Wang Degeng
Division of Cell Biology, Microbiology and Molecular Biology (CMM), Department of Biology, University of South Florida, Tampa, FL 33620, USA.
Comput Biol Chem. 2008 Dec;32(6):462-8. doi: 10.1016/j.compbiolchem.2008.07.014. Epub 2008 Jul 16.
Discrepancy between the abundance of cognate protein and RNA molecules is frequently observed. A theoretical understanding of this discrepancy remains elusive, and it is frequently described as surprises and/or technical difficulties in the literature. Protein and RNA represent different steps of the multi-stepped cellular genetic information flow process, in which they are dynamically produced and degraded. This paper explores a comparison with a similar process in computers-multi-step information flow from storage level to the execution level. Functional similarities can be found in almost every facet of the retrieval process. Firstly, common architecture is shared, as the ribonome (RNA space) and the proteome (protein space) are functionally similar to the computer primary memory and the computer cache memory, respectively. Secondly, the retrieval process functions, in both systems, to support the operation of dynamic networks-biochemical regulatory networks in cells and, in computers, the virtual networks (of CPU instructions) that the CPU travels through while executing computer programs. Moreover, many regulatory techniques are implemented in computers at each step of the information retrieval process, with a goal of optimizing system performance. Cellular counterparts can be easily identified for these regulatory techniques. In other words, this comparative study attempted to utilize theoretical insight from computer system design principles as catalysis to sketch an integrative view of the gene expression process, that is, how it functions to ensure efficient operation of the overall cellular regulatory network. In context of this bird's-eye view, discrepancy between protein and RNA abundance became a logical observation one would expect. It was suggested that this discrepancy, when interpreted in the context of system operation, serves as a potential source of information to decipher regulatory logics underneath biochemical network operation.
同源蛋白质和RNA分子丰度之间的差异经常被观察到。对这种差异的理论理解仍然难以捉摸,在文献中它经常被描述为意外和/或技术难题。蛋白质和RNA代表了多步骤细胞遗传信息流过程中的不同步骤,在这个过程中它们被动态地产生和降解。本文探讨了与计算机中类似过程的比较——从存储级别到执行级别的多步骤信息流。在检索过程的几乎每个方面都能发现功能上的相似之处。首先,它们具有共同的架构,核糖组(RNA空间)和蛋白质组(蛋白质空间)在功能上分别类似于计算机主内存和计算机高速缓存。其次,在这两个系统中,检索过程的功能都是支持动态网络的运行——细胞中的生化调节网络,以及在计算机中,CPU在执行计算机程序时所遍历的虚拟网络(CPU指令的网络)。此外,在信息检索过程的每个步骤中,计算机都实施了许多调节技术,目的是优化系统性能。这些调节技术的细胞对应物很容易识别。换句话说,这项比较研究试图利用计算机系统设计原则的理论见解作为催化剂来勾勒基因表达过程的综合视图,即它如何发挥作用以确保整个细胞调节网络的高效运行。在这个鸟瞰视角下,蛋白质和RNA丰度之间的差异成为了一个可以预期的逻辑观察结果。有人提出,当在系统运行的背景下解释这种差异时,它作为一种潜在的信息来源,有助于解读生化网络运行背后的调节逻辑。