Matching Items (33)
Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cancer is one of the most serious global diseases. We have focused on cancer immunoprevention. My thesis projects include developing a prophylactic primary and metastatic cancer vaccines, early cancer detection and investigation of genes involved in tumor development. These studies were focused on frame-shift (FS) antigens. The FS antigens are generated by genomic mutations or abnormal RNA processing, which cause a portion of a normal protein to be translated out of frame. The concept of the prophylactic cancer vaccine is to develop a general cancer vaccine that could prevent healthy people from developing different types of cancer. We have discovered a set of cancer specific FS antigens. One of the FS candidates, structural maintenance of chromosomes protein 1A (SMC1A) FS, could start to accumulate at early stages of tumor and be specifically exposed to the immune system by tumor cells. Prophylactic immunization with SMC1A-FS could significantly inhibit primary tumor development in different murine tumor models and also has the potential to inhibit tumor metastasis. The SMC1A-FS transcript was detected in the plasma of the 4T1/BALB/c mouse tumor model. The tumor size was correlated with the transcript ratio of the SMC1A-FS verses the WT in plasma, which could be measured by regular RT-PCR. This unique cancer biomarker has a practical potential for a large population cancer screen, as well as clinical tumor monitoring. With a set of mimotope peptides, antibodies against SMC1A-FS peptide were detected in different cancer patients, including breast cancer, pancreas cancer and lung cancer with a 53.8%, 56.5% and 12.5% positive rate respectively. This suggested that the FS antibody could be a biomarker for early cancer detection. The characterization of SMC1A suggested that: First, the deficiency of the SMC1A is common in different tumors and able to promote tumor initiation and development; second, the FS truncated protein may have nucleolus function in normal cells. Mis-control of this protein may promote tumor development. In summary, we developed a systematic general cancer prevention strategy through the variety immunological and molecular methods. The results gathered suggest the SMC1A-FS may be useful for the detection and prevention of cancer.
ContributorsShen, Luhui (Author) / Johnston, Stephen Albert (Thesis advisor) / Chang, Yung (Committee member) / Miller, Laurence (Committee member) / Sykes, Kathryn (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
It is important to consider factors that contribute to successful fertilization and the development of viable offspring. Better understanding the factors that contribute to infertility can be used to assist in the development of viable offspring, especially for human beings looking to successfully reproduce. Identifying paternal effect genes, genes that come from the father, introduces more targets that can be manipulated to produce specific reproductive effects. Use of Drosophila melanogaster as a model to study reproduction has increased, in part, due to the use of the GAL4 system. In this system, the GAL4 gene encodes an 881 amino acid protein that binds to the 4-site Upstream Activating Sequence (UAS) to induce transcription of the gene of interest. These sequences constitute the two components of the system: the driver (GAL4) and the responder (gene of interest) \u2014 each of which is maintained as a separate parental line. Effects of the GAL4 driver line "driving" transcription of the responder can be assessed by examining the offspring. One of the more common uses of the GAL4 system involves analyzing phenotypic effects of reducing or eliminating expression of a target gene through the induction of RNAi transcription, which often results in toxicity, lethality, or reduced viability. Utilizing these principles, we strove to demonstrate the effect of knocking down the expression of testis-specific sperm-leucyl-aminopeptidases gene CG13340 on progeny by inducing expression of RNAi with two distinct GAL4 driver lines - one with a nonspecific actin-binding activation sequence and the other with a testis-specific activation sequence. Comparison of both GAL4 driver lines to crosses using N01 wild type ("wt") flies verify that inducing RNAi transcription using the GAL4 system results in reduction of proper offspring development. Further studies using D. melanogaster and the GAL4 system can improve knowledge of factors contributing to male fertility and also be applied to better understand mammalian, specifically human, fertility.
