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  1. Author Response

    Reviewer #2 (Public Review):

    In this study, Radtke et al. use a model of helminth infection in IL-4-IRES-eGFP (4get) mice, in which transcription at the Il4 locus is reported by eGFP, in order to define the transcriptional signatures and clonal relatedness between Il4-licensed, CD4+ T cells in the mesenteric lymph nodes (mLN) and lungs. By infecting 4get mice with the hookworm Nippostrongylus brasiliensis, which is well described to induce a robust type 2 immune response, the authors isolated and sorted eGFP+CD4+ T cells from the mLN and lungs at 10day post infection and performed single cell RNA-seq analysis using the 10X Chromium platform. Transcriptional profiling of activated CD4+ T cells with scRNA-seq has been performed in a murine model of allergic asthma, including the lung and lung-draining lymph nodes, but this study involved unbiased capture of all activated CD4+ T cells (Tibbitt et al., Immunity, 2019). Radtke et al. have used a distinct model with Nippostrongylus brasiliensis and have focused on sorting Il4-licensed, CD4+ T cells, allowing for a greater number of captured CD4+ T cells with a "type 2" lymphocyte program for single cell analysis. Furthermore, this study sought to identify distinct and overlapping transcriptional signatures and clonal relatedness between Il4-licensed, CD4+ T cells in two "distant" tissues. In support of such an approach, there is growing evidence for tissue-specific and model-specific features of CD4+ T cell differentiation (Poholek, Immunohorizons, 2021; Hiltensperger et al., Nature Immunol, 2021; Kiner et al., Nature Immunol, 2021).

    Upon dimension reduction, the authors found mLN- and lung-specific clusters, including two juxtaposed clusters that form a "bridge" between the mLN and lung compartments, suggesting immigrating and/or emigrating cells. Consistent with previous studies, the dominant lung cluster (L2) exhibited unique expression of Il5 and Il13, enhanced IL-33 and IL-2 signaling, and exhibited an effector/resident memory profile. The authors did find a small cluster in the mLN (ML4) with an effector/resident memory signature that also expressed CCR9, suggesting the potential for homing to the gut mucosa. Whether this population is specific to the mLN or would also be found in the lung-draining lymph nodes remains unclear. In the mLN, the authors also describe an iNKT cell cluster with CCR9 expression and a CD4+ T cell cluster with a myeloid gene signature, but the significance of these populations remains unclear.

    The authors then use RNA velocity analysis to infer the developmental trajectory of Il4licensed, CD4+ T cells from the two tissue sites. Consistent with previous studies, the authors found that T cell proliferation was associated with fate decisions. Furthermore, among the two lung CD4+ T cell clusters, L1 represents highly differentiated, effector Th2 cells while L2, which is juxtaposed to the mLN clusters, represents a population likely entering the lung with the potential to differentiate into L1 cells.

    Next, the authors perform TCR repertoire analysis. The authors identified a broad TCR repertoire with the majority of distinct TCRs being found in only one cell. Among the TCRs found in more than one cell, a substantial number of clones can be found in both tissue sites, which is consistent with the findings that individual CD4+ T cells clones can produce different types of effector cells (Tubo et al., Cell, 2013). The authors find significant overlap of clones between the mLN and lung. In addition, they also identify clones enriched in a particular site and suggest that this represents local expansion. However, an alternative possibility is that certain CD4+ T cell clones are expanded at a particular site because the specific TCR preferentially instructs a particular cell fate. For example, fate-mapping of individual naïve CD8+ T cells suggests that certain T cell clones exhibit a greatly heightened capacity to form tissue-resident memory T cells over other cell fates (Kok et al., J Exp Med, 2020). Lastly, the authors analyze CDR3 sequences, finding the most abundant CDR3 motif belonging to the invariant TCRa chain of iNKTs. Among conventional CD4+ T cells, the abundant CDR3 motifs were not restricted to an exact TCRa/TCRb combination beyond a slight preferential usage of the Trbv1 gene. While TCR repertoire analysis allows for defining clonal relatedness among Il4-licensed, CD4+ T cells, the importance and relevance of the above findings to the in vivo type 2 immune response remain unclear.

