Browsing by Subject "Mass spectrometry"

The primary goals of this study were to demonstrate and fully characterize a microscale ionization source (i.e. micro-ion source) and to determine the validity of impact ionization theory for microscale devices and pressures up to 100 mTorr. The field emission properties of carbon nanotubes (CNTs) along with Micro-Electro-Mechanical Systems (MEMS) design processes were used to achieve these goals. Microwave Plasma-enhanced CVD was used to grow vertically aligned Multi-Walled Carbon Nanotubes (MWNTs) on the microscale devices. A 4-dimensional parametric study focusing on CNT growth parameters confirmed that Fe catalyst thickness had a strong effect on MWNT diameter. The MWNT growth rate was seen to be a strong function of the methane-to-ammonia gas ratio during MWNT growth. A high methane-to-ammonia gas ratio was selected for MWNT growth on the MEMS devices in order to minimize growth time and ensure that the thermal budget of those devices was met.

A CNT-enabled microtriode device was fabricated and characterized. A new aspect of this device was the inclusion of a 10 micron-thick silicon dioxide electrical isolation layer. This thick oxide layer enabled anode current saturation and performance improvements such as an increase in dc amplification factor from 27 to 600. The same 3-panel device was also used as an ionization source. Ion currents were measured in the 3-panel micro-ion source for helium, argon, nitrogen and xenon in the 0.1 to 100 mTorr pressure range. A linear increase in ion current was observed for an increase in pressure. However, simulations indicated that the 3-panel design could be modified to improve performance as well as better understand device behavior. Thus, simulations and literature reports on electron impact ionization sources were used to design a new 4-panel micro-ion source. The 4-panel micro-ion source showed an approximate 10-fold performance improvement compared to the 3-panel ion source device. The improvement was attributed to the increased electron current and improved ion collection efficiency of the 4-panel device. Further, the same device was also operated in a 3-panel mode and showed superior performance compared to the original 3-panel device, mainly because of increased ion collection efficiency.

The effect of voltages applied to the different electrodes in the 4-panel micro-ion source on ion source performance was studied to better understand device behavior. The validity of the ion current equation (which was developed for macroscale ion sources operating at low pressures) in the 4-panel micro-ion source was studied. Experimental ion currents were measured for helium, argon and xenon in the 3 to 100 mTorr pressure range. For comparison, theoretical ion currents were calculated using the ion current equation for the 4-panel micro-ion source utilizing values calculated from SIMION simulations and measured electron currents. The measured ion current values in the 3 to 20 mTorr pressure range followed the calculated ion currents quite closely. A significant deviation was observed in the 20-100 mTorr pressure range. The experimental ion current values were used to develop a corrected empirical model for the 4-panel micro-ion source in this high pressure range (i.e., 3 to 100 mTorr). The role of secondary electrons and electron path lengths at higher pressures is discussed.

Mass spectrometry is widely considered to be the gold standard of elemental analysis techniques due to its ability to resolve atomic and molecular and biological species. Expanding the application space of mass spectrometry often requires the need for portable or hand-held systems for use in field work or harsh environments. While only requiring “sufficient” mass resolution to meet the needs of their application space, these miniaturized systems suffer from poor signal to background ratio which limits their sensitivity as well as their usefulness in field applications.

Spatial aperture coding techniques have been used in optical spectroscopy to achieve large increases in signal intensity without compromising system resolution. In this work similar computational methods are used in the application of these techniques to the field of magnetic sector mass spectrometry. Gains in signal intensity of 10x and 4x were achieved for 1D and 2D coding techniques (respectively) using a simple 90 degree magnetic sector test setup. Initial compatibility with a higher mass resolution double focusing Mattauch-Herzog mass spectrograph is demonstrated experimentally and with high fidelity particle tracing simulations. A novel electric sector lens system was designed to stigmate high order coded aperture patterned beam which shows simulated gains in signal intensity of 50x are achievable using these techniques.

Conventional mass spectrometry sensing has isomorphic nature, which means measure the input mass spectrum abundance function by a resemble of delta function to avoid ambiguity. However, the delta function nature of traditional mass spectrometry sensing approach imposes trade-offs between mass resolution and throughput/mass analysis time. This dissertation proposes a new field of mass spectrometry sensing which combines both computational signal processing and hardware modification to break the above trade-offs. We introduce the concept of generalized sensing matrix/discretized forward model in mass spectrometry filed. The presence of forward model can bridge the cap between sensing system hardware design and computational sensing algorithm including compressive sensing, feature/variable selection machine learning algorithms, and stat-of-art inversion algorithms.

Throughout this dissertation, the main theme is the sensing matrix/forward model design subject to the physical constraints of varies types of mass analyzers. For quadrupole ion trap systems, we develop a new compressive and multiplexed mass analysis approach mutli Resonant Frequency Excitation (mRFE) ejection which can reduce mass analysis time by a factor 3-6 without losing mass spectra specificity for chemical classification. A new information-theoretical adaptive sensing and classification framework has proposed on quadrupole mass filter systems, and it can significantly reduces the number of measurements needed and achieve a high level of classification accuracy. Furthermore, we present a coded aperture sector mass spectrometry which can yield a order-of-magnitude throughput gain without compromising mass resolution compare to conventional single slit sector mass spectrometer.

Carbon nanotubes (CNTs) have recently emerged as promising candidates for electron field emission (FE) cathodes in integrated FE devices. These nanostructured carbon materials possess exceptional properties and their synthesis can be thoroughly controlled. Their integration into advanced electronic devices, including not only FE cathodes, but sensors, energy storage devices, and circuit components, has seen rapid growth in recent years. The results of the studies presented here demonstrate that the CNT field emitter is an excellent candidate for next generation vacuum microelectronics and related electron emission devices in several advanced applications.

The work presented in this study addresses determining factors that currently confine the performance and application of CNT-FE devices. Characterization studies and improvements to the FE properties of CNTs, along with Micro-Electro-Mechanical Systems (MEMS) design and fabrication, were utilized in achieving these goals. Important performance limiting parameters, including emitter lifetime and failure from poor substrate adhesion, are examined. The compatibility and integration of CNT emitters with the governing MEMS substrate (i.e., polycrystalline silicon), and its impact on these performance limiting parameters, are reported. CNT growth mechanisms and kinetics were investigated and compared to silicon (100) to improve the design of CNT emitter integrated MEMS based electronic devices, specifically in vacuum microelectronic device (VMD) applications.

