We have previously reported a high prevalence of H. pylori DNA in saliva. In this study, the cytotoxin genotypes of H. pylori strains from both stomach and saliva were compared in 31 patients with gastritis and peptic ulcer. The cagA, vacA m1, vacA m2, and vacA s1 genotypes were analyzed by PCR. The 417 bp PCR products from three patients were also subjected to DNA sequencing analysis. There was 95% agreement between stomach H. pylori isolates and their corresponding saliva DNA in at least one cytotoxin genotype; 86% agreement with two cytotoxin genotypes; 59% agreement with three cytotoxin genotypes; and 27% agreement with all four cytotoxin genotypes studied. DNA sequencing from three patients showed 78.0%, 64.0%, and 66.9% homology of H. pylori from both sources, respectively. The data suggest that more than one H. pylori strain may exist in the stomach and saliva in the same patient.

No description available.

Antimicrobial resistance (AMR) is a threat to global health, food security, and economic productivity. Infections caused by drug resistant Gram-negative pathogens, such as Escherichia coli, Pseudomonas aeruginosa, and Neisseria gonorrhoeae, are continuously becoming harder to treat due to limited treatment options and long turnaround times for culture-based phenotypic diagnosis. Alternatively, genotypic approaches that exploit whole genome sequencing have the potential to be faster and more accurate. Genotypic approaches rely on using bacterial genomes to predict AMR phenotypes. I generated a rules-based algorithm and machine learning models using known resistance determinants from bacterial genomes to predict resistance or susceptibility. I showed that machine learning was superior to a rules-based algorithm and achieved an average accuracy of 94% and 89% for E. coli and P. aeruginosa, respectively. These machine learning models identified novel AMR genotype-phenotype relationships between known resistance determinants and resistance phenotypes, which were experimentally validated. To identify the parameters that can improve machine learning models, I tested a variety of genetic features, algorithms, and evaluation metrics. I observed an intricate dependency between parameters for AMR prediction performance, illustrating that careful selection of parameters is required to generate accurate AMR prediction models. A limitation of this work was its prediction of resistance and susceptibility categories, as these are interpretations of minimum inhibitory concentrations defined by clinical breakpoint guidelines. Since multiple guidelines exist, these prediction models are not generalizable, so prediction of MIC values was explored. The average accuracy of my MIC prediction models was 86%, 41%, and 98% for E. coli, P. aeruginosa, and N. gonorrhoea, respectively. Despite the multifactorial and intricate nature of the resistome, I was able to accurately predict AMR phenotypes for many antibiotics for these pathogens. This is a step towards advanced diagnostic microbiology methods driven by genomics. / Thesis / Doctor of Philosophy (PhD) / Many surgeries, chemotherapy, and transplantation will be impossible if antibiotic resistance is not addressed. Antibiotic misuse, overuse, and time to definitive therapy exacerbate this global health problem. Phenotypic testing determines definitive therapy, but bacterial culturing is slow. A potentially faster and more accurate approach relies on sequencing the pathogen’s genome. I used machine learning to generate antibiotic resistance prediction models that achieved average accuracies of 94% and 89% for Escherichia coli and Pseudomonas aeruginosa, respectively. These models identified novel relationships between known resistance genes and resistance phenotypes, which were experimentally validated. Resistance and susceptibility are interpretations of a minimum inhibitory concentration (MIC) using a clinical breakpoint guideline. Since there are different guidelines, I generated MIC prediction models with average accuracies of 86%, 41%, and 98% for E. coli, P. aeruginosa, and Neisseria gonorrhoea, respectively. My findings work towards a world where clinical sequencing and genomics-based diagnostics are the gold standard.

Background: Unlike other non-hepatitis c viral infection, hepatitis c viral infection is a non-vaccine preventable disease. Thus, effective treatment is an important part in the prevention of complication of chronic hepatitis c infection. The viral genotype plays a significant role in the choice of treatment regimen. Aim: the purpose of this study is to estimate the prevalence of hepatitis c viral infection and the distribution of viral genotype in the US population. Methods: Diagnosis of Hepatitis C viral infection was made by assaying the blood specimen collected from the study participants using Ampiclor monitor (Roche Diagnostic System, Inc Branchburg NJ), and genotype determined from the NS5b region. The data is from NHANSE 2006-2016. SAS v 9.4 software was used to perform the analysis. Results: Of the 356 participants (2006-2016) who tested positive to Hepatitis C virus-RNA, 205 persons had genotype 1a, 1b (n=66), other forms of genotype 1 (n=1), genotype 2(n=41), genotype 3 (n=30), genotype 4 (n=1), genotype 6(n=1), undetermined genotype (n=8). Based on weighted analysis of person infected with genotype 1, 2, 3; genotype 1 was highest across all ages and gender (78.2%). Of 271 participants infected with genotype 1, there were 5.09% Mexican Americans, 3.94% other Hispanics, 56.58% non-Hispanic whites, 28.74% non-Hispanic black, and 5.65% other races including multiracial population. Subjects aged 50 years or above was 27.7% less likely being infected with HCV genotype 1 vs 2 and 3, compared with younger individuals (adjusted Odds Ratio (95% confidence interval) (aOR): 0.72 (0.72-0.73)). Non-Hispanic black were about 13 times (aOR: 13.1 (13.0-13.2)) as likely to be infected with genotype 1 vs 2 and 3 as non-Hispanic white. Conclusion: Hepatitis C virus genotype 1 is predominant among those infected with hepatitis c virus in the US population. Improvement in therapy targeting genotype 1 is essential to reduce the burden and complication of chronic hepatitis C in the United States.

