Based on past studies, urinary glycan biomarkers have the potential to be used as diagnostic and prognostic markers for treatment purposes. This study brought into play the bottom-up glycan node analysis approach to analyze 39 urine samples from COVID-19 positive and negative individuals using gas chromatography-mass spectrometry (GC-MS) to determine potential urinary glycan biomarkers of COVID-19. Glycan node analysis involves chemically breaking down glycans in whole biospecimens in a way that conserves both monosaccharide identity and linkage information that facilitates the capture of unique glycan features as single analytical signals. Following data acquisition, the student t-test was done on all the nodes, but only four prominent nodes (t-Deoxyhexopyranose, 2,3-Gal, t-GlcNAc, and 3,6-GalNAc with respective p-values 0.03027, 0.03973, 0.0224, and 0.0004) were below the threshold p-value of 0.05 and showed some differences in the mean between both groups. To eliminate the probability of having false positive p-values, Bonferroni correction was done on the four nodes but only the 3,6-GalNAc node emerged as the only node that was below the newly adjusted p-value. Because sample analyses were done in batches, the Kruskal Wallis test was done to know if the batch effect was responsible for the observed lower relative concentration of 3,6-GalNAc in COVID-19 positive patients than in negative patients. A receiver operating characteristic curve (ROC) was plotted for the 3,6-GalNAc node and the area under the curve (AUC) was calculated to be 0.84, casting the 3,6-GalNAc node was a potential biomarker of COVID-19. 3,6-GalNAc largely arises from branched O-glycan core structures, which are abundant in mucin glycoproteins that line the urogenital tract. Lowered relative concentrations of 3,6-GalNAc in the urine of COVID-19 positive patients may be explained by compromised kidney function that allows non-mucinous glycoproteins from the blood to contribute a greater proportion of the relative glycan node signals than in COVID-19 negative patients. Future prospective clinical studies will be needed to validate both the biomarker findings and this hypothesis.

Coccidioidomycosis, or Valley fever, is an endemic pneumonia of the arid and semi-arid regions of North and South America and is responsible for up to 30% of community-acquired pneumonias in endemic and highly populated areas of the United States southwest. The causative agents of Valley fever are the dimorphic fungi Coccidioides immitis and Coccidioides posadasii, which grow as mycelia in the environment and spherules within the lungs of vulnerable hosts. The current diagnostics for Valley fever are severely lacking due to poor sensitivity and invasiveness, strongly contributing to a 23-day median time-to-diagnosis. There is a critical need for sensitive and non-invasive diagnostics for identifying Valley fever lung infections. The long-term goal of my work is to substantially shorten the time-to-diagnosis for Valley fever through the development of sensitive and specific breath-based diagnostics for coccidioidomycosis lung infections. Herein, I characterized the volatile organic compounds (VOCs) produced by C. immitis and C. posadasii in vitro and evaluated the relationship of the volatile metabolomes to lifecycle. I explored the VOC profiles of bronchoalveolar lavage fluid (BALF) samples from mouse model lung infections of Valley fever. Finally, I investigated the VOC profiles of BALF from persons with community-acquired pneumonia. All VOCs were analyzed by headspace solid-phase microextraction and comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). The volatile metabolomes were compared using a variety of statistical analyses. For the in vitro samples, I detected a total of 353 VOCs that were at least two-fold more abundant in a Coccidioides culture versus medium controls and found the volatile metabolome of Coccidioides is more dependent on lifecycle than species. The mouse BALF samples indicate that lung infection VOCs are correlated to cytokine production and classify mice based on their individual level of infection. From the human BALF samples, I identified VOCs that were able to differentiate between Coccidioides and bacterial pneumonia. Combined, these studies suggest that Coccidioides spp. and the host produce volatile metabolites that may yield biomarkers for a Valley fever breath test.

