Using Environmental and Natural History Traits to Predict On-going Global Amphibian Die-offs

Kristina Frogoso, a student from the University of Arkansas at Little Rock, worked with Dr. Scott Connelly to examine the threat of a fungal pathogen to amphibian populations.

Abstract: Biodiversity loss is occurring in substantial rates, and more specifically we are seeing major amphibian declines due to infectious diseases. One infectious disease in particular is chytridiomycosis which is caused by a fungal pathogen called Batrachocytrium dendrobatidis (Bd). In order to predict future amphibian die-offs and prevent population decline using conservation methods, it is necessary to understand environmental variables and natural history traits in relation to Bd. The question is what variables are significant predictors of die-offs? A multiple linear regression (logit) was generated on RStudio to model the relationship first between environmental variables and then with added natural life history traits as the explanatory variables and threat status as the response variable. The threat status for species that had unknown threat status was predicted with 77% accuracy. Also, breeding site showed the most significant in predicting threat status of amphibian species, p < 0.5. The results show that species living in more permanent bodies of water tend to be more threatened that species that live in ephemeral sites. In conclusion, more information for other amphibian species and more thorough integration of trait data are needed to better predict population decline.


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Is the Transmission Rate of The Wolbachia Parasite Lower in Hybrids Compared To Pure Species?

Jasmine Gipson, from Kennesaw State University, worked with Dr. Kelly Dyer in the UGA Genetics department to study the transmission of Wolbachia, a parasite of insects.

Abstract: Wolbachia is an endosymbiont parasite that lives in the reproductive system 70% of all insects. It is passed down vertically to its offspring from the mother. Wolbachia occurs naturally in D. recens, but not D. subquinaria. In the wild, D. recens and D. subquinaria hybridize and about 2-3% of those hybrid offsprings contain a D. recenâ’s mitochondria, but not the wolbachia. This is a strange situation because the mitochondria is only passed down through the mother’s eggs, just like wolbachia. So how is it possible to have a D. recenâ’s mitochondria, but not the wolbachia as well? This peculiar scenario led to the question, is the transmission rate of wolbachia lower in hybrids compared to pure species? To answer this question, a D. recens female was crossed with a D. subquinaria. The F1 hybrid female was then backcrossed to a D. subquinaria male. The F1 and F2 generations were both test for wolbachia using PCR. The transmission rate for the F1 generation had a transmission rate of 100% and the F2 generation had a transmission rate of 95.7%. This shows that the transmission rate of wolbachia is lowered in hybrid species compared to pure species. Possible explanations for this decrease in transmission rate is because of the genetic variation between D. recens and D. subquinaria or the parasite could have been randomly loss due to oogenesis.


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Mapping autochthonous transmission potential of Chikungunya virus in the United States

Nicole Solano, a student at Agnes Scott College, worked with Dr. John Drake to model factors that could influence the risk of Chikungunya virus in the United States.

Abstract: Chikungunya virus (CHIKV) is an arbovirus endemic to Africa and South and East Asia, that is transmitted to humans by the bite of an infected mosquito, primarily Aedes aegypti or Aedes albopictus.  Since its identification in Tanzania in 1952, CHIKV has spread around the globe, making itself a very prevalent infectious disease. To date (20 June 2015) there have been eleven reported cases of autochthonous transmission in the U.S. (in Florida). Since its introduction into the Americas, concerns have been raised about which areas in the United States are most vulnerable to importation of CHIKV. We examined the correlation between human West Nile Virus (WNV) cases and human Meningitis and Encephalitis cases. A strong correlation was observed (p-value < 2.2-16) informing us that Meningitis and Encephalitis is a good predictor of WNV infection. Given this, we wanted to know which socio-economic covariates were important to consider when thinking about exposure to a disease. A regression analysis helped us identify age and poverty level as the most important covariates. Presence of Aedes albopictus and relative exposure per county was mapped to depict which counties are most vulnerable for onward Chikungunya virus transmission.


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Visualizing the Effect of Interventions during the 2014-2015 West Africa Ebola Outbreak

Timothy Wildauer, a student from Bethany Lutheran College, worked with Dr. John Drake to test new methods of determining time of infection for Ebola patients.