Improved growth allowed for design and development of novel cold-cathode FE devices utilizing CNT field emitters. A chemical ionization (CI) source based on a CNT-FE electron source was developed and evaluated in a commercial desktop mass spectrometer for explosives trace detection. This work demonstrated the first reported use of a CNT-based ion source capable of collecting CI mass spectra. The CNT-FE source demonstrated low power requirements, pulsing capabilities, and average lifetimes of over 320 hours when operated in constant emission mode under elevated pressures, without sacrificing performance. Additionally, a novel packaged ion source for miniature mass spectrometer applications using CNT emitters, a MEMS based Nier-type geometry, and a Low Temperature Cofired Ceramic (LTCC) 3D scaffold with integrated ion optics were developed and characterized. While previous research has shown other devices capable of collecting ion currents on chip, this LTCC packaged MEMS micro-ion source demonstrated improvements in energy and angular dispersion as well as the ability to direct the ions out of the packaged source and towards a mass analyzer. Simulations and experimental design, fabrication, and characterization were used to make these improvements.

Finally, novel CNT-FE devices were developed to investigate their potential to perform as active circuit elements in VMD circuits. Difficulty integrating devices at micron-scales has hindered the use of vacuum electronic devices in integrated circuits, despite the unique advantages they offer in select applications. Using a combination of particle trajectory simulation and experimental characterization, device performance in an integrated platform was investigated. Solutions to the difficulties in operating multiple devices in close proximity and enhancing electron transmission (i.e., reducing grid loss) are explored in detail. A systematic and iterative process was used to develop isolation structures that reduced crosstalk between neighboring devices from 15% on average, to nearly zero. Innovative geometries and a new operational mode reduced grid loss by nearly threefold, thereby improving transmission of the emitted cathode current to the anode from 25% in initial designs to 70% on average. These performance enhancements are important enablers for larger scale integration and for the realization of complex vacuum microelectronic circuits.

In the past decade, several mass spectrometry-based proteomic techniques have been developed for the large-scale analysis of protein folding stabilities. The main focus of this dissertation is to develop and apply these large-scale protein folding stability approaches in drug target identification and disease biomarker discovery. One goal of this work is to develop a novel chemo-selection strategy to improve the bottom-up proteomics readout in proteome-wide limited proteolysis experiments. Another goal of this work is to apply these methods to the target identification of two drugs with known mode of action, and to the biomarker discovery of Parkinson’s disease.

Described in the first part of the dissertation is the development of a chemo-selective enrichment strategy to isolate the semi-tryptic peptides generated in mass spectrometry-based applications of limited proteolysis methods. The method is termed Semi-Tryptic Peptide Enrichment Strategy for Proteolysis Procedures (STEPP). The STEPP-PP workflow was evaluated in two proof-of-principle drug target identification experiments involving two well-studied drugs, cyclosporin A and geldanamycin. The STEPP-LiP workflow was evaluated in one proof-of-principle experiment on identification of protein conformational changes between a breast cancer cell line, MCF-7, and a normal cell line, MCF-10A. The STEPP protocol increased the number of semitryptic peptides detected in the LiP and PP experiments by 5- to 10-fold. The STEPP protocol not only increases the proteomic coverage, but also increases the amount of structural information that can be gleaned from limited proteolysis experiments. Moreover, the protocol also enables the quantitative determination of ligand binding affinities. When coupled to a one-pot data acquisition strategy, the one-pot STEPP-PP technique was found to have a very low false positive rate (i.e., 0.09%) in a proof-of-principle drug target identification experiments involving cyclosporin A and a yeast lysate.

The second part of this dissertation describes the application of protein folding stability approaches to the identification of protein targets of subglutinol A (a natural immunosuppressant) and manassantin A (a natural product with anti-cancer activity).

In the suglutinol A study, a combination of SPROX, TPP, CPP and STEPP-PP strategies was used to identified two consistent protein hits, deoxycytidine kinase (DCK) and exportin-2 (XPO2), from more than 2000 assayed proteins in a 2B4T cell lysate. The binding of DCK with subglutinol A was validated using a targeted gel-based pulse proteolysis experiment. A set of chemical biology experiments were performed to uncover the relation of this interaction with subglutinol A’s mode of action. It was shown that neither of the kinase activity, expression level or phosphorylation modification level of DCK was alternated by subglutinol A. However, the nuclear transportation of DCK was blocked by subgltutinol A. This reduction of DCK level in the cell nucleus possibly leads to the observed reduction of nuclear dCMP pool and the halted proliferation of sublgutinol A treated T cells.

In the manassantin A study, a combination of STEPP-LiP, STEPP-PP, one-pot STEPP-PP, one-pot SPROX and one-pot TPP strategies were performed to identify the protein target of the drug in a hypoxia-treated HEK293T cell lysate. These experiments assayed over 4000 proteins and found 4 protein hits for further validation of their interaction with manassantin A.

The third part of describes the utilization of the SPROX method to characterize the progression of PD in a mouse model of the disease in which the human α-synuclein protein with an A53T mutation was overexpressed. The thermodynamic stabilities of proteins in brain tissue cell lysates from Huα-Syn(A53T) transgenic mice were profiled at three time points including at 1 Month (n=9), at 6 Months (n=7), and at the time (between 9 and 16 Months) a mouse became Symptomatic (n=8). The thermodynamic stability profiles generated here on over 300 proteins were compared to the thermodynamic stability profiles generated on the same proteins from similarly aged wild-type mice using a two-way ANOVA analysis. A group of 22 proteins were identified with age-related protein stability changes, and a group of 11 proteins were found to be differential stabilized in the Huα-Syn(A53T) transgenic mouse model. The proteins differentially stabilized in the disease mouse model could potentially be used as Parkinson’s disease biomarkers upon further validation.

Many of the biological roles of proteins are modulated through protein-ligand interactions, making proteins important targets for drug therapies and diagnostic imaging probes. The discovery of novel ligands for a protein of interest often relies on the use of high throughput screening (HTS) technologies designed to detect protein-ligand binding. The basis of one such technology is a recently reported mass spectrometry-based assay termed SUPREX (stability of unpurified proteins from rates of H/D exchange). SUPREX is a technique that uses H/D exchange and MALDI-mass spectrometry for the measurement of protein stabilities and protein-ligand binding affinities. The single-point SUPREX assay is an abbreviated form of SUPREX that is capable of detecting protein-ligand interactions in a high throughput manner by exploiting the change in protein stability that occurs upon ligand binding.

