Metal complexes as artificial proteases in proteomics: a palladium(II) complex cleaves various proteins in solutions containing detergents

Most popular agents for site-specific protein cleavage are proteolytic enzymes. Because they become denatured and inactivated by detergents, enzymes are inconvenient for proteomic analysis of hydrophobic proteins which require detergents as solubilizing agents. We used cis-[Pd(en)(H₂O)₂]²⁺ (in which en represents ethylenediamine) as an artificial protease to effect cleavage of three bovine proteins, namely ubiquitin, β-casein, and serum albumin, in separate experiments. Cleavage took place in aqueous solutions containing 1.0% wt./vol. of either 3-[(3-Cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS) or Zwittergent 3-14 at 2.5 < pH < 2.9 and 55-60 °C for 3-72 h. Digests were separated by HPLC and analyzed by tandem mass spectrometry. Peptides were identified by de novo sequencing and matched against the bovine genome. Because cleavage by Pd(II) complexes is rather selective and therefore infrequent, 72% of the identified peptides in the digests contained more than 10 amino acid. Palladium(II) complexes hold promise as cleavage agents in proteomics studies of membrane proteins.     

Quantitative proteomic analysis of the budding yeast cell cycle using acid-cleavable isotope-coded affinity tag reagents

Quantitative profiling of proteins, the direct effectors of nearly all biological functions, will undoubtedly complement technologies for the measurement of mRNA. Systematic proteomic measurement of the cell cycle is now possible by using stable isotopic labeling with isotope-coded affinity tag reagents and software tools for high-throughput analysis of LC-MS/MS data. We provide here the first such study achieving quantitative, global proteomic measurement of a time-course gene expression experiment in a model eukaryote, the budding yeast Saccharomyces cerevisiae, during the cell cycle. We sampled 48% of all predicted ORFs, and provide the data, including identifications, quantitations, and statistical measures of certainty, to the community in a sortable matrix. We do not detect significant concordance in the dynamics of the system over the time-course tested between our proteomic measurements and microarray measures collected from similarly treated yeast cultures. Our proteomic dataset therefore provides a necessary and complementary measure of eukaryotic gene expression, establishes a rich database for the functional analysis of S. cerevisiae proteins, and will enable further development of technologies for global proteomic analysis of higher eukaryotes.     

Comparative proteomic analysis of the insulin‐induced L6 myotube secretome

Emerging evidence has revealed an endocrine function for skeletal muscle; in fact, certain anti‐inflammatory cytokines are secreted only from contractile skeletal muscle. However, the skeletal muscle secretome as a whole is poorly characterized, as is how it changes in response to extracellular stimuli. Herein, we sought to identify and characterize the members of the skeletal muscle secretome, and to determine which protein secretion levels were modulated in response to insulin stimulation. To conduct these studies, we treated differentiated L6 rat skeletal muscle cells with insulin or left them untreated, and we comparatively analyzed the proteins secreted into the media. We fractionated this conditioned media using offline RP HPLC, digested the fractionated proteins, and analyzed the resulting peptides with LC‐ESI‐MS/MS. We identified a total of 254 proteins, and by using three different filtering methods, we identified 153 of these as secretory proteins. Fourteen proteins were secreted at higher levels under insulin stimulation, including several proteins known to be highly secreted in metabolic diseases; 19 proteins were secreted at lower levels under insulin stimulation. These result not only pinpointed several previously unknown, insulin induced, secretory proteins of skeletal muscle, it also described a novel approach for conditioned secretome analysis.     

