Designer of life

What does the decoding of the genome give?

Sergey Medvedev: When I was a child and a young man, I remember how the newspapers were constantly trumpeted: something is about to be deciphered by the human genome when all these cubes and bricks will become clear ... And now the human genome is deciphered-what's next? A science appears called "Bioinformatics". What is it? Is a person deciphered by the human gene, Lego from which human life has been created? Our guest is Mikhail Gelfand , bioinformatics, head of the master's program "Biotechnology" Skoltha , Deputy Director of the Institute for Problems of Information RAS Information .

Mikhail Gelfand: I am still a professor at the Faculty of Computer Sciences of the Higher School of Economics and the Faculty of Bioenginery and Bioinformatics of Moscow State University.

Sergey Medvedev: As I understand it, the genome has three billion letters. We know the code - what can we do with this code? This is a kind of cook book of life, can we now prepare a person, a homunculus from a test tube?

Life knows how to reproduce itself according to the recipes contained in this book

Mikhail Gelfand: This is a cook book of life in the sense that life is able to reproduce itself according to the recipes that are contained in this book. We do not know how, in this sense we are bad cooks.

In general, this metaphor with decoding and reading the genome is not very successful, because decoding involves understanding, but we still understand quite poorly. The DNA inheritance molecule that was in a living cage, and then in the test tube, we have learned to reproduce on the computer, we know in what order the letters in this molecule are combined. But understanding of meaning is a slightly different thing.

Bioinformatics appeared as an independent science exactly when biology gradually began to turn from science working with individual objects into science, in which there is a lot of data. At this moment, there is a need to store, comprehend, analyze this data and do something with it.

Sergey Medvedev: What about what years?

Mikhail Gelfand: In 1977, they developed methods for determining the sequence of DNA (I specifically say: not "decryption", but "definition of sequence"). Bioinformatics began to emerge, apparently, in the early 80s. I was terribly lucky: when I graduated from the university in 1985, there was such a wonderful area in which it was not necessary to teach anything, it began from scratch, it was possible to take and do it. So very rarely happens in history.

Sergey Medvedev: Does it use mathematical methods more in it?

Bioinformatics began to emerge in the early 80s

Mikhail Gelfand: Methods in it are mathematical in the following sense: you need to think. There, in some places there are beautiful algorithms, beautiful statistics, but, in principle, mathematics there is quite trivial, there are no mathematical magic sticks there. We need to keep the skill in your head a lot and try to explain it differently, and the second skill is to ask simple questions. In this sense, in this sense, a mathematical education was very useful for me, not so much, maybe education as communication with my grandfather Israel Moiseevich Gelfand, who was a mathematician and worked a lot in experimental biology.

Sergey Medvedev: Now the genome is recorded, the sequence is determined - what can we do from this? I heard there is a new technology: we can take some kind of genes chain and fix it, insert a good place instead. That is, we can operate with these letters?

Mikhail Gelfand: CRISPR is a genetic engineering technique, one of the very advanced, very modern technologies that allows you to make very accurate and specific manipulations.

People simply had more opportunities. In principle, people knew how to insert and remove genes before, it was just harder to experimentally, not any manipulations were technically feasible. A set of tools has expanded now. It was possible to build houses, as in Sparta, only with an ax, and now there is still a saw and even a jigsaw, you can cut out some beautiful platbands. In this sense, the technological promotion is very large, but so far not very substantial. We understand some things: that there is a simple monogenic disease in which one single gene is broken-it is clear that if it is repaired, there will be a normal embryo.

Sergey Medvedev: And this is already being treated?

People just had more opportunities

Mikhail Gelfand: No, this is not treated, it is impossible to manipulate with human embryos - it is simply prohibited by law.

Sergey Medvedev: But, as I understand it, it moves. In England, they allowed - with embryos up to 11 days ...

Mikhail Gelfand: In China, they will not even ask anyone. You cannot brake the rink by laying turtles under it: it is a pity for turtles, but there will be nothing. In this sense, of course, this will move, but humanity needs to be comprehended. This is a really serious thing that requires understanding.

She is not the first. When genetic engineering only began in the mid-70s, when it became clear that genomes could be manipulated (then even bacterial), there was already a serious problem: for example, they were afraid that they would accidentally make some superbacteria, and she would eat everyone. There were special conferences where the rules were developed, what we are doing and what we do not. Every new set of tools expands opportunities, increases responsibility, and it must be meaningful.

Sergey Medvedev: raises ethical questions ...

Mikhail Gelfand: And if we talk about bioinformatics, returning to what you asked, then there is a slightly different story. There are two aspects. It turned out that we can answer quite a few classical biological questions simply in the computer.

