Department of Molecular Cell Physiology, Vrije Universiteit Amsterdam Amsterdam, Netherlands ; Manchester Centre for Integrative Systems Biology, The University of Manchester Manchester, UK ; Synthetic Systems Biology, University of Amsterdam Amsterdam, Netherlands.
Institute for Systems Biology Seattle, WA, USA ; Molecular and Cellular Biology Program, University of Washington Seattle, WA, USA.
Front Microbiol. 2014 Jul 22;5:379. doi: 10.3389/fmicb.2014.00379. eCollection 2014.
Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity - particularly activity of the human brain - with a phenomenon we call "intelligence." Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as "human" and "brain" out of the defining features of "intelligence," all forms of life - from microbes to humans - exhibit some or all characteristics consistent with "intelligence." We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo.
生物体通过许多组件之间的复杂相互作用而存在，这些组件组织成动态的、对环境有响应的网络，跨越多个尺度和维度。生物网络构成了一种信息和通信技术（ICT）：它们从细胞内外接收信息，整合和解释这些信息，然后激活响应。生物网络使细胞内的分子，甚至细胞本身，能够相互通信和与环境通信。我们已经习惯将大脑活动——特别是人类大脑的活动——与我们称之为“智能”的现象联系在一起。然而，四十亿年的进化可能已经选择了具有拓扑结构和动力学的网络，这些网络赋予了类似于这种智能的特征，尽管它们不在大脑的细胞间网络中。在这里，我们探讨了微生物中的大分子网络如何赋予智能特征，例如记忆、预期、适应和反思，我们回顾了当前对网络组织如何反映其被选择的环境所需的智能类型的理解。我们提出，如果我们将“人类”和“大脑”等术语从“智能”的定义特征中排除，那么从微生物到人类的所有生命形式都表现出一些或所有与“智能”一致的特征。然后，我们回顾了在全基因组数据产生和分析方面的进展，特别是在微生物方面，这些进展为微生物智能提供了一个视角，并提出了如何通过定量表征生物分子网络来为生物技术创造智能分子网络，可能会首先在计算机中，然后在活体中产生新的形式的智能。
