Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2 + TMPRSS2 + cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

248 words) Rationale: The respiratory tract constitutes an elaborated line of defense based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. Methods:We have explored cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12 th division of the airway tree. Results:The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with peculiar cellular proportions in different sites of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression was stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine (PNEC) and brush cells, which are likely derived from a common population of precursor cells. We also report a population of KRT13 positive cells with a high percentage of dividing cells which are reminiscent of "hillock" cells previously described in mouse. Conclusions:Robust characterization of this unprecedented large single-cell cohort establishes an important resource for future investigations. The precise description of the continuum existing from nasal epithelium to successive divisions of lung airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed. Results Building a molecular cell atlas of the airways in healthy volunteers Data collectionCells were analyzed by droplet-based single-cell RNA sequencing (scRNA-seq), after isolation from 4 distinct locations using 2 sampling methods: (i) nasal biopsies (3 samples) and (ii) nasal brushings (4 samples), (iii) tracheal biopsies (carina, 1 st division, 9 samples), (iv) intermediate bronchial biopsies (5-6 th divisions, 10 samples), (v) distal brushings (9-12 th divisions, 9 samples) in 10 healthy volunteers ( Figure 1A, 1B, Figure E1A, Table E1). Optimized handling and dissociation protocols allowed the profiling of 77,969 single cells which were collected at 35 distinct positions of the airways, resulting in the detection of an average of 1,892 expressed genes per cell with 7,070 UMI per cell ( Figure E2A).Following batch correction and graph-based clustering, cell types were assigned to each cluster using well-established sets of marker genes ( Figure 1C, Figure E3). We identified 14 epithelial cell types, including 12 for the surface epithelium and 2 for submucosal glands, which collectively represented 89.1% of total cells ( Figure 1C-1E, Table E2; See also our interactive web tool https://www.genomique.eu/cellbrowser/HCA/?ds=HCA_airway_epithelium).Strom...

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The emergence and quick spread of SARS-CoV-2 has pointed at a low capacity response for testing large populations in many countries, in line of material, technical and staff limitations. The traditional RT-qPCR diagnostic test remains the reference method and is by far the most widely used test. These assays are limited to a couple of probe sets, require large sample PCR reaction volumes, along with an expensive and time-consuming RNA extraction steps. Here we describe a quantitative nanofluidic assay that overcomes some of these shortcomings, based on the Biomark instrument from Fluidigm. This system offers the possibility of performing 4608 qPCR end-points in a single run, equivalent to 192 clinical samples combined with 12 pairs of primers/probe sets in duplicate, thus allowing the monitoring in addition to SARS-CoV-2 probes of other pathogens and/or host cellular responses (virus receptors, response markers, microRNAs). Its 10 nL range volume is compatible with sensitive and reproducible reactions that can be easily and cost-effectively adapted to various RT-qPCR configurations and sets of primers/probe. Finally, we also evaluated the use of inactivating lysis buffers composed of various detergents in the presence or absence of proteinase K to assess the compatibility of these buffers with a direct reverse transcription enzymatic step and we propose several procedures, bypassing the need for RNA purification. We advocate that the combined utilization of an optimized processing buffer and a high-throughput real-time PCR device would contribute to improve the turn-around-time to deliver the test results to patients and increase the SARS-CoV-2 testing capacities.