(C) PLOS One
This story was originally published by PLOS One and is unaltered.
. . . . . . . . . .



Exposure to Mycobacterium remodels alveolar macrophages and the early innate response to Mycobacterium tuberculosis infection [1]

['Dat Mai', 'Center For Global Infectious Disease Research', 'Seattle Children S Research Institute', 'Seattle', 'Washington', 'United States Of America', 'Ana Jahn', 'Tara Murray', 'Michael Morikubo', 'Pamelia N. Lim']

Date: 2024-02

Alveolar macrophages (AMs) play a critical role during Mycobacterium tuberculosis (Mtb) infection as the first cells in the lung to encounter bacteria. We previously showed that AMs initially respond to Mtb in vivo by mounting a cell-protective, rather than pro-inflammatory response. However, the plasticity of the initial AM response was unknown. Here, we characterize how previous exposure to Mycobacterium, either through subcutaneous vaccination with Mycobacterium bovis (scBCG) or through a contained Mtb infection (coMtb) that mimics aspects of concomitant immunity, impacts the initial response by AMs. We find that both scBCG and coMtb accelerate early innate cell activation and recruitment and generate a stronger pro-inflammatory response to Mtb in vivo by AMs. Within the lung environment, AMs from scBCG vaccinated mice mount a robust interferon-associated response, while AMs from coMtb mice produce a broader inflammatory response that is not dominated by Interferon Stimulated Genes. Using scRNAseq, we identify changes to the frequency and phenotype of airway-resident macrophages following Mycobacterium exposure, with enrichment for both interferon-associated and pro-inflammatory populations of AMs. In contrast, minimal changes were found for airway-resident T cells and dendritic cells after exposures. Ex vivo stimulation of AMs with Pam3Cys, LPS and Mtb reveal that scBCG and coMtb exposures generate stronger interferon-associated responses to LPS and Mtb that are cell-intrinsic changes. However, AM profiles that were unique to each exposure modality following Mtb infection in vivo are dependent on the lung environment and do not emerge following ex vivo stimulation. Overall, our studies reveal significant and durable remodeling of AMs following exposure to Mycobacterium, with evidence for both AM-intrinsic changes and contributions from the altered lung microenvironments. Comparisons between the scBCG and coMtb models highlight the plasticity of AMs in the airway and opportunities to target their function through vaccination or host-directed therapies.

Tuberculosis, a disease caused by the bacteria Mycobacterium tuberculosis (Mtb), claims around 1.6 million lives each year, making it one of the leading causes of death worldwide by an infectious agent. Based on principles of conventional immunological memory, prior exposure to either Mtb or M. bovis BCG leads to antigen-specific long-lasting changes to the adaptive immune response that can be effective at protecting against subsequent challenge. However, how these exposures may also impact the innate immune response is less understood. Alveolar macrophages are tissue-resident myeloid cells that play an important role during Mtb infection as innate immune sentinels in the lung and the first host cells to respond to infection. Here, we examined how prior Mycobacterium exposure, either through BCG vaccination or a model of contained Mtb infection, impacts the early innate response by alveolar macrophages. We find that prior exposure remodels the alveolar macrophage response to Mtb through both cell-intrinsic changes and signals that depend on the altered lung environment. These findings suggest that the early innate immune response could be targeted through vaccination or host-directed therapy and could complement existing strategies to enhance the host response to Mtb.

Funding: This work was supported by National Institute of Allergy and Infectious Disease of the National Institute of Health under Awards U19AI135976 (A.A.), R01AI032972 (A.A.), 75N93019C00070 (K.U., A.C.R., A.A.), and R21AI163809 (A.C.R.). J.N. was supported by the Swiss National Foundation under grant 310030_200407. P.L. was supported by National Research Service Award T32 GM135096 from the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Here, we show that while both coMtb and scBCG protect against low dose Mtb aerosol challenge, they remodel the in vivo innate response in different ways. In AMs, scBCG elicits a very strong interferon response in AMs, while coMtb promotes a broader pro-inflammatory response that is less dominated by Interferon Stimulated Genes. Prior exposure to Mycobacterium also remodels the frequency and phenotype of AM subsets in the lung prior to aerosol challenge and leads to significant changes in the early dynamics of the overall innate response. While changes in the AM responses that are unique to each exposure (scBCG, coMtb) depend on the lung environment, stronger interferon-associated responses following both LPS and Mtb stimulation ex vivo reveal cell-intrinsic changes.

The coMtb model is generated by intradermal inoculation with virulent Mtb into the ears of mice and leads to a contained but persistent lymph node Mtb infection [ 24 , 25 ]. The model replicates observations in both humans and non-human primates (NHPs) that prior exposure to Mtb infection provides protection against subsequent exposure, through a form of concomitant immunity [ 26 , 27 ]. In a previous study, we found that coMtb leads to protection against challenge with aerosol Mtb infection and protects mice against heterologous challenges, including infection with Listeria monocytogenes and expansion of B16 melanoma cells, results which suggest there is substantial remodeling of innate immune responses [ 25 ]. We found that AMs from coMtb mice mount a more inflammatory response to Mtb infection compared to AMs from control mice, and the enhancement in AM activation after infection, as measured by MHC II expression, was dependent on IFNγR signaling [ 25 ].

