H2-O deficiency promotes regulatory T cell differentiation and CD4 hyperactivity

  1. Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
  2. Department of Pharmaceutics, College of Pharmacy, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju 28644, Korea


  • Reviewing Editor
    Juan Carlos Zúñiga-Pflücker
    University of Toronto, Sunnybrook Research Institute, Toronto, Canada
  • Senior Editor
    Satyajit Rath
    Indian Institute of Science Education and Research (IISER), Pune, India

Reviewer #1 (Public Review):

The non-classical MHCII-like protein H2-M is essential for the loading of peptides on MHCII. The discovery that DM was partnered with a second MHCII-like protein, H2-O, which squelched or modified its activity was confounding. It was immediately speculated that H2-O was likely diminished self-peptide presentation. This led to the hypothesis that H2-O was involved in preventing unwanted CD4 T cell activation, thereby making autoimmunity less likely. 25 years of analysis of H2-O deficient mice have, indeed, shown that the self-peptide repertoire in the absence of H2-O is modestly altered. Demonstrating that autoimmunity results from this altered peptide repertoire has been decidedly less convincing. Old mice are reported to have increased serum anti-nuclear antibody titers, but mice prone to type 1 diabetes (T1D) and systemic lupus erythematosus (SLE) were not impacted by the loss of H2-O (Lee et al, 2021). Induction of the multiple sclerosis-like disease, EAE, in mice, was also shown to not be impacted by Lee et al 2021, although in a previous paper (Welsh et al 2020), the authors of this current manuscript suggest otherwise. Unfortunately, these discrepancies are not acknowledged by the authors, and the papers are, for the most part, not referenced.

In addition to antigen-presenting cells, H2-O is also found in MHCII-expressing medullary epithelial cells, suggesting it might play a role in T-cell selection. Direct data to support this idea, however, has, at most, shown a minimal impact. In this manuscript, the authors follow up on their previous paper (Welsh et al, 2020) to further evaluate changes to T cell development. The conclusions are that H2-O impacts Treg development and changes the frequency and homeostasis of CD4 T cells. Although these would be interesting results, the data analysis is flawed, the presentation is incomplete, and the conclusions are exaggerated.

T-cell development analysis shown in Figs. 1 and 2 use the discovery from the Hogquist lab (Breed et all 2019) that thymocytes destined for clonal deletion can be differentiated from those still "auditioning" for selection by FACS for expression of cleaved caspase 3. Detection relies on complex FACS analysis that requires the exclusion of multiple populations, followed by accurate gating on CD5+TCRb+ cells (see Hogquist Fig. 1A). The authors apparently neglected to use the essential gating steps, but rather only used CD4 and CCR7 expression (Fig. 1A). This deviation from the Hogquist approach makes interpretation of Figs 1 and 2 meaningless. Even if this is an oversight in the description of the experiments, key conclusions are drawn from minimal changes to CD69 expression. CD69 is expressed as a continuum in the thymus (a "shoulder") making gating somewhat subjective and prone to variation from experiment to experiment. At the minimum, FACS data should be shown to indicate how these changes were measured, plus variations from mouse to mouse should be plotted, with statistics. FACS data needs to be shown to define how the complex semi-mature, M1, and M2 populations were defined (see Hogquist Fig. 2) from which key conclusions are drawn.

To make the data more robust, 1) cell numbers must be included for all experiments;

  1. rather than normalizing results to "the average H2-O WT levels", the actual data should be included;

  2. figures should be more completely labeled/described;

  3. FACS gating strategies should be clearly laid out (again, see Hogquist for examples). Furthermore, efforts must be made to explain why results are so different from analyses of H2-O deficient mice that have been published by many other groups. For example, the reported "dramatic increase in the proportion of CD3+CD4+ T cells" is not consistent with previous reports starting with Lars Karlsson's initial report (Liljedahl et al 1998). Extensive spontaneous activation of CD4 T cells has also not been reported in other papers that have studied these mice. Again, the paper is not placed in the context of the long, very thorough analysis of both the H2-O deficient mice and the study of H2-O/DO and H2-M/DM in general.

