Mercedes Pascual - US grants

BIOCOMPLEXITY: Collaborative Research: Factors affecting, and impact of, diazotrophic microorganisms in the western Equatorial Atlantic Ocean

This biocomplexity research focuses on plankton dynamics in the western Equatorial Atlantic Ocean (WEQAT). This is a complex and understudied ecosystem that has significant impacts on marine resources in the region as well as in downstream areas such as the Caribbean Sea. The study centers on diazotrophic (nitrogen fixing) microorganisms as keystone species. Geological, physical, biological, chemical and even social factors all have a major influence on population biology and activity of diazotrophs in the WEQAT. Diazotrophs in turn have a major impact on other phytoplankton and trophic levels through input of fixed nitrogen (N). The Amazon River affects the region physically by changing salinity and thereby water column stratification, and geochemically by introducing iron and silicate which can then biologically stimulate the growth of diatoms that contain the N2 fixing endosymbiont Richelia intracellularis. Furthermore, the area receives significant seasonal atmospheric inputs of iron in dust from the Sahel region of Africa, which can promote the growth of the important N2 fixing cyanobacterium Trichodesmium. This atmospheric iron source is directly deposited on the surface waters where biological activity is greatest. For Trichodesmium, the physical environment (e.g. high wind speed) can also inhibit activity and the formation of blooms. Diazotrophs may be affected by land use practices in the Amazon Basin and the African Sahel, and N2 fixed by marine plankton can affect humans by stimulating primary productivity and fishery yields.
Using both remote sensing and shipboard measurements, scientists will examine the complex processes which structure these planktonic diazotroph populations, influence their importance in CO2 and N2 fixation, which, in turn, affect other planktonic processes. The seasonal and spatial relationships of Trichodesmium and Hemiaulus / Richelia associations will be examined with direct reference to the major routes of inputs of Fe and Si, and with regard to the physical environment. The group of collaborating scientists will examine the trophic structures associated with each diazotrophic community, including the vertical distribution of processes and associated autotrophic and heterotrophic plankton populations. These data will be used to develop and verify biogeochemical and trophodynamic models that incorporate the complex physical, chemical and biological interactions that characterize the WEQAT region. The models will, in turn, be used to examine the hypothesis that physical forcing, through its effect on the diazotrophic populations and the structure of the food web, influences N2 fixation and, in part, determines the high productivity of the WEQAT.
The work uses a combination of both observations and models to address three fundamental issues in biocomplexity: 1) the relationship between ecosystem structure and function in a system that is both nonlinear and high-dimensional; 2) the response of a nonlinear ecosystem to environmental forcing; and 3) the relevant level of detail, including the resolution of physical space, that must be incorporated in nonlinear systems to capture the dynamics of a global ecosystem property (here, high productivity). The research will significantly advance our understanding of the interaction between physical and biogeochemical processes in an important area the world's oceans, and identify how these interactions regulate variability in marine ecosystem productivity.

The outbreaks of many infectious diseases display pronounced seasonal and interannual (year to year) variation. To date, investigations of the role of environmental factors including climatic ones, have not significantly progressed beyond simple correlative analyses. This project develops quantitative approaches to address the role of climate and other environmental factors in the population dynamics of infectious diseases, particularly those with temporary (short-lived) immunity and free-living infectious stages. The work focuses on cholera in its main endemic region (NE India and Bangladesh), but also other regions of Asia (Vietnam) and Africa (Mozambique). Its ultimate aim is to develop quantitative scenarios for cholera under climate change, by combining results on disease-environmental couplings with climate models.The applicability of the developed quantitative approaches to other diseases (particularly malaria and other vector borne pathogens) will be examined.

The global climate is changing. The most likely avenues for impacts on disease dynamics are through concomitant changes in the seasonal environmental variables that drive transmission, and through changes in the dominant (interannual) modes of variability (e.g. ENSO) that are observed in the current climate. Neither mechanism can be understood without a solid understanding of how climate variability has influenced disease patterns in the past. Extensive spatial and temporal cholera records provide an opportunity to address such understanding for an infectious disease remaining a public health problem around the globe, particularly in Asia but also Africa, for which the role of the environment is an important open question.

Most living systems are comprised of complex networks of interactions; describing the structure of these networks and their dynamic properties is a major challenge for theoretical and empirical biologists. Food webs are paradigmatic of complex natural networks. Formed by species and their feeding relationships, they underlie the flow of energy through ecosystems and their responses to human-induced and environmental perturbations, including species' extinctions. Several simple models of food web structure exist, but these do not accurately represent the complexities present in real networks. The goals of this project are to develop new theory to extend simple models of food web structure, investigate biological mechanisms underlying this structure, examine the modularity of food webs, and consider networks quantitatively by incorporating interaction strengths among components. In particular, the researchers will address the effects of species extinctions on food web robustness and examine how stability at the level of an entire network results from instability of individual components. The resulting theory will provide a general framework to advance our understanding of food webs and diverse other complex biological networks.

