Share brush ảnh sáng lung linh

     
View ORCID ProfileElo Madissoon, View ORCID ProfileAmanda J. Oliver, View ORCID ProfileVitalii Kleshchevnikov, Anna Wilbrey-Clark, View ORCID ProfileKrzysztof Polanski, View ORCID ProfileAna Ribeiro Orsi, Lira Mamanova, View ORCID ProfileLiam Bolt, Nathan Richoz, View ORCID ProfileRasa Elmentaite, View ORCID ProfileJ. Patrick Pett, Ni Huang, View ORCID ProfilePeng He, Monika Dabrowska, View ORCID ProfileSophie Pritchard, Liz Tuck, View ORCID ProfileElena Prigmore, View ORCID ProfileAndrew Knights, View ORCID ProfileAgnes Oszlanczi, View ORCID ProfileAdam Hunter, View ORCID ProfileSara F. Vieira, Minal Patel, View ORCID ProfileNikitas Georgakopoulos, View ORCID ProfileKrishnaa Mahbubani, View ORCID ProfileKourosh Saeb-Parsy, View ORCID ProfileMenna Clatworthy, View ORCID ProfileOmer Ali Bayraktar, View ORCID ProfileOliver Stegle, View ORCID ProfileNatsuhiko Kumasaka, View ORCID ProfileSarah A. Teichmann, View ORCID ProfileKerstin B. Meyer
doi: https://doi.org/10.1101/2021.11.26.470108
Elo Madissoon
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
2European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
Amanda J. Oliver
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Vitalii Kleshchevnikov
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Anna Wilbrey-Clark
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Krzysztof Polanski
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Ana Ribeiro Orsi
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
3Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, SP 05508-090, São Paulo, Brazil
Lira Mamanova
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Liam Bolt
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Nathan Richoz
4Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Ave, Cambridge CB2 OQH, UK
Rasa Elmentaite
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
J. Patrick Pett
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Ni Huang
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Peng He
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Monika Dabrowska
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Sophie Pritchard
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Liz Tuck
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Elena Prigmore
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Andrew Knights
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Agnes Oszlanczi
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Adam Hunter
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Sara F. Vieira
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Minal Patel
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Nikitas Georgakopoulos
5Department of Surgery, University of Cambridge, & Cambridge NIHR Biomedical Research Centre, Cambridge, CB2 0QQ, UK
Krishnaa Mahbubani
5Department of Surgery, University of Cambridge, & Cambridge NIHR Biomedical Research Centre, Cambridge, CB2 0QQ, UK
Kourosh Saeb-Parsy
5Department of Surgery, University of Cambridge, và Cambridge NIHR Biomedical Research Centre, Cambridge, CB2 0QQ, UK
Menna Clatworthy
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
4Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Ave, Cambridge CB2 OQH, UK
Omer Ali Bayraktar
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Oliver Stegle
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
6European Molecular Biology Laboratory EMBL, Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany
7Deutsches Krebsforschungszentrum DKFZ, im Neuenheimer Feld 280, 69120 Heidelberg, Germany
Natsuhiko Kumasaka
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
Sarah A. Teichmann
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
8Theory of Condensed Matter, Cavendish Laboratory/Dept Physics, University of Cambridge, JJ Thomson Ave, Cambridge CB3 0HE, UK
Kerstin B. Meyer
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK

Figure 4. IgA plasma cells in human airways co-localise with submucosal glands

(a) UMAP of single nuclei RNA-seq airway epithelial cells (excluding parenchyma AT1 & AT2 epithelial cells) with dashed line around SMG-Duct & myoepithelial cells và a dot plot for the SMG-Duct marker genes. (b) RNAscope staining of mucous, serous & duct cells with respective marker genes MUC5B, LPO và ALDH1A3/RRARES1 in human bronchus. (c) UMAP plots of myeloid, T/NK và B cell lineage cells, colored by cell type. (d) Number of B lineage cells with different Ig isotypes in airway (trachea & bronchi) from the analysis of VDJ amplified libraries. (e) Percentages of different isotypes of B & plasma cells from the nasal and tracheal brushes of COVID-19+ and healthy control patients (Yoshida et al. 2021). Patients with over 20 B & plasma cells were considered. (f) Visium ST results show IgA plasma cells specific localisation in the glands. H&E on bronchi with manually annotated gland regions shown in blue, Cell2location mật độ trùng lặp từ khóa scores for IgA-plasma cells, and normalised average cell abundance (dot form size and color) for SMG cell types và B lineage cell types across the manually annotated regions in the Visium data. (g) Multiplex IHC staining of human trachea for the SMG structure (Hoechst for nuclei, EpCAM for epithelium, Phalloidin for actin, CD31 for vessels), B lineage markers (IgD, IgA2, IgG) & CD4 T-cells (CD45, CD3, CD4). Arrows point khổng lồ CD45+CD3+CD4+ cells. Scale bar 100 µm.

