Acid maltase deficiency (AMD) is a rare autosomal recessive genetic disorder that results in an accumulation of glycogen in the lysosomal storage vacuoles. It is classified as a glycogen storage disease (type II) and is also known as Pompe's disease. The prognosis of the patient with AMD is poor and the main cause of death is respiratory failure. We report a female patient whose respiratory insufficiency was documented to occur most severely during rapid eye movement sleep and who benefited clinically from the institution of nocturnal noninvasive bilevel positive airway pressure.

Indiana University-Purdue University Indianapolis (IUPUI) / Signal Transducer and Activator of Transcription 3 (STAT3) is known to be related to bone metabolism. Mutation of STAT3 causes a rare disorder in which serum levels of IgE are elevated. This causes various skeletal problems similar to osteoporosis. To examine the effect of STAT3 in the osteoclast, we obtained two osteoclast specific STAT3 knockout mouse models: one using the CTSK promoter to drive Cre recombinase and another using a TRAP promoter. Examination of these mice at 8 weeks of age revealed a decreased trabecular bone volume in CTSK specific STAT3 knockout mice along with a slight decrease in osteoclast number in both CTSK and TRAP specific STAT3 knockout females. We also noticed changes in bone mineral density and bone mechanical strength in females. These data suggest that STAT3 plays a part in the function of the osteoclast.

Indiana University-Purdue University Indianapolis (IUPUI) / Several common diseases such as atherosclerosis, post-angioplasty restenosis, and graft vasculopathies, are associated with the changes in the structure and function of smooth muscle cells. During the pathogenesis of these diseases, smooth muscle cells have a marked alteration in the expression of many smooth muscle-specific genes and smooth muscle cells undergo a phenotypic switch from the contractile/differentiated status to the proliferative/dedifferentiated one. Serum response factor (SRF) is the major transcription factor that plays an essential role in coordinating a variety of transcriptional events during this phenotypic change. The first goal of my thesis studies is to determine how SRF regulates the expression of smooth muscle myosin light chain kinase (smMLCK) to mediate changes in contractility. Using a combination of transgenic reporter mouse and knockout mouse models I demonstrated that a CArG element in intron 15 of the mylk1 gene is necessary for maximal transcription of smMLCK. SRF binding to this CArG element modulates the expression of smMLCK to control smooth muscle contractility. A second goal of my thesis work is to determine how SRF coordinates the activity of chromatin remodeling enzymes to control expression of microRNAs that regulate the phenotypes of smooth muscle cells. Using both mouse knockout models and in vitro studies in cultured smooth muscle cells I showed how SRF acts together with Brg1-containing chromatin remodeling complexes to regulate expression of microRNAs-143, 145, 133a and 133b. Moreover, I found that SRF transcription cofactor myocardin acts together with SRF to regulate expression of microRNAs-143 and 145 but not microRNAs-133a and 133b. SRF can, thus, further modulate gene expression through post-transcriptional mechanisms via changes in microRNA levels. Overall my research demonstrates that through direct interaction with a CArG box in the mylk1 gene, SRF is important for regulating expression of smMLCK to control smooth muscle contractility. Additionally, SRF is able to harness epigenetic mechanisms to modulate expression of smooth muscle contractile protein genes directly and indirectly via changes in microRNA expression. Together these mechanisms permit SRF to coordinate the complex phenotypic changes that occur in smooth muscle cells.

Safety concerns arising from cytotoxic behavior of nanoparticles (NPs) in complex biological environment remain the main problem limiting NPs application in biomedicine. In this study, we have investigated cytotoxicity of NPs with different composition, shape and size, namely SiO2 NPs (SiNPs, 7-14 nm), superparamagnetic iron oxide NPs (SPIONs, 8 nm) and carboxylated multiwalled carbon nanotubes (CNTCOOHs, diameter: 60-100 nm, length: 1-2 μm). Cytotoxicity was evaluated with newly designed screening assay capable to simultaneously assess activity of cell dehydrogenases, activity of lactate dehydrogenase (LDH) released from cells into environment and number of intact cell nuclei and apoptotic bodies in human umbilical vein endothelial cell (HUVEC) culture growing in the very same well of the 96-well plate. Aforementioned attributes were subsequently utilized to obtain information about cell viability and necrotic and apoptotic aspects of cell death. Results from this "three-in-one" cell death screening (CDS) assay showed that SiNPs and CNTCOOHs evoked pronounced cytotoxic effect demonstrated as decrease of cell viability and development of apoptotic bodies formation. In contrast to this, SPIONs induced only mild cytotoxicity. Moreover, SiNPs impaired cell membrane leading to increased LDH release...

