MRCQuant- an accurate LC-MS relative isotopic quantification algorithm on TOF instruments

<p>Abstract</p> <p>Background</p> <p>Relative isotope abundance quantification, which can be used for peptide identification and differential peptide quantification, plays an important role in liquid chromatography-mass spectrometry (LC-MS)-based proteomics. However, several major issues exist in the relative isotopic quantification of peptides on time-of-flight (TOF) instruments: LC peak boundary detection, thermal noise suppression, interference removal and mass drift correction. We propose to use the Maximum Ratio Combining (MRC) method to extract MS signal templates for interference detection/removal and LC peak boundary detection. In our method, MRCQuant, MS templates are extracted directly from experimental values, and the mass drift in each LC-MS run is automatically captured and compensated. We compared the quantification accuracy of MRCQuant to that of another representative LC-MS quantification algorithm (msInspect) using datasets downloaded from a public data repository.</p> <p>Results</p> <p>MRCQuant showed significant improvement in the number of accurately quantified peptides.</p> <p>Conclusions</p> <p>MRCQuant effectively addresses major issues in the relative quantification of LC-MS-based proteomics data, and it provides improved performance in the quantification of low abundance peptides.</p

Microstructure and mechanical properties of fibrin gels.

"This thesis reports an extensive study of the structural and rheological characteristics of the three-dimensional fibrin clot network. The importance of blood clotting in the area of NanoHealth is testified to by the fact that complications due to thrombosis accounts for about 10 per cent of all deaths in hospitals in the UK. It is therefore imperative to understand the clotting process of blood as fully as possible. The techniques implemented include confocal laser scanning microscopy, and rheo logical methods such as Fourier transform mechanical spectroscopy. Both techniques provide a foundation for performing a fractal analysis as a quantitative basis for defining, where appropriate, morphological/micro structural differentiation in clotting. Fractal analysis provides the framework for structural complexity and allows us to develop relationships between the structural features of blood clots and their rheological properties. The experimental methods involve following the mechanical properties of a gelling system up to and beyond the gel point. The mechanical (viscoelastic) properties of fibrin are significant and unique among polymers. Hence, they are essential to the physiology of blood clotting and vital for the understanding and therefore prevention and treatment of thrombosis. An unsatisfactory aspect of work in this area is that the micro structures of such clots are usually reported in only adjectival terms (e.g., "dense" or "tight") - usually on the basis of a visual inspection of fragments of desiccated clots in SEM micrographs. This work includes an extensive approach using confocal microscopy to visualise fibrin clot networks, with several forms of fractal analysis investigated for quantifying structural complexity. The present study is the first to report a modification of the fractal characteristics of incipient clots in fibrin-thrombin gels due to the availability of thrombin. This work confirms the hypothesis that the self-similar (fractal) stress relaxation behaviour recorded at the Gel Point of samples of coagulating blood (Evans et al., 2008) is associated with the micro structural characteristics of the incipient blood clot's fibrin network. It also supports the hypothesis that in various pathologies prothrombotic conditions can modify the underlying micro structure of a blood clot. The provision of a new technique capable of detecting the formation of altered clot microstructures at their incipient state could have significant clinical diagnostic potential e.g. in thromboembolic disease screening applications.

