A novel myeloid cell in murine spleen defined through gene profiling

Abstract

A novel myeloid antigen presenting cell can be generated through in vitro haematopoiesis in long-term splenic stromal cocultures. The in vivo equivalent subset was recently identified as phenotypically and functionally distinct from the spleen subsets of macrophages, conventional (c) dendritic cells (DC), resident monocytes, inflammatory monocytes and eosinophils. This novel subset which is myeloid on the basis of cell surface phenotype, but dendritic-like on the basis of cell surface marker expression and antigen presenting function, has been tentatively labelled "L-DC." Transcriptome analysis has now been employed to determine the lineage relationship of this cell type with known splenic cDC and monocyte subsets. Principal components analysis showed separation of "L-DC" and monocytes from cDC subsets in the second principal component. Hierarchical clustering then indicated a close lineage relationship between this novel subset, resident monocytes and inflammatory monocytes. Resident monocytes were the most closely aligned, with no genes specifically expressed by the novel subset. This subset, however, showed upregulation of genes reflecting both dendritic and myeloid lineages, with strong upregulation of several genes, particularly CD300e. While resident monocytes were found to be dependent on Toll-like receptor signalling for development and were reduced in number in Myd88-/- and Trif-/- mutant mice, both the novel subset and inflammatory monocytes were unaffected. Here, we describe a novel myeloid cell type closely aligned with resident monocytes in terms of lineage but distinct in terms of development and functional capacity.

Keywords: dendritic cells; monocytes; myelopoiesis; spleen.

Figure 1

Variability in gene expression amongst dendritic and myeloid subsets. Transcriptome analysis was performed on subsets of cells sorted from murine spleen. RNA was extracted and labelled for hybridization to Murine Gene ST1.0 genechips (Affymetrix). Following scanning to collect signal values from samples prepared in duplicate experiments, data were analysed using Partek and ANOVA by pairwise comparison. A, Mean signal values were calculated and plotted for a total of 35 556 genes in pairwise subset comparisons. The darker blue inner polygon contains 50% of data points, while the pale blue outer polygon contains all other data points which are not outliers (shown in red outside the polygon). The bivariate median is shown by the red asterisk at the centre of the polygon. B, Principle component analysis was used to determine variability in gene expression for each subset. Three principle components are shown for each subset prepared for analysis in duplicate experiments. C, Hierarchical clustering was used to analyse the relationship between subsets on the basis of average gene expression. The dendrogram displays distance between subsets based on clustering of 8508 genes selected for analysis on the basis of mean signal value ≥100 for any one subset

Figure 2

Pathway‐specific gene expression in dendritic and myeloid subsets. Data mining was applied to Affymetrix data sets collected from “L‐DC,” cDC and myeloid subsets prepared in duplicate experiments. For each subset, log₂ average signal values were plotted as a heat map. The line chart (blue) overlaid on heat maps indicates log₂ signal intensity changes about the mean (dashed blue line). Genes were clustered by level of expression as shown by row dendrograms. In addition, dendritic and myeloid subsets were clustered on the basis of gene expression as shown by column dendrograms. Data mining involved sets of genes utilized by SABioscience for their PCR arrays. These reflect: (A) Cell surface markers, (B) DC and APC markers, (C) Chemokines and (D) Inflammatory cytokines and receptors

Figure 3

Differential gene expression between “L‐DC” and monocyte subsets. ANOVA was used to make pairwise comparisons of average gene expression (n = 2) between different subsets and to calculate relative fold changes. A, Venn diagram shows numbers of genes upregulated ≥3‐fold in one of two subsets assessed in pairwise comparison. Infl mono: Inflammatory monocytes; Resi mono: Resident monocytes; and “L‐DC.” B, Genes uniquely expressed by each of the three subsets. C, Genes upregulated in ‘L‐DC’ and no other dendritic or myeloid subset in spleen were selected on the basis of mean signal value in “L‐DC” ≥150, with fold change between “L‐DC” and the lowest expressing subset ≥2‐fold, ≥2.5‐fold and ≥3‐fold as shown

Figure 4

Genes upregulated or specifically expressed between “L‐DC” and resident monocytes. ANOVA was used to make pairwise comparisons of average gene expression (n = 2) between subsets and to calculate relative fold changes. A, Genes upregulated in either “L‐DC” or resident monocytes were selected as those for which the signal value in one subset was ≥50, and the signal value in the second subset was ≥125. Data shown reflect genes with ≥2.5‐fold difference in signal value. B, Genes specifically expressed in either “L‐DC” or resident monocytes were selected on the basis of the mean signal value in one subset ≤50, and mean signal value in the second subset ≥125. No genes were found to be specifically expressed by “L‐DC”

Figure 5

Genes upregulated in either resident monocytes or inflammatory monocytes. ANOVA was used to make pairwise comparisons between average gene expression (n = 2) in inflammatory and resident monocytes. Genes were selected which showed ≥4‐fold change in mean signal value in either resident monocytes (Resi mono) or inflammatory monocytes (Infl mono), where mean signal value in both subsets was ≥50

Figure 6

“L‐DC” development occurs independently of Toll‐like receptor signalling. Splenocytes were harvested from C57BL/6J mutant and C57BL/6J (wild type) mice. Cells were stained with antibodies to delineate subsets as described in Table 1. Gates were set based on fluorescence minus one controls, to estimate % cells amongst the total myeloid and dendritic subset (CD11b⁺ and/or CD11c⁺) cells. Individual mice were analysed (n = 4 or 5). A bar is used to show mean values. Wild type mice (Open circles) were compared with mutants (filled circles) (A) MyD88 ^−/− (MyD88 KO) (B) Trif ^−/− (TRIF KO) and (C) C57BL/6J MyD88 ^−/− TRIF ^−/− (MyD88/Trif KO). Red boxes indicate significant change in subset representation relative to wild‐type mice using Student’s t test (P ≤ 0.05)