Enrichment and Detection of Molecules Secreted by Tumor Cells Using Magnetic Reversed-Phase Particles and LC-MALDI-TOF-MS

Tumor cells change their genetic expression pattern as they progress to states of increasing malignancy. Investigations at the DNA and RNA level alone cannot provide all the information resulting after the translation and processing of the corresponding proteins, which is one reason for a poor correlation between mRNA and the respective protein abundance. In diagnostics, differentially expressed peptides or proteins are important markers for the early detection of cancer. Unfortunately, tumor cells secrete peptides and proteins in only very low amounts, making mass spectrometric determination very difficult. In this publication, methods have been developed for the effective enrichment and cleanup of substances secreted by cultivated cancer cells. To obviate peptides from fetal calf serum used in cell culture, a serum surrogate was developed, which maintained growth of the cancer cells. After the binding of substances from cell-culture supernatants to custom-made magnetic reversed-phase particles, the substances were eluted and separated by capillary high-performance liquid chromatography. Fractions were spotted directly on a MALDI target, and MALDI-TOF mass spectrometric data acquisition was performed in automatic mode. This technology was used to detect substances secreted by two mammary carcinoma cell lines differing in their malignancy (MCF-7, MDA-MB 231). Unequivocal differences in the peptide secretion patterns were observed. In conclusion, this system allows the sensitive investigation of peptides secreted by cancer cells in culture and provides a valuable tool for the investigation of cancer cells in different states of malignancy.     

Current trends in high throughput proteomics in cyanobacteria

Advancements in genome sequencing and high throughput proteomics of cyanobacterial strains led to 13 published reports, from a small number of laboratories. These successful studies focused on Synechocystis, Nostoc and Anabaena strains, prochlorococcus, and halotolerant Euhalothece. The implications of emerging quantitative aspects developed and applied in these large-scale studies are assessed in the wake of advanced cyanobacterial research. Furthermore, contributions from traditional and early high throughput analysis of cyanobacterial proteomics are compared and summarised. Finally, opinions are provided to link both the trends and the future challenges. This review aims to push the synergy between proteomics and cyanobacterial research to improve both the technical and biological significance.     

Analysis of glycoproteins in human serum by means of glycospecific magnetic bead separation and LC-MALDI-TOF/TOF analysis with automated glycopeptide detection.

Comprehensive proteomic analyses require efficient and selective pre-fractionation to facilitate analysis of post-translationally modified peptides and proteins, and automated analysis workflows enabling the detection, identification, and structural characterization of the corresponding peptide modifications. Human serum contains a high number of glycoproteins, comprising several orders of magnitude in concentration. Thereby, isolation and subsequent identification of low-abundant glycoproteins from serum is a challenging task. selective capturing of glycopeptides and -proteins was attained by means of magnetic particles specifically functionalized with lectins or boronic acids that bind to various structural motifs. Human serum was incubated with differentially functionalized magnetic micro-particles (lectins or boronic acids), and isolated proteins were digested with trypsin. Subsequently, the resulting complex mixture of peptides and glycopeptides was subjected to LC-MALDI analysis and database searching. In parallel, a second magnetic bead capturing was performed on the peptide level to separate and analyze by LC-MALDI intact glycopeptides, both peptide sequence and glycan structure. Detection of glycopeptides was achieved by means of a software algorithm that allows extraction and characterization of potential glycopeptide candidates from large LC-MALDI-MS/MS data sets, based on N-glycopeptide-specific fragmentation patterns and characteristic fragment mass peaks, respectively. By means of fast and simple glycospecific capturing applied in conjunction with extensive LC-MALDI-MS/MS analysis and novel data analysis tools, a high number of low-abundant proteins were identified, comprising known or predicted glycosylation sites. According to the specific binding preferences of the different types of beads, complementary results were obtained from the experiments using either magnetic ConA-, LCA-, WGA-, and boronic acid beads, respectively.