    There are several limitations of the study:

    (1) The authors use the term "Th2 cells" to describe all Il4-licensed, CD4+ T cells. While CD4+ T helper cell nomenclature has evolved, Th2 cells and Tfh2 cells are generally used to describe distinct subsets driven by unique transcriptional programs (Ruterbusch et al., Annu Rev Immunol, 2020). While previous data suggested that Tfh2 cells are precursors to effector Th2 cells, subsequent studies support a model in which Tfh2 and Th2 cells represent distinct developmental pathways and should be designated as distinct subsets (Ballesteros-Tato et al., Immunity, 2016; Tibbitt et al., Immunity, 2019). Consequently, the authors' broad use of "Th2 cells" and a description of "Th2 cell heterogeneity" includes CD4+ T cell subsets with distinct developmental pathways that includes canonical Th2 cells as well as Tfh2 and iNKT cells. The clarity of the manuscript would be improved by describing eGFP+CD4+ cells as Il4licensed, CD4+ T cells rather than Th2 cells.

    We thank the reviewer for the helpful comment and state now that our IL-4 reporter positive population also includes cells that don’t meet the Th2 criteria in the introduction (lines 76-78).

    (2) The authors used perfused lungs to isolate Il4-licensed, CD4+ T cells for scRNA-seq of "Th2 cells" in the lung tissue. However, previous studies indicate that leukocytes, including CD4+ T cells, in lung vasculature are not completely removed by perfusion, which confounds the interpretation of a tissue cell profile due to contaminating circulating cells (Galkina, E et al., J Clin Invest, 2005; Anderson, KG et al., Nat Protoc, 2014). This is particularly true in the lung and relevant as the authors found a lung cluster (L2) with a circulating signature and suggested that L2 may represent a recent immigrant "Th2 cells". Thus, it is unclear whether L2 cluster identifies immigrant Th2 cells or simply reflect the circulating Th2 cells trapped in the lung vasculature. The study would benefit of using the intravascular staining to discriminate cells within the lungs from those in the circulation (Anderson, KG et al., Nat Protoc, 2014) for the proper isolation of Il4-licensed lung CD4+ T cells to truly define immigrant "Th2 cells" within the lung parenchyma.

    According to the reviewers suggestion we performed an intravascular staining to discriminate cells within the lungs from those in the circulation (new Figure 2—figure supplement 1). According to the vascularity staining method (with slightly increased time between i.v. and sacrifice compared to Anderson, KG et al., Nat Protoc, 2014 for higher probability of successful staining) the L2 lung cluster is a mixture of circulating cells and immigrating cells which we describe in the text (lines 210-213). The finding that the cells from the vasculature and the cells we classified as “migrating” seem to cluster together based on the similarity of their expression profiles on our UMAP further supports the classification of the L2 tissue fraction as “recent immigrants”. We thank the reviewer for this helpful comment which improved the quality of the manuscript.

    (3) The authors describe T cell exchange/trafficking across organs. However, in general, interorgan trafficking refers to lymphocyte trafficking between distinct non-lymphoid tissues, rather than trafficking between lymph nodes and peripheral tissues (Huang et al., Science, 2018). Rather than inter-organ trafficking, the authors have described shared and distinct features of Il4-licensed, CD4+ T cells from a draining lymph node of one organ (gut) and a distant non-lymphoid organ (lung). The experimental approach used makes interpretation of some of the findings challenging. Specifically, canonical effector Th2 cell differentiation is well described to occur via two checkpoints, including the draining lymph node and the peripheral (non-lymphoid) tissue (Liang et al., Nature Immunol, 2011; Van Dyken et al., Nature Immunol, 2016; Tibbitt et al., Immunity, 2019). In the draining lymph node, Th2 cells acquire the capacity to express IL-4 alone, but do not complete effector Th2 cell differentiation until trafficking to the inflamed peripheral tissues and receiving additional inflammatory signals. Consequently, it is unclear whether the differences identified in the mesenteric lymph node and lungs simply reflect well-described differences between the two Th2 cell checkpoints or organ-specific differences (gut vs lung). Il4-licensed, CD4+ T cells from the intestinal mucosa and lung-draining lymph node would also be needed to truly define organ-specific differences during helminth infection.

