Persistent pneumococcal colonisation in antiretroviral-treated HIV infection is associated with nasal inflammation

Domain: biology
Published: 2025-12-15
Editorial outcome: major_revision

Abstract
Despite systemic viral suppression, people living with HIV (PLHIV) on antiretroviral therapy (ART) remain highly susceptible to pneumococcal colonisation and disease. Here, we show that long-term ART does not restore nasal mucosal immunity. Using flow cytometry, single-cell transcriptomics, and neutrophil functional assays, we identify a persistent mucosal immune signature in PLHIV-ART > 1 yr marked by epithelial-driven neutrophilic inflammation, T cell exhaustion, and cellular senescence. Neutrophils exhibit mitochondrial stress, senescence-associated secretory phenotype (SASP) gene expression, and impaired oxidative burst, particularly in individuals with pneumococcal carriage. Epithelial cells express elevated neutrophil-recruiting ligand genes, while nasal T cells display pro-apoptotic and exhaustion gene profiles. Neutrophilic inflammation is strongly associated with pneumococcal carriage density, implicating a feed forward loop between inflammation and microbial persistence. Our findings reveal tissue-specific immune dysregulation despite ART and suggest that targeting epithelial-immune signalling or neutrophil senescence may offer novel therapeutic avenues to reduce respiratory pathogen burden in PLHIV.

Introduction
People living with HIV (PLHIV) remain at an elevated risk of respiratory infections, including Streptococcus pneumoniae (S. pneumoniae), despite long-term antiretroviral therapy (ART) and viral suppression 1–4. S. pneumoniae continues to be a leading cause of morbidity and mortality in PLHIV on suppressive ART, with studies showing a 30–100-fold increased risk of invasive pneumococcal disease, alongside a 5-fold increase in mortality in PLHIV on suppressive ART than HIV-uninfected 5–8. In addition, nasopharyngeal carriage is more frequent and persistent in PLHIV on suppressive ART than in HIV-uninfected individuals 3. Pneumococcal carriage is a prerequisite for pneumococcal disease 9. These patterns suggest that immune reconstitution under ART may be incomplete, particularly at mucosal surfaces where pathogen colonisation initiates.

While ART is known to restore peripheral CD4+ T-cell counts 10,11 and reduce systemic immune activation 12, its effects on local immunity at the upper respiratory tract mucosa remain poorly understood. The nasal mucosa, the primary site of pneumococcal colonisation, plays a critical role in host-pathogen interactions 13–15. However, a limited number of studies have characterised immune cell composition, epithelial-immune interactions, or functional mucosal responses in this tissue in the context of HIV.

Evidence from viral infection studies and controlled human HIV-infection models have shown that mucosal inflammation can enhance pneumococcal acquisition and persistence 16–18. Neutrophils as among the predominant innate immune cells in the nasal mucosa 19,20, are key to controlling colonisation 21,22. However their recruitment and function are tightly regulated by epithelial cues 23–25 and their dysregulation could impair mucosal defence. Whether HIV infection alters this epithelial-neutrophil axis and whether such changes persist despite ART remain open questions.

To address this knowledge gap we investigated the upper respiratory mucosal immune landscape in HIV-uninfected adults and PLHIV at different stages of ART. We applied multiparameter flow cytometry single-cell transcriptomics and neutrophil functional profiling to evaluate immune cell composition, epithelial-immune communication and their relationship with pneumococcal carriage. This study aims to define how HIV and ART shape nasal immunity and to identify mechanisms that may underlie persistent pneumococcal colonisation susceptibility in PLHIV on long-term ART.

Results
Cohort characteristics and sampling
We recruited 132 adults in Blantyre, Malawi. The cohort comprised 37 PLHIV within 3 months of ART initiation (PLHIV-ART < 3 months) and 49 PLHIV on ART for over 1 year (PLHIV-ART > 1 year), both enroled from Gateway Voluntary Counselling and Testing Centre and Lighthouse ART Clinic. In addition, we recruited 46 HIV-uninfected adults (HIV-adults) from Gateway Voluntary Counselling and Testing Centre and surrounding communities in Blantyre through our community engagement work (Fig. 1a). Nasal mucosal cells, nasal lining fluid and peripheral blood were collected from all participants.

Baseline characteristics, including median age, sex distribution and number of under-five children per household, were comparable across study groups (Table 1). Socioeconomic status (SES) was higher among HIV-adults compared to PLHIV groups, although no significant SES difference was noted between PLHIV-ART < 3 months and PLHIV-ART > 1 year (Table 1). Among PLHIV, the median duration of ART was 1 month (IQR; 0, 1) for PLHIV-ART < 3 months and 5.7 (IQR; 3.1, 9.25) years for PLHIV-ART > 1 year. Median peripheral CD4+ T-cell counts were 475 cells/μl (IQR; 285 cells/μl, 674 cells/μl) and 512 cells/μl (IQR; 366 cells/μl, 671 cells/μl) for PLHIV-ART < 3 months and PLHIV-ART > 1 year, respectively. Detectable plasma viral load was observed in 24% (9/37) of PLHIV-ART < 3 months and 10% (5/49) of PLHIV-ART > 1 year (Table 1).

HIV alters nasal immune cell composition despite long-term ART
To investigate the impact of HIV on upper respiratory tract mucosal immunity, we performed flow cytometry for profiling of nasal cells collected using nasal curettes from HIV-adults, PLHIV-ART < 3 months and PLHIV-ART > 1 year (Fig. 1a). In HIV-adults, the nasal mucosa was predominantly populated by CD66b+ neutrophils and CD3+ T cells, with a smaller proportion of CD14+ monocytes (Fig. 1b and Supplementary Fig. S1a). Neutrophil abundance was significantly higher in PLHIV-ART > 1 year compared to HIV-adults, but only marginally higher compared to PLHIV-ART < 3 months, however, this was not statistically significant (Fig. 1c). Monocyte levels were comparable across all cohorts (Fig. 1d). Subset analysis of lymphocyte populations revealed a lower proportion of CD4+ T cells in PLHIV-ART < 3 months relative to HIV-adults and PLHIV-ART > 1 year participants, with the latter two groups showing similar levels (Fig. 1e and Supplementary Fig. S1b). There were no significant differences observed in the proportions of CD8+ T cells, mucosal-associated invariant T (MAIT) cells (CD3+ CD161++ TCRVα7.2+), or γδ T cells (CD3+ TCRγδ+) across study groups (Fig. 1f–h). On the other hand, natural killer T (NKT) cells were higher in PLHIV-ART > 1 year compared to PLHIV-ART < 3 months, but not significantly different from HIV-adults (Fig. 1i). These findings indicate persistent perturbations in nasal immune cell composition among PLHIV on long-term ART, particularly involving neutrophil accumulation.

Activated nasal neutrophils accumulate in PLHIV despite long-term ART
Given the enrichment of nasal CD66b+ neutrophils in PLHIV-ART > 1 year, we next assessed their activation (CD11b, CD62L) 26, maturation (CD10) 27 and granule content, tissue residency and maturity (CD63) 28 profiles using multiparameter flow cytometry. Uniform Manifold Approximation and Projection (UMAP) of immune cells from matched peripheral blood and nasal samples revealed eight clusters, four of which were CD66b+ neutrophil subsets (Fig. 2a). Clusters 4 (CD11b+ CD10- CD63+ CD62L- CD14-) and 6 (CD11b+ CD10+ CD63+ CD62L+ CD14-) were predominantly observed in blood, while cluster 7 (CD11b+ CD10+ CD63- CD62L- CD14-), representing activated mature neutrophils, was enriched in the nasal mucosa. Cluster 7 abundance was elevated in the nasal mucosa of both PLHIV-ART < 3 months and PLHIV-ART > 1 year compared to HIV-adults (Fig. 2a). This was corroborated by conventional gating on an expanded cohort, which showed significantly higher frequencies of CD66b+ CD11b++ neutrophils in PLHIV-ART > 1 year than in HIV-adults (Fig. 2b). These cells strongly correlated with the UMAP-identified cluster 7 phenotype (Supplementary Fig. S2a), confirming population overlap.