I do a lot of bacteria genomics. There are a lot of bacteria with which one experience was made in their life, namely: they determined the sequence of the genome. We know quite a bit about them: what they eat, what they can’t eat, how they breathe, what they need to add to Wednesday, without which they cannot survive, but they themselves cannot do, and so on.

Sergey Medvedev: How is it easier than the bacteria genome compared to human genome?

Every new set of tools expands opportunities and increases responsibility

Mikhail Gelfand: This is not so critical. We have a 30% common genes with E. coli. By the number of genes, a typical bacterium is thousands, and a person is 25 thousand.

Sergey Medvedev: Do you know entirely what gene is responsible for the bacteria for?

Mikhail Gelfand: Not entirely, but we know a lot.

Sergey Medvedev: much more than about a person?

Mikhail Gelfand: As a percentage - of course.

The second thing that appeared (and this, again, is associated with technological development in experimental biology) and requires comprehension in bioinformatics is that we can look at the whole cage. A classic thing: a graduate student studies some kind of protein, he knows the partners of this protein, knows how this protein interacts with DNA, if it interacts with it, knows when the gene of this protein turns on. This is such a full -fledged dissertation, several scientific articles about one protein. And then methods appear that allow you to answer the same questions for all proteins at once. For the first time, an integral picture of how a cell is arranged; She is now very imperfect.

Sergey Medvedev: There is a protein that is unfamiliar to you, but you can predict, looking at his genome ...

We have a 30% of the total genes with an E.

Mikhail Gelfand: These are two different questions. We can predict the functions of proteins without doing any experiments with them. This is a beautiful bioinformatics based on all evolutionary considerations.

Sergey Medvedev: based on his genetic profile?

Mikhail Gelfand: Squirrel is what is encoded in the gene, so it’s better to talk about the gene: based on whom this gene lies nearby, to whom this protein is similar from at least a little known, how it is regulated when it turns on and turns off.

Sergey Medvedev: The same thing can probably be done about a person?

Mikhail Gelfand: This is more difficult. Theoretically, you can.

Sergey Medvedev: Look at the genome of a person on an embryonic level and say: a genius will grow up or a person with Down syndrome will grow.

Mikhail Gelfand: This is a story about the fact that the protein function is generally unknown, did not know anything about it at all, and we can predict it. And what you are talking about is a well-known set of proteins, but with some variations is a slightly different story.

Sergey Medvedev: A person consists of famous proteins.

Mikhail Gelfand: Partially known, partially - no. It turned out that we have a lot of heterogeneous information about how a cell is arranged. The information is very imperfect, each individual small fact can easily be incorrect, but in the aggregate they are still correct. And from this you can try to describe the whole cage.

Molecular biology has been scolded by philosophers for a very long time for the fact that it is reductionist science

Molecular biology has been scolded by philosophers for a very long time for the fact that it is reductionist science. Here you look at the elephant in parts: someone studies the leg, someone-the tail, someone-the trunk, and no integral picture is folded. Now she first begins to take shape. One of the paradoxical results of this is that our knowledge and understanding in the absolute sense increase very quickly. In biology, the progress is amazing: we know much more than we knew 10 or 20 years ago, not even at times, but by magnitude more.

But the area of ignorance increases even faster. That is, our relative knowledge is actually decreasing, since it becomes clear that there are such expanses, about which ten years ago it just never occurred to us that this happens. And now we see that it is, but we do not know what to do with it. This is terribly cool.

Mikhail Gelfand

Who will have Down syndrome is understandable: an extra chromosome. But who will be and who will not be a genius, we do not know how to predict, and thank God. We even know how to predict growth.

Sergey Medvedev: Doesn't this information accumulate?

Mikhail Gelfand: It goes, of course.

Sergey Medvedev: Is it possible, say, to compare the behavior of a person, his profile in social networks with his genetic profile?

Mikhail Gelfand: I don’t know about this, but psychological features are partially determined by the genome, and they can be predicted a little.

Sergey Medvedev: Partly - genome, partially - society.

The psychological features of a person are partially determined by the genome, and they can be a little predictable

Mikhail Gelfand: A society, some life circumstances ... In genetics, this is a developed thing, you can quantify the contribution of genetic factors in a particular sign. Let's take someone alone-me. I have the same genomes in all cells, and my cells are different.

Sergey Medvedev: That is, at some point, genomes understand which cell to develop in?

Mikhail Gelfand: At some point, the cell understands that it should become the predecessor of the epithelium or nervous system, or liver, or something else. After the first divisions, all cells are the same, the genes in them work the same way, and then begin to work differently. The key thing is actually not the genes themselves: I and the chimpanzees have 50% proteins are the same, and those that are different, differ in one letter.

Sergey Medvedev: That is, the question is where the program that at some point tells the cell that it should develop into a person or in a chimpanzee, and in a person in the brain or to the liver.