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An additional population was revealed from snRNAseq, exhibiting both basal epithelium and muscle markers with localisation around the glands (Figure 4a, Figure S8g), consistent with a myoepithelial cell signature (Goldfarbmuren et al. 2020b). Co-localisation of FHOD3, epithelial marker KRT14 and muscle marker TAGLN in the same cells confirmed the myoepithelial cell signature by smFISH (Figure S8g). Interestingly, mouse myoepithelial cells have also been shown to lớn regenerate the surface airway epithelium (Tata et al. 2018)). This cell type is not as well described in humans, potentially due khổng lồ difficulties in dissociating this cell type from the airways consistent with exclusive recovery of myoepithelial cells from nuclei data. Overall, we provide the human transcriptome for novel SMG populations, & mapped the constituents of the SMG và their spatial location using both spatial transcriptomics và smFISH.


Proportions & gene signatures of the airway epithelial cells

Using statistical modelling that accounted for material, donor and dissociation protocol (see Methods), we examined the proportions of airway epithelial cells at the 5 different locations sampled (Figure S8c), with significance given as local true sign rate (LTR). As expected, club cells were enriched in the parenchyma, whereas SMG epithelial cells were enriched in the trachea. While donor và protocol had little effect on the epithelial cell type proportions, the starting material of cells versus nuclei strongly influenced cell type composition (Figure S8c). SMG epithelial cell capture was increased in nuclei, while the capture of other epithelial cell types was better achieved with the dissociation into single cells (Figure S8c).

Taking advantage of our multi-location data, we compared gene expression for ciliated cells, as one of the most abundant cell types present, across the five locations. We avoided any artefacts due khổng lồ differing ambient RNA contamination between locations using only snRNAseq data where samples were pooled across locations for the 10X sequencing reaction (Figure 1a). Using a linear mixed model (A. M. H. Young et al. 2021) (Methods) we detected 80 differentially expressed genes in ciliated cells from trachea compared to lớn other locations (LTSR>0.9), many of which are upregulated in nasopharyngeal carcinoma including FBXL7, TSHZ2 and RAET1E (Figure S8i) (Borchers et al. 2009; Motz et al. 2010; Wortham et al. 2013). We also examined ACE2 expression, a SARS-COV-2 entry gene, which we found lớn be highest in ciliated cells from the trachea, & lower in the distal regions of the lung, where expression of ACE2 is likely to be more relevant in AT2 cells as reported previously (Figure S8j) (Deprez et al. 2020).

Altogether, we describe transcriptomes for two key cell types involved in the SMG structure in the human airways which also functions as an immunological niche which we describe below.


Myeloid cells show previously undescribed heterogeneity

For the immune compartment, we identified all major populations including myeloid, T&NK, B lineage, mast cells and megakaryocytes which were analysed separately khổng lồ reveal previously undescribed heterogeneity, especially in the myeloid cells (Figure 4c, Figure S9a-c, Figure S10 a). We found all major myeloid cell types (DCs, monocytes & macrophages) including many known & novel subsets. Previously identified macrophage subsets included intravascular macrophages (expressing LYVE1 and MAF) (Chakarov et al. 2019; Evren et al. 2021), Macro-AW-CX3CR1 (Chakarov et al. 2019; Pirzgalska et al. 2017; Y. Wolf et al. 2017; Hulsmans et al. 2017), Macro-CHIT1 (CHIT1 expressing with roles in asthma, COPD & lung fibrosis) (Travaglini et al. 2020; Chang, Sharma, và Dela Cruz 2020) and interstitial macrophages (Macro-interstitial expressing chemokines CXCL9, 10 & 11)(Evren et al. 2021). We identified a new cluster expressing both monocyte CD14 and macrophage markers, termed Macro-intermediate (Figure S9a). Among alveolar macrophages, two more clusters appeared: dividing cells (Macro-alv-dividing), và a novel cell cluster expressing metallothioneins (Macro-alv-MT) including MT1G, MT1X and MT1F. Metallothioneins have a role in binding & metabolising metal ions (Artur Krężel 2017), immunity & stress response (Subramanian Vignesh & Deepe 2017; Takano et al. 2004), and therefore this population may have a function in response to lớn air pollution. The final rare novel population of macrophages expressed chemokines including CXCL8, CCL4 & CCL20 & was named Macro-CCL. While the expression of CCL4 was previously identified in interstitial macrophages (Evren et al. 2021), the expression of CXCL8 & CCL20 distinguishes this novel subset. Dysregulation of CXCL8 expression is associated with multiple lung conditions including infection, asthma, IPF and COPD (Mukaida 2003) and was identified as a marker for a separate macrophage population in psoriatic skin (Reynolds et al. 2021).

Overall, we have identified multiple known & novel myeloid populations in the healthy human lungs và airways, many of them expressing specific sets of chemokines, orchestrating the complex lung immune homeostasis.


