Ribosomal Quality Control

In order to demonstrate the validity of viewing cells as computers that are able to manipulate information, consider the following finding.

The Ribosome: Perfectionist Protein-maker Trashes Errors

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ScienceDaily (Jan. 9, 2009) — The enzyme machine that translates a cell's DNA code into the proteins of life is nothing if not an editorial perfectionist.

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It turns out, the Johns Hopkins researchers say, that the ribosome exerts far tighter quality control than anyone ever suspected over its precious protein products which, as workhorses of the cell, carry out the very business of life. "What we now know is that in the event of miscoding, the ribosome cuts the bond and aborts the protein-in-progress, end of story," says Rachel Green, a Howard Hughes Medical Institute investigator and professor of molecular biology and genetics in the Johns Hopkins University School of Medicine. "There's no second chance." Previously, Green says, molecular biologists thought the ribosome tightly managed its actions only prior to the actual incorporation of the next building block by being super-selective about which chemical ingredients it allows to enter the process. Because a protein's chemical "shape" dictates its function, mistakes in translating assembly codes can be toxic to cells, resulting in the misfolding of proteins often associated with neurodegenerative conditions. Working with bacterial ribosomes, Green and her team watched them react to lab-induced chemical errors and were surprised to see that the protein-manufacturing process didn't proceed as usual, getting past the error and continuing its "walk" along the DNA's protein-encoding genetic messages. "We thought that once the mistake was made, it would have just gone on to make the next bond and the next," Green says. "But instead, we noticed that one mistake on the ribosomal assembly line begets another, and it's this compounding of errors that leads to the partially finished protein being tossed into the cellular trash," she adds.

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So what is being monitored by the ribosome? Information. Material representations (amino acid sequence vs DNA sequence) of information. But, it does not only monitor it, it manipulates it as a means to an end... fidelity.

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To their further surprise, the ribosome lets go of error-laden proteins 10,000 times faster than it would normally release error-free proteins, a rate of destruction that Green says is "shocking" and reveals just how much of a stickler the ribosome is about high-fidelity protein synthesis. "These are not subtle numbers," she says, noting that there's a clear biological cost for this ribosomal editing and jettisoning of errors, but a necessary expense. "The cell is a wasteful system in that it makes something and then says, forget it, throw it out," Green concedes. "But it's evidently worth the waste to increase fidelity. There are places in life where fidelity matters."

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The ribosome is optimized to manipulate information for fidelity.

Computers Making Computers?

An interesting article authored by Antoine Danchin from the Pasteur Institut was recently published and is sure to bring forth much discussion.
Bacteria as computers making computers

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.

The quantum teleportation experiments have demonstrated that information can be viewed as a fundamental irreducible property of physics (informationalism). Systems biology is moving in that same direction, as viewing cells as computers with machinery and software makes it possible to view information as a fundamental category of nature and all future developments of systems biology can include this concept when looking at cells.

There are many interesting passages in this article. A few of these are going to be highlighted for discussion.

Historically, systems biology follows on from molecular biology, a science based on many concepts more closely linked to arithmetic and computation than to classical physics or chemistry. Molecular biology relies heavily on concepts such as ‘control’, ‘coding’ or ‘information’, which are at the heart of arithmetic and computation. To accept the cell as a computer conjecture first requires an exploration of the concept of information, in relation to the concept of genetic program.

Cellular processes are exquisitely controlled and carried out by remarkable biomolecular machines. The software needed to coordinate these processes is located in a fairly optimal genetic code that is optimized for evolution and maintains its own functional integrity.

The Austrian mathematician Kurt Godel showed that arithmetic (the science of whole numbers) can make statements about itself. To substantiate this remarkable claim, which implies that just manipulating whole numbers with the rules of arithmetic can generate novel information, G¨odel used a simple trick. He coded the words used in Number Theory as integers (e.g. four, which is quatre in French, vier in German and tessera in Greek, can be coded by 4) and used the corresponding code to translate propositions of arithmetic. This generated a large whole number, which could be manipulated by the rules of arithmetic, and after a sequence of operations, this manipulation generated another whole number. The latter could be decoded using the initial code. Godel’s trick was to drive the sequence of operations modifying the initial statement, to lead to a very particular conclusion. When decoded, the manipulated sequence translated into a particular proposition, which, briefly, stated: ‘I am impossible to prove’. In other words, arithmetic is incomplete, i.e. some propositions of arithmetic can be understood as valid; yet they cannot be proven within the frame of arithmetic. But this ‘incompleteness’ can also be seen as a positive feature; it is what allows the creation of new information – in Godel’s case, the statement of a fact of which the world was previously unaware. In his book, Hofstadter showed that the genetic code, which enables the world of nucleic acids to be translated into the world of proteins, which in turn manipulate nucleic acids, behaves exactly as Godel’s code does. This implies that manipulating strings of symbols, via a process that uses a code, can generate novel information. Of course, in the case of nucleic acids and proteins, there is no Godel to drive the process, and no need for one: while Godel knew what he was aiming at, living systems will accumulate information through recursivity, without any design being required. We only perceive a design because the end result is familiar to us, and thus seems more ‘right’ than any other possible result. But what we commonly term the ‘genetic program’ because it unfolds through time in a consistent manner is not a programme with an aim – it is merely there, and functions because it cannot do otherwise.

