Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.
Read more about eLife’s peer review process.Editors
- Reviewing EditorSarah RussellPeter MacCallum Cancer Centre, East Melbourne, Australia
- Senior EditorBetty DiamondThe Feinstein Institute for Medical Research, Manhasset, United States of America
Reviewer #1 (Public Review):
Summary
In their manuscript, Ho and colleagues investigate the importance of thymic-imprinted self-reactivity in determining CD8 T cell pathogenicity in non-obese diabetic (NOD) mice. The authors describe pre-existing functional biases associated with naive CD8 T cell self-reactivity based on CD5 levels, a well-characterized proxy for T cell affinity to self-peptide. They find that naive CD5hi CD8 T cells are poised to respond to antigen challenge; these findings are largely consistent with previously published data on the B6 background. The authors go on to suggest that CD5hi CD8 T cells are more diabetogenic as 1) the CD5hi naive CD8 T cell receptor repertoire has features associated with autoreactivity and contains a larger population of islet-specific T cells, and 2) the autoreactivity of "CD5hi" monoclonal islet-specific TCR transgenic T cells cannot be controlled by phosphatase over-expression. Thus, they implicate CD8 T cells with relatively higher levels of basal self-reactivity in autoimmunity. However, the interpretation of some of the presented data is questioned and compromises some of the conclusions at this stage. A clearer explanation of the data and experimental methods as well as increased rigor in presentation is suggested.
Specific comments
(1) Figures 1 through 4 contain data that largely recapitulate published findings (Fulton et al., Nat. Immunol, 2015; Lee et al, Nat. Comm., 2024; Swee et al, Open Biol, 2016; Dong et al, Immunology & Cell Biology, 2021); it is noted that there is value in confirming phenotypic differences between naive CD5lo and CD5hi CD8 T cells in the NOD background. It is important to contextualize the data while being wary of making parallels with results obtained from CD5lo and CD5hi CD4 T cells. There should also be additional attention paid to the wording in the text describing the data (e.g, the authors assert that, in Figure 4C, the "CD5hi group exhibited higher percentages of CD8+ T cells producing TNF-α, IFN-γ and IL-2" though there is no difference in IL-2 nor consistent differences in TNF-α between the CD5lo and CD5hi populations).
(2) The comparison of a marker of self-reactivity, CD5 in this case, on broad thymocyte populations (DN/DP/CD8SP) is cautioned (Figure 5). CD5 is upregulated with signals associated with b-selection and positive selection; CD5 levels will thus vary even among subsets within these broad developmental intermediates. This is a particularly important consideration when comparing CD5 across thymic intermediates in polyclonal versus TCR transgenic thymocytes due to the striking differences in thymic selection efficiency, resulting in different developmental population profiles. The higher levels of CD5 noted in the DN population of NOD8.3 mice, for example, is likely due to the shift towards more mature DN4 post-b-selection cells (Figure 5E, Supplementary Figure 3A). Similarly, in the DP population, the larger population of post-positive selection cells in the NOD8.3 transgenic thymus may also skew CD5 levels significantly (Figure 5F, Supplementary Figure 3A). Overall, the reported differences between NOD and NOD8.3 thymocyte subsets could be due largely to differences in differentiation/maturation stage rather than affinity for self-antigen during T cell development. The lack of differences in CD5 levels of CD8 SP thymocytes (Fig. 5B) and CD8 T cells in the pancreas draining lymph nodes (Fig. 6B) from NOD vs NOD8.3 mice also raises questions about the relevance of this model to address the question of basal self-reactivity and diabetogenicity; the phenotype of the CD8 T cells that were analyzed in the pancreas draining lymph nodes is not clear (i.e., are these gated on naive T cells?). Furthermore, the rationale for the comparison with NOD-BDC2.5 mice that carry an MHC II-restricted TCR is unclear.
(3) In reference to the conclusion that transgenic Pep phosphatase does not inhibit the diabetogenic potential of "CD5hi" CD8 T cells, there is some concern that comparing diabetes development in mice receiving polyclonal versus TCR transgenic T cells specific for an islet antigen is not appropriate. The increased frequency and number of antigen-specific T cells in the NOD8.3 mice may be responsible for some of the observed differences. Further justification for the comparison is suggested.
(4) There is an interesting observation that TCR sequences from the CD5hi CD8 T cells may share some characteristics with diabetogenic T cells found in patients (e.g., CDR3 length) and that IGFP-specific T cells may be preferentially found within the CD5hi naive CD8 T cell population. However, there are questions about the reproducibility of the TCR sequencing data given the low number of replicates and sampling size. In particular, the TRAV, TRAJ, TRBV, and TRBJ frequency is variable across sequencing runs. Is this data truly representative of the overall TCR repertoire of CD5hi vs CD5lo CD8 T cells?
(5) For clarity and transparency, please consider:
● Naïve T cell gating/sorting is not always clear.
● Additional controls should be considered for tetramer and cytokine stains/gating, in particular.
