Mast cell infiltration of the choroid and protease release are early events in age-related macular degeneration associated with genetic risk at both chromosomes 1q32 and 10q26.

Age-related macular degeneration (AMD) is a leading cause of visual loss. It has a strong genetic basis, and common haplotypes on chromosome (Chr) 1 (CFH Y402H variant) and on Chr10 (near HTRA1/ARMS2) contribute the most risk. Little is known about the early molecular and cellular processes in AMD, and we hypothesized that analyzing submacular tissue from older donors with genetic risk but without clinical features of AMD would provide biological insights. Therefore, we used mass spectrometry­based quantitative proteomics to compare the proteins in human submacular stromal tissue punches from donors who were homozygous for high-risk alleles at either Chr1 or Chr10 with those from donors who had protective haplotypes at these loci, all without clinical features of AMD. Additional comparisons were made with tissue from donors who were homozygous for high-risk Chr1 alleles and had early AMD. The Chr1 and Chr10 risk groups shared common changes compared with the low-risk group, particularly increased levels of mast cell­specific proteases, including tryptase, chymase, and carboxypeptidase A3. Histological analyses of submacular tissue from donors with genetic risk of AMD but without clinical features of AMD and from donors with Chr1 risk and AMD demonstrated increased mast cells, particularly the tryptase-positive/chymase-negative cells variety, along with increased levels of denatured collagen compared with tissue from low­genetic risk donors. We conclude that increased mast cell infiltration of the inner choroid, degranulation, and subsequent extracellular matrix remodeling are early events in AMD pathogenesis and represent a unifying mechanistic link between Chr1- and Chr10-mediated AMD.

Development and validation of a methotrexate adherence assay.

BACKGROUND: The first-line therapy for rheumatoid arthritis (RA) is weekly oral methotrexate (MTX) at low dosages (7.5-25 mg/week). However, ~40% of patients are non-adherent which may explain why some do not respond and need to start more expensive biological therapies. To monitor adherence more accurately and develop strategies to improve it, a validated objective MTX adherence test is required. OBJECTIVE: To develop and validate the diagnostic accuracy of a novel MTX adherence assay using high-performance liquid chromatography-selected reaction monitoring- mass spectrometry (HPLC-SRM-MS) based biochemical analysis of drug levels. METHODS: 20 patients with RA underwent MTX pharmacokinetic assessment using HPLC-SRM-MS MTX plasma concentration analysis over a 6-day period. Directly observed therapy was the reference standard. Pharmacokinetic model validation was performed using independent plasma samples from real-world patients (n=50) with self-reported times of drug administration. Following assay optimisation, the sensitivity of the assay to detect adherence was established using samples from an observational cohort study (n=138). RESULTS: A two-compartment pharmacokinetic model was developed and validated. Simulations described the sensitivity required for MTX detection over 7 days; subsequent assay optimisation and retesting of samples confirmed that all patients were correctly identified as MTX adherers. Using real-world samples, the assays sensitivity was 95%. CONCLUSION: Non-adherence to MTX is common and can have a significant effect on disease activity. HPLC-SRM-MS plasma analysis accurately detects MTX adherence. The validated objective test could easily be used in clinic to identify patients requiring adherence support.

Regional protein expression in human Alzheimer's brain correlates with disease severity.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that currently affects 36 million people worldwide with no effective treatment available. Development of AD follows a distinctive pattern in the brain and is poorly modelled in animals. Therefore, it is vital to widen the spatial scope of the study of AD and prioritise the study of human brains. Here we show that functionally distinct human brain regions display varying and region-specific changes in protein expression. These changes provide insights into the progression of disease, novel AD-related pathways, the presence of a gradient of protein expression change from less to more affected regions and a possibly protective protein expression profile in the cerebellum. This spatial proteomics analysis provides a framework which can underpin current research and open new avenues to enhance molecular understanding of AD pathophysiology, provide new targets for intervention and broaden the conceptual frameworks for future AD research.

