Traject3d allows label-free identification of distinct co-occurring phenotypes within 3D culture by live imaging
Eva C. Freckmann, Emma Sandilands, Erin M. Cumming, Matthew Neilson, Álvaro Román‐Fernández, Konstantina Nikolatou, Marisa Nacke, Tamsin R.M. Lannagan, Ann Hedley, David Strachan, Mark J. Salji, Jennifer P. Morton, Lynn McGarry, Hing Y. Leung, Owen J. Sansom, Crispin Miller, David M. Bryant
Abstract
Single cell profiling by genetic, proteomic and imaging methods has expanded the ability to identify programmes regulating distinct cell states. The 3-dimensional (3D) culture of cells or tissue fragments provides a system to study how such states contribute to multicellular morphogenesis. Whether cells plated into 3D cultures give rise to a singular phenotype or whether multiple biologically distinct phenotypes arise in parallel is largely unknown due to a lack of tools to detect such heterogeneity. Here we develop Traject3d (Trajectory identification in 3D), a method for identifying heterogeneous states in 3D culture and how these give rise to distinct phenotypes over time, from label-free multi-day time-lapse imaging. We use this to characterise the temporal landscape of morphological states of cancer cell lines, varying in metastatic potential and drug resistance, and use this information to identify drug combinations that inhibit such heterogeneity. Traject3d is therefore an important companion to other single-cell technologies by facilitating real-time identification via live imaging of how distinct states can lead to alternate phenotypes that occur in parallel in 3D culture.