Spatial Proteomics for Further Exploration of Missing Proteins: A Case Study of the Ovary

图谱 生物 蛋白质组学 计算生物学 卵巢 电池类型 蛋白质组 生物信息学 细胞 基因 遗传学 蛋白质表达
作者
Loren Méar,Thanadol Sutantiwanichkul,Josephine Östman,Pauliina Damdimopoulou,Cecilia Lindskog
出处
期刊:Journal of Proteome Research [American Chemical Society]
卷期号:22 (4): 1071-1079 被引量:3
标识
DOI:10.1021/acs.jproteome.2c00392
摘要

In the quest for "missing proteins" (MPs), the proteins encoded by the human genome still lacking evidence of existence at the protein level, novel approaches are needed to detect this challenging group of proteins. The current count stands at 1,343 MPs, and it is likely that many of these proteins are expressed at low levels, in rare cell or tissue types, or the cells in which they are expressed may only represent a small minority of the tissue. Here, we used an integrated omics approach to identify and explore MPs in human ovaries. By taking advantage of publicly available transcriptomics and antibody-based proteomics data in the Human Protein Atlas (HPA), we selected 18 candidates for further immunohistochemical analysis using an exclusive collection of ovarian tissues from women and patients of reproductive age. The results were compared with data from single-cell mRNA sequencing, and seven proteins (CTXN1, MRO, RERGL, TTLL3, TRIM61, TRIM73, and ZNF793) could be validated at the single-cell type level with both methods. We present for the first time the cell type-specific spatial localization of 18 MPs in human ovarian follicles, thereby showcasing the utility of the HPA database as an important resource for identification of MPs suitable for exploration in specialized tissue samples. The results constitute a starting point for further quantitative and qualitative analysis of the human ovaries, and the novel data for the seven proteins that were validated with both methods should be considered as evidence of existence of these proteins in human ovary.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Endeavor完成签到,获得积分10
刚刚
save完成签到,获得积分10
1秒前
Shawn完成签到,获得积分10
1秒前
顾矜应助一自文又欠采纳,获得10
2秒前
3秒前
自信的冬日完成签到,获得积分10
5秒前
JiahaoRao完成签到,获得积分10
6秒前
8秒前
8秒前
haru完成签到,获得积分10
8秒前
阿涵发布了新的文献求助10
8秒前
9秒前
阳光稀完成签到,获得积分10
10秒前
乐乐应助可靠强炫采纳,获得30
10秒前
lumcy发布了新的文献求助10
11秒前
拼搏的青雪完成签到,获得积分10
11秒前
布丁完成签到,获得积分10
11秒前
南亭完成签到,获得积分10
11秒前
hetao完成签到,获得积分10
11秒前
zzzzz完成签到,获得积分10
12秒前
科研通AI2S应助j736999565采纳,获得10
12秒前
Anany发布了新的文献求助10
12秒前
淡淡的若冰应助Ganlou采纳,获得10
13秒前
凪凪发布了新的文献求助10
13秒前
烟雨醉巷完成签到 ,获得积分10
13秒前
蔷薇完成签到,获得积分10
13秒前
儒雅的焦完成签到,获得积分10
13秒前
ytrewq完成签到 ,获得积分10
13秒前
丁莞完成签到,获得积分10
14秒前
xxx完成签到,获得积分10
15秒前
15秒前
16秒前
充电宝应助阿涵采纳,获得10
16秒前
勇往直前完成签到,获得积分10
16秒前
赛赛完成签到 ,获得积分10
17秒前
17秒前
自然芹发布了新的文献求助10
18秒前
不做大哥好多年完成签到,获得积分10
18秒前
喜悦香薇完成签到 ,获得积分10
18秒前
zhang完成签到,获得积分10
19秒前
高分求助中
Evolution 10000
CANCER DISCOVERY癌症研究的新前沿:中国科研领军人物的创新构想 中国专刊 500
Distribution Dependent Stochastic Differential Equations 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
Die Gottesanbeterin: Mantis religiosa: 656 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3158687
求助须知:如何正确求助?哪些是违规求助? 2809923
关于积分的说明 7884302
捐赠科研通 2468638
什么是DOI,文献DOI怎么找? 1314374
科研通“疑难数据库(出版商)”最低求助积分说明 630601
版权声明 602012