High sequence coverage by in-capillary proteolysis of native proteins and simultaneous analysis of the resulting peptides by nanoelectrospray ionization-mass spectrometry and tandem mass spectrometry

Losses of proteolytic peptides during extraction and/or purification procedures succeeding in-gel or in-solution digests of proteins frequently occur in the course of protein identification investigations. In order to overcome this disadvantage, the method of in-capillary digest was developed: native proteins were incubated in the presence of endoproteases in the electrospray capillary and the resulting peptides were analyzed by nanoelectrospray-mass spectrometry during the ongoing proteolysis. In-capillary digest of apomyglobin by use of trypsin in a molar ratio of 25:1 yielded complete degradation already after 15 min. The sequence coverage based on formation of molecular ions was 100% and peptide ions could be fragmented by collision-induced dissociation and sequenced. When myoglobin was incubated in the electrospray capillary with trypsin in a molar ratio of 500:1, a clear shift from molecular ions and miscleaved peptide ions to the expected final tryptic peptide ions was observed over a 2 h period. The peptide spectra obtained from tryptic in-capillary proteolysis of bovine serum albumin and apotransferrin, respectively, gave rise to sequence coverages of more than 40% for both proteins. The data obtained from the peptide maps as well as from collision-induced dissociation (CID) of selected peptides were more than sufficient for protein identification by database searches. An elephant milk protein preparation was used to demonstrate the application of in-capillary proteolysis on protein mixtures. Tryptic digest, simultaneous analysis of the proteolytic peptides by use of CID, and subsequent sequencing allowed the identification of lactoferrin, alphas1-casein, beta-casein, delta-casein, and kappa-casein by homology search.     

Glycosidase activity profiling for bacterial identification by a chemical proteomics approach

Genome sequencing projects are suggesting there are dozens of glycosidase sequences that could be used to fingerprint cell types and serve as starting points for biocatalyst discovery. Herein, we present a simple chemical proteomics approach to profile intracellular glycosidase activities of three different bacterial cell extracts using a synthetic α- and β-linked library of 18 representative substrates with electrospray ionization-mass spectrometry (ESI-MS) reaction monitoring. Three target bacteria – Escherichia coli K12, Bacillus cereus and Pseudomonas aeruginosa – can be easily differentiated by this method. Compared with traditional chromogenic and fluorogenic methods to profile bacterial enzyme activities individually, this MS-based method can detect multiple enzyme activities in one reaction and easily highlight activity differences between whole cell extracts.     

Alkaline methanolysis of lipid extracts extends shotgun lipidomics analyses to the low-abundance regime of cellular sphingolipids

Sphingolipids that contain a sphingoid base are composed of hundreds to thousands of distinct compounds, many of which serve as lipid regulators of biological functions. The global analysis of the large number of low-abundance sphingolipid molecular species has been hampered in many cases by the sphingolipid molecular species being overwhelmed by the quantity of other classes of lipid (e.g., glycerophospholipid) molecular species present, thereby imposing severe restrictions on the dynamic range of their measurement using shotgun lipidomics. Herein, we developed a facile approach in which the sphingolipids of cellular extracts were dramatically enriched by direct alkaline methanolysis of lipid extracts followed by extraction to remove the large majority of other endogenous lipid classes. Through direct infusion of the resultant enriched solution, we identified and quantitated a variety of very-low-abundance sphingolipid classes (e.g., sphingosine, psychosine, and lysosphingomyelin) and molecular species (e.g., sphingomyelin) using electrospray ionization mass spectrometry (i.e., shotgun sphingolipidomics). Accordingly, through utilization of these facile enrichment techniques, direct penetrance into the sphingolipidomes has been greatly extended, facilitating new insights into their metabolism and signaling functions in biological systems.     

