Identifying new PCR targets for pathogenic bacteria using top-down LC/MS protein discovery.

We have investigated the use of a top-down liquid chromatography/mass spectrometric (LC/MS) approach for the identification of specific protein biomarkers useful for differentiation of closely related strains of bacteria. The sequence information derived from the protein biomarker was then used to develop specific polymerase chain reaction primers useful for rapid identification of the strains. Shiga-toxigenic Escherichia coli (STEC) strains were used for this evaluation. The expressed protein profiles of two closely related serotype 0157:H7 strains, the predominant strain implicated in illness worldwide, and the nonpathogenic E. coli K-12 strain were compared with each other in an attempt to identify new protein markers that could be used to distinguish the 0157:H7 strains from each other and from the E. coli K-12 strain. Sequencing of a single protein unique to one of the 0157:H7 strains identified it as a cytolethal distending toxin, a potential virulence marker. The protein sequence information enabled the derivation of genetic sequence information for this toxin, thus allowing the development of specific polymerase chain reaction primers for its detection. In addition, the top-down LC/MS technique was able to identify other unique biomarkers and differentiate nearly identical 0157:H7 strains, which exhibited identical phenotypic, serologic, and genetic traits. The results of these studies demonstrate that this approach can be expanded to other serotypes of interest and provide a rational approach to identifying new molecular targets for detection.     

Post alignment clustering procedure for comparative quantitative proteomics LC-MS data

Comparative LC-MS is a powerful method for detailed quantitative comparison of complex protein mixtures. Dedicated software is required for detection, matching, and alignment of peaks in multiple LC-MS datasets. However, retention time shifts, saturation effects, limitations of experimental accuracy, and possible occurrence of split peaks make it difficult for software to perfectly match all chromatograms. We describe a procedure to assess the above problems and show that dataset quality can be enhanced with the aid of cluster analysis.     

Rapidly maturing field of proteomics: A gateway to studying diseases

The proteomics work reported by Smith et al. represents a giant step forward in characterizing the cerebrospinal fluid (CSF) proteome in mouse models of human diseases. Whereas prior studies were limited to analysis of CSF pools, Smith et al. (Proteomics 2014, 14, 1102–1106) base their conclusions on data derived from individual mice, thereby capturing a fuller range of the biological diversity present. These results underscore how far proteomics has come in the past few years, developing into a modern tool with the capacity to remove bottlenecks in the study of neuropsychiatric diseases. Past efforts with mass spectrometry (MS) have been hampered by limitations in access to CSF samples, and small volumes when available. These barriers have been overcome with newer MS platforms and advances in sample preparation. We are far closer than before to producing the production of clinically useful proteomic data for biomarker discovery and for deriving insights into pathogenesis that can lead to more effective treatments for many diseases.     

The challenge of the proteome dynamic range and its implications for in‐depth proteomics

The dynamic range of the cellular proteome approaches seven orders of magnitude—from one copy per cell to ten million copies per cell. Since a proteome's abundance distribution represents a nearly symmetric bell‐shape curve on the logarithmic copy number scale, detection of half of the expressed cellular proteome, i.e. approximately 5000 proteins, should be a relatively straightforward task with modern mass spectrometric instrumentation that exhibits four orders of magnitude of the dynamic range, while deeper proteome analysis should be progressively more difficult. Indeed, metaanalysis of 15 recent papers that claim detection of >5000 protein groups reveals that the half‐proteome analyses currently requires ≈5 h of chromatographic separation, while deeper analyses yield on average ≤20 new proteins per hour of chromatographic gradient. Therefore, a typical proteomics experiment consists of a “high‐content” part, with the detection rate of approximately 1000 proteins/h, and a “low‐content” tail with much lower rate of discovery and respectively, lower cost efficiency. This result calls for disruptive innovation in deep proteomics analysis.     

Application of proteomics for discovery of protein biomarkers.

Biomarkers of drug efficacy and toxicity are becoming a key need in the drug development process. Mass spectral-based proteomic technologies are ideally suited for the discovery of protein biomarkers in the absence of any prior knowledge of quantitative changes in protein levels. The success of any biomarker discovery effort will depend upon the quality of samples analysed, the ability to generate quantitative information on relative protein levels and the ability to readily interpret the data generated. This review will focus on the strengths and weaknesses of technologies currently utilised to address these issues.     

