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Identification of high affinity aptamers using massively parallel DNA sequencing

使用大规模并行 DNA 测序鉴定高亲和力适体

基本信息

批准号：
BB/I013245/1
负责人：
Andrew Cossins
金额：
$ 28.6万
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2011
资助国家：
英国
起止时间：
2011 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FI013245%2F1
关键词：
Identification affinity aptamers using massively

项目摘要

The vast majority of molecules are far too small to be seen with the unaided eye. In most cases the only way to detect them is with other molecules that fit round them like a key fits round a lock. The human body produces molecules like this called antibodies. When we are invaded by harmful bacteria antibodies stick to them and mark them out for destruction. Many years ago scientists realized that they could use antibodies to detect almost any kind of molecule. This opened the door to a whole range of new technologies in medicine, healthcare and research. DNA is familiar to most people as the molecule that contains the information for living things, but it can also fold into three-dimensional shapes that resemble antibodies. The shape of these structures depends on the sequence of information encoded in the DNA. Twenty years ago scientists speculated that it might be possible to combine the information properties of DNA with its ability to recognize other molecules. In a process that resembles natural selection they mixed many different DNA sequences with a single type of protein molecule. Most of them did not stick, but quite a few did, some of them more tightly than others. The scientists then used the information in DNA to make many copies of the sequences that stuck and mixed this amplified population with the protein again. This time some of the DNA that survived the first round of selection was excluded by sequences that stuck to the protein more tightly. These sequences were discarded while those that stuck were amplified to produce an even more enriched population. After many rounds of selection and amplification only a few sequences remained. The scientists called these surviving sequences aptamers after a Latin word that describes the way that other molecules fit into them like a key fits into a lock. Aptamers have many advantages over antibodies. They are smaller and more robust, and once the information encoded in an aptamer is known large amounts of it can be made inexpensively. With advantages like these it might be thought that aptamers would have supplanted antibodies long ago, but twenty years after their discovery they are still the poor-relation. The problem is that aptamers do not stick to other molecules as tightly as antibodies and recently scientists have found out why. The natural selection process used to identify them not only eliminates sequences that do not stick to the protein at all but also sequences that stick to it less strongly than the strongest. If these weaker sequences are joined to the strongest sequence a new aptamer is produced that sticks to the protein hundreds of times more tightly than the original. Technologies that read the information encoded in DNA are known as sequencing technologies. When aptamers were first discovered twenty years ago it required a great deal of effort to read the sequence of a single aptamer even though it contained less than a hundred bits of information. Now by contrast the entire 3 billion bits of information in the human genome can be read in only a few days. These advances have made it feasible to read the information encoded in all the DNA sequences that bind to a protein and not just the few that bind to it most strongly. This is what we will do in this project. When we have read all the sequences we will assemble them into a vast table using the same computing techniques that scientists use to understand the human genome. This table will tell us how sequences can be linked together to make an aptamer that sticks to molecules as tightly as an antibody. By making aptamers that stick as tightly as antibodies we will break down the barrier that is preventing their other advantages from being used. The will lead to new and improved tests that allow scientists and physicians to detect many different kinds of molecule in the same minute spot of blood, and new drugs that seek out and destroy cancer cells and harmful viruses.

绝大多数分子都太小，无法用肉眼看到。在大多数情况下，检测它们的唯一方法是使用围绕它们的其他分子，就像钥匙围绕锁一样。人体产生这样的分子，称为抗体。当我们受到有害细菌入侵时，抗体会粘附在它们上并标记它们以进行破坏。许多年前，科学家们意识到他们可以使用抗体来检测几乎任何类型的分子。这为医学、保健和研究领域的一系列新技术打开了大门。 DNA 是大多数人所熟悉的包含生物信息的分子，但它也可以折叠成类似于抗体的三维形状。这些结构的形状取决于 DNA 中编码的信息序列。二十年前，科学家推测或许可以将 DNA 的信息特性与其识别其他分子的能力结合起来。在一个类似于自然选择的过程中，他们将许多不同的 DNA 序列与单一类型的蛋白质分子混合。大多数都没有粘住，但也有不少粘住了，其中一些比其他更紧。然后，科学家们利用 DNA 中的信息复制了许多序列副本，并将这些扩增的群体再次与蛋白质混合在一起。这次，一些在第一轮选择中幸存下来的 DNA 被更紧密地粘附在蛋白质上的序列排除了。这些序列被丢弃，而那些被卡住的序列被扩增以产生更加丰富的群体。经过多轮选择和扩增后，只剩下少数序列。科学家们根据一个拉丁词将这些幸存的序列称为适体，该词描述了其他分子插入其中的方式，就像钥匙插入锁一样。与抗体相比，适体具有许多优点。它们更小、更稳健，一旦知道适体中编码的信息，就可以廉价地制造大量适体。凭借这些优势，人们可能会认为适配体很久以前就已经取代了抗体，但在它们被发现二十年后，它们仍然是劣势。问题在于适体不像抗体那样紧密地粘附在其他分子上，最近科学家们发现了原因。用于识别它们的自然选择过程不仅消除了根本不粘附在蛋白质上的序列，而且还消除了粘附力不如最强的序列。如果这些较弱的序列与最强的序列连接，就会产生一个新的适体，它与蛋白质的粘附力比原始适体牢固数百倍。读取 DNA 编码信息的技术称为测序技术。二十年前首次发现适配体时，尽管单个适配体包含的信息不到一百位，但仍需要付出很大的努力来读取单个适配体的序列。相比之下，现在只需几天就可以读取人类基因组中全部 30 亿比特的信息。这些进步使得读取与蛋白质结合的所有 DNA 序列中编码的信息成为可能，而不仅仅是与蛋白质结合最强的少数 DNA 序列。这就是我们将在这个项目中做的事情。当我们读取了所有序列后，我们将使用科学家用于理解人类基因组的相同计算技术将它们组装成一个巨大的表。该表将告诉我们如何将序列连接在一起以形成像抗体一样紧密地粘附在分子上的适体。通过制造像抗体一样紧密粘附的适体，我们将打破阻碍其其他优势被利用的障碍。这将带来新的和改进的测试，使科学家和医生能够检测血液中同一微小点中的许多不同种类的分子，以及寻找并消灭癌细胞和有害病毒的新药物。