Proteomic profiling of the retinas in a neonatal rat model of oxygen-induced retinopathy with a reproducible ion-current-based MS1 approach.

Investigation of the retina proteome during hypoxia-induced retinal neovascularization is valuable for understanding pathogenesis of retinopathy of prematurity (ROP). Here we employed a reproducible ion-current-based MS1 quantification approach (ICB) to explore the retinal proteomic changes in early stage of ROP in a rat model of oxygen-induced retinopathy (OIR). Retina proteins, which are rich in membrane proteins, were efficiently extracted by a detergent-cocktail and subjected to precipitation/on-pellet-digestion, followed by nano-LC-MS analysis on a 75-cm column with a 7-h gradient. The high reproducibility of sample preparation and chromatography separation enabled excellent peak alignment and contributed to the superior performance of ICB over parallel label-free approaches. In this study, sum-of-intensity with rejection was incorporated to determine the protein ratios. In total, 1325 unique protein groups were quantified from rat retinas (n = 4/group) with at least two distinct peptides at a protein FDR of 1%. Thirty-two significantly altered proteins were observed with confidence, and the elevated glial fibrillary acidic protein and decreased crystalline proteins in OIR retinas agree well with previous studies. Selected key alterations were further validated by Western blot analysis. Interestingly, Rab21/RhoA/ROCK2/moesin signaling pathway was found to be involved in retinal neovascularization of OIR. Moreover, highly elevated annexin A3, a potential angiogenic mediator, was observed in OIR retinas and may serve as a potential therapeutic target. In conclusion, reproducible ICB profiling enabled reliable discovery of many altered mediators and pathways in OIR retinas, thereby providing new insights into molecular mechanisms involved in pathogenesis of ROP.

Quantitative measurement of phosphoproteome response to osmotic stress in arabidopsis based on Library-Assisted eXtracted Ion Chromatogram (LAXIC).

Global phosphorylation changes in plants in response to environmental stress have been relatively poorly characterized to date. Here we introduce a novel mass spectrometry-based label-free quantitation method that facilitates systematic profiling plant phosphoproteome changes with high efficiency and accuracy. This method employs synthetic peptide libraries tailored specifically as internal standards for complex phosphopeptide samples and accordingly, a local normalization algorithm, LAXIC, which calculates phosphopeptide abundance normalized locally with co-eluting library peptides. Normalization was achieved in a small time frame centered to each phosphopeptide to compensate for the diverse ion suppression effect across retention time. The label-free LAXIC method was further treated with a linear regression function to accurately measure phosphoproteome responses to osmotic stress in Arabidopsis. Among 2027 unique phosphopeptides identified and 1850 quantified phosphopeptides in Arabidopsis samples, 468 regulated phosphopeptides representing 497 phosphosites have shown significant changes. Several known and novel components in the abiotic stress pathway were identified, illustrating the capability of this method to identify critical signaling events among dynamic and complex phosphorylation. Further assessment of those regulated proteins may help shed light on phosphorylation response to osmotic stress in plants.

Issues and applications in label-free quantitative mass spectrometry.

To address the challenges associated with differential expression proteomics, label-free mass spectrometric protein quantification methods have been developed as alternatives to array-based, gel-based, and stable isotope tag or label-based approaches. In this paper, we focus on the issues associated with label-free methods that rely on quantitation based on peptide ion peak area measurement. These issues include chromatographic alignment, peptide qualification for quantitation, and normalization. In addressing these issues, we present various approaches, assembled in a recently developed label-free quantitative mass spectrometry platform, that overcome these difficulties and enable comprehensive, accurate, and reproducible protein quantitation in highly complex protein mixtures from experiments with many sample groups. As examples of the utility of this approach, we present a variety of cases where the platform was applied successfully to assess differential protein expression or abundance in body fluids, in vitro nanotoxicology models, tissue proteomics in genetic knock-in mice, and cell membrane proteomics.

Effect of vulculic acid produced by Nimbya alternantherae on the photosynthetic apparatus of Alternanthera philoxeroides.

