On-Chip Expression of Transcription Factors and Force-Based Interaction Analysis with DNA

蛋白质调节基因表达，其产物可能反过来调节其他基因。一个高度纠缠的多组件网络出现了，生活就建立在这个网络之上。更不用说，要破译这一网络，就需要追踪越来越多的互动伙伴，并对他们进行量化，以便确定他们互动的质量。过去开发了各种高度平行的分析方法，其中大多数由于缺乏足够的灵敏度和/或选择性而受到阻碍。需要更多给定交互作用的独立测量值来扩展这些交互作用所投射到的参数空间。这里的提议建议测量蛋白质和DNA之间的相互作用力，并通过这一方法提供一个额外的参数来表征相互作用。提出了一种高度并行的芯片格式，它将蛋白质在软橡胶微流控中的表达与基于分子力天平的荧光结合力测量相结合。作为原理的证明，来自酵母的一组转录因子将与10个不同的靶序列和6个不同的解结力的矩阵进行测试，并与文献结果进行比较。预计整合密度至少扩大一个数量级，从而能够对大量相互作用伙伴进行定量筛选，特别是对弱粘结剂进行并行筛选。然后，我们将扩大我们的合作，基于相互作用力来表征果蝇转录因子。

Proteins regulate gene expression and their products may in turn regulate other genes. A highly en-tangled multi-component network arises upon which life is built. Needless to mention that deciphering this network requires the tracing of an exceedingly growing number of interaction partners and their quantification in order to characterize the quality of their interactions. A variety of highly parallel assays were developed in the past and most of them were hampered by a lack of sufficient sensitivity and/or selectivity. More independent measured values of a given interaction are needed to expand the parameter space into which these interactions are projected. The proposal here suggests to measure the interaction forces between proteins and DNA and by means of this to provide an additional parameter that characterizes the interaction. A highly parallel chip format is proposed which combines the expression of the proteins in soft rubber micro-fluidics with fluorescence-based binding force measurements via molecular force balances. As proof of principle a set of transcription factors from yeast will be tested against a matrix of ten different target sequences and for six different unbinding forces and compared to literature results. An expansion by at least one order of magnitude in integration density is envisioned which then allows the quantitative screening of a large number of interaction partners in particularly also weak binders in parallel. We will then expand our collaborations to characterize drosophila transcription factors based on interaction forces.