ASU Scholarship Showcase

Background: The success of new sequencing technologies and informatic methods for identifying genes has made establishing gene product function a critical rate limiting step in progressing the molecular sciences. We present a method to functionally mine genomes for useful activities in vivo, using an unusual property of a member of the poxvirus family to demonstrate this screening approach.

Results: The genome of Parapoxvirus ovis (Orf virus) was sequenced, annotated, and then used to PCR-amplify its open-reading-frames. Employing a cloning-independent protocol, a viral expression-library was rapidly built and arrayed into sub-library pools. These were directly delivered into mice as expressible cassettes and assayed for an immune-modulating activity associated with parapoxvirus infection. The product of the B2L gene, a homolog of vaccinia F13L, was identified as the factor eliciting immune cell accumulation at sites of skin inoculation. Administration of purified B2 protein also elicited immune cell accumulation activity, and additionally was found to serve as an adjuvant for antigen-specific responses. Co-delivery of the B2L gene with an influenza gene-vaccine significantly improved protection in mice. Furthermore, delivery of the B2L expression construct, without antigen, non-specifically reduced tumor growth in murine models of cancer.

Conclusion: A streamlined, functional approach to genome-wide screening of a biological activity in vivo is presented. Its application to screening in mice for an immune activity elicited by the pathogen genome of Parapoxvirus ovis yielded a novel immunomodulator. In this inverted discovery method, it was possible to identify the adjuvant responsible for a function of interest prior to a mechanistic study of the adjuvant. The non-specific immune activity of this modulator, B2, is similar to that associated with administration of inactivated particles to a host or to a live viral infection. Administration of B2 may provide the opportunity to significantly impact host immunity while being itself only weakly recognized. The functional genomics method used to pinpoint B2 within an ORFeome may be more broadly applicable to screening for other biological activities in an animal.

Background: Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time.

Methods: We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature.

Results: The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.

Conclusions: The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.

Background: The use of culture-independent nucleic acid techniques, such as ribosomal RNA gene cloning library analysis, has unveiled the tremendous microbial diversity that exists in natural environments. In sharp contrast to this great achievement is the current difficulty in cultivating the majority of bacterial species or phylotypes revealed by molecular approaches. Although recent new technologies such as metagenomics and metatranscriptomics can provide more functionality information about the microbial communities, it is still important to develop the capacity to isolate and cultivate individual microbial species or strains in order to gain a better understanding of microbial physiology and to apply isolates for various biotechnological applications.

Results: We have developed a new system to cultivate bacteria in an array of droplets. The key component of the system is the microbe observation and cultivation array (MOCA), which consists of a Petri dish that contains an array of droplets as cultivation chambers. MOCA exploits the dominance of surface tension in small amounts of liquid to spontaneously trap cells in well-defined droplets on hydrophilic patterns. During cultivation, the growth of the bacterial cells across the droplet array can be monitored using an automated microscope, which can produce a real-time record of the growth. When bacterial cells grow to a visible microcolony level in the system, they can be transferred using a micropipette for further cultivation or analysis.

Conclusions: MOCA is a flexible system that is easy to set up, and provides the sensitivity to monitor growth of single bacterial cells. It is a cost-efficient technical platform for bioassay screening and for cultivation and isolation of bacteria from natural environments.

Background: Plasmodium vivax is the most widespread of the human malaria parasites in terms of geography, and is thought to present unique challenges to local efforts aimed at control and elimination. Parasite molecular markers can provide much needed data on P. vivax populations, but few such markers have been critically evaluated. One marker that has seen extensive use is the gene encoding merozoite surface protein 3-alpha (MSP-3α), a blood-stage antigen known to be highly variable among P. vivax isolates. Here, a sample of complete msp-3α gene sequences is analyzed in order to assess its utility as a molecular marker for epidemiologic investigations.

Methods: Amplification, cloning and sequencing of additional P. vivax isolates from different geographic locations, including a set of Venezuelan field isolates (n = 10), yielded a sample of 48 complete msp-3α coding sequences. Characterization of standard population genetic measures of diversity, phylogenetic analysis, and tests for recombination were performed. This allowed comparisons to patterns inferred from the in silico simulation of a polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) protocol used widely.

Results: The larger sample of MSP-3α diversity revealed incongruence between the observed levels of nucleotide polymorphism, which were high in all populations, and the pattern of PCR-RFLP haplotype diversity. Indeed, PCR-RFLP haplotypes were not informative of a population’s genetic diversity and identical haplotypes could be produced from analogous bands in the commonly used protocol. Evidence of frequent and variable insertion-deletion mutations and recurrent recombination between MSP-3α haplotypes complicated the inference of genetic diversity patterns and reduced the phylogenetic signal.

Conclusions: The genetic diversity of P. vivax msp-3α involves intragenic recombination events. Whereas the high genetic diversity of msp-3α makes it a promising marker for some epidemiological applications, the ability of msp-3α PCR-RFLP analysis to accurately track parasites is limited. Local studies of the circulating alleles are needed before implementing PCR-RFLP approaches. Furthermore, evidence from the global sample analyzed here suggests such msp-3α PCR-RFLP methods are not suitable for broad geographic studies or tracking parasite populations for an extended period of time.