Understanding cellular processes can provide insight into disease pathogenesis and reveal critical information for prevention, diagnosis, and treatment. As key executors and signaling regulators, proteins carry relevant information not available from genomics and transcriptomics. Cell-to-cell differences significantly affect disease incidence and drug responses, generating a need for protein analysis at the single-cell level. However, quantitative protein analysis at the single-cell level remains challenging due to the low protein amount in a single cell and the proteome complexity. It requires sensitive detection techniques and appropriate sample preparation and delivery to the detection area. Here, a microfluidic platform in tandem with matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) has been developed for targeted intracellular protein analysis. The elastomeric multi-layer microfluidic platform, termed MIMAS, was designed as a series of 8.75 nL wells separated by pneumatic valves. The MIMAS platform allows cell loading, sample processing on-chip, and further in situ mass spectrometry analysis. The sample processing includes cell lysis, immunocapture, tryptic digestion and MALDI matrix solution loading for co-crystallization. This work demonstrates that the MIMAS approach is suitable for protein quantification by assessing the apoptotic protein Bcl-2 from MCF-7 breast cancer cells using an isotope-labeled peptide. The limit of detection was determined as 11.22 nM, equivalent to 5.91 x 10^7 protein molecules per well. Moreover, the MIMAS platform design was improved, allowing the successful quantification of Bcl-2 protein in small cell ensembles down to ~10 cells in 4 nL wells. Furthermore, the MIMAS platform was integrated with laser capture microdissection (LCM) for protein analysis from post-mortem human tissues. Intracellular amyloid-β peptide (Aβ), a hallmark of Alzheimer’s Disease, was assessed from human brain tissue using the LCM-MIMAS. The successful detection of Aβ from small cell ensembles (20 sliced pyramidal cells) demonstrated the LCM-MIMAS capability of assessing intracellular proteins from specific tissue cell subpopulations. The MIMAS approach is a promising tool for intracellular protein analysis from small cell ensembles, with the potential for single-cell analysis. It allows for protein analysis towards the understanding of biological phenomena for clinical and biological research.

Exposure of liquid biospecimens like plasma and serum (P/S) to improper handling and storage can impact the integrity of biomolecules, potentially leading to apparent quantitative changes of important clinical proteins. An accurate and quick estimate of the quality of biospecimens employed in biomarker discovery and validation studies is essential to facilitating accurate conclusions. ΔS-Cys-Albumin is a marker of blood P/S exposure to thawed conditions that can quantitatively track the exposure of P/S to temperatures greater than their freezing point of -30 C. Reported here are studies carried out to evaluate the potential of ΔS-Cys-Albumin to track the stability of clinically important analytes present in P/S upon their exposure to thawed conditions. P/S samples obtained from both cancer-free donors and cancer patients were exposed to 23 C (room temperature), 4 C and -20 C degrees, and the degree to which the apparent concentrations of clinically relevant biomolecules present in P/S were impacted during the time it took ΔS-Cys-Albumin to reach zero was measured. Analyte concentrations measured by molecular interaction-based assays were significantly impacted when samples were exposed to the point where average ΔS-Cys-Albumin fell below 12% at each temperature. Furthermore, the percentage of proteins that became unstable with time under thawed conditions exhibited a strong inverse linear relationship to ΔS-Cys-Albumin, indicating that ΔS-Cys-Albumin can serve as an effective surrogate marker to track the stability of other clinically relevant proteins in plasma as well as to estimate the fraction of proteins that have been destabilized by exposure to thawed conditions, regardless of what the exposure temperature(s) may have been. These results indicated that P/S exposure to thawed conditions disrupts epitopes required for clinical protein quantification via molecular interaction-based assays. In continuation of this theme, a spurious binding event between two clinically important proteins, Apolipoprotein E (ApoE) and Interferon-  (IFN) present in human plasma under in vitro experimental conditions is also reported. The interaction was confirmed to be evident only when ApoE was expressed in vitro with a Glutathione-S-Transferase (GST) fusion tag. Future steps required to find the exact manner in which the GST fusion tag facilitated the association between ApoE and IFNγ are discussed with emphasis on the possible pitfalls associated with using fusion proteins for studying novel protein-protein interactions.

