A cost-benefit analysis of multidimensional fractionation of affinity purification-mass spectrometry samples

Affinity purification coupled to mass spectrometry (AP-MS) is gaining widespread use for the identification of protein-protein interactions. It is unclear, however, whether typical AP sample complexity is limiting for the identification of all protein components using standard one-dimensional LC-MS/MS. Multidimensional sample separation is useful for reducing sample complexity prior to MS analysis and increases peptide and protein coverage of complex samples. Here, we monitored the effects of upstream protein or peptide separation techniques on typical mammalian AP-MS samples, generated by FLAG affinity purification of four baits with different biological functions and/or subcellular distribution. As a first separation step, we employed SDS-PAGE, strong cation exchange LC, or reversed-phase LC at basic pH. We also analyzed the benefits of using an instrument with a faster scan rate, the new TripleTOF 5600 mass spectrometer. While all multidimensional approaches yielded a clear increase in spectral counts, the increase in unique peptides and additional protein identification was modest and came at the cost of increased instrument and handling time. The use of a high duty-cycle instrument achieved similar benefits without these drawbacks. An increase in spectral counts is beneficial when data analysis methods relying on spectral counts, including Significance Analysis of INTeractome (SAINT), are used.     

Online multidimensional separation with biphasic monolithic capillary column for shotgun proteome analysis

A biphasic monolithic capillary column with 10 cm segment of strong-cation exchange monolith and 65 cm segment of reversed-phase monolith was prepared within a single 100 microm i.d. capillary. Separation performance of this column was evaluated by a five-cycle online multidimensional separation of 10 microg tryptic digest of yeast proteins using nanoflow liquid chromatography coupled with tandem mass spectrometry, and it took 12 h for whole separation under the operating pressure only approximately 900 psi. Totally, 780 distinct proteins were positively identified through assignment of 2953 unique peptides at false-positive rate less than 1%. The good separation performance of this biphasic column was largely attributed to the good orthogonality of the strong-cation exchange monolith and reversed-phase monolith for multidimensional separation.     

Proteomic analysis of exosomes from human neural stem cells by flow field-flow fractionation and nanoflow liquid chromatography-tandem mass spectrometry

Exosomes, small membrane vesicles secreted by a multitude of cell types, are involved in a wide range of physiological roles such as intercellular communication, membrane exchange between cells, and degradation as an alternative to lysosomes. Because of the small size of exosomes (30-100 nm) and the limitations of common separation procedures including ultracentrifugation and flow cytometry, size-based fractionation of exosomes has been challenging. In this study, we used flow field-flow fractionation (FlFFF) to fractionate exosomes according to differences in hydrodynamic diameter. The exosome fractions collected from FlFFF runs were examined by transmission electron microscopy (TEM) to morphologically confirm their identification as exosomes. Exosomal lysates of each fraction were digested and analyzed using nanoflow LC-ESI-MS-MS for protein identification. FIFFF, coupled with mass spectrometry, allows nanoscale size-based fractionation of exosomes and is more applicable to primary cells and stem cells since it requires much less starting material than conventional gel-based separation, in-gel digestion and the MS-MS method.     

Isoform analysis of LC-MS/MS data from multidimensional fractionation of the serum proteome

We developed a visualization approach for the identification of protein isoforms, precursor/mature protein combinations, and fragments from LC-MS/MS analysis of multidimensional fractionation of serum and plasma proteins. We also describe a pattern recognition algorithm to automatically detect and flag potentially heterogeneous species of proteins in proteomic experiments that involve extensive fractionation and result in a large number of identified serum or plasma proteins in an experiment. Examples are given of proteins with known isoforms that validate our approach and present a subset of precursor/mature protein pairs that were detected with this approach. Potential applications include identification of differentially expressed isoforms in disease states.     