Quantitative data describing the impact of the flavonol rutin on in-vivo blood-glucose and fluid-intake profiles, and survival of human-amylin transgenic mice.

Here we provide data describing the time-course of blood-glucose and fluid-intake profiles of diabetic hemizygous human-amylin (hA) transgenic mice orally treated with rutin, and matched control mice treated with water. We employed "parametric change-point regression analysis" for investigation of differences in time-course profiles between the control and rutin-treatment groups to extract, for each animal, baseline levels of blood glucose and fluid-intake, the change-point time at which blood glucose (diabetes-onset) and fluid-intake (polydipsia-onset) accelerated away from baseline, and the rate of this acceleration. The parametric change-point regression approach applied here allowed a much more accurate determination of the exact time of onset of diabetes than do the standard diagnostic criteria. These data are related to the article entitled "Rutin suppresses human-amylin/hIAPP misfolding and oligomer formation in-vitro, and ameliorates diabetes and its impacts in human-amylin/hIAPP transgenic mice" (J.F. Aitken, K.M. Loomes, I. Riba-Garcia, R.D. Unwin, G. Prijic, A.S. Phillips, A.R.J. Phillips, D. Wu, S.D. Poppitt, K. Ding, P.E. Barran, A.W. Dowsey, G.J.S. Cooper. 2016) [1].

Rutin suppresses human-amylin/hIAPP misfolding and oligomer formation in-vitro, and ameliorates diabetes and its impacts in human-amylin/hIAPP transgenic mice.

Pancreatic islet ß-cells secrete the hormones insulin and amylin, and defective ß-cell function plays a central role in the pathogenesis of type-2 diabetes (T2D). Human amylin (hA, also termed hIAPP) misfolds and forms amyloid aggregates whereas orthologous mouse amylin does neither. Furthermore, hA elicits apoptosis in cultured ß-cells and ß-cell death in ex-vivo islets. In addition, hA-transgenic mice that selectively express hA in their ß-cells, manifest ß-cell apoptosis and progressive islet damage that leads to diabetes closely resembling that in patients with T2D. Aggregation of hA is thus linked to the causation of diabetes. We employed time-dependent thioflavin-T spectroscopy and ion-mobility mass spectrometry to screen potential suppressors of hA misfolding for anti-diabetic activity. We identified the dietary flavonol rutin as an inhibitor of hA-misfolding and measured its anti-diabetic efficacy in hA-transgenic mice. In vitro, rutin bound hA, suppressed misfolding, disaggregated oligomers and reverted hA-conformation towards the physiological. In hA-transgenic mice, measurements of glucose, fluid-intake, and body-weight showed that rutin-treatment slowed diabetes-progression by lowering of rates of elevation in blood glucose (P = 0.030), retarding deterioration from symptomatic diabetes to death (P = 0.014) and stabilizing body-weight (P < 0.0001). In conclusion, rutin treatment suppressed hA-aggregation in vitro and doubled the lifespan of diabetic mice (P = 0.011) by a median of 69 days compared with vehicle-treated control-diabetic hA-transgenic mice.

Streaming visualisation of quantitative mass spectrometry data based on a novel raw signal decomposition method.

As data rates rise, there is a danger that informatics for high-throughput LC-MS becomes more opaque and inaccessible to practitioners. It is therefore critical that efficient visualisation tools are available to facilitate quality control, verification, validation, interpretation, and sharing of raw MS data and the results of MS analyses. Currently, MS data is stored as contiguous spectra. Recall of individual spectra is quick but panoramas, zooming and panning across whole datasets necessitates processing/memory overheads impractical for interactive use. Moreover, visualisation is challenging if significant quantification data is missing due to data-dependent acquisition of MS/MS spectra. In order to tackle these issues, we leverage our seaMass technique for novel signal decomposition. LC-MS data is modelled as a 2D surface through selection of a sparse set of weighted B-spline basis functions from an over-complete dictionary. By ordering and spatially partitioning the weights with an R-tree data model, efficient streaming visualisations are achieved. In this paper, we describe the core MS1 visualisation engine and overlay of MS/MS annotations. This enables the mass spectrometrist to quickly inspect whole runs for ionisation/chromatographic issues, MS/MS precursors for coverage problems, or putative biomarkers for interferences, for example. The open-source software is available from http://seamass.net/viz/.

