Improving Proteome Coverage for Small Sample Amounts: An Advanced Method for Proteomics Approaches with Low Bacterial Cell Numbers

Proteome analyses are often hampered by the low amount of available starting material like a low bacterial cell number obtained from in vivo settings. Here, the single pot solid‐phase enhanced sample preparation (SP3) protocol is adapted and combined with effective cell disruption using detergents for the proteome analysis of bacteria available in limited numbers only. Using this optimized protocol, identification of peptides and proteins for different Gram‐positive and Gram‐negative species can be dramatically increased and, reliable quantification can also be ensured. This adapted method is compared to already established strain‐specific sample processing protocols for Staphylococcus aureus, Streptococcus suis, and Legionella pneumophila. The highest species‐specific increase in identifications is observed using the adapted method with L. pneumophila samples by increasing protein and peptide identifications up to 300% and 620%, respectively. This increase is accompanied by an improvement in reproducibility of protein quantification and data completeness between replicates. Thus, this protocol is of interest for performing comprehensive proteomics analyses of low bacterial cell numbers from different settings ranging from infection assays to environmental samples.     

The Sarda Sheep Host Fecal Proteome

The first characterization of the sheep fecal microbiota was recently reported, as obtained by using a multi meta‐omic approach. Here, the mass spectra generated by single‐run LC/high‐resolution MS in the context of that study were reanalyzed using a host‐specific database, in order to gain insights for the first time into the host fecal proteome of healthy Sarda sheep. On the whole, 5349 non‐redundant tryptic peptide sequences were identified, belonging to 1046 different proteins. The “core” fecal proteome (common to all animals) comprised 431 proteins, mainly related to biological processes as immune response and proteolysis. Proteins involved in the immune/inflammatory response and peptidases were specifically investigated. This dataset provides novel insights into the repertoire of proteins secreted in the sheep intestinal lumen, and constitutes the basis for future shotgun and targeted proteomics studies aimed at monitoring changes in the sheep fecal proteome in response to production variables, infectious/inflammatory states, and variations in the gut microbiota. Data are available via ProteomeXchange with identifier PXD006145.     

Strategy for surveying the proteome using affinity proteomics and mass spectrometry

Antibody‐based microarrays is a rapidly evolving technology that has gone from the first proof‐of‐concept studies to more demanding proteome profiling applications, during the last years. Miniaturized microarrays can be printed with large number of antibodies harbouring predetermined specificities, capable of targeting high‐ as well as low‐abundant analytes in complex, nonfractionated proteomes. Consequently, the resolution of such proteome profiling efforts correlate directly to the number of antibodies included, which today is a key limiting factor. To overcome this bottleneck and to be able to perform in‐depth global proteome surveys, we propose to interface affinity proteomics with MS‐based read‐out, as outlined in this technical perspective. Briefly, we have defined a range of peptide motifs, each motif being present in 5–100 different proteins. In this manner, 100 antibodies, binding 100 different motifs commonly distributed among different proteins, would potentially target a protein cluster of 10⁴ individual molecules, i.e. around 50% of the nonredundant human proteome. Notably, these motif‐specific antibodies would be directly applicable to any proteome in a specie independent manner and not biased towards abundant proteins or certain protein classes. The biological sample is digested, exposed to these immobilized antibodies, whereby motif‐containing peptides are specifically captured, enriched and subsequently detected and identified using MS.     

Proteomics of human seminal plasma: Identification of biomarker candidates for fertility and infertility and the evolution of technology

Proteomics is a research area that has developed rapidly in the last decade. It studies the large‐scale characterization of the full protein components of a cell, a tissue, or a biological fluid. In the last decade, clinical proteomics has developed new technology and bioinformatics useful in identifying molecular markers of pathology; the next decade might be the era of proteomics. Seminal plasma (SP) represents a good sample for proteomic analysis in the evaluation of male fertility/infertility. SP is an acellular fluid conglomerate, comprised of contributions from the epididymis and accessory sexual glands. Human SP contains many proteins that are important to the successful fertilization of the oocyte by the spermatozoa. Proteomic studies have identified numerous seminal‐specific proteins, and recent reports have provided a further understanding of their function with respect to male fertility. Upon further validation, these proteins may be useful in the clinical distinction between fertility and infertility. This article reviews the proteomic methods, such as one dimensional polyacrylamide gel electrophoresis (1D–PAGE), two‐dimensional polyacrylamide gel electrophoresis (2D–PAGE), and mass spectrometry (MS), employed to detect human SP markers involved in fertility and infertility. As such, proteomic studies will help the development of new techniques to identify novel biomarkers for a better clinical diagnosis and treatment of male infertility. Mol. Reprod. Dev. 80: 350–357, 2013. © 2013 Wiley Periodicals, Inc.     

