Proteomic Exploration of Membrane Curvature Sensors Using a Series of Spherical Supported Lipid Bilayers

Membrane
curvature-sensing (MCS) proteins recognize and regulate
the morphologies of biological membranes. As these proteins lack characteristic
sequence motifs in their primary structure, they are not instantly
recognizable by genomic databases. Overcoming this technological challenge
toward the agile identification of new proteins can promote the elucidation
of membrane morphological regulation. Here, for the selective identification
of MCS proteins, comparative proteomic analysis was performed using
different sizes of the spherical supported lipid bilayer (SSLB), which
consists of spherical SiO2 particles covered with a lipid
bilayer. Because of the presence of SiO2 core, the curvature
of the surrounding membrane is well-controlled and stable even on
a micron scale. To prove this concept, known membrane curvature-sensing
protein domains, Bin/Amphiphysin/Rvs (BAR) and Epsin N-terminal homology
(ENTH), were evaluated by performing a binding assay using SSLBs,
and the preferential binding to the highly curved membrane was confirmed.
Peripheral membrane proteins obtained from normal human dermal fibroblast
(NHDF) and human breast cancer (MDA-MB-231) cells were used in shotgun
proteomic analysis, and 786 and 949 proteins were identified from
SSLBs as lipid membrane binders, respectively. Statistical quantitative
analyses of proteins detected from each SSLB with a different size
revealed 118 candidate proteins, including 23 proteins unique to MDA-MB-231
cells, as membrane curvature sensors, including some previously reported
curvature sensors. Functional clustering analysis based on the KEGG
orthology database revealed that the protein-binding property to specific
high or low membrane curvature correlated with their functions. Further
investigation of candidate proteins will lead to the identification
of new MCS proteins as well as cancer biomarkers.

膜曲率感知蛋白（Membrane curvature-sensing, MCS）可识别并调控生物膜的形态。由于该类蛋白质的一级结构中缺乏特征性序列基序，无法通过基因组数据库直接快速鉴定。攻克这一技术瓶颈以实现新型MCS蛋白的高效鉴定，将有助于阐明膜形态的调控机制。本研究针对MCS蛋白的选择性鉴定需求，采用不同尺寸的球形支撑脂质双层（spherical supported lipid bilayer, SSLB）开展比较蛋白质组学分析；该体系由包覆脂质双层的球形SiO₂颗粒构成。由于SiO₂核的存在，周围膜的曲率可得到精准调控且稳定性优异，即便在微米尺度下亦能保持稳定。为验证这一研究思路，本研究针对已知的膜曲率感知蛋白结构域——Bin/Amphiphysin/Rvs（BAR）结构域与Epsin N端同源结构域（Epsin N-terminal homology, ENTH），采用SSLB开展结合实验，证实其可优先结合高曲率膜结构。本研究分别从正常人真皮成纤维细胞（normal human dermal fibroblast, NHDF）与人类乳腺癌细胞（MDA-MB-231）中提取外周膜蛋白，开展鸟枪法蛋白质组学分析，最终分别从SSLB体系中鉴定得到786种与949种脂质膜结合蛋白。对不同尺寸SSLB体系中检测到的蛋白质开展统计定量分析，共筛选得到118个膜曲率感知候选蛋白，其中包含23个仅在MDA-MB-231细胞中特异性表达的特有蛋白，且其中部分为已有文献报道的曲率感知蛋白。基于KEGG同源性数据库开展功能聚类分析，结果显示蛋白质对特定高/低曲率膜的结合特性与其功能密切相关。对候选蛋白的后续研究，将助力新型MCS蛋白的发现以及癌症生物标志物的筛选。