Metabolomics study of human embryonic stem cell culture media

Self-renewal and pluripotency, the hallmarks of human embryonic stem cells (hESC), confer these cells with the capacity to expand indefinitely while maintaining the ability to differentiate into any cell type of the human body; thus, making hESC a valuable source of functional differentiated cells suitable for applications in regenerative medicine, drug discovery, biotechnology, biopharmaceuticals and developmental biology. However, the large-scale production of clinical-grade hESC, required for such applications, has been hampered by the current culture conditions in which hESC still depend on the use of mouse embryonic fibroblast-conditioned medium (MEF-CM) for their efficient growth. Therefore, investigation of the factors provided by MEFs is of the utmost importance to discover which components of MEF-CM allow the long-term expansion of undifferentiated hESC. While considerable progress has been made on the identification of the protein components of MEF-CM, very little is known about the small molecules (metabolites) secreted by MEFs. In this context, an untargeted metabolomics method was developed for the investigation of potential bioactive metabolites present in MEF-CM implicated in the proliferation and/or maintenance of pluripotency of hESC in vitro. A metabolomics method was applied and successfully identified a number of metabolites which were later confirmed in their identities with the use of authentic standards, to be further investigated for their effect on hESC culture. Interestingly, the addition of PGE2, 6-keto-PGF1α, 9, 12, 13-TriHOME, 7-Ketocholesterol and stearidonic acid (the metabolites found in MEF-CM) to the unconditioned medium (UM), a medium incapable of the maintenance of hESC, showed a delay in apoptosis when compared to the negative control UM; thus, suggesting that these metabolites could help with the proliferation of hESC. Increasing evidence that hESC secrete factors into their microenvironment that can also help them to proliferate or to maintain an undifferentiated state prompted the application of the same metabolomics method to the analysis of hESC spent culture media. The results identified lysophospholipids (LPLs) as potential molecules mediating some biological activities; however, the precise role of these LPLs still remains to be determined. Overall, the results of this thesis are expected to impact and add knowledge to the field of stem cell biology providing useful information for the creation and development of more efficient and defined culture conditions for the propagation of hESC with the appropriate quality to realise their widespread application in clinic and other research areas

Advanced methods in fourier transform ion cyclotron resonance mass spectrometry

Mass spectrometry (MS) is a powerful analytical technique used to characterize various compounds by measuring the mass-to-charge ratio (m/z). Among different types of mass analyzers, Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) is the instrument of choice for those working at the forefront of research, as it offers incomparable mass accuracy, resolving power, and the highest flexibility for hybrid instrumentation and fragmentation techniques. The FT-ICR MS requires professional and careful tuning to achieve its superior performance. Our work aims to review, develop and apply advanced methods to improve the data quality of FT-ICR and push the limits of the instrument. FT-ICR spectrometry has been limited to the magnitude-mode for 40 years due to the complexity of the phase-wrapping problem. However, it is well known that by correcting phase of the data, the spectrum can be plotted in the absorption-mode with a mass resolving power that is as much as two times higher than conventional magnitude-mode. Based on the assumption that the frequency sweep excitation produces a quadratic accumulation in an ion’s phase value, a robust manual method to correct all ions’ phase shifts has been developed, which allows a broadband FT-ICR spectrum to be plotted in the absorption-mode. The developed phasing method has then been applied to a large variety of samples (peptides, proteins, crude oil), different spectral acquisition-mode (broadband, narrowband), and different design of ICR cells (Infinity cell, ParaCell) to compare the performance with the conventional magnitude-mode spectra. The outcome shows that, by plotting the absorption-mode spectrum, not only is the spectral quality improved at no extra cost, but the number of detectable peaks is also increased. Additionally, it has been found that artifactual peaks, such as noise or harmonics in the spectrum can be diagnosed immediately in the absorption-mode. Given the improved characteristics of the absorption-mode spectrum, the following research was then focused on a data processing procedure for phase correction and the features of the phase function. The results demonstrate that in the vast majority of cases, the phase function needs to be calculated just once, whenever the instrument is calibrated. In addition, an internal calibration method for calculating the phase function of spectra with insufficient peak density across the whole mass range has been developed. The above research is the basis of the Autophaser program which allows spectra recorded on any FT-ICR MS to be phase corrected in an automated manner

Practical Applications of NMR to Solve Real-World Problems

Nuclear magnetic resonance spectroscopy (NMR) has developed from primarily a method of academic study into a recognized technology that has advanced measurement capabilities within many different industrial sectors. These sectors include areas such as national security, energy, forensics, life sciences, pharmaceuticals, etc. Despite this diversity, these applications have many shared technical challenges and regulatory burdens, yet interdisciplinary cross-talk is often limited. To facilitate the sharing of knowledge, this Special Issue presents technical articles from four different areas, including the oil industry, nanostructured systems and materials, metabolomics, and biologics. These areas use NMR or magnetic resonance imaging (MRI) technologies that range from low-field relaxometry to magnetic fields as high as 700 MHz. Each article represents a practical application of NMR. A few articles are focused on basic research concepts, which will likely have the cross-cutting effect of advancing multiple disciplinary areas