Abstract: Data recorded during the 2014-2015 West Africa Ebola Outbreak indicates when patients presented themselves at a hospital for treatment. However, to know if interventions were successful, we need to know when patients became infected. The number of people who became infected on a given date is corrupted by the incubation period for us to see when patients begin showing symptoms. The current method for finding when people became infected is to shift the dates on the observed data set backwards by the average infection period. We developed two non-parametric filters to find when patients became infected with Ebola: multiple trials of randomly selecting incubation periods for patients, and a Ridge Regression. These methods were tested on simulated outbreaks of different difficulties to see which method worked best. We selected four interventions during the outbreak to see if there was an effect on the transmissibility of the disease. In Sierra Leone, the transmission rate dropped significantly after the country was shut down for three days in September 2014. After other events, the transmission changed significantly, but the change may be the natural course of the outbreak. Through testing we found that Random deconvolution achieves a high correlation with the infection curve.


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Protective Population Behavior Change in Outbreaks of Emerging Infectious Disease

Evans Lodge, a student from Calvin College, worked with Dr. John Drake to measure how human behaviors change during disease outbreaks.

Abstract: In outbreaks of emerging infectious disease, public health interventions aim at increasing the speed with which infected individuals are removed from the susceptible population, limiting opportunities for secondary infection. Isolation, hospitalization, and barrier-nursing practices are crucial for controlling disease spread in these contexts. Ebola virus disease (EVD), Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) are all zoonotic infections that have caused significant international outbreaks in the past. Here, we use patient-level data from the 2014-2015 Liberian Ebola epidemic, 2003 Hong Kong SARS epidemic, 2014 Saudi Arabia MERS outbreaks, and 2015 South Korea MERS outbreak to quantify changing removal rates, burial practices, contact tracing, and other measures of protective behavior change. Using the removal rate, γ, as a measure of protective behavior change allows direct comparison of health behavior development in different outbreaks and locations. Robust regression analysis and analyses of covariance are used to estimate the rate at which γ increases in each outbreak by epidemic week and serial interval. Measured interactions between models show that mean removal rates varied within a factor of three, falling between the 2003 Hong Kong SARS outbreak and the 2014-2015 Ebola epidemic in Liberia.

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Can Internal Parasites Affect Wound-healing Rates in Insects?

Lexi Calderon, a student from the University of Redlands, worked with Dr. Andy Davis and members of his lab to study parasites affect wound-healing in bess beetles.

Abstract: By definition, parasites depend on the resources of their host to survive. This relationship can result in a decrease of energy and fitness for the host. The parasitic nematode Chondronema passali resides in the hemocoel cavity of the bess beetle, Odontotaenius disjunctus. Although this parasite is non-lethal, a single beetle can harbor thousands of nematodes. Previous research has demonstrated this parasite affects the stress reaction of beetles, but very little research has investigated the effect parasites have on the host’s ability to heal a wound. Wound healing can be thought of as an indicator of the effectiveness of the immune system and by studying healing we can infer the effect this parasite has on the fitness of its host. We conducted a series of experiments where beetles were wounded with a dremel rotary drill and observed every hour for 12 hours after initial wounding. Each hour beetles were given a value from 1-5 to measure their status in the wound healing process, and values were summed to generate a ‘wound healing score’ for each beetle. Beetles were killed and dissected following the experiment to define gender and parasite abundance. Out of 188 beetles, 83% were infected with C.passali. Wound healing scores were not significantly predicted by parasite status. Beetle weight was a predictor of wound healing scores where heavier beetles had higher scores. Oxygen consumption was also measured in a subset of beetles after wounding, and we found parasitized beetles tended to have higher respiration (10% higher) than non-infected beetles.

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Microclimate effects on Aedes albopictus mosquitoes

Taylor McClanahan, a student at the University of Arkansas at Little Rock, worked with Dr. Courtney Murdock and members of her lab to examine how microclimate affects mosquitoes.

Abstract: Aedes albopictus, (Asian tiger mosquito), has successfully colonized in several countries in North and South America. Ae. albopictus is a highly efficient vector, capable of transmitting at least 27 different arboviruses, and is contributing to the global expansion of both dengue and Chikungunya. However, whether or not dengue or Chikungunya will emerge in a given area will depend on its interaction with local mosquito populations and local environmental conditions. The aim of this study was to characterize variation in local climate conditions and how this variation impacts Ae. albopictus traits important for transmission. An impervious surface map of Athens-Clarke County was used to select three urban, suburban, and rural sites (30m2). Six pots were placed (>10 m apart) at each site in full shade, filled with 200 ml leaf infusion, seeded with 30 Ae. albopictus larvae, and paired with a data logger on the inside and outside of the pot. All pots were checked daily for emerging adults, and any adults present were counted and removed. Urban sites were characterized by the following: warmer daily mean and minimum temperatures, decreased daily diurnal temperature variation, earlier adult emergence, and lower numbers of emerging adults relative to suburban and rural sites. Further, weather station temperature data were not necessarily a good predictor of mosquito microclimate across the three land uses. This cautions against the use of downscaled global climate patterns in predicting how vector-borne diseases may respond to current and future climate change. Ultimately, we see that microclimate data generates a more precise representation of the environments these mosquitoes inhabit.

