What drives us

What distinguishes a non-living matter from a living matter? They are both made of atoms. They are both governed by the same fundamental physical laws and principles. A single atom doesn't have a "life" of its own. If we put two atoms together, we still don't get a living system. But step by step, as we wire together three, four, five, and eventually many Avogadro numbers of atoms together in just the "right" way, a living system emerges. In ways that are poorly understood, these remarkable features of life emerge from the myriad interactions among the molecules that compose cells. One of the biggest challenges that physical scientists have yet to resolve is identifying quantitative rules and principles governing living systems, and then showing how they emerge from putting together fundamental physical laws governing the behaviours of lifeless molecules. By doing so, one day, we might truly understand living systems through a physics framework in the same way that we now understand non-living systems today. Our lab is motivated by this very fundamental goal. We perform experiments that perturb, rewire, build, and eliminate interactions within unicellular and multicellular systems to reveal quantitative principles of living systems.

Below, we outline our lab's specific research activities.

How cells "talk" to each other to coordinate their gene expression - Emergent collective behaviours, rules, and frameworks.

Our papers on this topic:

Mapping cellular automaton to a drifting-diffusing particle

E. P. Olimpio*, Y. Dang*, and H. Youk (*Co-first authors)
Statistical dynamics of spatial-order formation by communicating cells
iScience (April 2018)
   research article + Supp. Info (.pdf)   

                                              Positive feedbacks and controlling signal-range

T. Maire and H. Youk
Molecular-level tuning of cellular autonomy controls collective behaviors of cell populations
Cell Systems (November 2015)
   research article (.pdf)       supplementary material (.pdf)   

Biological challenge - In multicellular systems - whether they are tissues, embryos, or microbial biofilms - hundreds of cells coordinate their gene expressions by "talking" to each other. They do this by secreting and sensing signalling molecules. Our lab builds theories and performs experiments to discover how cells can reliably coordinate their gene expressions via diffusing signalling molecules, what the cells can then collectively do, and theoretical frameworks that are "simple" yet realistic for understanding the complex web of cell-cell communications and intracellular signal-processing.
              The simplest example of a cellular communication that uses diffusing signalling molecules is a cell - which we call a "secrete-and-sense cell" - secreting a signalling moleucle while also sensing that same molecule by making a receptor for it. A secrete-and-sense cell can thus talk to itself (by capturing its own molecule) and simultaneously talk to other cells (by sending its molecule to other cells). It can tune by how much it talks to itself and to other cells. Due to this versatility, and its ubiquity in nature (e.g., quorum-sensing microbes and hair follicles, autocrine-signalling T-cells), we have been using secrete-and-sense cells as a workhorse for understanding multicellular coordination of gene-expressions. We are also investgating other cell types that secrete diffusing signalling molecules.

Physical challenge - A living cell is too complex to be understood through equations that describe its constituent molecules. A similar challenge exists for non-living systems such as strongly correlated electronic systems. There, physicists have discovered “emergent rules” that govern them. These rules arise from the microscopic laws and are cast in the language of statistical mechanics. Our lab seeks to discover if the complex web of cell-cell communication and intracellular signal-processing circuits also yield a concise, higher-level picture of how hundreds of cells coordinate their gene expressions. We use engineered and natural multicellular systems to aid our search. We ask if these emergent rules can be cast in statistical-mechanics-type frameworks that take ideas from statistical physics of non-living systems and then adapt them to multicellular systems. A challenge here is that conventional metrics of physics (e.g., force, energy, entropy, momentum) cannot describe how cells coordinate their gene expressions because these systems typically do not use mechanical, electrical, or magnetic mechanisms. By investigating distinct multicellular systems, we hope to find common statistical-physics-type principles that govern coordination of gene expressions by multiple cells.