Project- The Gunawardena Lab studies cellular information processing using a combination of mathematical and experimental techniques. In recent years, the lab has shifted from being primarily experimental to being primarily theoretical, in part because our experiments are now done in collaboration and in part because the theoretical problems have become more challenging. We have a tradition of mentoring undergraduate students into scientific research and welcome students from groups who are under-represented in science. Several of our students have been first authors on papers arising from their undergraduate work (http://vcp.med.harvard.edu/people). Students come from a range of backgrounds and usually work on mathematical projects arising from the main research directions in the lab. At present, we are interested in the following kinds of questions, which can be explored further through our papers (http://vcp.med.harvard.edu/papers.html).
(1) How is information encoded by protein post-translational modification?
(2) How does energy expenditure allow cells to process information better?
(3) How do biochemical mechanisms function robustly while being plastic on
Our lab offers a halfway house between the biological and the mathematical sciences. If you are not scared of mathematics, have a genuine interest in modern biology and are willing to work hard for a couple of months, you could have a lot of fun.
Project- Imaging cellular societies
Cells are the basic computational units of living systems. Each one has a genome which provides its code, it has networks of interacting proteins that can perform computations, and it has a small set of signaling proteins and receptors that allow it to communicate. Importantly, this communication tends to be very short range—just a few cell diameters. In the context of a developing embryo or regenerating adult, how do thousands of individual cells, each making their own decisions, cooperate to forward the goals of the organism they comprise despite living in an anarchist society in which no one is in charge? We investigate this question by performing timelapse fluorescent microscopy in zebrafish embryos which allows us to watch what each and every cell in an entire society of cells is thinking as they cooperate to build an embryo.
Project #1: Deep phenotyping of behavior in freely-moving rats
Project #2: Information processing in the olfactory systems
Project #3: Algorithmic and neuronal models of the dauer decision
Project #4: Biological plausible learning algorithms
The molecular and ecological basis of coexistence and speciation in microbes
How do populations of cells that look exactly the same diverge over evolutionary time to form distinct species? Conversely, how do two populations of cells that are nothing alike simultaneously inhabit, co-evolve, and even symbiotically help each other in the same environment? Although we think of these two questions in very different contexts, they are inherently linked to each other, as cells can only continue to diverge into distinct species when interactions between them (or sometimes lack thereof) allows for this diversity to be maintained. We will address both these questions using microbial evolution experiments. In an ongoing evolution experiment with E. coli that has lasted over 30 years (https://en.wikipedia.org/wiki/E._coli_long-term_evolution_experiment), many populations show signatures of divergent subpopulations that co-exist for over 10,000 generations. Using evolution and competition experiments, we will probe whether co-existence in these populations is driven by negative frequency dependent selection, and if the nature of this coexistence evolves over time. Using metabolomics and coexistence assays, we will identify the mechanism of frequency dependence: what by-products are the subpopulations producing and how are these by-products influencing both co-existing subpopulations? Moreover, how does the production and effects of these by-products change over evolutionary time? Even in a constant environment consisting of a single carbon source, it is a mystery how microbes can build complex communities that involves cross-feeding of varied metabolites. And because divergence occurs over such long evolutionary timescales in this experiment (50,000 generations in one case!), we will evaluate our work in the context of microbial speciation.
Higgins Lab: How do single-cell properties propagate to pathologic outcomes in sickle cell disease?
Supervisor Names: Brody Foy, Daniel De Souza, and John Higgins
Sickle cell disease is caused by a single amino acid substitution generating a variant hemoglobin molecule that can polymerize inside red blood cells (RBCs) under conditions of low oxygen. These intracellular polymers dramatically reduce the RBC’s normal flexibility and compliance. Collectively, when enough RBCs contain enough polymer, blood effective viscosity increases resulting in increased shear stress and inflammation in blood vessel walls, decreased tissue oxygenation, and increased risk for vaso-occlusive episodes where local blood flow stops entirely leading to stroke, acute chest syndrome, avascular necrosis, and other serious consequences.
We are working to understand the mechanistic links between changes at the single-cell level and increased risk of disease complications for patients. To help us pursue this research goal, we are looking for a summer intern interested in helping with both experimental and computational modeling work. Experimental work will involve assisting in measurements of hemoglobin polymer in thousands of individual RBCs from sickle cell patients, some stable and untreated and some participating in a local gene therapy clinical trial. Computational work will involve mathematical and statistical modeling of probability distributions of single-cell measurements as well as fluid mechanics-based modeling of in vitro blood rheology under controlled oxygen tension. These models will then be used to understand and to quantify how functional and mechanical changes in individual blood cells affect the overall flow and function of human blood.
A suitable student for this project should already have a basic understanding of how to solve differential equations numerically, some prior exposure to programming (either in MATLAB or Python), and have taken at least one college-level probability/statistics course. Additional coursework in applied mathematics, computation, and human physiology is desirable but not necessary, as a large part of the project will be the exploration of these areas.
Through this project the student will:
- Learn how to integrate experimental data into mathematical models
- Learn basic machine learning techniques
- Learn some basics of human physiology and clinical hematology
- Undertake a combination of wet-lab work, mathematical work, and programming
Bacteria are among the simplest and most abundant life forms on the plant. Even in our own body, we carry about 2 to 4 pounds of bacteria with us. Those bacteria play an important role for health and disease. In our modern microbiology lab, you will get the chance to learn how we study bacteria. You will learn how to modify DNA of the bacteria to reprogram their behavior. In our lab, we use this technique to learn more how bacteria control their shape, size and growth. If we understand better how bacteria grow, we can develop drugs that dysregulate growth and kill the bacteria. Such drugs, the antibiotics, are desperately needed to treat illnesses like urinary tract infections, diarrhea, lung infections or sepsis from which millions of Americans suffer each year and tens of thousands die. We also study how bacteria can resist such drugs, because there is a growing problem of antibiotic resistant infections in the clinic.
The fruit fly Drosophila melanogaster is one of the best model organisms to study the basic biology underlying the growth of tumors and the development of cancer. An impressive toolkit of genetic techniques is available in the fly that allows us to probe the role of different genes in causing cancer or preventing its growth. It is becoming increasingly clear that interactions between the tumor and the surrounding healthy tissue play an important role in the progression of cancer. You will learn how to induce tumors in flies and follow their progression using microscopy. We will teach you the basics of compiling genetic constructs in flies by setting up crosses, but also by making genetic constructs. In addition, you will get the opportunity to work with mammalian cell lines and apply state-of-the-art microscopy methods to study the homeostasis of epithelial tissues, the tissues that make up the majority of tissues in our body and also give rise to the vast majority of cancers.
Klein Lab: Project TBD
Prigozhin Lab: Project TBD
Baym Lab: Project TBD
Cluzel Lab: Project TBD
Murthy Lab: Project TBD
Lahav Lab: Project TBD