Mikhail Gelfand: He is there, in genes, but the key thing is not the genes themselves, but how they turn on and turn off. And this is the most interesting thing that is happening in biology now.

Sergey Medvedev: Is there a program that turns on and off?

There are mutations when Drosophil has a leg instead

Mikhail Gelfand: Of course. Drosophile is well known. Drosophila is simple, her germ is also simple ... No, Drosophila is complex, but the early stages of its development are very well described in quantitatively at the level of models. For example, you can predict the results of mutations. There are mutations when Drosophil has a leg instead of a mustache. At the same time, it is known in which gene mutation, what is broken, and this can be simulated-how the predecessor cells are mistaken.

Sergey Medvedev: Can I fix it with new technologies?

Mikhail Gelfand: It is possible, but only at the embryo. When a leg or an extra pair of wings grew, you can’t fix it.

Sergey Medvedev: What can this bring in a practical sense? Say, what is interested in every person is the fight against cancer ... With this stunning CRISPR technology, the Chinese seem to try to fight lung cancer. As I understand it, in this technology, a bacterium, when it sees a fragment of broken DNA, takes a piece of healthy bacteria and replaces the broken chain of healthy.

Mikhail Gelfand: Yes, only an interesting question of what is happening with a healthy bacterium ... No, not so. CRISPR/CAS systems are bacterial immunity, a slightly different thing. When the bacterium infects the virus, if he did not have time to kill it, the war begins there, the virus switches some bacterial systems, breaks the bacterial genetic program and switches the bacterium to the production of new viruses. Actually, all viruses do this: both bacterial and human, and any. There is a system that allows bacteria if the virus did not have time to kill it at the very beginning, cut a piece of DNA of the virus and use it as a sample during the next attack of the same virus.

Sergey Medvedev: The bacterium instills itself with this virus.

A typical sign of cancer - when the genes that work at the embryonic stages begin to work in adult fabrics

Mikhail Gelfand: In a sense, yes. And then it turned out that there is a protein that is able to cut a piece and purposefully insert it somewhere, and you can use the same enzyme for genetic engineering purposes.

I don’t really understand about such cancer therapy: when you have billions of cells, how are you going to integrate the correct system in each of them? I don't understand how to do it technically. This can be done to treat genetic defects at the embryo stage when there is one cage.

With cancer, the story is a little different, there is really very significant progress. It became clear that what we took for the same disease was actually at the molecular level - different diseases, and targets for therapy should also be different. Cancer was first classified simply in place: there was lung cancer, stomach cancer, skin cancer. Then histology began. When they began to look at the structure of the tumor, at what cells it consists of, diagnoses of the type of "small lung cancer" began. Then biochemistry began, some markers began to watch, it crushed even further.

And now we can see what, in fact, mutations have occurred. You take a sample from a cancer tumor and a sample from the same normal fabric, and see how they differ. They are very different, because with cancer everything breaks, errors begin to accumulate very quickly. There are special terms-“drivers” and “passengers”: some of these mistakes are passengers, they turned out by chance, and some were drivers, they, in fact, led to rebirth.

There are completely practical things there, because, for example, it is clear that some crayfish that considered one disease must be treated differently. And vice versa, if you have different crayfish, but they have the same molecular breakdown, then you can try to use a medicine effective against one.

Sergey Medvedev: Is this a breakdown at the genetic level, some kind of gene is knocked out?

Mikhail Gelfand: either knocked out, or, conversely, began to work too intensively. A typical sign of cancer - when genes that work at the embryonic stages begin to work in adult fabrics. These cells begin to share uncontrollably. Quite many crayfish - this is actually rebirth, degradation back in time.

Bioinformatics is not a science in the same sense in which it is not electron microscopy - this is a set of admission

I immediately want to emphasize: I'm not a doctor, I know about it as a biologist and a person who reads a little review. I'm just very afraid to disappoint people. There is always a balance between successes in science and a practical issue - for those who go to be treated tomorrow. These are experimental things. There is a single example when it worked. But it is clear that it is in this direction that everything will happen.

Sergey Medvedev: If you look at medical use, do you see that genetic engineering, genetic therapy will already go? Now, as I understand it, on individual autoimmune diseases it is clear that one gene is broken.

Mikhail Gelfand: This, rather, on the contrary, is a defect in the immune system, an knocked out immune system. They are trying to treat it.

Sergey Medvedev: Immunodeficiency at the genetic level?

Mikhail Gelfand: This is due to the specifics of the immune system. There, cells are divided all the time, new clones arise all the time. Even if you have everything defective, but you have made a small number of repaired predecessor cells, they can replace the entire immunity system, give rise to it again. This is due to the specifics of how the immune system is arranged. Она в этом смысле потрясающе пластична.

