Identification of markers to characterize and sort human articular chondrocytes with enhanced in vitro chondrogenic capacity

OBJECTIVE: To identify markers associated with the chondrogenic capacity of expanded human articular chondrocytes and to use these markers for sorting of more highly chondrogenic subpopulations. METHODS: The chondrogenic capacity of chondrocyte populations derived from different donors (n = 21) or different clonal strains from the same cartilage biopsy specimen (n = 21) was defined based on the glycosaminoglycan (GAG) content of tissues generated using a pellet culture model. Selected cell populations were analyzed by microarray and flow cytometry. In some experiments, cells were sorted using antibodies against molecules found to be associated with differential chondrogenic capacity and again assessed in pellet cultures. RESULTS: Significance Analysis of Microarrays indicated that chondrocytes with low chondrogenic capacity expressed higher levels of insulin-like growth factor 1 and of catabolic genes (e.g., matrix metalloproteinase 2, aggrecanase 2), while chondrocytes with high chondrogenic capacity expressed higher levels of genes involved in cell-cell or cell-matrix interactions (e.g., CD49c, CD49f). Flow cytometry analysis showed that CD44, CD151, and CD49c were expressed at significantly higher levels in chondrocytes with higher chondrogenic capacity. Flow cytometry analysis of clonal chondrocyte strains indicated that CD44 and CD151 could also identify more chondrogenic clones. Chondrocytes sorted for brighter CD49c or CD44 signal expression produced tissues with higher levels of GAG per DNA (up to 1.4-fold) and type II collagen messenger RNA (up to 3.4-fold) than did unsorted cells. CONCLUSION: We identified markers that allow characterization of the capacity of monolayer-expanded chondrocytes to form in vitro cartilaginous tissue and enable enrichment for subpopulations with higher chondrogenic capacity. These markers might be used as a means to predict and possibly improve the outcome of cell-based cartilage repair techniques.

Identification of polymorphisms in the human 11beta-hydroxysteroid dehydrogenase type 2 gene promoter: functional characterization and relevance for salt sensitivity

Reduced activity of 11beta-hydroxysteroid dehydrogenase type 2 (11beta-HSD2) plays a role in essential hypertension and the sensitivity of blood pressure to dietary salt. Nonconservative mutations in the coding region are extremely rare and do not explain the variable 11beta-HSD2 activity. We focused therefore on the 5'-regulatory region and identified and characterized the first promoter polymorphisms. Transfections of variants G-209A and G-126A into SW620 cells reduced promoter activity and affinity for activators nuclear factor 1 (NF1) and Sp1. Chromatin immunoprecipitation revealed Sp1, NF1, and glucocorticoid receptor (GR) binding to the HSD11B2 promoter. Dexamethasone induced expression of mRNA and activity of HSD11B2. GR and/or NF1 overexpression increased endogenous HSD11B2 mRNA and activity. GR complexes cooperated with NF1 to activate HSD11B2, an effect diminished in the presence of the G-209A variant. When compared to salt-resistant subjects (96), salt-sensitive volunteers (54) more frequently had the G-209A variant, higher occurrence of alleles A4/A7 of polymorphic microsatellite marker, and higher urinary ratios of cortisol to cortisone metabolites. First, we conclude that the mechanism of glucocorticoid-induced HSD11B2 expression is mainly mediated by cooperation between GR and NF1 on the HSD11B2 promoter and, second, that the newly identified promoter variants reduce activity and cooperation of cognate transcription factors, resulting in diminished HSD11B2 transcription, an effect favoring salt sensitivity.