Osteocalcin (Oc) is the most abundant non-collagen protein found in the bone, but its precise function is still not completely understood. Three glutamic acid (Glu) residues within its sequence are sites for vitamin K-dependent post-translational modification, replacing a hydrogen with a carboxylate located at the γ-carbon position, converting these to γ-carboxyglutamic acid (Gla) residues. This modification confers increased binding of Oc to Ca2+ and hydroxyapatite matrix. Presented here, novel metal binding partners Mn2+, Fe3+, and Cr3+ of human Oc were determined, while the previously identified binders to (generally) non-human Oc, Ca2+, Mg2+, Pb2+ and Al3+ were validated as binders to human Oc by direct infusion mass spectrometry with all metals binding with higher affinity to the post-translationally modified form (Gla-Oc) compared to the unmodified form (Glu-Oc). Oc was also found to form pentamer (Gla-Oc) and pentamer and tetramer (Glu-Oc) homomeric self-assemblies in the absence of NaCl, which disassembled to monomers in the presence of near physiological Na+ concentrations. Additionally, Oc was found to form filamentous structures in vitro by negative stain TEM in the presence of increased Ca2+ titrations in a Gla- and pH-dependent manner. Finally, by combining circular dichroism spectroscopy to determine the fraction of Gla-Oc bound, and inductively-coupled plasma mass spectrometry to quantify total Al concentrations, the data were fit to a single-site binding model and the equilibrium dissociation constant for Al3+ binding to human Gla-Oc was determined (Kd = 1.0 ± 0.12 nM). Including citrate, a known competitive binder of Al3+, maintained Al in solution and enabled calculation of free Al3+ concentrations using a Matlab script to solve the complex set of linear equations. To further improve Al solubility limits, the pH of the system was lowered to 4.5, the pH during bone resorption. Complementary binding experiments with Glu-Oc were not possible due to the observed precipitation of Glu-Oc at pH 4.5, although qualitatively if Glu-Oc binds Al3+, it is with much lower affinity compared to Gla-Oc. Taken together, the results presented here further support the importance of post-translational modification, and thus adequate nutritional intake of vitamin K, on the binding and self-assembly properties of human Oc.

Glycans are complex biological sugar polymers that are commonly found covalently attached to proteins, lipids, and lipoproteins. About 50% of all mammalian proteins are glycosylated. Aberrant glycosylation is a hallmark of most types of cancer, and glycosylation changes that occur in this disease are known to facilitate tumor development. In this dissertation, a bottom-up approach to glycomics, “glycan node analysis”, which is a method based on glycan linkage analysis that quantifies unique glycan features, such as “core fucosylation”, “α2-6 sialylation”, “β1-6 branching”, and “bisecting GlcNAc”, as single analytical signals by gas chromatography-mass spectrometry (GC-MS), was applied to cancer cell lines, antibodies, extracellular vesicles, and low density lipoproteins to understand the mechanisms leading to aberrant glycosylation in cancer, and to understand the role of blood plasma glycan sialylation in cancer immunity. Specific tumor antigens such as β1-6-branching, β1-4-branching, bisecting GlcNAc, antennary fucosylation, and Tn antigen (GalNAc-Ser/Thr), were found to be regulated by IL-6 in HepG2 cells; fewer glycan features were regulated by IL-1β. Additionally, neuraminidase enzyme treatment of alpha-1 antitrypsin IgG demonstrates how glycan node analysis can be used to detect relative changes in “α2-6-sialylation” along with corresponding increases in terminal galactose. Extracellular vesicles (EVs) derived from metastatic and non-metastatic cancer cell lines displayed upregulated or downregulated expression of several specific glycan nodes, particularly 3-GlcNAc, which represents hyaluronic acid. EVs displayed several glycan features that distinguished them from the whole blood plasma glycome. These results were promising for developing new diagnostic strategies in cancer. A “liquid phase permethylation” procedure for glycan node analysis that does not require spin columns was applied for the first time to whole biological specimens, and it demonstrated potential clinical utility in detecting specific tumor antigens. Significantly different glycan node profiles were found among three cancer cell lines and in peripheral blood mononuclear cells from healthy donors. Changes in glycosylation and mechanisms regulating glycan changes were studied extensively in cancer cells. Subsequently, it is reported how glycosylation changes can have an impact in cancer immunity. A novel role for oxidized-desialylated low density lipoprotein in cancer immunity is reported, and its implications in cancer and atherosclerosis are discussed.