ContributorsEvans, Donna Marie (Author) / Karr, Timothy L. (Thesis director) / Roland, Kenneth (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of English (Contributor)
Created2014-05
Description
Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the 10th leading cause of death, worldwide. The prevalence of drug-resistant clinical isolates and the paucity of newly-approved antituberculosis drugs impedes the successful eradication of Mtb. Bacteria commonly use two-component systems (TCS) to sense their environment and genetically modulate adaptive responses. The prrAB TCS is essential in Mtb, thus representing an auspicious drug target; however, the inability to generate an Mtb ΔprrAB mutant complicates investigating how this TCS contributes to pathogenesis. Mycobacterium smegmatis, a commonly used M. tuberculosis genetic surrogate was used here. This work shows that prrAB is not essential in M. smegmatis. During ammonium stress, the ΔprrAB mutant excessively accumulates triacylglycerol lipids, a phenotype associated with M. tuberculosis dormancy and chronic infection. Additionally, triacylglycerol biosynthetic genes were induced in the ΔprrAB mutant relative to the wild-type and complementation strains during ammonium stress. Next, RNA-seq was used to define the M. smegmatis PrrAB regulon. PrrAB regulates genes participating in respiration, metabolism, redox balance, and oxidative phosphorylation. The M. smegmatis ΔprrAB mutant is compromised for growth under hypoxia, is hypersensitive to cyanide, and fails to induce high-affinity respiratory genes during hypoxia. Furthermore, PrrAB positively regulates the hypoxia-responsive dosR TCS response regulator, potentially explaining the hypoxia-mediated growth defects in the ΔprrAB mutant. Despite inducing genes encoding the F1F0 ATP synthase, the ΔprrAB mutant accumulates significantly less ATP during aerobic, exponential growth compared to the wild-type and complementation strains. Finally, the M. smegmatis ΔprrAB mutant exhibited growth impairment in media containing gluconeogenic carbon sources. M. tuberculosis mutants unable to utilize these substrates fail to establish chronic infection, suggesting that PrrAB may regulate Mtb central carbon metabolism in response to chronic infection. In conclusion, 1) prrAB is not universally essential in mycobacteria; 2) M. smegmatis PrrAB regulates genetic responsiveness to nutrient and oxygen stress; and 3) PrrAB may provide feed-forward control of the DosRS TCS and dormancy phenotypes. The data generated in these studies provide insight into the mycobacterial PrrAB TCS transcriptional regulon, PrrAB essentiality in Mtb, and how PrrAB may mediate stresses encountered by Mtb during the transition to chronic infection.
ContributorsMaarsingh, Jason (Author) / Haydel, Shelley E (Thesis advisor) / Roland, Kenneth (Committee member) / Sandrin, Todd (Committee member) / Bean, Heather (Committee member) / Arizona State University (Publisher)
Created2019
Description
Massive glycerol cluster ions with many charges (~ 106 Da, ~ ±100 charges) have been generated by electrospray to bombard biomolecules and biological sample surfaces. The low impact energy per nucleon facilitates intact sputtering and ionization of biomolecules which can be subsequently imaged. Various lipids, peptides and proteins have been studied. The primary cluster ion source has been coupled with an ion-microscope imaging mass spectrometer (TRIFT-1, Physical Electronics). A lateral resolution of ~3µm has been demonstrated, which is acceptable for sub-cellular imaging of animal cells (e.g. single cancer cell imaging in early diagnosis). Since the available amount of target molecules per pixel is limited in biological samples, the measurement of useful ion yields (ratio of detected molecular ion counts to the sample molecules sputtered) is important to determine whether enough ion counts per pixel can be obtained. The useful ion yields of several lipids and peptides are in the 1-3×10-5 range. A 3×3 µm2lipid bilayer can produce ~260 counts/pixel for a meaningful 3×3 µm2 pixel ion image. This method can probably be used in cell imaging in the future, when there is a change in the lipid contents of the cell membrane (e.g. cancer cells vs. normal cells).
ContributorsZhang, Jitao (Author) / Williams, Peter (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cell heterogeneity is widely present in the biological world and exists even in an isogenic population. Resolving the protein heterogeneity at the single cell level is of enormous biological and clinical relevance. However, single cell protein analysis has proven to be challenging due to extremely low amount of protein in a single cell and the huge complexity of proteome. This requires appropriate sampling and sensitive detection techniques. Here, a new approach, microfluidics combined with MALDI-TOF mass spectrometry was brought forward, for the analysis of proteins in single cells. The detection sensitivity of peptides as low as 300 molecules and of proteins as low as 10^6 molecules has been demonstrated. Furthermore, an immunoassay was successfully integrated in the microfluidic device for capturing the proteins of interest and further identifying them by subsequent enzymatic digestion. Moreover, an improved microfluidic platform was designed with separate chambers and valves, allowing the absolute quantification by employing iTRAQ tags or an isotopically labeled peptide. The study was further extended to analyze a protein in MCF-7 cell lysate. The approach capable of identifying and quantifying protein molecules in MCF-7 cells is promising for future proteomic studies at the single cell level.