Different subsets of T và NK cells in the lung & airways

T lymphocytes and natural killer (NK) cells included all major cell types (CD4, CD8, mucosal-associated invariant T (MAIT), NK, NKT, innate lymphoid cells (ILC)) & their subsets (Figure 4c, Figure S9b). In the CD4 compartment we distinguished naive/central memory (CD4-naive/CM), effector memory/effector (CD4-EM/Effector), regulatory T cells (Treg) and tissue resident memory (CD4-TRM) cells. Within CD8 cells we found gamma-delta T cells (γδT) TRMs (CD8-TRM) (Hadley et al. 1997) which nicely localised khổng lồ airway epithelium in our spatial data as known in the literature (Figure S9d)(Piet et al. 2011; Wu et al. 2014). In addition we saw two distinct CD8+ clusters analogous to lớn populations found in the lung in cross tissue analysis (Conde et al., n.d.) expressing CX3CR1 & GZMB (CD8-EM/EMRA) & CRTAM and GZMK (CD8-TRM/EM). NK subsets included clusters with markers ITGAD/CD11d, LAG3, KLRC3/NKG3E, KLRC2/NKG2C (NK-CD11d), CD16+ (NK-CD16hi) và CD56 bright NK cells (NK-CD56 bright) (Ghilas et al., n.d.; Böttcher et al. 2018). NK cells positive for CD11d have an activation or viral response in infection in both mouse and human (Ma et al. 2017; Fang et al. 2011; Triebel et al. 1990) và were previously shown in human blood (Siegers et al. 2017). To our knowledge this is the first time this subset has been described in healthy human lung.

The T & NK cells displayed striking donor-to-donor variability in cell type proportions compared lớn the myeloid clusters (Figure S9 g-i), consistent with higher inter-individual variability in the adaptive immune compartment. The location of origin, material and protocol explained little variation for any of the cell types proportions, including for the B cells.

We also obtained TCR VDJ sequencing data that confirmed MAIT cell type annotation (with preferential use of TRAJ33 và TRAV1-2)(Treiner et al. 2003), & showed low clonal expansion in naive và Treg populations compared to memory & effector subsets (Figure S9 e). Lastly we show that, as expected, there was no clonal sharing between individuals, but expanded clones were found in multiple locations of the lung within one donor (Figure S9 f).


Co-localisation of IgA plasma cells with the SMG

B cells included naive & memory B cells, & plasma cells that were further annotated into immunoglobulin (Ig) IgG or IgA secreting plasma cells and plasmablasts (Figure 4c, Figure S10a, b), & this annotation was supported by VDJ-seq data via Scirpy BCR isotype analysis. IgA, which is important for mucosal immunity (Corthesy 2013, Kunkel & Butcher 2003, Salvi & Holgate 1999), was the most frequent isotype in the airway samples, while only the third most abundant in the parenchyma (Figure 4d, Figure S10 e). Interestingly, we observe that proportions of IgA plasma cells, relative khổng lồ IgG, are increased in COVID-19 patients versus healthy controls in single cell data from nasal và bronchial brush samples (Figure 4e) (Yoshida et al. 2021). The distinguishing markers for IgA versus IgG plasma cells included CCR10 và B-cell maturation antigen BCMA (TNFRSF17) (Figure S10 b), which are important for plasma cell localisation & survival, respectively (Morteau et al. 2008; Kunkel and Butcher 2003; O’Connor et al. 2004)

Using Visium ST, we observed the localisation of IgA B plasma cells, but not B or IgG plasma cells, in the airway SMG in trachea and bronchi sections (Figure 4f). Annotation of anatomical regions across all Visium sections confirmed co-localisation of IgA plasma cells with duct, serous và mucous SMG cells, whilst IgG mapped khổng lồ immune infiltrates (Figure 4f). The mapping of IgA plasma cells to lớn the SMG is confirmed in the Human Protein Atlas which shows an abundance of plasma cells (MZB1+) in the SMG region of the bronchus và the nasopharynx (Figure S10 c, d), along with a study from the 1970s that showed localisation of IgA plasma cells in human airway SMG (Soutar 1976).

Using multiplex IHC we showed the specific presence of IgA2 plasma cells in the SMG at single cell resolution, while IgG positive cells were present in the airways only outside the SMG, consistent with Visium ST (Figure 4g, Figure S10 f). We also detected IgD+ naive B cells & CD3+CD4+ T helper cells in the SMG (Figure 4g), suggesting that IgA plasma cells are supported by a complement of cell types that can orchestrate B cell maturation for IgA secretion directly into the airway mucous. We hypothesise that together these different cell types constitute an immune niche which we term gland associated lymphoid niche (GALN). Understanding the immunological mechanisms at the SMG can help understand disease, as increased plasma cell numbers in SMG have been shown in smokers (Soutar 1976), in COPD (Zhu et al. 2007) và in Kawasaki disease (Rowley et al. 2000).


