Accelerated Diversification of Nonhuman Primate Malarias in Southeast Asia: Adaptive Radiation or Geographic Speciation?

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Description

Although parasitic organisms are found worldwide, the relative importance of host specificity and geographic isolation for parasite speciation has been explored in only a few systems. Here, we study Plasmodium parasites known to infect Asian nonhuman primates, a monophyletic grou…

Although parasitic organisms are found worldwide, the relative importance of host specificity and geographic isolation for parasite speciation has been explored in only a few systems. Here, we study Plasmodium parasites known to infect Asian nonhuman primates, a monophyletic group that includes the lineage leading to the human parasite Plasmodium vivax and several species used as laboratory models in malaria research. We analyze the available data together with new samples from three sympatric primate species from Borneo: The Bornean orangutan and the long-tailed and the pig-tailed macaques. We find several species of malaria parasites, including three putatively new species in this biodiversity hotspot. Among those newly discovered lineages, we report two sympatric parasites in orangutans. We find no differences in the sets of malaria species infecting each macaque species indicating that these species show no host specificity. Finally, phylogenetic analysis of these data suggests that the malaria parasites infecting Southeast Asian macaques and their relatives are speciating three to four times more rapidly than those with other mammalian hosts such as lemurs and African apes. We estimate that these events took place in approximately a 3–4-Ma period. Based on the genetic and phenotypic diversity of the macaque malarias, we hypothesize that the diversification of this group of parasites has been facilitated by the diversity, geographic distributions, and demographic histories of their primate hosts.

Date Created
2014-11-10
Agent

Scalable control strategies and a customizable swarm robotic platform for boundary coverage and collective transport tasks

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Description
Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks…

Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks with a high degree of parallelism and redundancy, enabling effective operation even in the presence of unknown environmental factors and individual robot failures. Social insect colonies provide a rich source of inspiration for these types of control approaches, since they can perform complex collective tasks under a range of conditions. To validate swarm robotic control strategies, experimental testbeds with large numbers of robots are required; however, existing low-cost robots are specialized and can lack the necessary sensing, navigation, control, and manipulation capabilities.

To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies.
Date Created
2017
Agent

Longitudinal Analysis of Plasmodium Falciparum Genetic Variation in Turbo, Colombia: Implications for Malaria Control and Elimination

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Description

Background: Malaria programs estimate changes in prevalence to evaluate their efficacy. In this study, parasite genetic data was used to explore how the demography of the parasite population can inform about the processes driving variation in prevalence. In particular, how changes…

Background: Malaria programs estimate changes in prevalence to evaluate their efficacy. In this study, parasite genetic data was used to explore how the demography of the parasite population can inform about the processes driving variation in prevalence. In particular, how changes in treatment and population movement have affected malaria prevalence in an area with seasonal malaria.

Methods: Samples of Plasmodium falciparum collected over 8 years from a population in Turbo, Colombia were genotyped at nine microsatellite loci and three drug-resistance loci. These data were analyzed using several population genetic methods to detect changes in parasite genetic diversity and population structure. In addition, a coalescent-based method was used to estimate substitution rates at the microsatellite loci.

Results: The estimated mean microsatellite substitution rates varied between 5.35 × 10-3 and 3.77 × 10-2 substitutions/locus/month. Cluster analysis identified six distinct parasite clusters, five of which persisted for the full duration of the study. However, the frequencies of the clusters varied significantly between years, consistent with a small effective population size.

Conclusions: Malaria control programs can detect re-introductions and changes in transmission using rapidly evolving microsatellite loci. In this population, the steadily decreasing diversity and the relatively constant effective population size suggest that an increase in malaria prevalence from 2004 to 2007 was primarily driven by local rather than imported cases.