Biomarker discovery from the plasma proteome using multidimensional fractionation proteomics

Because biomarkers are typically low in abundance, the crucial step of biomarker discovery is to efficiently separate clinically relevant sets of proteins that might define disease stages and/or predict disease development. It is anticipated that a multi-dimensional fractionation system (MDFS) will provide an efficient means of separating low abundance proteins from plasma proteins, resulting in the extension of the detection limit. However, when using an MDFS to analyze the plasma proteome it is important to consider how sample processing, yield, resolution and throughput potential may influence the detection limit. This review evaluates the recent advances in MDFS research with respect to '4RS criterion' (4R: resolution, reproducibility, recovery, and robustness; 4S: simplicity, speed, selectivity and sensitivity) and discusses perspectives for future plasma-derived biomarker discovery.     

Evaluation of four phosphopeptide enrichment strategies for mass spectrometry-based proteomic analysis

Information about phosphorylation status can be used to prioritize and characterize biological processes in the cell. Various analytical strategies have been proposed to address the complexity of phosphorylation status and comprehensively identify phosphopeptides. In this study, we evaluated four strategies for phosphopeptide enrichment, using titanium dioxide (TiO₂) and Phos-tag ligand particles from in-gel or in-solution digests prior to mass spectrometry-based analysis. Using TiO₂ and Phos-tag magnetic beads, it was possible to enrich phosphopeptides from in-gel digests of phosphorylated ovalbumin separated by Phos-tag SDS-PAGE or in-solution serum digests, while minimizing non-specific adsorption. The tip-column strategy with TiO₂ particles enabled enrichment of phosphopeptides from in-solution digests of whole-cell lysates with high efficiency and selectivity. However, the tip-column strategy with Phos-tag agarose beads yielded the greatest number of identified phosphopeptides. The strategies using both types of tip columns had a high degree of overlap, although there were differences in selectivity between the identified phosphopeptides. Together, our results indicate that multi-enrichment strategies using TiO₂ particles and Phos-tag agarose beads are useful for comprehensive phosphoproteomic analysis.     

Automated metal-free multiple-column nanoLC for improved phosphopeptide analysis sensitivity and throughput

We report on the development and characterization of automated metal-free multiple-column nanoLC instrumentation for sensitive and high-throughput analysis of phosphopeptides with mass spectrometry. The system employs a multiple-column capillary LC fluidic design developed for high-throughput analysis of peptides (Anal. Chem. 2001, 73, 3011–3021), incorporating modifications to achieve broad and sensitive analysis of phosphopeptides. The integrated nanoLC columns (50 μm i.d. × 30 cm containing 5 μm C18 particles) and the on-line solid phase extraction columns (150 μm i.d. × 4 cm containing 5 μm C18 particles) were connected to automatic switching valves with non-metal chromatographic accessories, and other modifications to avoid the exposure of the analyte to any metal surfaces during handling, separation, and electrospray ionization. The nanoLC developed provided a separation peak capacity of ～250 for phosphopeptides (and ～400 for normal peptides). A detection limit of 0.4 fmol was obtained when a linear ion trap tandem mass spectrometer (Finnegan LTQ) was coupled to a 50-μm i.d. column of the nanoLC. The separation power and sensitivity provided by the nanoLC–LTQ enabled identification of ～4600 phosphopeptide candidates from ～60 μg COS-7 cell tryptic digest followed by IMAC enrichment and ～520 tyrosine phosphopeptides from ～2 mg of human T cells digests followed by phosphotyrosine peptide immunoprecipitation.     

Breeding for high water-use efficiency

There is a pressing need to improve the water-use efficiency of rain-fed and irrigated crop production. Breeding crop varieties with higher water-use efficiency is seen as providing part of the solution. Three key processes can be exploited in breeding for high water-use efficiency: (i) moving more of the available water through the crop rather than it being wasted as evaporation from the soil surface or drainage beyond the root zone or being left behind in the root zone at harvest; (ii) acquiring more carbon (biomass) in exchange for the water transpired by the crop, i.e. improving crop transpiration efficiency; (iii) partitioning more of the achieved biomass into the harvested product. The relative importance of any one of these processes will vary depending on how water availability varies during the crop cycle. However, these three processes are not independent. Targeting specific traits to improve one process may have detrimental effects on the other two, but there may also be positive interactions. Progress in breeding for improved water-use efficiency of rain-fed wheat is reviewed to illustrate the nature of some of these interactions and to highlight opportunities that may be exploited in other crops as well as potential pitfalls. For C3 species, measuring carbon isotope discrimination provides a powerful means of improving water-use efficiency of leaf gas exchange, but experience has shown that improvements in leaf-level water-use efficiency may not always translate into higher crop water-use efficiency or yield. In fact, the reverse has frequently been observed. Reasons for this are explored in some detail. Crop simulation modelling can be used to assess the likely impact on water-use efficiency and yield of changing the expression of traits of interest. Results of such simulations indicate that greater progress may be achieved by pyramiding traits so that potential negative effects of individual traits are neutralized. DNA-based selection techniques may assist in such a strategy.     