Reviewer #2 (Public Review):


The manuscript's main claim is that the absence of H2-O, a component of the MHC II presentation pathway, promotes regulatory T cell development and function.

Unfortunately, the submitted material is not sufficient for proper evaluation of the manuscript, both in terms of the significance of the findings and the strength of the supporting evidence.

Major issues include:

- the scRNAseq (shown in Fig. 5) is too rudimentary to allow any conclusion. Statements in the text (eg "Principle Component Analysis (PCA) of the normalized scRNA-seq data identified 11 distinct CD4 T cell clusters", line 166) suggest that additional expertise should be leveraged for these analyses.

- Most flow cytometry data (Figs. 1 and 2) shows marginal (at best) differences on y-axis truncated bar graphs, with no original data plot, gating strategies, etc., severely challenging conclusions drawn from this data.

Author Response:

We are sorry that both eLife and the Reviewers feel that our submitted studies are currently insufficient to support our hypothesis that loss of H2-O function affects thymic Treg selection. As this is the first study directly evaluating loss of H2-O in the thymus we do not feel that we overstated our finding as suggested by Reviewer 1. We hope that a revised version of the manuscript can satisfy the reviewers’ criticisms.

-Reviewer 1 is asking us to address the presumed discrepancies between our previous work (Welsh et al 2020, https://doi.org/10.1371/journal.pbio.3000590) and data from Lee et al. 2021 (https://doi.org/10.4049/jimmunol.2100650) in this current manuscript, which does not report on the development of EAE in DO-KO and DO-WT mice. All experiments here are on naïve mice. As such, we wish to justify our lack of discussion of Lee et al (2021) findings.

Lee et al (2021) reported the effects of DO on both EAE and SLE development, they used mainly H2-Oβ KO mice. As we have never used these CRISPR generated mice, we cannot have a direct in-house comparison. However, we did note that reported disease curve for female H2-Oβ KO mice had a similar trend indicating increased EAE disease development, similar to what we have reported back in our 2020 paper (Welsh et al PLoS Biology). In the single experiment that utilized H2-Oβ KO mice for EAE development, Lee et al found a different disease trend than ours. However, Lee et al (2021)’s tested only 4-5 mice per group in the single experiment and their measurement of the disease development solely relied on visual assessment of the limbs and tail functionality. Our study verified EAE disease development by multiple approached including analyses of MOG-specific tetramer staining of the CNS CD4 lymphocyte infiltrate, and in vivo NIRF whole-body imaging on diseased DO-WT and DO-KO mice using an antibody probe specific to MBP. We had repeated our experiments on the disease development greater than 15 times using 5-8 mice per group. Below is an excerpt from our Results Section of Welsh et al PLoS Biology, clearly explaining how many experiments were performed and the number of mice per group per experiment:

“From these studies, we found that DO-KO mice had an accelerated onset of disease compared to DO-WT mice (Fig 7A). Disease symptoms (Score 1) appeared around Day 8–10 and quickly progressed to advanced disease (Score 3–4) by Day 14–16 in DO-KO. In contrast, DO-WT mice started showing symptoms around Day 12 and progressed to advanced disease scores by Day 20. Total cell infiltration into the CNS tissue was slightly higher in DO-KO mice, but no change in total brain weight was observed (S5 Fig). To further correlate the state of disease with CD4 infiltration, we performed in vivo NIRF whole-body imaging on diseased DO-WT and DO-KO mice using an antibody (Ab) probe specific to myelin basic protein (MBP). The Ab reacts with MBP only when the myelinated glia cells are damaged during disease development [56]. Thus, by detecting demyelination, whole-body imaging allowed us to fully visualize the co-localization of CD4 T cells at the sites of demyelination occurring in diseased mice. Interestingly, when mice of various disease scores were imaged, we found increased co-localization of infiltrating CD4 T cells with anti-MBP staining in DO-KO mice, but not in DO-WT mice (Fig 7B). These data not only confirmed the flow cytometric findings that diseased DO-KO mice have a greater influx of lymphocytes into their CNS tissue (S5 Fig), it also verified the massive demyelination that occurs during the disease”

And again in the Legend to Figure 7;

“Representative curves showing the time course of disease development in DO-KO (red) and DO-WT mice (white). N = 5 mice per group, representative of >15 repeat experiments. Score system: 0 = no symptoms, 1 = limp tail, 2 = limp tail + partial hind limb paralysis, 3 = limp tail + total hind limb paralysis, 4 = limp tail + total hind limb paralysis + partial forelimb paralysis. Data represented as mean ± SEM.”

