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Nanostring GeoMx digital spatial profliing of myeloid cells from COVID-19 and normal lung

ABSTRACT: To determine definitively whether lung myeloid cells exhibit a pro- or anti-inflammatory signature in COVID-19 disease, we performed digital spatial profiling using the nanoString GeoMx ImmuneOncology plus COVID-19 platform on CD68+ macrophages, myeloperoxidase+ granulocytes and cytokeratin+ epithelium in normal and COVID-19 lung tissue specimens, collecting RNA expression data for each type within 6-8 regions of 5mM tissue sections. One COVID-19 lung tissue yielded minimal sequence data and was excluded from analysis. A volcano plot and heat map of differentially expressed genes within macrophages demonstrate that COVID-19 lung macrophages when compared with normal lung macrophages exhibit a largely alternatively activated, wound-healing signature characterized by expression of the alternatively active macrophage marker CD163, complement/coagulation genes (C1QA, C1QB, THBS1, C1S, C1R), IL6 signaling (STAT2, STAT1) and wound healing (COL3A1, COL6A3), but also interferon response signatures (ISG15, OAS3, IFITM2, IFI6, HLA-A, HLA-B, HLA-C) (Fig. 3H-J). As one of the tissues used for macrophage spatial profiling was from a patient was positive for the virus at the time of death, we compared the expression profiles of virus+ and virus- specimens and found that macrophages in virus+ tissues predominantly expressed an interferon-associated signature

ORGANISM(S): blank sample Homo sapiens

PROVIDER: GSE190494 | GEO | 2023/04/12

REPOSITORIES: GEO

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Project description:SARS-CoV-2 infections induce aberrant pulmonary and systemic inflammation, vascular leak, coagulation and fatal organ damage. To identify therapeutic strategies to suppress COVID-19-associated inflammation, we characterized lung tissue of COVID-19 patients using tissue transcriptomics. FFPE lung tissue from anonymized normal and postmortem COVID19 patients and brochoalveolar lavage specimens from normal and COVID19 patients were sequenced using Tempo-Seq from Biospyder, Calrbad, CA. Bioinformatics analysis revealed that lungs of deceased patients exhibited substantial infiltration by neutrophils and wound-healing macrophages, fibrosis, vascular leak and alveolar type II cell depletion, with a pervasive wound-healing transcriptional profile. Methods:Two five-micron FFPE sections from each of fourteen postmortem lung specimens from COVID patients, five normal lung specimens, nine BALF specimens from COVID patients and five BALF specimens from normal patients were used to perform TempoSeq FFPE human whole transcriptome RNA sequencing at BioSpyder Technologies, Inc, Carlsbad, CA, as described (Trejo et al., 2019; Turnbull et al., 2020). Prepared libraries were sequenced on NovaSeq6000; mapped reads were generated by TempO-SeqR alignment of demultiplexed FASTQ files using Bowtie, allowing for up to 2 mismatches in the 50-nucleotide target sequence.Unnormalized counts were obtained from BioSpyder TempO-seq. The R BioConductor packages edgeR (Robinson et al., 2010) and limma (Ritchie et al., 2015) were used to implement the limma-voom (Law et al., 2014) method for differential expression analysis. We analyzed normal lung, COVID-19 lung and COVID-19 BALF sample groups together and also lung samples alone due to low levels of alignment in the BALF samples. We also analyzed COVID-19 BALF and normal BALF together. One COVID-19 BALF sample was removed from downstream analysis because it had <300,000 quantified reads. Lowly expressed genes—those not having counts per million (cpm)  10 in at least 10 of the samples—were filtered out in the combined analysis and for lung samples only a less stringent filter of (cpm)  1 in at least 5 of the samples was applied. Trimmed mean of M-values (TMM) normalization (Robinson and Oshlack, 2010) was applied after filtering. The experimental design was modeled upon condition, called condition (~0 + condition). The voom method was employed to model the mean-variance relationship, after which lmFit was used to fit per-gene linear models and empirical Bayes moderation was applied with the eBayes function. Significance was defined by using an adjusted p-value cut-off of <0.05 after multiple testing correction (Benjamini and Hochberg, 1995) using a moderated t-statistic in limma. Functional enrichment of the differentially expressed genes was performed using SPIA (Tarca et al., 2009), gProfiler (Raudvere et al., 2019) and fGSEA (Korotkevich et al., 2021).

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Nanostring GeoMx digital spatial profliing of myeloid cells from COVID-19 and normal lung

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