High‐throughput Gene Expression Profiling of Myeloid Cells in Mechanically Ventilated Patients with Pneumonia

Rationale Transcriptomic analysis of peripheral blood leukocytes has improved our understanding of the host response to pneumonia. However, this approach is limited as these cells may not be directly exposed to causative pathogens in the alveolar space. Non‐bronchoscopic bronchoalveolar lavage (NBBAL) allows for rapid sampling of the distal airspaces in critically ill patients. We have adapted protocols for isolating individual myeloid cell populations from human lung tissue using fluorescence‐activated cell sorting (FACS) to isolate alveolar macrophages from NBBAL fluid in mechanically ventilated patients with suspected pneumonia. Hypothesis High‐throughput gene expression profiling (RNA‐Seq) using FACS‐sorted alveolar macrophages from critically ill patients with pneumonia readily identifies transcriptional signatures of infection. Methods NBBAL fluid was collected from mechanically ventilated patients with suspected pneumonia. After mechanical disaggregation and enzymatic digestion, single cell suspensions were subjected to red blood cell lysis, live/dead staining, and incubation with an FcR‐blocking reagent and a mixture of fluorochrome‐labeled antibodies. Data was acquired using a BD FACSAria cell sorter. Alveolar macrophages were identified as CD11b+HLADR++CD206++CD169+FSChighSSChigh cells. Following RNA extraction, libraries were prepared using NEBNext chemistry and sequenced on Illumina NextSeq 500 platform. Gene Ontology was used for enrichment analysis. Results 65 patients have been recruited with a planned enrollment of 100 patients. Ventilator‐associated pneumonia was the most common suspected pneumonia type (42%). Twenty patients (31%) had microbiologically confirmed pneumonia and over 90% of the cohort received antibiotics prior to NBBAL. In‐hospital mortality was 31%. The most common pathogens isolated were Pseudomonas aeruginosa (4 patients), methicillin‐sensitive staphylococcus aureus (3 patients), and Escherichia Coli (3 patients). To demonstrate the feasibility of our approach, transcriptomes were sequenced in a subgroup of 20 samples. High quality transcriptional data was obtained as measured by multiple variables including percentage of samples with a quality score ≥30 (96%), read depth (12.4M ± 3.3M), and alignment (93.7% ± 1.7%). Differentially expressed genes with a P<0.01 and logFC >|1.4| were identified and 236 genes were found to be upregulated in patients with pneumonia versus those without infection. Enrichment analysis identified multiple pathways involved in the host response to infection including immune response, regulation of cytokine production, and cellular response to interferon‐gamma ( Figure 1). Conclusions We have developed a protocol to pair real‐time collection of resident alveolar macrophages in the lung with rapid transcriptional profiling of purified cell populations that readily identifies transcriptional signatures of infection. This represents a novel method to analyze changes in the alveolar macrophage transcriptome over the course of critical illness. Support or Funding Information AG049665, HL071643, ES013995, The Veterans Administration, DOD W81XWH‐15‐1‐0215