To assess neutrophil-associated inflammation we collected nasal lining fluid using nasosorption filters and measured nasal myeloperoxidase (MPO) levels, which were significantly elevated in PLHIV-ART > 1 year relative to HIV-adults (Fig. 2c). MPO levels correlated with nasal CD66b+ neutrophil abundance (Fig. 2d) but not with nasal monocyte abundance (Fig. 2e), implicating neutrophils as the primary MPO source. However, despite elevated neutrophil abundance, nasal concentrations of proinflammatory cytokines and chemokines, including TNF-α, IL-6, IL-8, IL-1β, IFN-γ, IL-2, IL-12p70, IL-13, IL-4 and IL-10, did not differ significantly across study groups (Supplementary Fig. S2b–k). Correlation matrices further revealed that in HIV-adults, neutrophil chemoattractants (IL-8, IL-1β, TNF-α and IL-6) were positively associated with nasal neutrophil abundance (Fig. 2f), whereas these associations were lost in the PLHIV groups (Fig. 2g, h), suggesting dysregulation of neutrophil recruitment pathways. Altogether, these findings indicate neutrophilic inflammation and activation in the nasal mucosa of PLHIV-ART > 1 year, characterised by high neutrophil abundance and high levels of MPO.

Airway epithelial-neutrophil crosstalk is amplified in PLHIV on long-term ART
To investigate the molecular pathways contributing to nasal neutrophilia in PLHIV-ART > 1 year, we performed single-cell RNA sequencing (scRNA-seq) on nasal cells from 3 HIV-adults, 3 PLHIV-ART < 3 months and 5 PLHIV-ART > 1 year from the same cohort (Fig. 3a and Supplementary Table S1). All individuals were asymptomatic and tested negative for common respiratory viruses. Plasma and nasal lining fluid HIV viral loads were undetectable in all PLHIV participants, except in the plasma of one PLHIV-ART < 3 months. Using the 10x Genomics 5′ platform, we generated scRNA-seq libraries from freshly isolated viable nasal cells, yielding 22,119 cells that passed quality control. Dimensionality reduction using UMAP identified 11 major transcriptional clusters (Fig. 3c), which were annotated by canonical gene expression and validated through projection onto the Human Cell Atlas using SingleR and Azimuth 29–31. The epithelial compartment included goblet cells (CYP2F1, SERPINB3, MUC5AC, SPDEF and VMO1), secretory cells (SERPINB3, VMO1 and MUC5AC low), basal cells (CYP2F1 and SERPINB3 high), ciliated cells (CAPS, CFAP157, DNAF1 and FOXJ1), squamous cells (SPRR3, SPRR2A and KRT4), Ionocytes, a newly identified epithelial cell type responsible for regulating ion transport and osmotic regulation (CFTR, SCNN1B and RARRES2) and deuterosomal cells, a transient, intermediate airway epithelial cells that serve as precursors to multiciliated cells (CDC20B, CCNO and MSMB). The immune clusters comprised neutrophils (SRGN, CSF3R, GOS2 and CXCL8), T cells (CD3E, CD3D, CD8A and PTPRC), B cells (PTPRC, CD79A, MS4A1 and CD19), monocytes/macrophages (TYROBP, HLA-DPA1 and HLA-DPB1) and dendritic cells (CD83, CD86, LYZ and FCER1G). Further sub-clustering of the 4099 immune cells revealed nine subsets: CD8+ T cells, NKT cells, B cells, plasma cells, neutrophils, monocytes, macrophages, dendritic cells and mast cells (Fig. 3d). Consistent with flow cytometry findings (Figs. 1c and 2d), we observed a higher abundance of neutrophils in the nasal mucosa of PLHIV-ART > 1 year compared to HIV-adults (Fig. 3e, f).

Epithelial cues are known to regulate neutrophil recruitment 23–25. To determine which epithelial-immune interactions may be driving this neutrophilic response, we performed cell-to-cell communication inference using Multinichenet 32. In PLHIV-ART > 1 year, epithelial-neutrophil interactions were significantly expanded relative to HIV-adults and PLHIV-ART < 3 months (Fig. 4a). Notably, PLHIV-ART > 1 year showed strong ligand-receptor signalling pathways associated with neutrophil recruitment, including CXCL1-CXCR1, MIF-CD44 and ADGRE5-CD55, originating from basal, secretory, goblet, squamous and ciliated epithelial subsets (Fig. 4a). Gene set scores for these prioritised interactions were elevated in all epithelial subsets of PLHIV-ART > 1 year compared to HIV-adults and were also higher than in PLHIV-ART < 3 months across all epithelial subsets except squamous cells (Fig. 4b–f). In PLHIV-ART < 3 months, distinct ligand-receptor pairs predominated, including ICAM1-ITGAX/ITGB2, ICAM1-MSN, ICAM1-IL2RG and BST2-LILRA5, which also involved major epithelial subsets and neutrophils (Fig. 4a). In contrast, epithelial-neutrophil interactions were sparse in HIV-adults and primarily mediated by MFAP2-NOTCH1 signalling between basal and secretory cells (Fig. 4a). Additional analysis of immune cell-neutrophil interactions in PLHIV-ART > 1 year revealed enriched signalling pathways including CXCL1-CXCR1, IL-1β-IL-1R2 and IL-18-IL18RAP, predominantly involving neutrophils, macrophages and dendritic cells (Supplementary Fig. S3). In contrast, PLHIV-ART < 3 months exhibited distinct ligand-receptor interactions, including ICAM1-IL2RG and TNF-TNFRSF1A, primarily associated with neutrophils and T cells, while in HIV-adults, these interactions involved IL-17A-IL17RA, DLK2-NOTCH and MFNG-NOTCH1, involving NKT cells and dendritic cells (Supplementary Fig. S3). Collectively, these findings suggest that airway epithelial cells likely contribute to neutrophil recruitment and activation in the nasal mucosa of PLHIV-ART > 1 year.

Nasal neutrophils in PLHIV-ART > 1 year exhibit transcriptional signatures of stress and senescence
To dissect the transcriptional changes underlying neutrophilic inflammation, we performed differential gene expression analysis on nasal neutrophils using the Model-based analysis of single-cell transcriptomics (MAST) pipeline 33. In PLHIV-ART > 1 year, neutrophils showed upregulation of mitochondrial stress-associated genes, including MT-ND4, MT-CO1, LYPD2, PRDX1, MSMB and WFDC2, compared to HIV-adults (Fig. 5a and Supplementary Data 1). In contrast, neutrophils from PLHIV-ART < 3 months exhibited elevated expression of antiviral response genes, including IFITM1, IFITM3, IRF7 and XAF1, relative to HIV-adults (Fig. 5b and Supplementary Data 1). When comparing PLHIV-ART > 1 year to PLHIV-ART < 3 months, mitochondrial stress genes such as MT-CO1, MT-ND6, MT-ND5 and PRDX1 remained upregulated in the former, while antiviral response genes, including IFITM1, IFIT2, ISG15, IRF7 and IL1B, were elevated in the latter (Fig. 5c and Supplementary Data 1).

To further interrogate gene expression patterns, we employed CEMiTool 34 to identify co-expressed gene modules enriched in neutrophils across the study groups. Two modules were uniquely enriched, module M1 in PLHIV-ART > 1 year and module M2 in PLHIV-ART < 3 months (Fig. 5d). Over-representation analysis of M1 revealed enrichment in pathways linked to homoeostatic regulation and the Senescence-Associated Secretory Phenotype (SASP) (Fig. 5e; Supplementary Fig. S4a and Supplementary Data 2), while M2 was enriched for pathways involved in cytokine signalling, interferon response, antigen presentation and immunoregulatory interactions (Fig. 5f; Supplementary Fig. S4b and Supplementary Data 2). Moreover, SASP pathway gene module scores were significantly higher in neutrophils from both PLHIV-ART > 1 year and PLHIV-ART < 3 months compared to HIV-adults (Fig. 5g and Supplementary Fig. S4c), indicating persistent inflammatory signalling. In contrast, module scores for genes involved in interferon signalling, Nef-mediated HIV replication inhibition and MHC class I antigen presentation were markedly higher in PLHIV-ART < 3 months compared to both HIV-adults and PLHIV-ART > 1 year (Fig. 5h–j and Supplementary Fig. S4c), consistent with active antiviral responses during early ART.

