Contrasting Inflammatory Signatures in Peripheral Blood and Bronchoalveolar Cells Reveal Compartment-Specific Effects of HIV Infection

Cell-type deconvolution for bulk RNA-seq data using single-cell reference: a comparative analysis and recommendation guideline

The accurate estimation of cell type proportions in tissues is crucial for various downstream analyses. With the increasing availability of single-cell sequencing data, numerous deconvolution methods that use single-cell RNA sequencing data as a reference have been developed. However, a unified understanding of how these deconvolution approaches perform in practical applications is still lacking. To address this, we systematically assessed the accuracy and robustness of nine deconvolution methods that use single-cell RNA sequencing data as a reference, evaluating them on real bulk data with cell proportions verified through flow cytometry, as well as simulated bulk data generated from five single-cell RNA sequencing datasets. Our study highlights the importance of several factors-including reference dataset construction strategies, dataset size, cell type subdivision, and cell type inconsistency-on the accuracy and robustness of deconvolution results. We also propose a set of recommended guidelines for software users in diverse scenarios.

Dysfunctional bronchoalveolar effector memory CD8+ T cells in tuberculosis-exposed people living with antiretroviral-naïve HIV infection

HIV causes susceptibility to respiratory pathogens, including tuberculosis (TB), but the underlying immunological mechanisms remain incompletely understood. We obtained whole blood and bronchoalveolar lavage (BAL) from TB-exposed people in the presence or absence of antiretroviral-naïve HIV co-infection. Bulk transcriptional profiling demonstrated compartment-specific enrichment of immunological processes. Systems-level deconvolution of whole blood from people living with HIV identified elevated type I and type II interferon cytokine activity and T cell proliferation. Transcriptional modules derived from both peripheral blood and sorted BAL immune cells demonstrated an increased frequency of effector memory CD8 T cells in whole BAL samples. Both compartments displayed reduced induction of CD8 T-cell-derived interleukin-17A (IL-17A) in people with HIV, associated with elevated T cell regulatory molecule expression. The data suggest that dysfunctional CD8 T cell responses in uncontrolled HIV may contribute to compromised respiratory immunity to pathogens, a process that could be modulated by host-directed therapies that target CD8 T cell effector functions.

Uncovering the Bronchoalveolar Single-Cell Landscape of Patients With Pulmonary Tuberculosis With Human Immunodeficiency Virus Type 1 Coinfection

BACKGROUND

Coinfection of human immunodeficiency virus type 1 (HIV-1) is the most significant risk factor for tuberculosis (TB). The immune responses of the lung are essential to restrict the growth of Mycobacterium tuberculosis and avoid the emergence of the disease. Nevertheless, there is still limited knowledge about the local immune response in people with HIV-1-TB coinfection.

METHODS

We employed single-cell RNA sequencing (scRNA-seq) on bronchoalveolar lavage fluid from 9 individuals with HIV-1-TB coinfection and 10 with pulmonary TB.

RESULTS

A total of 19 058 cells were grouped into 4 major cell types: myeloid cells, T/natural killer (NK) cells, B cells, and epithelial cells. The myeloid cells and T/NK cells were further divided into 10 and 11 subsets, respectively. The proportions of dendritic cell subsets, CD4+ T cells, and NK cells were lower in the HIV-1-TB coinfection group compared to the TB group, while the frequency of CD8+ T cells was higher. Additionally, we identified numerous differentially expressed genes between the CD4+ and CD8+ T-cell subsets between the 2 groups.

CONCLUSIONS

HIV-1 infection not only affects the abundance of immune cells in the lungs but also alters their functions in patients with pulmonary TB.