Lung resident alveolar macrophages (AMs) are the first cells to become infected with inhaled Mtb and engage a cell-protective response, mediated by the transcription factor Nrf2, that impedes their ability to effectively control bacterial growth [ 10 , 11 ]. In this study, we examined how prior mycobacterial exposure reprograms AMs and alters the overall innate response in the lung to aerosol challenge with Mtb. To evaluate the range of AM plasticity, we chose to compare the effects of subcutaneous BCG vaccination (scBCG) with those arising from a contained Mtb-infection (coMtb) model. BCG, a live-attenuated TB vaccine derived from M. bovis and typically given during infancy, provides protection against disseminated pediatric disease but has lower efficiency against adult pulmonary disease [ 12 – 14 ]. In addition to enhancement of Mtb-specific adaptive responses, based on shared antigens, BCG vaccination also leads to changes in hematopoiesis and epigenetic reprogramming of myeloid cells in the bone marrow [ 15 ], early monocyte recruitment and Mtb dissemination [ 16 ], and innate activation of dendritic cells critical for T cell priming [ 17 ]. Intranasal BCG vaccination protects against Streptococcus pneumoniae and induces long term activation of AMs [ 18 ]. A recent study has shown that one mechanism by which BCG vaccination can elicit innate training effects on AMs, separate from alterations to the monocyte population, is through changes to the gut microbiome and microbial metabolites [ 19 ]. BCG vaccination is also associated with trained immunity effects in humans [ 20 – 22 ], including well-described reductions in all-cause neonatal mortality and protection against bladder cancer [ 3 , 23 ].

Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis (TB), claimed more than 1.6 million lives in 2021. For the first time since 2005, the number of TB deaths worldwide is increasing [ 1 , 2 ]. These trends highlight the urgent need for new vaccine and therapeutic strategies. Traditionally, vaccine design has focused on generating a rapid, robust, and effective adaptive immune response. However, recent studies suggest that the innate immune system can undergo long-term changes in the form of trained immunity [ 3 ], which affect the outcome of infection and could function as important components of an effective TB vaccine [ 4 , 5 ]. Initial trained immunity studies focused on central trained immunity, long-term changes to hematopoietic stem cells that lead to functional changes in short-lived innate cell compartments (i.e., monocytes, NK cells, dendritic cells) [ 3 ]. More recent studies have examined innate training in tissue-resident macrophages and demonstrated that these cells are also affected by prior exposures. Tissue-resident macrophages can respond to remote injury and inflammation [ 6 ], undergo long-term changes [ 3 ], and display altered responses to bacteria after pulmonary viral infection [ 7 – 9 ].

These results demonstrate that prior Mycobacterium exposure leads to cell-intrinsic changes in AMs that license an enhancement of IFN-dependent responses to Mtb that are retained in vitro, while qualitative differences in the response between scBCG and coMtb in vivo are dependent on signals from the lung environment.

Gene expression changes measured by bulk RNA-seq for Mtb-infected AMs compared to respective unstimulated AMs (i.e., Mtb-inf control AM vs unstim control AM; Mtb-inf scBCG AM vs unstim scBCG AM; Mtb-inf coMtb AM vs unstim coMtb AM). A) Gene expression for control, scBCG, and coMtb AMs, 6 hour H37Rv infection ex vivo, log 2 fold change (Mtb-infected/uninfected). IFN-dependent genes (339 total) and IFN-independent genes (352 total) based on WT vs IFNAR -/- BMDM bulk RNA-seq dataset (Olson et al, 2021) (see Methods section). B) Gene expression for control, scBCG, and coMtb AMs, 24 hour in vivo H37Rv infection, Mtb-infected sorted, log 2 fold change (Mtb-infected/uninfected) for the same IFN-dependent and IFN-independent gene sets in (A). Grey bars indicate N.D. Normalized Enrichment Score (NES) calculated by GSEA for two data sets alongside Hallmark Pathways. +FDR< 0.05, ++FDR< 0.01, +++FDR< 0.001.

Because the “Interferon Alpha Response” and “Interferon Gamma Response” pathways were most highly enriched for the H37Rv stimulation following Mycobacterium exposure, we decided to further investigate the Interferon-associated response [ 30 ]. We specifically sought out a dataset that would identify ISGs specific to Mtb-infected macrophages. To generate an IFNγ-derived signature, we would need a macrophage-T cell co-culture system and to sort out the Mtb-infected macrophages, because murine macrophages do not produce IFNγ during Mtb infection in vitro. Therefore, we decided to examine an IFNα/β-derived signature from a data set of Mtb-infected IFNAR -/- bone marrow derived macrophages (BMDMs). We categorized the macrophage response to H37Rv stimulation as “IFN-dependent” or “IFN-independent” based on gene expression of WT versus IFNAR -/- BMDMs following H37Rv infection (see methods section) ( S4 Table ) [ 38 ]. Expression of IFN-dependent genes was minimally induced in control AMs but strongly up-regulated in AMs from Mycobacterium exposed mice, as measured by the GSEA normalized enrichment score (NES) ( Fig 6A , left ). In contrast, expression of IFN-independent genes was modestly upregulated in control AMs and only slightly altered by Mycobacterium exposure ( Fig 6A , right ). When we applied these two gene sets to the in vivo response profiles described in Fig 2 generated for Mtb-infected AMs following high dose infection with mEmerald-H37Rv, we observe that Mtb-infected AMs from scBCG mice up-regulate the IFN-dependent response in vivo, suggesting that the licensing of the IFN-dependent response plays a role in vivo following BCG vaccination ( Fig 6B ). The difference between the in vitro and in vivo response for AMs from coMtb mice points to an additional contribution of the lung environment.