A method for profiling gangliosides in animal tissues using electrospray ionization-tandem mass spectrometry

Gangliosides are critical in many functions of mammalian cells but present as a minor lipid component with many molecular species of subtle differences. Conventional strategies for profiling gangliosides suffer from poor reproducibility, low sensitivity, and low-throughput capacity. Prior separation of gangliosides by thin-layer chromatography and/or high-performance liquid chromatography not only was laborious and tedious but also could introduce uneven losses of molecular species. We developed a new strategy of using electrospray ionization-tandem mass spectrometry (ESI-MS/MS) to profile gangliosides with high-throughput potential. This strategy involves three new findings: (i) collision-induced fragmentation of gangliosides gave rise to a common ion of m/z 290, a derivative of N-acetylneuraminic acid; (ii) phospholipids exert a profound suppression of ganglioside detection in ESI-MS/MS to prevent a direct detection in total cellular lipid extracts; and (iii) enrichment of gangliosides in the aqueous phase from total cellular lipid extracts eliminates the damping effect of phospholipids and permits direct precursor scan.     

Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics

Due to the lack of precise markers indicative of its occurrence and progression, coronary artery disease (CAD), the most common type of heart diseases, is currently associated with high mortality in the United States. To systemically identify novel protein biomarkers associated with CAD progression for early diagnosis and possible therapeutic intervention, we employed an iTRAQ‐based quantitative proteomic approach to analyze the proteome changes in the plasma collected from a pair of wild‐type versus apolipoprotein E knockout (APOE^?/?) mice which were fed with a high fat diet. In a multiplex manner, iTRAQ serves as the quantitative ‘in‐spectra’ marker for ‘cross‐sample’ comparisons to determine the differentially expressed/secreted proteins caused by APOE knock‐out. To obtain the most comprehensive proteomic data sets from this CAD‐associated mouse model, we applied both MALDI and ESI‐based mass spectrometric (MS) platforms coupled with two different schemes of multidimensional liquid chromatography (2‐D LC) separation. We then comparatively analyzed a series of the plasma samples collected at 6 and 12 wk of age after the mice were fed with fat diets, where the 6‐ or 12‐wk time point represents the early or intermediate phase of the fat‐induced CAD, respectively. We then categorized those proteins showing abundance changes in accordance with APOE depletion. Several proteins such as the γ and β chains of fibrinogen, apolipoprotein B, apolipoprotein C‐I, and thrombospondin‐4 were among the previously known CAD markers identified by other methods. Our results suggested that these unbiased proteomic methods are both feasible and a practical means of discovering potential biomarkers associated with CAD progression.     

Genome annotating proteomics pipelines: available tools

Proteomics based on tandem mass spectrometry is a powerful tool for identifying novel biomarkers and drug targets. Previously, a major bottleneck in high-throughput proteomics has been that the computational techniques needed to reliably identify proteins from proteomic data lagged behind the ability to collect the immense quantity of data generated. This is no longer the case, as fully automated pipelines for peptide and protein identification exist, and these are publicly and privately accessible. Such pipelines can automatically and rapidly generate high-confidence protein identifications from large datasets in a searchable format covering multiple experimental runs. However, the main challenge for the community now is to use these resources as they are, by taking full advantage of the pooling of information, so that the next barrier in our understanding of biology may be broken. There are currently two pipelines in the public domain that provide such potential: PeptideAtlas and the Genome Annotating Proteomic Pipeline. This review will introduce their features in the context of high-throughput proteomics, and provide indicative results as to their usefulness and usability through a side-by-side comparison of results obtained when processing a set of human plasma samples.     

A streamlined approach to high-throughput proteomics

Proteomics has rapidly become an important tool for life science research, allowing the integrated analysis of global protein expression from a single experiment. To accommodate the complexity and dynamic nature of any proteome, researchers must use a combination of disparate protein biochemistry techniques, often a highly involved and time-consuming process. Whilst highly sophisticated, individual technologies for each step in studying a proteome are available, true high-throughput proteomics that provides a high degree of reproducibility and sensitivity has been difficult to achieve. The development of high-throughput proteomic platforms, encompassing all aspects of proteome analysis and integrated with genomics and bioinformatics technology, therefore represents a crucial step for the advancement of proteomics research. ProteomIQ? (Proteome Systems) is the first fully integrated, start-to-finish proteomics platform to enter the market. Sample preparation and tracking, centralized data acquisition and instrument control, and direct interfacing with genomics and bioinformatics databases are combined into a single suite of integrated hardware and software tools, facilitating high reproducibility and rapid turnaround times. This review will highlight some features of ProteomIQ, with particular emphasis on the analysis of proteins separated by 2D polyacrylamide gel electrophoresis.     