Air pollution has been linked to various health problems but how different air pollutants and exposure levels contribute to those diseases remain largely unknown. Researchers have mainly relied on data from government air monitoring stations to study the health effects of air pollution exposure. The limited information provided by sparse stations has low spatial and temporal resolution, which is not able to represent the actual exposure of individuals. A tool that can accurately monitor personal exposure provides valuable data for epidemiologists to understand the relationship between air pollution and certain diseases. It also allows individuals to be aware of any ambient air quality issues and prevent air pollution exposure. To build such a tool, sensors with features of fast response, small size, long lifetime, high sensitivity, high selectivity, and multi-analyte sensing are of great importance.

In order to meet these requirements, three generations of novel colorimetric sensors have been developed. The first generation is mosaic colorimetric sensors based on tiny sensor blocks and by detecting absorbance change after each air sample injection, the target analyte concentration can be measured. The second generation is a gradient-based colorimetric sensor. Lateral transport of analytes across the colorimetric sensor surface creates a color gradient that shifts along the transport direction over time, and the sensor tracks the gradient shift and converts it into analyte concentration in real-time. The third generation is gradient-based colorimetric arrays fabricated by inkjet-printing method that integrates multiple sensors on a miniaturized sensor chip. Unlike traditional colorimetric sensors, such as detection tubes and optoelectronic nose, that are typically for one-time use, the presented three generations of colorimetric sensors aim to continuously monitor multiple air pollutants and the sensor lifetime and fabrication methods have been improved over each generation. Ozone, nitrogen dioxide, formaldehyde and carbon monoxide are chosen as analytes of interest. The performance of sensors has been validated in the lab and field tests, proving the capability of the sensors to be used for personal exposure monitoring.

The highly specialized telomerase ribonucleoprotein enzyme is composed minimally of telomerase reverse transcriptase (TERT) and telomerase RNA (TR) for catalytic activity. Telomerase is an RNA-dependent DNA polymerase that syntheizes DNA repeats at chromosome ends to maintain genome stability. While TERT is highly conserved among various groups of species, the TR subunit exhibits remarkable divergence in primary sequence, length, secondary structure and biogenesis, making TR identification extremely challenging even among closely related groups of organisms.

A unique computational approach combined with in vitro telomerase activity reconstitution studies was used to identify 83 novel TRs from 10 animal kingdom phyla spanning 18 diverse classes from the most basal sponges to the late evolving vertebrates. This revealed that three structural domains, pseudoknot, a distal stem-loop moiety and box H/ACA, are conserved within TRs from basal groups to vertebrates, while group-specific elements emerge or disappear during animal TR evolution along different lineages.

Next the corn-smut fungus Ustilago maydis TR was identified using an RNA-immunoprecipitation and next-generation sequencing approach followed by computational identification of TRs from 19 additional class Ustilaginomycetes fungi, leveraging conserved gene synteny among TR genes. Phylogenetic comparative analysis, in vitro telomerase activity and TR mutagenesis studies reveal a secondary structure of TRs from higher fungi, which is also conserved with vertebrates and filamentous fungi, providing a crucial link in TR evolution within the opisthokonta super-kingdom.

Lastly, work by collabarotors from Texas A&M university and others identified the first bona fide TR from the model plant Arabidopsis thaliana. Computational analysis was performed to identify 85 novel AtTR orthologs from three major plant clades: angiosperms, gymnosperms and lycophytes, which facilitated phylogenetic comparative analysis to infer the first plant TR secondary structural model. This model was confirmed using site-specific mutagenesis and telomerase activity assays of in vitro reconstituted enzyme. The structures of plant TRs are conserved across land plants providing an evolutionary bridge that unites the disparate structures of previously characterized TRs from ciliates and vertebrates.