Cell-cell interactions and the SMG immune cell niche

To understand colocalization of B cells, IgA plasma cells and T cells in the SMG (Figure 4f), we explored the molecular mechanisms underpinning the SMG as a potential immune niche. We report that expression of pIgR, which facilitates transcytosis of polymeric Ig across the surface epithelium, was high across all SMG epithelial cells, as was Mucosal Epithelial Chemokine (MEC)/CCL28, known khổng lồ recruit IgA plasma cells through CCR10 in other mucosal sites (Figure 5a, b) (Wilson and Butcher 2004; Morteau et al. 2008). Using cell-cell interaction analysis tool CellChat on cells from the airways (Jin et al. 2021) we saw that, in addition lớn the CCL28-CCR10 axis between SMG cells và B plasma cells (combined IgA, IgG & plasmablasts), SMG-Duct cells were predicted khổng lồ interact with CCR6 on memory & naive B cells and CD4 T cells (combined CD4 subsets, excluding Tregs) through CCL20 (A. Y. S. Lee et al. 2017; Elgueta et al. 2015; Bowman et al. 2000) (Figure 5b-d).


Cell-cell signaling at submucosal gland for B cell recruitment và survival niche. (a) Expression of PIGR & CCL28 in epithelial cells. (b) CellChat cell-cell interaction analysis pathways for CCL chemokines present from SMG epithelial cells to B cells (memory, naive và IgA/IgG/plasmablast combined) or CD4-T cells (CD4-naive/CM, CD4-EM/Effector & CD4-TRM combined) within airway tissue (trachea & bronchi). Arrow direction denotes chemokine-receptor pairs on specific cell types, arrowhead thickness reflects the relative expression of chemokine signal from each cell type. (c-d) Expression dot plot of relevant chemokines và corresponding receptors as shown in (b). (e) CellChat analysis as in (b) showing signalling from HLA genes expressed by SMG epithelial cells, signaling to CD4 on CD4-T cells. Arrow direction denotes ligand-receptor pairs on specific cell types, arrowhead thickness and proportion of the circle by each HLA gene/SMG epithelial cell type reflects the relative expression. (f) RNA expression of HLA-DRA, HLA-DRB1 and CD40 in B cells (as professional antigen presenting cell controls), ciliated and SMG epithelial cells from sc/snRNAseq. (g) Protein staining of HLA-DR và EpCAM in human trachea showing strong expression of HLA-DR in the SMG. (h-i) CellChat analysis as in (b) và (e) showing signalling of APRIL & IL-6 from SMG epithelial cells to relevant B cell subsets và CD4-naive/CM. Arrow direction denotes ligand-receptor pairs on specific cell types, arrowhead thickness & proportion of the circle for each gene/cell type reflects the relative expression. (i) Expression dot plot of relevant ligands and corresponding receptors as shown in (h). (j) Schematic of SMG immune niche showing immune cell recruitment and extravasation facilitated by venous endothelial cells và IR-Ven-Peri and signaling patterns between SMG gland epithelial cells, CD4-T cells, B-naive/memory cells và B-plasma cells khổng lồ attract immune cells và promote antigen-specific T cell dependent và T cell independent pathways leading khổng lồ IgA secretion at the SMG.
Figure 5. Cell-cell signaling at submucosal gland for B cell recruitment và survival niche.

(a) Expression of PIGR và CCL28 in epithelial cells. (b) CellChat cell-cell interaction analysis pathways for CCL chemokines present from SMG epithelial cells lớn B cells (memory, naive và IgA/IgG/plasmablast combined) or CD4-T cells (CD4-naive/CM, CD4-EM/Effector and CD4-TRM combined) within airway tissue (trachea & bronchi). Arrow direction denotes chemokine-receptor pairs on specific cell types, arrowhead thickness reflects the relative expression of chemokine signal from each cell type. (c-d) Expression dot plot of relevant chemokines & corresponding receptors as shown in (b). (e) CellChat analysis as in (b) showing signalling from HLA genes expressed by SMG epithelial cells, signaling to lớn CD4 on CD4-T cells. Arrow direction denotes ligand-receptor pairs on specific cell types, arrowhead thickness và proportion of the circle by each HLA gene/SMG epithelial cell type reflects the relative expression. (f) RNA expression of HLA-DRA, HLA-DRB1 & CD40 in B cells (as professional antigen presenting cell controls), ciliated and SMG epithelial cells from sc/snRNAseq. (g) Protein staining of HLA-DR và EpCAM in human trachea showing strong expression of HLA-DR in the SMG. (h-i) CellChat analysis as in (b) và (e) showing signalling of APRIL và IL-6 from SMG epithelial cells to lớn relevant B cell subsets & CD4-naive/CM. Arrow direction denotes ligand-receptor pairs on specific cell types, arrowhead thickness & proportion of the circle for each gene/cell type reflects the relative expression. (i) Expression dot plot of relevant ligands & corresponding receptors as shown in (h). (j) Schematic of SMG immune niche showing immune cell recruitment và extravasation facilitated by venous endothelial cells và IR-Ven-Peri & signaling patterns between SMG gland epithelial cells, CD4-T cells, B-naive/memory cells and B-plasma cells lớn attract immune cells & promote antigen-specific T cell dependent và T cell independent pathways leading khổng lồ IgA secretion at the SMG.


