Spatial sequencing of young and aged lungs following influenza A virus infection

Aging is known to alter the host repsonse to influenza infection. Here, we use 10x Visium spatial sequencing to identify spatial changes in mRNA expression of left lungs of young (16-week-old) and aged (80-week-old) mice following influenza infection. Overall design: Mice were infected with influenza A/PR8/34 (~50 PFU/mouse) to establish acute infection. Infections were performed by intranasal (i.n.) administration under anesthesia as described before (Sun et al., 2009). Mice were then euthanized and the right ventricle was perfused with 10 mL cold DPBS (Corning). For Visium spatial sequencing, mice were euthanized and lungs were inflated with 500 µL of 50% v/v OCT/PBS (Fisher Healthcare) via an intratracheal catheter. The left lung was excised and the caudal half was placed in a cryomold containing OCT. The mold was frozen in an isopentane (Fisher Scientific) bath chilled by liquid nitrogen. 10 µm sections were generated from frozen inflated left lungs using a cryostat and placed on barcoded slides (10x Genomics). The Visium Spatial Gene Expression Slide & Reagent Kit (10x Genomics) was used to generate barcoded cDNA libraries. H&E stained tissues on Visium slides were imaged using a Nikon Eclipse Ti2 inverted microscope. Lung tissue on Visium slides was permeabilized for 14 minutes to extract mRNA. Barcoded cDNA libraries were sequenced on an Illumina NextSeq 500 instrument using a NextSeq 500/550 High Output Kit v2 (150 cycles) (20024907, Illumina) with the following cycle counts: 28 (read 1), 10 (index 1), 10 (index 2), 90 (read 2). Loupe Browser (v5.0, 10x Genomics) was used to identify which spatial sequencing capture area spots were in contact with tissue. Demultiplexing and alignment was performed with Space Ranger (v2.1, 10x Genomics) and the mm10 2020-A reference transcriptome (10x Genomics). Analysis was mainly performed in R using Seurat (v4.0). Visium datasets were integrated using the SCTransform pipeline, and PCA and UMAP were performed using the top 30 principal components. SPOTlight (Elosua-Bayes et al., 2021) was used to demultiplex Visium data with our integrated scRNA-seq data used as a reference.