The effect of the toxin vulculic acid produced by Nimbya alternantherae, on the photosynthetic apparatus of Alternanthera philoxeroides, was investigated via the photochemical activity and SDS-PAGE of protein on thylakoid membranes, fast chlorophyll a fluorescence transient measurements and the JIP-test. The electron transport rate of photosystem II (PSII), non-cyclic photophosphorylation activity, as well as the activity of chloroplast ATPase and Rubisco reduced significantly after vulculic acid treatment. Vulculic acid affected the O-J-I-P fluorescence induction kinetics, showing an increase of the parameters FV/FO, VK and VJ and a decrease of FO, FM, PIABS, φPo, ψEo, φEo, φRo, δRo and PItotal. In addition, it significantly decreased the amounts of major photosystem I (PSI) and PSII proteins. It is concluded that vulculic acid is a photosynthetic inhibitor with multiple action sites. The main targets are the light harvesting complex (LHC) and the oxygen evolving complex (OEC) on the PSII donor side. Vulculic acid blocks electron transport beyond QA and on the PSI acceptor side by digesting major PSI and PSII proteins.

A novel alignment method and multiple filters for exclusion of unqualified peptides to enhance label-free quantification using peptide intensity in LC-MS/MS.

Though many software packages have been developed to perform label-free quantification of proteins in complex biological samples using peptide intensities generated by LC-MS/MS, two critical issues are generally ignored in this field: (i) peptides have multiple elution patterns across runs in an experiment, and (ii) many peptides cannot be used for protein quantification. To address these two key issues, we have developed a novel alignment method to enable accurate peptide peak retention time determination and multiple filters to eliminate unqualified peptides for protein quantification. Repeatability and linearity have been tested using six very different samples, i.e., standard peptides, kidney tissue lysates, HT29-MTX cell lysates, depleted human serum, human serum albumin-bound proteins, and standard proteins spiked in kidney tissue lysates. At least 90.8% of the proteins (up to 1,390) had CVs ≤ 30% across 10 technical replicates, and at least 93.6% (up to 2,013) had R(2) ≥ 0.9500 across 7 concentrations. Identical amounts of standard protein spiked in complex biological samples achieved a CV of 8.6% across eight injections of two groups. Further assessment was made by comparing mass spectrometric results to immunodetection, and consistent results were obtained. The new approach has novel and specific features enabling accurate label-free quantification.

High-coverage proteome analysis reveals the first insight of protein modification systems in the pathogenic spirochete Leptospira interrogans.

Leptospirosis is a widespread zoonotic disease caused by pathogenic spirochetes of the genus Leptospira that infects humans and a wide range of animals. By combining computational prediction and high-accuracy tandem mass spectra, we revised the genome annotation of Leptospira interrogans serovar Lai, a free-living pathogenic spirochete responsible for leptospirosis, providing substantial peptide evidence for novel genes and new gene boundaries. Subsequently, we presented a high-coverage proteome analysis of protein expression and multiple posttranslational modifications (PTMs). Approximately 64.3% of the predicted L. interrogans proteins were cataloged by detecting 2 540 proteins. Meanwhile, a profile of multiple PTMs was concurrently established, containing in total 32 phosphorylated, 46 acetylated and 155 methylated proteins. The PTM systems in the serovar Lai show unique features. Unique eukaryotic-like features of L. interrogans protein modifications were demonstrated in both phosphorylation and arginine methylation. This systematic analysis provides not only comprehensive information of high-coverage protein expression and multiple modifications in prokaryotes but also a view suggesting that the evolutionarily primitive L. interrogans shares significant similarities in protein modification systems with eukaryotes.

Quantitative analysis of secretome from adipocytes regulated by insulin.

Adipocyte is not only a central player involved in storage and release of energy, but also in regulation of energy metabolism in other organs via secretion of peptides and proteins. During the pathogenesis of insulin resistance and type 2 diabetes, adipocytes are subjected to the increased levels of insulin, which may have a major impact on the secretion of adipokines. We have undertaken cleavable isotope-coded affinity tag (cICAT) and label-free quantitation approaches to identify and quantify secretory factors that are differentially secreted by 3T3-L1 adipocytes with or without insulin treatment. Combination of cICAT and label-free results, there are 317 proteins predicted or annotated as secretory proteins. Among these secretory proteins, 179 proteins and 53 proteins were significantly upregulated and down-regulated, respectively. A total of 77 reported adipokines were quantified in our study, such as adiponectin, cathepsin D, cystatin C, resistin, and transferrin. Western blot analysis of these adipokines confirmed the quantitative results from mass spectrometry, and revealed individualized secreting patterns of these proteins by increasing insulin dose. In addition, 240 proteins were newly identified and quantified as secreted proteins from 3T3-L1 adipocytes in our study, most of which were up-regulated upon insulin treatment. Further comprehensive bioinformatics analysis revealed that the secretory proteins in extracellular matrix-receptor interaction pathway and glycan structure degradation pathway were significantly upregulated by insulin stimulation.