A) AM isolation 8 weeks following scBCG or coMtb exposure. AMs were stimulated with Pam3Cys (10 ng/ml), LPS (10 ng/ml), and H37Rv (effective MOI ~2:1) for 6 hours (RNA-seq) or 20 hours (flow cytometry). B-D) Gene expression changes measured by bulk RNA-seq for stimulated AMs compared to respective unstimulated AMs (i.e., LPS-stim control AM vs unstim control AM; LPS-stim scBCG AM vs unstim scBCG AM; LPS-stim coMtb AM vs unstim coMtb AM). B) Scatterplots, log 2 fold change gene expression for stimulated to unstimulated AMs for each condition (control, scBCG, coMtb). Differentially expressed genes (DEG) are highlighted for one or both conditions (|Fold change| > 2, FDR< 0.05 for Pam3Cys and LPS; |Fold change| > 2, FDR< 0.2 for H37Rv). C) Scatterplots, log 2 fold change gene expression for H37Rv-stimulated to unstimulated scBCG versus coMtb AMs. Genes highlighted derived from gene sets in Fig 2E . Nrf2-associated genes (56 genes, purple), Interferon Alpha/ Gamma Response (61 genes, orange), and IL6 JAK STAT3 (23 genes, green). D) Gene Set Enrichment Analysis results for 50 HALLMARK pathways. Pathways shown have NES> 1.5 and FDR< 0.05 for at least one of the conditions. *FDR< 0.05, **FDR< 0.01, ***FDR< 0.001. E) Gating strategy and MHC II and TNF histograms for coMtb AMs, no stimulation versus LPS. F-G) MHC II and TNF MFI in control, scBCG, and coMtb AMs after 20 hours of LPS stimulation. *p< 0.05, **p< 0.01, ***p< 0.001, One-way ANOVA with Tukey post-test.

Analysis of the AM response to Mtb in vivo demonstrates that the very earliest immune response to Mtb is altered by previous Mycobacterium exposure. However, one limitation to this approach is the inability to discern whether changes to AMs are cell-intrinsic or dependent on the altered tissue environment, especially the presence of Mtb-specific T cells. Therefore, to determine whether Mycobacterium exposure induces cell-intrinsic changes to AMs, we isolated AMs from control, scBCG, and coMtb mice, stimulated them ex vivo with LPS, Pam3Cys, or H37Rv, and measured their transcriptional profiles 6 hours later ( Fig 5A ). First, PAMP-specific trends were notable. AMs from coMtb and scBCG mice showed distinct responses compared to AMs from control mice following LPS and H37Rv stimulation, but only minimal changes following Pam3Cys stimulation( Fig 5B and S3 Table ). No obvious changes in innate receptor or adaptor expression explain the PAMP-specific differences ( S11 Fig ). Second, as we have previously reported, Mtb-infected AMs did not strongly up-regulate Nrf2-associated genes ex vivo ( Fig 5C ). Third, when we examined the gene sets that distinguished the in vivo AM response between scBCG and coMtb mice, “Interferon Alpha/Gamma Response” and “IL6 JAK STAT3” ( Fig 2E ), we found that the differences between exposure modalities were diminished ex vivo, suggesting contribution of the lung environment to the quality of the response ( Fig 5C ). Using Gene Set Enrichment Analysis, we identified “Interferon Gamma Response”, “Interferon Alpha Response”, “TNFa signaling via NF-kB”, and”Inflammatory Response” pathways as the most strongly enriched for LPS and H37Rv responses from scBCG and coMtb AMs ( Fig 5D ) . To assess whether the cell-intrinsic changes observed were long-lasting, we compared the responses of AMs at 8 or 23 weeks following scBCG vaccination by RT-qPCR. Increases in gene expression were as robust or even enhanced 23 weeks following exposure compared to 8 weeks, suggesting that exposure-induced changes to AMs are relatively long-lived ( S12 Fig ). To validate whether changes in gene expression were reflected at the protein level, we sought to develop a flow cytometry-based assay to assess AM-specific responses. Primary AMs were stimulated with LPS for 20 hours and both MHC II and TNF expression were measured by flow cytometry ( Fig 5E ). We found that AM from coMtb mice had significantly higher MHC II expression than controls and a similar pattern was seen for scBCG AM in 1 of 2 experiments ( Fig 5F ). AMs from coMtb mice also showed a significant increase in TNF expression in 1 of 2 experiments ( Fig 5G ).

Re-clustering of DCs yielded 2 major clusters (Cluster 0, 1) and 1 minor cluster (Cluster 2), which had a mixed phenotype with expression of genes from both major clusters ( Fig 4G ). Cells in Cluster 0 had high expression of Clec9a, Itgae (CD103), and MHC II genes (H2-Ab1, H2-DMa) consistent with an expression profile of lung CD103 + cDCs [ 37 ] ( Fig 4I ), while cells in Cluster 1 had higher expression of Batf3, Ccr7, and Fscn1. All three of the clusters had high Irf8 expression and lower expression of Xcr1, Irf4, and Itgam (CD11b) ( Fig 4I ). While the coMtb samples trended higher in relative frequency for Cluster 0 and low for Cluster 1, compared to the control or scBCG samples, these differences did not meet statistical significance (One-way ANOVA with Tukey post-test, p = 0.16, p = 0.11) ( Fig 4H ). This was likely due to the limit in statistical power with only 2 replicates. However, it was notable that for cells within Cluster 0, there was a significantly higher expression level for MHC II genes (H2-Aa, H2-DMb1, and Cd74) for coMtb cells compared to control or scBCG cells ( Fig 4J ). This suggests that coMtb might be able to elicit more mature or activated DCs in the airway. Overall, scRNAseq analysis shows that Mycobacterium exposure leads to minimal changes in T cell and dendritic cell populations in the airway, although we hypothesize that small changes in DC maturation/activation could have important impacts on adaptive immune priming dynamics after aerosol infection.

