Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland.
Bioinformatics. 2012 Nov 15;28(22):2971-8. doi: 10.1093/bioinformatics/bts537. Epub 2012 Aug 31.
Biologistics provides data for quantitative analysis of transport (diffusion) processes and their spatio-temporal correlations in cells. Mobility of proteins is one of the few parameters necessary to describe reaction rates for gene regulation. Although understanding of diffusion-limited biochemical reactions in vivo requires mobility data for the largest possible number of proteins in their native forms, currently, there is no database that would contain the complete information about the diffusion coefficients (DCs) of proteins in a given cell type.
We demonstrate a method for the determination of in vivo DCs for any molecule--regardless of its molecular weight, size and structure--in any type of cell. We exemplify the method with the database of in vivo DC for all proteins (4302 records) from the proteome of K12 strain of Escherichia coli, together with examples of DC of amino acids, sugars, RNA and DNA. The database follows from the scale-dependent viscosity reference curve (sdVRC). Construction of sdVRC for prokaryotic or eukaryotic cell requires ~20 in vivo measurements using techniques such as fluorescence correlation spectroscopy (FCS), fluorescence recovery after photobleaching (FRAP), nuclear magnetic resonance (NMR) or particle tracking. The shape of the sdVRC would be different for each organism, but the mathematical form of the curve remains the same. The presented method has a high predictive power, as the measurements of DCs of several inert, properly chosen probes in a single cell type allows to determine the DCs of thousands of proteins. Additionally, obtained mobility data allow quantitative study of biochemical interactions in vivo.
Supplementary data are available at Bioinformatics Online.
生物物流学提供了数据,用于对细胞内运输(扩散)过程及其时空相关性进行定量分析。蛋白质的流动性是描述基因调控反应速率所需的少数几个参数之一。尽管要了解体内扩散限制的生化反应,需要尽可能多的天然形式的蛋白质的迁移率数据,但目前没有包含给定细胞类型中所有蛋白质扩散系数 (DC) 的完整信息的数据库。
我们展示了一种方法,用于确定任何分子(无论其分子量、大小和结构如何)在任何类型的细胞中的体内 DC。我们用大肠杆菌 K12 菌株蛋白质组的所有蛋白质(4302 条记录)的体内 DC 数据库为例,同时还举例说明了氨基酸、糖、RNA 和 DNA 的 DC。该数据库源自与分子量相关的粘度参考曲线 (sdVRC)。构建原核或真核细胞的 sdVRC 需要使用荧光相关光谱 (FCS)、光漂白后荧光恢复 (FRAP)、核磁共振 (NMR) 或颗粒追踪等技术进行约 20 次体内测量。sdVRC 的形状因生物体而异,但曲线的数学形式保持不变。所提出的方法具有很高的预测能力,因为在单个细胞类型中测量几个惰性、选择得当的探针的 DC,可用于确定数千种蛋白质的 DC。此外,获得的迁移率数据允许对体内生化相互作用进行定量研究。
补充数据可在生物信息学在线获取。