A proteomic investigation into mechanisms underpinning corticosteroid effects on neural stem cells.

Corticosteroids (CSs) are widely used clinically, for example in pediatric respiratory distress syndrome, and immunosuppression to prevent rejection of stem cell transplant populations in neural cell therapy. However, such treatment can be associated with adverse effects such as impaired neurogenesis and myelination, and increased risk of cerebral palsy. There is increasing evidence that CSs can adversely influence key biological properties of neural stem cells (NSCs) but the molecular mechanisms underpinning such effects are largely unknown. This is an important issue to address given the key roles NSCs play during brain development and as transplant cells for regenerative neurology. Here, we describe the use of label-free quantitative proteomics in conjunction with histological analyses to study CS effects on NSCs at the cellular and molecular levels, following treatment with methylprednisolone (MPRED). Immunocytochemical staining showed that both parent NSCs and newly generated daughter cells expressed the glucocorticoid receptor, with nuclear localisation of the receptor induced by MPRED treatment. MPRED markedly decreased NSC proliferation and neuronal differentiation while accelerating the maturation of oligodendrocytes, without concomitant effects on cell viability and apoptosis. Parallel proteomic analysis revealed that MPRED induced downregulation of growth associated protein 43 and matrix metallopeptidase 16 with upregulation of the cytochrome P450 family 51 subfamily A member 1. Our findings support the hypothesis that some neurological deficits associated with CS use may be mediated via effects on NSCs, and highlight putative target mechanisms underpinning such effects.

Simplifying the Proteome: Analytical Strategies for Improving Peak Capacity.

The diversity of biological samples and dynamic range of analytes being analyzed can prove to be an analytical challenge and is particularly prevalent to proteomic studies. Maximizing the peak capacity of the workflow employed can extend the dynamic range and increase identification rates. The focus of this chapter is to present means of achieving this for various analytical techniques such as liquid chromatography, mass spectrometry and ion mobility. A combination of these methods can be used as part of a data independent acquisition strategy, thereby limiting issues such as chimericy when analyzing regions of extreme analyte density.

Simplifying the proteome: analytical strategies for improving peak capacity.

The diversity of biological samples and dynamic range of analytes being analyzed can prove to be an analytical challenge and is particularly prevalent to proteomic studies. Maximizing the peak capacity of the workflow employed can extend the dynamic range and increase identification rates. The focus of this chapter is to present means of achieving this for various analytical techniques such as liquid chromatography, mass spectrometry, and ion mobility. A combination of these methods can be used as part of a data-independent acquisition strategy, thereby limiting issues such as chimericy when analyzing regions of extreme analyte density.

Comparison of one- and two-dimensional liquid chromatography approaches in the label-free quantitative analysis of Methylocella silvestris.

The proteome of the bacterium Methylocella silvestris has been characterized using reversed phase ultra high pressure liquid chromatography (UPLC) and two-dimensional reversed phase (high pH)-reversed phase (low pH) UPLC prior to mass spectrometric analysis. Variations in protein expression levels were identified with the aid of label-free quantification in a study of soluble protein extracts from the organism grown using methane, succinate, or propane as a substrate. The number of first dimensional fractionation steps has been varied for 2D analyses, and the impact on data throughput and quality has been demonstrated. Comparisons have been made regarding required experimental considerations including total loading of biological samples required, instrument time, and resulting data file sizes. The data obtained have been evaluated with respect to number of protein identifications, confidence of assignments, sequence coverage, relative levels of proteins, and dynamic range. Good qualitative and quantitative agreement was observed between the different approaches, and the potential benefits and limitations of the reversed phase-reversed phase UPLC technique in label-free analysis are discussed. A preliminary screen of the protein regulation data has also been performed, providing evidence for a possible propane assimilation route.

Astroglial DJ-1 over-expression up-regulates proteins involved in redox regulation and is neuroprotective in vivo.

