Peter James

Protein phosphorylation is one of the most important and common ways of regulating protein function in cells. However, phosphopeptides are difficult to analyse, ionising poorly under standard MALDI conditions. Several methods have been developed to deal with the low sensitivity and specificity of phosphopeptide analysis. Here, we show an approach using a simple one‐step beta‐elimination/Michael addition reaction for the derivatization of phosphoserine and phosphothreonine. The substitution of the negatively charged phosphate group by a positively charged S‐ethylpyridyl group greatly improves the ionisation of the modified peptides, especially in MALDI MS, increasing the sensitivity of the analysis. The modification allows the formation of a unique fragment ion at m/z 106 under mild collisional activation conditions, which can be used for parent (precursor) ion scanning in order to improve both the sensitivity and the selectivity of the analysis. The optimisation of the approach is described for a standard model peptide and protein and then applied to phosphorylation analysis in two biologically derived proteins purified from different experimental systems.

The acidic proteome of Lactococcus lactis grown anaerobically was compared for three different growth conditions: cells growing on maltose, resting cells metabolizing maltose, and cells growing on glucose. In maltose metabolizing cells several proteins were up‐regulated compared with glucose metabolizing cells, however only some of the up‐regulated proteins had apparent relation to maltose metabolism. Cells growing on maltose produced formate, acetate and ethanol in addition to lactate, whereas resting cells metabolizing maltose and cells growing on glucose produced only lactate. Increased levels of alcohol‐acetaldehyde dehydrogenase (ADH) and phosphate acetyltransferase (PTA) in maltose‐growing cells compared with glucose‐growing cells coincided with formation of mixed acids in maltose‐growing cells. The resting cells did not grow due to lack of an amino acid source and fermented maltose with lactate as the sole product, although ADH and PTA were present at high levels. The maltose consumption rate was approximately three times lower in resting cells than in exponentially growing cells. However, the enzyme levels in resting and growing cells metabolizing maltose were similar, which indicates that the difference in product formation in this case is due to regulation at the enzyme level. The levels of 30S ribosomal proteins S1 and S2 increased with increasing growth rate for resting cells metabolizing maltose, maltose‐growing cells and glucose‐growing cells. A modified form of HPr was synthesized under amino acid starvation. This is suggested to be due to alanine misincorporation for valine, which L. lactis is auxotrophic for. L. lactis conserves the protein profile to a high extent, even after prolonged amino acid starvation, so that the protein expression profile of the bacterium remains almost invariant.

In order to maximize protein identification by peptide mass fingerprinting noise peaks must be removed from spectra and recalibration is often required. The preprocessing of the spectra before database searching is essential but is time‐consuming. Nevertheless, the optimal database search parameters often vary over a batch of samples. For high‐throughput protein identification, these factors should be set automatically, with no or little human intervention. In the present work automated batch filtering and recalibration using a statistical filter is described. The filter is combined with multiple data searches that are performed automatically. We show that, using several hundred protein digests, protein identification rates could be more than doubled, compared to standard database searching. Furthermore, automated large‐scale in‐gel digestion of proteins with endoproteinase LysC, and matrix‐assisted laser desorption/ionization‐time of flight (MALDI‐TOF) analysis, followed by subsequent trypsin digestion and MALDI‐TOF analysis were performed. Several proteins could be identified only after digestion with one of the enzymes, and some less significant protein identifications were confirmed after digestion with the other enzyme. The results indicate that identification of especially small and low‐abundance proteins could be significantly improved after sequential digestions with two enzymes.

In this review I will describe the advances that have recently been made in ‘traditional’ two‐dimensional gel based protein expression analysis. A major jump has been made toward the automation of gel image analysis and comparison, one of the major bottlenecks in the analysis chain as well as the automation of spot excision and preparation for mass spectrometric analysis. Currently the gel‐based ‘proteome mapping’ approach is highly effective and 300 gels and over 10,000 spots a week can be analysed. Very recently, viable alternatives to the use of two‐dimensional gel electrophoresis have emerged and these approaches are discussed here. In combination with the recently developed stable isotopic tagging methods for peptide quantitation and new mass spectrometers, this emerging technology will be a rapid and highly effective alternative to gel‐based methods with few of the latter′s shortcomings.