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.

BACKGROUND: Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). RESULTS: 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. CONCLUSION: This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

Studies of peptide a- and b-type fragment ions using stable isotope labeling and integrated ion mobility/tandem mass spectrometry.

The structures of peptide a- and b-type fragment ions were studied using synthetic peptides including a set of isomeric peptides, differing in the sequence location of an alanine residue labeled with (15)N and uniformly with (13)C. The pattern of isotope labeling of second-generation fragment ions derived via a(n) and b(n) ions (where n = 4 or 5) suggested that these intermediates existed in part as macrocyclic structures, where alternative sites of ring opening gave rise to different linear forms whose simple cleavage might give rise to the observed final products. Similar conclusions were derived from combined ion mobility/tandem MS analyses where different fragmentation patterns were observed for isomeric a- or b-type ions that display different ion mobilities. These analyses were facilitated by a new approach to the processing of ion mobility/tandem MS data, from which distinct and separate product ion spectra are derived from ions that are incompletely separated by ion mobility. Finally, an example is provided of evidence for a macrocyclic structure for b(n) ions where n = 8 or 9.

Evidence for structural variants of a- and b-type peptide fragment ions using combined ion mobility/mass spectrometry.

Tandem mass spectrometry (MS/MS) of peptides plays a key role in the field of proteomics, and an understanding of the fragmentation mechanisms involved is vital for data interpretation. Not all the fragment ions observed by low-energy collision-induced dissociation of protonated peptides are readily explained by the generally accepted structures for a- and b-ions. The possibility of a macrocyclic structure for b-type ions has been recently proposed. In this study, we have undertaken investigations of linear protonated YAGFL-NH(2), N-acetylated-YAGFL-NH(2), and cyclo-(YAGFL) peptides and their fragments using a combination of ion mobility (IM) separation and mass spectrometry. The use of IM in this work both gives insight into relative structural forms of the ion species and crucial separation of isobaric species. Our study provides compelling evidence for the formation of a stable macrocyclic structure for the b(5) ion generated by fragmentation of protonated linear YAGFL-NH(2). Additionally we demonstrate that the a(4) ion fragment of protonated YAGFL-NH(2) has at least two structures; one of which is attributable to a macrocyclic structure on the basis of its subsequent fragmentation. More generally, this work emphasizes the value of combined IM-MS/MS in probing the detailed fragmentation mechanisms of peptide ions, and illustrates the use of combined ion mobility/collisional activation/mass spectrometry analysis in achieving an effective enhancement of the resolution of the mobility separator.

Development of a technique to determine bicyclomycin-rho binding and stoichiometry by isothermal titration calorimetry and mass spectrometry.

Bicyclomycin (1) is the only natural product inhibitor of the transcription termination factor rho. Rho is a hexameric helicase that terminates nascent RNA transcripts utilizing ATP hydrolysis and is an essential protein for many bacteria. The paucity of information concerning the 1-rho interaction stems from the weak binding affinity of 1. We report a novel technique using imine formation with rho to enhance the affinity of a bicyclomycin analogue and determine the binding stoichiometry by isothermal titration calorimetry (ITC) and mass spectrometry (MS). Our designed bicyclomycin ligand, 5a-(3-formyl-phenylsulfanyl)-dihydrobicyclomycin (2) (apparent I(50) = 4 muM), inhibits rho an order of magnitude more efficiently than 1 (I(50) = 60 muM). MS shows that 2 selectively forms an imine with K181 in rho. We found that despite the heterogeneity of ATP binding (three tight and three weak) imposed on the rho hexamer, the nearby bicyclomycin binding pocket is not affected, and both 1 and 2 bind with equal affinity to all six subunits.

