptide and protein identifications from tandem mass spectrometry and SEQUEST analysis: the human proteome.

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.

Blood Proteins↗

PubMedDate not supplied

Application of peptide LC retention time information in a discriminant function for peptide identification by tandem mass spectrometry.

We describe the application of a peptide retention time reversed phase liquid chromatography (RPLC) prediction model previously reported (Petritis et al. Anal. Chem. 2003, 75, 1039) for improved peptide identification. The model uses peptide sequence information to generate a theoretical (predicted) elution time that can be compared with the observed elution time. Using data from a set of known proteins, the retention time parameter was incorporated into a discriminant function for use with tandem mass spectrometry (MS/MS) data analyzed with the peptide/protein identification program SEQUEST. For singly charged ions, the number of confident identifications increased by 12% when the elution time metric is included compared to when mass spectral data is the sole source of information in the context of a Drosophila melanogaster database. A 3-4% improvement was obtained for doubly and triply charged ions for the same biological system. Application to the larger Rattus norvegicus (rat) and human proteome databases resulted in an 8-9% overall increase in the number of confident identifications, when both the discriminant function and elution time are used. The effect of adding "runner-up" hits (peptide matches that are not the highest scoring for a spectra) from SEQUEST is also explored, and we find that the number of confident identifications is further increased by 1% when these hits are also considered. Finally, application of the discriminant functions derived in this work with approximately 2.2 million spectra from over three hundred LC-MS/MS analyses of peptides from human plasma protein resulted in a 16% increase in confident peptide identifications (9022 vs 7779) using elution time information. Further improvements from the use of elution time information can be expected as both the experimental control of elution time reproducibility and the predictive capability are improved.

Animals↗

PubMedDate not supplied

Comparison of normal and breast cancer cell lines using proteome, genome, and interactome data.

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled identification of 2235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multistep search strategy was used to identify post-translational modifications, revealing several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal and cancer cell lines.

Amino Acid Sequence↗