Furthermore, based on the premise that the neutrophils in the nasal mucosa were likely recruited from the blood, we evaluated the functional competence of blood neutrophils, assessing phagocytosis and oxidative burst in the three study groups using our in-house published bead-based assay 35–37. The phagocytic capacity of blood neutrophils was comparable across the study groups (Fig. 5k). In contrast, neutrophil oxidative burst capacity was significantly lower in both PLHIV-ART > 1 year and PLHIV-ART < 3 months relative to HIV-adults (Fig. 5i), suggesting potential impairment in killing capacity. Together, these data indicate that nasal neutrophils from PLHIV-ART > 1 year adopt a transcriptional profile marked by cellular stress and senescence, indicating inflammaging despite virological suppression.

Nasal T cells in PLHIV on long-term ART exhibit transcriptional signatures of exhaustion, senescence and apoptosis
Given that chronic inflammation can drive T cell exhaustion and senescence 38, we hypothesised that neutrophilic inflammation in PLHIV-ART > 1 year is associated with altered T cell function. Differential gene expression analysis revealed that nasal T cells from PLHIV-ART > 1 year exhibited upregulation of immune activation genes (HLA-B, HLA-DQA1 and TRAV6), chemokine genes (CXCR4, CCL4 and CCL3) and ageing-associated genes (FKBP5, HMGB2 and BTG1) compared to HIV-adults (Fig. 6a and Supplementary Data 1). In PLHIV-ART < 3 months, nasal T cells showed elevated expression of cytotoxicity-associated genes (GZMH, GNLY, GZMB and NKG7) and immune activation genes (LAG3, HLA-DQA1, HLA-A, IRF1 and STAT1) relative to HIV-adults (Fig. 6b and Supplementary Data 1). Notably, TRAV6, CXCR4 and FKBP5 remained significantly upregulated in PLHIV-ART > 1 year compared to PLHIV-ART < 3 months (Fig. 6c and Supplementary Data 1), suggesting persistent transcriptional changes with long-term ART.

Gene co-expression module analysis using CEMiTool identified distinct modules enriched in each PLHIV group. The M1 module, enriched in PLHIV-ART > 1 year, was associated with pathways related to apoptosis and cell-to-cell communication (Fig. 6d, e; Supplementary Fig. S5a and Supplementary Data 2), while the M2 module, enriched in PLHIV-ART < 3 months, highlighted pathways involved in antigen presentation and immunoregulation (Fig. 6f; Supplementary Fig. S5b and Supplementary Data 2). Geneset scoring further revealed that exhaustion and senescence-associated genes (S100A10, PDCL3, CTLA4, PDCD7, PDCD5, LAG3, KLRG1, TIGIT, CDKN1A and NR4A1) were more highly expressed in T cells from both PLHIV-ART > 1 year and PLHIV-ART < 3 months compared to HIV-adults (Fig. 6g). Similarly, activation-related genes (STAT1, IRF4, HLA-DRA, HLA-DRB1, JUN, GZMB and FOS) were elevated in both PLHIV groups (Fig. 6h, i), indicating ongoing T cell activation.

Considering that chronic T cell activation results in activation-induced cell death 39, we explored T cell death pathways by examining intrinsic and extrinsic apoptosis-associated gene sets. The intrinsic apoptosis gene set (BCL2, BAK, CASP3, CASP8, TNFRSF1A, TP53, BCL2L11, APAF1 and NFKB1) showed higher module scores in PLHIV-ART > 1 year compared to PLHIV-ART < 3 months, while no significant differences were observed for the extrinsic apoptosis gene set (FAS, TNFRSF1A, TNFRSF10A and TNFRSF10B) (Fig. 6j). Taken together, these findings suggest that nasal T cells from PLHIV-ART > 1 year are transcriptionally programmed toward heightened immune activation, exhaustion and intrinsic apoptotic susceptibility.

Neutrophilic inflammation is associated with pneumococcal carriage in PLHIV on long-term ART
Next, we investigated whether persistent neutrophilic inflammation in PLHIV-ART > 1 year is linked to increased susceptibility to pneumococcal carriage. Among PLHIV-ART > 1 year, neutrophil abundance was significantly higher in individuals with pneumococcal carriage compared to those without (Fig. 7a). Monocyte abundance followed a similar pattern, with elevated levels in carriage-positive individuals within the same group (Fig. 7b). In contrast, no significant differences in neutrophil or monocyte abundance were observed between carriage-positive and carriage-negative individuals among HIV-adults or PLHIV-ART < 3 months (Fig. 7a, b).

Further, we found that the proportion of activated nasal CD11b++ neutrophils negatively correlated with pneumococcal carriage density in PLHIV-ART > 1 year, suggesting a potential contribution to carriage density control without clearance (Fig. 7c). No such correlations were observed in the HIV-adults or PLHIV-ART < 3 months groups. Monocyte abundance did not correlate with carriage density in any group (Fig. 7d). Using blood neutrophils as a surrogate of infiltrating nasal neutrophil functional capacity, we observed that the phagocytic capacity was similar regardless of carriage status across all groups (Fig. 7e), but the neutrophil oxidative burst capacity was significantly lower in carriage-positive PLHIV-ART > 1 year compared to their carriage-negative counterparts (Fig. 7f). This impaired neutrophil oxidative burst capacity was not observed in HIV-adults or PLHIV-ART < 3 months. Collectively, these data support an association between persistent nasal neutrophilic inflammation, functional impairment and potential increased susceptibility to pneumococcal carriage in PLHIV-ART > 1 year.

Methods
Study design
The study was a cross-sectional observational cohort design, conducted between September 2021 and December 2023 and aimed to assess upper airway mucosal immune responses in PLHIV at different stages of ART. Healthy adults aged 18–45 years were recruited from Queen Elizabeth Central Hospital Lighthouse HIV Clinic and Blantyre District Office Gateway Clinic in Blantyre, Malawi, during routine HIV or ART clinics and from surrounding communities following community engagement activities. Participants were stratified into three groups: (1) HIV-uninfected adults, (2) PLHIV on ART for less than 3 months (PLHIV-ART < 3 months) and (3) PLHIV on ART for more than 1 year (PLHIV-ART > 1 year). HIV status for PLHIV on ART was self-reported and confirmed in the health passport book (a personal health record), for the HIV-uninfected individuals, this was confirmed using a standard HIV rapid test protocol (2 independent rapid tests). ART duration and regimen were confirmed using official clinic records and ART adherence was confirmed via official clinic pharmacy refill records. In addition, viral control was confirmed using plasma viral load suppression. Exclusion criteria included any signs or symptoms of acute illness, chronic medical conditions, active SARS-CoV-2 infection using polymerase chain reaction (PCR), or self-reported SARS-CoV-2 infection within the preceding 14 days. Participants were screened in accordance with local clinical protocols.

Nasal sample collection
Nasal cells were collected by gently scraping the nasal inferior turbinate using curettes (Rhino-Pro, Arlington Scientific). Two curettes per nostril were transferred into cold RPMI 1640 medium supplemented with 10% Fetal Bovine Serum (Sigma-Aldrich), 1% HEPES (Fisher Scientific) and 1% Penicillin and Streptomycin (Fisher Scientific), transported on ice and processed within 30 min. All samples with visible blood or mucus contamination were excluded from the analysis. For flow cytometry analysis, cells were dislodged by pipetting liquid up and down the tip of the curette, centrifuged at 500 × g for 10 min at 4°C. The supernatant was completely removed and cells were resuspended in 500 µl of PBS (Fisher Scientific). Nasal lining fluid was collected using a synthetic absorptive matrix (Hunt Development (UK) ltd) and eluted with 200 μL PBS (Fisher Scientific), then centrifuged at 1500 × g for 10 min. The eluate was stored at -80°C until the day of the analysis. The full list of reagents has been provided in Supplementary Table S2.

Flow cytometry and immunophenotyping
Dislodged nasal cells were centrifuged (500 × g, 5 min), resuspended in PBS and stained with Far Red viability dye (1:500) (Thermo Fisher Scientific) and a panel of fluorochrome-conjugated antibodies. Antibodies included markers for lymphocytes (CD3, CD4, CD8, CD56, CD161, TCRvα7.2 and TCRγδ), neutrophils (CD66b, CD63, CD10, CD11b and CD62L), monocytes (CD14) and epithelial cells (EpCAM). Cells and compensation tubes were acquired using a BD LSRFORTESSA™ cytometer (BD Biosciences). A minimum of 50,000 total events was acquired per sample and FlowJo v10.10.0 (BD Biosciences) was used for analysis. The full list of reagents has been provided in Supplementary Table S2.

