Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of ~10³) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 10⁶ for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.     

Proteomic profiling of serum samples from chikungunya-infected patients provides insights into host response

Background

Chikungunya is a highly debilitating febrile illness caused by Chikungunya virus, a single-stranded RNA virus, which is transmitted by Aedes aegypti or Aedes albopictus mosquito species. The pathogenesis and host responses in individuals infected with the chikungunya virus are not well understood at the molecular level. We carried out proteomic profiling of serum samples from chikungunya patients in order to identify molecules associated with the host response to infection by this virus.

Results

Proteomic profiling of serum obtained from the infected individuals resulted in identification of 569 proteins. Of these, 63 proteins were found to be differentially expressed (≥ 2-fold) in patient as compared to control sera. These differentially expressed proteins were involved in various processes such as lipid metabolism, immune response, transport, signal transduction and apoptosis.

Conclusions

This is the first report providing a global proteomic profile of serum samples from individuals infected with the chikungunya virus. Our data provide an insight into the proteins that are involved as host response factors during an infection. These proteins include clusterin, apolipoproteins and S100A family of proteins.     

Phosphoproteomic analysis identifies insulin enhancement of discoidin domain receptor 2 phosphorylation

The discoidin domain receptors (DDRs) are collagen binding receptor tyrosine kinases that play important roles in cell migration, invasion and adhesion. Crosstalk between growth factor signaling and components of the extracellular matrix are drivers of cellular function but the integrated signaling networks downstream of such crosstalk events have not been extensively characterized. In this report, we have employed mass spectrometry-based quantitative phosphotyrosine analysis to identify crosstalk between DDR2 and the insulin receptor. Our phosphoproteomic analysis reveals a cluster of phosphorylation sites in which collagen and insulin cooperate to enhance phosphotyrosine levels. Importantly, Y740 on the DDR2 catalytic loop was found in this cluster indicating that insulin acts to promote collagen I signaling by increasing the activity of DDR2. Furthermore, we identify two additional migration associated proteins that are candidate substrates downstream of DDR2 activation. Our data suggests that insulin promotes collagen I signaling through the upregulation of DDR2 phosphorylation which may have important consequences in DDR2 function in health and disease.     

Tissue damage in organic rainbow trout muscle investigated by proteomics and bioinformatics

The response to tissue damage is a complex process, which involves the coordinated regulation of multiple proteins to ensure tissue repair. In order to investigate the effect of tissue damage in a lower vertebrate, samples were taken from rainbow trout (Oncorhynchus mykiss) at day 7 after damage and proteins were separated using 2DE. The experimental design included two groups of rainbow trout, which were fed organic feed either with or without astaxanthin. In total, 96 proteins were found to be affected by tissue damage, clearly demonstrating in this lower vertebrate the complexity and magnitude of the cellular response, in the context of a regenerative process. Using a bioinformatics approach, the main biological function of these proteins were assigned, showing the regulation of proteins involved in processes such as apoptosis, iron homeostasis, and regulation of muscular structure. Interestingly, it was established that exclusively within the astaxanthin feed group, three members of the annexin protein family (annexin IV, V, and VI) were regulated in response to tissue damage.     

Extending the coverage of spectral libraries: A neighbor‐based approach to predicting intensities of peptide fragmentation spectra

Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well‐studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor‐based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K‐nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20–60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.     

Bottom‐up proteome analysis of E. coli using capillary zone electrophoresis‐tandem mass spectrometry with an electrokinetic sheath‐flow electrospray interface

The Escherichia coli proteome was digested with trypsin and fractionated using SPE on a C18 SPE column. Seven fractions were collected and analyzed by CZE‐ESI‐MS/MS. The separation was performed in a 60‐cm‐long linear polyacrylamide‐coated capillary with a 0.1% v/v formic acid separation buffer. An electrokinetic sheath‐flow electrospray interface was used to couple the separation capillary with an Orbitrap‐Velos operating in higher‐energy collisional dissociation mode. Each CZE‐ESI‐MS/MS run lasted 50 min and total MS time was 350 min. A total of 23 706 peptide spectra matches, 4902 peptide IDs, and 871 protein group IDs were generated using MASCOT with false discovery rate less than 1% on the peptide level. The total mass spectrometer analysis time was less than 6 h, the sample identification rate (145 proteins/h) was more than two times higher than previous studies of the E. coli proteome, and the amount of sample consumed (<1 μg) was roughly fourfold less than previous studies. These results demonstrate that CZE is a useful tool for the bottom‐up analysis of prokaryote proteomes.     

Tissue proteomics of the low‐molecular weight proteome using an integrated cLC‐ESI‐QTOFMS approach

Analysis of the protein/peptide composition of tissue has provided meaningful insights into tissue biology and even disease mechanisms. However, little has been published regarding top down methods to investigate lower molecular weight (MW) (500–5000 Da) species in tissue. Here, we evaluate a tissue proteomics approach involving tissue homogenization followed by depletion of large proteins and then cLC‐MS (where c stands for capillary) analysis to interrogate the low MW/low abundance tissue proteome. In the development of this method, sheep heart, lung, liver, kidney, and spleen were surveyed to test our ability to observe tissue differences. After categorical tissue differences were demonstrated, a detailed study of this method's reproducibility was undertaken to determine whether or not it is suitable for analyzing more subtle differences in the abundance of small proteins and peptides. Our results suggest that this method should be useful in exploring the low MW proteome of tissues.