Affinity-based proteomics utilizes affinity binders to detect target proteins in a large-scale manner. This thesis describes a high-throughput method, which enables the search for biomarker candidates in human plasma and serum. A highly multiplexed antibody-based suspension bead array is created by coupling antibodies generated in the Human Protein Atlas project to color-coded beads. The beads are combined for parallel analysis of up to 384 analytes in patient and control samples. This provides data to compare protein levels from the different groups. In paper I osteoporosis patients are compared to healthy individuals to find disease-linked proteins. An untargeted discovery screening was conducted using 4608 antibodies in 16 cases and 6 controls. This revealed 72 unique proteins, which appeared differentially abundant. A validation screening of 91 cases and 89 controls confirmed that the protein autocrine motility factor receptor (AMFR) is decreased in the osteoporosis patients. Paper II investigates the risk proteome of inflammatory bowel disease (IBD). Antibodies targeting 209 proteins corresponding to 163 IBD genetic risk loci were selected. To find proteins related to IBD or its subgroups, sera from 49 patients with Crohn’s disease, 51 with ulcerative colitis and 50 matched controls were analyzed. From these targeted assays, the known inflammation-related marker serum amyloid protein A (SAA) was shown to be elevated in the IBD cases. In addition, the protein laccase (multi-copper oxidoreductase) domain containing 1 (LACC1) was found to be decreased in the IBD subjects. In conclusion, assays using affinity-based bead arrays were developed and applied to screen human plasma and serum samples in two disease contexts. Untargeted and targeted screening strategies were applied to discover disease-associated proteins. Upon further validation, these potential biomarker candidates could be valuable in future disease studies. / <p>QC 20180412</p>

Non-resolving inflammation plays a critical role during the transition from renal injury towards end-stage renal disease. The glucocorticoid-inducible protein annexin A1 has been shown to function as key regulator in the resolution phase of inflammation, but its role in immune-mediated crescentic glomerulonephritis has not been studied so far. Methods: Acute crescentic glomerulonephritis was induced in annexin A1-deficient and wildtype mice using a sheep serum against rat glomerular basement membrane constituents. Animals were sacrificed at d5 and d10 after nephritis induction. Renal leukocyte abundance was studied by immunofluorescence and flow cytometry. Alterations in gene expression were determined by RNA-Seq and gene ontology analysis. Renal levels of eicosanoids and related lipid products were measured using lipid mass spectrometry. Results: Histological analysis revealed an increased number of sclerotic glomeruli and aggravated tubulointerstitial damage in the kidneys of annexin A1-deficient mice compared to the wildtype controls. Flow cytometry analysis confirmed an increased number of CD45+ leukocytes and neutrophil granulocytes in the absence of annexin A1. Lipid mass spectrometry showed elevated levels of prostaglandins PGE2 and PGD2 and reduced levels of antiinflammatory epoxydocosapentaenoic acid regioisomers. RNA-Seq with subsequent gene ontology analysis revealed induction of gene products related to leukocyte activation and chemotaxis as well as regulation of cytokine production and secretion. Conclusion: Intrinsic annexin A1 reduces proinflammatory signals and infiltration of neutrophil granulocytes and thereby protects the kidney during crescentic glomerulonephritis. The annexin A1 signaling cascade may therefore provide novel targets for the treatment of inflammatory kidney disease.