Single-cell RNA-sequencing of BAL samples from control, scBCG, and coMtb mice pre-aerosol challenge. A) Compiled scRNAseq data for all BAL samples, with T cell and dendritic cell clusters highlighted. B) Relative frequency of T cells and DCs. C-F) T cell subcluster analysis. C) T cell subclusters compiled and split by condition. Annotations made following Immgen profile matches and manual marker inspection. D) Relative frequency of Clusters 0–4 for each condition. E) UMAP gene expression plot for general T cell markers. F) UMAP gene expression plot cluster-specific markers split by condition. G-J) Dendritic cell subcluster analysis. G) Dendritic cell subcluster, colored by each of 3 different clusters. H) Relative frequency of Clusters 0–2 for each condition. I) Violin plots for cluster-specific markers and genes of interest. J) Differentially expressed genes in Cluster 0 split by condition. *adj-p< 0.05, **adj-p< 0 .01, ***adj-p< 0.001, Wilcoxon Rank Sum Test, Bonferroni adjusted p-values. Data is compiled from two independent experiments with 3 conditions each for a total of 6 samples.

While AMs are the dominant immune cell type in the airway, other cell populations make up an average of 18.4% of the cells within the BAL in controls (range: 10.4–26.3%) and 31.3% in exposed groups (range: 14.0–48.8%). To examine how Mycobacterium exposure influenced other cells in the airway, we focused on T cells and dendritic cells (DCs) which have two of the highest relative frequencies after AMs ( Fig 4A and 4B ). T cells and DCs were each combined from two original clusters each. Neither population showed a statistically significant difference in relative frequency ( Fig 4B ). To examine qualitative changes in the T cell population in greater detail, we next reclustered the T cells, resulting in 7 T cell clusters. We manually annotated each of the clusters based on the most closely matched Immgen profiles and the expression of key lineage specific markers ( Figs 4A–4C and S10 ). We focused on the 5 most abundant T cell subclusters (Clusters 0–4). While we observed subtle shifts in the relative frequency of each group, none reached statistical significance. Cluster 0, the most abundant cluster, had an expression profile most consistent with γδ T cells, including expression of Cd3e with low to nil Cd4 and Cd8a and some expression of Zbtb16 (PLZF) and Tmem176a, an ion channel regulated by RORγt and reported to be expressed by lung γδ T cells [ 35 , 36 ] ( Figs 4D–4F and S10 ). Cluster 1 matched a profile for effector CD4 + T cells ( Figs 4D–4F and S10 ), and Cluster 2 matched a profile for naïve CD8 + T cells ( Figs 4D–4F and S10 ). Cluster 3 had a profile consistent with effector memory/resident memory CD8 + T cells (T EM/RM ) ( Figs 4D–4F and S10 ) and Cluster 4 had a profile consistent with NK cells. Overall, there were no significant changes in the relative frequency of T cell or NK subclusters, despite detection of a number of different lymphocyte subsets in the airway.

In summary, scRNAseq analysis of macrophages isolated by BAL demonstrate that Mycobacterium exposure leads to subtle changes in a small minority of AM subsets in the airway, including ones associated with interferon responses and an interstitial macrophage phenotype, while leaving the most abundant subsets of AMs unchanged in frequency or gene expression. We hypothesize that these small changes in baseline profiles may be sufficient to drive the more substantial changes observed in the AM Mtb response in vivo, as described in Fig 2 .

Additionally, we compared baseline changes to AMs following scBCG and coMtb exposures to AM changes following ivBCG vaccination ( S9 Fig ). Overall, we found that ivBCG exposure led to similar changes in AM populations to that of scBCG vaccination, with increased frequency of AMs clustering to “oxidative stress response” and “interferon stimulated genes (ISGs)” ( S9C Fig ). These baseline changes by scRNAseq mirror what is observed for the response of Mtb-infected AMs from ivBCG mice 24 hours after infection by bulk RNAseq ( S9A and S9B Fig ). Profiles of Mtb-infected AMs from ivBCG vaccinated mice most closely match those of Mtb-infected AMs from scBCG vaccinated mice, with robust up-regulation of Interferon Stimulated Genes. These results demonstrate that both SC and IV BCG vaccination lead to similar remodeling of AMs, with profiles distinct from that of coMtb exposure.

To investigate potential reprogramming of non-AM macrophages, we examined Cluster 6, the macrophage cluster with low Siglecf and high Itgam expression that is consistent with a monocyte-derived macrophage population. We observed no statistically significant differences in the relative size of this cluster between each of the three conditions ( S8A Fig ). However, there were a number of Differentially Expressed Genes (DEGs) between the groups, including decreases in expression of CD11b (Itgam) and Macrophage scavenger receptor (Msr1) for scBCG and coMtb macrophages compared to controls, increases in MHC-related genes (H2-Aa, Cd74) and iron-metabolism associated genes (Cd63, Fth1, Ftl1) for coMtb macrophages compared to controls ( S8B Fig ). A previous study found IV BCG induced chromatin accessibility changes in AMs and IMs for some of these genes [ 31 ].

To further investigate whether a sub-cluster of AMs might be responsible for the increased enrichment for Interferon Alpha/Gamma Response pathways in the in vivo Mtb response in scBCG and coMtb mice, we scored each cluster based on the ISG gene module, previously used in Fig 2D . As expected, we observed that only Cluster 7 showed strong enrichment for ISGs, which trended up in frequency for both scBCG and coMtb samples ( Fig 3K ).

Interestingly, Cluster 2 (higher relative frequency in scBCG) and Cluster 3 (higher relative frequency in coMtb) represent divergent endpoints of a pseudotime plot generated by a trajectory inference analysis, regardless of whether the starting point is the most abundant cluster in the control group (Cluster 0) ( Fig 3J , top ) or the cluster of proliferating cells (Cluster 4) ( Fig 3J , bottom ). This result suggests that scBCG and coMtb may drive AM phenotypes in divergent directions and indicates that AM responses can be remodeled into more than one flavor, rather than only a binary “on/off” state.