Why can't the function of the program be to actively manipulate information as a means to an end... self-replication and preservation. Later in the article something similar to this is actually suggested:

The reluctance of investigators to regard information as an authentic category of Nature suggests that, at this point in the present review of the literature, it may still be difficult for the reader to accept that a cell could behave as a computer. Indeed, what would the role of computation be in the process of evolution? We have already provided some elements of the answer to the question: Turing showed that the consequence of the process of computation along the lines he outlined is that his machine would be able to perform any conceivable operation of logic or computation by reading and writing on a data/program tape. Stated otherwise, and in a way that is easier to relate to biology, the machine manipulates information and, because arithmetic is incomplete [as illustrated in the introduction above (Hofstadter, 1979)], it is able to create information. The machine is therefore in essence unpredictable (Turing, 1936–1937), but not in a random way – quite the contrary, in a very interesting way, as lack of prediction is not due to lack of determinism, but due to a creative action that results in novel information. If the image is correct, then it shows that living organisms are those material systems that are able to manipulate information so as to produce unexpected solutions that enable them to survive in an unpredictable future (Danchin, 2003, 2008a).

There we go, organisms can be viewed as entities that are able to manipulate information as a means to an end. Why would it be difficult to accept that cells to behave like computers? Yet, cells are capable of more than computers, e.g. self-replication and autonomous manipulation of information.

A form of endogenous adaptive mutagenesis (EAM) is also being alluded to in the article:
Living organisms are, therefore, infinitely far removed from the clockwork mechanicism that superficial opponents of molecular biology associate with the widespread analytical stance they call ‘reductionism’ (Lewontin, 1993). It is important to emphasize here that, in the Turing machine, the machine is not only allowed to read the program but also to write on it. If, then, the conjecture of the cell as a Turing machine is valid, apparent paradoxes such as the controversial ‘adaptive mutations’ that enable the cell to invent novel metabolic pathways should not be unexpected (Cairns et al., 1988; Danchin, 1988b).

There is also room for drawing parallels between evolution, memetic algorithms and designed molecular docking programs.

Finally, we must note that the algorithmic approach, presented when considering the genetic program as an authentic program in a Turing machine (Danchin, 2003), identifies two completely different levels: the level of the program and the level of the machine.

The article continues to discuss at length the parallels between our own created information processing systems (computers) and molecular processes fundamental to life. The article is sure to provide information for many more interesting blog discussions.

Replication Machinery and Transcription Factories

How DNA Is Unwound So That Its Code Can Be Read

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ScienceDaily (Nov. 24, 2008) — Researchers at The Scripps Research Institute have figured out how a macromolecular machine is able to unwind the long and twisted tangles of DNA within a cell's nucleus so that genetic information can be "read" and used to direct the synthesis of proteins, which have many specific functions in the body.

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"This is a fundamental processes that takes place countless times inside each of our cells every day, but how it happens had not been understood." says the study's lead investigator, Francisco Asturias, Ph.D., associate professor in the Department of Cell Biology at Scripps Research. "The structure we have solved provides important clues into one of the first steps in gene expression regulation."

Anybody interested in some of the 3D-structure, go to rcsb.org.

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"Remarkable Unpacking and Repacking" To understand the complexity of the process, it is important to know that if the DNA in each cell were stretched out, it would be more than three feet long—and given the trillions of cells within a human body, it has been calculated that a single individual's DNA could stretch to cover the distance to the sun and back many times over. So DNA must be packaged into tidy little chromosomes. The DNA in each gene first assembles into what looks like a string of beads: the string is the DNA and to compact its length, it is wrapped two times around a spool-like bead of histone protein, to form a nucleosome. But there is so much DNA in a single gene that each gene is packed into a necklace of nucleosomes on a DNA string. These beads then become further compressed into twisted ropes that eventually form chromatin, in which DNA is compacted about 10,000 times from its extended length. What the Scripps Research scientists set out to do is to understand how the RSC complex unwinds DNA from the many histone beads within a gene so that other molecular machines can read the genetic code. RSC is a huge complex of 13 different proteins and the scientists first found that it holds an individual nucleosome in what looks like a vise grip. They then found that RSC creates a little bulge in the DNA that can be propagated around the nucleosome and make possible translocation of the DNA with respect to the histones, exposing the DNA so that it can be read. "Imagine a rubber band wrapped twice around a water glass. The easiest way to move the band is to pull a little of it away from the glass and then slide it" Asturias says. "By using energy from an external source (ATP hydrolysis) RSC can repeatedly pull DNA away from the histones and eventually expose all of the DNA." The researchers believe that by translocating a nucleosome along the DNA, RSC eventually slides into the next adjoining nucleosome, causing the histones to be ejected and exposing the DNA. "Interestingly, although its DNA is gradually exposed, the nucleosome to which RSC is bound remains intact," Asturias says. The structure RSC interacting with a nucleosome explains how previously observed DNA bulges formed by chromatin remodeling complexes are formed, and why a single intact nucleosome appears to be left on a fully activated gene before other cellular machinery scoop up the histones and repack the DNA until it needs to be read again. "Every time your cell expresses a gene, it goes through this remarkable unpacking and repacking," he says. "We are happy to have provided some clarity to the process."