Despite clarity of the description of our experiments, Lee et al have publicly slandered us and grossly misrepresented our work by stating the following:

“A recent study (11-Welsh et al) found that B6.Oa−/− mice were more susceptible to EAE than control B6J animals. However, that conclusion was based on a single experiment, in which control B6J mice developed very mild EAE disease with an average score of 1, which is far lower than the disease scores published by other groups (30–32) and also observed in our study. Thus, in this inducible model of autoimmunity, H2-O deficiency does not contribute to either disease development or severity.”

-Another important variable between our studies and Lee et al (Lee et al 2021) was the use of a commercially available disease induction kit versus our immunization solutions that followed the established protocols by Nancy Ruddle et al (J Exp Med. 1997 Oct 20; 186(8): 1233–1240. doi: 10.1084/jem.186.8.1233). Notoriously, EAE disease development could vary widely based upon the quantities and purity of, a) MOG peptide, b) amount of tuberculosis antigen in the CFA, c) quantity of pertussis toxin and injection strategies, as well as many other uncontrollable factors. While a comparison these two results are irrelevant to our current study, we will be more than happy to compare our results from the previously published work with Lee et al. in the discussion.

-We want to emphasize that we did follow Hogquists et al’s gating strategy for detecting auditing vs deleted thymocytes by subdividing total thymocytes into “Non-signaled” (TCR-β-, CD5-/inter) and “Signaled” (TCR-β+ CD5+/hi) populations before further gating on only medulla localized CD4 T cells. The “CCR7+ CD4+” label in Figure 1 was meant to orient the reader without overwhelming the figure with numerous flow plots. To address this concern, we will be including (1) updated Supplemental figures showing the complete gating strategy, (2) updated figure legends and text to emphasize the fact that auditing/deletion gating came from CD4 T cells which passed positive selection (i.e. TCR-β+ CD5+/hi), and (3) including representative flow plots for all Figure 1 panels to the revise manuscript.

-Also, regarding “discrepancies between our data and Liljedahl et al 1998”;

H2-O KO mice used by Liljedahl et al were on a 129/Ola genomic background. The H2-O KO mice used for both of our papers have been completely backcrossed to C57BL/6J. Clearly, non-MHC genes contribute to the impacts of MHC proteins, yet how the 129/Ola genomic background could affect the H2-O genes remains to be discovered. And (B), no data was shown supporting their published statement below:

“The proportions of B cells as well as of CD4+ and CD8+ T cells in the lymph node, spleen, and thymus were similar in H2-Oa–deficient and wild-type mice (data not shown)”. (Liljedahl et al 1998).

Reviewer 2:

scRNA-Seq analysis was performed by the Computational Biology Computing Core at Johns Hopkins School of Medicine. We missed including this acknowledgement as our core facility does not request authorship or acknowledgements. The sentence has been edited for the correct terminology.

-About truncated bar graph, in the entire paper we have only two bar graphs, neither of which is truncated. So, we are puzzled by the reviewer’s comment as to what figure he/she is referring to. -We would like to remind the Reviewer 2 that since DO works together with DM and functions differently on peptide of different sequences, the reported data on cumulative effects of DO in vivo have notoriously been rather minor. Especially, since our current study focuses on the naïve mice, major changes were not expected.

-Regarding leaving out gating strategies, we missed out on providing the gating strategies for all the figure in the original version. However, full FACS gating strategies have now been provided in the new supplemental figures and representative FACS plots have been added to ALL main figures.

  1. Howard Hughes Medical Institute
  2. Wellcome Trust
  3. Max-Planck-Gesellschaft
  4. Knut and Alice Wallenberg Foundation