A new scoring function for top-down spectral deconvolution

Background

Top-down mass spectrometry plays an important role in intact protein identification and characterization. Top-down mass spectra are more complex than bottom-up mass spectra because they often contain many isotopomer envelopes from highly charged ions, which may overlap with one another. As a result, spectral deconvolution, which converts a complex top-down mass spectrum into a monoisotopic mass list, is a key step in top-down spectral interpretation.

Results

In this paper, we propose a new scoring function, L-score, for evaluating isotopomer envelopes. By combining L-score with MS-Deconv, a new software tool, MS-Deconv+, was developed for top-down spectral deconvolution. Experimental results showed that MS-Deconv+ outperformed existing software tools in top-down spectral deconvolution.

Conclusions

L-score shows high discriminative ability in identification of isotopomer envelopes. Using L-score, MS-Deconv+ reports many correct monoisotopic masses missed by other software tools, which are valuable for proteoform identification and characterization.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1140) contains supplementary material, which is available to authorized users.     

DNA affects the composition of lipoplex protein corona: a proteomics approach

The distribution of drug delivery systems into the body is affected by plasma proteins adsorbed onto their surface. Furthermore, an exact understanding of the structure and morphology of drug carriers is fundamental to understand their role as gene delivery systems. In this work, the adsorption of human plasma proteins bound to cationic liposomes and to their relative DNA lipoplexes was compared. A shotgun proteomics approach based on HPLC coupled to high resolution MS was used for an efficient identification of proteins adsorbed onto liposome and lipoplex surfaces. The distinct pattern of proteins adsorbed helps to better understand the DNA compaction process. The experimental evidence leads us to hypothesize that polyanionic DNA is associated to the lipoplex surface and can interact with basic plasma proteins. Such a finding is in agreement with recent results showing that lipoplexes are multilamellar DNA/lipid domains partially decorated with DNA at their surface. Proteomics experiments showed that the lipoplex corona is rich of biologically relevant proteins such as fibronectin, histones and complement proteins. Our results provide novel insights to understand how lipoplexes activate the immune system and why they are rapidly cleared from the blood stream. The differences in the protein adsorption data detected in the presented experiments could be the basis for the establishment of a correlation between protein adsorption pattern and in vivo fate of intravenously administered nanoparticles and will require some consideration in the future.     

Fully automatable two-dimensional reversed-phase capillary liquid chromatography with online tandem mass spectrometry for shotgun proteomics

Herein, we describe the development of a fully automatable technology that features online coupling of high‐pH RP separation with conventional low‐pH RP separation in a two‐dimensional capillary liquid chromatography (2‐D LC) system for shotgun proteomics analyses. The complete analysis comprises 13 separation cycles, each involving transfer of the eluate from the first‐dimension, high‐pH RP separation onto the second RP dimension for further separation. The solvent strength increases across the 13 fractions (cycles) to elute all peptides for further resolution on the second‐dimension, low‐pH RP separation, each under identical gradient‐elution conditions. The total run time per analysis is 52 h. In triplicate analyses of a lysate of mouse embryonic fibroblasts, we used this technology to identify 2431 non‐redundant proteins, of which 50% were observed in all three replicates. A comparison of RP‐RP 2‐D LC and strong cation exchange‐RP 2‐D LC analyses reveals that the two technologies identify primarily different peptides, thereby underscoring the differences in their separation chemistries.     

Self-made frits for nanoscale columns in proteomics

We report here the production of self-made frits for nano-columns. The frits introduce a minor dead volume and can be placed in capillaries with a wide range of diameters (20-250 microm tested) in an extremely simple and low-cost procedure. The obtained columns appear to be comparable to "no-frit" columns with near-ideal chromatographic characteristics. We expect that this frit will be useful for the spotting of gradients onto MALDI plates but also where special ESI set-ups do not allow for "no-frit" solutions.     

Discovery of biomarkers for gastric cancer: a proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.     