The open nature of Cell-Free Protein Synthesis (CFPS) systems has enabled flexible design, easy manipulation, and novel applications of protein engineering in therapeutic production, biocatalysis, and biosensors. This dissertation reports on three advances in the application of CFPS systems for 1) improving biocatalysis performance in industrial applications by site-specific covalent enzyme immobilization, 2) expressing and optimizing a difficult to express a mammalian protein in bacterial-based CFPS systems and its application for cost-effective, on-demand biosensors compatible with human body fluids, and 3) streamlining the procedure of an E. coli extract with built-in compatibility with human body fluid biosensors. Site-specific covalent immobilization stabilizes enzymes and facilitates recovery and reuse of enzymes which improves the net profit margin of industrial enzymes. Yet, the suitability of a given site on the enzyme for immobilization remains a trial-and-error procedure. This dissertation reports the reliability of several design heuristics and a coarse-grain molecular simulation in predicting the optimum sites for covalent immobilization of a target enzyme, TEM-1 ?-lactamase. This work demonstrates that the design heuristics can successfully identify a subset of favorable locations for experimental validation. This approach highlights the advantages of combining coarse-grain simulation and high-throughput experimentation using CFPS to efficiently identify optimal enzyme immobilization sites. Additionally, this dissertation reports high-yield soluble expression of a difficult-to-express protein (murine RNase Inhibitor or m-RI) in E. coli-lysate-based CFPS. Several factors including reaction temperature, reaction time, redox potential, and presence of folding chaperones in CFPS reactions were altered to find suitable conditions for m-RI expression. m-RI with the highest activity and stability was used to develop a lyophilized CFPS biosensor in human body fluids which reduced the cost of biosensor test by ~90%. Moreover, an E. coli extract with RNase inhibition activity was developed and tested which further streamlines the production of CFPS biosensors compatible with human body fluids.

The aim of this project has been to investigate whether there are correlations to be found between gut microbes and serum metabolites, which could be involved in the development of epilepsy. To do so, metabolomics data containing metabolites and metagenomics data containing bacteria have been integrated and used in a pipeline utilizing the software package DIABLO in R Studio. DIABLO stands for Data Integration Analysis for Biomarker discovery using Latent cOmponents and utilizes multi-block pls-da to integrate multiple omics data sets to find potential biomarkers. The results in this project are mainly divided into two groups, the first group being from taking samples at an early time point, where subjects have not yet developed symptoms of epilepsy and the second group being from taking samples at a late time point, where the subjects have developed epilepsy. To find biomarkers in the data used for the integration, two subgroups are of highest interest, namely subgroup PTE, which is the group that develops epilepsy symptoms after an induced trauma to the brain, as well as subgroup TBI which do not develop epilepsy symptoms after an induced trauma to the brain. Results from the early time point suggests that bacteria such as those from Phelethenecus, Christenselellales, Ventrimonas, Ruminococcaceae and Acetatifactor, as well as metabolites such as LPC 17:0, Indole and Indole-3-carboxyaldehyde might be of interest in finding biomarkers previous to the development of epilepsy after induced brain trauma.  Results from the late time point suggests that bacteria such as those from Muribaculaceae and Avidehalobacter, as well as metabolites such as Dioctyl sulfosuccinate, Canrenone, LPC 18:0, Uric acid, Arjunolic acid and Pseudouridine might be of interest in finding underlying mechanisms behind the existing condition of epilepsy. The hope is that findings in this paper might aid in future development of knowledge behind this disease as well as its underlying mechanisms.

