Bcl11b dose-dependently regulates positive selection of CD8 T cells to the virtual memory fate

Reviewer #1 (Public review):

Summary:

In this study, Sidwell and Rothenberg report a genetically rigorous study whose central finding - reduction of Bcl11b at the positive selection stage reroutes CD8 T cells to the T cell virtual memory (TVM) fate - is well supported by the convergence of elegant mouse models (WT, Bcl11bΔEnh, Bcl11b+/-, Bcl11bR3S). In wildtype mice, Bcl11b acts as a transcriptional repressor that limits the reprogramming of CD8 T cells to the TVM cell type. Reducing Bcl11b dosage partially relieves this repression, resulting in increased development toward the TVM fate. Their analysis reveals several interesting aspects: 1)
Strengths:

Factors that drive CD8 TVM fate are important and relatively poorly understood. This study makes the unexpected and interesting observation that Bcl11b gene dosage impacts TVM during T cell selection in the thymus. The conclusions are strongly supported by multiple independent lines of evidence.

Weaknesses:

The direct genomic targets impacted by Bcl11b heterozygosity were not identified.

Reviewer #2 (Public review):

This manuscript by Sidwell and Rothenberg demonstrates that commitment of CD8 T cells to the virtual memory TVM cell lineage is fine-tuned in a dose-dependent manner by the transcription factor Bcl11b during intrathymic positive selection. Using multiple mouse models, the authors show that a subtle, less than two-fold reduction in Bcl11b expression or disruption of its corepressor-recruitment domain biases developing CD8 single-positive thymocytes toward a TVM cell fate without requiring peripheral activation, lymphopenia, or external cytokine signaling. Mechanistically, this modest decrease in Bcl11b does not alter global chromatin accessibility but instead enhances downstream T-cell receptor (TCR) signal responsiveness, effectively mimicking a high-affinity selection response to divert late-cycling CD8SP thymocytes into the TVM pathway. These data suggest that Bcl11b essentially serves to attenuate the interpretation of TCR (and cytokine) mediated signals to prevent the excessive differentiation characterised by virtual memory T cells and the CD44int naïve T cells. This is distinct from alternative pathways of Tvm development that are driven predominantly by exposure to cytokines, namely IL-4, in the thymus, and serves to reinforce our understanding that Tvm cells are an alternate lineage of T cells that arise during development, in part as a consequence of strong TCR signalling. There are some issues arising, not least of which is why the attenuated Bcl11b expression is insufficient to drive negative selection rather than Tvm formation.

This paper was an absolute pleasure to read given its engaging narrative style. However, in some parts it was a bit long-winded and took a while to get to the destination. Some effort should go into making the narrative more concise, while retaining the thoroughly clear explanation and interpretation of the data.

Reviewer #3 (Public review):

Summary:

The authors explore the impact of a modest (<2-fold) reduction in the expression of Bcl11b on the differentiation of CD8+ T cells, with a special focus on the generation of memory-like cells (sometimes called "virtual" memory cells - or TVM). The manuscript covers a lot of ground, but highlights are using diverse models to show that reduced Bcl11b expression during thymic development (but not in naïve CD8+ T cells that have accessed the periphery) leads to enhanced generation of cells with phenotypic, transcriptional, epigenetic and functional characteristics of TVM; that this is a cell-intrinsic effect, but not apparently driven by enhanced responsiveness to cytokines (which promote TVM in some models); decreased Bcl11b improves T cell sensitivity at the mature (and likely in immature thymocytes). Myriad approaches and controls are used, providing a very thoroughly explored model.

This is a tour-de-force in applying the geneticists tool-box for investigating how a tantalizingly modest decrease in Bcl11b expression impacts the generation of TVM-like cells during thymic development. It is unreasonable to request additional data, but clarification of some key conclusions is needed.

Author response:

We sincerely thank the editors and the three reviewers for their thorough, highly constructive, and positive evaluation of our manuscript. We are gratified by the reviewers’ recognition of the genetic rigor of our study and the compelling nature of our findings regarding the dose-dependent role of Bcl11b in virtual memory CD8 T cell differentiation.

We agree that the reviewers have raised fair and addressable points that will undoubtedly strengthen the final manuscript. Below, we outline our planned revisions to address the primary themes raised in the public reviews:

(1) Genomic Targets and Bcl11b Occupancy (Reviewers #1 & #3)

To address the request for direct genomic targets of Bcl11b, we will incorporate our existing Bcl11b ChIP-seq data from Bcl11b haploinsufficient and control peripheral naïve CD8+ T cells. We will provide comparative analyses demonstrating that Bcl11b ChIP-seq read density per region is highly concordant with population-matched ATAC-seq accessibility profiles, highlighting that direct Bcl11b occupancy closely mirrors the accessible chromatin landscape, which itself we have assayed thoroughly in thymic precursors. Furthermore, we will integrate this ChIP-seq analysis to cross-reference our bulk and pseudobulk differentially expressed gene lists to better define target overlaps.

(2) Phenotypic Definitions, Cytokine Independence, and Quantification (Reviewers #2 & #3)

We appreciate the reviewers’ suggestions to further solidify the phenotypic definitions of our populations. In our revision, we will:

Perform targeted flow cytometry utilizing our Bcl11b haploinsufficient models to provide explicit quantification of CD5 expression across mature thymic (DP to CD8SP) and peripheral CD8 T cell populations.

Include supplementary flow cytometry panels for CD122 alongside our standard CD44, CD62L, and CD49d gating strategies used throughout the manuscript in order to comprehensively lock down the T_VM vs. T_CM phenotypic definitions.

Provide absolute cell counts (rather than just relative frequencies) for neonatal CD8 populations to explicitly confirm absolute expansion.

Expand our evaluation of cytokine-independence by analyzing ImmGen-derived cytokine-response signatures against our scRNA-seq datasets.

(3) Single-Cell Transcriptomic Alignments (Reviewer #3)

To contextualize our findings within the broader literature, we will score our scRNA-seq datasets against the derived T_VM transcriptional signatures recently published by Zhang et al. (2024). While exact cluster-to-cluster matching may be limited by differences in experimental models (e.g., steady-state ontogeny versus influenza infection), this alignment will allow us to demonstrate where our newly minted thymic T_VM(/precursor) cells map along the established peripheral T_VM-state continuum.

Additionally, we will generate targeted split-violin visualizations of T_VM module scores specifically within scRNA-seq Cluster 8. This will visually clarify the transcriptomic shifts driven by Bcl11b haploinsufficiency within this specific cluster, supplementing the DEG/GSEA tables currently provided.

(4) Conceptual Clarifications and Discussion Expansions (Reviewers #2 & #3)

We will expand our discussion to address several excellent conceptual points raised by the reviewers:

Negative Selection vs. Fate Diversion: We will clarify why attenuated Bcl11b alters TCR-induced gene programs without triggering negative selection, emphasizing that Bcl11b dose reduction drives a portional failure of specific transcriptional repression rather than a general deregulation of global TCR-dependent signaling.

Haploinsufficiency vs. Knockout: We will explicitly contrast our haploinsufficient (<2 fold reduction) virtual memory phenotype with the innate-like T (and ex-T) cell phenotypes previously reported in complete Bcl11b loss-of-function models.

Mitochondrial Dynamics: We will refine our text regarding mitochondrial biology to more clearly distinguish between compensatory nuclear transcription (the mitochondrial gene module) and physical organelle performance (mitochondrial membrane potential).

We look forward to submitting the fully revised manuscript and a detailed point-by-point response in the near future.