Label‐Free Quantitative Proteomics Distinguishes General and Site‐Specific Host Responses to Pseudomonas aeruginosa Infection at the Ocular Surface

Mass spectrometry‐based proteomics enables the unbiased and sensitive profiling of cellular proteomes and extracellular environments. Recent technological and bioinformatic advances permit identifying dual biological systems in a single experiment, supporting investigation of infection from both the host and pathogen perspectives. At the ocular surface, Pseudomonas aeruginosa is commonly associated with biofilm formation and inflammation of the ocular tissues, causing damage to the eye. The interaction between P. aeruginosa and the immune system at the site of infection describes limitations in clearance of infection and enhanced pathogenesis. Here, the extracellular environment (eye wash) of murine ocular surfaces infected with a clinical isolate of P. aeruginosa is profiled and neutrophil marker proteins are detected, indicating neutrophil recruitment to the site of infection. The first potential diagnostic markers of P. aeruginosa‐associated keratitis are also identified. In addition, the deepest murine corneal proteome to date is defined and proteins, categories, and networks critical to the host response are detected. Moreover, the first identification of bacterial proteins attached to the ocular surface is reported. The findings are validated through in silico comparisons and enzymatic profiling. Overall, the work provides comprehensive profiling of the host–pathogen interface and uncovers differences between general and site‐specific host responses to infection.     

Enhanced recovery of lyophilized peptides in shotgun proteomics by using an LC‐ESI‐MS compatible surfactant

LC‐ESI/MS/MS‐based shotgun proteomics is currently the most commonly used approach for the identification and quantification of proteins in large‐scale studies of biomarker discovery. In the past several years, the shotgun proteomics technologies have been refined toward further enhancement of proteome coverage. In the complex series of protocols involved in shotgun proteomics, however, loss of proteolytic peptides during the lyophilization step prior to the LC/MS/MS injection has been relatively neglected despite the fact that the dissolution of the hydrophobic peptides in lyophilized samples is difficult in 0.05–0.1% TFA or formic acid, causing substantial loss of precious peptide samples. In order to prevent the loss of peptide samples during this step, we devised a new protocol using Invitrosol (IVS), a commercially available surfactant compatible with ESI‐MS; by dissolving the lyophilized peptides in IVS, we show improved recovery of hydrophobic peptides, leading to enhanced coverage of proteome. Thus, the use of IVS in the recovery step of lyophilized peptides will help the shotgun proteomics analysis by expanding the proteome coverage, which would significantly promote the discovery and development of new diagnostic markers and therapeutic targets.     

Drosophila wing modularity revisited through a quantitative genetic approach

To predict the response of complex morphological structures to selection it is necessary to know how the covariation among its different parts is organized. Two key features of covariation are modularity and integration. The Drosophila wing is currently considered a fully integrated structure. Here, we study the patterns of integration of the Drosophila wing and test the hypothesis of the wing being divided into two modules along the proximo‐distal axis, as suggested by developmental, biomechanical, and evolutionary evidence. To achieve these goals we perform a multilevel analysis of covariation combining the techniques of geometric morphometrics and quantitative genetics. Our results indicate that the Drosophila wing is indeed organized into two main modules, the wing base and the wing blade. The patterns of integration and modularity were highly concordant at the phenotypic, genetic, environmental, and developmental levels. Besides, we found that modularity at the developmental level was considerably higher than modularity at other levels, suggesting that in the Drosophila wing direct developmental interactions are major contributors to total phenotypic shape variation. We propose that the precise time at which covariance‐generating developmental processes occur and/or the magnitude of variation that they produce favor proximo‐distal, rather than anterior‐posterior, modularity in the Drosophila wing.     

Revisiting biomarker discovery by plasma proteomics

Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)‐based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous “triangular strategies” aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a “rectangular” plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision‐making, and we discuss some first steps in this direction.     

Systematic Evaluation of Immobilized Trypsin‐Based Fast Protein Digestion for Deep and High‐Throughput Bottom‐Up Proteomics

Immobilized trypsin (IM) has been recognized as an alternative to free trypsin (FT) for accelerating protein digestion 30 years ago. However, some questions of IM still need to be answered. How does the solid matrix of IM influence its preference for protein cleavage and how well can IM perform for deep bottom‐up proteomics compared to FT? By analyzing Escherichia coli proteome samples digested with amine or carboxyl functionalized magnetic bead–based IM (IM‐N or IM‐C) or FT, it is observed that IM‐N with the nearly neutral solid matrix, IM‐C with the negatively charged solid matrix, and FT have similar cleavage preference considering the microenvironment surrounding the cleavage sites. IM‐N (15 min) and FT (12 h) both approach 9000 protein identifications (IDs) from a mouse brain proteome. Compared to FT, IM‐N has no bias in the digestion of proteins that are involved in various biological processes, are located in different components of cells, have diverse functions, and are expressed in varying abundance. A high‐throughput bottom‐up proteomics workflow comprising IM‐N‐based rapid protein cleavage and fast CZE‐MS/MS enables the completion of protein sample preparation, CZE‐MS/MS analysis, and data analysis in only 3 h, resulting in 1000 protein IDs from the mouse brain proteome.     