This work is focused on the development and application of high throughput SUPREX protocols for the detection of protein-ligand binding. The first step in this process was to explore the scope of SUPREX for the analysis of non-two-state proteins to determine whether this large subset of proteins would be amenable to SUPREX analyses. Studies conducted on two model proteins, Bcl-xL and alanine:glyoxylate aminotransferase, indicate that SUPREX can be used to detect and quantify the strength of protein-ligand binding interactions in non-two-state proteins.

The throughput and efficiency of a high throughput SUPREX protocol (i.e., single-point SUPREX) was also evaluated in this work. As part of this evaluation, cyclophilin A, a protein target of diagnostic and therapeutic significance, was screened against the 880-member Prestwick Chemical Library to identify novel ligands that might be useful as therapeutics or imaging agents for lung cancer. This screening not only established the analytical parameters of the assay, but it revealed a limitation of the technique: the efficiency of the assay is highly dependent on the precision of each mass measurement, which generally decreases as protein size increases.

To overcome this limitation and improve the efficiency and generality of the assay, a new SUPREX protocol was developed that incorporated a protease digestion step into the single-point SUPREX protocol. This new protocol was tested on two model proteins, cyclophilin A and alanine:glyoxylate aminotransferase, and was found to result in a significant improvement in the efficiency of the SUPREX assay in HTS applications. This body of work resulted in advancements in the use of SUPREX for high throughput applications and laid the groundwork for future HTS campaigns on target proteins of medical significance.

The identification and quantification of protein-protein interactions in large scale is critical to understanding biological processes at a systems level. Current approaches for the analysis of protein -protein interactions are generally not quantitative and largely limited to certain types of interactions such as binary and strong binding interactions. They also have high false-positive and false-negative rates. Described here is the development of and application of mass spectrometry-based proteomics metehods to detect and quantify the strength of protein-protein and protein-ligand interactions in the context of their interaction networks. Characterization of protein-protein and protein-ligand interactions can directly benefit diseased state analyses and drug discovery efforts.

The methodologies and protocols developed and applied in this work are all related to the Stability of Unpurified Proteins from Rates of amide H/D Exchange (SUPREX) and Stability of Protein from Rates of Oxidation (SPROX) techniques, which have been previously established for the thermodynamic analysis of protein folding reactions and protein-ligand binding interactions. The work in this thesis is comprised of four parts. Part I involves the development of a Histidine Slow H/D exchange protocol to facility SURPEX-like measurements on the proteomic scale. The Histidine Slow H/D exchange protocol is developed in the context of selected model protein systems and used to investigate the thermodynamic properties of proteins in a yeast cell lysate.

In Part II an isobaric mass tagging strategy is used in combination with SPROX (i.e., a so-called iTRAQ-SPROX protocol) is used to characterize the altered protein interactions networks associated with lung cancer. This work involved differential thermodynamic analyses on the proteins in two different cell lines, including ADLC-5M2 and ADLC-5M2-C2.

Parts III and IV of this thesis describe the development and application of a SPROX protocol for proteome-wide thermodynamic analyses that involves the use of Stable Isotope Labeling by Amino acid in cell Culture (SILAC) quantitation. A solution-based SILAC-SPROX protocol is described in Part III and a SILAC-SPROX protocol involving the use of cyanogen bromide and a gel-based fractionation step is described in Part IV. The SILAC-SPROX-Cyanogen bromide (SILAC-SPROX-CnBr) protocol is demonstrated to significantly improve the peptide and protein coverage in proteome-wide SPROX experiments. Both the SILAC-SPROX and SILAC-SPROX-CnBr porotocols were used to characterize the ATP binding properties of yeast proteins. Ultimately, the two protocols enabled 526 yeast proteins to be assayed for binding to AMP-PNP, an ATP mimic. A total of 140 proteins, including 37 known ATP-binding proteins, were found to have ATP binding interactions.

Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.

The direct link between a protein’s thermodynamic stability and function influenced the development of mass spectrometry-based methods to characterize the energetics associated with protein folding that enabled the large-scale elucidation of drug protein targets and disease state protein biomarkers. This area of structural biology is undergoing constant development and new applications are emerging. Consequently, the original contributions of this dissertation include (1) the continuation or extension of mass spectrometry and energetic-based strategies for proteome-wide characterization of protein folding stabilities in allergen-containing proteomes to discriminate allergenicity, (2) the hybridization of novel strategies with existing energetic-based approaches utilizing mass spectrometry readout for simpler and efficient characterization of protein folding stabilities and ligand binding, and (3) the development of novel mass spectrometry-based strategies for comprehensive evaluations of the thermodynamics and kinetics of protein folding.First, this dissertation describes comprehensive protein profiling methods to discriminate allergens from non-allergens. As continuation, RNA sequencing (RNA-seq) analysis served as a proxy for protein abundance, and the Stability of Proteins from Rates of Oxidation (SPROX) reported on thermodynamic stability. These techniques characterized the protein expression levels and stability of proteins in the European white birch pollen, Betula pendula (Bp), and German cockroach, Blattella germanica (Bg). The simultaneous comparison of stability and abundance confirmed that Bp and Bg allergens had significantly higher expression levels and higher stabilities compared to non-allergens from the same source. Combining the Bp and Bg results with previous studies for a robust statistical comparison of the abundance and stability of allergens and non-allergens from indoor and outdoor sources confirmed that allergens were significantly more abundant and more stable. The thermodynamic stability of the proteins in Bp was further investigated utilizing a denaturant-dependent Pulse Proteolysis (PP) strategy with thermolysin. Additionally, proteolytic susceptibility was assessed by employing a time-dependent cathepsin S digestion under native conditions. The results confirmed that allergens were significantly less susceptible to thermolysin (more thermodynamically stable) or cathepsin S digestion than the non-allergens in Bp. Additionally, no correlation resulted between the SPROX- and PP-derived thermodynamic stabilities and between the thermodynamic stabilities and proteolytic susceptibilities of selected proteins from Bp. The absence of correlation is attributed to the fundamental differences between techniques—each technique utilizes distinct probes to report on a protein’s thermodynamic stability and/or proteolytic susceptibility. Finally, the PP-derived stability for the major Bp allergen, Bet v 1, correlated with the LiP-derived proteolytic susceptibility and the generation of known T-cell epitopes connecting stability with endosomal processing having allergenic or immunogenic implications. Next, this dissertation reports the first application of the novel one-pot analysis in conjunction with the SPROX methodology for a simplified and efficient evaluation of protein folding and ligand-binding. A hybrid of the one-pot analysis with SPROX utilizing a MALDI readout enabled efficient evaluations of protein stability and ligand binding. The approach generated protein folding stabilities with similar precision to the standard curve-fitting SPROX technique. Furthermore, the one-pot analysis was coupled with the SPROX strategy for a comprehensive deconvolution of Cyclosporine A (CsA) protein targets in yeast. This novel approach identified 3 known CsA protein hits with a 0.04% false positive rate. A cross-validation between techniques (i.e., TPP, CPP, or PP, performed under similar conditions) resulted in false positive rates approaching 0 %. Finally, this dissertation showcases the development of a novel approach utilizing a native or low denaturant-based Reagent-dependent Thiolate-based Reactivity (RTR) assay utilizing mass spectrometry for the evaluation of the thermodynamics and kinetics of protein folding. An RTR strategy titled MTR utilizing a MALDI readout was performed under native conditions to report on the thermodynamics of protein folding. The MTR strategy measured the thermodynamic stability of mutants of the C domain of protein A from Staphylococcus aureus. Additionally, a low denaturant MTR approach reported the thermodynamics and kinetics of protein folding for bovine β-lactoglobulin B (LG-B). A comprehensive application of the native RTR approach was performed on yeast providing thermodynamic stability information for a subset of the proteins.

