An in vitro model of tissue boundary formation for dissecting the contribution of different boundary forming mechanisms. Issue 3 (22nd January 2015) - Javaherian, Sahar; D'Arcangelo, Elisa; Slater, Benjamin; Zulueta-Coarasa, Teresa; Fernandez-Gonzalez, Rodrigo; McGuigan, Alison P.
Abstract : Separation of phenotypically distinct cell populations is necessary to ensure proper organization and function of tissues and organs therefore understanding fundamental mechanisms that drive this cell segregation is important. In this work, authors present an in vivo model system that accurately recapitulates important aspects of cell segregation in vivo and allows dissection of cell behaviours driving cell segregation. Abstract : During development and in adult tissues separation of phenotypically distinct cell populations is necessary to ensure proper organization and function of tissues and organs. Various phenomena, such as differential adhesion, differential mechanical tension and cell–cell repulsion, are proposed to cause boundary formation. Moreover, emerging evidence suggests that interplay between multiple such phenomena can underlie boundary formation. Boundary-forming mechanisms are commonly studied in vivo in complex embryo models or in vitro using simple model systems not reflective of in vivo boundary complexity. To better elucidate the interplay between multiple boundary formation mechanism, there is therefore a need for more relevant in vitro model systems that allow quantitative and concomitant studies of the multiple changes in cell/tissue behaviour that lead to boundary establishment. Here, we develop such a model using patterned co-cultures of two cell populations. Using a set of quantitative tools, we demonstrate that our approach allows us to study the mechanisms underlying boundary formation. We demonstrate that in our specific system differential mechanical tension and modulation of migratory behavior of cells accompany boundary formation. The design of our in vitro model system will allow researchers to obtain quantitative, integrative mechanistic data facilitating a faster and more thorough understanding of the fundamental principles underlying boundary formation.