Department of Chemistry, University at Albany, SUNY, 1400 Washington Ave., Albany, NY 12222, USA.
Chem Soc Rev. 2011 Jul;40(7):4049-76. doi: 10.1039/c0cs00212g. Epub 2011 Apr 12.
In the past decade, the tendency to move from a global, one-size-fits-all treatment philosophy to personalized medicine is based, in part, on the nuanced differences and sub-classifications of disease states. Our knowledge of these varied states stems from not only the ability to diagnose, classify, and perform experiments on cell populations as a whole, but also from new technologies that allow interrogation of cell populations at the individual cell level. Such departures from conventional thinking are driven by the recognition that clonal cell populations have numerous activities that manifest as significant levels of non-genetic heterogeneity. Clonal populations by definition originate from a single genetic origin so are regarded as having a high level of homogeneity as compared to genetically distinct cell populations. However, analysis at the single cell level has revealed a different phenomenon; cells and organisms require an inherent level of non-genetic heterogeneity to function properly, and in some cases, to survive. The growing understanding of this occurrence has lead to the development of methods to monitor, analyze, and better characterize the heterogeneity in cell populations. Following the trend of DNA- and protein microarrays, platforms capable of simultaneously monitoring each cell in a population have been developed. These cellular microarray platforms and other related formats allow for continuous monitoring of single live cells and simultaneously generate individual cell and average population data that are more descriptive and information-rich than traditional bulk methods. These technological advances have helped develop a better understanding of the intricacies associated with biological processes and afforded greater insight into complex biological systems. The associated instruments, techniques, and reagents now allow for highly multiplexed analyses, which enable multiple cellular activities, processes, or pathways to be monitored simultaneously. This critical review will discuss the paradigm shift associated with cellular heterogeneity, speak to the key developments that have lead to our better understanding of systems biology, and detail the future directions of the discipline (281 references).
在过去的十年中，从全球、一刀切的治疗理念转向个性化医学的趋势部分基于疾病状态的细微差异和亚分类。我们对这些不同状态的了解不仅源于诊断、分类和对整个细胞群体进行实验的能力，还源于允许在单细胞水平上对细胞群体进行询问的新技术。这些与传统思维的背离是由于认识到克隆细胞群体具有许多表现为显著非遗传异质性水平的活动。克隆群体从定义上讲起源于单个遗传起源，因此与遗传上不同的细胞群体相比，被认为具有高度的同质性。然而，单细胞水平的分析揭示了一个不同的现象；细胞和生物体需要一定水平的非遗传异质性才能正常运作，在某些情况下，为了生存。对这种现象的认识不断加深，导致了开发监测、分析和更好地表征细胞群体异质性的方法。继 DNA 和蛋白质微阵列之后，已经开发出能够同时监测群体中每个细胞的平台。这些细胞微阵列平台和其他相关格式允许连续监测单个活细胞，并同时生成单个细胞和平均群体数据，这些数据比传统的批量方法更具描述性和信息量。这些技术进步有助于更好地理解与生物过程相关的复杂性，并深入了解复杂的生物系统。相关的仪器、技术和试剂现在允许进行高度多重分析，能够同时监测多个细胞活动、过程或途径。这篇综述将讨论与细胞异质性相关的范式转变，探讨导致我们更好地理解系统生物学的关键发展，并详细介绍该学科的未来方向（281 篇参考文献）。