Сергей Медведев: Бактерия создала себе некую прививку, иммунитет?

Михаил Гельфанд: Да, но там немножко другое. Опять-таки, когда речь идет об иммунодефиците, это означает, что вообще нет каких-то классов клеток, потому что сломан тот ген, который должен работать, когда эти клетки созревают. Если вы почините этот ген каким-то предшественникам, они созреют в эти клетки, то они дадут начало всей этой большой иммунной картине.

Сергей Медведев: Есть же еще, как я понимаю, вычислительная эволюционная биология. Вы можете откатиться назад и посмотреть ген древнего человека?

Наши отличия от мышки начинаются на первых стадиях эмбриона, а потом уже все фиксируется

​ Михаил Гельфанд: Это почти самое интересное. Биоинформатика – это не наука в том же смысле, в котором не является ею электронная микроскопия, – это набор приемов. Научная часть биоинформатики, это, во-первых, то, что связано с биологией развития, а во-вторых, это молекулярная эволюция, и там можно делать разные чудесные вещи.

Мы гораздо лучше понимаем, как это происходило. Наши отличия от мышки начинаются на первых стадиях эмбриона, а потом уже все фиксируется. Одни и те же гены работали немножко в разных комбинациях. Эта мечта описать разнообразие животных с пониманием того, как они возникали, идет еще от Геккеля . Геккель многое подтасовывал, за что его и ругают, но сама по себе идея очень правильная. Чтобы понять отличие человека от мыши, надо смотреть не взрослого человека и взрослую мышь, а эмбрионы на первых стадиях. Это сейчас становится реальным.

Вторая вещь: мы понимаем, кто кому родственник, просто сравнивая геномы. Понятно: чем меньше отличий, тем ближе родство. Это очень простая идея, ее можно алгоритмизировать. Наши представления об эволюции живых существ вообще довольно сильно поменялись. Традиционно грибы всегда изучали на кафедре низших растений, а на самом деле грибы никакие не низшие растения, а наши ближайшие родственники. Нам с грибами цветочки – двоюродные. Из этого следует, что многоклеточность возникала много раз независимо, а это уже очень принципиальный вопрос. Когда мы с вами учились в школе, были бактерии, потом были простейшие, а потом простейшие начали слипаться и получились многоклеточные, а потом многоклеточные разделились на растения и животных. Были какие-то низшие растения, грибы и высшие растения – розы и лютики. А на самом деле не так: было много разных одноклеточных, и в этих разных линиях одноклеточных несколько раз независимо возникала многоклеточность.

Сергей Медведев: Человек как высшая форма многоклеточности?..

Грибы никакие не низшие растения, а наши ближайшие родственники

​ Михаил Гельфанд: Я не знаю, в каком смысле высшая. Если смотреть по разнообразию тканей, то все млекопитающие в одну цену. Если смотреть по сложности нервной системы, то нас надо сравнивать с осьминогами. Но если кому-то приятно быть антропоцентристом, то на здоровье, я не возражаю.

Наше представление о происхождении человека очень сильно поменялось. В каждом из нас 2% неандертальца, а еще были денисовцы ( денисовский человек ), про которых вообще никто не подозревал. На самом деле в Евразии 40 тысяч лет назад было три независимых ветки человечества, они скрещивались во всех сочетаниях, и остатки этих скрещиваний мы видим в геноме.

Сергей Медведев: Это вы все берете по останкам того, что осталось на стоянках?

Михаил Гельфанд: Это старая ДНК и анализ современной ДНК разных людей. По-моему, это очень здорово. Это очень сильно перекашивает мою картину мира.

Сергей Медведев: Михаил, вы нас озадачили. 2% неандертальцев, зато очень много общего с грибами, с цветами… Действительно, здесь идет речь о кубиках, из которых устроена жизнь. Сейчас, как я понимаю, вы эти кубики комбинируете в разном порядке, смотрите, какие признаки произошли и в онтогенезе, и в филогенезе, как развился эмбрион отдельного человека, как вообще развилась жизнь на Земле.

Михаил Гельфанд: Да. Мы делаем это в компьютере, а экспериментаторы делают в клеточках.

Мы живем в восхитительное время!

​ Сергей Медведев: Мы живем в восхитительное время! Будем надеяться, что эти эксперименты приведут и к созданию лекарств от рака и СПИДа.

Михаил Гельфанд: Вообще-то лекарство от рака уже создали.

Сергей Медведев: Я имею в виду понимание механизмов действия.

Михаил Гельфанд: А с диагнозом СПИД люди живут и живут на современных лекарствах.

Сергей Медведев: Вопрос не о лекарствах, а о том, чтобы лечить это на генном уровне. Это дальнейшее пожелание.