Cancer is a major public health challenge and the second leading cause of death in the United States. Large amount of effort has been made to achieve sensitive and specific detection of cancer, and to predict the course of cancer. Glycans are promising avenues toward the diagnosis and prognosis of cancer, because aberrant glycosylation is a prevalent hallmark of diverse types of cancer. A bottom-up “glycan node analysis” approach was employed as a useful tool, which captures most essential glycan features from blood plasma or serum (P/S) specimens and quantifies them as single analytical signals, to a lung cancer set from the Women Epidemiology Lung Cancer (WELCA) study. In addition, developments were performed to simplify a relatively cumbersome step involved in sample preparation of glycan node analysis. Furthermore, as a biomarker discovery research, one crucial concern of the glycan node analysis is to ensure that the specimen integrity has not been compromised for the employed P/S samples. A simple P/S integrity quality assurance assay was applied to the same sample set from WELCA study, which also afford the opportunity to evaluate the effects of different collection sites on sample integrity in a multisite clinical trial.

Here, 208 samples from lung cancer patients and 207 age-matched controls enrolled in the WELCA study were analyzed by glycan node analysis. Glycan features, quantified as single analytical signals, including 2-linked mannose, α2‐6 sialylation, β1‐4 branching, β1‐6 branching, 4-linked GlcNAc, and outer-arm fucosylation, exhibited abilities to distinguish lung cancer cases from controls and predict survival in patients.

To circumvent the laborious preparation steps for permethylation of glycan node analysis, a spin column-free (SCF) glycan permethylation procedure was developed, applicable to both intact glycan analysis or glycan node analysis, with improved or comparable permethylation efficiency relative to some widely-used spin column-based procedures.

Biospecimen integrity of the same set of plasma samples from WELCA study was evaluated by a simple intact protein assay (ΔS-Cysteinylated-Albumin), which quantifies cumulative exposure of P/S to thawed conditions (-30 °C). Notable differences were observed between different groups of samples with various initial handling/storage conditions, as well as among the different collection sites.

Exposure of blood plasma/serum (P/S) to thawed conditions, greater than -30°C, can produce biomolecular changes that misleadingly impact measurements of clinical markers within archived samples. Reported here is a low sample-volume, dilute-and-shoot, intact protein mass spectrometric assay of albumin proteoforms called “ΔS-Cys-Albumin” that quantifies cumulative exposure of archived P/S samples to thawed conditions. The assay uses the fact that S-cysteinylation (oxidation) of albumin in P/S increases to a maximum value when exposed to temperatures greater than -30°C. The multi-reaction rate law that governs this albumin S-cysteinylation formation in P/S was determined and was shown to predict the rate of formation of S-cysteinylated albumin in P/S samples—a step that enables back-calculation of the time at which unknown P/S specimens have been exposed to room temperature. To emphasize the capability of this assay, a blind challenge demonstrated the ability of ΔS-Cys-Albumin to detect exposure of individual and grouped P/S samples to unfavorable storage conditions. The assay was also capable of detecting an anomaly in a case study of nominally pristine serum samples collected under NIH-sponsorship, demonstrating that empirical evidence is required to guarantee accurate knowledge of archived P/S biospecimen storage history.

The ex vivo glycation of human serum albumin was also investigated showing that P/S samples stored above their freezing point leads to significant increases in glycated albumin. These increases were found to occur within hours at room temperature, and within days at -20 °C. These increases continued over a period of 1-2 weeks at room temperature and over 200 days at -20 °C, ultimately resulting in a doubling of glycated albumin in both healthy and diabetic patients. It was also shown that samples stored at lower surface area-to-volume ratios or incubated under a nitrogen atmosphere experienced less rapid glucose adduction of albumin—suggesting a role for oxidative glycation in the ex vivo glycation of albumin.