Identification and characterization of a novel RPGR isoform in human retina

Retinitis pigmentosa (RP) constitutes a major cause of blindness and the Retinitis Pigmentosa GTPase Regulator (RPGR) gene accounts for up to 80% of all X-linked RP cases. A novel isoform of RPGR, expressed in the human retina, was identified and characterized. It truncates the Regulator of Chromosome Condensation 1 (RCC1) homologous protein domain (RCC1h) of RPGR and mediates the formation of isoform-specific complexes with the RPGR-interacting protein 1 (RPGRIP1). Immunohistochemistry localized the novel RPGR isoform predominantly to inner segments of cone photoreceptors, where it colocalizes with RPGRIP1 in the human retina. In a patient with a mild RP phenotype, we identified a nucleotide substitution in a splicing regulator, which leads to 3.5 times higher levels of the transcripts coding for the novel RPGR isoform. The nucleotide substitution affects regulated alternative splicing of the novel RPGR isoform and suggests a tight adjustment of splicing as a prerequisite for proper function of photoreceptors.

Screening, optimization and extraction of polyhydroxyalkanoates and peptidoglycan from Bacillus megaterium

Bioplastics are polymers (such as polyesters) produced from bacterial fermentations that are biodegradable and nonhazardous. They are produced by a wide variety of bacteria and are made only when stress conditions allow, such as when nutrient levels are low, more specifically levels of nitrogen and oxygen. These stress conditions cause certain bacteria to build up excess carbon deposits as energy reserves in the form of polyhydroxyalkanoates (PHAs). PHAs can be extracted and formed into actual plastic with the same strength of conventional, synthetic-based plastics without the need to rely on foreign petroleum. The overall goal of this project was to select for a bacteria that could grow on sugars found in the lignocellulosic biomass, and get the bacteria to produce PHAs and peptidoglycan. Once this was accomplished the goal was to extract PHAs and peptidoglycan in order to make a stronger more rigid plastic, by combing them into a co-polymer. The individual goals of this project were to: (1) Select and screen bacteria that are capable of producing PHAs by utilizing the carbon/energy sources found in lignocellulosic biomass; (2) Maximize the utilization of those sugars present in woody biomass in order to produce optimal levels of PHAs. (3) Use room temperature ionic liquids (RTILs) in order to separate the cell membrane and peptidoglycan, allowing for better extraction of PHAs and more intact peptidoglycan. B. megaterium a Gram-positive PHA-producing bacterium was selected for study in this project. It was grown on a variety of different substrates in order to maximize both its growth and production of PHAs. The optimal conditions were found to be 30°C, pH 6.0 and sugar concentration of either 30g/L glucose or xylose. After optimal growth was obtained, both RTILs and enzymatic treatments were used to break the cell wall, in order to extract the PHAs, and peptidoglycan. PHAs and peptidoglycan were successfully extracted from the cell, and will be used in the future to create a new stronger co-polymer. Peptidoglycan recovery yield was 16% of the cells’ dry weight.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Rapid screening for carriage of methicillin-resistant Staphylococcus aureus by PCR and associated costs

PCR tests for the rapid and valid detection of methicillin-resistant Staphylococcus aureus (MRSA) are now available. We evaluated the costs associated with contact screening for MRSA carriage in a tertiary-care hospital with low MRSA endemicity. Between 1 October 2005 and 28 February 2006, 232 patients were screened during 258 screening episodes (644 samples) for MRSA carriage by GenoType MRSA Direct (Hain Lifescience GmbH, Nehren, Germany). Conventional culture confirmed all PCR results. According to in-house algorithms, 34 of 258 screening episodes (14.7%) would have qualified for preemptive contact isolation, but such isolation was not done upon negative PCR results. MRSA carriage was detected in 4 (1.5%) of 258 screening episodes (i.e., in four patients), of which none qualified for preemptive contact isolation. The use of PCR for all 258 screening episodes added costs (in Swiss francs [CHF]) of CHF 104,328.00 and saved CHF 38,528.00 (for preemptive isolation). The restriction of PCR screening to the 34 episodes that qualified for preemptive contact isolation and screening all others by culture would have lowered costs for PCR to only CHF 11,988.00, a savings of CHF 38,528.00. Therefore, PCR tests are valuable for the rapid detection of MRSA carriers, but high costs require the careful evaluation of their use. In patient populations with low MRSA endemicity, the broad use of PCR probably is not cost-effective.

Identification of pathogen and host-response markers correlated with periodontal disease

BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.