Date Created
2015-09-22
Agent

Evolution of multigene families and single copy genes in Plasmodium spp

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Description
The complex life cycle and widespread range of infection of Plasmodium parasites, the causal agent of malaria in humans, makes them the perfect organism for the study of various evolutionary mechanisms. In particular, multigene families are considered one of the…

The complex life cycle and widespread range of infection of Plasmodium parasites, the causal agent of malaria in humans, makes them the perfect organism for the study of various evolutionary mechanisms. In particular, multigene families are considered one of the main sources for genome adaptability and innovation. Within Plasmodium, numerous species- and clade-specific multigene families have major functions in the development and maintenance of infection. Nonetheless, while the evolutionary mechanisms predominant on many species- and clade-specific multigene families have been previously studied, there are far less studies dedicated to analyzing genus common multigene families (GCMFs). I studied the patterns of natural selection and recombination in 90 GCMFs with diverse numbers of gene gain/loss events. I found that the majority of GCMFs are formed by duplications events that predate speciation of mammal Plasmodium species, with many paralogs being neutrally maintained thereafter. In general, multigene families involved in immune evasion and host cell invasion commonly showed signs of positive selection and species-specific gain/loss events; particularly, on Plasmodium species is the simian and rodent clades. A particular multigene family: the merozoite surface protein-7 (msp7) family, is found in all Plasmodium species and has functions related to the erythrocyte invasion. Within Plasmodium vivax, differences in the number of paralogs in this multigene family has been previously explained, at least in part, as potential adaptations to the human host. To investigate this I studied msp7 orthologs in closely related non-human primate parasites where homology was evident. I also estimated paralogs’ evolutionary history and genetic polymorphism. The emerging patterns where compared with those of Plasmodium falciparum. I found that the evolution of the msp7 multigene family is consistent with a Birth-and-Death model where duplications, pseudogenization and gene lost events are common. In order to study additional aspects in the evolution of Plasmodium, I evaluated the trends of long term and short term evolution and the putative effects of vertebrate- host’s immune pressure of gametocytes across various Plasmodium species. Gametocytes, represent the only sexual stage within the Plasmodium life cycle, and are also the transition stages from the vertebrate to the mosquito vector. I found that, while male and female gametocytes showed different levels of immunogenicity, signs of positive selection were not entirely related to the location and presence of immune epitope regions. Overall, these studies further highlight the complex evolutionary patterns observed in Plasmodium.
Date Created
2016
Agent

Spatial genetic structure under limited dispersal: theory, methods and consequences of isolation-by-distance

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Description
Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity…

Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to identify isolation-by-distance because it can impact the statistical analysis of population samples and it can help us better understand evolutionary dynamics. For this dissertation I investigated several aspects of isolation-by-distance. First, I looked at how the shape of the dispersal distribution affects the observed pattern of isolation-by-distance. If, as theory predicts, the shape of the distribution has little effect, then it would be more practical to model isolation-by-distance using a simple dispersal distribution rather than replicating the complexities of more realistic distributions. Therefore, I developed an efficient algorithm to simulate dispersal based on a simple triangular distribution, and using a simulation, I confirmed that the pattern of isolation-by-distance was similar to other more realistic distributions. Second, I developed a Bayesian method to quantify isolation-by-distance using genetic data by estimating Wright’s neighborhood size parameter. I analyzed the performance of this method using simulated data and a microsatellite data set from two populations of Maritime pine, and I found that the neighborhood size estimates had good coverage and low error. Finally, one of the major consequences of isolation-by-distance is an increase in inbreeding. Plants are often particularly susceptible to inbreeding, and as a result, they have evolved many inbreeding avoidance mechanisms. Using a simulation, I determined which mechanisms are more successful at preventing inbreeding associated with isolation-by-distance.
Date Created
2015
Agent

Mathematical and statistical insights in evaluating state dependent effectiveness of HIV prevention interventions

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Description
Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease. Most commonly, PrEP refers to an experimental HIV-prevention strategy that…

Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease. Most commonly, PrEP refers to an experimental HIV-prevention strategy that would use antiretrovirals to protect HIV-negative people from HIV infection. A deterministic mathematical model of HIV transmission is developed to evaluate the public-health impact of oral PrEP interventions, and to compare PrEP effectiveness with respect to different evaluation methods. The effects of demographic, behavioral, and epidemic parameters on the PrEP impact are studied in a multivariate sensitivity analysis. Most of the published models on HIV intervention impact assume that the number of individuals joining the sexually active population per year is constant or proportional to the total population. In the second part of this study, three models are presented and analyzed to study the PrEP intervention, with constant, linear, and logistic recruitment rates. How different demographic assumptions can affect the evaluation of PrEP is studied. When provided with data, often least square fitting or similar approaches can be used to determine a single set of approximated parameter values that make the model fit the data best. However, least square fitting only provides point estimates and does not provide information on how strongly the data supports these particular estimates. Therefore, in the third part of this study, Bayesian parameter estimation is applied on fitting ODE model to the related HIV data. Starting with a set of prior distributions for the parameters as initial guess, Bayes' formula can be applied to obtain a set of posterior distributions for the parameters which makes the model fit the observed data best. Evaluating the posterior distribution often requires the integration of high-dimensional functions, which is usually difficult to calculate numerically. Therefore, the Markov chain Monte Carlo (MCMC) method is used to approximate the posterior distribution.
Date Created
2014
Agent

A: kinetic approach to anomalous diffusion in biological trapping regions

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Description
Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology.…

Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have been observed to follow a power law $\left \propto t^\alpha$ scaling of the mean square displacement of a particle. This contrasts with the expected linear behavior of particles undergoing normal diffusion. \emph{Anomalous sub-diffusion} ($\alpha<1$) has been attributed to factors such as cytoplasmic crowding of macromolecules, and trap-like structures in the subcellular environment non-linearly slowing the diffusion of molecules. Compared to normal diffusion, signaling molecules in these constrained spaces can be more concentrated at the source, and more diffuse at longer distances, potentially effecting the signalling dynamics. As diffusion at the cellular scale is a fundamental mechanism of cellular signaling and additionally is an implicit underlying mathematical assumption of many canonical models, a closer look at models of anomalous diffusion is warranted. Approaches in the literature include derivations of fractional differential diffusion equations (FDE) and continuous time random walks (CTRW). However these approaches are typically based on \emph{ad-hoc} assumptions on time- and space- jump distributions. We apply recent developments in asymptotic techniques on collisional kinetic equations to develop a FDE model of sub-diffusion due to trapping regions and investigate the nature of the space/time probability distributions assosiated with trapping regions. This approach both contrasts and compliments the stochastic CTRW approach by positing more physically realistic underlying assumptions on the motion of particles and their interactions with trapping regions, and additionally allowing varying assumptions to be applied individually to the traps and particle kinetics.
Date Created
2014
Agent

Time-dependent models of signal transduction networks

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Description
Signaling cascades transduce signals received on the cell membrane to the nucleus. While noise filtering, ultra-sensitive switches, and signal amplification have all been shown to be features of such signaling cascades, it is not understood why cascades typically show three…

Signaling cascades transduce signals received on the cell membrane to the nucleus. While noise filtering, ultra-sensitive switches, and signal amplification have all been shown to be features of such signaling cascades, it is not understood why cascades typically show three or four layers. Using singular perturbation theory, Michaelis-Menten type equations are derived for open enzymatic systems. When these equations are organized into a cascade, it is demonstrated that the output signal as a function of time becomes sigmoidal with the addition of more layers. Furthermore, it is shown that the activation time will speed up to a point, after which more layers become superfluous. It is shown that three layers create a reliable sigmoidal response progress curve from a wide variety of time-dependent signaling inputs arriving at the cell membrane, suggesting that natural selection may have favored signaling cascades as a parsimonious solution to the problem of generating switch-like behavior in a noisy environment.
Date Created
2013
Agent
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