Development of functionalized lineage tracing tools to characterize and manipulate complex biological systems

Multicellular organisms are composed of heterogeneous groups of cells that, through specialized roles, work in a cooperative fashion to assume higher level functions. Flaws can arise in these multicellular systems, causing a breakdown of cooperativity. This is exemplified in cancer, where dysregulation of cellular proliferation gives rise to invasive tumors that may kill the host. This breakdown from regular order is self-perpetuating and culminates in variegating cell populations that accrue variation at the genotypic and phenotypic levels. Clonal diversity is a hallmark of cancer and a primary determinant in cancer’s ability to evade therapeutic treatment. Characterizing these heterogeneous evolving populations is a daunting challenge, as measurements need to resolve both the variation and clonal identity between constituent cells. Recent technological advancements have made these observations possible, with single-cell omics technologies driving granular resolution of heterogeneous populations and lineage tracing methods providing highly sensitive measurements of clonal composition. The work described in this text details the development and validation of a novel lineage tracing technology, Control Of Lineage by Barcode Enabled Recombinant Transcription (COLBERT), to tag, track, and manipulate clones within a complex biological system. We show that this technique is highly sensitive and broadly effective in multiple cell types. Further, we integrate COLBERT with other methodologies and single-cell workflows to characterize evolutionary dynamics of therapeutic resistance in a CLL model system. Implementing these combined approaches has uniquely enabled the identification of pre-existing drug tolerant subpopulations which are distinct in their clonal composition. With knowledge of these clonally linked phenotypes, we have been able to isolate high tolerance clones for further molecular characterization to uncover the factors stabilizing this survival phenotype. As our technical capabilities increase and our biological questions become more ambitious, it is clear that the next frontiers will be to simultaneously measure and integrate multiple facets of biology at single-cell resolution. The capacity to then manipulate these systems based on understandings of their phenotypic and clonal contexts will offer tremendous opportunities for biological engineering and discovery.