A label-free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen

In order to assess the biological function of proteins and their modifications for understanding signaling mechanisms within cells as well as specific biomarkers to disease, it is important that quantitative information be obtained under different experimental conditions. Stable isotope labeling is a powerful method for accurately determining changes in the levels of proteins and PTMs; however, isotope labeling experiments suffer from limited dynamic range resulting in signal change ratios of less than approximately 20:1 using most commercial mass spectrometers. Label-free approaches to relative quantification in proteomics such as spectral counting have gained popularity since no additional chemistries are needed. Here, we show a label-free method for relative quantification based on the TIC from peptide MS/MS spectra collected from data-dependent runs can be used effectively as a quantitative measure and expands the dynamic range over isotope labeling experiments allowing for abundance differences up to approximately 60:1 in a screen for proteins that bind to phosphotyrosine residues.     

Dereplication of Mammea neurophylla metabolites to isolate original 4-phenylcoumarins

Mammea coumarins are isoprenylated 4-alkyl or 4-phenylcoumarins. Their distribution is limited to 3 Clusiaceae/Calophyllaceae genera. We recently reported on their presence in Mammea neurophylla bark extracts, where they exhibited anti-AGE properties associated with a prevention of the endothelial dysfunction. About 120 mammea coumarins were already described so, in order to focus further phytochemical analysis on original or bio-active compounds, we developed a methodology to facilitate the detection and identification of compounds of interest. Our aim was to develop a LC-DAD–ESI-MSⁿ method for rapid, sensitive and simple analysis of the mammea coumarins in calophyllaceous/clusiaceous species. For that, full LC-DAD–MSⁿ data were acquired from 11 4-phenylcoumarins previously isolated in our laboratory. Bark, leaves and fruits of M. neurophylla were then extracted with DCM using an ASE apparatus. Extracts were finally analyzed through LC-DAD–HRMSⁿ and UV and MS profiles were compared to our database as well as literature data. Detected new compounds were isolated and their structures elucidated through ¹H, ¹³C and 2D NMR analysis. Finally, 24 known mammea coumarins were dereplicated from bark, leaf and fruit DCM extracts of M. neurophylla and the structure of 4 unreported compounds could be predicted. In particular, the structures of mammea A/AA 9-hydroxyCycloF and mammea A/AB 9-hydroxyCycloF were confirmed after purification and extensive NMR analyses. By comparison of UV and mass fragmentation data from a small library of reference compounds, LC-DAD–HRMSⁿ analysis of mammea coumarins in crude extracts allows the structure prediction of novel or bio-active compounds. This useful guiding-tool could be easily applied to other Clusiaceae/Calophyllaceae phytochemical analysis.     

A novel fractionation method of the rough ER integral membrane proteins; Resident proteins versus exported proteins?

We treated the high salt‐washed canine pancreatic rough ER (KRM) with 0.18% Triton X‐100, separated the extract from the residual membrane (0.18%Tx KRM), and processed the extract with SM‐2 beads to recover membrane proteins in proteoliposomes. To focus on integral membrane proteins, KRM, 0.18%Tx KRM and proteoliposomes were subjected to sodium carbonate treatment, and analyzed by 2‐D gel electrophoresis. Consequently we found that a distinct group of integral membrane protein of KRM preferentially extracted from the membrane and recovered in proteoliposomes did exist, while majority of KRM integral membrane proteins were fractionated in 0.18%Tx KRM, which retained the basic structure and functions of KRM. Protein identification showed that the former group was enriched with proteins exported from the ER and the latter group comprised mostly of ER resident proteins. This result will potentially affect the prevailing view of the ER membrane structure as well as protein sorting from the ER.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