DJ-1, a Parkinson's disease-associated protein, is strongly up-regulated in reactive astrocytes in Parkinson's disease. This is proposed to represent a neuronal protective response, although the mechanism has not yet been identified. We have generated a transgenic zebrafish line with increased astroglial DJ-1 expression driven by regulatory elements from the zebrafish GFAP gene. Larvae from this transgenic line are protected from oxidative stress-induced injuries as caused by MPP+, a mitochondrial complex I inhibitor shown to induce dopaminergic cells death. In a global label-free proteomics analysis of wild type and transgenic larvae exposed to MPP+, 3418 proteins were identified, in which 366 proteins were differentially regulated. In particular, we identified enzymes belonging to primary metabolism to be among proteins affected by MPP+ in wild type animals, but not affected in the transgenic line. Moreover, by performing protein profiling on isolated astrocytes we showed that an increase in astrocytic DJ-1 expression up-regulated a large group of proteins associated with redox regulation, inflammation and mitochondrial respiration. The majority of these proteins have also been shown to be regulated by Nrf2. These findings provide a mechanistic insight into the protective role of astroglial up-regulation of DJ-1 and show that our transgenic zebrafish line with astrocytic DJ-1 over-expression can serve as a useful animal model to understand astrocyte-regulated neuroprotection associated with oxidative stress-related neurodegenerative disease.

Inflammation decreases keratin level in ulcerative colitis; inadequate restoration associates with increased risk of colitis-associated cancer.

BACKGROUND: Keratins are intermediate filament (IF) proteins, which form part of the epithelial cytoskeleton and which have been implicated pathology of inflammatory bowel diseases (IBD). METHODS: In this study biopsies were obtained from IBD patients grouped by disease duration and subtype into eight categories based on cancer risk and inflammatory status: quiescent recent onset (<5 years) UC (ROUC); UC with primary sclerosing cholangitis; quiescent long-standing pancolitis (20-40 years) (LSPC); active colitis and non-inflamed proximal colonic mucosa; pancolitis with dysplasia-both dysplastic lesions (DT) and distal rectal mucosa (DR); control group without pathology. Alterations in IF protein composition across the groups were determined by quantitative proteomics. Key protein changes were validated by western immunoblotting and immunohistochemical analysis. RESULT: Acute inflammation resulted in reduced K8, K18, K19 and VIM (all p<0.05) compared to controls and non inflamed mucosa; reduced levels of if- associated proteins were also seen in DT and DR. Increased levels of keratins in LSPC was noted relative to controls or ROUC (K8, K18, K19 and VIM, p<0.05). Multiple K8 forms were noted on immunoblotting, with K8 phosphorylation reduced in progressive disease along with an increase in VIM:K8 ratio. K8 levels and phosphorylation are reduced in acute inflammation but appear restored or elevated in subjects with clinical and endoscopic remission (LSPC) but not apparent in subjects with elevated risk of cancer. CONCLUSIONS: These data suggest that keratin regulation in remission may influence subsequent cancer risk.

Protein deep sequencing applied to biobank samples from patients with pancreatic cancer.

PURPOSE: Pancreatic cancer is commonly detected at advanced stages when the tumor is no longer amenable to surgical resection. Therefore, finding biomarkers for early stage disease is urgent. Here, we show that high-definition mass spectrometry (HDMS(E)) can be used to identify serum protein alterations associated with early stage pancreatic cancer. METHODS: We analyzed serum samples from patients with resectable pancreatic cancer, benign pancreatic disease, and healthy controls. The SYNAPT G2-Si platform was used in a data-independent manner coupled with ion mobility. The dilution of the samples with yeast alcohol dehydrogenase tryptic digest of known concentration allowed the estimated amounts of each identified protein to be calculated (Silva et al. in Anal Chem 77:2187-2200, 2005; Silva et al. in Mol Cell Proteomics 5:144-156, 2006). A global protein expression comparison of the three study groups was made using label-free quantification and bioinformatic analyses. RESULTS: Two-way unsupervised hierarchical clustering revealed 134 proteins that successfully classified pancreatic cancer patients from the controls, and identified 40 proteins that showed a significant up-regulation in the pancreatic cancer group. This discrimination reliability was further confirmed by principal component analysis. The differentially expressed candidates were aligned with protein network analyses and linked to biological pathways related to pancreatic tumorigenesis. Pancreatic disease link associations could be made for BAZ2A, CDK13, DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by pathway network linkages to p53, the most frequently altered tumor suppressor in pancreatic cancer. CONCLUSION: These pancreatic cancer study candidates may provide new avenues of research for a noninvasive blood-based diagnosis for pancreatic tumor stratification.

Characterisation of isoform-specific tryptic peptides of rat cardiac myosin heavy chains using automated liquid chromatography-matrix assisted laser desorption ionisation (LC-MALDI) mass spectrometry.

