计算生物学
编码
生物
鉴定(生物学)
蛋白质组学
人体微生物群
微生物群
工作流程
打开阅读框
肠道微生物群
人类蛋白质
生物信息学
细菌蛋白
人类微生物组计划
蛋白质组
基因组
人类基因组
计算机科学
肠道菌群
系统生物学
翻译后修饰
生物标志物发现
肽序列
进化生物学
模式生物
蛋白质组
蛋白质-蛋白质相互作用
人类健康
作者
Megan E. Davin,Júlia Ortís Sunyer,Luis F. Delgado,Steven Tavis,Tuesday Lowndes,Zainab Zafar,Jordan Caussin,Rashi Halder,Oskar Hickl,Cédric C. Laczny,Etienne Hanslian,Daniela Koppold,Anika Rajput-Khokhar,Nico Steckhan,Sebastian Schade,Jochen Schneider,Brit Mollenhauer,Andreas Michalsen,Patrick May,Robert L. Hettich
标识
DOI:10.1038/s41467-026-72762-5
摘要
Small open reading frames (smORFs), which encode proteins under 100 amino acids, represent an underexplored dimension of the human gut microbiome, despite growing evidence of their essential biological roles. Due to small size and poor annotation, smORFs are typically excluded from metagenomic/metaproteomic analyses. Here, we present a high-resolution multi-omic workflow that integrates smORF prediction into metaproteome searches and enables ultra-deep detection of smORF-encoded proteins (SEPs), without experimental size-based enrichment, utilizing state-of-the-art mass spectrometry instrumentation. Applied to human gut microbiomes, this approach resulted in the largest number of detected SEPs to date, allowing identification of over 25,000 SEPs in the metaproteome, alongside the measurements of the larger proteins. Our multi-omics integrative strategy is critical for advancing human metaproteome research. It also provides a generalizable strategy for comprehensive SEP discovery across diverse microbial ecosystems greatly expanding the previously hidden proteomic landscape.
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