Browsing by Subject "Protein stability"

The emergence of resistance to existing antibiotic drugs necessitates the development of new strategies to treat bacterial infections. Copper (Cu) has been used since ancient times to inhibit bacterial growth and has recently experienced a resurgence in its clinical utility as an antimicrobial coating for surfaces in hospitals. Small molecule chelators that bind Cu have also been shown to have antibacterial activity and are believed to disrupt metal homeostasis within the microbes they kill. Molecules called ionophores shuttle Cu into the cell to poison it. However, the antibacterial modes of action behind Cu and small molecule ionophores are not well understood. In this work, we employ a variety of biological, spectrometric, and proteomic techniques to study how Cu and a small molecule ionophore called pyrithione (PT) kill bacteria. First, we present antibacterial susceptibility assays that demonstrate PT and a β-lactamase-activated prodrug of PT called PcephPT kill bacteria in a Cu-dependent manner. Cu hyperaccumulated in cells that were cotreated with low-micromolar Cu and either PT or PcephPT, demonstrating their activity as metal-shuttling ionophores. Next, proteome-wide protein expression level and stability measurements were used to probe treatment-induced cellular changes after E. coli were exposed to Cu in the absence and presence of PT or PcephPT. The stability-based study identified key protein targets such as the metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and isocitrate dehydrogenase, whose activities were confirmed to be inhibited by PT-induced copper toxicity in enzymatic assays. Finally, the impact of Cu on the proteome was further investigated in a metal-induced protein precipitation experiment. Unlike other divalent first row transition metals, low millimolar Cu induced complete protein precipitation from E. coli lysate. Protein solubility was restored by addition of Cu chelators, showing that Cu-induced protein precipitation is reversible. We then obtained Cu precipitation curves for over 800 proteins and saw that some were more sensitive while others were more tolerant to precipitation by Cu. Finally, we analyzed the data set to better understand what biophysical characteristics of the proteins may contribute to making them sensitive or tolerant to precipitation by Cu.

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.

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.

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.

Driven by the development of new technologies and an ever expanding knowledge base of molecular and cellular function, Biology is rapidly gaining the potential to develop into a veritable engineering discipline - the so-called `era of synthetic biology' is upon us. Designing biological systems is advantageous because the engineer can leverage existing capacity for self-replication, elaborate chemistry, and dynamic information processing. On the other hand these functions are complex, highly intertwined, and in most cases, remain incompletely understood. Brazenly designing within these systems, despite large gaps in understanding, engenders understanding because the design process itself highlights gaps and discredits false assumptions.

Here we cover results from design projects that span several scales of complexity. First we describe the adaptation and experimental validation of protein functional assays on minute amounts of material. This work enables the application of cell-free protein expression tools in a high-throughput protein engineering pipeline, dramatically increasing turnaround time and reducing costs. The parts production pipeline can provide new building blocks for synthetic biology efforts with unprecedented speed. Tools to streamline the transition from the in vitro pipeline to conventional cloning were also developed. Next we detail an effort to expand the scope of a cysteine reactivity assay for generating information-rich datasets on protein stability and unfolding kinetics. We go on to demonstrate how the degree of site-specific local unfolding can also be determined by this method. This knowledge will be critical to understanding how proteins behave in the cellular context, particularly with regards to covalent modification reactions. Finally, we present results from an effort to engineer bacterial cell suicide in a population-dependent manner, and show how an underappreciated facet of plasmid physiology can produce complex oscillatory dynamics. This work is a prime example of engineering towards understanding.