Target class strategies in mass spectrometry-based proteomics

The cornerstone of proteomics resides in using traditional methods of protein chemistry, to extract and resolve complex mixtures, in concert with the powerful engines of mass spectrometry to decipher peptide and protein identities. The broad utility of proteomics technologies to map protein interactions, understand regulatory mechanisms and identify biomarkers associated with disease states and drug treatments necessitates a targeted biochemical approach tailored to the characteristics of the tissue, fluid or cellular extract being studied. The application of affinity methods in proteomic studies to focus on particular classes of molecules is being used with increasing frequency and comprises the subject of this review. An overview of successfully applied affinity methods is provided, along with speculation on the use of innovative approaches. Sample preparation and processing are critical for proteomics with affinity reagents, as only functional and active proteins can be isolated in most cases. Considerations for methods of sample preparation to optimize affinity capture and release are also discussed.     

Discovery and development of a type II collagen neoepitope (TIINE) biomarker for matrix metalloproteinase activity: from in vitro to in vivo

Destruction of cartilage by matrix metalloproteinases (MMPs) plays a significant role in the pathology of osteoarthritis (OA). A translatable biomarker of MMP activity would enable development of MMP inhibitors for the treatment of OA and potentially the improved diagnosis of OA. A directed approach to identifying specific MMP cleavage products as potential biomarkers has been undertaken. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify peptides generated by MMP-driven degradation of human articular cartilage (HAC) in vivo. It was shown that a 45-mer peptide fragment of collagen type II with five hydroxyprolines (OH) can be selectively produced by the activity of collagenase, an enzyme purported to be involved in the pathology of OA. This 45-mer is the most abundant neoepitope peptide found in biological fluids such as urine and synovial fluid. An immunoaffinity LC-MS/MS assay has been developed to quantify collagen type II neoepitope peptides as biomarkers of collagenase modulation. The lower limit of quantification for this assay was established to be 0.035 nM. The assay was used to measure the levels of collagen type II peptides in the urine of both clinical (healthy human subjects) and preclinical species. The urinary levels of the most abundant peptides are reported for rat, rabbit, guinea pig, dog, and healthy human adult subjects. The utility of this peptide to monitor collagenase activity in vivo has been demonstrated through its detailed characterization in HAC explants as well as in the urine of human and other preclinical species.     

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.     

Estimating glutathione synthesis with deuterated water: a model for peptide biosynthesis

Glutathione (GSH), an intracellular tripeptide that combats oxidative stress, must be continually replaced due to loss through conjugation and destruction. Previous methods, estimating the synthesis of GSH in vivo, used constant infusions of labeled amino acid precursors. We developed a new method based on incorporation of ²H from orally supplied ²H₂O into stable C-H bonds on the tripeptide. The incorporation of ²H₂O into GSH was studied in rabbits over a 2-week period. The method estimated N, the maximum number of C-H bonds in GSH that equilibrate with ²H₂O as amino acids. GSH was analyzed by liquid chromatography/mass spectrometry after derivatization to yield GSH-N-ethylmaleimide (GSNEM). A model, which simulated the expected abundance at each mass isotopomer for the GSNEM ion at various values for N, was used to find the best fit to the data. The plateau labeling fit best a model with N = 6 of a possible 10 C-H bonds. Thus, the amino acid precursors do not completely equilibrate with ²H₂O prior to GSH synthesis. Advantages of this new method include replacing costly amino acid infusions with the oral administration of ²H₂O and a statistical basis for estimating N.     

Integrative proteomics: structure, function, and interaction report on the 3rd joint meeting of the British Society for Proteome Research and the European Bioinformatics Institute, July 2006

This report summarizes the highlights of the recent British Society for Proteome Research (BSPR) meeting jointly organized with the European Bioinformatics Institute (EBI) which was held at the Wellcome Trust Genome Campus, Hinxton, Cambridge, UK in July 2006. This was the third annual scientific meeting organized by the BSPR and EBI and the theme of this years meeting was Integrative Proteomics: Structure, function and interaction. A wealth of local and overseas speakers were invited to discuss both their own work and specific challenges present in modern day proteomic based experiments.     

Mechanisms of hydrazine toxicity in rat liver investigated by proteomics and multivariate data analysis

A proteomics approach combined with multivariate data analysis was used to examine the hepatotoxic effect of hydrazine in 30 male Sprague Dawley rats, assigned to four treatment groups and two control groups. Liver samples from the individual animals were resolved by two-dimensional differential gel electrophoresis (2-D DIGE) and protein patterns from the 2-D gels were analyzed by principal component analysis (PCA) and partial least squares regression (PLSR). The PCA plot was able to describe the variation in the protein expression related to dose and time, by separation or clustering of different animal groups. PLSR followed by variable selection (Jack-knifing) was used to select proteins that varied significantly in relation to the dose related response of the hydrazine treatment. The 10 up-regulated and 10 down-regulated proteins with highest rank in the PLSR model were identified by mass spectrometry. Hydrazine treatment induced altered expression of proteins related to lipid metabolism, Ca(2+) homeostasis, thyroid hormone pathways and stress response. Several of the identified proteins have not previously been implicated in hydrazine toxicity and may thus be regarded as new potential biomarkers of induced liver toxicity.     