No / Symptoms and signs (symptoms in brief) are the essential clinical manifestations for traditional Chinese medicine (TCM) diagnosis and treatments. To gain insights into the molecular mechanism of symptoms, this paper presents a network-based data mining method to integrate multiple phenotype-genotype data sources and predict the prioritizing gene rank list of symptoms. The result of this pilot study suggested some insights on the molecular mechanism of symptoms.

Genetic predisposition to obesity presents a paradox: how do genetic variants with such a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, for instance the thrifty genotype hypothesis, attempt to explain this phenomenon, yet fail to provide a satisfying answer to the modern obesity epidemic. In this critical review, I appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change that may help explain the distribution of obesity and leanness predisposing variants in modern human populations. Gene pleiotropy and adaptations to diverse environmental niches may explain the rise and subsequent selection of obesity risk alleles. The regulation of gene expression by epigenetic mechanisms may serve as a stochastic factor affecting the manifestation of obesity phenotypes. Finally, exposure to malnutrition and disease epidemics in the wake of colonialism, culturally mediated notions of attractiveness and desirability, and diverse mating systems – including forced copulation, consanguinity and polygamy – may play a role in shaping the human genome. In short, I posit that in order to explain ethnic variation in obesity susceptibility, we must examine the origin of physiological adaptations and understand the sociocultural experiences of individuals and populations. As an imperative first step towards the identification of important drivers of obesity gene evolution, this review will inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling. Ultimately, these data will promote a better understanding of the aetiology of obesity and are expected to guide the development of targeted management, treatment, and prevention strategies. / Thesis / Master of Science (MSc)

No description available.

The purported chemopreventive and chemotherapeutic properties of the dietary phytochemical resveratrol continue to undergo active investigations. Systemic pharmacokinetics of this compound revealed that it was rapidly and extensively metabolized into its sulfate and glucuronide conjugates. This extensive metabolism leads to high plasma levels of resveratrol sulfates and glucuronides and very low levels of the parent compound (low bioavailability). These observations raised many questions, some of which this body of work examined and has helped to explain. Chapter 1 presents a detailed introduction to resveratrol and its role in colorectal cancer chemoprevention. It also lays the foundation for the hypotheses generated and the studies presented in succeeding chapters. In chapter 2, we explored the possibility that resveratrol metabolites possess intrinsic activity and thus contribute to the observed effects of the parent. The mono-sulfated and glucuronidated conjugates of trans-resveratrol were synthesized and tested for antiproliferative activity in a panel of mammalian cell lines. Their activity was then compared with the parent compound. Resveratrol was shown to be antiproliferative in all cell lines studied while no discernible antiproliferative activity was observed for the metabolites. Chapter 3 details the results of the glucuronidation kinetics of cis and trans-resveratrol isomers across a wide concentration range chosen to mimic blood levels following high dose consumption. Human tissue microsomes and recombinant supersomes over-expressing the enzymes (UGTs) of interest were used for these studies. Our results show the presence of atypical kinetics for the formation of resveratrol glucuronides across most of the protein sources used. Prior to this study, the full glucuronidation kinetics of total resveratrol had not been conducted. In chapter 4, we examined the association between genetic polymorphisms in the major enzymes (UGT1A1 and UGT1A6) and rates of glucuronidation of trans and cis-resveratrol. We set out to correlate functional genetic variations in these UGTs with their catalytic rates and a positive association was made for cis-resveratrol and UGT1A6 where the UGT1A6 variants mediated higher glucuronidation rates compared to the reference genotype. Chapter 5 explored the inherent ability of resveratrol to induce its own glucuronidation upon chronic dosing. Enzyme induction has been proposed as a mechanism that may contribute to the low bioavailability of resveratrol. Since dietary polyphenols like resveratrol are not consumed in isolation, we also studied the effects of combining resveratrol with two dietary polyphenols (curcumin and chrysin) on two chemoprevention endpoints - i) antiproliferation and ii) UGT enzyme induction. Our results indicate that resveratrol is capable of inducing UGT1A1 expression and activity in a non-concentration dependent manner and this induction as well as its antiproliferative effects are enhanced by both curcumin and chrysin. In summary, en route to probing the activity of resveratrol metabolites, we optimized two synthetic routes and generated measurable quantities of these compounds for future use. While the in vitro kinetics of resveratrol did not allow for any in vivo predictions, we were able to show alterations in resveratrol metabolism with respect to genotypic differences and enzyme induction that may contribute to the observed low bioavailability profile. / Pharmaceutical Sciences