    According to the reviewers suggestion, we avoid the term “inter-organ trafficking” and replaced it by “at distant sites” in the title. As the reviewer points out we chose the setup of comparing a lymphoid and a non-lymphoid organ to acquire a broad picture of Th2 developmental stages in Nb infection. The limited overlap in clusters on the UMAP shows that expression profiles between MLN and lung strongly differ. However, this notion is not in conflict with cells of both organs being in a different developmental stage. We added information to highlight it in the manuscript (lines 99-101). Lung and MLN (rather than medLN and MLN) were selected to enable clonal relatedness/distribution analysis of T cells at distant sites. As part of the revision we additionally provide newly generated single cell sequencing data that compares medLN and MLN cells at day 10 after Nb infection and find that UMAP clusters are largely overlapping between medLN and MLN (new Figure 1—figure supplement 3). This suggests that there is no broad medLN/MLN site specific signature present that would force the medLN and MLN cells to cluster apart. Addition of the newly generated medLN/MLN data on the lung/MLN UMAP based on shared anchors (Stuart et al. Cell. 2019) also leads to a clear separation between all LN and lung cells supporting that cells don’t cluster due to a site-specific respiratory tract vs intestinal tract signature but likely based on developmental stages (new Fig. 1C,D). An exception are defined effector clusters that show signs of a site-specific signature (L1 expresses Ccr8, MLN4 and MLN6 express Ccr9, differences are also suggested by clustering described in lines 247-252). A similar phenotype to the one observed on the transcriptional level is observed when we cluster medLN/MLN and lung cells based on scRNAseq suggested surface marker expression after flow cytometric analysis, extending analysis to medLN on protein level (new Fig. 3). It would have also been interesting to include lamina propria T cells as the reviewer suggested but we were not able to extract high quality cells at day 10 after Nb infection which is a common limitation in the Nb model.

    (4) The study includes a single time point (day 10) whereas Tibbitt et al. performed scRNAseq in the lung and lung-draining lymph node at multiple time points during type 2 immunity (Tibbitt et al., Immunity, 2019). As a result, it remains unclear how similarities or differences between the mesenteric lymph node and lung response would change over the duration of helminth infection, especially given the helminth life cycle involves multiple infection stages.

    As part of the revision we screened for surface marker expression in the single cell sequencing dataset on transcript level and stained these on protein level (new Fig. 3 and Figure 3—figure supplement 1). This allows to follow the populations defined by scRNAseq longitudinally (d0, d6, d8, d10) by flow cytometry during Nb infection. We compared medLN, MLN and lung. The dynamic of the response in the medLN and the MLN seems similar with a small delay in the MLN compared to medLN.

    Nb with its relatively well defined migratory path through the body provides a relevant complex model antigen naturally present in the respiratory tract and the intestine during infection. However, analysis of complexity and relevance does often invoke limitations. While stage 4 larvae are found in lung and gut and certainly provide a shared antigen basis between both sites (migration stage from lung to intestine; Camberis et al. Curr Protoc Immunol. 2003), we also think that there is a reasonable number of antigens shared between different larval stages and antigen (either actively secreted or from dying larvae) that are systemically distributed. However, there are probably immunogenic differences between larval stages but to analyze these is beyond the scope of the manuscript.

