Frey J R, Kettman J R, Lefkovits I
Basel Institute for Immunology, Switzerland.
Appl Theor Electrophor. 1993;3(6):283-96.
In our effort to collect, organize and assemble data from lymphocyte cDNA libraries, we assign DNA restriction sites collectively to the spots on two-dimensional (2D) gel patterns. In order to test the efficiency and reliability of such an approach, we have modeled the restriction analysis of cDNA libraries with a panel of restriction endonucleases. The work has two parts. In the first, we have chosen 255 proteins from the EMBL data base and determined whether or not their coding sequences contain restriction sites for the enzymes of our choice. In order to apply a sufficient discriminatory power we decided to use a relatively large number of cleaving enzymes with low and high cutting frequencies. In total, 13 restriction enzymes were chosen, which could distinguish 2(13) or 8192 different restriction site combinations. We have compiled a table in which the absence or presence of restriction sites yields a pattern of 'zeros' and 'ones'. Such a restriction pattern can be read as a binary number. The binary numbers with maximally 13 digits would uniquely assign each of the 255 proteins if the nucleotide sequences would be truly at random. As the restriction sites are not randomly distributed, the 'typing' does not yield a unique assignment. The choice of sequences was not random either. In fact, there are some human nucleotide sequences which possess the same cut number (the decimal equivalent of the binary number representing the restriction pattern). In spite of this redundancy, 141 coding sequences could uniquely be distinguished by the above treatment. In the second part of the project we have used the above mentioned coding sequences to prepare two-dimensional maps (plots of charge vs size) of the same kind as one obtains from experimental 2D gels and submitted such a map together with 13 maps of restriction enzyme treated populations to a computer image analysis. Ideally, one would expect results (cut numbers) congruent to those obtained in the first part of the work. In the modeled system we were confronted with 2D maps which closely resembled the experimental situation (e.g. some spots were close together and overlapping) and instances of incorrect spot detection yielding 'false cut numbers'. From 255 proteins we were able to assign unequivocally 161 proteins. To implement the model in an actual experiment we will perform the digestion with the restriction enzymes in duplicate, and only spots assigned the same cut number upon the two independent treatments will be considered as carrying a valid restriction tag.
在我们从淋巴细胞cDNA文库收集、整理和汇集数据的过程中，我们将DNA限制性酶切位点集中分配到二维（2D）凝胶图谱上的各个点。为了测试这种方法的效率和可靠性，我们用一组限制性内切酶对cDNA文库的限制性分析进行了建模。这项工作分为两个部分。第一，我们从EMBL数据库中选择了255种蛋白质，并确定它们的编码序列是否含有我们所选酶的限制性酶切位点。为了具备足够的区分能力，我们决定使用相对大量的切割频率高低不同的切割酶。总共选择了13种限制性酶，它们可以区分2的13次方即8192种不同的限制性酶切位点组合。我们编制了一个表格，其中限制性酶切位点的有无产生了一个由“0”和“1”组成的模式。这样的限制性模式可以被看作是一个二进制数。如果核苷酸序列是真正随机的，那么最多13位数字的二进制数将唯一地分配255种蛋白质中的每一种。由于限制性酶切位点不是随机分布的，这种“分型”并不能产生唯一的分配。序列的选择也不是随机的。实际上，有一些人类核苷酸序列具有相同的切割数（代表限制性模式的二进制数的十进制等价物）。尽管存在这种冗余性，但通过上述处理仍可唯一区分141个编码序列。在项目的第二部分，我们使用上述编码序列制备了与从实验性2D凝胶获得的相同类型的二维图谱（电荷与大小的图），并将这样的图谱以及13个经限制性酶处理群体的图谱提交给计算机图像分析。理想情况下，人们会期望得到与工作第一部分获得的结果（切割数）一致的结果。在建模系统中，我们遇到了与实验情况非常相似的二维图谱（例如，一些点靠得很近且相互重叠）以及错误的点检测情况，从而产生“错误的切割数”。从255种蛋白质中，我们能够明确地分配161种蛋白质。为了在实际实验中应用该模型，我们将对限制性酶进行重复消化，并且只有在两次独立处理中被分配相同切割数的点才会被视为带有有效的限制性标签。