Proteomic response to amino acid starvation in Candida albicans and Saccharomyces cerevisiae.

Saccharomyces cerevisiae activates general amino acid control (GCN) in response to amino acid starvation. Some aspects of this response are known to be conserved in other fungi including Candida albicans, the major systemic fungal pathogen of humans. Here, we describe a proteomic comparison of the GCN responses in S. cerevisiae and C. albicans. We have used high-resolution two-dimensional (2-D) gel electrophoresis and peptide mass fingerprinting to develop a 2-D protein map of C. albicans. A total of 391 protein spots, representing 316 open reading frames, were identified. Fifty-five C. albicans and 65 S. cerevisiae proteins were identified that responded reproducibly to 3-aminotriazole (3AT) in a Gcn4p-dependent fashion. The changes in the S. cerevisiae proteome correlated with the response in the S. cerevisiae transcript profile to 3AT treatment (rank correlation coefficient = 0.59; Natarajan et al., Molec. Cell. Biol. 2001, 21, 4347-4368). Significant aspects of the GCN response were conserved in C. albicans and S. cerevisiae. In both fungi, amino acid biosynthetic enzymes on multiple metabolic pathways were induced by 3AT in a Gcn4p-dependent fashion. Carbon metabolism functions were also induced. However, subtle differences were observed between these fungi. For example, purine biosynthetic enzymes were induced in S. cerevisiae, but were not significantly induced in C. albicans. These differences presumably reflect the contrasting niches of these relatively benign and pathogenic yeasts, respectively.

Genome-wide analysis of the effects of heat shock on a Saccharomyces cerevisiae mutant with a constitutively activated cAMP-dependent pathway.

We have used DNA microarray technology and 2-D gel electrophoresis combined with mass spectrometry to investigate the effects of a drastic heat shock from 30 to 50 on a genome-wide scale. This experimental condition is used to differentiate between wild-type cells and those with a constitutively active cAMP-dependent pathway in Saccharomyces cerevisiae. Whilst more than 50% of the former survive this shock, almost all of the latter lose viability. We compared the transcriptomes of the wildtype and a mutant strain deleted for the gene PDE2, encoding the high-affinity cAMP phosphodiesterase before and after heat shock treatment. We also compared the two heat-shocked samples with one another, allowing us to determine the changes that occur in the pde2Delta mutant which cause such a dramatic loss of viability after heat shock. Several genes involved in ergosterol biosynthesis and carbon source utilization had altered expression levels, suggesting that these processes might be potential factors in heat shock survival. These predictions and also the effect of the different phases of the cell cycle were confirmed by biochemical and phenotypic analyses. 146 genes of previously unknown function were identified amongst the genes with altered expression levels and deletion mutants in 13 of these genes were found to be highly sensitive to heat shock. Differences in response to heat shock were also observed at the level of the proteome, with a higher level of protein degradation in the mutant, as revealed by comparing 2-D gels of wild-type and mutant heat-shocked samples and mass spectrometry analysis of the differentially produced proteins.

A systematic approach to modeling, capturing, and disseminating proteomics experimental data.

Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.

Dynamics of protein turnover, a missing dimension in proteomics.

Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucose-limited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.

Stable isotope labelling in vivo as an aid to protein identification in peptide mass fingerprinting.

Peptide mass fingerprinting (PMF) is a powerful technique for identification of proteins derived from in-gel digests by virtue of their matrix-assisted laser desorption/ionization-time of flight mass spectra. However, there are circumstances where the under-representation of peptides in the mass spectrum and the complexity of the source proteome mean that PMF is inadequate as an identification tool. In this paper, we show that identification is substantially enhanced by inclusion of composition data for a single amino acid. Labelling in vivo with a stable isotope labelled amino acid (in this paper, decadeuterated leucine) identifies the number of such amino acids in each digest fragment, and show a considerable gain in the ability of PMF to identify the parent protein. The method is tolerant to the extent of labelling, and as such, may be applicable to a range of single cell systems.