Optimized GeLC-MS/MS for Bottom-Up Proteomics

Despite tremendous advances in mass spectrometry instrumentation and mass spectrometry-based methodologies, global protein profiling of organellar, cellular, tissue and body fluid proteomes in different organisms remains a challenging task due to the complexity of the samples and the wide dynamic range of protein concentrations. In addition, large amounts of produced data make result exploitation difficult. To overcome these issues, further advances in sample preparation, mass spectrometry instrumentation as well as data processing and data analysis are required. The presented study focuses as first on the improvement of the proteolytic digestion of proteins in in-gel based proteomic approach (Gel-LCMS). To this end commonly used bovine trypsin (BT) was modified with oligosaccharides in order to overcome its main disadvantages, such as weak thermostability and fast autolysis at basic pH. Glycosylated trypsin derivates maintained their cleavage specifity and showed better thermostability, autolysis resistance and less autolytic background than unmodified BT. In line with the “accelerated digestion protocol” (ADP) previously established in our laboratory modified enzymes were tested in in-gel digestion of proteins. Kinetics of in-gel digestion was studied by MALDI TOF mass spectrometry using 18O-labeled peptides as internal standards as well as by label-free quantification approach, which utilizes intensities of peptide ions detected by nanoLC-MS/MS. In the performed kinetic study the effect of temperature, enzyme concentration and digestion time on the yield of digestion products was characterized. The obtained results showed that in-gel digestion of proteins by glycosylated trypsin conjugates was less efficient compared to the conventional digestion (CD) and achieved maximal 50 to 70% of CD yield, suggesting that the attached sugar molecules limit free diffusion of the modified trypsins into the polyacrylamide gel pores. Nevertheless, these thermostable and autolysis resistant enzymes can be regarded as promising candidates for gel-free shotgun approach. To address the reliability issue of proteomic data I further focused on protein identifications with borderline statistical confidence produced by database searching. These hits are typically produced by matching a few marginal quality MS/MS spectra to database peptide sequences and represent a significant bottleneck in proteomics. A method was developed for rapid validation of borderline hits, which takes advantage of the independent interpretation of the acquired tandem mass spectra by de novo sequencing software PepNovo followed by mass-spectrometry driven BLAST (MS BLAST) sequence similarity searching that utilize all partially accurate, degenerate and redundant proposed peptide sequences. It was demonstrated that a combination of MASCOT software, de novo sequencing software PepNovo and MS BLAST, bundled by a simple scripted interface, enabled rapid and efficient validation of a large number of borderline hits, produced by matching of one or two MS/MS spectra with marginal statistical significance

Metabolomics study of human embryonic stem cell culture media

Self-renewal and pluripotency, the hallmarks of human embryonic stem cells (hESC), confer these cells with the capacity to expand indefinitely while maintaining the ability to differentiate into any cell type of the human body; thus, making hESC a valuable source of functional differentiated cells suitable for applications in regenerative medicine, drug discovery, biotechnology, biopharmaceuticals and developmental biology. However, the large-scale production of clinical-grade hESC, required for such applications, has been hampered by the current culture conditions in which hESC still depend on the use of mouse embryonic fibroblast-conditioned medium (MEF-CM) for their efficient growth. Therefore, investigation of the factors provided by MEFs is of the utmost importance to discover which components of MEF-CM allow the long-term expansion of undifferentiated hESC. While considerable progress has been made on the identification of the protein components of MEF-CM, very little is known about the small molecules (metabolites) secreted by MEFs. In this context, an untargeted metabolomics method was developed for the investigation of potential bioactive metabolites present in MEF-CM implicated in the proliferation and/or maintenance of pluripotency of hESC in vitro. A metabolomics method was applied and successfully identified a number of metabolites which were later confirmed in their identities with the use of authentic standards, to be further investigated for their effect on hESC culture. Interestingly, the addition of PGE2, 6-keto-PGF1α, 9, 12, 13-TriHOME, 7-Ketocholesterol and stearidonic acid (the metabolites found in MEF-CM) to the unconditioned medium (UM), a medium incapable of the maintenance of hESC, showed a delay in apoptosis when compared to the negative control UM; thus, suggesting that these metabolites could help with the proliferation of hESC. Increasing evidence that hESC secrete factors into their microenvironment that can also help them to proliferate or to maintain an undifferentiated state prompted the application of the same metabolomics method to the analysis of hESC spent culture media. The results identified lysophospholipids (LPLs) as potential molecules mediating some biological activities; however, the precise role of these LPLs still remains to be determined. Overall, the results of this thesis are expected to impact and add knowledge to the field of stem cell biology providing useful information for the creation and development of more efficient and defined culture conditions for the propagation of hESC with the appropriate quality to realise their widespread application in clinic and other research areas