A chip‐based amide‐HILIC LC/MS platform for glycosaminoglycan glycomics profiling

A key challenge to investigations into the functional roles of glycosaminoglycans (GAGs) in biological systems is the difficulty in achieving sensitive, stable, and reproducible mass spectrometric analysis. GAGs are linear carbohydrates with domains that vary in the extent of sulfation, acetylation, and uronic acid epimerization. It is of particular importance to determine spatial and temporal variations of GAG domain structures in biological tissues. In order to analyze GAGs from tissue, it is useful to couple MS with an on‐line separation system. The purposes of the separation system are both to remove components that inhibit GAG ionization and to enable the analysis of very complex mixtures. This contribution presents amide–silica hydrophilic interaction chromatography (HILIC) in a chip‐based format for LC/MS of heparin, heparan sulfate (HS) GAGs. The chip interface yields robust performance in the negative ion mode that is essential for GAGs and other acidic glycan classes while the built‐in trapping cartridge reduces background from the biological tissue matrix. The HILIC chromatographic separation is based on a combination of the glycan chain lengths and the numbers of hydrophobic acetate (Ac) groups and acidic sulfate groups. In summary, chip based amide‐HILIC LC/MS is an enabling technology for GAG glycomics profiling.     

Improving the reliability and throughput of mass spectrometry-based proteomics by spectrum quality filtering

In contemporary peptide-centric or non-gel proteome studies, vast amounts of peptide fragmentation data are generated of which only a small part leads to peptide or protein identification. This motivates the development and use of a filtering algorithm that removes spectra that contribute little to protein identification. Removal of unidentifiable spectra reduced both the amount of computational and human time spent on analyzing spectra as well as the chances of obtaining false identifications. Thorough testing on various proteome datasets from different instruments showed that the best suggested machine-learning classifier is, on average, able to recognize half of the unidentified spectra as bad spectra. Further analyses showed that several unidentified spectra classified as good were derived from peptides carrying unanticipated amino acid modifications or contained sequence tags that allowed peptide identification using homology searches. The implementation of the classifiers is available under the GNU General Public License at http://www.bioinfo.no/software/spectrumquality.     

Bioinformatics in mass spectrometry data analysis for proteomics studies

Mass spectrometry is a technique widely employed for the identification and characterization of proteins. The role of bioinformatics is fundamental for the elaboration of mass spectrometry data due to the amount of data that this technique can produce. To process data efficiently, new software packages and algorithms are continuously being developed to improve protein identification and characterization in terms of high-throughput and statistical accuracy. However, many limitations exist concerning bioinformatics spectral data elaboration. This review aims to critically cover the recent and future developments of new bioinformatics approaches in mass spectrometry data analysis for proteomics studies.     

Mass spectrometry technologies for proteomics.

In the late 1980s, the advent of soft ionization techniques capable of generating stable gas phase ions from thermally unstable biomolecules, namely matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI), laid the way for the development of a set of powerful alternatives to the traditional Edman chemistry for the structural characterization of peptides and proteins. The rapid protein identification capabilities that, coupled with two-dimensional gel electrophoresis, provided insights into all sorts of biological systems since the dawn of proteomics and have been exploited in the last few years for the development of more powerful and automatable gel-free strategies, mainly based on multidimensional chromatographic separations of peptides from proteolytic digests. In parallel to the evolution of ion sources, mass analysers and scan modes, the invention of new elegant biochemical strategies to fractionate or simplify highly complex mixtures, or to introduce isotopic labels in peptides in a variety of ways now makes also possible large-scale, high-coverage quantitative studies in a wide dynamic range. In this review, we provide the fundamental concepts of mass spectrometry (MS) and describe the technological progress of MS-based proteomics since its earliest days. Representative literature examples of their true power, either when employed as exploratory or as targeted techniques, is provided as well.