Salmonella enterica serovar Typhimurium, a gram-negative facultative rod-shaped bacterium causing salmonellosis and foodborne disease, is one of the most common isolated Salmonella serovars in both developed and developing nations. Several S. Typhimurium genomes have been completed and many more genome-sequencing projects are underway. Comparative genome analysis of the multiple strains leads to a better understanding of the evolution of S. Typhimurium and its pathogenesis. S. Typhimurium strain UK-1 (belongs to phage type 1) is highly virulent when orally administered to mice and chickens and efficiently colonizes lymphoid tissues of these species. These characteristics make this strain a good choice for use in vaccine development. In fact, UK-1 has been used as the parent strain for a number of nonrecombinant and recombinant vaccine strains, including several commercial vaccines for poultry. In this study, we conducted a thorough comparative genome analysis of the UK-1 strain with other S. Typhimurium strains and examined the phenotypic impact of several genomic differences. Whole genomic comparison highlights an extremely close relationship between the UK-1 strain and other S. Typhimurium strains; however, many interesting genetic and genomic variations specific to UK-1 were explored. In particular, the deletion of a UK-1-specific gene that is highly similar to the gene encoding the T3SS effector protein NleC exhibited a significant decrease in oral virulence in BALB/c mice. The complete genetic complements in UK-1, especially those elements that contribute to virulence or aid in determining the diversity within bacterial species, provide key information in evaluating the functional characterization of important genetic determinants and for development of vaccines.

Uropathogenic Escherichia coli (UPEC), a member of extraintestinal pathogenic E. coli, cause ∼80% of community-acquired urinary tract infections (UTI) in humans. UPEC initiates its colonization in epithelial cells lining the urinary tract with a complicated life cycle, replicating and persisting in intracellular and extracellular niches. Consequently, UPEC causes cystitis and more severe form of pyelonephritis. To further understand the virulence characteristics of UPEC, we investigated the roles of BarA-UvrY two-component system (TCS) in regulating UPEC virulence. Our results showed that mutation of BarA-UvrY TCS significantly decreased the virulence of UPEC CFT073, as assessed by mouse urinary tract infection, chicken embryo killing assay, and cytotoxicity assay on human kidney and uroepithelial cell lines. Furthermore, mutation of either barA or uvrY gene reduced the production of hemolysin, lipopolysaccharide (LPS), proinflammatory cytokines (TNF-α and IL-6) and chemokine (IL-8). The virulence phenotype was restored similar to that of wild-type by complementation of either barA or uvrY gene in trans. In addition, we discussed a possible link between the BarA-UvrY TCS and CsrA in positively and negatively controlling virulence in UPEC. Overall, this study provides the evidences for BarA-UvrY TCS regulates the virulence of UPEC CFT073 and may point to mechanisms by which virulence regulations are observed in different ways may control the long-term survival of UPEC in the urinary tract.

Introduction: Apolipoprotein C-III (apoC-III) regulates triglyceride (TG) metabolism. In plasma, apoC-III exists in non-sialylated (apoC-III_0a without glycosylation and apoC-III[subscript 0b] with glycosylation), monosialylated (apoC-III₁) or disialylated (apoC-III₂) proteoforms. Our aim was to clarify the relationship between apoC-III sialylation proteoforms with fasting plasma TG concentrations.

Methods: In 204 non-diabetic adolescent participants, the relative abundance of apoC-III plasma proteoforms was measured using mass spectrometric immunoassay.

Results: Compared with the healthy weight subgroup (n = 16), the ratios of apoC-III_0a, apoC-III_0b, and apoC-III₁ to apoC-III₂ were significantly greater in overweight (n = 33) and obese participants (n = 155). These ratios were positively correlated with BMI z-scores and negatively correlated with measures of insulin sensitivity (S[subscript i]). The relationship of apoC-III₁ / apoC-III₂ with S_i persisted after adjusting for BMI (p = 0.02). Fasting TG was correlated with the ratio of apoC-III_0a / apoC-III₂ (r = 0.47, p<0.001), apoC-III_0b / apoC-III₂ (r = 0.41, p<0.001), apoC-III₁ / apoC-III₂ (r = 0.43, p<0.001). By examining apoC-III concentrations, the association of apoC-III proteoforms with TG was driven by apoC-III_0a (r = 0.57, p<0.001), apoC-III_0b (r = 0.56. p<0.001) and apoC-III₁ (r = 0.67, p<0.001), but not apoC-III₂ (r = 0.006, p = 0.9) concentrations, indicating that apoC-III relationship with plasma TG differed in apoC-III₂ compared with the other proteoforms.

Conclusion: We conclude that apoC-III_0a, apoC-III_0b, and apoC-III₁, but not apoC-III₂ appear to be under metabolic control and associate with fasting plasma TG. Measurement of apoC-III proteoforms can offer insights into the biology of TG metabolism in obesity.

Background: On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness.

Methods: We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses.

Results: Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus.

Conclusion: Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months.

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.

Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization.

Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south–north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918–19, but different factors explained mortality variation in each wave.

Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.