Detection of residual plasma viremia in antiretroviral therapy (ART)-suppressed HIV-infected individuals is critical for characterizing the latent reservoir and evaluating the impact of cure interventions. Ultracentrifugation-based single-copy assays are sensitive but labor intensive. Fully automated replicate testing using a standard clinical viral load assay was evaluated as a high-throughput alternative for the quantification of low-level viremia. Four plasma samples from blood donors with acute HIV-1 infection and one viral culture supernatant were serially diluted into 25-ml samples to nominal viral loads ranging from 39 to <0.5 copies (cp)/ml. Each dilution was tested with 45 replicates (reps) using 0.5 ml/rep with the Aptima HIV-1 Quant assay. The nominal and estimated viral loads based on the single-hit Poisson model were compared, and a hybrid Poisson digital model for calibrated viral load estimation was derived. Testing performed using 45 reps on longitudinal plasma samples from 50 ART-suppressed individuals in the Reservoir Assay Validation and Evaluation Network (RAVEN) study cohort (range of 1 to 19 years of continuous ART suppression) showed a median viral load of 0.54 cp/ml (interquartile range [IQR], 0.22 to 1.46 cp/ml) and a 14% (95% confidence interval [CI], 9% to 19%) decline in viral load for each additional year in duration suppressed. Within the RAVEN cohort, the expected false-negative rate for detection at lower rep numbers using 9 and 18 reps was 26% and 14%, respectively. Residual plasma viremia levels positively correlated with cell-associated HIV RNA and DNA. The performance characteristics of the replicate Aptima assay support its use for quantifying residual plasma viremia to study the latent HIV reservoir and cure interventions.

The search for a cure for HIV infection has highlighted the need for increasingly sensitive and precise assays to measure viral burden in various tissues and body fluids. We describe the application of a standardized assay for HIV-1 RNA in multiple specimen types. The fully automated Aptima HIV-1 Quant Dx assay (Aptima assay) is FDA cleared for blood plasma HIV-1 RNA quantitation. In this study, the Aptima assay was applied for the quantitation of HIV RNA in peripheral blood mononuclear cells (PBMCs; n = 72), seminal plasma (n = 20), cerebrospinal fluid (CSF; n = 36), dried blood spots (DBS; n = 104), and dried plasma spots (DPS; n = 104). The Aptima assay was equivalent to or better than commercial assays or validated in-house assays for the quantitation of HIV RNA in CSF and seminal plasma. For PBMC specimens, the sensitivity of the Aptima assay in the detection of HIV RNA decayed as background uninfected PBMC counts increased; proteinase K treatment demonstrated some benefit in restoring signal at higher levels of background PBMCs. Finally, the Aptima assay yielded 100% detection rates of DBS in participants with plasma HIV RNA levels of ≥35 copies/ml and 100% detection rates of DPS in participants with plasma HIV RNA levels of ≥394 copies/ml. The Aptima assay can be applied to a variety of specimens from HIV-infected subjects to measure HIV RNA for studies of viral persistence and cure strategies. It can also detect HIV in dried blood and plasma specimens, which may be of benefit in resource-limited settings.

Background.  Subjects on suppressive combination antiretroviral therapy (cART) who do not achieve robust reconstitution of CD4(+) T cells face higher risk of complications and death. We studied participants in the Women's Interagency HIV Study with good (immunological responder [IR]) or poor (immunological nonresponder [INR]) CD4(+) T-cell recovery after suppressive cART (n = 50 per group) to determine whether cytokine levels or low-level viral load correlated with INR status. Methods.  A baseline sample prior to viral control and 2 subsequent samples 1 and 2 years after viral control were tested. Serum levels of 30 cytokines were measured at each time point, and low-level human immunodeficiency virus (HIV) viral load and anti-HIV antibody levels were measured 2 years after viral suppression. Results.  There were minimal differences in cytokine levels between IR and INR subjects. At baseline, macrophage inflammatory protein-3β levels were higher in IR subjects; after 1 year of suppressive cART, soluble vascular endothelial growth factor-R3 levels were higher in IR subjects; and after 2 years of suppressive cART, interferon gamma-induced protein 10 levels were higher in INR subjects. Very low-level HIV viral load and anti-HIV antibody levels did not differ between IR and INR subjects. Conclusions.  These results imply that targeting residual viral replication might not be the optimum therapeutic approach for INR subjects.

Single-cell transcriptomics has allowed unprecedented resolution of cell types/states in the human lung, but their spatial context is less well defined. To (re)define tissue architecture of lung and airways, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and spatial transcriptomics (queryable at lungcellatlas.org ). Using computational data integration and analysis, we extend beyond the suspension cell paradigm and discover macro and micro-anatomical tissue compartments including previously unannotated cell types in the epithelial, vascular, stromal and nerve bundle micro-environments. We identify and implicate peribronchial fibroblasts in lung disease. Importantly, we discover and validate a survival niche for IgA plasma cells in the airway submucosal glands (SMG). We show that gland epithelial cells recruit B cells and IgA plasma cells, and promote longevity and antibody secretion locally through expression of CCL28, APRIL and IL-6. This new gland-associated immune niche has implications for respiratory health.

Studies of human lung development have focused on epithelial and mesenchymal cell types and function, but much less is known about the developing lung immune cells, even though the airways are a major site of mucosal immunity after birth. An unanswered question is whether tissue-resident immune cells play a role in shaping the tissue as it develops in utero. Here, we profiled human embryonic and fetal lung immune cells using scRNA-seq, smFISH, and immunohistochemistry. At the embryonic stage, we observed an early wave of innate immune cells, including innate lymphoid cells, natural killer cells, myeloid cells, and lineage progenitors. By the canalicular stage, we detected naive T lymphocytes expressing high levels of cytotoxicity genes and the presence of mature B lymphocytes, including B-1 cells. Our analysis suggests that fetal lungs provide a niche for full B cell maturation. Given the presence and diversity of immune cells during development, we also investigated their possible effect on epithelial maturation. We found that IL-1β drives epithelial progenitor exit from self-renewal and differentiation to basal cells in vitro. In vivo, IL-1β-producing myeloid cells were found throughout the lung and adjacent to epithelial tips, suggesting that immune cells may direct human lung epithelial development.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1⁺ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.