Ex vivo neutrophil bead-based phagocytosis and oxidation assay
We adapted a previously described bead-based assay to assess the phagocytosis and oxidative capacity of peripheral blood neutrophils 35,37. The assay uses silica beads derivatised with a calibration fluorochrome (Alexa 405-SE) and the fluorogenic reporter substrate Oxyburst Green, succinimidyl ester (OGSE) (Molecular Probes, Eugene, OR) to measure superoxide burst. When the beads are internalised by neutrophils, they gain fluorescence intensity proportional to the degree of oxidative burst activity in the phagosome. In brief, 100 μL of peripheral blood was stimulated with 10 ng/mL LPS and co-incubated with 120 μL of IgG-coated silica beads. Samples were incubated in the dark at 37°C for 45 min on a shaker at 250 rpm. The samples were then washed with 500 μL pf PBS to remove the unphagocytosed beads. The supernatant was carefully discarded and samples were stained with live/dead amine-reactive dye for 15 min in the dark, followed by staining with a cocktail of fluorochrome-conjugated antibodies (CD45 PerCP/Cy5.5, CD66b PE and CD16 PE/Cy7; all from Biolegend). Red blood cells were lysed with 2 mL of 1X BD FACS Lysing Solution and samples were washed twice with 500 μL of PBS. Samples were resuspended in FACS buffer and analysed using a BD LSRFortessa™ flow cytometer equipped with FACSDiva software version 8 (BD Biosciences). Data were processed using FlowJo version 10.10.0 (BD Biosciences). The Phagocytic Index was calculated by multiplying the proportion of Alexa 405+ cells with a median fluorescence intensity of Alexa 405, while the Oxidative Index was calculated by multiplying the proportion of OGSE+ cells with a median fluorescence intensity of OGSE.

Streptococcus pneumoniae culture and quantitation
Nasopharyngeal swabs were tested for the presence of S. pneumoniae using World Health Organisation standardised microbiological culture 3,69. Briefly 20 μL of the sample was diluted in a 1:10 dilution using sterile PBS and plated on sheep blood agar (SBG) with gentamicin. The plates were incubated overnight at 37°C in 5% CO2. Pneumococcal isolates were identified by their colony morphology (alpha-haemolytic on blood agar) and optochin disc susceptibility (Oxoid). Isolates with no or intermediate resistance (zone diameter ≥ 14 mm) to optochin were further confirmed using the bile solubility test. Individuals positive for S. pneumoniae were designated as carriage positive, while those without were designated as carriage negative. Pneumococcal density was determined by serial sample dilution 3,69,70 culture on SBG and reported as colony-forming units per millilitre.

Multiplex cytokine assay
Proinflammatory cytokines (IFN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13 and TNF-α) were quantified in nasal lining fluid using a Mesoscale Discovery 10-plex immunoassay. Following blocking and incubation, plates were washed and developed with SULFO-TAG detection antibodies. Signals were read using MESO® QuickPlex SQ 120 MM. Assay details followed the manufacturer’s instructions. Samples below the assay detection limit were given the minimum value for that specific target.

RT-qPCR for detection of respiratory viruses
For respiratory virus detection, nucleic acid was extracted from 50 µL of nasal lining fluid samples using the QIAamp Viral RNA Mini Kit (Qiagen, Germany), following a column-based protocol. The process included lysis with Buffer AVL, ethanol precipitation, binding to silica columns, washing with AW1 and AW2 buffers and elution with 50 µL of Buffer. Respiratory viruses were detected using reverse transcription qPCR (RT-qPCR) targeting the following: respiratory syncytial virus, influenza A virus, HRV, influenza B virus, parainfluenza virus types 1–4 (HPIV), human metapneumovirus, adenovirus, enterovirus and human bocavirus. Reactions were conducted using Luna Universal Probe one-step RT-qPCR Kit (New England Biolabs, E3006S) in a 20 µL volume, with 5 µL of extracted viral RNA/DNA. Cycling conditions were 52°C for 10 min, 95°C for 2 min, followed by 45 cycles of 95°C for 10 s and 55°C for 30 s. Viral positivity was defined as Ct < 38. Positive and negative controls were included in each run.

Myeloperoxidase (MPO) enzyme-linked immunosorbent assay (ELISA)
MPO levels in nasal lining fluid were quantified using a commercial ELISA kit (Invitrogen, UK; BMS2038INST) according to the manufacturer’s instructions. Samples stored at -80°C were thawed, diluted 1:50 and added in duplicate to pre-equilibrated wells. After 3 h of incubation at room temperature with agitation, plates were washed, developed with TMB substrate and the reaction was stopped after 10 min. Absorbance was read at 450 nm. Duplicate readings with > 20% variation were excluded. MPO concentrations were interpolated from standard curves using MyAssays.com.

Single-cell library preparation
Participants for scRNA-seq were randomly recruited using the same recruitment criteria and process as the other participants. Only samples with an initial cell count greater than 200,000 cells, no visible mucus and no blood contamination were included and further processed for single-cell library preparation. Single-cell RNA libraries were generated from freshly isolated nasal curette samples, collected from both nostrils, using the Chromium Next GEM Single Cell 5′ Reagent Kit v2 and Chromium Controller (10x Genomics) according to the manufacturer’s protocol. Nasal cells were dislodged from the curette, washed in FACS buffer (PBS with 3% FBS, 5 mM EDTA and 32 U/mL DNase I) by centrifugation at 400 × g for 5 min and the supernatant was discarded. Cells were resuspended in 1 mL of PBS with 3% FBS, filtered through a 40-μm FlowME filter and 10,000–16,000 cells with ≥ 80% viability were loaded into microfluidic chips to generate gel beads-in-emulsion.

Purified cDNA was quantified using Qubit 4.0 (Thermo Fisher Scientific) and its size distribution assessed using Agilent High Sensitivity D5000 ScreenTape on a TapeStation 4200 system. Libraries were constructed by fragmentation, end-repair, A-tailing, adaptor ligation and index PCR. Final libraries were quantified and quality-checked, then sequenced on an Illumina NextSeq 2000 platform (150 bp paired-end reads) to a depth of ≥ 50,000 reads per cell. Library sequencing was performed by Glasgow Polyomics (University of Glasgow, UK).

Single-cell RNA-seq data processing and analysis
Fastq files were processed using Cell Ranger (v8.0.1, 10× Genomics) and mapped to the human reference genome (GRCh38), including intronic reads to capture unspliced transcripts. The cellranger count pipeline performed alignment, barcode demultiplexing and UMI counting, generating gene expression matrices for each sample. The quality metrics for each sample have been summarised in a single cell metrics table (Supplementary Data 3) and the raw data files, including fastq files and processed data, have been deposited in the NCBI’s Gene Expression Omnibus and are accessible through the GEO accession number GSE296893. Downstream analysis was conducted in R (v4.4.1) using Seurat (v5.0.1). Cells with fewer than 200 detected genes or > 30% mitochondrial gene expression were excluded. Genes expressed in fewer than 3 cells were removed. Samples were merged and normalised using the SCTransform() function, selecting the top 2000 variable genes for downstream clustering and batch effects across samples were corrected using Harmony.

Principal component analysis was performed for dimensionality reduction, followed by clustering using a shared nearest neighbour modularity optimisation algorithm and visualised via UMAP. Cell types were annotated using canonical marker genes and validated with automated label transfer from the Human Lung Cell Atlas via SingleR and Azimuth. Differential expression analysis was performed using the MAST or DESeq2 function in Seurat. Cell-to-cell communication networks were inferred using Multinichenet(), prioritising significant receptor-ligand interactions across epithelial and immune subsets.

Gene module enrichment and over representation analyses were performed using CEMiTool (Bioconductor), integrating transcriptomic data with curated interactomes. Gene set enrichment analysis identified statistically enriched pathways associated with group-specific modules. All visualisations were generated in R using the ggplot2 and ComplexHeatmap packages.