A systems biology approach to musculoskeletal tissue engineering: transcriptomic and proteomic analysis of cartilage and tendon cells

Disorders of cartilage and tendon account for a high incidence of disability and are highly prevalent co-morbidities within the ageing population; therefore, musculoskeletal disorders represent a major public health policy issue. Despite considerable efforts to characterise biochemical and biomechanical cues that promote a stable differentiated cartilage or tendon phenotype in vitro the benchmarks by which progress is measured are limited. Common regenerative interventions, such as autologous cartilage implantation, have a required period of monolayer expansion that induces a loss of the functional phenotype, termed dedifferentiation. Dedifferentiation has no definitive mechanism yet is widely described in both regenerative and degenerative contexts; in addition to stem cell transplantation and cell-seeding in three-dimensional scaffolds, dedifferentiation represents the third approach to the development of regenerative mechanisms for mammalian tissue repair. Cartilage and tendon show a number of common features in structure, develop, disease, and repair. The extracellular matrix is a dynamic and complex structure that confers the functional mechanical properties of cartilage and tendon. Dysregulation of production and degradation are critical to the pathophysiology of musculoskeletal disorders, therefore, reparative interventions require a stable, functional phenotype from the outset. Cartilage and tendon demonstrate a commonality in terms of function defining structure both being sparsely cellular with a preponderance of collagenous matrix. Parity of functionality with the pre- injury state after healing is rarely achieved for cartilage and tendon. Cartilage and  tendon also share common embryological origins. Common mesenchymal progenitor cells differentiate into many musculoskeletal tissues with diverse functions. Specialist sub-populations of tendon and cartilage progenitors enable formation of transitional zones between these developing tissues. The development of musculoskeletal structures does not occur in isolation, however, cartilage and tendon have not previously been considered together in a systems context. An integrated understanding of the differentiation of these tissues should inform regenerative therapies and tissue engineering strategies. Systems biology is paradigm shift in scientific thinking where traditional reductionist strategies to complex biological problems have been superseded by a holistic philosophy seeking to understand the emergent behavior of a system by the integrative and predictive modeling of all elements of that system. Whole transcriptome and proteome profiling studies are used to collect quantitative data about a system, which may then be exploited by systems biology methodologies including the analysis of gene and protein networks. Gene-gene co-expression relationships, which are core regulatory mechanisms in biology, are often not part of a comprehensive gene expression analysis. Many biological networks are sparse and have a scale-free topology, which generally indicates that the majority of genes have very few connections, whilst certain key regulators, or ‘hubs’, are highly interconnected. Co-expression networks may be used to define regulatory sub- networks and ‘hubs’ that have phenotypic associations. This approach allows all quantitative data to be used and makes no a priori assumptions about relationships in the system and, therefore, can facilitate the exploration of emergent behavior in the system and the generation of novel hypotheses. The ultimate goal of tissue engineering is the replacement of lost or damaged cells, and in vitro, to develop biomimetic (organotypic) structures to serve as experimental models. Tissues, and the strategies to functionally replicate them ex vivo, are complex and require an integrated, multi-disciplinary approach. Systems biology approaches, using data arising from multiple-levels of the biological hierarchy, can facilitate the development of predictive models for bioengineered tissue. The iterative refinement, quantification, and perturbation of these models may expedite the translation of well-validated organotypic systems, through legal regulatory frameworks, into regenerative strategies for musculoskeletal disorders in humans. In this thesis the systems under consideration are the major cell populations of cartilage and tendon (chondrocytes and tenocytes, respectively). They are described in three environmental conditions: native tissue, monolayer (two- dimensional), or three-dimensional models. There has been no systematic investigate of the global gene and protein profiles of cartilage and tendon in their native state relative to monolayer or three-dimensional cultures. There is no clear mechanistic description of the impact of in vitro environmental perturbations on the system or indeed the adequacy of these models as proxies for cartilage and tendon. A discovery approach using transcriptomic and proteomic profiling is undertaken to define a robust and consistent gene and protein profile for each condition. Differentially expressed elements are functionally annotated and pathway topology approaches employed to predict major signalling pathways associated with the observed phenotype. This study defines dedifferentiated chondrocytes and tenocytes in monolayer culture as expressing markers of musculoskeletal development, including scleraxis (Scx) and Mohawk (Mkx). Furthermore, there is reproducible synthetic profile convergence in monolayer culture between cartilage and tendon cells. Standard three-dimensional culture systems for chondrocyte and tenocytes fail to replicate the gene expression profile of cartilage and tendon. The PI-3K/Akt signaling pathway is predicted to be the predominant canonical pathway associated with de- and re-differentiation in vitro. Using novel, and publically available, transcriptomic data sets a meta-analysis of microarray gene expression profiles is performed using weighted gene co- expression network analysis. This is employed for transcriptome network decomposition to isolate highly correlated and interconnected gene-sets (modules) from gene expression profiles of cartilage and tendon cells in different environmental conditions. Sub-networks strongly associated with de- and re- differentiation phenotypes are defined. Comparison of global transcriptome network architecture was performed to define the conservation of network modules between a model species (rat) and human data. In addition to the annotation of an osteoarthritis-associated module in the rat a class-prediction analysis defined a minimal gene signature for the prediction of three-dimensional cultures from standard monolayer culture. Finally, proteomic and transcriptomic data sets are integrated by defining common upstream regulators (TGFB and PDGF BB) and unified mechanistic networks are generated for de- and re- differentiation. The studies collected in this thesis contribute to a wider understanding of cartilage and tendon tissue engineering and organotypic culture development. A clear mechanistic understanding of the regulatory networks controlling differentiation of cartilage and tendon progenitor cells is required in order to develop improved in vitro models and bio-engineered tissue that are physiologically relevant. The findings presented here provide practical outputs and testable hypotheses to drive future evidence-based research in organotypic culture development for musculoskeletal tissues

