The major goal of our unit is to understand the mechanisms and outcomes of evolution and to use that understanding to design novel biological tools and forms. Since all living beings and their individual components are the product of evolution, the Evolutionary and Synthetic Biology Unit has an extremely broad and opportunistic approach towards our research. We make no attempt to restrict our curiosity and have no fundamental barriers on selecting any concept or species to study, guiding our curiosity by convenience and feasibility. Over the years we established and excelled in specific areas of research, however, new venues of inquiry continue to emerge.
As a consequence of our curiosity-driven approach, the breadth of our interests and the combination of tools from different fields we use, perspective PhD students should expect to develop an independent research agenda exploring new research questions collaborating with other members of the lab with complementary sets of skills and expertise. Specific ongoing lines of research are outlined below.
How does the information that is encoded on the genotypic level manifest on the level of the phenotype? The representation of the phenotypes of many different genotypes is called the fitness landscape and understanding it is arguably the most important question in all of biology. Knowing which genotypes lead to which phenotypes has immediate implications for our understanding of evolution, disease and is increasingly used in protein engineering. We work to understand fitness landscapes using theory, computational and experimental approaches. Our main ongoing line of work in this direction is the experimental assay of fitness landscapes of specific model proteins. We create large synthetic libraries, query the associated phenotypes of tens of thousands of genotypes and construct various fitness landscapes. We welcome students and postdocs with theoretical and experimental skills who are interested to continue working on existing models in the lab, or to design their own models.
Synthetic biology and protein design
Our work in synthetic biology is guided by our interest in fitness landscapes. An ultimate understanding of which genotypes produce which phenotypes would, for example, allow to predict which protein sequences would confer a novel desired function. As such, protein fitness landscapes are increasingly used by synthetic biology labs to guide protein design. We use data obtained in our lab and by others to design novel protein sequences and functions using machine learning algorithms. This area of research heavily depends on our ability to construct synthetic libraries, interrogate them experimentally, use machine learning to make predictions and bring them back to the lab. We welcome students and postdocs with synthetic biology or machine learning experience who are interested in using fitness landscape data for any biological engineering questions.
Time and again we encounter experimental or computational data that cannot be adequately described by existing theoretical frameworks. When that happens, we sometimes succeed in creating novel theory that leads to novel fundamental understanding of evolution. Examples of our theoretical work includes a model of SARS-CoV-2 epidemiology and evolution, the application of Morse theory to fitness landscapes, novel model of the rates of sequence divergence, understanding the strength of selection on stop codons and a model of protein evolution that explicitly takes into account the extent of epistasis. Theoretical work in our unit is appropriate for independent students and postdocs who are already comfortable with mathematical modeling.
A new area of research in our laboratory is the study of how living things evolve in the laboratory. Using an in-house designed morbidostat we hope to harness the power of selection in the lab and of high-throughput scalable directed evolution experiments. We will then use the setup to query larger fitness landscape but also as a tool for the creation and perfection of new biological functions. This area of research is suitable for students and postdocs with an interest in evolution and with a strong background in microbiology, synthetic or molecular biology or cell culture growth automation.
Evolutionary genomics and bioinformatics
Sequence information continues to reveal fundamentally novel insights into the organization of life and mechanisms of their evolution. Our evolutionary genomics tactics have two forms. First, we use the plethora of available sequence information to ask questions about sequence evolution in a way that has not been done before. Second, if we encounter an interesting question that require previously genes and genomes not previously sequenced, we go out of our way to nature to obtain the necessary samples and get those sequences. So far, we sequenced novel bacteria, archaea, fungi, birds, plants, and various marine and terrestrial invertebrates. For the foreseeable future fungal genomics is likely to be heavily represented in the laboratory. Students or postdocs who wish to pursue this line of research in our laboratory should be proficient or have an interest to extensively use bioinformatic tools. Alternatively, this area is appropriate for researchers with an interest in developing genomics in their established organismal systems.
For the past decade our laboratory played a role in a large international effort to save the spoon-billed sandpiper – a critically endangered species on the East Asian Australian Flyway, on which Okinawa is located. Our work combines a long-term headstarting effort with field work observations around the world and genomic monitoring of the species. Our work is just a part of an international effort of conservation work around the Flyway, including teams from around East Asia and Arctic countries. Students and postdocs with strong experience in population genetics, field work in ornithology or veterinary science are welcome to join this work. Alternatively, researchers with a broad interest in the EAAF or any other species of conservation interest may find a home in our lab in this area.