The proposed research will contribute directly to education and outreach programs for grade school students, undergraduate and graduate students, and postdoctoral researchers. These activities will be coordinated through ongoing programs at the National Center for Ecological Analysis and Synthesis' 'Kids Do Ecology' program and through the University of Michigan. Web-based teaching modules and classroom presentations will introduce grade school students to ecology, complex systems, and mathematics by teaching them about many different types of biological networks. Seminars presented at Historically Minority Institutions and Minority Serving Institutions will introduce undergraduate students to careers in ecology and mathematics. Results from the project will be incorporated into graduate and undergraduate courses at University of Michigan.

The main goal of this research project is to create a novel method to quantitatively forecast bifurcations as well as the pre- and post-bifurcation dynamics of large dimensional nonlinear systems with a low dimensional inertial manifold. Dramatic changes in the dynamics of complex systems, from ecosystems to engineered systems, occur. Forecasting such events using advanced nonlinear techniques is of major importance. The behavior of such complex systems is commonly characterized by nonlinearities that can lead to regime shifts or bifurcations from a stable to an unstable dynamics. A method that can quantitatively predict bifurcations as well as the pre- and post-bifurcation dynamics for large dimensional nonlinear systems would have a significant impact in a variety of fields, from the analysis of nano-systems to the design of disease eradication campaigns. The three key tasks are to: (1) develop novel techniques to differentiate the dynamics along the inertial manifold from the overall dynamics and to handle noise using a robust signal processing methodology, (2) develop innovative methods to forecast stable/unstable branches of bifurcation diagrams, and (3) refine the general methods for application to complex nonlinear systems including population dynamics and aeroelastic systems.

This project has broader impacts on the society at large. This effort will answer important scientific questions, and will impact applications spanning from computational dynamics to population dynamics. For example, there is an acute need for reliable methods to predict catastrophic events in populations of plants and/or animals because such events can lead to irreversible consequences such as extinction of species. The potential impact of this method is even higher when applied to disease eradication (populations of infectious diseases). While the dynamics of diseases is a very complex system and the method may not be perfect, it can prove to outperform most other methods because of its ability to filter out noise and the ability to provide forecasts without the need for an accurate model.

DESCRIPTION (provided by applicant): Transmission dynamics of the malaria parasite Plasmodium falciparum have been proposed to be largely driven by immune selection to the major surface antigen of the blood stages known as erythrocyte membrane protein 1 (PfEMP1) encoded by up to 60 members of the var multigene family per haploid genome. Emerging population genetic data have revealed that the malaria transmission system is remarkably complex necessitating a much deeper molecular sampling of parasite populations and the development of computational approaches that extend previous 'strain theory' through the lens of var genetics. This project aims to define the population structure of P. falciparum in the context of var gene diversity and explore epidemiological dynamics in this framework. A team project has been created that brings together mathematical modelers, epidemiologists, entomologists, bioinformaticians, population geneticists and malaria epidemiologists from Ghana and US. Our approach combines both modeling and empirical studies to explore malaria transmission dynamics of P. falciparum at the level of local parasite populations in northern Ghana in the context of var genetics. Specific objectives are: (1) An individual-based, stochastic modeling framework that couples within and between-host transmission and describes the individual-host immunological history of exposure to different var gene repertoires to explore strain dynamics of P. falciparum in relation to age, seasonality and vector intervention. (2): For the first time in malaria epidemiology research, the longitudinal seasonal sampling of entire asymptomatic P. falciparum populations in human communities using deep 454 sequencing of var genes. (3): The quantitative description of var gene diversity and of var repertoires in wet and dry seasons, as well as across a major vector control intervention using indoor residual spraying (IRS), in comparison to microsatellite diversity. Through these objectives',-we-will address the fundamental question of strain structure despite extensive recombination and driven by immune selection, competitive interactions between parasites for hosts in the transmission dynamics. In turn, we will also ask how this structure and associated parasite diversity influence transmission dynamics.

DESCRIPTION (provided by applicant): Transmission dynamics of the malaria parasite Plasmodium falciparum have been proposed to be largely driven by immune selection to the major surface antigen of the blood stages known as erythrocyte membrane protein 1 (PfEMP1) encoded by up to 60 members of the var multigene family per haploid genome. Emerging population genetic data have revealed that the malaria transmission system is remarkably complex necessitating a much deeper molecular sampling of parasite populations and the development of computational approaches that extend previous 'strain theory' through the lens of var genetics. This project aims to define the population structure of P. falciparum in the context of var gene diversity and explore epidemiological dynamics in this framework. A team project has been created that brings together mathematical modelers, epidemiologists, entomologists, bioinformaticians, population geneticists and malaria epidemiologists from Ghana and US. Our approach combines both modeling and empirical studies to explore malaria transmission dynamics of P. falciparum at the level of local parasite populations in northern Ghana in the context of var genetics. Specific objectives are: (1) An individual-based, stochastic modeling framework that couples within and between-host transmission and describes the individual-host immunological history of exposure to different var gene repertoires to explore strain dynamics of P. falciparum in relation to age, seasonality and vector intervention. (2): For the first time in malaria epidemiology research, the longitudinal seasonal sampling of entire asymptomatic P. falciparum populations in human communities using deep 454 sequencing of var genes. (3): The quantitative description of var gene diversity and of var repertoires in wet and dry seasons, as well as across a major vector control intervention using indoor residual spraying (IRS), in comparison to microsatellite diversity. Through these objectives',-we-will address the fundamental question of strain structure despite extensive recombination and driven by immune selection, competitive interactions between parasites for hosts in the transmission dynamics. In turn, we will also ask how this structure and associated parasite diversity influence transmission dynamics.