Proteins fold into well-defined three-dimensional structures to carry out their biological functions which involve non-covalent interactions with other cellular molecules. Knowledge about the thermodynamic properties of proteins and protein-ligand complexes is essential for answering fundamental biological questions and drug or biomarker discovery. Recently, chemical labeling strategies have been combined with mass spectrometry methods to generate thermodynamic information about protein folding and ligand binding interactions. The work in this thesis is focused on the development and application of two such chemical labeling protocols coupled with mass spectrometry including one termed, SUPREX (stability of unpurified proteins from rates of H/D exchange), and one termed SPROX (stability of proteins from rates of oxidation). The work described in this thesis is divided into two parts. The first part involves the application of SUPREX to the thermodynamic analysis of a protein folding chaperone, Hsp33, and its interaction with unfolded protein substrates. The second part involves the development of a new chemical labeling protocol that can be used to make protein folding and ligand binding measurements on the proteomic scale.

In the first part of this work, the SUPREX technique was used to study the binding interaction between the molecular chaperone Hsp33 and four different unfolded protein substrates including citrate synthase, lactate dehydrogenase, malate dehydrogenase, and aldolase. The results of the studies, which were performed at the intact protein level, suggest that the cooperativity of the Hsp33 folding/unfolding reaction increases upon binding with denatured protein substrates. This is consistent with the burial of significant hydrophobic surface area in Hsp33 when it interacts with its substrate proteins. The SUPREX derived Kd-values for Hsp33 complexes with four different substrates were also found to be all within a range of 3-300 nM. The interaction between Hsp33 and one of its substrates, citrate synthase (CS), was characterized at a higher structural resolution by using the SUPREX technique in combination with a protease digestion protocol. Using this protocol, the thermodynamic properties for both Hsp33 and CS were evaluated at different stages of binding, including reduced Hsp33 (inactive form), oxidized Hsp33 (active form), followed by native CS and finally of Hsp33ox -CS complexes before and after reduction with DTT. The results suggest that Hsp33 binds unfolded proteins that still have a significant amount of residual higher- order structure. Structural rearrangements of the substrate protein appear to occur upon reduction of the Hsp33-substrate complexes, which may facilitate the transfer of the substrate protein to other protein folding chaperone systems.

In the second part of this dissertation, a mass spectrometry-based covalent labeling protocol, which relies on the amidination rate of globally protected protein amine groups, was designed and applied to the thermodynamic analysis of several eight protein samples including: six purified proteins (ubiquitin, BCAII, RNaseA, 4OT, and lysozyme with, and without GlcNAc), a five-protein mixture comprised of ubiquitin, BCAII, RNaseA, Cytochome C, and lysozyme, and a yeast cell lysate. The results demonstrate that in ideal cases the folding free energies of proteins and the dissociation constants of protein-ligand complexes can be accurately evaluated using the protocol. Also demonstrated is the new method's compatibility with three different mass spectrometry-based readouts including an intact protein readout using MALDI, a gel-based proteomics readout using MALDI, and an LC-MS-based proteomics readout using isobaric mass tags. The results of the cell lysate sample analysis highlight the complementarity of the labeling protocol to other chemical modification strategies that have been recently developed to make thermodynamic measurements of protein folding and stability on the proteomic scale.

Detection and quantification of protein-ligand binding interactions is extremely important for understanding interactions that occur in biological systems. Since traditional techniques for characterizing these types of interactions cannot be performed in complex systems such as cell lysates, a series of energetics-based techniques that are capable of assessing protein stability and measuring ligand binding affinities have been developed to overcome some of the limitations of previous techniques. Now that the capabilities of the energetics-based techniques have been exhibited in model systems, the false-positive rates of the techniques, the range of biological questions to which the techniques can be addressed, and the use of the techniques to discover novel interactions in unknown systems remained to be shown. The Stability of Proteins from Rates of Oxidation (SPROX) technique and the Pulse Proteolysis (PP) technique were applied to a wide range of biological questions in both yeast and human cell lysates to evaluate the scope of these experimental workflows. The false-positive rate of iTRAQ-SPROX protein target discovery on orbitrap mass spectrometer systems was determined to be < 0.8 %. The iTRAQ-SPROX technique was successfully applied to the discovery of both known and novel protein-protein, protein-ATP, and protein-drug interactions, leading to the quantification of protein-ligand binding affinities in each of these studies. In the pursuit of discovering geldanamycin protein interactors, the use of iTRAQ-SPROX and SILAC-PP in combination was determined to be advantageous for confirming protein-ligand interactions since the techniques utilize different quantitation strategies that are subject to separate technical errors in quantitation. Finally, the iTRAQ-SPROX and SILAC-PP techniques were used to evaluate the interactions of manassantin A in a human cell lysate. In this work, a previously unknown protein target of manassantin A, Filamin A, was detected as a hit protein using both the iTRAQ-SPROX and SILAC-PP protocols. The work completed in this dissertation has expanded the understanding of the limitations of energetics-based techniques and shown that biological replicate analyses are essential to confirm ligand interactions with novel protein targets.