Autism is a severe developmental disorder characterized by impairments in reciprocal social interaction and communication, coupled with repetitive stereotypic activities. Evidence from twin and family studies strongly suggest that genetic factors play a significant role in the etiology of autism. The factors involved in the development of autism are also thought to underlie related pervasive developmental disorders (PDD). The affected sib-pair method was used to screen nine autosomal candidate loci in 18 families, each of which have two or more children with autism or a related PDD. Candidate loci were selected on the basis that: (1) the locus is near genetic disorders or chromosomal abnormalities found to co-occur with autism; and/or (2) the gene encodes a protein which has been speculated to play a role in the pathophysiology of autism. Genotypes of the affected children and their parents were determined for the following microsatellite markers which are tightly linked to the candidate genes/regions: 13S118, DRD2, TH, HRAS-1, 22S343, D15S11, GABRB3, 16S291, and DBH. No significant concordance between affected siblings was observed for any of the loci tested. During the study, however, many of the families were found to be uninformative at the dopamine beta hydroxylase (DBH) microsatellite locus. A comparsion of DBH allele frequencies observed in the parents to published British values revealed a significant difference between the two groups (L2=13.16, df=5, p<0.05). Given this finding, and the knowledge that serum DBH activity is largely under the control of DNA sequences in or close to the DBH gene, serum DBH activities were measured in the parents and in an adult control group. Mean serum DBH activity was found to be significantly lower in parents with two autistic/PDD children compared to an adult control group (Student's t=-1.71, df=60, p<0.05). DBH alleles are defined by a polymorphic dinucleotide repeat and the presence or absence of a 19 bp sequence. Upon further analysis the frequency of alleles in which the 19 bp sequence is deleted was found to be significantly increased in the mothers with two autistic/PDD children, compared to both published frequencies (L2=11.99, df=1, p<0.001) and to a Canadian control group (L2=6.96, df=1, p<0.01). Subsequent investigation revealed that deletion of the 19 bp sequence is associated with lower mean serum DBH enzyme activity (nondeletion homozygotes 44.5±28.6 iu/L; heterozygotes 30.4±16.0 iu/L; and deletion homozygotes 20.5±15.3 iu/L; F=5.45, df=59, p<0.01). Based on these findings it is proposed that lowered maternal serum DBH activity provides a uterine environment which, in conjunction with genotypic susceptiblity of a fetus, results in autism or a related PDD. / Thesis / Master of Science (MS)

Hepatitis E virus (HEV), the causative agent of hepatitis E, is endemic in many developing countries. However, sporadic cases of acute hepatitis E have also been reported in industrialized countries including the United States. Increasing evidence suggested that hepatitis E is zoonotic. Swine HEV was discovered in 1997 from a pig in the United States and has the ability to cross species barrier and infect humans. There are four major genotypes of HEV worldwide and swine HEV identified to date in different countries belongs to either genotypes 3 or 4. Thus far, genotypes 1 (Asian strains) and 2 (a single Mexican strain) of HEV are exclusively found in humans. To determine if genotypes 1 and 2 of HEV also exist in pigs we tested serum and/or fecal samples for from pigs of different age groups in Thailand, and from pigs 2-4 months-of-age in two states (Sonora, Sinaloa) in Mexico. A universal RT-PCR was first standardized to detect all 4 different genotypes of HEV. Swine HEV RNA was detected from in 10/26 pigs at 2-4 months-of-age but not in pigs of 1-, 6-month old, adult/sow pigs from Thailand. In Mexico, swine HEV RNA was detected in 8 of 125 serum samples, 28 of 92 fecal samples of 2-4 month-old pigs. Antibodies to swine HEV were detected in 101 of 125 (80.8%) Mexican pigs. A total of 44 swine HEV isolates were amplified and sequenced for the ORF2 capsid gene region. Sequence analyses revealed that all the swine HEV isolates identified from pigs in Thailand and Mexico belong to genotype 3. Overall, the Mexican swine HEV isolates shared 89-100% sequence identity to each other, and about 89-92% identity with the prototype genotype 3 US swine HEV. The Thailand swine HEV isolates displayed 97-100% nucleotide sequence identity with each other, and 90-91% identity with the prototype genotype 3 swine HEV. Phylogenic analysis revealed that minor branches do exist among Mexican swine HEV isolates. The results from this study indicated that genotype 1 or 2 swine HEV does not exist in pig from countries where human genotypes 1 and 2 HEVs are prevalent. / Master of Science