Proteins are biological macromolecules made up of amino acids. Proteins range from enzymes to antibodies and perform their functions through a variety of mechanisms, including through protein-protein interactions (PPIs). Computational structure-based protein design (CSPD) seeks to design proteins toward some specific or novel function by changing the amino acid composition of a protein and modeling the effects. CSPD is a particularly challenging problem since the size of the search space grows exponentially with the number of amino acid positions included in each design. This challenge is most often encountered when considering large designs such as the re-design of a PPI. Herein, we discuss how to use CSPD to predict resistance mutations in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus and we investigate the accuracy of an existing CSPD suite of algorithms, osprey. We have also developed novel algorithms and tools within osprey to more efficiently and accurately predict the effects of mutations. We apply these various algorithms and tools to three systems toward a variety of goals: predicting the affect on stability of mutations in staphylococcal protein A (SpA), re-designing HIV-1 broadly neutralizing antibody PG9-RSH toward improved potency, and designing toward a peptide inhibitor of KRas:effector PPIs.

In the last 10 years, several mass spectrometry-based proteomic techniques have been developed for the large-scale characterization of protein conformations, thermodynamic stabilities, and protein−ligand interactions. The main focus of this dissertation involves the development and application of several mass spectrometry-based-methods in this current suite of proteomics techniques for the large-scale analysis of protein folding and stability measurement. One goal of this work is to investigate the use of protein folding and stability measurements to better detect and understand the biophysical properties of post-translational modifications. Another goal of this work is to develop a novel protein stability measurement technique for making thermodynamic measurements of protein folding and ligand binding interactions. This technique, which involves a combination chemical denaturant and protein precipitation yields significantly better proteomic coverage and a largely reduced false discovery rate compared to its sister technique, Stability of Proteins from Rates of Oxidation (SPROX).

The first part of this dissertation describes the application of the stability of proteins from rates of oxidation (SPROX) and limited proteolysis (LiP) on comparing the conformational properties of proteins in two MCF-7 cell lysates including one that was and one that was not dephosphorylated with alkaline phosphatase. A total of 168 and 251 protein hits were identified with dephosphorylation-induced stability changes using the SPROX and LiP techniques, respectively. The SPROX results revealed that the magnitudes of the destabilizing effects of dephosphorylation on the different aaRSs were directly correlated with their previously reported aminoacylation activity change upon dephosphorylation. The example of these aaRSs substantiates the close link between protein folding thermodynamic and function and helps establish the utility of thermodynamic stability measurements for understanding protein function.

The second part of this dissertation describes the development of a new protein-stability based proteomic method for identification and quantification of protein-drug interactions. The approach involves the evaluation of ligand-induced protein folding free energy changes (ΔΔGf) using chemical denaturation and protein precipitation (CPP) to identify the protein targets of drugs and to quantify protein−drug binding affinities. In the proof-of-principle studies performed here, the CPP technique was able to identify the well-known protein targets of cyclosporin A and geldanamycin in a yeast lysate. The technique was also used to identify protein targets of sinefungin in a human MCF-7 cell lysate. The CPP technique yielded dissociation constant (Kd) measurements for these well-studied drugs that were in general agreement with previously reported Kd or IC50 values.

The third part of this dissertation describes two protein target discovery applications of the CPP approach including one involving subglutinol A (a natural product with immunosuppressive activity) and one involving clemastine fumarate (an existing anti-histamine drug with recently discovered anti-malarial activity). As part of this work, about 800 proteins in a mouse 2B4 T cell lysate were assayed for subglutinol A-induced stability changes, and deoxycytidine kinase was identified as the protein hit. The magnitude of the ligand induced stability change was used to calculate a Kd value of 250 M, which is close to the reported cell based IC50. In the protein target discovery study on clemastine fumarate, a total of 800 yeast proteins were assayed for drug-induced stability changes and 8 protein with clemastine-induced stability changes were identified, including SEC14 cytosolic factor, glycerol kinase, asparagine--tRNA ligase, and inosine triphosphate pyrophosphatase. The latter two applications demonstrate that CPP can reliably identify and quantify protein-drug interactions in a complex biological mixture, making it a valuable addition to the current suite of proteomic methods for the large-scale detection and quantitation of protein-ligand binding interactions.