To interpret the various expression subclusters, we identified the genes that most distinguished each cluster from the others ( S6 Fig and S2 Table ). As has been reported by other groups [ 31 , 32 ], a small proportion of the AMs in two clusters (Clusters 4, 9) had high expression of cell cycle genes (i.e., Top2a, Mki67), indicative of cell proliferation ( Fig 3E and S2 Table ). Cluster 0 was the most abundant macrophage cluster with high expression of lipid metabolism genes (i.e., Abcg1, Fabp1) ( Fig 3F and S2 Table ). Cluster 2 was significantly increased in relative frequency for scBCG samples compared to coMtb (p = 0.032, One-way ANOVA with Tukey post-test) and associated with oxidative stress response genes (Hmox1, Gclm). Several Cluster 2 associated genes, Slc7a11, Hmox1, and Sqstm1 also had higher overall expression level in scBCG samples compared to either control or coMtb ( Fig 3G and S2 Table ). Cluster 7 was the only cluster with an increase in relative frequency trending for both scBCG and coMtb (p = 0.076, One-way ANOVA). Cells in this cluster had high expression of Interferon Stimulated Genes (Ifit1, Isg15) and within this cluster, cells from scBCG samples had higher expression of Axl and Ifi204 than cells from coMtb samples. ( Fig 3H and S2 Table ). Cluster 3 had significantly higher relative frequency for coMtb samples compared to control and scBCG samples (p = 0.021, 0.039, respectively, One-way ANOVA with Tukey post-test) and was distinguished by expression of macrophage-associated transcription factors (Cebpb, Zeb2, Bhlhe40) [ 33 , 34 ], mitochondrial oxidative phosphorylation (mt-Co1, mt-Cytb, mt-Nd2), chromatin remodeling (Ankrd11, Baz1a), and immune signaling including the CARD9 complex (Malt1, Bcl10, Prkcd) ( Figs 3I and S7 and S2 Table ). This expression profile closely matches a subcluster of AMs previously described by Pisu et al, as an “interstitial macrophage-like” AM population (labeled “AM_2”) that expanded in relative frequency in lung samples 3 weeks following low-dose H37Rv infection [ 31 ]. Relative expression level for Cebpb, Mt-Cyb, and Lars2 within Cluster 3 was higher for cells from coMtb samples compared to either control or scBCG samples.

Single-cell RNA-sequencing of BAL samples from control, scBCG, and coMtb mice pre-aerosol challenge. A) Compiled scRNAseq data for all BAL samples, highlighted by major clusters, annotated based on closest Immgen sample match. B) Highlighting of the two clusters used for macrophage subcluster analysis. C) The 11 clusters generated by the macrophage subcluster analysis, separated by condition. D) Expression of major macrophage-specific markers: Siglecf, Mertk, Fcgr1, Lyz2, Itgam (CD11b), and Itgax (CD11c). E-I) Relative frequency of each macrophage subcluster by condition. (violin plots by cluster) Expression level of representative genes distinguished by that cluster compared to other clusters. One-way ANOVA with Tukey post-test, * p< 0.05. (3-way violin plots by condition) Differentially expressed genes within Clusters 2, 7, and 3 between control vs scBCG vs coMtb samples. Wilcoxon Rank Sum Test, Bonferroni adjusted p-value. *adj-p< 0.05, **adj-p< 0.01, ***adj-p< 0.001. J) Pseudotime analysis (Monocle3) with starting node at the largest cluster in control, Cluster 0 (top) and at the cluster of proliferating cells, Cluster 4,9 (bottom). K) ISG Module Score by cluster. Module derived from macrophage response to IFNα (fold change> 2, p-value< 0.01) (Mostafavi et al, 2016) [ 30 ]. Data is compiled from two independent experiments (circle, triangle) with 3 conditions each for a total of 6 samples.

Six samples, with an average of 2,709 cells per sample (range: 2,117–4,232), were analyzed together for a total of 17,788 genes detected. The most prominent expression cluster mapped to an AM profile, with smaller clusters mapping to T and B lymphocytes, dendritic cells, and neutrophils ( Fig 3A ). All cells that mapped to a macrophage profile were extracted and reclustered into 11 macrophage subclusters ( Fig 3B and 3C ). All but two of the macrophage subclusters (clusters 6 and 8) expressed AM lineage markers (Siglecf, Mertk, Fcgr1 (CD64), Lyz2 (LysM), and Itgax (CD11c) and had low expression of Itgam (CD11b) ( Fig 3D ). Cluster 6 showed high Itgam and Lyz2 expression and lower Siglecf expression, likely representing a small monocyte-derived macrophage population in the airway, while cluster 8 displayed high Lyz2 expression, low expression for other AM markers, and expression of Sftpa1 and Wfdc2 ( S2 Table ), genes most commonly expressed by pulmonary epithelial cells, suggesting that this cluster represents a small population of epithelial cells,

Although scBCG and coMtb exposures alter the AM responses to Mtb infection in vivo, transcriptional effects are not widely evident prior to infection as measured by bulk RNA-sequencing of naïve AMs from control, scBCG, or coMtb mice, including expression of innate receptors and adaptors ( S4 Fig ). However, we posited that remodeling effects were likely not homogenous across the entire AM population and that small heterogenous changes to baseline profiles might be detectable using a single cell approach. We therefore analyzed pooled BAL samples taken from 10 age- and sex-matched mice from each of the three conditions (control, scBCG, coMtb) eight weeks following Mycobacterium exposure by single cell RNA-sequencing (scRNAseq). Gross cellularity was unaffected by mycobacterial exposure as measured by flow cytometry analysis of common lineage markers with AMs being the dominant hematopoietic cell type (57.4–85.8% of CD45 + live cells), followed by lymphocytes (5.26–22.7% of CD45 + live cells) with smaller contributions from other innate cell populations ( S5 Fig ).

In summary, Mycobacterium exposures alter the initial in vivo response of AMs to Mtb infection 24 hours after challenge and remodel the AM response in distinct ways. AMs from scBCG vaccinated animals mount a strong interferon-associated response, while AMs from coMtb mice express a more diverse inflammatory profile consisting of both interferon-associated genes as well as other pro-inflammatory genes, including those within the IL-6 JAK STAT3 pathway.