Inflammatory profiles in sputum and blood of people with TB with and without HIV coinfection

Although tuberculosis (TB) remains a major killer among infectious diseases and the leading cause of death for people with HIV, drivers of immunopathology, particularly at the site of infection in the lungs remain incompletely understood. To fill this gap, we compared cytokine profiles in paired plasma and sputum samples collected from adults with pulmonary TB with and without HIV. We found that people with pulmonary TB with HIV had significantly higher markers of inflammation in both plasma and sputum than those without HIV; these differences were present despite a similar extent of radiographic involvement. We also found that the strength and direction of correlations between biomarkers in the blood and lung compartments differed by HIV status and people with HIV had more positive correlations than those without HIV. Future studies can further explore these differences in inflammation by HIV status across the blood and lung compartments and seek to establish how these profiles may be associated with long-term outcomes and lung health after completion of TB treatment.

Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis

SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.

A Pilot Cross-Sectional Study of Immunological and Microbiome Profiling Reveals Distinct Inflammatory Profiles for Smokers, Electronic Cigarette Users, and Never-Smokers

Smokers (SM) have increased lung immune cell counts and inflammatory gene expression compared to electronic cigarette (EC) users and never-smokers (NS). The objective of this study is to further assess associations for SM and EC lung microbiomes with immune cell subtypes and inflammatory gene expression in samples obtained by bronchoscopy and bronchoalveolar lavage (n = 28). RNASeq with the CIBERSORT computational algorithm were used to determine immune cell subtypes, along with inflammatory gene expression and microbiome metatranscriptomics. Macrophage subtypes revealed a two-fold increase in M0 (undifferentiated) macrophages for SM and EC users relative to NS, with a concordant decrease in M2 (anti-inflammatory) macrophages. There were 68, 19, and 1 significantly differentially expressed inflammatory genes (DEG) between SM/NS, SM/EC users, and EC users/NS, respectively. CSF-1 and GATA3 expression correlated positively and inversely with M0 and M2 macrophages, respectively. Correlation profiling for DEG showed distinct lung profiles for each participant group. There were three bacteria genera-DEG correlations and three bacteria genera-macrophage subtype correlations. In this pilot study, SM and EC use were associated with an increase in undifferentiated M0 macrophages, but SM differed from EC users and NS for inflammatory gene expression. The data support the hypothesis that SM and EC have toxic lung effects influencing inflammatory responses, but this may not be via changes in the microbiome.

Dysfunctional effector memory CD8 T cells in the bronchoalveolar compartment of people living with HIV

Mechanisms by which HIV causes susceptibility to respiratory pathogens remain incompletely understood. We obtained whole blood and bronchoalveolar lavage (BAL) from people with latent TB infection in the presence or absence of antiretroviral-naïve HIV co-infection. Transcriptomic and flow cytometric analyses demonstrated HIV-associated cell proliferation plus type I interferon activity in blood and effector memory CD8 T-cells in BAL. Both compartments displayed reduced induction of CD8 T-cell-derived IL-17A in people with HIV, associated with elevated T-cell regulatory molecule expression. The data suggest that dysfunctional CD8 T-cell responses in uncontrolled HIV contribute to susceptibility to secondary bacterial infections, including tuberculosis.

Transcription Factor ZNF683 Inhibits SIV/HIV Replication through Regulating IFNγ Secretion of CD8+ T Cells

Pulmonary microbial invasion frequently occurs during AIDS progression in HIV patients. Inflammatory cytokines and other immunoregulatory factors play important roles in this process. We previously established an AIDS model of SIVmac239 infection in northern pig-tailed macaques (NPMs), which were divided into rapid progressor (RP) and slow progressor (SP) groups according to their AIDS progression rates. In this study, we performed 16S rDNA and transcriptome sequencing of the lungs to reveal the molecular mechanism underlying the difference in progression rate between the RPs and SPs. We found that microbial invasion in the RP group was distinct from that in the SP group, showing marker flora of the Family XI, Enterococcus and Ezakiella, and more Lactobacilli. Through pulmonary transcriptome analysis, we found that the transcription factor ZNF683 had higher expression in the SP group than in the RP group. In subsequent functional experiments, we found that ZNF683 increased the proliferation and IFNγ secretion ability of CD8+ T cells, thus decreasing SIV or HIV replication, which may be related to AIDS progression in SIVmac239-infected NPMs. This study helps elucidate the various complexities of disease progression in HIV-1-infected individuals.