Protein biomarkers can facilitate the diagnosis of many diseases such as cancer and they can be important for the development of effective therapeutic interventions. Current large-scale biomarker discovery and disease state characterization studies have largely focused on the global analysis of gene and protein expression levels, which are not directly tied to function. Moreover, functionally significant proteins with similar expression levels go undetected in the current paradigm of using gene and protein expression level analyses for protein biomarker discovery. Protein-ligand interactions play an important role in biological processes. A number of diseases such as cancer are reported to have altered protein interaction networks. Current understanding of biophysical properties and consequences of altered protein interaction network in disease state is limited due to the lack of reproducible and high-throughput methods to make such measurements. Thermodynamic stability measurements can report on a wide range of biologically significant phenomena (e.g., point mutations, post-translational modifications, and new or altered binding interactions with cellular ligands) associated with proteins in different disease states. Investigated here is the use of thermodynamic stability measurements to probe the altered interaction networks and functions of proteins in disease states. This thesis outlines the development and application of mass spectrometry based methods for making proteome-wide thermodynamic measurements of protein stability in multifactorial complex diseases such as cancer. Initial work involved the development of SILAC-SPROX and SILAC-PP approaches for thermodynamic stability measurements in proof-of-concept studies with two test ligands, CsA and a non-hydrolyzable adenosine triphosphate (ATP) analogue, adenylyl imidodiphosphate (AMP-PNP). In these proof-of-principle studies, known direct binding target of CsA, cyclophilin A, was successfully identified and quantified. Similarly a number of known and previously unknown ATP binding proteins were also detected and quantified using these SILAC-based energetics approaches.

Subsequent studies in this thesis involved thermodynamic stability measurements of proteins in the breast cancer cell line models to differentiate disease states. Using the SILAC-SPROX, ~800 proteins were assayed for changes in their protein folding behavior in three different cell line models of breast cancer including the MCF-10A, MCF-7, and MDA-MB-231 cell lines. Approximately, 10-12% of the assayed proteins in the comparative analyses performed here exhibited differential stability in cell lysates prepared from the different cell lines. Thermodynamic profiling differences of 28 proteins identified with SILAC-SPROX strategy in MCF-10A versus MCF-7 cell line comparison were also confirmed with SILAC-PP technique. The thermodynamic analyses performed here enabled the non-tumorigenic MCF-10A breast cell line to be differentiated from the MCF-7 and MDA-MB-231 breast cancer cell lines. Differentiation of the less invasive MCF-7 breast cancer cell line from the more highly invasive MDA-MB-231 breast cancer cell line was also possible using thermodynamic stability measurements. The differentially stabilized protein hits in these studies encompassed those with a wide range of functions and protein expression levels, and they included a significant fraction (~45%) with similar expression levels in the cell line comparisons. These proteins created novel molecular signatures to differentiate the cancer cell lines studied here. Our results suggest that protein folding and stability measurements complement the current paradigm of expression level analyses for biomarker discovery and help elucidate the molecular basis of disease.

High-throughput molecular profiling is being increasingly applied to identify novel biomarkers and mechanisms of health and disease. One such application is the use of mass spectrometry-based metabolomic profiling in cardiovascular disease (CVD), whose underlying pathophysiology and risk prediction models are incompletely understood. Two general approaches have been taken in these applications: targeted and non-targeted profiling. The targeted approach identifies and quantifies select known or potential biomarkers in CVD, often via isotope-labeled internal standards. The non-targeted approach attempts to profile the full spectrum of the metabolome, with identification of metabolites aided by existing spectral libraries. In contrast to many successful applications of targeted metabolomics to CVD, early applications of non-targeted profiling have resulted in several pitfalls due to lack of rigor in study design, immature technologic platforms, and challenges in metabolite identification and quantification both at the experimental and computational level. These pitfalls highlight the importance of experimental design and method development in non-targeted metabolomic profiling. The overall goal of this dissertation is to improve methods in non-targeted metabolomic profiling both at the experimental and computational level, and apply these improved methods to CVD human studies. Specifically, this dissertation aims to: 1) identify and modify factors that could influence metabolite identification and quantification in GC-MS based non-targeted profiling at the experimental level; (2) apply emerging methods for metabolite identification at the computational level to generate hypotheses for unknowns; and (3) apply metabolomic profiling to studies in human cardiovascular disease, using the refined methods from the first two aims.

For the first aim, we sought to identify and modify factors in GC-MS-based metabolomic profiling of human plasma that could influence metabolite identification and quantification at the experimental level. Our experimental design included two studies: 1) the limiting-dilution study, which investigated the effects of laboratory preparation and analysis on analyte identification and quantification, and 2) the concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We tested and confirmed our hypothesis that contaminants, concentration, intra- and inter-experiment variability are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized into recommendations for experimental design of GC-MS-based profiling of human plasma.

For the second aim, we applied emerging methods for metabolite identification level to generate hypotheses for unknowns at the computational level. Specifically, we tested and confirmed our hypothesis that integrating genomic, transcriptomic, and metabolomic data could generate hypotheses for unknowns. Combining the strengths of multiple omics platforms and metabolomic databases, we were able to generate hypotheses for three unknown metabolites implicated in CVD at the computational level.

For the third aim, we applied metabolomic profiling to two studies of CVD and tested the hypothesis that application of the refined methods developed in the first two aims of this dissertation are useful in CVD biomarker and mechanism discovery. In one study, we used heart failure with preserved ejection fraction (HFpEF) as a model to demonstrate the power of targeted metabolomic profiling in testing existing hypotheses of CVD biomarkers and mechanisms. In a second study, we used incident CVD events as a model to 1) apply the refined methods from the first two aims of this dissertation, and 2) demonstrate the power of non-targeted metabolomic profiling in generating novel hypotheses of CVD biomarkers and mechanisms.

This dissertation contributes to research in metabolomics and CVD in several ways. The most significant contribution is the set of recommendations for experimental design in non-targeted metabolomics, which has been incorporated into the workflow of non-targeted profiling at the Duke Molecular Physiology Institute for future studies. Additional contributions include the following: hypotheses for three unknowns implicated in incident CVD events, and novel biomarkers and mechanisms implicated in HFpEF and CVD. Future directions from this dissertation include the following: 1) application of the same principles to method development and validation of metabolomic profiling using other analytical technologies; 2) experimental validation of the hypotheses for unknowns generated by this dissertation; and 3) functional validation of the biomarkers and mechanisms implicated in CVD at the experimental level.