Cellchat also predicted interactions between HLA genes expressed by SMG epithelial cells, particularly SMG-Duct cells, and CD4-T cells (Figure 5e, f). The expression of HLA-DRAHLA-DRB1 in SMG-Duct cells was comparable lớn ciliated cells and, as expected, less than B memory and naive cells (Figure 5f). Interestingly, we observed strong expression of HLA-DR protein by IHC in the glands, but not in the surface epithelium showing discrepancy between transcript and protein levels (Figure 5g). We additionally found expression of CD40, a co-stimulatory molecule key for APC-T cell interactions, in SMG epithelial cells (Figure 5f). The expression of both these factors suggests that SMG-Duct cells can present antigen lớn CD4 T cells. Expression of HLA-DR và CD40 has previously been observed in airway & nasal epithelial cells, resulting in promotion of T cell proliferation in vitro (Rossi et al. 1990; Kalb et al. 1991; Cagnoni et al. 2004; Gormand et al. 1999; Tanaka et al. 2001). Interestingly, CD40 expression has been observed in duct, but not other cells, of the salivary gland and is upregulated in Sjögren’s syndrome, a systemic autoimmune exocrinopathy (Dimitriou et al. 2002).

In further tư vấn of an immune niche, A Proliferation Inducing Ligand (APRIL), a factor important for B cell survival, differentiation & class switching, was expressed by SMG-Duct cells, và to a lesser extent by SMG-Serous cells (Figure 5h,j). Cell-cell communication through these ligands was predicted between SMG epithelial cells and B-memory và B-plasma cells, based on differential expression of the receptors TACI and BCMA (Figure 5 h, j). In the colon, APRIL expression can be induced on intestinal epithelial cells & leads to IgA2 class-switch recombination (CSR) in the local tissue environment (He et al. 2007). We also find that a portion of B memory cells express activation-induced cytidine deaminase (AIDCA), suggesting the possibility of local CSR at the SMG through TACI-APRIL signaling (Figure S10 g). SMG-Duct, and to a lesser extent SMG-Serous, cells expressed IL-6, which was predicted to lớn interact with IL-6R/IL-6ST on B plasma and a subset of CD4-T cells, the CD4-naive/CM T cells (Figure 5 i,j). In combination with APRIL, IL-6 induces and supports long lived plasma cells, and is a potent inducer of IgA secretion in IgA committed plasma cells (Beagley et al. 1989; Hirano et al. 1986). Furthermore, IL-6 has been shown as a required factor for CD4 T cell memory formation, and for overcoming Treg mediated suppression (Nish et al. 2014). Salivary gland epithelial cells have been shown to induce CD4 T cell differentiation into Tfh cells in an IL-6 dependent manner (Gong et al. 2014), which induced proliferation of B cells. In this study, proliferation of B cells was also induced in co-culture only with salivary gland epithelial cells, suggesting additional T-independent mechanisms. IL-6 is upregulated in serum and bronchoalveolar lavage fluid in asthma and COPD patients, suggesting that the balance of IL-6 signaling in the SMG is important for disease (Mercedes Rincon 2012; Savelikhina et al. 2018; Tillie-Leblond et al. 1999).

In conclusion, we have identified the localisation of IgA plasma cells, naive/memory B cells và T cells at the SMG along with a large number of molecular signalling pathways involved in B lymphocyte recruitment, antigen presentation and both T cell-dependent và -independent maturation & survival. These pathways are known khổng lồ be functional in other secondary lymphoid organs, including within MALT, and we now show their possible involvement in establishing & maintaining the GALN (Figure 5k) of the lung.


Summary và Conclusions

We have produced a detailed annotation of the transcriptomes of cell types in the human lung; assessing their different locations along the tracheobronchial tree và parenchyma. Within the over 193,000 high chất lượng transcriptomes presented, we identify 77 cell types or states, including for the first time the transcriptomes of chondrocytes, peripheral nerve cells, and SMG duct cells as well as subtypes of Schwann cells, muscle và macrophages. Among the newly identified cell types we find specialised cell types expressing specific sets of chemokines within the fibroblast, smooth muscle and macrophage compartments. We also identify a novel IgA immune cell niche within the airway submucosal glands, which we term the gland associated lymphoid niche (GALN), with potential disease relevance.

The strength of this study comes from combining multiple complementary technologies: scRNAseq, scRNAseq, VDJ analysis và spatial transcriptomics. SnRNAseq, though more limited in the number of genes detected than scRNAseq, is not biased by enzymatic treatments & dissociation artefacts. This has allowed us to lớn define the transcriptomes of chondrocytes & perichondrial fibroblasts (PC-Fibro) và to separate rare cell types such as Schwann cell subsets và nerve-associated fibroblasts (NAFs). Visium ST has allowed us to lớn demonstrate the localisation of cell types within the tissue; confirming those already known (such as ciliated epithelial cells), those previously transcriptionally undefined such as chondrocytes, & entirely undescribed cell types in the human lung.

