David Gennert

Dynamic regulatory network controlling Th17 cell differentiation

Despite their importance, the molecular circuits that control the differentiation of naive T cells remain largely unknown. Recent studies that reconstructed regulatory networks in mammalian cells have focused on short-term responses and relied on perturbation-based approaches that cannot be readily applied to primary T cells. Here we combine transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based perturbation tools to systematically derive and experimentally validate a model of the dynamic regulatory network that controls the differentiation of mouse TH17 cells, a proinflammatory T-cell subset that has been implicated in the pathogenesis of multiple autoimmune diseases. The TH17 transcriptional network consists of two self-reinforcing, but mutually antagonistic, modules, with 12 novel regulators, the coupled action of which may be essential for maintaining the balance between TH17 and other CD4+ T-cell subsets. Our study identifies and validates 39 regulatory factors, embeds them within a comprehensive temporal network and reveals its organizational principles; it also highlights novel drug targets for controlling TH17 cell differentiation.

Deconstructing transcriptional heterogeneity in pluripotent stem cells

Pluripotent stem cells (PSCs) are capable of dynamic interconversion between distinct substates; however, the regulatory circuits specifying these states and enabling transitions between them are not well understood. Here we set out to characterize transcriptional heterogeneity in mouse PSCs by single-cell expression profiling under different chemical and genetic perturbations. Signalling factors and developmental regulators show highly variable expression, with expression states for some variable genes heritable through multiple cell divisions. Expression variability and population heterogeneity can be influenced by perturbation of signalling pathways and chromatin regulators. Notably, either removal of mature microRNAs or pharmacological blockage of signalling pathways drives PSCs into a low-noise ground state characterized by a reconfigured pluripotency network, enhanced self-renewal and a distinct chromatin state, an effect mediated by opposing microRNA families acting on the Myc/Lin28/let-7 axis. These data provide insight into the nature of transcriptional heterogeneity in PSCs.

Preparation of Single-Cell RNA-Seq Libraries for Next Generation Sequencing

For the past several decades, due to technical limitations, the field of transcriptomics has focused on population‐level measurements that can mask significant differences between individual cells. With the advent of single‐cell RNA‐Seq, it is now possible to profile the responses of individual cells at unprecedented depth and thereby uncover, transcriptome‐wide, the heterogeneity that exists within these populations. This unit describes a method that merges several important technologies to produce, in high‐throughput, single‐cell RNA‐Seq libraries. Complementary DNA (cDNA) is made from full‐length mRNA transcripts using a reverse transcriptase that has terminal transferase activity. This, when combined with a second “template‐switch” primer, allows for cDNAs to be constructed that have two universal priming sequences. Following preamplification from these common sequences, Nextera XT is used to prepare a pool of 96 uniquely indexed samples ready for Illumina sequencing. Curr. Protoc. Mol. Biol. 107:4.22.1‐4.22.17.

Abstract A10: A distinct gene module for T cell dysfunction uncoupled from T cell activation and controlled by metallothioneins

Reversing the dysfunctional (also known as “exhausted”) T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and for only some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we leveraged mouse models to analyze RNA profiles of CD8+ tumor-infiltrating lymphocytes (TILs) at various functional states. In a comparative study we identified metallothioneins, regulators of zinc metabolism, as drivers of T cell dysfunction and used genetic perturbation to identify, for the first time, a distinct gene module for T cell dysfunction that is uncoupled from T cell activation and associated with a CD8+ Treg signature. An analysis of TILs at single-cell resolution revealed that our dysfunction module negatively correlates with activation signatures also at the single-cell level, indicating that our uncoupled signatures for T cell dysfunction and activation can represent cell-intrinsic states. Clustering of the single-cells revealed a previously uncharacterized subpopulation of CD8+ TILs that was strongly enriched for our novel dysfunction signature, but not for activation signatures. This subpopulation was depleted of cells from a metallothionein KO mouse model in which T cell dysfunction was not observed, implying that we have indeed identified a phenotypically dysfunctional subpopulation. Using CRISPR/Cas9 genome editing we validate that Gata-3, a transcription factor expressed specifically in our identified subpopulation, is a driver of the dysfunctional phenotype in CD8+ TILs. Our results open novel avenues for specifically targeting the dysfunctional T cell state while leaving T cell activation programs intact. Citation Format: Meromit Singer, Chao Wang, Le Cong, Nemanja D. Marjanovic, Monika S. Kowalczyk, Huiyuan Zhang, Jackson Nyman, Kaori Sakuishi, Sema Kurtulus, David Gennert, Junrong Xia, John YH Kwon, James Nevin, Rebecca H. Herbst, Itai Yanai, Orit Rozenblatt-Rosen, Vijay K. Kuchroo, Aviv Regev, Ana C. Anderson. A distinct gene module for T cell dysfunction uncoupled from T cell activation and controlled by metallothioneins. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A10.