To identify trends between groups, we performed Gene Set Enrichment Analysis using a set of 50 Hallmark Pathways. As we’ve shown previously, Mtb-infected AMs from control mice at 24 hours had strong enrichment for “Xenobiotic Metabolism” and “Reactive Oxygen Species” pathways, indicative of the Nrf2-associated cell-protective response ( Fig 2C ). While these two pathways were not among the most enriched pathways in the exposed groups, Mtb-infected AMs from all groups upregulated genes associated with the 131 in vivo DEG that make up the cell-protective Nrf2-driven response at 24 hours [ 10 ] ( Fig 2D ). Expression profiles for Mtb-infected AMs from scBCG mice showed the strongest enrichment for “Interferon Alpha Response” and “Interferon Gamma Response” pathways, which contain many shared genes ( Fig 2C ). The strength of the interferon response was further highlighted by examining gene expression changes in a set of Interferon Stimulated Genes (ISGs) identified from macrophages responding to IFNα (fold change > 2, p-value < 0.01) [ 30 ] ( Fig 2D ). Expression profiles for Mtb-infected AMs from coMtb mice showed a weaker enrichment for interferon response pathways with fewer up-regulated ISGs compared to scBCG, and instead showed enrichment across a number of inflammatory pathways including “IL6 JAK STAT3 signaling” in comparison to the other groups ( Fig 2C and 2D ). A direct comparison between the gene expression patterns for AMs from scBCG versus coMtb mice could be visualized more readily by scatterplots highlighting either Nrf2-associated, Interferon Alpha and Gamma Response, or IL-6 JAK STAT3 pathway genes ( Fig 2E ).

Bulk RNA-seq profiles of Mtb-infected AMs 24 hours following high-dose mEmerald-H37Rv infection. Gene expression changes are compared to respective naïve samples: Mtb-inf control vs naïve control; Mtb-inf scBCG vs naïve scBCG; Mtb-inf coMtb vs naïve coMtb (controls- reported in Rothchild et al, 2019 [ 10 ]; coMtb- reported in Nemeth et al, 2020 [ 25 ]). A) Principal Component Analysis using DEG (|fold change| > 2, FDR< 0.05) in Mtb-infected AMs compared to respective naïve AMs (control, scBCG, or coMtb). B) Venn Diagram and Intersection plot of overlap in up-regulated DEG between the 3 conditions. C) Gene Set Enrichment Analysis of 50 Hallmark Pathways. Pathways shown have |NES| > 1.5 and FDR< 0.05 for at least one of the conditions. * FDR< 0.05, **FDR< 0.01, ***FDR< 0.001. D) Heatmap of 131 original in vivo DEG at 24 hours in Mtb-infected AM (left), Interferon Stimulated Genes, derived from macrophage response to IFNα (fold change >2, p-value < 0.01) Mostafavi et al, 2016 [ 30 ] (center-left), IL6 JAK STAT3 hallmark pathway (center-right) and selected coMtb signature genes (right, *FDR< 0.05, FC> 2). E) Scatterplots depicting fold change (log 2 ) for Mtb-infected AMs over naïve AMs for scBCG versus coMtb. Highlighted pathways: Nrf2-associated genes out of 131 original in vivo DEG (56 genes, purple), shared leading edge genes for scBCG Interferon Alpha Response and Interferon Gamma Response pathways (61 genes, orange), and leading edge genes for coMtb IL6 JAK STAT3 pathway (23 genes, green). Compiled from 4 independent experiments per condition for control, 2 independent experiments per condition for scBCG and coMtb.

To examine the earliest response to Mtb, we measured the gene expression profiles of Mtb-infected AMs isolated by bronchoalveolar lavage and cell sorting, as previously described [ 10 ], 24 hours following aerosol challenge with high dose mEmerald-H37Rv (depositions: 4667, 4800) in scBCG-vaccinated mice and compared these measurements to previously generated profiles of AMs from control (unexposed) mice [ 10 ] and coMtb mice [ 25 ] ( S1 Table ). As previously observed for the high dose infection, an average of 1.79% (range: 0.91–3.18%) of total isolated AMs were Mtb infected 24 hours after infection. Changes induced by Mtb infection were measured by comparing gene expression between Mtb-infected AMs and respective naïve AMs for each of the three groups (control, scBCG, coMtb). Principal Component Analysis on Mtb infection-induced changes showed that each of the three conditions led to distinct expression changes ( Fig 2A ) and the majority of up-regulated Differentially Expressed Genes (DEG) (fold change > 2, FDR < 0.05) were unique to each condition (control: 151 unique/257 total DEG, scBCG: 222/289, coMtb: 156/229) ( Fig 2B ). The divergence in the responses of Mtb-infected AMs from each of the 3 conditions was also reflected in the diversity in the Top 20 Canonical Pathways identified by Ingenuity Pathway Analysis ( S3 Fig ).

We also evaluated whether these cell recruitment differences correlated with changes in bacterial burden. To compile CFU results from three independent experiments, each with slightly different bacterial growth ( S2A Fig ), we calculated a ΔCFU value that compared the bacterial burden of each sample to the average for the respective control based on timepoint, organ, and experiment. We found that both modalities generated a significant reduction in bacterial burden compared to controls in the lung, spleen, and lung-draining lymph node (LN) at day 14 and at day 28, as previously reported [ 16 , 25 , 29 ] ( S2A–S2D Fig ) . At day 10, we observed no difference in lung bacterial burden in scBCG or coMtb mice compared to controls and a small increase in coMtb mice over scBCG. The majority of control mice had undetectable bacteria in spleen and LN at this time. There was a significant reduction in bacterial burden in the lung by day 12 in coMtb but not scBCG mice and a significant reduction in CFU in the LN in both models compared to controls ( S2B Fig ). Our results demonstrate that prior Mycobacterium exposure leads to accelerated innate cell activation and recruitment, alongside an increase in activated T cells, within the first two weeks of infection, with coMtb generating a faster and more robust response compared to scBCG. These early immune changes are associated with reductions in bacterial load in the lung. Differences in bacterial burden in the LN and spleen suggest delays in bacterial dissemination, which first appear in the LN at day 12 and then in the spleen at day 14 ( S2A Fig ).

