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Dynamic responses by lymph node stromal cells to primary and secondary infection.

ABSTRACT: Lymph nodes (LN) are constructed of intricate networks of endothelial and mesenchymal stromal cells. These include the fibroblastic reticular cells (FRC), lymphatic endothelial cells (LEC) and blood endothelial cells (BEC). We performed a comprehensive analysis of LSC responses to skin viral infection and found that LSC subsets responded robustly. Infection induced rapid transcriptional regulation of large numbers of both shared and unique genes in FRC, LEC and BEC to support LN remodeling and the immune response. This transcriptional program was transient, returning to homeostasis within one month of infection. Yet, expanded FRC networks persisted for greater than three months after infection. Our results reveal the complexity of LN stromal cell responses during infection and suggest that LN remodeling to acute infection supports successive immune responses.

ORGANISM(S): Mus musculus

PROVIDER: GSE84284 | GEO | 2016/12/21

SECONDARY ACCESSION(S): PRJNA328588

REPOSITORIES: GEO

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Project description:Purpose: The goal of this study is to compare the transcriptome profiles of freshly isolated primary murine endothelial populations, namely the lymph node-derived lymphatic endothelial cell (LN-LEC) and blood endothelial cell (LN-BEC), and the diaphragm-derived LEC (D-LEC) in homeostasis. Methods: LN-LEC and LN-BEC total RNA samples were prepared by pooling inguinal, axillary, brachial, cervical, and mesenteric LNs from wild-type C57BL/6 (B6) mice (6-8 weeks of age, purchased from NCI), followed by mechanical and enzymatic digestion, CD45- cell lineage enrichment using MACS beads (deplete S protocol in AUTOMACS), and sorted by flow cytometry based on CD45, CD31, and podoplanin expressions using Influx (BD) into RNA Protect (Qiagen). D-LEC total RNA samples were prepared by mechanical and enzymatic digestion of tissues, followed directly by flow cytometry sorting as described above. Total RNA extraction was performed using RNAeasy mini kit (Qiagen) as per manufacturer’s instructions. The cDNA library preparation and sequencing were performed by the Genomic Services Laboratory at Hudson Alpha, USA. Briefly, purified total RNAs (RIN score of 7.0 or higher) were prepared for sequencing using the Ovation RNA-seq System V2 kit (Nugen) followed by RNA-sequencing of 100 paired-end reads using the Illumina HiSeq 2500 v4 platform. Raw RNA-sequencing read quality was assessed using FastQC and low quality regions were trimmed using Fastx-trimmer. Cleaned reads were aligned to the mouse reference genome (build mm9) using STAR and read counts on known mouse genes were calculated using featureCounts, part of the Subread package. Next, uniquely aligned reads were analyzed using the DEseq2 package in the R statistical computing environment to obtain normalized counts, estimate dispersion, and determine a negative binomial model for each gene. Differentially expressed genes (DEG) were determined using DESeq2 and the Benjamini-Hochberg False Discovery Rate procedure was used to re-estimate the adjusted p-values. Differentially expressed genes (DEGs) were subsequently identified as those with an FPKM of 1 or greater, p-adjusted < 0.05, and additionally 5X-DEG subsets were identified as those with fold-change of 5 or greater. Results: Post-sort analyses of LN-LEC, LN-BEC, and D-LEC replicates showed 92.6-98.6% purity. RNAseq yielded 48-98 million reads per replicate, with an average length of 180 nucleotides, and an average of 85.7% uniquely mapped reads. These reads mapped a total of 23284 genes, of which 15331 were considered expressed based on an average FPKM of 1 or greater in at least one cell type. Of this number, 14718, 14893, and 14384 genes were considered expressed in LN-LEC, LN-BEC, and D-LEC, respectively. Principal component analysis revealed that the transcriptional profiles of sample replicates clustered tightly, and that those of LN-LEC, LN-BEC, and D-LEC differed from each other. Conclusions: Our study provides insights into key genes involved in niche-associated functions of primary murine LEC and BEC in homeostasis. The RNA-seq data reported here may provide a conceptual framework for future comparative investigations of LN-LEC, LN-BEC, and D-LEC phenotypic expression profiles, heterogeneity, and niche-specific functions in homeostasis as well as disease.

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Dynamic responses by lymph node stromal cells to primary and secondary infection.

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