● The reporting of the percentage of cells expressing a certain marker (e.g., activation marker) and gMFI of this marker is often used interchangeably. Reporting gMFI is most appropriate for unimodal populations (normal distribution), but some of the populations for which gMFI is reported are bimodal (e.g., DN CD5 in Supplementary Figure 3D, etc.). The figure legends throughout the paper do not clearly explain the gating strategy when reporting gMFI. When reporting frequency, the reference population is often unclear (% of parent population, % of naive CD8 T cells, etc.).
● Several items are missing or incorrectly described in the methods section; for example:
--EdU incorporation assay presented in Supplementary Figure 4.
--Construction of the Overlapped Count Matrix in Figure 7G.
--Clonality, Pielou's evenness, richness, and medium metrics, although reported in the methods, are not shown in any of the figures as far as noted.
Reviewer #2 (Public Review):
Summary:
In this study, Chia-Lo Ho et al. study the impact of CD5high CD8 T cells in the pathophysiology of type 1 diabetes (T1D) in NOD mice. The authors used high expression of CD5 as a surrogate of high TCR signaling and self-reactivity and compared the phenotype, transcriptome, TCR usage, function, and pathogenic properties of CD5high vs. CD5low CD8 T cells extracted from the so-called naive T cell pool. The study shows that CD5high CD8 T cells resemble memory T cells poised for a stronger response to TCR stimulation and that they exacerbate disease upon transfer in RAG-deficient NOD mice. The authors attempt to link these features to the thymic selection events of these CD5high CD8 T cells. Importantly, forced overexpression of the phosphatase PTPN22 in T cells attenuated TCR signaling and reduced pathogenicity of polyclonal CD8 T cells but not highly autoreactive 8.3-TCR CD8 T cells.
Strengths:
The study is nicely performed and the manuscript is clear and well-written. Interpretation of the data is careful and fair. The data are novel and likely important. However, some issues would need to be clarified through either text changes or the addition of new data.
Weaknesses:
The definition of naïve T cells based solely on CD44low and CD62Lhigh staining may be oversimplistic. Indeed, even within this definition, naïve CD5high CD8 T cells express much higher levels of CD44 than CD5low CD8 T cells.
Reviewer #3 (Public Review):
Summary:
In this study, Ho et al. hypothesised that autoreactive T cells receiving enhanced TCR signals during positive selection in the thymus are primed for generating effector and memory T cells. They used CD5 as a marker for TCR signal strength during their selection at the double positive stage. Supporting their hypothesis, naïve T cells with high CD5 levels expressed markers of T cell activation and function at higher levels compared to naïve T cells with lower levels of CD5. Furthermore, results showed that autoimmune diabetes can be efficiently induced after the transfer of naïve CD5 hi T cells compared to CD5 lo T cells, this provided solid evidence in support of their hypothesis that T cells receiving higher basal TCR signaling are primmed to develop into effector T cells. These results have to be carefully interpreted because both CD5 hi and CD5 lo naïve T cells are capable of inducing diabetes, meaning that both CD5 hi and CD5 lo T cell compartments harbour autoreactive T cells. The evidence that transgenic PTPN22 expression could not regulate T cell activation in CD5 hi TCR transgenic autoreactive T cells was weak.
Strengths:
(1) Demonstrating that CD5 hi cells in naïve CD8 T cell compartment express markers of T cell activation, proliferation, and cytotoxicity at a higher level.
(2) Using gene expression analysis, the study showed CD5 hi cells among naïve CD8 T cells are transcriptionally poised to develop into effector or memory T cells.
(3) The study showed that CD5 hi cells have higher basal TCR signaling compared to CD5 lo T cells.
(4) Key evidence of pathogenicity of autoreactive CD5 hi T cells was provided by doing the adoptive transfer of CD5 hi and CD5 lo CD8 T cells into NOD Rag1-/- mice and comparing them.
Weaknesses:
(1) Although CD5 can be used as a marker for self-reactivity and T cell signal strength during thymic development, it can be also regulated in the periphery by tonic TCR signaling or when T cells are activated by its cognate antigen. Hence, TCR signals in the periphery could also prime the T cells toward effector/memory differentiation. That's why from the evidence presented here it cannot be concluded that this predisposition of T cells towards effector/memory differentiation is programmed due to higher reactivity towards self-MHC molecules in the thymus, as stated in the title.
(2) Experiments done in this study did not address why CD5 hi T cells could be negatively regulated in NOD mice when PTPN22 is overexpressed resulting in protection from diabetes but the same cannot be achieved in NOD8.3 mice.
(3) Experimental evidence provided to show that PTPN22 overexpression does not regulate TCR signaling in NOD8.3 T cells is weak.
(4) TCR sequencing analysis does not conclusively show that the CD5 hi population is linked with autoreactive T cells. Doing single-cell RNAseq and TCR seq analysis would have helped address this question.
(5) When analysing data from CD5 hi T cells from the pancreatic lymph node, it is difficult to discriminate if the phenotype is just because of T cells that would have just encountered the cognate antigen in the draining lymph node or if it is truly due to basal TCR signaling.
(6) In general, authors should provide relevant positive-negative controls and gating with representative flow-cytometry plots when they are showing activation of T cells in CD5 lo and CD5 hi compartments.