In addition to early changes in innate cell activation and recruitment, we observed early recruitment of activated CD44 + CD4 + and CD8 + T cells in the lungs of both coMtb and scBCG mice starting at day 10 as well as TB antigen-specific T cells, ESAT6-tetramer + CD4 + T cells and TB10.4-tetramer + CD8 + T cells in coMtb mice starting at day 10 compared to controls and scBCG mice ( Figs 1D and S1 ). The differences in the recruitment of ESAT6-tetramer + CD4 + T cells between scBCG and coMtb were expected, as the ESAT6 antigen is expressed by H37Rv but not by BCG.

We first determined the earliest stage of infection when the immune response was altered by prior exposure to Mycobacterium. Mice were vaccinated with scBCG or treated with coMtb, rested for 8 weeks, and then challenged with low-dose H37Rv aerosol infection. We measured both the cellularity and activation of innate immune cells in the lung at 10, 12 and 14 days following infection, the earliest timepoints when innate cells are known to be recruited [ 10 , 11 , 28 ]. We observed a significant increase in MHC II Median Fluorescence Intensity (MFI) as early as day 10 for AMs from coMtb mice and day 12 for AMs from scBCG mice compared to controls ( Figs 1A and S1 ). There were no significant differences in MHC II expression prior to challenge on day 0 ( Fig 1A ). There were also significant increases in the numbers of monocyte-derived macrophages (MDM), neutrophils (PMN), dendritic cells, and Ly6C + CD11b + monocytes by day 10 in coMtb mice compared to controls, with further increases by days 12 and 14 ( Figs 1B and S1 ). scBCG elicited similar increases in these populations starting at day 10, but the increases were not as robust or rapid as those observed in coMtb. Significant differences between scBCG and coMtb groups were found at days 10, 12, and 14 in MDM, day 14 in PMN, days 12 and 14 in dendritic cells, and day 14 in Ly6C + CD11b + monocytes ( Fig 1B ). While there were not significant differences in AM cell number between the three conditions, there was a modest drop in viability for both AMs from scBCG and coMtb mice by day 14 ( Fig 1C ).

Discussion

Here we describe remodeling of AMs, long-lived airway-resident innate cells, following two modalities of Mycobacterium exposure, scBCG vaccination and coMtb, a model of contained Mtb infection. AMs are the first cells to be productively infected in the lung following aerosol Mtb infection [10,11]. We previously showed that AMs initially respond to Mtb infection with a cell-protective, Nrf2-driven program that is detrimental to early host control [10], suggesting that the lack of a robust response by AMs prevents effective host control early on. In line with this model, others have shown that depletion of AMs or strategies that “bypass” AMs including directly injecting antigen-primed DCs or activating DCs accelerate the immune response and reduce bacterial burden [17,39,40]. However, how vaccination or prior exposures impact the initial response of AMs and whether there are therapeutic strategies that would enhance their initial response to infection have not been well studied [41].

Most studies examining the impacts of prior exposure to either Mtb or other species of mycobacteria, including BCG vaccination, have focused on the durable antigen-specific changes to the adaptive immune response. In contrast, we focused on changes to tissue-resident innate cells and their responses at the earliest stages of infection (≤ 14 days). Along with early changes to the T cell response, both scBCG and coMtb accelerate innate cell activation and immune cell recruitment in the first 10–14 days following Mtb aerosol infection, and even the very initial AM response to Mtb, within the first 24 hours of infection, is remodeled following exposure to Mycobacterium. The durable changes observed fit with a number of recent studies which have uncovered either enhanced AM antimicrobial phenotypes [7–9] or impaired responses [42,43] following viral infection. Other studies have identified long-lasting changes to AMs following intranasal immunization of either adenoviral-based or inactivated whole cell vaccines [18,44,45].

We observe that the most robust cell-intrinsic changes to AM responses following scBCG or coMtb are found in IFN-dependent genes (Fig 6) and ISGs (Fig 2D), suggesting a critical role for interferon signaling in the changes to the early innate response in the lung during infection. Notably, this finding is not limited to the murine model. BAL from NHPs following IV, ID, or aerosol BCG vaccination similarly show AMs enriched for Interferon Gamma Response pathway genes [46]. AMs can respond to both Type I (IFNα/β) and Type II Interferons (IFNγ) and it is not possible to distinguish between responses to IFNα/β and IFNγ based on transcriptional analysis alone. The presence of live bacteria within both scBCG and coMtb models limits system-wide perturbations, such as T cell depletion or anti-IFNγ blockade, which would reverse containment [24]. For this reason, we have not been able to directly test how interferon signals derived from scBCG or coMtb remodel AMs in a cell-autonomous manner, but we envision future studies to examine the specific effects of individual cytokines on AM remodeling.

