Identification of factors that function in Drosophila salivary gland cell death during development using proteomics

Proteasome inhibitors induce cell death and are used in cancer therapy, but little is known about the relationship between proteasome impairment and cell death under normal physiological conditions. Here, we investigate the relationship between proteasome function and larval salivary gland cell death during development in Drosophila. Drosophila larval salivary gland cells undergo synchronized programmed cell death requiring both caspases and autophagy (Atg) genes during development. Here, we show that ubiquitin proteasome system (UPS) function is reduced during normal salivary gland cell death, and that ectopic proteasome impairment in salivary gland cells leads to early DNA fragmentation and salivary gland condensation in vivo. Shotgun proteomic analyses of purified dying salivary glands identified the UPS as the top category of proteins enriched, suggesting a possible compensatory induction of these factors to maintain proteolysis during cell death. We compared the proteome following ectopic proteasome impairment to the proteome during developmental cell death in salivary gland cells. Proteins that were enriched in both populations of cells were screened for their function in salivary gland degradation using RNAi knockdown. We identified several factors, including trol, a novel gene CG11880, and the cop9 signalsome component cop9 signalsome 6, as required for Drosophila larval salivary gland degradation.     

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.     

Increased proteome coverage by combining PAGE and peptide isoelectric focusing: Comparative study of gel‐based separation approaches

The in‐depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC‐MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in‐gel IEF, prior to RP‐HPLC‐MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.     

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.     

Host response to intravenous injection of epsilon toxin in mouse model: A proteomic view

Epsilon toxin (ETX) is an extremely potent pore‐forming toxin and a category B biological agent. ETX is a major virulence determinant of Clostridium perfringens toxinotypes B and D, and is implicated in pathogenesis of rapidly fatal economically important pulpy kidney disease in lambs caused by toxinotype D. Despite being a toxin, ETX can be utilized as a tool to target glutamatergic neurons and for drug delivery into the CNS. 2DE‐MS approach was employed to elucidate the host response to ETX following intravenous injection in mouse model. In total, 136 proteins were identified either differentially expressed in brain (18) and kidney (33); showing specific interaction with ETX from lysates of brain (4), kidney (21), or from plasma (42); and urine markers (18) of intoxication. Differentially expressed proteins in kidney included those involved in calcium homeostasis and cytoskeletal organization. Proteins involved in ER and oxidative stress and energy metabolism also showed differential levels in the target tissue after ETX treatment. The known functions of the proteins differentially expressed and those interacting with ETX indicate involvement of interlinked pathways. This study provides first proteomic account of host response to ETX exposure providing clues to mechanism of toxicity and potential therapeutic targets.     

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.