Enhancement of the efficiency of phosphoproteomic identification by removing phosphates after phosphopeptide enrichment

Immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO2) chromatography are simple, widely used, and cost-effective methods to enrich phosphopeptides, but the sample loading buffer composition, desalting procedure, and control of loading amount are critical to avoid nonspecific interactions and to achieve efficient phosphopeptide enrichment. Although the combination of MS3 analysis and high-resolution mass spectrometry (MS) is helpful to identify phosphopeptides, the quality of many MS/MS spectra having a neutral loss peak of phosphate is still too poor to allow sequence identification, and this results in many false-negative as well as false-positive identifications. Here, we present a novel strategy, which is based on the use of alkaline phosphatase to remove phosphates and analysis of phospho/dephosphopeptide retention times to increase the reliability of identification. The use of phospho/dephosphopeptide retention time ratios allows the identification of phosphopeptides with high confidence with the aid of a focused database of dephosphopeptides. This approach was very effective to identify multiple phophorylations in tryptic peptides. A 'true' phosphorylation data set should contain about 90% phospho-Ser and a few percent phospho-Tyr, and this ratio can be used as a quality criterion for evaluation of data sets. By applying this efficient approach, we were able to identify more than one thousand phosphopeptides.     

Mining phosphopeptide signals in liquid chromatography-mass spectrometry data for protein phosphorylation analysis

Protein phosphorylation is a key post-translational modification that governs biological processes. Despite the fact that a number of analytical strategies have been exploited for the characterization of protein phosphorylation, the identification of protein phosphorylation sites is still challenging. We proposed here an alternative approach to mine phosphopeptide signals generated from a mixture of proteins when liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is involved. The approach combined dephosphorylation reaction, accurate mass measurements from a quadrupole/time-of-flight mass spectrometer, and a computing algorithm to differentiate possible phosphopeptide signals obtained from the LC-MS analyses by taking advantage of the mass shift generated by alkaline phosphatase treatment. The retention times and m/z values of these selected LC-MS signals were used to facilitate subsequent LC-MS/MS experiments for phosphorylation site determination. Unlike commonly used neutral loss scan experiments for phosphopeptide detection, this strategy may not bias against tyrosine-phosphorylated peptides. We have demonstrated the applicability of this strategy to sequence more, in comparison with conventional data-dependent LC-MS/MS experiments, phosphopeptides in a mixture of alpha- and beta-caseins. The analytical scheme was applied to characterize the nasopharyngeal carcinoma (NPC) cellular phosphoproteome and yielded 221 distinct phosphorylation sites. Our data presented in this paper demonstrated the merits of computation in mining phosphopeptide signals from a complex mass spectrometric data set.     

High performance computing environment for multidimensional image analysis

Background

The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications.

Results

We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478× speedup.

Conclusion

Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

     

Online resources for SNP analysis

The major online single nucleotide polymorphism (SNP) databases freely available as research tools for genetic analysis are explained, reviewed, and compared. An outline is given of the search strategies that can be used with the most extensive current SNP databases: National Centre for Biotechnology Information (NCBI) dbSNP and HapMap to help the user secure the most appropriate data for the research needs of clinical genetics and population genetics research. A range of online tools that can be useful in designing SNP genotyping assays are also detailed.     