We characterise cell types that may cooperate lớn generate an immune niche at the SMG, finding signalling circuits also observed in lymph nodes, MALT and immunologically active tissues such as the gut, resulting in both T cell-dependent and independent B cell responses. We propose cell-cell interactions between SMG epithelial cells, including the SMG-Duct cells, CD4-T cells & B-naive, -memory and IgA secreting plasma cells, that we bản đồ to the SMG. The survival, maturation và potentially class switching of B-lineage cells are supported by APRIL and IL-6, expressed by SMG-Duct cells, providing T cell independent factors. Additionally, the SMG epithelial cells have the potential capacity to lớn induce T cell dependent immunity và B cell responses through expression of MHC-II và CD40. Further functional analysis will have khổng lồ investigate our findings, examine the roles of the T cells we detect, and test the function of SMG-Duct cells as professional APCs and in promoting class switch recombination và somatic hypermutation at these sites.

Many of the signalling pathways we described have been observed in other tissues và are particularly well described for the recruitment of IgA plasma cells to lớn the mammary gland & to the Peyer’s patches of the gut. No such secondary lymphoid structures or pathways within healthy lung tissue has been observed in the airways, but we postulate that the SMG microenvironment may fulfil a similar function.

Overall, the multi-omics data presented herein offer a comprehensive view of cell types and states within the human lung, with both macro- và micro-anatomical cell localisation information. We present new cell types with potential impact on a number of disease conditions both within & outside of the lung, and computationally analyse cellular interactions, advancing our understanding of lung composition và immunity. This comprehensive analysis has allowed us to take a systems approach that begins lớn define organ function as a result of the interactions between cells from distinct compartments. The interactions observed at the newly defined GALN may be relevant for other IgA secreting sites, such as mammary, salivary and tear glands.

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Our findings are likely to lớn be highly relevant lớn infectious disease biology, since IgA secretion is critical in combating infectious pathogens such as SARS-CoV-2 (Sterlin et al. 2021). We report higher proportions of IgA plasma cells in the airways of COVID-19 patients, supporting the importance of IgA immune niche. Nasal vaccines could induce a strong local sIgA response, yet all currently licenced COVID-19 vaccines are administered intramuscularly (Lund & Randall 2021). These vaccines are highly effective in preventing serious disease, but preclinical studies suggest that they provide little protection against viral replication và shedding in the upper airway (Bleier, Ramanathan, and Lane 2021; van Doremalen et al. 2021). Novel nasal vaccines are being developed that in non-human primates have shown promising prevention of replication và shedding of the virus due to the induction of a mucosal IgA response in the upper & lower respiratory tract (reviewed in (Tiboni, Casettari, và Illum 2021)). Whether the same is true in humans remains to be determined, but in COVID-19 patients, SARS-CoV-2 neutralisation was more closely correlated with IgA than IgM or IgG (Sterlin et al. 2021), và increased titres of IgA were observed in tears, nasal fluid & saliva (Cervia et al., n.d.) further highlighting the importance of the IgA immune niche in COVID-19 immunity. A better understanding of the mucosal IgA immune niche & the pathways that establish this niche, which we describe here, may offer options lớn augment this immune response.


Author Contributions

K.B.M and E.M. Conceived và designed the experiments; E.M., A.J.O., K.P., A.R.O., J.P.P., và N.H. Carried out computational analysis; V.K. Ran and optimised Cell2Location analysis.; A.W-C. Helped with experimental planning, sample management and spatial gene expression; L.M., L.B., A.K., E.P., A.H., & A.O. Carried out tissue dissociation và sc và snRNAseq experiments; M.D., L.T., S.P. & S.F.V. Performed Visium Spatial Transcriptomics và RNAScope analysis, supervised by M.P; N.R. Carried out IHC & protein staining; P.H. Và R.E. Contributed lớn cell types annotation; K.M., N.G., K.S-P provided human tissue samples; N.K. Carried out statistical analysis; O.A.B., M.C., O.S., S.A.T. Và K.B.M provided funding, discussion & supervision; & E.M., A.J.O., A.W-C and K.B.M wrote the manuscript.


Declaration of Interest

In the past three years, SAT has received remuneration for consulting and Scientific Advisory Board Membership from Genentech, Roche, Biogen, GlaxoSmithKline, Foresite Labs and Qiagen. SAT is a co-founder, board member and holds equity in Transition Bio.


Data availability

Sequencing data for scRNAseq, snRNAseq, VDJ-seq and Visium ST will be available via the DCP (http://data.humancellatlas.org). Sc/snRNAseq data will be available for browsing and gene expression data download via cellxgene website.