Effluence of organic compounds like benzene, toluene, ethylbenzene and xylenes (“BTEX”), and methane from an industrial setting can have a negative impact on human health and the environment. Miniature sector mass spectrometers have the potential to acquire desirable attributes for ideal organic compound detection such as robustness, low cost, high chemical specificity, high sensitivity, and low power requirements. However, barriers to their miniaturization exist in the form of a throughput vs. resolution tradeoff. Spatially coded apertures can break this tradeoff by increasing throughput without sacrificing resolution. Cycloidal sector mass spectrometers are ideal candidates for incorporation of spatially coded apertures when used with array detectors, since they use perfectly focus the image of coded aperture at the detector due to perpendicularly oriented uniform electric and magnetic fields.

A previous demonstration of a proof-of concept cycloidal-coded aperture miniature mass spectrometer (C-CAMMS) instrument employed aperture coding, a carbon nanotube (CNT) field emission electron ionization source, a cycloidal mass analyzer, and a capacitive transimpedance amplifier (CTIA) array detector to achieve greater than ten-fold increase in throughput without sacrificing resolution. However, the coded aperture image corresponding to each ion species was not constant due to a spatiotemporal variation in electron emission from CNTs, a non-uniformity in the electric field, and a misalignment of the detector and the ion source with the mass analyzer focal plane.

In this work, modifications to the sample inlet, ion source, and the mass analyzer design of the previous C-CAMMS instrument were made to improve its performance. A membrane inlet enhanced the organic compound detection sensitivity of the new C-CAMMS instrument and enabled low detection limits of 50 ppm for methane and 20 ppb for toluene. A thermionic filament-based ion source produced a significantly more stable coded aperture image than the CNT based ion source. The aperture image fluctuations in the CNT-based source were determined to be likely a result of adsorption and desorption of molecules on the CNT surface that caused local work function changes and induced spatiotemporal variation in electron emission and subsequent ion generation. Modifications to the mass analyzer improved the electric field uniformity, improved the alignment of the ion source and the detector with the mass analyzer focal plane, and increased the depth-of-focus to further facilitate alignment. Finally, a comparison of reconstructed spectra of a mixture of dry air and toluene at different electric fields was performed using the improved C-CAMMS prototype. A reduction in reconstruction artifacts for a wide mass-to-charge (m/z) range highlighted the improved performance enabled by the design changes.

The obligate intracellular pathogen, Chlamydia trachomatis, is becoming an ever greater public health threat worldwide. Despite aggressive public health awareness campaigns and treatment with antibiotics, chlamydial infections continue to be the most frequently reported sexually transmitted infection in the United States and the cause of 3% of worldwide blindness. While research into understanding various mechanisms of chlamydial pathogenesis is ongoing, efforts to identify critical protein targets are hampered by the lack of facile genetic manipulation systems available for Chlamydia. Without the ability to perform genetic studies, researchers have employed chemical biology tools to close the gap in understanding how Chlamydia survives and thrives in the host cell.

Chlamydial protease-like activity factor (CPAF) has been identified as a central virulence factor in chlamydial pathogenesis. Several studies have indicated a role for CPAF-mediated degradation of host proteins in the late stages of infection. CPAF is hypothesized to interfere with myriad host cell processes, including inflammation, cell proliferation, cytoskeletal development, and immunity presentation. However, recent studies have called into question the methods used to previously identify bona fide in vivo CPAF targets, as CPAF has been shown to retain proteolytic activity even in the presence of broad spectrum protease inhibitors. As a result of these new finding, there is a renewed call to carefully identify CPAF substrates using methods that ensure total inhibition of post-lysis proteolysis.

This dissertation aims to clarify the role of CPAF in chlamydial pathogenesis and to identify mechanisms by which CPAF exhibits substrate specificity. Because enzymes can manifest specificity through kinetic mechanisms, sequence recognition, secondary site substrate binding, or protein structure level specificity, multiple methods of biochemical characterization were employed to distinguish between these modes of specificity.

Optimized HPLC-based and fluorescence quenching assays were developed and used to investigate the chemical and kinetic mechanism of CPAF proteolysis, as well as to characterize CPAF resistance to broad spectrum protease inhibitors. Peptide library proteomics were designed to probe active site sequence recognition of specific amino acids. Bioinformatic approaches were used to recognize and annotate a cryptic PDZ-like domain in CPAF, which bears strong structural similarity to human epithelial tight junction proteins. Using a new endocervical cellular model of infection, a recently developed C. trachomatis mutant lacking CPAF activity was investigated. Mass spectrometry proteomics analysis was employed to detect differential cleavage of host proteins in endocervical cells infected with CPAF+ and CPAF- strains of C. trachomatis. Lastly, methods for N-terminal labeling and enrichment were adapted for further identifying CPAF substrates in a cellular infection model. The subtiligase system for biotinylation of N-terminal amines was adapted for integration with C. trachomatis infection assays and downstream mass spectrometry proteomics. Ultimately, the dissertation offers clarification of the role of CPAF in chlamydial infection and provides chemical biology tools for further study of protease function in bacterial pathogenesis.

Proteomic methods for disease state characterization and biomarker discovery have traditionally utilized quantitative mass spectrometry methods to identify proteins with altered expression levels in disease states. Unfortunately, these studies have not been as useful as expected at identifying disease-related proteins that can be exploited for diagnostic and therapeutic purposes, presumably due to the indirect link between a protein’s expression level and its function. Investigated here is the use of thermodynamic stability measurements to probe a more biologically relevant dimension of the proteome. It has the potential to become a new strategy for disease state characterization and to help elucidate the molecular basis of the disease. This thesis outlines the use of two discovery based techniques and one validation based technique to study protein folding and stability changes associated with breast cancer.

The first part of this dissertation describes the application of a mass spectrometry-based technique, stable isotope labeling with amino acids in cell culture and stability of proteins from rates of oxidation (SILAC-SPROX), in a comparison of the MCF-7 versus BT-474 breast cancer cell lines and a comparison of the MCF-7 versus MDA-MB-468 breast cancer cell lines. This work enabled ~1000 proteins to be assayed for breast cancer-related thermodynamic stability differences. The 242 and 445 protein hits identified with altered stabilities in these comparative analyses created distinct molecular markers to differentiate the three cell lines.

