RNAseq identifies distinct gene expression profiles in gBT-I isolated from SPF and GF animals.

Purpose: The aim of this study is to disentangle if microbiota influences the transcriptome of antigen-activated CD8+ T cells. Methods: gBT-I mRNA profiles from SPF and GF mice were generated by deep sequencing, in duplicates, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: The analysis of RNAseq data of gBT-I from SPF and GF mice lead to 371 differentially expressed genes (FDR < 0.05; fold change >2). GSEA enrichment analysis revealed depletion of memory T cells signatures in gBT-I from GF mice (Sarkar et al., 2008), and underrepresentation of OXPHOS-related genes. Conclusions: Our data shows that microbiota has an impact on the transcriptome of effector CD8+ T cells, in particular their memory and metabolism signature. in vitro activated and transferred gBT-I mRNA profiles of SPF and GF mice on d7 were generated by deep sequencing, in duplicate, using Illumina GAIIx.

研究目的：本研究旨在厘清微生物群是否对抗原激活的CD8+ T细胞转录组产生影响。
研究方法：本研究采用Illumina GAIIx平台对无特定病原体（SPF, Specific Pathogen Free）小鼠与无菌（GF, Germ Free）小鼠的gBT-I细胞mRNA转录组开展双生物学重复深度测序。对通过质量过滤的序列读数，将在转录本异构体水平采用两种方法进行分析：一是Burrows–Wheeler对齐工具（BWA）结合方差分析（ANOVA），二是TopHat结合Cufflinks。
研究结果：对SPF与GF小鼠来源的gBT-I细胞RNA测序数据进行分析后，共筛选得到371个差异表达基因（错误发现率FDR < 0.05，倍数变化>2）。基因集富集分析（GSEA, Gene Set Enrichment Analysis）结果显示，GF小鼠来源的gBT-I细胞中记忆性T细胞特征基因集富集程度降低（Sarkar等，2008），且氧化磷酸化（OXPHOS, Oxidative Phosphorylation）相关基因表达不足。
研究结论：本研究数据表明，微生物群可影响效应性CD8+ T细胞的转录组，特别是其记忆性及代谢相关特征。此外，本研究还对第7天的SPF与GF小鼠的体外激活并过继转移的gBT-I细胞进行了双生物学重复深度测序，获取其mRNA转录组数据。