Allen Discovery Center at Tufts University
Reading and Writing the Morphogenetic Code
Living systems are able not just to grow tissues, but to maintain them over time and, in some cases, regenerate them when they are altered by injury or disease. Underlying this ability is the morphogenetic code, which consists of the mechanisms and information structures by which networks of cells represent and dynamically regulate the target morphology of the system.
With the ultimate goal being the top-down control of complex biological shape, we need to understand how biological systems control anatomy, from the level of tissues to the entire body plan. Control over these processes would have transformative implications for not only biology and medicine but many other disciplines.
Current technology and conceptual schemes target the level of proteins, genes and cells, but are unable to link these to large-scale anatomy. The Discovery Center team will fill this major gap by building new tools that exploit endogenous bioelectric and regulatory pathways, resulting in impactful new capabilities in regenerative medicine.
Bioelectricity is one layer of a complex morphogenic field that harnesses individual cell behavior toward the anatomical needs of the body. However, it is not simply yet another mechanism of single-cell control. Briefly altering the bioelectric connectivity of a cellular network enables permanent rewriting of an organism’s target morphology, making it a convenient and tractable entry point for understanding and rationally controlling information processing that maintains larger-scale order in vivo.
The team seeks to understand where bioelectric patterns originate, how they map the organization of cells, and how their code is interpreted by cells. This will enable the team to create the first quantitative theory of top-down pattern control, and ultimately harness new modalities for reading and writing the bioelectric code with applications in embryogenesis, regeneration, cancer and bioengineering.
Michael Levin, Ph.D.
Prior to college, Michael Levin worked as a software engineer and independent contractor in the field of scientific computing. He attended Tufts University, interested in artificial intelligence and unconventional computation. To explore the algorithms by which the biological world implemented complex adaptive behavior, he got dual B.S. degrees, in CS and in Biology. He received a PhD from Harvard University for the first characterization of the molecular-genetic mechanisms that allow embryos to form consistently left-right asymmetric body structures in a universe that does not macroscopically distinguish left from right (1992-1996); this work is on Nature’s list of 100 Milestones of Developmental biology of the Century. He then did post-doctoral training at Harvard Medical School (1996-2000), where he began to uncover a new bioelectric language by which cells coordinate their activity during embryogenesis. His independent laboratory (2000-2007 at Forsyth Institute, Harvard; 2008-present at Tufts University) develops new molecular-genetic and conceptual tools to understand information processing in regeneration, embryogenesis, and cancer suppression. He holds the Vannevar Bush endowed Chair and serves as director of the Tufts Center for Regenerative and Developmental Biology. Recent honors include the Scientist of Vision award and the Distinguished Scholar Award. His group’s specific focus is on endogenous biophysical mechanisms that implement decision-making during pattern regulation, and harnessing voltage gradients that serve as prepatterns for anatomical polarity, organ identity, gene expression, and epigenetic modification. The lab’s current main directions are: 1) understanding how somatic cells form bioelectrical networks for processing pattern memories and guiding morphogenesis, 2) creating next-generation AI tools for helping scientists understand top-down control of pattern regulation (a new bioinformatics of shape), and 3) using these insights to discover new capabilities in regenerative medicine and engineering.