A multidimensional chromatography technology for in-depth phosphoproteome analysis

Protein phosphorylation is a post-translational modification widely used to regulate cellular responses. Recent studies showed that global phosphorylation analysis could be used to study signaling pathways and to identify targets of protein kinases in cells. A key objective of global phosphorylation analysis is to obtain an in-depth mapping of low abundance protein phosphorylation in cells; this necessitates the use of suitable separation techniques because of the complexity of the phosphoproteome. Here we developed a multidimensional chromatography technology, combining IMAC, hydrophilic interaction chromatography, and reverse phase LC, for phosphopeptide purification and fractionation. Its application to the yeast Saccharomyces cerevisiae after DNA damage led to the identification of 8764 unique phosphopeptides from 2278 phosphoproteins using tandem MS. Analysis of two low abundance proteins, Rad9 and Mrc1, revealed that approximately 50% of their phosphorylation was identified via this global phosphorylation analysis. Thus, this technology is suited for in-depth phosphoproteome studies.     

Specific phosphopeptide enrichment with immobilized titanium ion affinity chromatography adsorbent for phosphoproteome analysis

The elucidation of protein post-translational modifications, such as phosphorylation, remains a challenging analytical task for proteomic studies. Since many of the proteins targeted for phosphorylation are low in abundance and phosphorylation is typically substoichiometric, a prerequisite for their identification is the specific enrichment of phosphopeptide prior to mass spectrometric analysis. Here, we presented a new method termed as immobilized titanium ion affinity chromatography (Ti (4+)-IMAC) for enriching phosphopeptides. A phosphate polymer, which was prepared by direct polymerization of monomers containing phosphate groups, was applied to immobilize Ti (4+) through the chelating interaction between phosphate groups on the polymer and Ti (4+). The resulting Ti (4+)-IMAC resin specifically isolates phosphopeptides from a digest mixture of standard phosphoproteins and nonphosphoprotein (BSA) in a ratio as low as 1:500. Ti (4+)-IMAC was further applied for phosphoproteome analysis of mouse liver. We also compared Ti (4+)-IMAC to other enrichment methods including Fe (3+)-IMAC, Zr (4+)-IMAC, TiO 2 and ZrO 2, and demonstrate superior selectivity and efficiency of Ti (4+)-IMAC for the isolation and enrichment of phosphopeptides. The high specificity and efficiency of phosphopeptide enrichment by Ti (4+)-IMAC mainly resulted from the flexibility of immobilized titanium ion with spacer arm linked to polymer beads as well as the specific interaction between immobilized titanium ion and phosphate group on phosphopeptides.     

Improving the efficiency of multidimensional scaling in the analysis of high-dimensional data using singular value decomposition

MOTIVATION: Multidimensional scaling (MDS) is a well-known multivariate statistical analysis method used for dimensionality reduction and visualization of similarities and dissimilarities in multidimensional data. The advantage of MDS with respect to singular value decomposition (SVD) based methods such as principal component analysis is its superior fidelity in representing the distance between different instances specially for high-dimensional geometric objects. Here, we investigate the importance of the choice of initial conditions for MDS, and show that SVD is the best choice to initiate MDS. Furthermore, we demonstrate that the use of the first principal components of SVD to initiate the MDS algorithm is more efficient than an iteration through all the principal components. Adding stochasticity to the molecular dynamics simulations typically used for MDS of large datasets, contrary to previous suggestions, likewise does not increase accuracy. Finally, we introduce a k nearest neighbor method to analyze the local structure of the geometric objects and use it to control the quality of the dimensionality reduction. RESULTS: We demonstrate here the, to our knowledge, most efficient and accurate initialization strategy for MDS algorithms, reducing considerably computational load. SVD-based initialization renders MDS methodology much more useful in the analysis of high-dimensional data such as functional genomics datasets.     