PTH1R Signaling in Osteoblasts Stimulated with Functionally Selective Ligands: Phosphoproteomics Reveals Unique Signaling Networks

The past 20 years have seen G-protein coupled receptor (GPCR) theory advance significantly. Receptors are now thought of as adopting multiple conformations in a state of dynamic equilibrium. The study of GPCR biased agonism has emerged from this changing concept of receptors and introduced the field to “pluridimensional efficacy.” It is thought that a single readout of efficacy is no longer sufficient and multiple parameters of efficacy must be measured in drug screens to improve the ability to predict in vivo effects. While several GPCRs have multiple cognate ligands that elicit functionally-selective responses, the present study focused on biased signaling of the parathyroid hormone receptor (PTH1R). Parathyroid hormone (PTH) maintains serum calcium and is a key regulator of bone remodeling. Human PTH1-34 (Forteo) is the only FDA approved drug used for treatment of osteoporosis that acts via its anabolic actions on osteoblasts. However, the therapeutic utilization of PTH1-34 is limited by its catabolic effects, mediated in part by protein kinase A, which after two years culminate in net bone resporption through the activation of osteoclasts by RANKL. The experimental, biased ligand of the PTH1R, bovine parathyroid hormone residues 7-34 with D-Trp12 and Tyr34 (bPTH(7-34)), does not exhibit the catabolic effects of PTH1-34. In vivo administration of the conventional ligand, PTH 1-34, and the biased ligand, bPTH(7-34), for eight weeks increased bone mineral density (BMD) in mice. The anabolic effect of bPTH(7-34) in vivo was lost in β-arrestin deficient mice, revealing a dependence on β-arrestin mediated signaling. Further analysis of osteoblast and osteoclast number, transcript expression, and the generation of second messengers revealed the anabolic effect of each ligand was achieved by different mechanisms. To elucidate the unique, proximal signaling events activated by acute stimulation of the PTH1R with the biased agonist, this study focused on characterization and comparison of the phosphorylation-mediated signaling profiles of osteoblasts stimulated with each osteogenic agonist. Relative changes in phosphorylation were measured using a SILAC-based phosphoproteomic screen following acute stimulation of MC3T3- E1 preosteoblast cells with hPTH(1-34) or bPTH(7-34) for 5 minutes. The experiments were performed in proliferating preosteoblasts (Day 0) and differentiating osteoblasts (Day 10). Over ten thousand sites of phosphorylation were observed. Regulated phosphosites and phosphoproteins were examined for putative kinase activity, targeted signaling pathways, and biological processes. Differences were observed in the kinases stimulated by each agonist. For example, bPTH(7-34) treatment activated MAPK1 and increased phosphorylation of downstream substrates, while phosphorylation of predicted MAPK1 substrates were decreased with hPTH(1-34) activation. While both drugs regulated phosphorylation of proteins in signaling pathways involving GPCR signaling (PLC, MTOR, Rho GTPases); Ingenuity Pathway Analysis (IPA) also revealed discrete signaling networks engaged by each drug. PTH (1-34) treatment yielded regulated proteins involved in cytoskeletal dynamics and the Wnt/β- catenin pathway, whereas bPTH(7-34) treatment modulated pathways related to survival (ATM, CDKs, and p70S6K) and transcription (Jak/Stat, and PPARα). Cell-based assays confirmed hPTH(1-34) and bPTH(7-34) both confer resistance to etoposide-induced apoptosis and bPTH(7-34) increases proliferation in MC3T3-E1 cells. At the biological process level, both ligands modulated proteins involved in cell survival, migration, growth, and bone metabolism. Comparison of regulated phosphoproteins at two time points during osteogenic differentiation unexpectedly revealed that the bPTH(7-34) gave a more robust effect in proliferating preosteoblasts, whereas hPTH(1-34) stimulated more sites of phosphorylation in differentiating osteoblasts. This observation indicates the differential effects of each agonist may result from changes in signaling mediators that are expressed at these two time points. While the PTH receptor was present at both time points, β-arrestin was more highly expressed in proliferating preosteoblasts

