Identification of 491 proteins in the tear fluid proteome reveals a large number of proteases and protease inhibitors

BACKGROUND: The tear film is a thin layer of fluid that covers the ocular surface and is involved in lubrication and protection of the eye. Little is known about the protein composition of tear fluid but its deregulation is associated with disease states, such as diabetic dry eyes. This makes this body fluid an interesting candidate for in-depth proteomic analysis. RESULTS: In this study, we employ state-of-the-art mass spectrometric identification, using both a hybrid linear ion trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) mass spectrometer, and high confidence identification by two consecutive stages of peptide fragmentation (MS/MS/MS or MS(3)), to characterize the protein content of the tear fluid. Low microliter amounts of tear fluid samples were either pre-fractionated with one-dimensional SDS-PAGE and digested in situ with trypsin, or digested in solution. Five times more proteins were detected after gel electrophoresis compared to in solution digestion (320 versus 63 proteins). Ontology classification revealed that 64 of the identified proteins are proteases or protease inhibitors. Of these, only 24 have previously been described as components of the tear fluid. We also identified 18 anti-oxidant enzymes, which protect the eye from harmful consequences of its exposure to oxygen. Only two proteins with this activity have been previously described in the literature. CONCLUSION: Interplay between proteases and protease inhibitors, and between oxidative reactions, is an important feature of the ocular environment. Identification of a large set of proteins participating in these reactions may allow discovery of molecular markers of disease conditions of the eye

Status of complete proteome analysis by mass spectrometry: SILAC labeled yeast as a model system

BACKGROUND: Mass spectrometry has become a powerful tool for the analysis of large numbers of proteins in complex samples, enabling much of proteomics. Due to various analytical challenges, so far no proteome has been sequenced completely. O'Shea, Weissman and co-workers have recently determined the copy number of yeast proteins, making this proteome an excellent model system to study factors affecting coverage. RESULTS: To probe the yeast proteome in depth and determine factors currently preventing complete analysis, we grew yeast cells, extracted proteins and separated them by one-dimensional gel electrophoresis. Peptides resulting from trypsin digestion were analyzed by liquid chromatography mass spectrometry on a linear ion trap-Fourier transform mass spectrometer with very high mass accuracy and sequencing speed. We achieved unambiguous identification of more than 2,000 proteins, including very low abundant ones. Effective dynamic range was limited to about 1,000 and effective sensitivity to about 500 femtomoles, far from the subfemtomole sensitivity possible with single proteins. We used SILAC (stable isotope labeling by amino acids in cell culture) to generate one-to-one pairs of true peptide signals and investigated if sensitivity, sequencing speed or dynamic range were limiting the analysis. CONCLUSION: Advanced mass spectrometry methods can unambiguously identify more than 2,000 proteins in a single proteome. Complex mixture analysis is not limited by sensitivity but by a combination of dynamic range (high abundance peptides preventing sequencing of low abundance ones) and by effective sequencing speed. Substantially increased coverage of the yeast proteome appears feasible with further development in software and instrumentation

Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells

Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts

The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation

<p>Abstract</p> <p>Background</p> <p>Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments.</p> <p>Results</p> <p>In this manuscript, we present the <it>Drosophila melanogaster </it>PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal <url>http://www.drosophila-peptideatlas.org</url> allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed.</p> <p>Conclusion</p> <p>PeptideAtlas is an open access database for the <it>Drosophila </it>community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed <it>Drosophila </it>peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.</p

Effective Rheology of Bubbles Moving in a Capillary Tube

We calculate the average volumetric flux versus pressure drop of bubbles moving in a single capillary tube with varying diameter, finding a square-root relation from mapping the flow equations onto that of a driven overdamped pendulum. The calculation is based on a derivation of the equation of motion of a bubble train from considering the capillary forces and the entropy production associated with the viscous flow. We also calculate the configurational probability of the positions of the bubbles.Comment: 4 pages, 1 figur

Ecological Adaptation of Diverse Honey Bee (Apis mellifera) Populations

BACKGROUND: Honey bees are complex eusocial insects that provide a critical contribution to human agricultural food production. Their natural migration has selected for traits that increase fitness within geographical areas, but in parallel their domestication has selected for traits that enhance productivity and survival under local conditions. Elucidating the biochemical mechanisms of these local adaptive processes is a key goal of evolutionary biology. Proteomics provides tools unique among the major 'omics disciplines for identifying the mechanisms employed by an organism in adapting to environmental challenges. RESULTS: Through proteome profiling of adult honey bee midgut from geographically dispersed, domesticated populations combined with multiple parallel statistical treatments, the data presented here suggest some of the major cellular processes involved in adapting to different climates. These findings provide insight into the molecular underpinnings that may confer an advantage to honey bee populations. Significantly, the major energy-producing pathways of the mitochondria, the organelle most closely involved in heat production, were consistently higher in bees that had adapted to colder climates. In opposition, up-regulation of protein metabolism capacity, from biosynthesis to degradation, had been selected for in bees from warmer climates. CONCLUSIONS: Overall, our results present a proteomic interpretation of expression polymorphisms between honey bee ecotypes and provide insight into molecular aspects of local adaptation or selection with consequences for honey bee management and breeding. The implications of our findings extend beyond apiculture as they underscore the need to consider the interdependence of animal populations and their agro-ecological context

Protein misfolding and dysregulated protein homeostasis in autoinflammatory diseases and beyond.

Cells have a number of mechanisms to maintain protein homeostasis, including proteasome-mediated degradation of ubiquitinated proteins and autophagy, a regulated process of ‘self-eating’ where the contents of entire organelles can be recycled for other uses. The unfolded protein response prevents protein overload in the secretory pathway. In the past decade, it has become clear that these fundamental cellular processes also help contain inflammation though degrading pro-inflammatory protein complexes such as the NLRP3 inflammasome. Signaling pathways such as the UPR can also be co-opted by toll-like receptor and mitochondrial reactive oxygen species signaling to induce inflammatory responses. Mutations that alter key inflammatory proteins, such as NLRP3 or TNFR1, can overcome normal protein homeostasis mechanisms, resulting in autoinflammatory diseases. Conversely, Mendelian defects in the proteasome cause protein accumulation, which can trigger interferon-dependent autoinflammatory disease. In non-Mendelian inflammatory diseases, polymorphisms in genes affecting the UPR or autophagy pathways can contribute to disease, and in diseases not formerly considered inflammatory such as neurodegenerative conditions and type 2 diabetes, there is increasing evidence that cell intrinsic or environmental alterations in protein homeostasis may contribute to pathogenesis