Ethics statement
This study was conducted in accordance with the Declaration of Helsinki and adhered to all relevant ethical regulations. Ethical approval was granted by the National Health Science Research Committee (protocol #21/24/2680, Malawi) and the Liverpool School of Tropical Medicine Research Ethics Committee (protocol #21-035, UK). All participants provided written informed consent prior to enrolment and were compensated for their time according to established ethical guidelines.

Statistical analysis
All statistical analyses were conducted in R version 4.4.1. Unless otherwise specified, comparisons between groups were performed using non-parametric tests (the Wilcoxon test or Kruskal–Wallis test). Categorical data were analysed using Fisher’s exact test. Correlation analyses were performed using Spearman’s rank correlation coefficient. For single-cell transcriptomic data, differential expression was assessed using MAST or DESeq2 as applied in Seurat FindMarkers() function. Multiplex cytokine data were log-transformed before analysis to approximate normality. Where appropriate, p-values were adjusted for multiple testing using the Benjamini–Hochberg false discovery rate method. A two-sided p < 0.05 was considered statistically significant. Statistical approaches and sample sizes for each analysis are detailed in the relevant figure legends and Supplementary Information.

Data availability
The source data generated in this study have been deposited in the GitHub repository and are accessible through https://doi.org/10.5281/zenodo.17580059. The raw single-cell sequencing fastq files and single-cell processed data have been deposited in the NCBI’s Gene Expression Omnibus and are accessible through the GEO accession number GSE296893.