Temporal and spatial profiling of nuclei-associated proteins upon TNF-alpha/NF-kappaB signaling.

The tumor necrosis factor (TNF)-alpha/NF-kappaB-signaling pathway plays a pivotal role in various processes including apoptosis, cellular differentiation, host defense, inflammation, autoimmunity and organogenesis. The complexity of the TNF-alpha/NF-kappaB signaling is in part due to the dynamic protein behaviors of key players in this pathway. In this present work, a dynamic and global view of the signaling components in the nucleus at the early stages of TNF-alpha/NF-kappaB signaling was obtained in HEK293 cells, by a combination of subcellular fractionation and stable isotope labeling by amino acids in cell culture (SILAC). The dynamic profile patterns of 547 TNF-alpha-induced nuclei-associated proteins were quantified in our studies. The functional characters of all the profiles were further analyzed using that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation. Additionally, many previously unknown effectors of TNF-alpha/NF-kappaB signaling were identified, quantified and clustered into differential activation profiles. Interestingly, levels of Fanconi anemia group D2 protein (FANCD2), one of the Fanconi anemia family proteins, was found to be increased in the nucleus by SILAC quantitation upon TNF-alpha stimulation, which was further verified by western blotting and immunofluorescence analysis. This indicates that FANCD2 might be involved in TNF-alpha/NF-kappaB signaling through its accumulation in the nucleus. In summary, the combination of subcellular proteomics with quantitative analysis not only allowed for a dissection of the nuclear TNF-alpha/NF-kappaB-signaling pathway, but also provided a systematic strategy for monitoring temporal and spatial changes in cell signaling.

Fully automatic separation and identification of phosphopeptides by continuous pH-gradient anion exchange online coupled with reversed-phase liquid chromatography mass spectrometry.

Most current technologies for the enrichment of phosphopeptides rely on a tandem combination of different chromatography modes. Here, a fully automatic two-dimensional liquid chromatography mass spectrometry method was developed for global phosphopeptide identification. The peptide mixtures were loaded on a strong anion exchange (SAX) column under basic pH conditions and eluted with a continuous gradient to pH 2.0. This SAX system could be coupled online with reversed-phase liquid chromatography mass spectrometry (RP-LC-MS/MS). For peptide digests from a standard protein mixture spiked with synthesized phosphopeptides, most of the nonphosphorylated peptides were eluted in more basic pH than phosphopeptides, and the phosphopeptides were focused to acidic pH ranges and gradually eluted according to the phosphorylated states of peptides. Compared with the pH step elution method, the continuous gradient method displayed better repeatability and less peptide cross-overlap between fractions. This system provided a robust and fully automatic approach to large-scale phosphoproteomic profiling. For protein tryptic digests from HeLa cells, 1833 nonredundant phosphorylation sites were identified based on this two-phase separation. Compared with the method combining cation exchange and titanium dioxide, this anion-exchange based system preferred to identify more acidic and multiphosphorylated peptides. It also covered a more complete series of phosphorylation states of peptides.

Quantitative phosphoproteome profiling of Wnt3a-mediated signaling network: indicating the involvement of ribonucleoside-diphosphate reductase M2 subunit phosphorylation at residue serine 20 in canonical Wnt signal transduction.