Even though IFNAR-/- macrophages were used to generate the ISG signature identified in Fig 6, IFNγ is the more likely candidate to contribute to AM remodeling following Mycobacterium exposure. IFNγ is required for the generation of trained immunity in bone marrow-derived myeloid cells following IV BCG vaccination [15,47]. While IV and aerosol H37Rv infection was found to induce Type I IFNs and reduce myelopoiesis [47], we previously found that coMtb, in which Mtb is contained within the ear-draining lymph node, leads to low-level systemic cytokinemia, including IFNγ production. Using WT:Ifngr1-/- mixed bone marrow chimeras, we showed that IFNγ signaling was responsible for monocyte and AM activation following establishment of coMtb [25]. Additionally, several reports have identified T cell-derived IFNγ as critical for altering AM function, although the immunological outcome varies substantially based on the context. In one study, T cell-derived IFNγ following adenoviral infection leads to AM activation, innate training and protection from S. pneumoniae [8], while in another study influenza-induced T cell-derived IFNγ leads to AM dysfunction and impaired clearance of S. pneumoniae [43]. A study of 88 SARS-CoV-2 patients identified AMs and T cell-derived IFNγ as part of a positive feedback loop in the airway [48]. In contrast, type I IFN signatures are associated with active TB or TB disease progression in both humans and non-human primates [49–51]. Host perturbations such as treatment with poly I:C or viral co-infection that induce type I IFN lead to worsened disease [52,53], type I IFN has been shown to block production of IL-1β in myeloid cells during Mtb infection [54], and type I IFN drives mitochondrial stress and metabolic dysfunction in Mtb infected macrophages [38].

We note that the two modalities tested here consist of different mycobacterial species, different doses, and different routes. We expect that all three of these factors likely contribute to the quality of AM remodeling. For example, they could be important for the location, timing, and amount of IFNγ that AMs are exposed to. While an in-depth examination of each of these factors is beyond the scope of this study, the side-by-side comparison of the two different exposure models, scBCG and coMtb, allows us to examine the plasticity of AM phenotypes and the impact of the local and/or systemic environments leading to different responses. It is notable that scBCG is quickly cleared from WT mice, while coMtb replication is sustained in the superficial cervical lymph node for up to a year or longer [25]. Protection from H37Rv challenge mediated by coMtb is abrogated following antibiotic treatment but not completely lost [25]. This suggests that there may be different contributions to AM remodeling from active bacterial replication and from long-term microenvironment changes following bacterial clearance, which will be addressed in follow-up studies.

In particular, it is notable that the modality-specific signatures identified through in vivo transcriptional analysis disappeared following ex vivo isolation, along with the Nrf2 signature. The difference between in vivo and ex vivo signatures suggests a critical contribution of the altered lung microenvironments in AM remodeling, which deserves additional follow-up studies.

One additional limitation of our approach is that the ex vivo samples were collected in bulk, in the absence of cell sorting, and so, unlike the in vivo studies, a very small number of bystander AMs were likely collected alongside the Mtb-infected AMs, which could have had minor impacts on the transcriptional signatures. The fact that AMs can be remodeled into more than one state suggests additional complexity in innate immune features that has not yet been fully explored. Heterogeneity in myeloid reprogramming is not limited to the murine model and has also been observed in human monocytes [55].

Several studies have recently described innate-adaptive interactions within the airway that are thought to impact infection dynamics [46,48]. We note that in these models we observe innate cell activation and recruitment occurring at the same time as T cell activation and recruitment, and that these events are likely promoting one another. We are particularly intrigued by the changes in AM MHC class II expression that we observed in vivo during the first two weeks of infection (Fig 1A) and following ex vivo stimulation (Fig 5F). AMs are considered to be poor antigen presenters, relative to other myeloid subsets, yet the faster Mtb-specific T cells are recruited to the lung, the more likely it is that AMs will serve as primary T cell targets [37,56–60]. Our results suggest that enhancement of AM antigen presentation could be one innate mechanism that could be targeted to complement and synergize with the adaptive immune response during infection. Other potential mechanisms by which AM remodeling may contribute to enhanced bacterial control after Mtb aerosol challenge include enhanced phagocytic activity or increased direct antimycobacterial activity, as previously demonstrated by Jeyanathan et al [19]. Future studies are needed to further interrogate the contribution of these innate mechanisms.

There are many other remaining questions. While we identify both cell-intrinsic changes and changes dependent on the lung environment, we do not yet know whether the cell-intrinsic changes are retained long-term in the absence of environmental cues. We do not know the durability of the changes, both cell-intrinsic and environment-dependent, and whether they are mediated by epigenetic effects. Our longest experiment showed retention of cell-intrinsic changes to AMs after 23 weeks. In Nemeth et al, we showed that antibiotic treatment lessened the protection mediated by coMtb, suggesting that ongoing replication is a key part of host protection [25]. AM remodeling is retained 8 weeks or longer after the initial exposures, a timepoint when there is little to no detectable mycobacteria in the lung, ruling out a requirement for local ongoing bacterial replication in AM remodeling, although systemic signals derived from remote bacterial replication may still play a role. We also performed several of these studies with intravenous BCG vaccination (ivBCG), which in the mouse model leads to more sustained bacterial replication than scBCG [61]. While we observed similar remodeling to AMs in the ivBCG model, these were not different in quality to those of scBCG vaccination, despite the major differences in bacterial replication and far greater T cell recruitment to the airway, suggesting that these changes are not required for AM remodeling (S9 Fig).

There is still much unknown about the signals that drive reprogramming of tissue-resident innate cells. Ideally, vaccines would be designed to leverage these signals in order to promote the most effective interactions between innate and adaptive responses. Identifying the ways that AMs are reprogrammed by inflammatory signals and the effects of their changed phenotypes on the early stages of infection will help to improve future vaccines or host-directed therapies.

[END]
---
[1] Url: https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1011871

Published and (C) by PLOS One
Content appears here under this condition or license: Creative Commons - Attribution BY 4.0.

via Magical.Fish Gopher News Feeds:
gopher://magical.fish/1/feeds/news/plosone/

You are viewing proxied material from magical.fish. The copyright of proxied material belongs to its original authors. Any comments or complaints in relation to proxied material should be directed to the original authors of the content concerned. Please see the disclaimer for more details.