Code availability
Manuscript code and R script that were used to analyse the datasets are available in the GitHub repository https://github.com/japhiri/HIV-PAPER/tree/main.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript, “HIV-associated epithelial-immune cell dysfunction in the nasal mucosa promotes pneumococcal carriage despite ART,” investigates nasal mucosal immunity in people living with HIV (PLHIV) who are stable on long-term antiretroviral therapy (ART), with a particular focus on their susceptibility to pneumococcal colonization. Using a combination of flow cytometry, cytokine profiling, and single-cell RNA sequencing, the study characterizes epithelial and neutrophil phenotypes, epithelial-neutrophil interactions, and transcriptional signatures in the nasal mucosa. The authors report that PLHIV exhibit impaired neutrophil function, signs of epithelial barrier disruption, and increased markers of immune exhaustion, despite viral suppression. The study offers novel insights into tissue-specific immunity in HIV and its potential implications for infection risk and vaccine responsiveness.\n\nThe study is described as cross-sectional; however, some data appear to have been collected at different time points (e.g., over several years or ART durations). It would be helpful if the authors clarified whether these samples were collected from the same individuals longitudinally or from different individuals at each time point. This distinction is important for interpreting any temporal or ART-duration-related comparisons and understanding whether observed differences reflect within-individual changes or inter-individual variability.\n\nPlease can the authors provide why these participants were attending the clinics? Were they routine visits, did they have any other underlying illnesses, or were they attending for medical care?\n\nThe use of nasal curettes is appropriate for obtaining high-quality mucosal samples for transcriptomic and cellular immune profiling. However, this method can be more invasive and prone to inter-operator variability compared to flocked swabs. It would be helpful if the authors provided additional detail on standardization procedures for sample collection and whether any participants experienced discomfort or bleeding. Furthermore, given the possibility of blood contamination with curettage, the authors should clarify whether any quality control steps were taken to assess or mitigate this, especially in RNAseq or cytokine analyses.\n\nAlthough the sample size (n=57 PLHIV, n=51 controls) appears modestly adequate, subgroup comparisons (e.g., between carriers and non-carriers within PLHIV) become underpowered. Some findings may be due to chance, especially in the context of functional assays with smaller n.\n\nIn lines 96-98, the authors say, “Neutrophil abundance was significantly higher in PLHIV-ART>1yr compared to HIV− adults, but only marginally higher compared to PLHIV-ART<3m (Fig. 1c).” However, this was not significant. The authors need to rephrase this sentence to reflect this.\n\nThroughout the results section, the authors need to provide the p-values where comparisons are made.\n\nThe cohort of PLHIV, despite long-term ART and viral suppression, may still represent individuals with varying degrees of immune reconstitution. The manuscript does not adequately address potential confounding due to differences in CD4 count, ART duration, co-infections, or mucosal inflammation unrelated to HIV.\n\nThe methodology used for detecting pneumococcal carriage is not described in sufficient detail. The criteria for defining “carriage” are not well established in the text.\n\nIn the results section, in the text, the authors make mention of CD66b+ neutrophils, CD3+ T cells and CD4+ monocytes; however, the figure has it labelled as neutrophils, T cells and monocytes. The figure needs to be changed to match the description in the text.\n\nIn Table 1, there is an asterisk on socioeconomic status; however, there is no corresponding footnote below the table describing what the asterisk means.\n\nLine 145 – What were the viruses tested? How were they tested? This needs to be included in the methods section.\n\nReferences: Reference 17 is duplicated and again referenced as reference 42.\n\nThis is a well-conceived and important study that addresses persistent gaps in our understanding of mucosal immunity in PLHIV. However, revisions are required. With these changes, the manuscript will make a valuable contribution to the field.", "reviewer_2": "As people living with HIV (PLHIV) remain at an elevated risk of Streptococcus pneumoniae, even when on long-term antiretroviral therapy (ART), the authors investigated the upper respiratory mucosal immune landscape in HIV-uninfected adults and PLHIV at different stages of ART.\n\nUsing multiparameter flow cytometry, single-cell transcriptomics, and neutrophil functional assays they evaluate immune cell composition, epithelial-immune communication, and their relationship with pneumococcal carriage.\n\nFlow cytometry revealed that long-term ART does not restore nasal mucosal immunity with increased neutrophils in ART+ HIV+ donors and decreased CD4 T cells. As one might expect, activated neutrophil subsets were enriched in nasal mucosa compared to blood especially in ART+ HIV+ donors correlating with myeloperoxidase (MPO) levels but not proinflammatory cytokines. However neutrophil chemo-attractants were only positively associated with nasal neutrophil abundance in HIV- donors suggesting dysregulation of neutrophil recruitment pathways.\n\nScRNA-seq was then carried out on nasal immune cells neutrophils derived from HIV- and HIV+ART+ donors. Multinichenet was first used to infer to-cell communication and revealed that epithelial cell - neutrophil interactions were significantly expanded in HIV+ donors showed strong ligand-receptor signalling pathways associated with neutrophil recruitment from basal, secretory, goblet, squamous, and ciliated epithelial subsets. Airway epithelial cells were therefore concluded to contribute to neutrophil recruitment and activation. Compared to HIV- donors, neutrophils from HIV+ donors who had been on ART for more than year showed elevation of mitochondrial stress-associated genes, whereas donors who had been on ART for less than 3 months showed elevated levels of antiviral response genes. CEMiTool was then used to identify co-expressed gene modules enriched in neutrophils across the study groups indicating enrichment in homeostatic regulation pathways as well as those associated with cytokine signalling, interferon response, antigen presentation, and immunoregulatory.\n\nFunctional competence of blood neutrophils was then assessed by measuring phagocytic uptake and oxidative burst assays. No difference in phagocytic uptake was recorded but oxidative burst capacity was significantly lower in both HIV+ groups suggesting potential impairment in killing capacity.\n\nSimilar to neutrophils, CD4 T cells derived from both HIV+ donor groups also showed elevated levels of genes associated with immune activation, chemokines and age associated genes.\n\nFinally, the authors showed that in HIV+-ART+>1yr donors (but not PLHIV-ART<3m donors), neutrophil abundance was significantly higher in individuals with pneumococcal carriage compared to those without with a similar pattern observed for CD14+ monocytes.\n\nStrengths\n\nA very clear strength of the study is the recruitment of 132 adults from Malawi including HIV+ patients who have only recently started ART (within 3 months), those who have been taking ART for over a year and HIV- controls. Nasal mucosal cells, nasal lining fluid, and peripheral blood were collected from all participants which allowed this study to be possible. Thus, this study is as physiologically relevant as is possible in a human setting.\n\n• cells for nasal immunity and notably were detected in the single cell analysis of nasal cells (Fig 3).\n• If single-cell transcriptomic profiling was done, what specific helper CD4 T cells were reduced?\n• The authors have been open about acknowledging the several limitations such as the limited sample for single-cell analyses, functional studies being restricted to blood-derived neutrophils and lack of assessment of microbial community composition, which may shape mucosal immunity and carriage risk.\n\nWeaknesses\n\n1. It odd that myeloid antigen presenting cells were not investigated as they showed up in flow cytometry analysis (Figure 1) as well as scRNA-seq analysis which would account for an enrichment of genes encoding protein associated with cytokine signalling, interferon response, antigen presentation, and immunoregulatory. Why were markers for myeloid antigen presenting cells not included such as CD1c, CD11c, XCR1 for dendritic cells and CD68, CD163, FXIIIA for macrophages. APCs are an important mucosal immune constituent.\n\n2. Figure 1: The authors state that flow cytometry and single-cell transcriptomic profiling was carried out. What single-cell transcriptomic profiling platform was used and where is the data? Figure 1 extended Figure 1 only show flow cytometry data.\n\n3. Neutrophil functional assay was conducted with blood neutrophils rather nasal. However, this assay would likely be impossible to conduct using the small numbers that can be derived from the nasal mucosa. As the authors state in the discussion, neutrophils are generally short-lived and nasal neutrophils almost certainly traffic from peripheral blood, so the use of blood derived neutrophils is justified. Direct assessment of mucosal neutrophil function does remain an important future direction. Please could the authors speculate how this might be achieved.\n\n4. The study is over reliant on gene expression data. Some functional data is carried out on neutrophils but nothing on T cells. The T cell part feels a little bit ‘stuck on the end’. I wonder if this should be removed and make the manuscript solely about neutrophils given these cells where some functional assays have been carried out? Or would it be possible to provide more information about the specific Th subsets between study groups and/or memory status.", "reviewer_3": "This interesting paper assesses the relationship between nasal mucosal neutrophil function and immune composition to pneumococcal colonisation in people with HIV (PWH) treated with either 3 months or >1year of ART. The major strengths are the novelty of the hypothesis, the new insights generated into an important issue of streptococcal infection and the use of multiple new technologies to gain insights into mucosal immunity in the nose. The weaknesses are that this is a cross sectional study and therefore only describes associations, the group with PWH on ART for <3 months are a heterogeneous group and therefore may not be easy to interpret, there may be other confounders to the findings such as CD4 count, duration on ART and the presence of viremia. the cohort is overall very young and therefore relevance to other age groups is unclear.