The second part of this dissertation describes the development of a SILAC-based limited proteolysis (SILAC-LiP) strategy. The applicability of the protocol was demonstrated in a proof-of-principle study using proteins from a yeast cell lysate and a ubiquitous ligand. The SILAC-LiP protocol was further applied in a comparison of the MCF-7 versus MCF-10A cell lines. This work identified ∼200 proteins with cell line dependent conformational changes, as determined by their differential susceptibility to proteolytic digestion using the nonspecific protease, proteinase K. The overlap between the SILAC-LiP hits reported here and the SILAC-SPROX hits previously identified in these same cell lines was relatively small (~20%). Thus, this work indicates that the SILAC-SPROX and SILAC-LiP techniques can be used together to provide complementary information on the disease states.

Furthermore, the protein hits identified in both the SILAC-SPROX and SILAC- LiP experiments included a large fraction (∼70%) with no significant expression level changes. This suggests protein folding and stability measurements can provide information about disease states that is orthogonal to that obtained in protein expression level analyses.

The last part of this dissertation focuses on the establishment of targeted mass spectrometry-based validation assays for the protein biomarker candidates with altered thermodynamic stabilities identified in the SILAC-SPROX experiments. Application of the PAB-SPROX protocol on the MCF-7 cell lysate enabled reproducible identification and quantitation of a subset of prioritized target peptides.

Over the past two decades, a toolbox of mass spectrometry-based proteomic methods has been developed that enables the conformational properties of proteins and protein-ligand complexes to be probed in complex biological mixtures, from cell lysates to whole cells. The focus of this dissertation is the extension of these methodologies to the study of protein-gas and protein-metal interactions, an area of limited application. The goals of this work are two-fold. The first is to improve current mass spectrometry-based proteomic methods that measure protein folding stability, which is accomplished by the development of a chemo-selection strategy for proteolysis procedures and a “one-pot” approach that increases statistical significance while decreasing experiment costs. The second goal of this work is the application of these methodologies and others to the study of protein-gas and protein-metal interactions in complex biological mixtures (i.e., cell lysates), in which insights could be gained about gas and metal biological activities by surveying their interactions within a proteome. The first part of this dissertation describes in more detail the development and application of a semitryptic peptide enrichment strategy for proteolysis procedures (STEPP) that enables the isolation of information-rich semitryptic peptides. With the STEPP protocol, the number of semitryptic peptides increased by 5- to 10-fold and the amount of structural information was maximized in limited proteolysis experiments. The combination of the pulse proteolysis technique with a novel “one-pot” approach for data acquisition and analysis (one-pot STEPP-PP), resulted in false positive rates reaching close to zero (i.e., 0.09%) for a proof-of-principle drug target identification experiment for cyclosporine A and a yeast lysate. Described in the second part of this dissertation is the application of the improved proteolysis methodologies and others to multiple studies of protein-gas and protein-metal interactions on the proteomic scale. First, the development and application of protein stability measurements to the study of protein-gas interactions, specifically protein-xenon interactions, is described. A sample preparation protocol that was conducive to protein-gas binding studies is developed and validated against a known xenon-binding protein, metmyoglobin. Ultimately, this sample preparation protocol was employed in large-scale, proteome-wide SPROX and limited proteolysis experiments to identify xenon-interacting proteins in a yeast lysate. The SPROX and LiP analyses identified 31 and 60 Xe-interacting proteins, respectively, none of which were previously known. Our survey of the proteome revealed that these Xe-interacting proteins were enriched in those involved in ATP-driven processes and revealed correlations between the mechanisms by which ATP and Xe target proteins. Next, the application of one-pot STEPP-PP is described in the context of two research areas, both related to identifying the protein targets of metal-associated cell death processes. First described is the utilization of this technique in combination with protein expression level analysis to identify bacterial protein targets of copper delivered by small molecule ionophores. The protein folding stability and expression level profiles generated in this work enabled the effects of ionophore vs. copper to be distinguished and revealed copper-driven stability changes in proteins from processes spanning metabolism, translation, and cell redox homeostasis. The 159 differentially stabilized proteins identified in this analysis were significantly more numerous (by 3-fold) than the 53 proteins identified with differential expression levels. These results illustrate the unique information that protein stability measurements can provide to decipher metal-dependent processes in drug mode of action studies. The second application of the one-pot STEPP-PP methodology is to the study of Fe- and Zn-mediated sensitization to erastin-induced ferroptotic cell death. Our approach enabled differential protein expression and protein folding stability measurements to be made on RCC4 cells exposed to excess iron and zinc along with the ferroptosis-inducing molecule erastin. Of the protein targets identified, a few have known ties to pathways involved in ferroptotic cell death, while others have not been previously linked with ferroptosis. Future work aims at assaying the potential metal binding properties of these proteins, to connect them to their metal-enhancing ferroptosis effects. The final research area described in this dissertation is the development and application of a novel metal-induced protein precipitation (MiPP) approach which exploits the protein precipitation properties of metals to study proteins that are susceptible to metal overload. Total protein precipitation as a function of metal concentration was assayed across various proteomes (bacterial, fungal, and mammalian) and metals (copper, zinc, iron, etc). Copper-induced protein precipitation was measured within E. coli and C. albicans proteomes by coupling precipitation curves with a bottom-up proteomics readout. Proteome-wide precipitation studies revealed a wide distribution of copper precipitation midpoints for the identified proteins within these species. A fundamental understanding of the biophysical basis of susceptibility or tolerance to metal precipitation can potentially be garnered through more in-depth analysis of the proteins that fall significantly outside the average precipitation midpoint of each proteome.