Supplementary legends

Figure S1. Overview of human lung dataset across five locations (a) H&E sections of the deep human tissue biopsies from multiple regions showing all major structures of the lungs and airways. (b) Expression of cell type marker genes in the master cell type groups, from both single cell & single nuclei RNAseq combined. (c) Protein staining of chondrocyte markers in the cartilage of human bronchus from the Human Protein Atlas. (d) Proportion of mesenchyme cell type groups in the airways from cells và nuclei. (e) UMAP of sequencing material (cells or nuclei) & location (trachea, bronchi, parenchyma). (f) Variance of ren expression explained by metadata variables in the combined sc/snRNA-seq dataset, scRNA-seq and snRNA-seq datasets.

Figure S2. Overview of Spatial Transcriptomics slides used in the study. H&E staining as well as the number of UMI counts per spot are visualised for each section. RNA-seq sample names match those in Supplementary Table 3.

Figure S3: Novel fibroblast subsets (a) Dot plot of marker gen expression for indicated cell types. (b) UMAP of location và sequencing material from fibroblasts. (c) Heatmap showing annotated cell types to lớn the predicted labels for fibroblasts from Travaglini et al. (Travaglini et al. 2020) by the Azimuth tool, colored by proportion. Labels by the proportion of annotated cells and the total number of cells mapping to the reference. (d) Violin plots with predicted annotation score for each of the annotated cell types to lớn the reference. Small dots represent cells, circles represent mean values and bars show standard deviation.

Figure S4: Validation of immune recruiting fibroblasts & their tissue localisation. (a) smFISH staining in human bronchi tissue for IR-Fibro markers (CCL21, CCL19) showing independent localisation from immune cells (PTPR) và smooth muscle cells (ACTA2). (b) H&E staining on Visium ST with manually annotated regions for the immune infiltrate in blue. Cell2location mapping density scores with zoom into the region of interest, showing mật độ trùng lặp từ khóa values for IR-Fibro & relevant immune cells from the current lung study as well as for germinal center cell types from a gut dataset (R. Elmentaite et al. 2021). Dashed lines are added for better visual comparison between the cell types and regions.

Figure S5: Peribronchial & perichondrial fibroblasts. (a) Protein staining of PB-Fibro markers (COL15A & ENTPD1) in human bronchus sections from the Human Protein Atlas. (b) Marker genes for PB-fibro & PC-fibro. (c) Protein staining of PC-Fibro marker (COL12A1) in human bronchus from the Human Protein Atlas mapping to cartilage. (d) UMAP of adventitial fibroblasts, PC-fibro and chondrocytes from single nuclei data colored by monocle 3 pseudotime & cell type. (e) Expression of genes associated with bone/cartilage function, markers of PC-fibro and cartilage genes in the nuclei as shown on (d), ordered by pseudotime. (f) PC-fibro marker ren enrichment in Human Phenotype Ontology by g:Profiler.

Figure S6. Schwann cells & nerve-associated fibroblasts (NAF). (a) Marker dot plot for myelinating, non-myelinating Scwhann cells và for epi- and endoneurial NAF-s. (b) g:Profiler enrichment results for myelinating Schwann cell markers with detailed results for myelination và transcription factor EVX1. (c) g:Profiler enrichment results for non-myelinating Schwann cell markers. (d) Expression in Transcript per million (TPM) of NAF markers in GTEx bulk RNA-seq data. (e) Visium ST H&E staining of human bronchi, with enlarged nerve bundle and Cell2location cell type mapping mật độ trùng lặp từ khóa scores for Schwann & NAF cell types. (f-h) Human Protein Atlas antibody staining of (f) non-myelinating Schwann cell markers (CADM, GRIK2, NCAM1, ITGB4 và L1CAM) (g) endoneurial NAF marker (USP54) and (h) epineurial NAF markers (SLC22A3 và SORBS1) within the nerve bundles in human bronchus. Arrows indicate nerve bundles. (i) RNAscope staining for myelinating (MLIP) and non-myelinating (SCN7A, SOX10) Schwann cell and epineurial (SLC2A1) NAF specific genes in bronchial nerves. (j) Expression of neuropathy associated genes in Schwann and NAF cell types. Previously unknown cell type specific expression shown in color: light green for novel expression pattern, light blue for distinguishing expression for nmSchwann cells.

Figure S7. Vascular & smooth muscle cell types. (a) Markers dot plot for vascular endothelia. (b) Bronchi section with H&E and Cell2location analysis mật độ trùng lặp từ khóa score for airway smooth muscle population on a Visium ST slide. (c) NPR2 staining in oesophagus & bronchus from the Human Protein Atlas. Black arrows indicate the airway and oesophagus surrounding non-vascular smooth muscle. (d) ASM marker expression in all GTEX tissues. Tissues are ordered by unsupervised clustering based on expression similarity. The dotted line highlights tissues which are surrounded by a thick smooth muscle layer. The orange rectangle shows muscular tissues from oesophagus, & the xanh rectangle shows the non-muscular mucous layer of oesophagus tissue. (e) Cell2location density scores of pulmonary and vascular endothelium for parenchyma & bronchi Visium ST sections. (f) IR-Ven-peri markers localise at the venous vessels in the airway. SmFISH staining for IR-Ven-peri (CCL21, CCL19), venous endothelia (ACKR1) & smooth muscle (ACTA2) markers. (g) Leukocyte rolling and homing genes, and chemokines expressed in Endothelia và Perivascular cells together with their interaction partners expression in immune cell groups. Interaction partners are indicated with xanh shades.