\n\nMajor concerns\n\n1. Study design – the study focuses on three groups – HIV uninfected, PWH on ART<3 months (24% virus detected) and PWH on ART >1yr (10% virus detected). I am concerned that the ART<3 months includes a heterogenous group, specifically those that are and aren’t viremic and who may and may not be undergoing inflammatory immune reconstitution. Ideally a group preART would have been far better to include. The authors should highlight this weakness in the discussion\n\n2. I struggled to understand why mucosal immunity would be more dysfunctional in people on ART>1year compared to <3 months. This intuitively didn’t make a lot of sense. One explanation is that the PWH on ART<3 months was a heterogenous group. On line 336, the authors propose that they observed evidence of ‘T-cell exhaustion, sensesence and apoptosis…..on long term ART’. However, this type of dysfunction is usually much worse in PWH without ART. The unespected findings that PWH on ART>1 year had more dysfunction and more colonisation needs to be more clearly discussed\n\n3. The authors should analyse the impact of viremia or no viremia on the parameters measured. This might explain why the ART<3 month group often are closer to HIV uninfected than the ART>1 year group. This relationship was difficult to understand eg figure 1c and 2b as two examples of an immune markers where HIV on ART<3 months looked closer to HIV uninfected participants\n\n4. Certain clinical parameters such as nadir and current CD4 and duration on ART may impact the findings,\n\na. CD4 count may play a very important role in nasal immunity – including both current and nadir CD4. The authors should assess the impact of current and nadir CD4 as a confounder for the findings of changes in nasal immunity\n\nb. The duration on ART is also quite variable, ranging from 37 to 111 months. The authors should assess whether duration on ART influences any of the key parameters of immune dysfunction\n\n5. The authors largely describe correlations and therefore are unable to infer causation. Have the authors treated any participants with antibiotics to clear colonisation? Have any participants been immunised against pneumococcus and if yes, can the authors compare vaccinated and unvaccinated groups? The addition of an intervention such as antibiotics or vaccination would greatly strengthen the findings\n\nMinor concerns\n\n6. The authors quote that there is a 30-100 fold increase in invasive pneumococcal disease in PWH on ART compared to HIV uninfected people, can they also include some background information on the relationship between colonisation and invasive disease\n\n7. The authors examine a subset of participants with scRNAseq. This is reasonable given the cost of scRNAseq. Why were 3 participants chosen per group? What was the statistical rationale for this? Also, how were the 3 participants selected. These details should be included to ensure there wasn’t bias in the selection of the subset which could have impacted the findings\n\n8. The figures show comparison between all three groups, both statistically significant and non-significant comparisons. I think it would be better to either write ns for the non-significant comparisons, or not show the p value at all. By including all the p values, significant and non-significant, its hard to digest the truly significantly different findings\n\n9. Figure 1 g-I show no significant differences between the three groups. Perhaps these panels could move to extended data?\n\n10. Figure 4a – are these analyses adjusted for total cell number? Could one explanation of the low level of connections for HIV negative donors is that there were fewer cells analysed?"}, "author_response": "Thank you for allowing us to resubmit the manuscript. We thank the reviewers for their constructive comments and queries. We have addressed all the queries, point-by-point, below.\n\nReviewer 1\n\nQuery 1: Please can the authors provide why these participants were attending the clinics?\nWere they routine visits, did they have any other underlying illnesses, or were they attending\nfor medical care?\nAll participants in this study were recruited either from voluntary testing and counselling\nservices at the Gateway Voluntary Counselling and Testing Centre or from routine ART\nclinics at the Lighthouse ART Clinic in Blantyre, Malawi. HIV-uninfected participants were\nenrolled from the surrounding community in Blantyre. Importantly, all individuals were\notherwise “healthy” and asymptomatic, with no evidence of infection or chronic illness, as\nconfirmed by standard clinical assessments. We have clarified this in the Cohort\ncharacteristics and sampling section (Page 4, lines 76–81).\n\nQuery 2: The use of nasal curettes is appropriate for obtaining high-quality mucosal samples\nfor transcriptomic and cellular immune profiling. However, this method can be more invasive\nand prone to inter-operator variability compared to flocked swabs. It would be helpful if the\nauthors provided additional detail on standardization procedures for sample collection and\nwhether any participants experienced discomfort or bleeding.\nResponse: While we acknowledge the potential for blood contamination and inter-operator\nvariability during sample collection, all procedures were performed by well-trained staff\nwith extensive experience in collecting nasal cells using a nasal curette for research\npurposes. Participants did not report significant discomfort during sampling. In the rare\ncases where blood contamination was observed (<1% of all samples), the affected samples\nwere excluded from analysis. We have clarified this in the Nasal sample collection section\n(Page 14, lines 418–419).\n\nQuery 3: Furthermore, given the possibility of blood contamination with curettage, the\nauthors should clarify whether any quality control steps were taken to assess or mitigate\nthis, especially in RNAseq or cytokine analyses.\nResponse: As noted above (Query 2 response), we applied several quality control measures\nto ensure that only high-quality nasal samples were included in the single-cell and nasal\nserological analyses. All samples with visible blood or mucus were excluded from processing\nor analysis. For single-cell RNA sequencing, we used the Seurat analysis pipeline to exclude\ncells with low complexity (nFeature_RNA < 100) and those containing reads mapped to\nhaemoglobin genes. Importantly, no reads mapped to haemoglobin were detected in our\ndataset, indicating an absence of blood contamination. These quality control metrics have\nbeen provided in the analysis R scripts (seurat_pipeline.R) available on our GitHub account.\nFor nasal lining fluid assays, samples with clear blood contamination, though rare, were also\nexcluded.\n\nQuery 4: Although the sample size (n=57 PLHIV, n=51 controls) appears modestly adequate,\nsubgroup comparisons (e.g., between carriers and non-carriers within PLHIV) become\nunderpowered. Some findings may be due to chance, especially in the context of functional\nassays with smaller n.\nResponse: Even though the sample size for the subgroup analysis was relatively small, the\nresults of the functional assays are consistent with the overall findings of the manuscript,\nmaking it unlikely that they occurred by chance. Nonetheless, this limitation has been\nacknowledged in the discussion section (Page 13, lines 374–376).\n\nQuery 5: In lines 96-98, the authors say, “Neutrophil abundance was significantly higher in\nPLHIV-ART>1yr compared to HIV− adults, but only marginally higher compared to PLHIV-\nART<3m (Fig. 1c).” However, this was not significant. The authors need to rephrase this\nsentence to reflect this.\nResponse: We have rephrased the sentence on Page 4, line 101, for clarity. The revised\nsentence now reads:\n“Neutrophil abundance was significantly higher in PLHIV-ART>1yr compared to HIV− adults,\nbut only marginally higher compared to PLHIV-ART<3m, however, this was not statistically\nsignificant.”\n\nQuery 6: Throughout the results section, the authors need to provide the p-values where\ncomparisons are made.\nResponse: We have adhered to the Nature Communications reporting guidelines, which do\nnot require inclusion of in-text p-values within the manuscript.\n\nQuery 7: The cohort of PLHIV, despite long-term ART and viral suppression, may still\nrepresent individuals with varying degrees of immune reconstitution. The manuscript does\nnot adequately address potential confounding due to differences in CD4 count, ART duration,\nco-infections, or mucosal inflammation unrelated to HIV.\nResponse: While CD4 count is primarily associated with impaired systemic immunity, our\nanalysis showed no relationship between CD4 count or ART duration and markers of nasal\ninflammation (including neutrophil and monocyte abundance). This indicates that, in this\nstudy, CD4 count and ART duration were not associated with nasal inflammation. To\nminimise potential confounding, participants were carefully selected: individuals with acute\ninfections, chronic diseases (including cancer, diabetes, hypertension, tuberculosis, and\nCOPD), or recent antibiotic use were excluded, except for co-trimoxazole prophylaxis in\nPLHIV.\n\nQuery 8: The methodology used for detecting pneumococcal carriage is not described in\nsufficient detail. The criteria for defining “carriage” are not well established in the text.\nResponse: We used standard WHO-recommended protocols for pneumococcal carriage\ndetection. To provide further clarity, we have added additional methodological details,\nincluding a citation of our previously published work on pneumococcal detection and\ncarriage density calculations (Page 16, lines 464–471).\n\nQuery 9: In the results section, in the text, the authors make mention of CD66b+ neutrophils,\nCD3+ T cells and CD4+ monocytes; however, the figure has it labelled as neutrophils,\nT cells and monocytes. The figure needs to be changed to match the description in the text.\nResponse: We have corrected the labelling in Figure 1b (Page 22) to accurately reflect that\nneutrophils were identified as CD66b⁺, T cells as CD3⁺, and monocytes as CD14⁺.\n\nQuery 10: In Table 1, there is an asterisk on socioeconomic status; however, there is no\ncorresponding footnote below the table describing what the asterisk means.\nLine 145 – What were the viruses tested? How were they tested? This needs to be included in\nthe methods section.\nResponse: We have corrected Table 1 by adding an asterisk in the legend to highlight\nsocioeconomic status and by removing the asterisk that was previously included for HIV viral\nload. In addition, we have added a section in the Methods (RT-qPCR for identification of\nrespiratory viruses) describing how respiratory viruses were tested (Page 16-17, lines 481–\n493).\n\nQuery 11: References: Reference 17 is duplicated and again referenced as reference 42.\nResponse: This has been corrected.\n\nReviewer 2\n\nQuery 1: If single-cell transcriptomic profiling was done, what specific helper CD4 T cells\nwere reduced?\nResponse: In Figure 3d (Page 25), we show that CD3⁺ T cells in the nasal curette are\npredominantly CD8⁺ T cells and natural killer T cells. This finding is consistent with our flow\ncytometry data (Figure 1e, Page 22), which demonstrate that CD4⁺ T cells are present at low\nfrequencies in nasal curettes, likely due to the sampling method, and is in agreement with\nprevious publications using nasal curette samples. Single-cell RNA sequencing did not\nfurther resolve this minor CD4⁺ T-cell subset, as the majority of CD3⁺ T cells were CD8⁺ and\nnatural killer T cells. However, our unpublished flow cytometry data from a larger sample\nsize of nasal curettes (to be reported in a separate manuscript) indicate that CCR6⁺ and\nCXCR3⁺ CD4⁺ T cells comprise the majority of this minor CD4⁺ T-cell population.\n\nQuery 2: Its odd that myeloid antigen presenting cells were not investigated as they showed\nup in flow cytometry analysis (Figure 1) as well as scRNA-seq analysis which would account\nfor an enrichment of genes encoding protein associated with cytokine signalling, interferon\nresponse, antigen presentation, and immunoregulatory. Why were markers for myeloid\nantigen presenting cells not included such as CD1c, CD11c, XCR1 for dendritic cells and CD68,\nCD163, FXIIIA for macrophages. APCs are an important mucosal immune constituent.\nResponse: The identification of myeloid antigen-presenting cells during cell annotation was\nbased on the expression of canonical markers shown in Figure 3c (Page 25) and validated by\nprevious single-cell studies of nasal cells (doi.org/10.1016/j.cell.2021.07.023; Nature\nMedicine, 2024). In our nasal single-cell dataset, CD1c was not constitutively expressed in\ndendritic cells, although CD11c and XCR1 expression coincided with dendritic cell subsets\nidentified in the data. Macrophages were also clearly defined by the expression of CD68,\nCD163, and F13A1 (FXIIA). However, we did not focus our analysis on antigen-presenting\nmyeloid cells because the larger flow cytometry dataset (Figure 1d, Page 22) showed no\nsignificant group differences. This does not diminish their importance as a key mucosal\nimmune constituent.