Malaria control and elimination in areas of high transmission in sub-Saharan Africa present a significant challenge to global health. A large fraction of the population across all ages in these areas harbor Plasmodium falciparum without clinical manifestations, providing a vast reservoir of infection for transmission. This asymptomatic reservoir is sustained by the enormous antigenic diversity of the parasite. Thus, the challenge for hyperendemic regions requires that the malaria field comes to terms with such diversity, studying it as a complex adaptive system. This study addresses the two-way interaction between epidemiology and P. falciparum diversity from the perspective of the multigene and highly recombinant family known as var, which encodes for the major antigen of the blood stage of infection. This project combines theory with field and laboratory work lo generate new understanding of the diverse transmission reservoir of P. falciparum and its resilience to elimination. The first aim is the longitudinal deep sampling of this reservoir in the Bongo District, Ghana following two control interventions (i.e. indoor residual spraying and seasonal malaria chemoprevention). On the basis of age-stratified serial cross-sectional data, this study will assess how informative the var system is to monitor this reservoir under conditions of the control interventions, compared to traditional malariometric indices and neutral molecular markers. The second aim develops strain theory based on a stochastic agent-based model that tracks the history of infection of each host and the evolutionary change of the parasite. Pathogen population structure over time and responses of the var system to intervention are investigated in ways that inform both molecular data analyses and control efforts. The third aim develops a transmission model of intermediate complexity that can be fitted to routine epidemiological data but still incorporates the major effects of parasite diversity on epidemiology. In particular, the existence of a threshold in transmission intensity that impacts parasite antigenic diversity will be investigated. Contributions include computational models at the interface of epidemiology and evolution, and network analyses of population genetic structure applicable to other multigene families of P. falciparum, as well as to other pathogens whose immune escape relies on highly-recombinant gene families.

Humans, and the animals and plants around them, live in a microbial world. It is now well-known that microbes and viruses infect, interact and move through the genomes of every organism on Earth. Relationships among organisms, and with their microbes, can dramatically change the traits, behaviors, and functions of the host plant or animal. Sometimes these interactions are beneficial and sometimes they can be detrimental by causing disease. Many influence host function and can have hidden but important global scale impacts, driving the rates of responses to climate change, health and disease, antibiotic resistance, and more. Understanding how nested interactions within the microbial world occur and influence our ecosystems is critical to controlling their impact. The new Biology Integration Institute, Genomics and Eco-evolution of Multi-Scale Symbiosis (GEMS), focuses on the classical species interaction between clover and honeybee pollinators as a model to understand the impact and dynamics of the myriad of microbes nested within them. The project takes an integrative approach to understand how molecular interactions impact the ecosystem. As a $20 billion US industry, the outcomes of the project studying clover/honeybee nested genomes has practical value as well as being a model for addressing fundamental questions in integrative biology. The researchers in GEMS are collaborative, diverse, interactive scientists and educators who take an inter-disciplinary approach to answer critical questions about how nested genomes interact and affect the world. The project uses a shared leadership model with co-mentorship between trainer and trainee and multisite educational activities. The established institute is designed to integrate biological disciplines to understand how nested genomes respond to environmental change.

GEMS will address the fundamental biological question, How do symbioses unify biology, from molecule to ecosystem? The goal of this project is to establish a framework for how the phenotypic variation generated by the mobility of nested symbionts influences the adaptability of traits and the strength and stability of species interactions. Ultimately, the Institute aims to understand how this variation impacts ecosystem responses to environmental change. The Institute is grounded in the canonical symbiosis between flowering plants and insect pollinators (clover and honeybees), expanding to include interactions nested in their microbial world. The research leverages the extensive knowledge in multiple nested interactions (plant?pollinator, legume?rhizobium, honey bee?microbiome) to build connections within and across systems from the molecular processes that govern establishment of symbiosis and extend phenotypic traits to define how they interact and evolve together in the natural world. Data are integrated with ecological and evolutionary theory to generalize beyond the focal systems to build predictive models. Computer science, statistics, and mathematics expand both the range of biological questions asked and the impact of their answers. Along with the traditional academic silos dividing researchers into molecular and organismal units that prevent a unified view of biology are many others, such as those separating microbe from macrobe, plant from animal, student from faculty, education from research, and diversity, equity, and inclusion from science. Through K-12 education in Spanish and targeting excellence with Project Microbe and the Jim Holland program in three urban and rural communities in the Midwest, GEMS focuses on the intersecting goals of changing how biology is done and who does it, unifying biology by including the small but powerful so often overlooked.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.