Sequential protein extraction as an efficient method for improved proteome coverage in larvae of Atlantic salmon (Salmo salar)

Understanding diet‐ and environmentally induced physiological changes in fish larvae is a major goal for the aquaculture industry. Proteomic analysis of whole fish larvae comprising multiple tissues offers considerable potential but is challenging due to the very large dynamic range of protein abundance. To extend the coverage of the larval phase of the Atlantic salmon (Salmo salar) proteome, we applied a two‐step sequential extraction (SE) method, based on differential protein solubility, using a nondenaturing buffer containing 150 mM NaCl followed by a denaturing buffer containing 7 M urea and 2 M thiourea. Extracts prepared using SE and one‐step direct extraction were characterized via label‐free shotgun proteomics using nanoLC‐MS/MS (LTQ‐Orbitrap). SE partitioned the proteins into two fractions of approximately equal amounts, but with very distinct protein composition, leading to identification of ～40% more proteins than direct extraction. This fractionation strategy enabled the most detailed characterization of the salmon larval proteome to date and provides a platform for greater understanding of physiological changes in whole fish larvae. The MS data are available via the ProteomeXchange Consortium PRIDE partner repository, dataset PXD003366.     

Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.     

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.     

Proteomic Characterization of Caenorhabditis elegans Larval Development

The nematode Caenorhabditis elegans is widely used as a model organism to study cell and developmental biology. Quantitative proteomics of C. elegans is still in its infancy and, so far, most studies have been performed on adult worm samples. Here, we used quantitative mass spectrometry to characterize protein level changes across the four larval developmental stages (L1–L4) of C. elegans. In total, we identified 4130 proteins, and quantified 1541 proteins that were present across all four stages in three biological replicates from independent experiments. Using hierarchical clustering and functional ontological analyses, we identified 21 clusters containing proteins with similar protein profiles across the four stages, and highlighted the most overrepresented biological functions in each of these protein clusters. In addition, we used the dataset to identify putative larval stage‐specific proteins in each individual developmental stage, as well as in the early and late developmental stages. In summary, this dataset provides system‐wide analysis of protein level changes across the four C. elegans larval developmental stages, which serves as a useful resource for the C. elegans research community. MS data were deposited in ProteomeXchange ( http://proteomecentral.proteomexchange.org ) via the PRIDE partner repository with the primary accession identifier PXD006676.     

Liquid chromatography MALDI MS/MS for membrane proteome analysis

Membrane proteins play critical roles in many biological functions and are often the molecular targets for drug discovery. However, their analysis presents a special challenge largely due to their highly hydrophobic nature. We present a surfactant-aided shotgun proteomics approach for membrane proteome analysis. In this approach, membrane proteins were solubilized and digested in the presence of SDS followed by newly developed auto-offline liquid chromatography/matrix-assisted laser desorption ionization (LC/MALDI) tandem MS analysis. Because of high tolerance of MALDI to SDS, one-dimensional (1D) LC separation can be combined with MALDI for direct analysis of protein digests containing SDS, without the need for extensive sample cleanup. In addition, the heated droplet interface used in LC/MALDI can work with high flow LC separations, allowing a relatively large amount of protein digest to be used for 1D LC/MALDI which facilitates the detection of low abundance proteins. The proteome identification results obtained by LC/MALDI are compared to the gel electrophoresis/MS method as well as the shotgun proteomics method using 2D LC/electrospray ionization MS. It is demonstrated that, while LC/MALDI provides more extensive proteome coverage compared to the other two methods, these three methods are complementary to each other and a combination of these methods should provide a more comprehensive membrane proteome analysis.     

When peptides fly: Advances in Drosophila proteomics

In the past decade, improvements in genome annotation, protein fractionation methods and mass spectrometry instrumentation resulted in rapid growth of Drosophila proteomics. This review presents the current status of proteomics research in the fly. Areas that have seen major advances in recent years include efforts to map and catalog the Drosophila proteome and high-throughput as well as targeted studies to analyze protein–protein interactions and post-translational modifications. Stable isotope labeling of flies and other applications of quantitative proteomics have opened up new possibilities for functional analyses. It is clear that proteomics is becoming an indispensable tool in Drosophila systems biology research that adds a unique dimension to studying gene function.     

Fractionation profiling: a fast and versatile approach for mapping vesicle proteomes and protein–protein interactions

We developed “fractionation profiling,” a method for rapid proteomic analysis of membrane vesicles and protein particles. The approach combines quantitative proteomics with subcellular fractionation to generate signature protein abundance distribution profiles. Functionally associated groups of proteins are revealed through cluster analysis. To validate the method, we first profiled >3500 proteins from HeLa cells and identified known clathrin-coated vesicle proteins with >90% accuracy. We then profiled >2400 proteins from Drosophila S2 cells, and we report the first comprehensive insect clathrin-coated vesicle proteome. Of importance, the cluster analysis extends to all profiled proteins and thus identifies a diverse range of known and novel cytosolic and membrane-associated protein complexes. We show that it also allows the detailed compositional characterization of complexes, including the delineation of subcomplexes and subunit stoichiometry. Our predictions are presented in an interactive database. Fractionation profiling is a universal method for defining the clathrin-coated vesicle proteome and may be adapted for the analysis of other types of vesicles and particles. In addition, it provides a versatile tool for the rapid generation of large-scale protein interaction maps.