Proteomic characterization of EL4 lymphoma‐derived tumors upon chemotherapy treatment reveals potential roles for lysosomes and caspase‐6 during tumor cell death in vivo

The murine mouse lymphoblastic lymphoma cell line (EL4) tumor model is an established in vivo apoptosis model for the investigation of novel cancer imaging agents and immunological treatments due to the rapid and significant response of the EL4 tumors to cyclophosphamide and etoposide combination chemotherapy. Despite the utility of this model system in cancer research, little is known regarding the molecular details of in vivo tumor cell death. Here, we report the first in‐depth quantitative proteomic analysis of the changes that occur in these tumors upon cyclophosphamide and etoposide treatment in vivo. Using a label‐free quantitative proteomic approach a total of 5838 proteins were identified in the treated and untreated tumors, of which 875 were determined to change in abundance with statistical significance. Initial analysis of the data reveals changes that may have been predicted, such as the downregulation of ribosomes, but demonstrates the robustness of the dataset. Analysis of the dataset also reveals the unexpected downregulation of caspase‐3 and an upregulation of caspase‐6 in addition to a global upregulation of lysosomal proteins in the bulk of the tumor.     

Changes in liver protein abundance in inbred alcohol-preferring rats due to chronic alcohol exposure, as measured through a proteomics approach

This study compares the total liver proteome of inbred alcohol‐preferring line (iP) rats exposed to alcohol with iP rats without alcohol experience. Rat liver proteins were extracted using a three‐step procedure. Each of the three solutions solubilizes a different set of proteins. The extracted proteins were separated by 2‐DE. Scanned gels of two sample groups, alcohol‐exposed iP and alcohol‐naïve iP, were compared, revealing many protein spots with significantly higher or lower densities. These spots were cut from the gel, destained, and subjected to trypsin digestion and subsequent identification by LC‐MS/MS. Twenty‐four individual rats, 12 alcohol‐naïve, and 12 alcohol‐exposed, were used in this study. Two groups, each containing six naïve and six exposed animals, were created for statistical comparison. For the first group, 64 spots were observed to have statistically significant intensity differences upon alcohol exposure across all three extracts while 118 such spots were found in the second group. There were 113 unique proteins in both groups together. The majority of these proteins were enzymes. Significant changes are observed for three major metabolic pathways: glycolysis, gluconeogenesis, and fatty acid β‐oxidation. In addition, enzymes involved in protein synthesis and antioxidant activity show significant changes in abundance in response to alcohol exposure.     

Profiling Eph receptor expression in cells and tissues: A targeted mass spectrometry approach

The Eph receptor tyrosine kinase family includes many members, which are often expressed together in various combinations and can promiscuously interact with multiple ephrin ligands, generating intricate networks of intracellular signals that control physiological and pathological processes. Knowing the entire repertoire of Eph receptors and ephrins expressed in a biological sample is important when studying their biological roles. Moreover, given the correlation between Eph receptor/ephrin expression and cancer pathogenesis, their expression patterns could serve important diagnostic and prognostic purposes. However, profiling Eph receptor and ephrin expression has been challenging. Here we describe a novel and straightforward approach to catalog the Eph receptors present in cultured cells and tissues. By measuring the binding of ephrin Fc fusion proteins to Eph receptors in ELISA and pull-down assays, we determined that a mixture of four ephrins is suitable for isolating both EphA and EphB receptors in a single pull-down. We then used mass spectrometry to identify the Eph receptors present in the pull-downs and estimate their relative levels. This approach was validated in cultured human cancer cell lines, human tumor xenograft tissue grown in mice, and mouse brain tissue. The new mass spectrometry approach we have developed represents a useful tool for the identification of the spectrum of Eph receptors present in a biological sample and could also be extended to profiling ephrin expression.