The National Research Council’s Planetary Science 2013-2022 Decadal Survey underscores three interrelated themes pivotal to planetary science research: understanding solar system beginnings, searching for the requirements for life, and understanding the workings of solar systems. In situ mass spectrometry (MS) is the primary technique for the analysis of planetary substances, directly addressing the critical inquiries associated with these themes. The quintessential mass analyzer engineered for space exploration is envisioned to embody a suite of features: a mass range extending from 1 u to at least 500 u, capability for high-precision measurement of stable isotope ratios within a tolerance of ±1‰, and the ability to resolve distinct isobaric species at a low mass below 60 u, all with low power requirements. Incorporation of these capabilities within a single instrument is crucial for facilitating the exploration of the necessities of life and for advancing our understanding of solar system genesis and planetary development. Nevertheless, state-of-the-art existing spaceflight mass spectrometers do not fully integrate all these capabilities.In this research, three technologies are investigated to close this gap; spatial aperture coding, super-resolution, and field emission electron sources . The development of these three technologies as presented in this dissertation represent a significant step towards a mass spectrometer having all of the characteristics described above. First, Spatial aperture coding is a technique used to improve throughput without sacrificing resolution, historically in optical spectroscopy, and more recently as demonstrated by our laboratory at Duke University, in sector mass spectrometry (MS). Previously we demonstrated that aperture coding combined with a position-sensitive array detector in a miniature cycloidal mass spectrometer was successful in providing high-throughput, high-resolution measurements. However, due to poor alignment and field non-uniformities, reconstruction artifacts were present. In this dissertation, two methods were implemented to significantly reduce the presence of artifacts in reconstructed spectra. First, I employed a variable system response function across the mass range (10 – 110 u) instead of using a fixed function. Second, I modified the design by shifting the coded aperture slits relative to the center of the ionization volume to enable even illumination of the coded aperture slits. Both methods were successful in significantly reducing artifacts at low mass from above 35% of the peak height to less than 6% of the peak height. Second, higher resolution in fieldable mass spectrometers (MS) is desirable in space flight applications to enable resolving isobaric interferences at m/z < 60 u. Resolution in portable cycloidal MS coupled with array detectors could be improved by reducing the slit width and/or by reducing the width of the detector pixels. However, these solutions are expensive and can result in reduced sensitivity. In this dissertation, I demonstrate high-resolution spectral reconstruction in a cycloidal coded aperture miniature mass spectrometer (C-CAMMS) without changing the slit or detector pixel sizes using a class of signal processing techniques called super resolution (SR). I developed an SR reconstruction algorithm using a sampling SR approach whereby a set of spatially shifted low-resolution measurements are reconstructed into a higher-resolution spectrum. This algorithm was applied to experimental data collected using the C-CAMMS prototype. It was then applied to synthetic data with additive noise, system response variation, and spatial shift nonuniformity to investigate the source of reconstruction artifacts in the experimental data. Experimental results using two 1/2 pixel shifted spectra resulted in a resolution of 3/4 pixel full width at half maximum (FWHM) at m/z = 28 u. This resolution is equivalent to 0.013 u, six times better than the resolution previously published at m/z = 28 for N2+ using C-CAMMS. However, the reconstructed spectra exhibited some artifacts. The results of the synthetic data study indicate that the artifacts are most likely caused by the system response variation. Despite these artifacts, it was shown that the super-resolution algorithm is capable of resolving the isobaric interference between N2 and CO at m/z = 28. Third, Field emission electron sources for MS electron ionization have been of interest to spaceflight applications due to their low power compared to thermionic sources. However, state-of-the-art devices suffer from limitations such as high turn-on macroscopic field, low macroscopic current density, poor emission stability, and short lifetime. Field emitter arrays with a high spatial density of uniform emitters have the potential to address these problems. In this work, process development, fabrication, and testing of two novel field emission based devices are presented, including CNT array emitters and metallic nanowires. Instability in CNT emission was investigated using noise analysis and a polymer encapsulation process to reduce the effect of adsorbates on the tips of CNTs. This treatment was not successful in reducing emission noise in CNTs. Thus, electron beam lithography and templated electrodeposition were used to fabricate a high spatial density array of metallic nanowires, resulting in electron field emission with high macroscopic current density (2 A/cm2) and low turn-on macroscopic field (4.35 V/μm). Results indicate that templated electrodeposition of metallic nanowire arrays is a promising method for producing high-performance field emitters.

The detection and quantitation of protein-ligand binding interactions is important not only for understanding biological functions but also for the characterization of novel protein ligands. Because protein ligands can range from small molecules to other proteins, general techniques that can detect and quantitate the many classes of protein-ligand interactions are especially attractive. Additionally, the ability to detect and quantify protein-ligand interactions in complex biological mixtures would more accurately represent the protein-ligand interactions that occur in vivo, where differential protein expression and protein complexes can significantly affect a protein's ability to bind to a ligand of interest.

The work in this dissertation is focused on the development of new methodologies for the detection and measurement of protein-ligand interactions in complex mixtures using multiplex analyses. Methodologies for two types of multiplexed analyses of protein-ligand binding interactions are investigated here. The first type of multiplex analysis involves characterizing the binding of one protein target to many potential ligands, and the second type involves characterizing the binding of one ligand to many proteins. The described methodologies are derived from the SUPREX (stability of unpurified proteins from rates of H/D exchange) and SPROX (stability of proteins from rates of oxidation) techniques, which are chemical modification strategies that measure thermodynamic stabilities of proteins using a relationship between a protein's folding equilibrium and the extent of chemical modification. These two techniques were utilized in the development and application of several different experimental strategies designed to multiplex the analysis of protein-ligand interactions.

The first strategy that was developed involved a pooled compound approach for making SUPREX-based measurements of multiple ligands binding to a target protein. Screening rates of 6 s/ligand were demonstrated in a high-throughput screening project that involved the screening of two chemical libraries against human cyclophilin A (CypA), a protein commonly overexpressed in types of cancer. This study identified eight novel ligands to CypA with micromolar dissociation constants. Second, an affinity-based protein purification strategy was developed for the detection and quantitation of specific protein-ligand binding interactions in the context of complex protein mixtures. It involved performing SPROX in cell lysates and selecting the protein of interest using immunoprecipitation or affinity tag purification. A third strategy developed here involved a SPROX-based stable isotope labeling method for measuring protein-ligand interactions in multi-protein mixtures. This strategy was used in a proof-of-principle experiment designed to detect and quantify the indirect binding between yeast cyclophilin and calcineurin in a multi-component protein mixture. Finally, a quantitative proteomics platform was developed for the detection and quantitation of protein-ligand binding interactions on the proteomic scale. The platform was used to profile interactions of the proteins in a yeast cell lysate to several ligands, including the bioactive small molecules resveratrol and manassantin A, the cofactor nicotinamide adenine dinucleotide (NAD+), and two proteins, phosphoglycerate kinase (Pgk1) and pyruvate kinase (Pyk1). The above approaches should have broad application for use as discovery tools in the development of new therapeutic agents.