The Double-Stranded RNA Analog, Poly(I:C), Triggers Distinct Transcriptomic Shifts in Keratinocyte Subsets.
The Double-Stranded RNA Analog, Poly(I:C), Triggers Distinct Transcriptomic Shifts in Keratinocyte Subsets.
复制标题
DOI:
10.1016/j.jid.2022.03.015
复制
发表时间:
2022-10
影响因子:
6.5
通讯作者:
Nagao, K.
中科院分区:
文献类型:
--
作者:
Sakamoto, K.;Nagao, K.
Type I interferons (IFN) responses during viral infections activate host-protective immunity, but it may also trigger autoimmune cascades in lupus erythematosus and psoriasis (Illescas-Montes et al., 2019, Wang et al., 2021). Aspects of antiviral immunity can be modeled in mice via intraperitoneal injection of the double-stranded RNA analog, poly (I: C), which provokes systemic type I IFN production (Kühn et al., 1995). Utilizing this approach, we recently reported that innate epithelial barrier during a type I IFN response was bolstered by ADAM10-Notch signaling pathway in upper hair follicles, infundibulum (IFD) and isthmus (ISM)(Sakamoto et al., 2021). However, the transcriptomic landscape of keratinocyte subsets during type I IFN responses has not been systematically explored, the understanding of which could deepen our insight on how keratinocytes contribute to inflammation. Thus, we subjected C57BL/6 mice to one-time intraperitoneal injection with 200 μg of poly (I: C) or saline, prepared epidermal singlecell suspensions (Sakamoto et al., 2022), and sorted interfollicular epidermis (IFE) and the bulge (Figure 1a) to perform RNA-sequencing. Obtained data were analyzed with our recently reported RNA-sequencing data on the IFD and ISM, GSE18083 (Sakamoto et al., 2021). GSE180803 and GSE180435 from this study were sequenced simultaneously. All experiments procedures were approved by the NIAMS Animal Care and Use Committee. Data processing and gene expression analyses were performed utilizing Partek® Flow®. Expression levels of marker genes used for sorting revealed that keratinocyte subsets were properly acquired (Figure 1b). Generation of a Venn diagram for genes expressed at
登录
查看更多内容
影响因子:
32.4
作者:
Sakamoto K;Jin SP;Goel S;Jo JH;Voisin B;Kim D;Nadella V;Liang H;Kobayashi T;Huang X;Deming C;Horiuchi K;Segre JA;Kong HH;Nagao K
通讯作者:
Nagao K
影响因子:
3.6
作者:
Wang WM;Li F;Jin HZ
通讯作者:
Jin HZ
影响因子:
5.4
作者:
Rasmussen, Simon B.;Sorensen, Louise N.;Paludan, Soren R.
通讯作者:
Paludan, Soren R.
影响因子:
11.8
作者:
Gonzales KAU;Fuchs E
通讯作者:
Fuchs E
影响因子:
4.4
作者:
Tsoi, Lam C.;Hile, Grace A.;Kahlenberg, J. Michelle
通讯作者:
Kahlenberg, J. Michelle