Design, Optimization and Syntheses of Small Molecules to Disrupt Protein-Protein Interactions

Protein-protein interactions (PPIs) are one of the basic mechanisms in cellular biology, but also involve in diseases if they are dysregulation. Disrupting aberrant PPI activities is useful in medicinal chemistry. One approach to inhibit PPIs is to design small molecule peptidomimetics bearing side-chain orientations similar to protein ligands, in which those mimics might displace or interfere the native PPIs. Previous research in our group developed Exploring Key Orientations (EKO) program that matches Cɑ-Cß coordinates of virtual small molecules to the side-chain vectors of proteins at PPI interfaces. Similar Cɑ-Cß orientations between mimics and protein ligands indicate that small molecules might be suitable to displace protein ligands, i.e. those compounds might interfere PPIs. We used EKO to deduce small molecules that might disrupt medicinally-relevant PPIs. Herein, EKO implicated our designed mimics, hydantoin-oxazoline, triazole-oxazole and triazole-oxazoline derivatives, might disrupt Nef•MHC-I•AP1 and NEDD8•NAE interactions, in which they are relevant to HIV-1 and cancer diseases respectively. After learning from these projects, we designed hydantoin-piperazine analogues to disrupt PCSK9•LDLR interaction that causes hypercholesterolemia disease. Although the firstgeneration hydantoin-piperazine derivatives did not show good PCSK9•LDLR inhibition, we modified chemotype structures by cooperating with a docking program, Glide, to improve inhibitory potencies. As a result, we successfully obtained lead compounds that significantly disrupt PCSK9•LDLR interaction with the measurable binding affinities. Besides these protein targets, we synthesized another minimalist mimic, oxazoline piperidine-2,4-dione, that has conformational biases toward helical and sheet-turn-sheet motifs. This structure potentially has favorable cellular- and oral-permeability calculated by QikProp. We are also interested in how to design molecules suitable for PPI inhibition. A concept of secondary structure mimicry is widely applied to design molecules that resemble a secondary structure at an PPI interface, hence possibly disrupt protein-protein interaction. However, there is no direct study to prove a correlation between secondary structure mimicry and interface mimicry. To respond this issue, we used EKO to match several new chemotypes on the ideal secondary structures and PPIs database, and then compared the frequencies of secondary structures that chemotypes matched at PPI interfaces to the ideal secondary structure biases of each chemotype. We found that, in general, good secondary structure mimics tend to match frequently at PPI interfaces; however, they mostly match on non-ideal secondary structure motifs