Modular stop and go extraction tips with stacked disks for parallel and multidimensional Peptide fractionation in proteomics

Proteome complexity necessitates protein or peptide separation prior to analysis. We previously described a pipet-tip based peptide micropurification system named StageTips (STop and Go Extraction Tips), which consists of a very small disk of membrane-embedded separation material. Here, we extend this approach in several dimensions by stacking disks containing reversed phase (C(18)) and strong cation exchange (SCX) materials. Multidimensional fractionation as well as desalting, filtration, and concentration prior to mass spectrometry in single or tandem columns is described. C(18)-SCX-C(18) stacked disks significantly improved protein identification by LC-MS/MS for an E. coli protein digest and by MALDI-MS for a 12 standard protein digest. Sequential fractionation based on C(18)- followed by SCX material was also developed. This multidimensional fractionation approach was expanded to parallel sample preparation by incorporating C(18)-SCX-StageTips into a 96-well plate (StagePlate). Fractions were collected into other C(18)-StagePlates and desalted and eluted in parallel to sample well plates or MALDI targets. This approach is suitable for high throughput protein identification for moderately complex, low abundance samples using automated nanoelectrospray-MS/MS or MALDI-MS.     

Advances in phosphopeptide enrichment techniques for phosphoproteomics

Phosphoproteomics is increasingly used to address a wide range of biological questions. However, despite some success, techniques for phosphoproteomics are not without challenges. Phosphoproteins are present in cells in low abundance relative to their unphosphorylated counterparts; therefore phosphorylated proteins (or phosphopeptides after protein digestion) are rarely detected in standard shotgun proteomics experiments. Thus, extraction of phosphorylated polypeptides from complex mixtures is a critical step in the success of phosphoproteomics experiments. Intense research over the last decade has resulted in the development of powerful techniques for phosphopeptide enrichment prior to analysis by mass spectrometry. Here, we review how the development of IMAC, MOAC, chemical derivatization and antibody affinity purification and chromatography is contributing to the evolution of phosphoproteomics techniques. Although further developments are needed for the technology to reach maturity, current state-of-the-art techniques can already be used as powerful tools for biological research.     

Size-exclusion chromatography in multidimensional separation schemes for proteome analysis

Size-exclusion chromatography (SEC) is a separation technique with a relatively low resolving power, compared to those usually utilized in proteomics. Therefore, it is often overlooked in experimental protocols, when the main goal is resolving complex biological mixtures. In this report, we introduce innovative multidimensional schemes for proteomics analysis, in which SEC plays a practical role. Liquid isoelectric focusing (IEF) was combined with SEC, and experimental results were compared to those obtained by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), well-established techniques relying upon similar criteria for separation.Additional experiments were performed to evaluate the practical contribution of SEC in multidimensional chromatographic separations. Specifically, we evaluated the combination of SEC and ion exchange chromatography in an analytical scheme for the mass spectrometric analysis of protein-extracts obtained from bacterial cultures grown in stable isotope enriched media. Experimental conditions and practical considerations are discussed.     

Improved frequency resolution in multidimensional constant-time experiments by multidimensional Bayesian analysis

Summary The resolution of spectral frequencies in NMR data obtained from discrete Fourier transformation (DFT) along D constant-time dimensions can be improved significantly through extrapolation of the D-dimensional free induction decay (FID) by multidimensional Bayesian analysis. Starting from Bayesian probability theory for parameter estimation and model detection of one-dimensional time-domain data [Bretthorst, (1990) J. Magn. Reson., 88, 533–551; 552–570; 571–595], a theory for the D-dimensional case has been developed and implemented in an algorithm called BAMBAM (BAyesian Model Building Algorithm in Multidimensions). BAMBAM finds the most probable sinusoidal model to account for the systematic portion of any D-dimensional stationary FID. According to the parameters estimated by the algorithm, the FID is extrapolated in D dimensions prior to apodization and Fourier transformation. Multidimensional Bayesian analysis allows for the detection of signals not resolved by the DFT alone or even by sequential one-dimensional extrapolation from mirror-image linear prediction prior to the DFT. The procedure has been tested with a theoretical two-dimensional dataset and with four-dimensional HN(CO)CAHA (Kay et al. (1992) J. Magn. Reson., 98, 443–450) data from a small protein (8 kDa) where BAMBAM was applied to the ¹³C and H constant-time dimensions.To whom correspondence should be addressed.