five

Proteases Shape the Chlamydomonas Secretome: Comparison to Classical Neuropeptide Processing Machinery

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://www.omicsdi.org/dataset/pride/PXD010945
下载链接
链接失效反馈
官方服务:
资源简介:
The recent identification of catalytically active peptidylglycine -amidating monooxygenase (PAM) in Chlamydomonas reinhardtii, a unicellular green alga, suggested the presence of a PAM-like gene and peptidergic signaling in the last eukaryotic common ancestor (LECA). Homologs of prototypical neuropeptide precursors and essential peptide processing enzymes (subtilisin-like prohormone convertases and carboxypeptidase B-like enzymes) were identified in the C. reinhardtii genome. Reasoning that sexual reproduction by C. reinhardtii requires extensive communication between cells, we used mass spectroscopy to identify proteins recovered from the soluble secretome of mating gametes and searched for evidence that the putative peptidergic processing enzymes were functional.After fractionation by SDS-PAGE, signal peptide-containing proteins that remained intact or were subjected to cleavage were identified. The C. reinhardtii mating secretome contained multiple matrix metalloproteinases, cysteine endopeptidases and serine carboxypeptidases, along with one subtilisin-like proteinase. Published transcriptomic studies support a role for these proteases in sexual reproduction. Multiple extracellular matrix proteins (ECM) were identified in the soluble mating secretome. Several pherophorins, ECM glycoproteins homologous to the Volvox sex-inducing pheromone, were present; most contained typical peptide processing sites and had been cleaved, generating stable N- or C-terminal fragments. Our data suggest that subtilisin endoproteases and matrix metalloproteinases similar to those important in vertebrate peptidergic and growth factor signaling play an important role in stage transitions during the life cycle of C. reinhardtii.
创建时间:
2019-07-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作