    While i.e. Tibbitt et al. nicely define cell clusters with a limited number of cells they don’t include any TCR analysis and clonal information. Not much was known about the expansion of T cells in the different clusters in one organ and between organs and we provide relevant data in this regard. Furthermore, HDM as an allergy model might invoke different Th2 differentiation pathways as. i.e. Tfh13 cells are found in allergic settings but not in worm models (Gowthaman U, Science. 2019). With our approach on single cell level we were able to show effective distribution of a number of T cell clones in a highly heterogeneous immune response and describe and functionally validate successfully expanded clones / expanded TCR chains later on (i.e. new Fig. 6). This kind of analysis has not been performed for a worm model before.

    (5) The study analyzed one scRNA-seq experiment that included two mice without validation via flow cytometry or other method to infer a role of a particular finding to the type 2 immune response in vivo.

    As noted above, we screened for surface marker expression in the single cell sequencing dataset on transcript level and measured these on protein level by flow cytometry as the reviewer suggested. This allows to follow the populations defined by scRNAseq longitudinally (d0, d6, d8, d10) during Nb infection (new Fig. 3). Furthermore, we added a newly generated set of scRNAseq data which confirms and extends findings made in the initial sequencing experiment (Fig. 1C,D and Figure 1—figure supplement 3). We also included validation experiments based on the performed TCR analysis and retrovirally expressed three TCRs from our study and confirm Nb specific expansion for one of them in vivo (new Fig. 6 and Figure 6—figure supplement 1).

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  2. Evaluation Summary:

    A well written and informative study that uses scRNA-seq to examine Th2 biology in worm infections. It offers a unique angle for better defining Th2 heterogeneity and differentiation in vivo.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #3 agreed to share their name with the authors.)

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  3. Reviewer #1 (Public Review):

    Radke et al. used scRNA-seq to characterize Th2 cells responding to infection with Nippostrongylus bradiliensis. By comparing IL-4+ T cells from lung and mesenteric lymph they describe tissue specific signatures as well subsets of cells that share migration and other transcriptional features, suggesting a continuum of differentiation between the two organs. Further analysis of the TCR repertoire highlights significant overlap between lung and distal lymphoid T cells, although highly expanded clones tend to be more abundant in one organ. The manuscript is well written and informative with a circumspect interpretation of the results and their relationship to the current literature. The dataset in the manuscript will be particularly useful for other groups investigating Th2 responses across a variety of infection and disease models.

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  4. Reviewer #2 (Public Review):

    In this study, Radtke et al. use a model of helminth infection in IL-4-IRES-eGFP (4get) mice, in which transcription at the Il4 locus is reported by eGFP, in order to define the transcriptional signatures and clonal relatedness between Il4-licensed, CD4+ T cells in the mesenteric lymph nodes (mLN) and lungs. By infecting 4get mice with the hookworm Nippostrongylus brasiliensis, which is well described to induce a robust type 2 immune response, the authors isolated and sorted eGFP+CD4+ T cells from the mLN and lungs at 10-day post infection and performed single cell RNA-seq analysis using the 10X Chromium platform. Transcriptional profiling of activated CD4+ T cells with scRNA-seq has been performed in a murine model of allergic asthma, including the lung and lung-draining lymph nodes, but this study involved unbiased capture of all activated CD4+ T cells (Tibbitt et al., Immunity, 2019). Radtke et al. have used a distinct model with Nippostrongylus brasiliensis and have focused on sorting Il4-licensed, CD4+ T cells, allowing for a greater number of captured CD4+ T cells with a "type 2" lymphocyte program for single cell analysis. Furthermore, this study sought to identify distinct and overlapping transcriptional signatures and clonal relatedness between Il4-licensed, CD4+ T cells in two "distant" tissues. In support of such an approach, there is growing evidence for tissue-specific and model-specific features of CD4+ T cell differentiation (Poholek, Immunohorizons, 2021; Hiltensperger et al., Nature Immunol, 2021; Kiner et al., Nature Immunol, 2021).