The complexity of canonical Wnt signaling comes not only from the numerous components but also from multiple post-translational modifications. Protein phosphorylation is one of the most common modifications that propagates signals from extracellular stimuli to downstream effectors. To investigate the global phosphorylation regulation and uncover novel phosphoproteins at the early stages of canonical Wnt signaling, HEK293 cells were metabolically labeled with two stable isotopic forms of lysine and were stimulated for 0, 1, or 30 min with purified Wnt3a. After phosphoprotein enrichment and LC-MS/MS analysis, 1057 proteins were identified in all three time points. In total 287 proteins showed a 1.5-fold or greater change in at least one time point. In addition to many known Wnt signaling transducers, other phosphoproteins were identified and quantitated, implicating their involvement in canonical Wnt signaling. k-Means clustering analysis showed dynamic patterns for the differential phosphoproteins. Profile pattern and interaction network analysis of the differential phosphoproteins implicated the possible roles for those unreported components in Wnt signaling. Moreover 100 unique phosphorylation sites were identified, and 54 of them were quantitated in the three time points. Site-specific phosphopeptide quantitation revealed that Ser-20 phosphorylation on RRM2 increased upon 30-min Wnt3a stimulation. Further studies with mutagenesis, the Wnt reporter gene assay, and RNA interference indicated that RRM2 functioned downstream of beta-catenin as an inhibitor of Wnt signaling and that Ser-20 phosphorylation of RRM2 counteracted its inhibition effect. Our systematic profiling of dynamic phosphorylation changes responding to Wnt3a stimulation not only presented a comprehensive phosphorylation network regulated by canonical Wnt signaling but also found novel molecules and phosphorylation involved in Wnt signaling.

Learning module networks from genome-wide location and expression data.

We develop a systematic algorithm for discovering network of regulatory modules, which identifies regulatory modules and their regulation program by integrating genome-wide location and expression data. Unlike previous approaches [Eisen, M.B., Spellman, P.T., Brown, P.O. and Botstein, D. (1998) Proc. Natl. Acad. Sci. USA 95, 14863-14868; Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J. and Church, G.M. (1999) Nat. Genet. 22, 281-285; Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Nat. Genet. 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Nat. Genet. 34, 166-176] that relied primarily on gene expression data, our algorithm regards the regulator binding data as prior knowledge that provide direct evidence of physical regulatory interactions. We applied the method to a Saccharomyces cerevisiae genome-wide location data [Lee, T.I., Rinaldi, N.J., Robert, F., Odom, D.T., Bar-Joseph, Z., Gerber, G.K., Hannett, N.M., Harbison, C.T., Thompson, C.M., Simon, I., Zeitlinger, J., Jennings, E.G., Murray, H.L. Gordon, D.B., Ren, B., Wyrick, J.J., Tagne, J.B., Volkert, T.L., Fraenkel, E., Gifford, D.K. and Young, R.A. (2002) Science 298, 799-804] for 106 DNA-binding transcription factors and 250 gene expression experiments under the conditions from the cell cycle to responses to various stress conditions. The results show that our method is able to identify functionally coherent modules and their proper regulators. Supplementary materials are available at http://compbio.sibnet.org/projects/module-network/.

[Estimating coarse gene networks from yeast gene expression time series].

Gene networks is the collection of gene-gene regulatory relations at the expression level. In this study, a combined approach of the linear transcriptional modeling, identification of promoter elements and gene co-expression clustering is developed to decipher yeast gene networks from expression time series. The cell must reorganize the genomic expression to programs required for growth and survival in each environment. The expression of many genes is regulated by environmental stress. The products of many genes that induced in the environmental stress are involved in metabolism of carbohydrates, structural repairs and even sporulation. Interestingly, it is identified that transcription factors Mcm1 and Dal82 matched their binding sites TT[bond]CC[triple bond]T[double bond]GGAAA and TGAAAAWTTT in cell cycle progression and environmental stress response, respectively. These conclusions agree with the known observations. The results indicate that the approach may be useful for modeling gene networks from microarray data.

[A novel approach for peptide identification by tandem mass spectrometry].

High throughput scoring algorithms that are used to find the match of a tandem mass spectrum to a predicted mass spectrum of a peptide within a database have been applied in shotgun proteomics. However, these algorithms could produce a significant number of incorrect peptide identifications. Here a novel approach was developed to scoring tandem mass spectra against a peptide database, in which fragment ion probabilities, number of enzymatic termini of candidate peptides, matching quality and match pattern between experimental and theoretical spectrum were considered. Benchmarking the novel scorer on a large set of experimental MS/MS spectra, it is demonstrated that PepSearch performs significantly better than the widely used software SEQUEST. The PepSearch software is available at http://compbio.sibsnet.org/projects/pepsearch.