Proteomics investigations using 2-dimensional electrophoresis (2-DE) cannot resolve the entire cardiac proteome because some proteins, including myosin heavy chains (MyHC), are insoluble in the buffers required for isoelectric focusing. Here, we report an automated mass spectrometry (MS) method complementary to 2-DE and capable of yielding important additional information. Rat myocardium was homogenised in standard lysis solution and centrifuged to produce a supernatant fraction, suitable for 2-DE. The pelleted fraction, which is normally discarded, was used for the current analysis. Proteins were digested with trypsin and the peptides fractionated by HPLC. Automated spotting of eluent fractions onto 384-well target plates and matrix-assisted laser desorption tandem time of flight (MALDI-ToF/ToF) MS were directed by dedicated software. Peptide ions were fragmented by collision-induced dissociation and the MS/MS spectra searched against the NCBI database using Mascot. This approach confidently identified 13 tryptic peptides specific to cardiac alpha-MyHC and 4 specific to beta-MyHC, which can be used to differentiate these highly homologous protein isoforms in future quantitative MS analyses.

Protein markers for insulin-producing beta cells with higher glucose sensitivity.

BACKGROUND AND METHODOLOGY: Pancreatic beta cells show intercellular differences in their metabolic glucose sensitivity and associated activation of insulin production. To identify protein markers for these variations in functional glucose sensitivity, rat beta cell subpopulations were flow-sorted for their level of glucose-induced NAD(P)H and their proteomes were quantified by label-free data independent alternate scanning LC-MS. Beta cell-selective proteins were also identified through comparison with rat brain and liver tissue and with purified islet alpha cells, after geometrical normalization using 6 stably expressed reference proteins. PRINCIPAL FINDINGS: All tissues combined, 943 proteins were reliably quantified. In beta cells, 93 out of 467 quantifiable proteins were uniquely detected in this cell type; several other proteins presented a high molar abundance in beta cells. The proteome of the beta cell subpopulation with high metabolic and biosynthetic responsiveness to 7.5 mM glucose was characterized by (i) an on average 50% higher expression of protein biosynthesis regulators such as 40S and 60S ribosomal constituents, NADPH-dependent protein folding factors and translation elongation factors; (ii) 50% higher levels of enzymes involved in glycolysis and in the cytosolic arm of the malate/aspartate-NADH-shuttle. No differences were noticed in mitochondrial enzymes of the Krebs cycle, beta-oxidation or respiratory chain. CONCLUSIONS: Quantification of subtle variations in the proteome using alternate scanning LC-MS shows that beta cell metabolic glucose responsiveness is mostly associated with higher levels of glycolytic but not of mitochondrial enzymes.

A comparison of labeling and label-free mass spectrometry-based proteomics approaches.

The proteome of the recently discovered bacterium Methylocella silvestris has been characterized using three profiling and comparative proteomics approaches. The organism has been grown on two different substrates enabling variations in protein expression to be identified. The results obtained using the experimental approaches have been compared with respect to number of proteins identified, confidence in identification, sequence coverage and agreement of regulated proteins. The sample preparation, instrumental time and sample loading requirements of the differing experiments are compared and discussed. A preliminary screen of the protein regulation results for biological significance has also been performed.

The use of proteome similarity for the qualitative and quantitative profiling of reperfused myocardium.

An LC-MS-based approach is presented for the identification and quantification of proteins from unsequenced organisms. The method relies on the preservation of homology across species and the similarity in detection characteristics of proteomes in general. Species related proteomes share similarity that progresses from the amino acid frequency distribution to the complete amino sequence of matured proteins. Moreover, the comparative analysis between theoretical and experimental proteome distributions can be used as a measure for the correctness of detection and identification obtained through LC-MS-based schemes. Presented are means to the identification and quantification of rabbit myocardium proteins, immediately after inducing cardiac arrest, using a data-independent LC-MS acquisition strategy. The employed method of acquisition affords accurate mass information on both the precursor and associated product ions, whilst preserving and recording the intensities of the ions. The latter facilitates label-free quantification. The experimental ion density observations obtained for the rabbit sub proteome were found to share great similarity with five other mammalian samples, including human heart, human breast tissue, human plasma, rat liver and a mouse cell line. Redundant, species-homologues peptide identifications from other mammalian organisms were used for initial protein identification, which were complemented with peptide identifications of translated gene sequences. The feasibility and accuracy of label-free quantification of the identified peptides and proteins utilizing above mentioned strategy is demonstrated for selected cardiac rabbit proteins.