Transcript- and protein-level analyses of the response of human eosinophils to glucocorticoids

Abstract

Glucocorticoids are first-line agents for the treatment of many eosinophil-associated disorders; however, their effects on human eosinophils remain poorly understood. To gain an unbiased, genome-wide view of the early transcriptional effects of glucocorticoids on human eosinophils in vivo, RNA sequencing was performed on purified blood eosinophils obtained before and 30, 60, and 120 minutes after administration of a single dose of oral prednisone (1 mg/kg) to three unrelated healthy subjects with hypereosinophilia of unknown significance. The resulting dataset is of high quality and suitable for differential expression analysis. Flow cytometry and qPCR were then performed on three additional cohorts of human subjects, to validate the key findings at the transcript and protein levels. The resulting datasets provide a resource for understanding the response of circulating human eosinophils to glucocorticoid administration.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1. Study design.

In cohort 1, three subjects with HEUS received a single weight-based dose of prednisone (1 mg/kg). Peripheral blood was collected pre- and post-treatment at 30, 60, and 120 min. Eosinophils were separately isolated from each sample. Eosinophil purity was measured by cytospin preparation stained with eosin and methylene blue. RNA was extracted from isolated eosinophils without further in vitro manipulation. Sequencing libraries were separately prepared for each sample, and subjected to RNA-seq. In cohort 2, circulating eosinophils were isolated from five additional unrelated subjects (four donors with normal eosinophil counts and one subject with HEUS). Purified eosinophils from each subject were cultured with media or 5 μM dexamethasone for 30, 60 and 120 min. RNA was extracted from purified eosinophils without further in vitro manipulation and subjected to qPCR. In cohort 3, three unrelated subjects, (two donors with normal eosinophil counts and one patient with HES) were studied. Donors with normal eosinophil counts received a single dose of 250 mg of IV methylprednisolone and the patient with HES received a single weight-based dose of 1 mg/kg of oral prednisone. Peripheral blood was collected pre- and post-treatment at 120 min. Purified eosinophils were stained for apoptosis and cell viability with Annexin-V and 7-AAD, respectively, and analyzed by flow cytometry. In cohort 4, peripheral blood leukocytes (PBL) were isolated from whole blood collected from six unrelated donors with normal eosinophil counts. PBL were cultured with vehicle, 20 μM methylprednisolone or 200 μM methylprednisolone for 120 min. Surface expression of CXCR4, CCR1, and CCR3 was assessed by flow cytometry.

Figure 2. Quality control of the RNA samples, sequencing libraries, sequencing reads, and read alignments.

(a) Electropherogram of a representative total RNA sample from this study, following extraction and prior to library preparation. The sample displayed had an RNA integrity number (RIN) of 9, which was the mean for all samples in the study. (b) Electropherogram of a representative dsDNA sequencing library from this study. The size distribution of the dsDNA molecules was very similar for all the libraries, with a mode around 300 bp. (c) Distribution of quality scores by base pair for a representative FASTQ file from this study. The quality scores on the y-axis are defined as -10log10e, where e is the estimated probability of a base call being wrong. Therefore, a quality score of 30 means that the estimated probability of a base being wrong is 1/1000. For each position in the sequenced reads, the corresponding box plot displays the distribution of quality scores across all the sequences in a FASTQ file. In each box plot, the red line displays the median, the yellow box the interquartile range (25–75%), and the lower and upper whiskers the 10th and 90th percentiles, respectively. The blue line displays the mean quality scores. (d) Distribution of the mean quality score by read for a representative FASTQ file from this study. (e) Sequence content in a representative FASTQ file from this study. For each position in the sequenced reads, the sequence content is the proportion of each of the four nucleotides (A, T, C, and G) at that position. (f) Distribution of mapping rates for the 12 samples in this study. The mapping rate is defined as the percent of reads in each sample that were uniquely aligned to the reference genome. (g) Distribution of the percentage of multi-mappers for the 12 samples in this study. This represents the percentage of mapped reads that aligned to more than one location in the reference genome. (h) Distribution of the number of aligned read pairs for the 12 samples in this study. Each read pair is counted once.

Figure 3. Quality control of the RNA-seq replicates.

(a) The plots display log2-transformed normalized read count values. Each dot represents one transcript. Transcripts with no evidence of expression in either subject (read count of 0) were excluded. The number of transcripts with non-zero read counts in each pairwise comparison is denoted by n. The Spearman rank correlation coefficient for each pairwise comparison is denoted by rho. (b) Principal Component Analysis (PCA) plot of the 12 samples. Regularized log-transformed read counts were used as input and the samples are spanned in the two-dimensional plane by their first two principal components. The proportion of the variance explained by each component is displayed in the respective axis.

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