C-MĀIKI – Center for Microbiome Analysis through Island Knowledge and Investigation
The research planned in this effort is a direct response to the recent recognition that the microbial world underlies the health of all components of the biosphere. The University of Hawaiʻi is uniquely positioned, with both the campus human resources and the natural landscape of Hawaiʻi, to explore the microbial underpinnings of natural environments. The C-MĀIKI team has the overarching goal of establishing a research model for the long-term study of the microbiomes of natural watersheds. Our hypothesis is that patterns of microbiome biogeography are impacted by environmental factors, including altitudinal gradients, precipitation events, and density of human populations. The ahupuaʻa offer a distinct, natural, and culturally relevant subject for the study of Hawaiian environmental microbiomes, and provide a compact model system for defining principles underlying the dynamics of microbiomes in more complex watersheds, such as those of the continental United States. The results of the foundational studies proposed below will provide the basis for strong, hypothesis-driven grant proposals. An initial investment is critical to demonstrating the feasibility of proposed research projects and fostering collaborations, as well as to developing research/administrative infrastructure, and supporting preliminary data and robust technological pipelines for data analysis.
Specific Research Aims
We will complete four objectives:
- Organize, launch and promote the C-MĀIKI research efforts;
- Develop and implement a strategy for acquiring the first datasets defining the microbiome of the Waikīkī ahupuaʻa;
- Formulate a sustainable, multidisciplinary plan for extending a comparative analysis to other Hawaiian ahupuaʻa; and,
- Foster productive collaborations among members of C-MĀIKI, which spans 5 UH schools/colleges, as well as between them and other individuals at UH and abroad.
- Molecular / bioinformatics analyses: To create a representative assessment of the baseline diversity of microorganisms present in a given ecosystem, we will use 16S-amplicon sequencing and metabolomics to infer the composition and activities of microbial communities associated with air, water, soil, insects and plants as a biological characteristic of these environments. We will partner with the UH Cyberinfrastructure group for data analysis.
- Mathematical modeling: The microbiome data collected will be complex, and call for formulation of new mathematical models, statistical methods and computational algorithms. Our collaborators in the Department of Mathematics will help identify patterns in these communities using an iterative network analysis, inferring and testing patterns that relate microbes and environments. Models provide a platform for hypothesis testing, tracing chains of causation, sensitivity analyses, and generating new insights and approaches. Vital to this analytical process is work in the LAVA Lab, with whom we will partner to explore theoretical models of the microbiome, using scalable data visualization.
- The first detailed viral/bacterial/fungal microbiome databases of the Waikīkī ahupuaʻa;
- announcement of the groupʻs mission through a team publication in a high-visibility journal;
- well-trained undergraduate researchers in the Scholar’s Program;
- development of an on-line presence for C-MĀIKI; and,
- submission of federal and private grant proposals for long-term research support of the program.
Teaching and outreach objectives
- Build a new biology curriculum for STEM education;
- Create a certificate program in “microbiomes” that emphasizes active undergraduate participation in research activities;
- Share with underserved children, insights into mechanisms underlying the role of microbes in environmental sustainability; and
- Provide the international community with a short-course on bioinformatics analysis, which we foresee as both a service and a revenue stream for the research efforts of C-MĀIKI.
M. McFall-Ngai (PI) (Pacific Biosciences Research Center), A. Amend (Botany Department), M. Chyba (Department of Mathematics), M. Dunlap (Pacific Biosciences Research Center), R. Hamilton (Department of Mathematics), N. Hynson (Botany Department), D. Karl (Center for Microbial Oceanography), & E. Ruby (Pacific Biosciences Research Center)