Figure S8. Epithelial cell annotations and location specific ciliated cell gene expression. (a) Marker gene expression dot plot for epithelial cells. (b) UMAP of epithelial cells (excluding AT1 & AT2 cells) from scRNAseq data. (c) RNA velocity results on UMAP plot for single cells from airway epithelia, with colors indicating cell types as in (b). (d) Cell type proportion analysis with fold changes and Local True Sign Rate (LTRS) score for all cell type groups with regards lớn location, donor, sequencing material and dissociation protocol. (e) smFISH staining for mucous (MUC5B), serous (LPO) & duct (MIA / ALDH1A3 / RARRES1) cell markers in human bronchus section. (f) smFISH staining of secretory goblet/club (SCGB1A1), ciliated (FOXJ1) & duct (ALDH1A3 / RARRES1) cells in human bronchus section. (g) smFISH staining for muscle (TAGLN), basal epithelia (KRT14), duct (ALDH1A3) and myoepithelium (FHOD3) cell type markers in human bronchus section. (h) H&E from bronchial section và Cell2location mật độ trùng lặp từ khóa values for mapping duct, mucous, serous, ciliated and myoepithelial cells onto the Visium ST section.(i) Linear mixed mã sản phẩm analysis revealed 80 differentially expressed genes in ciliated cells between trachea & other locations (bronchi and parenchyma). Violin plots of normalised log-transformed expression separated by location in the single nuclei RNA-seq data for three representative genes upregulated in nasopharyngeal carcinoma gen set from GSEA database with LTSR>0.9 consistently higher expressed in the trachea. (j) SARS-CoV-2 receptor và viral entry ren expression in airway epithelial cells, with expression levels of ACE-2 in the ciliated cells from snRNAseq data shown by location in a violin plot.

Figure S9. Immune cell type groups. (a) Marker genes dot plot for myeloid cells. (b) Marker genes dot plot for T&NK cells. (c) UMAP for Megakaryocytes and Mast cells along with marker gen expression dot plot. (d) Cell2Location density scores for CD8-TRM, Ciliated and CD8-EM cell types in human bronchi sections and corresponding H&E. (e) Fraction of clonally expanded cells in T và NKT cell types from VDJ data. (f) Proportion of shared TCR clonotypes between samples from VDJ data. Color bars indicate location và donor. (g) Effect of location, donor, material and protocol on immune cell type proportions. Cell type proportion analysis with fold changes & Local True Sign Rate (LTRS) score for myeloid cell types, T & NK cell types and B lineage cell types.

Figure S10. Additional B cell data (a) Marker ren expression dot plot for B-lineage cells. (c, d) Human Protein Atlas staining for B plasma marker MZB1 in the bronchus (c) nasopharyngeal glands (d). (e) Number of B lineage cells with different Ig isotypes in parenchyma from the analysis of VDJ amplified libraries. (f) Multiplex IHC of human trachea for Ig isotypes showing distinction between glands and non-gland regions of tissue (g) Violin plot for expression of AICDA in B cell subsets.

Supplementary tệp tin 1. Cell type marker genes.

Marker genes for all the described cell types.

Supplementary Table 1. Sample & donor info for single-cell RNA-seq.

Sample ID-s and corresponding location, spatial code, material of cells/nuclei, protocol, enrichment & dissociation notes, Donor ID-s with age, BMI, gender và smoking history if available, 10x version, gen expression sequencing run ID & corresponding BCR và TCR sample ID-s for single cell RNA-seq samples.

Supplementary Table 2. Sample info for single-nuclei RNA-seq.

Sample ID-s và corresponding information about pooling, donors, location, protocol and 10x version for single nuclei RNA-seq samples.

Supplementary Table 3. Sample info for Visium Spatial Transcriptomics.

Sample & image ID-s, location & donor information, permeabilization time and Visium slide ID for Visium ST samples.

Supplementary Table 4. Manual annotation of tissue regions on Visium ST. Manual annotation indicates presence (y) of various tissue regions on every Visium ST samples: Airway Smooth Muscle, Arterial vessel, Cartilage, Glands, Mesothelium, Multilayer epithelium, Nerve, Parenchyma, Perichondrium, Pulmonary vessel, Small airway, Venous vessel, iBALT-like immune infiltrate. The annotations on the tissue regions can be seen as categories on the accompanying loupe files stored in DCP.

Supplementary Table 5. Antibody information for IBEX staining. Staining cycle, antibody protein names, clone, conjugate, Vendor, catalog number and dilution used.


Chuyên mục: Tin Tức