Identification of immune features of HIV-infected patients with antiretroviral therapy through bioinformatics analysis

BACKGROUND

Acquired immunodeficiency syndrome (AIDS) is a disease arising from human immunodeficiency virus (HIV). Antiretroviral therapy (ART) is a main therapeutic regimen for inhibiting HIV proliferation and viability. Identification of differentially expressed genes (DEGs) in HIV-infected patients with and without ART could provide theoretical evidence for deep research into the efficacy of ART and corresponding mechanism.

METHODS

In this study, mRNA microarray data (GSE108296) of HIV-infected patients who received and didn't receive ART were downloaded from Gene Expression Omnibus (GEO) database. DEGs were obtained through differential analysis with R package limma. Then, protein-protein interaction (PPI) analysis was performed to identify hub genes and functional modules. Besides, immune-related DEGs were screened, followed by GO annotation and KEGG pathway enrichment analysis. Moreover, various immune cells and immune functions in samples were analyzed by ESTIMATE, ssGSEA and CIBERSORT, based on which the immune function of HIV-infected patients who received and didn't receive ART was evaluated.

RESULTS

A total of 109 DEGs were obtained from differential analysis. Among them, 19 immune-related DEGs were identified and subjected to GO and KEGG enrichment analyses. Furthermore, PPI network analysis was undertaken on the 109 DEGs. 10 hub genes and 3 functional modules were further screened. It was shown that these genes and functional modules were correlated with immune functions and relevant signaling pathways. ESTIMATE, ssGSEA and CIBERSORT results displayed that HIV-infected patients with ART presented a relatively high immune level.

CONCLUSION

According to bioinformatics analysis, we reasonably posited that HIV-infected patients who received ART had an increased immune level relative to patients who didn't receive ART.

Dysregulation of the Immune Environment in the Airways During HIV Infection

HIV-1 increases susceptibility to pulmonary infection and disease, suggesting pathogenesis in the lung. However, the lung immune environment during HIV infection remains poorly characterized. This study examined T cell activation and the cytokine milieu in paired bronchoalveolar lavage (BAL) and blood from 36 HIV-uninfected and 32 HIV-infected participants. Concentrations of 27 cytokines were measured by Luminex, and T cells were phenotyped by flow cytometry. Blood and BAL had distinct cytokine profiles (p=0.001). In plasma, concentrations of inflammatory cytokines like IFN-γ (p=0.004) and TNF-α (p=0.004) were elevated during HIV infection, as expected. Conversely, BAL cytokine concentrations were similar in HIV-infected and uninfected individuals, despite high BAL viral loads (VL; median 48,000 copies/ml epithelial lining fluid). HIV-infected individuals had greater numbers of T cells in BAL compared to uninfected individuals (p=0.007); and BAL VL positively associated with CD4+ and CD8+ T cell numbers (p=0.006 and p=0.0002, respectively) and CXCL10 concentrations (p=0.02). BAL T cells were highly activated in HIV-infected individuals, with nearly 2-3 fold greater frequencies of CD4+CD38+ (1.8-fold; p=0.007), CD4+CD38+HLA-DR+ (1.9-fold; p=0.0006), CD8+CD38+ (2.8-fold; p=0.0006), CD8+HLA-DR+ (2-fold; p=0.022) and CD8+CD38+HLA-DR+ (3.6-fold; p<0.0001) cells compared to HIV-uninfected individuals. Overall, this study demonstrates a clear disruption of the pulmonary immune environment during HIV infection, with readily detectable virus and activated T lymphocytes, which may be driven to accumulate by local chemokines.

Progress and challenge for computational quantification of tissue immune cells

Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.