Metabolomics is the methodical scientific study of biochemical processes associated with the metabolome—which comprises the entire collection of metabolites in any biological entity. Metabolome changes occur as a result of modifications in the genome and proteome, and are, therefore, directly related to cellular phenotype. Thus, metabolomic analysis is capable of providing a snapshot of cellular physiology. Untargeted metabolomics is an impartial, all-inclusive approach for detecting as many metabolites as possible without a priori knowledge of their identity. Hence, it is a valuable exploratory tool capable of providing extensive chemical information for discovery and hypothesis-generation regarding biochemical processes. A history of metabolomics and advances in the field corresponding to improved analytical technologies are described in Chapter 1 of this dissertation. Additionally, Chapter 1 introduces the analytical workflows involved in untargeted metabolomics research to provide a foundation for Chapters 2 – 5. Part I of this dissertation which encompasses Chapters 2 – 3 describes the utilization of mass spectrometry (MS)-based untargeted metabolomic analysis to acquire new insight into cancer detection. There is a knowledge deficit regarding the biochemical processes of the origin and proliferative molecular mechanisms of many types of cancer which has also led to a shortage of sensitive and specific biomarkers. Chapter 2 describes the development of an in vitro diagnostic multivariate index assay (IVDMIA) for prostate cancer (PCa) prediction based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) metabolic profiling of blood serum samples from 64 PCa patients and 50 healthy individuals. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent prostate-specific antigen blood test, thus, highlighting that a combination of multiple discriminant features yields higher predictive power for PCa detection than the univariate analysis of a single marker. Chapter 3 describes two approaches that were taken to investigate metabolic patterns for early detection of ovarian cancer (OC). First, Dicer-Pten double knockout (DKO) mice that phenocopy many of the features of metastatic high-grade serous carcinoma (HGSC) observed in women were studied. Using UPLC-MS, serum samples from 14 early-stage tumor DKO mice and 11 controls were analyzed. Iterative multivariate classification selected 18 metabolites that, when considered as a panel, yielded 100% accuracy, sensitivity, and specificity for early-stage HGSC detection. In the second approach, serum metabolic phenotypes of an early-stage OC pilot patient cohort were characterized. Serum samples were collected from 24 early-stage OC patients and 40 healthy women, and subsequently analyzed using UPLC-MS. Multivariate statistical analysis employing support vector machine learning methods and recursive feature elimination selected a panel of metabolites that differentiated between age-matched samples with 100% cross-validated accuracy, sensitivity, and specificity. This small pilot study demonstrated that metabolic phenotypes may be useful for detecting early-stage OC and, thus, supports conducting larger, more comprehensive studies. Many challenges exist in the field of untargeted metabolomics. Part II of this dissertation which encompasses Chapters 4 – 5 focuses on two specific challenges. While metabolomic data may be used to generate hypothesis concerning biological processes, determining causal relationships within metabolic networks with only metabolomic data is impractical. Proteins play major roles in these networks; therefore, pairing metabolomic information with that acquired from proteomics gives a more comprehensive snapshot of perturbations to metabolic pathways. Chapter 4 describes the integration of MS- and NMR-based metabolomics with proteomics analyses to investigate the role of chemically mediated ecological interactions between Karenia brevis and two diatom competitors, Asterionellopsis glacialis and Thalassiosira pseudonana. This integrated systems biology approach showed that K. brevis allelopathy distinctively perturbed the metabolisms of these two competitors. A. glacialis had a more robust metabolic response to K. brevis allelopathy which may be a result of its repeated exposure to K. brevis blooms in the Gulf of Mexico. However, K. brevis allelopathy disrupted energy metabolism and obstructed cellular protection mechanisms including altering cell membrane components, inhibiting osmoregulation, and increasing oxidative stress in T. pseudonana. This work represents the first instance of metabolites and proteins measured simultaneously to understand the effects of allelopathy or in fact any form of competition. Chromatography is traditionally coupled to MS for untargeted metabolomics studies. While coupling chromatography to MS greatly enhances metabolome analysis due to the orthogonality of the techniques, the lengthy analysis times pose challenges for large metabolomics studies. Consequently, there is still a need for developing higher throughput MS approaches. A rapid metabolic fingerprinting method that utilizes a new transmission mode direct analysis in real time (TM-DART) ambient sampling technique is presented in Chapter 5. The optimization of TM-DART parameters directly affecting metabolite desorption and ionization, such as sample position and ionizing gas desorption temperature, was critical in achieving high sensitivity and detecting a broad mass range of metabolites. In terms of reproducibility, TM-DART compared favorably with traditional probe mode DART analysis, with coefficients of variation as low as 16%. TM-DART MS proved to be a powerful analytical technique for rapid metabolome analysis of human blood sera and was adapted for exhaled breath condensate (EBC) analysis. To determine the feasibility of utilizing TM-DART for metabolomics investigations, TM-DART was interfaced with traveling wave ion mobility spectrometry (TWIMS) time-of-flight (TOF) MS for the analysis of EBC samples from cystic fibrosis patients and healthy controls. TM-DART-TWIMS-TOF MS was able to successfully detect cystic fibrosis in this small sample cohort, thereby, demonstrating it can be employed for probing metabolome changes. Finally, in Chapter 6, a perspective on the presented work is provided along with goals on which future studies may focus.

Recombinant human bone morphogenic proteins (rhBMPs) are extensively studied and employed clinically for treatment of various bone defects. Current clinical delivery vehicles suffer wasteful burst releases that mandate supra-physiological dosing driving concerns over safety and cost. It was therefore investigated whether a unique drug delivery vehicle sequestered within a composite scaffold could lower the burst release of rhBMP-2. PLGA-calcium phosphate tri-phasic composite scaffolds delivered model protein BSA with burst release of ~13% and sustained kinetics of 0.5-1.5% BSA/day up to 45 days. rhBMP-2 was delivered with zero burst release however at much lower levels, totaling 0.09% to 0.9 % release over 10 days, but had up to 6.3-fold greater bioactivity than fresh rhBMP-2 (p<0.05). In conclusion, the three-phase composite scaffold can deliver bioactive proteins with a reduced burst release and sustained secondary kinetics.