Peter James

Proteomics and automation

Proteome analysis is concerned with the global changes in protein expression as visualized most commonly by two‐dimensional gel electrophoresis and analyzed by mass spectrometry. A drastic increase in the rapidity and reproducibility of protein isolation and identification is needed for proteome analysis to become a useful complement to global mRNA analysis. Simplification and standardization, based on innovation in both hard‐ and software, are prerequisites to the creation of automated proteomics platforms that are both robust and user‐friendly, and will allow many more laboratories access to this technique. In this review we highlight the weak points in the chain of analysis (such as sample handling, protein separation and digestion) and summarize recent trends toward automation in instrumentation and software and offer our own personal view of future developments in the field.

GRP94 (endoplasmin) co-purifies with and is phosphorylated by Golgi apparatus casein kinase.

A phosphorylatable protein band of about 94 kDa (as judged by SDS–PAGE) which co‐purifies and co‐immunoprecipitates with Golgi apparatus casein kinase (G‐CK) from rat lactating mammary gland has been shown by mass spectrometric sequence analysis to be identical or very similar to the glucose‐regulated protein, GRP94. GRP94 is also readily phosphorylated by G‐CK (K m=0.2 μM) at seryl sites which are different from the sites affected by casein kinase‐2 (CK2) in the same protein. A study with peptide substrates would indicate that the G‐CK sites in GRP94 conform to the motif S‐R/K‐E‐X (X being different from D and E) which is not recognized by CK2.

Proteolysis of human calcitonin in excised bovine nasal mucosa : Elucidation of the metabolic pathway by liquid secondary ionization mass spectrometry (LSIMS) and matrix assisted laser desorption ionization mass spectrometry (MALDI)

AbstractPurpose. Two calcitonins, i.e. human calcitonin (hCT) and, for comparison, salmon calcitonin (sCT), were chosen as peptide models to investigate nasal mucosal metabolism. Methods. The susceptibility of hCT and sCT to nasal mucosal enzymes was assessed by in-and-out reflection kinetics experiments in an in vitro model based on the use of freshly excised bovine nasal mucosa, with the mucosal surface of the mucosa facing the peptide solution. The kinetics of CT degradation in the bulk solution was monitored by HPLC. Peptide sequences of the main nasal metabolites of hCT were analyzed by using both liquid secondary ionization mass spectrometry (LSIMS), following HPLC fractionation of the metabolites, and matrix-assisted laser desorption ionization mass (MALDI) spectrometry. For sCT, the molecular weights of two major metabolites were determined by LC-MS with electrospray ionization. Results. Both CTs were readily metabolized by nasal mucosal enzymes. In the concentration range studied metabolic rates were higher with hCT than with sCT. Presence of endopeptidase activities in the nasal mucosa was crucial, cleaving both calcitonins in the central domain of the molecules. Conclusions. Typically, initial metabolic cleavage of hCT in nasal mucosa is due to both chymotryptic- and tryptic-like endopeptidases. The subsequent metabolic break-down follows the sequential pattern of aminopeptidase activity. Tryptic endopeptidase activity is characteristic of nasal sCT cleavage.

Polypeptide sequence of the chlorophyll a/b/c-binding protein of the prasinophycean alga Mantoniella squamata.

The primary structure of the Chla/b/c-binding protein from Mantoniella squamata is determined. This is the first report that protein sequencing reveals one modified amino acid resulting in a LHCP-specific TFA-cleavage site. The comparison of the sequence of Mantoniella with other Chla/b-and Chla/c-binding proteins shows that the modified amino acid is located in a region which is highly conserved in all these proteins. The alignment also reveals that the LHCP of Mantoniella is related to the Chla/b-binding proteins. Finally, possible Chl-binding regions are discussed.

Cell fingerprinting: An approach to classifying cells according to mass profiles of digests of protein extracts

We present a statistical framework for classifying cells according to the set of peptide masses obtained by mass spectrometric analysis of digestions of whole cell protein extracts. The digest is separated by high performance liquid chromatography (HPLC) coupled directly to a mass spectrometer either by an electrospray interface or by collection to a matrix‐assisted laser desorption/ionization target plate. Here, the mass to charge ratio, intensity, and HPLC retention time of the peptides are measured. We have used defined bacterial strains to test this approach. For each bacterium, this process is repeated for extracts obtained at different points in the growth curve in order to try and define an invariant set of signals that uniquely identify the bacterium. This paper presents algorithms for the creation of this cell fingerprint database and develops a Bayesian classification scheme for deciding whether or not an unknown bacterium has a match in the database. Our initial testing based on a limited data set of three bacteria indicates that our approach is feasible. Via a jack‐knife test, our Bayesian classification scheme correctly identified the bacterium in 67.8% of the cases.

Interpreting Peptide Tandem Mass-Spectrometry Fragmentation Spectra

Mass spectrometers separate molecules according to their mass-to-charge ratio (m/z) using magnetic fields to deflect the ions [magnetic-sector mass spectrometry (MS)], crossed voltage (direct current) and radio-frequency (RF) emissions to create stable trajectories (quadrupole or ion-trap MS) or mass-selective acceleration to separate the ions in space [time-of-flight (TOF) MS]. All of these techniques require the ions to be in a vacuum (between 10-3 and 10-8 Torr). Thus, the main problem is moving the molecules to be analysed into the gas phase in an ionised state.