Published article:
Structure of a RSC–nucleosome complex and insights into chromatin remodeling

Nice video showing DNA wrapping.

An interesting blog entry (and an interesting blog worth a read) describes how the transcription machinery is assembled and disassembled in a few sites in cells.

Yet another twist in the world of gene expression - transcription factories

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First of all I will ask you, did you know that transcription only happened at a few sites within the nucleus? In mouse cells from the animal there are between 100-300 of these but in cultured cells such as HeLa cells there are many more. Transcription factories also known as RNAPII foci are where most, if not all mRNA is produced. This amazed me and raises the obvious questions of why and how. The why may be obvious. It is a good idea to keep the nucleus as I see it ‘tidy’ but in more technical terms it is a way of keeps gene expression organised and regulating it (see below). The how this work I don’t think has been addressed! All I can say is watch this space.

There is more there.

Gene activation governed by machines

How 'molecular machines' kick start gene activation revealed

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How 'molecular machines' inside cells swing into action to activate genes at different times in a cell's life is revealed today (6 November) in new research published in Molecular Cell. Genes are made of double stranded DNA molecules containing the coded information an organism's cells need to produce proteins. The DNA double strands need to be 'melted out' and separated in order for the code to be accessed. Once accessed, the genetic codes are converted to messenger RNAs (mRNA) which are used to make proteins. Cells need to produce particular proteins at different times in their lives, to help them respond and adapt to changes in their environment.

The "melting out" process is carried out by helicases which is part of the replisome. Exquisitely controlled.
Helicases are also known to be ring-shaped motor proteins, typically hexamers and separate double-stranded DNA into single-stranded templates for the replication machinery. Replication occurs at about 1000 base pairs per second due to the highly efficient combination of sliding clamps and the polymerases. Thus, helicases need to unwind DNA at at least that speed. Unwinding DNA too slowly and the replication machinery might break down . Unwind the DNA too fast or untimely and harmful mutations might occur as single-stranded DNA is prone to degradation and cytosine deamination. The speed at which helicase unwinds DNA is no accident though, as it is intrinsically controlled. As helicase is bound to the lagging strand, it unwinds the leading strand in a separate direction. Applying a pulling force on the leading strand leads to a 7-fold increase in the speed of DNA unwinding by helicase. The highly efficient DNA polymerase/sliding clamp combination provides this controlling force on the leading strand. This forms a robust unwinding/polymerization interaction whereby polymerization controls and prevents unwanted DNA unwinding.

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The new study outlines exactly how a molecular machine called RNA polymerase, which reads the DNA code and synthesizes mRNA, is kickstarted by specialised activator proteins. The scientists have discovered that RNA polymerase uses a tightly regulated internal blocking system that prevents genes from being activated when they are not needed. Using electron microscopy to look at the inner workings of bacterial cells, the researchers discovered that the DNA strand-separating process is kickstarted when RNA polymerase is modified by an activator protein, which the cell sends to the site of the gene that needs to be switched on. This activator protein jump-starts the RNA polymerase machine by removing a plug which blocks the DNA's entrance to the machine. The activator protein also causes the DNA strands to shift position so that the DNA lines up with the entrance to the RNA polymerase. Once these two movements have occurred and the DNA strands are in position, the RNA polymerase machine gets to work melting them out, so that the information they contain can be processed to produce mRNA, and ultimately allow production of proteins. Professor Xiaodong Zhang, lead author of the paper from the Department of Life Sciences at Imperial College London, explains the significance of the team's findings, saying: "Understanding how the RNA polymerase gene transcription 'machine' is activated, and how it is stalled from working when it is not needed, gives us a better insight than ever before into the inner workings of cells, and the complex processes that occur to facilitate the carefully regulated production of proteins." Professor Martin Buck, Head of Imperial's Division of Biology and one of the paper's co-authors, adds that understanding how this process works in bacteria cells is of particular interest, because it is this gene transcription and protein production process which allows bacterial cells to adapt, respond and thrive despite changes in their environment: "In other words, this is the process that occurs inside bacteria that makes them so good at survival. Many bacteria cause infection and disease in humans, and are hard to defeat. Bacterial RNA polymerase is a proven target for antibiotics such as rifampicin, against which many bacteria have become resistant. Insights gained form our research will now provide opportunities and strategies for the design of novel antibacterial compounds," he concludes

So machines govern the activity of gene expression, and machines are governed by gene expression through a reasonably optimal genetic code mmmm....