\nTo clarify, our CEMiTool and differential expression single-cell analyses were performed in a\ncell cluster–specific manner, focusing either on neutrophils or T cells. Accordingly, the\nenrichment of genes encoding proteins linked to cytokine signalling, interferon responses,\nantigen presentation, and immunoregulatory functions reflects neutrophil- or T cell–specific\nbiology as resolved by single-cell RNA sequencing.\n\nQuery 3: Figure 1: The authors state that flow cytometry and single-cell transcriptomic\nprofiling was carried out. What single-cell transcriptomic profiling platform was used and\nwhere is the data? Figure 1 extended Figure 1 only show flow cytometry data.\nResponse: We used the 10x Genomics Chromium Controller platform for single-cell gel\nbead-in-emulsion (GEM) preparation, together with the 10x 5’ v2 library preparation\nprotocol. This has been indicated in the Methods section, and we have amended the Results\nsection sentence under “HIV alters nasal immune cell composition despite long-term ART”\n(Page 4, line 96) for clarity. In addition, we confirm that Figures 3, 4, 5, and 6 present single-\ncell transcriptomic data.\n\nQuery 4: Neutrophil functional assay was conducted with blood neutrophils rather nasal.\nHowever, this assay would likely be impossible to conduct using the small numbers that can\nbe derived from the nasal mucosa. As the authors state in the discussion, neutrophils are\ngenerally short-lived and nasal neutrophils almost certainly traffic from peripheral blood, so\nthe use of blood derived neutrophils is justified. Direct assessment of mucosal neutrophil\nfunction does remain an important future direction. Please could the authors speculate how\nthis might be achieved.\nResponse: Our laboratory is currently developing approaches to improve cell recovery and\nyield by employing a combined curette-swab collection method. This strategy is intended to\nfacilitate downstream applications, including neutrophil functional assays.\n\nQuery 5: The study is over reliant on gene expression data. Some functional data is carried\nout on neutrophils but nothing on T cells. The T cell part feels a little bit ‘stuck on the end’. I\nwonder if this should be removed and make the manuscript solely about neutrophils given\nthese cells where some functional assays have been carried out? Or would it be possible to\nprovide more information about the specific Th subsets between study groups and/or\nmemory status.\nResponse: While the study is primarily focused on neutrophils due to their indispensable\nrole in pneumococcal carriage, the T-cell analysis is integral to the overall narrative. We\nused the T-cell transcriptomic data to demonstrate that the senescence-associated\nsecretory phenotype (SASP) observed in neutrophils is linked to broader effects within the\nnasal environment of PLHIV on long-term ART. Consistent with this, our T-cell data reveal\nstress and apoptotic responses in T cells from PLHIV on long-term ART. With respect to the\nspecific Th subsets, we kindly refer to our response to Query 1.\n\nReviewer 3\n\nQuery 1: Study design – the study focuses on three groups – HIV uninfected, PWH on ART<3\nmonths (24% virus detected) and PWH on ART >1yr (10% virus detected). I am concerned\nthat the ART<3 months includes a heterogenous group, specifically those that are and aren’t\nviremic and who may and may not be undergoing inflammatory immune reconstitution. Ideally a group preART would have been far better to include. The authors should highlight\nthis weakness in the discussion.\nI struggled to understand why mucosal immunity would be more dysfunctional in people on\nART>1year compared to <3 months. This intuitively didn’t make a lot of sense. One\nexplanation is that the PWH on ART<3 months was a heterogenous group. On line 336, the\nauthors propose that they observed evidence of ‘T-cell exhaustion, senescence and\napoptosis…..on long term ART’. However, this type of dysfunction is usually much worse in\nPWH without ART. The unexpected findings that PWH on ART>1 year had more dysfunction,\nand more colonisation needs to be more clearly discussed\nResponse:\nThe primary aim of this study was to immunologically investigate why PLHIV on ART >1 year\nexhibit persistently high pneumococcal colonisation. Elevated carriage prevalence in PLHIV-\nART>1yr has been consistently reported over the past 14 years\n(https://doi.org/10.1097/qad.0000000000000755,\nhttps://doi.org/10.1371/journal.pone.0100640, https://doi.org/10.1093/cid/cis842,\nhttps://doi.org/10.1038/s41467-020-15786-9), including studies directly comparing HIV-\nuninfected individuals, PLHIV pre-ART, and PLHIV on ART of varying durations. We also\nindependently confirmed this in our published BMC Medicine case–control study, showing\nthat PLHIV-ART>1yr have higher pneumococcal carriage compared to both HIV-uninfected\nand PLHIV-ART<3m (https://doi.org/10.1186/s12916-024-03631-5). This manuscript,\ntherefore, addresses the unexpected and important finding of sustained high carriage in\nPLHIV-ART>1yr.\nWe are not suggesting that PLHIV-ART<3m lack nasal immune dysfunction. Indeed, we show\nthat PLHIV-ART<3m exhibit lower nasal CD4⁺ T-cell frequencies, higher expression of T-cell\nexhaustion and senescence genes, and greater T-cell activation compared to PLHIV-\nART>1yr. However, this T-cell dysfunction persists in PLHIV-ART>1yr when compared with\nHIV-uninfected individuals.\nFinally, we have corrected the figure placement error in the submitted version. The\nappropriate figures (now Figure 6g and 6h, Page 29) have been inserted to match the\ncorresponding results narrative.\n\nQuery 2: The authors should analyse the impact of viremia or no viremia on the parameters\nmeasured. This might explain why the ART<3 month group often are closer to HIV uninfected\nthan the ART>1 year group. This relationship was difficult to understand e.g. figure 1c and\n2b as two examples of an immune markers where HIV on ART<3 months looked closer to HIV\nuninfected participants\nResponse: Our analysis of the impact of viraemia on markers of inflammation, including\nneutrophil and monocyte abundance, showed no significant differences. Refer to the figure\nbelow.\nConsistent with published literature on the impact of HIV on T cells, our data show that T-\ncell–associated dysfunction is most pronounced in PLHIV-ART<3m, while profiles in PLHIV-\nART>1yr are more comparable to those of HIV-uninfected individuals (refer to Query 1\nabove). In contrast, it is within the PLHIV-ART>1yr group that neutrophil dysregulation is\nmost evident and is associated with pneumococcal carriage.\n\nQuery 3: Certain clinical parameters such as nadir and current CD4 and duration on ART may\nimpact the findings,\n\na. CD4 count may play a very important role in nasal immunity – including both current and nadir\nCD4. The authors should assess the impact of current and nadir CD4 as a confounder for the\nfindings of changes in nasal immunity\nResponse: While we did not collect nadir CD4 count data for the participants in this study,\nour analysis of current CD4 counts showed no significant associations with markers of nasal\ninflammation, including neutrophil and monocyte abundance. Refer to the figure below.\n\nb. The duration on ART is also quite variable, ranging from 37 to 111 months. The authors should\nassess whether duration on ART influences any of the key parameters of immune dysfunction\nResponse: Our analysis of ART duration showed no significant associations with markers of\nnasal inflammation, including neutrophil and monocyte abundance. However, it is\nimportant to note that our study only assessed participants within two timeframes: 0–3\nmonths on ART and >1 year on ART, leaving a gap between 3 and 12 months that was not\nevaluated. Refer to the figure below.\n\nQuery 4: The authors largely describe correlations and therefore are unable to infer\ncausation. Have the authors treated any participants with antibiotics to clear colonisation?\nHave any participants been immunised against pneumococcus and if yes, can the authors\ncompare vaccinated and unvaccinated groups? The addition of an intervention such as\nantibiotics or vaccination would greatly strengthen the findings\nResponse: All participants included in this study had not taken antibiotics for at least 2\nweeks prior to enrolment, and we did not give any antibiotics as part of this study. However,\nparticipants in the PLHIV groups were receiving daily co-trimoxazole prophylaxis as part of\nthe routine programmatic rollout. All study participants were adults and unvaccinated, as\npneumococcal vaccination in Malawi is currently restricted to children under 5 years of age,\nfollowing a 3+0 schedule (doses at 6, 10, and 14 weeks).\n\nQuery 5: The authors quote that there is a 30-100-fold increase in invasive pneumococcal\ndisease in PWH on ART compared to HIV uninfected people, can they also include some\nbackground information on the relationship between colonisation and invasive disease.\nResponse: We have added the sentence “Pneumococcal carriage is a prerequisite for\npneumococcal disease” on Page 3, lines 46–47.\n\nQuery 6: The authors examine a subset of participants with scRNAseq. This is reasonable\ngiven the cost of scRNAseq. Why were 3 participants chosen per group? What was the\nstatistical rationale for this? Also, how were the 3 participants selected. These details should\nbe included to ensure there wasn’t bias in the selection of the subset which could have\nimpacted the findings\nResponse: We have clarified the participant selection criteria for single-cell RNA sequencing\nin the Methods section. Participants were randomly selected using the same recruitment\ncriteria and processes as the broader cohort. Only samples with an initial cell count\n>200,000, without visible mucus or blood contamination, were included and processed for\nsingle-cell library preparation (Page 17, lines 505–508). While we did not perform a formal\nsample size calculation for single-cell RNA sequencing, our approach was guided by\npublished studies indicating that a minimum of three biological replicates is sufficient to\nderive mechanistic insights, rather than for epidemiological generalisability.\n\nQuery 7: The figures show comparison between all three groups, both statistically significant\nand non-significant comparisons. I think it would be better to either write ns for the non-\nsignificant comparisons or not show the p value at all. By including all the p values,\nsignificant and non-significant, its hard to digest the truly significantly different findings.\nResponse: We have included all p-values in the figures, in line with Nature Communications\nreporting guidelines, to ensure transparency and avoid selective reporting of only significant\nfindings.\n\nQuery 8: Figure 1 g-I show no significant differences between the three groups. Perhaps\nthese panels could move to extended data?\nResponse: Although there were no significant differences among the groups in Figures 1g–i,\nwe retained these panels in the main figure to provide context and to highlight that the\nobserved differences were primarily in neutrophils, which are an important cell type for\nimmunity against Streptococcus pneumoniae.\n\nQuery 9: Figure 4a – are these analyses adjusted for total cell number? Could one\nexplanation of the low level of connections for HIV negative donors is that there were fewer\ncells analysed?\nResponse: We adjusted for both the total number of cells and the total number of samples\nper group. This information is detailed in the Multinichenet analysis R script, which is\navailable on our GitHub account."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have sufficiently addressed my comments and revised the manuscript.\nRecommend for publication.", "reviewer_2": "The authors have addressed my concerns. I congratulate them on this nice study.", "reviewer_3": "The authors have addressed all my concerns in a satisfactory manner."}, "author_response": ""}]

Decision letter