Synthetic Genetic Controller Circuits for Transcription Factor-Directed Differentiation
openNIBIB - National Institute of Biomedical Imaging and Bioengineering
Synthetic Genetic Controller Circuits for Transcription Factor-Directed
Differentiation
PI: Domitilla Del Vecchio1,2,3
co-I: James J. Collins2,3,4,5
co-I: Thorsten Schlaeger6
1Department of Mechanical Engineering, MIT; 2Department of Biological Engineering, MIT
3Synthetic Biology Center, MIT; 4Broad Institute of MIT & Harvard; 5The Wyss Institute
6 Stem Cell Transplantation Program, Boston Children’s Hospital
PROJECT SUMMARY
The ultimate goal of this project is to create synthetic genetic circuits that accurately control the level of cell fate-
specific transcription factors (TFs) autonomously in response to cell state changes. The underlying hypothesis is that
the level and timing of expression of critical TFs dictates the efficiency of cell conversion protocols and the quality of
produced cells. Here, we focus on the differentiation of human induced pluripotent stem cells (hiPSCs) into hemogenic
endothelial cells (HECs) from which all hematopoietic stem and progenitor cells (HSC/HPCs) arise. Current methods to
derive definite HECs (dHECs), which have the potential to produce adult-type lymphoid cells and HSCs, remain largely
inefficient and are also difficult to execute and scale, and, as a consequence, exhibit high degrees of variability in out-
comes between different labs, hiPSC lines, and even between replicate experiments.These problems hamper analysis
of the underlying developmental processes and pose formidable obstacles to clinical translation of hiPSC-derived blood
cell products since ensuring the safety and cost-effectiveness of the product necessitates high differentiation efficiency
and consistency. Prior work has demonstrated that SCL (S), LMO2 (L), GATA2 (G), and ETV2 (E) TFs, when expressed
in mesodermal cells, activate dHEC gene regulatory networks (GRNs) across species but also that efficient forward
programming to dHECs requires discovery and subsequent implementation of both optimal expression levels and tim-
ing for the TFs. Yet, conventional methods for TF-mediated cell fate programming generally rely on indiscriminate
overexpression with little control on cellular TF levels and without cell state sensing. This is largely due to our inability
to precisely control TF profiles during cell fate programming, and this limitation has prevented discovering optimal tra-
jectories and subsequently enforcing them. Here, we propose synthetic genetic controller circuits that overcome this
hurdle. In Aim 1, we create genetic circuit designs that set TF levels and use them in an efficient in vitro differentiation
protocol to discover the optimal combination of S, L, G, E levels and timing. In Aim 2, we develop a circuit architecture,
based on a novel TET1-enabled positive feedback system, to prevent epigenetic silencing of genetic circuits once de-
livered to hiPSCs. In Aim 3, we make our genetic controller circuits enforce autonomously the optimal SLGE TF levels
found in Aim 1 in response to the hiPSC-to-mesoderm transition. We achieve this by a new autocatalytic ADAR-based
RNA sense-and-respond system, which senses the mesoderm marker Brachyury (TBXT) and enforces user-defined
TF levels in response to it. We anticipate that this process, by being autonomous as opposed to manual and by
enforcing optimal TF trajectories, will result in a more efficient, repeatable, and robust hiPSCs to dHECs conversion
protocol, thereby helping fill the gap to clinical translation. Although in this project we tailor the genetic circuit designs
to controlling SLGE TFs after sensing mesoderm-specific transcripts, the designs can be readily modified to express
different TFs in response to any other cell type- or state-specific transcript. Therefore, we believe that the synthetic
biology technology that we will establish will have broad impact on any other cell fate programming as well as on cell-or
gene-therapy projects where expression levels and timing, as well as resistance to silencing, are important.
Up to $679K
health research