    Upon dimension reduction, the authors found mLN- and lung-specific clusters, including two juxtaposed clusters that form a "bridge" between the mLN and lung compartments, suggesting immigrating and/or emigrating cells. Consistent with previous studies, the dominant lung cluster (L2) exhibited unique expression of Il5 and Il13, enhanced IL-33 and IL-2 signaling, and exhibited an effector/resident memory profile. The authors did find a small cluster in the mLN (ML4) with an effector/resident memory signature that also expressed CCR9, suggesting the potential for homing to the gut mucosa. Whether this population is specific to the mLN or would also be found in the lung-draining lymph nodes remains unclear. In the mLN, the authors also describe an iNKT cell cluster with CCR9 expression and a CD4+ T cell cluster with a myeloid gene signature, but the significance of these populations remains unclear.

    The authors then use RNA velocity analysis to infer the developmental trajectory of Il4-licensed, CD4+ T cells from the two tissue sites. Consistent with previous studies, the authors found that T cell proliferation was associated with fate decisions. Furthermore, among the two lung CD4+ T cell clusters, L1 represents highly differentiated, effector Th2 cells while L2, which is juxtaposed to the mLN clusters, represents a population likely entering the lung with the potential to differentiate into L1 cells.

    Next, the authors perform TCR repertoire analysis. The authors identified a broad TCR repertoire with the majority of distinct TCRs being found in only one cell. Among the TCRs found in more than one cell, a substantial number of clones can be found in both tissue sites, which is consistent with the findings that individual CD4+ T cells clones can produce different types of effector cells (Tubo et al., Cell, 2013). The authors find significant overlap of clones between the mLN and lung. In addition, they also identify clones enriched in a particular site and suggest that this represents local expansion. However, an alternative possibility is that certain CD4+ T cell clones are expanded at a particular site because the specific TCR preferentially instructs a particular cell fate. For example, fate-mapping of individual naïve CD8+ T cells suggests that certain T cell clones exhibit a greatly heightened capacity to form tissue-resident memory T cells over other cell fates (Kok et al., J Exp Med, 2020). Lastly, the authors analyze CDR3 sequences, finding the most abundant CDR3 motif belonging to the invariant TCRa chain of iNKTs. Among conventional CD4+ T cells, the abundant CDR3 motifs were not restricted to an exact TCRa/TCRb combination beyond a slight preferential usage of the Trbv1 gene. While TCR repertoire analysis allows for defining clonal relatedness among Il4-licensed, CD4+ T cells, the importance and relevance of the above findings to the in vivo type 2 immune response remain unclear.

    There are several limitations of the study:
    (1) The authors use the term "Th2 cells" to describe all Il4-licensed, CD4+ T cells. While CD4+ T helper cell nomenclature has evolved, Th2 cells and Tfh2 cells are generally used to describe distinct subsets driven by unique transcriptional programs (Ruterbusch et al., Annu Rev Immunol, 2020). While previous data suggested that Tfh2 cells are precursors to effector Th2 cells, subsequent studies support a model in which Tfh2 and Th2 cells represent distinct developmental pathways and should be designated as distinct subsets (Ballesteros-Tato et al., Immunity, 2016; Tibbitt et al., Immunity, 2019). Consequently, the authors' broad use of "Th2 cells" and a description of "Th2 cell heterogeneity" includes CD4+ T cell subsets with distinct developmental pathways that includes canonical Th2 cells as well as Tfh2 and iNKT cells. The clarity of the manuscript would be improved by describing eGFP+CD4+ cells as Il4-licensed, CD4+ T cells rather than Th2 cells.

    (2) The authors used perfused lungs to isolate Il4-licensed, CD4+ T cells for scRNA-seq of "Th2 cells" in the lung tissue. However, previous studies indicate that leukocytes, including CD4+ T cells, in lung vasculature are not completely removed by perfusion, which confounds the interpretation of a tissue cell profile due to contaminating circulating cells (Galkina, E et al., J Clin Invest, 2005; Anderson, KG et al., Nat Protoc, 2014). This is particularly true in the lung and relevant as the authors found a lung cluster (L2) with a circulating signature and suggested that L2 may represent a recent immigrant "Th2 cells". Thus, it is unclear whether L2 cluster identifies immigrant Th2 cells or simply reflect the circulating Th2 cells trapped in the lung vasculature. The study would benefit of using the intravascular staining to discriminate cells within the lungs from those in the circulation (Anderson, KG et al., Nat Protoc, 2014) for the proper isolation of Il4-licensed lung CD4+ T cells to truly define immigrant "Th2 cells" within the lung parenchyma.