ContributorsYang, Mian (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2016
Description
The emergence of invasive non-Typhoidal Salmonella (iNTS) infections belonging to sequence type (ST) 313 are associated with severe bacteremia and high mortality in sub-Saharan Africa. Distinct features of ST313 strains include resistance to multiple antibiotics, extensive genomic degradation, and atypical clinical diagnosis including bloodstream infections, respiratory symptoms, and fever. Herein, I report the use of dynamic bioreactor technology to profile the impact of physiological fluid shear levels on the pathogenesis-related responses of ST313 pathovar, 5579. I show that culture of 5579 under these conditions induces profoundly different pathogenesis-related phenotypes than those normally observed when cultures are grown conventionally. Surprisingly, in response to physiological fluid shear, 5579 exhibited positive swimming motility, which was unexpected, since this strain was initially thought to be non-motile. Moreover, fluid shear altered the resistance of 5579 to acid, oxidative and bile stress, as well as its ability to colonize human colonic epithelial cells. This work leverages from and advances studies over the past 16 years in the Nickerson lab, which are at the forefront of bacterial mechanosensation and further demonstrates that bacterial pathogens are “hardwired” to respond to the force of fluid shear in ways that are not observed during conventional culture, and stresses the importance of mimicking the dynamic physical force microenvironment when studying host-pathogen interactions. The results from this study lay the foundation for future work to determine the underlying mechanisms operative in 5579 that are responsible for these phenotypic observations.
ContributorsCastro, Christian (Author) / Nickerson, Cheryl A. (Thesis advisor) / Ott, C. Mark (Committee member) / Roland, Kenneth (Committee member) / Barrila, Jennifer (Committee member) / Arizona State University (Publisher)
Created2016
Description
Invasive salmonellosis caused by Salmonella enterica serovar Typhimurium ST313 is a major health crisis in sub-Saharan Africa, with multidrug resistance and atypical clinical presentation challenging current treatment regimens and resulting in high mortality. Moreover, the increased risk of spreading ST313 pathovars worldwide is of major concern, given global public transportation networks and increased populations of immunocompromised individuals (as a result of HIV infection, drug use, cancer therapy, aging, etc). While it is unclear as to how Salmonella ST313 strains cause invasive disease in humans, it is intriguing that the genomic profile of some of these pathovars indicates key differences between classic Typhimurium (broad host range), but similarities to human-specific typhoidal Salmonella Typhi and Paratyphi. In an effort to advance fundamental understanding of the pathogenesis mechanisms of ST313 in humans, I report characterization of the molecular genetic, phenotypic and virulence profiles of D23580 (a representative ST313 strain). Preliminary studies to characterize D23580 virulence, baseline stress responses, and biochemical profiles, and in vitro infection profiles in human surrogate 3-D tissue culture models were done using conventional bacterial culture conditions; while subsequent studies integrated a range of incrementally increasing fluid shear levels relevant to those naturally encountered by D23580 in the infected host to understand the impact of biomechanical forces in altering these characteristics. In response to culture of D23580 under these conditions, distinct differences in transcriptional biosignatures, pathogenesis-related stress responses, in vitro infection profiles and in vivo virulence in mice were observed as compared to those of classic Salmonella pathovars tested.
Collectively, this work represents the first characterization of in vivo virulence and in vitro pathogenesis properties of D23580, the latter using advanced human surrogate models that mimic key aspects of the parental tissue. Results from these studies highlight the importance of studying infectious diseases using an integrated approach that combines actions of biological and physical networks that mimic the host-pathogen microenvironment and regulate pathogen responses.
Collectively, this work represents the first characterization of in vivo virulence and in vitro pathogenesis properties of D23580, the latter using advanced human surrogate models that mimic key aspects of the parental tissue. Results from these studies highlight the importance of studying infectious diseases using an integrated approach that combines actions of biological and physical networks that mimic the host-pathogen microenvironment and regulate pathogen responses.
ContributorsYang, Jiseon (Author) / Nickerson, Cheryl A. (Thesis advisor) / Chang, Yung (Committee member) / Stout, Valerie (Committee member) / Ott, C Mark (Committee member) / Roland, Kenneth (Committee member) / Barrila, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015