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Behavioral determinants of parasite transmission in a monarch (Danaus plexippus) population

Anna Schneider, a student from the University of Wisconsin-Stevens Point, worked with mentors Dr. Sonia Altizer, Dr. Richard Hall, and Ania Majewska to look at how butterfly behavior affects parasite transmission.

Abstract: Altered behavior of an infected host can have important consequences for pathogen transmission. Pathogens can cause the host to increase foraging behavior and decrease activity levels due to increased energetic demands, which can significantly change the spread of the pathogen. Monarchs can suffer from a debilitating protozoan parasite, Ophryocystis elektroscirrha (OE), which is transmitted when infected adults inadvertently shed spores on milkweed (Asclepias spp.) leaves that are subsequently consumed by the caterpillars.  While infected adults are known to experience reduced flight ability and survival, less is known about how infection influences milkweed visitation behavior and, therefore, spore deposition.  Here, we investigated whether infection status altered activity budgets of wild adult Monarchs, particularly visitation rates to milkweed for foraging or oviposition.  Behavioral observations and milkweed visitation rates of adult Monarchs, both infected and uninfected, were collected in the butterfly gardens at the Wormsloe Historic Site in Savannah, GA.  Our results concluded that sex, not infection status, showed significance in variation of behavior.  Milkweed visitation rates were higher than previously thought and these are critical for parasite persistence.  These data provide the first field estimates of parasite spore deposition rates in monarchs.  We modified an existing differential equation model of monarch-OE dynamics to include adults contaminated with OE spores through mating and milkweed visitation.  According to this model, late-season OE prevalence varied between 16.5 and 78.6%.  This is consistent with the wide range of OE prevalence recorded in US monarchs (6-20% in the Midwest, up to 100% in tropical milkweed patches in the Southeast).

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Microbial Community Assessment of Lone Star Ticks from Athens, GA

Sydney Barosko, a student from Michigan State University, worked in the lab of Dr. Travis Glenn to examine pathogen diversity in local lone star ticks.

Abstract: In the world of infectious diseases, ticks play an important role as a vector in transmitting pathogens to humans, companion animals, livestock, and wildlife. Amblyomma americanum (Lone Star ticks) are known to transmit the pathogens that cause ehrlichiosis, babesiosis, Q fever, and rickettsial diseases. Few studies have been done on the pathogen diversity of Lone Star tick individuals. We used microbial 16S amplification followed by Illumina sequencing of the 16S amplicons to characterize microbial communities in A. americanum collected near Athens, GA. We examined differences in 16S sequences:  1) when two different Taq DNA polymerases were used for amplification (one with high fidelity and the other with more tolerance for low-quality samples and primer mismatches) and, 2) between 19 male and 18 female A. americanum ticks. We focused on three genera of microbes with known pathogenic strains:  Coxiella, Rickettsia, and Ehrlichia. We did not find any significant differences between the communities when amplified with the different Taq DNA polymerases nor in the infection rate of males vs. females infected with Ehrlichia or Rickettsia.  Male vs. female infection rates did, however, differ for Coxiella. The proportion of Coxiella in the microbiome was much higher in females than in males. Our work demonstrates that 16S microbiome sequencing can be an effective tool in characterizing pathogens in ticks and builds a foundation for larger-scale surveys in the future.


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Predicting the Effectiveness of Novel Tuberculosis Regimens

Taylor Joseph, a student from Michigan State University, worked with Dr. Andreas Handel to use computational methods to examine new tuberculosis treatment regimes.

Abstract: Tuberculosis (TB) remains one of the world’s most deadly diseases, as current treatment protocols are far outdated and often ineffective. Furthermore, current regimens are complicated and last many months, often leading to patient non-compliance and drug resistant bacteria. There is thus a need for more effective and efficient treatment strategies, yet conducting human trials on these new strategies is expensive and time consuming. As an alternative or supplement to human and animal trials, computational models may be used to predict the outcomes of new treatment strategies. In this study, we use a system of differential equations to describe within-host dynamics of TB and drug treatment, and we assess the model’s accuracy in comparison to data collected from previous clinical studies. We then use the model to predict and evaluate the outcome of new treatment regimens.


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