    (3) The authors describe T cell exchange/trafficking across organs. However, in general, inter-organ trafficking refers to lymphocyte trafficking between distinct non-lymphoid tissues, rather than trafficking between lymph nodes and peripheral tissues (Huang et al., Science, 2018). Rather than inter-organ trafficking, the authors have described shared and distinct features of Il4-licensed, CD4+ T cells from a draining lymph node of one organ (gut) and a distant non-lymphoid organ (lung). The experimental approach used makes interpretation of some of the findings challenging. Specifically, canonical effector Th2 cell differentiation is well described to occur via two checkpoints, including the draining lymph node and the peripheral (non-lymphoid) tissue (Liang et al., Nature Immunol, 2011; Van Dyken et al., Nature Immunol, 2016; Tibbitt et al., Immunity, 2019). In the draining lymph node, Th2 cells acquire the capacity to express IL-4 alone, but do not complete effector Th2 cell differentiation until trafficking to the inflamed peripheral tissues and receiving additional inflammatory signals. Consequently, it is unclear whether the differences identified in the mesenteric lymph node and lungs simply reflect well-described differences between the two Th2 cell checkpoints or organ-specific differences (gut vs lung). Il4-licensed, CD4+ T cells from the intestinal mucosa and lung-draining lymph node would also be needed to truly define organ-specific differences during helminth infection.

    (4) The study includes a single time point (day 10) whereas Tibbitt et al. performed scRNA-seq in the lung and lung-draining lymph node at multiple time points during type 2 immunity (Tibbitt et al., Immunity, 2019). As a result, it remains unclear how similarities or differences between the mesenteric lymph node and lung response would change over the duration of helminth infection, especially given the helminth life cycle involves multiple infection stages.

    (5) The study analyzed one scRNA-seq experiment that included two mice without validation via flow cytometry or other method to infer a role of a particular finding to the type 2 immune response in vivo.

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  5. Reviewer #3 (Public Review):

    The authors aimed to study in detail the process of Th2 differentiation during helminth infection, using droplet-based, single-cell RNA-seq and TCR sequencing combined with an established IL-4-reporter mouse.

    A strength of this study is its focus on helminth infection. High-dimensional studies of Th2 cells have been published previously, but these have mostly examined allergic disease: https://www.jci.org/articles/view/125917 https://pubmed.ncbi.nlm.nih.gov/31231035/ https://pubmed.ncbi.nlm.nih.gov/31745340/. There are no such helminth papers or pre-prints that I am aware of; hence scRNA-seq examination of Th2 biology in worm infections offers a unique angle for better defining Th2 heterogeneity and differentiation in vivo.

    The authors use IL-4-eGFP reporter mouse to study Th2 responses. This is a certainly an established, conventional approach, carrying with it the assumption that IL-4 mRNA expression defines Th2-like cells. However, this approach also restricts the study, reducing the chances of detecting Th2 cells that perhaps don't strictly adhere to this definition.

    The authors examine mesenteric lymph nodes (MLN) and lung tissue, which given that the helminth infection proceeds via the GI tract and lung is appropriate. However, direct comparison between a secondary lymphoid organ (SLO) and non-lymphoid tissue is difficult and may be confounded by the different cell isolation methods needed. It was notable that assessment of lung draining lymph nodes or the gut epithelium/lamina propria was not included.

    One weakness of this study was its apparent reliance on data from only two mice, and the lack of biological "validation" studies using, for example, flow cytometric detection of novel proteins or cellular states, or examination of Th2 biology in gene knockout mice.

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