The production system of the E-COLI bacterium is aimed at only one product: it seeks to replicate itself, that is, to produce another plant. And like any good business manager, he wants to get maximum output at minimum cost
In business administration schools, students are taught how to achieve higher profits: reduce costs, increase revenues and optimize the work processes in the factory as much as possible. Surprisingly, the one who can offer interesting insights in the field of economic efficiency is none other than the bacterium Escherichia coli, one of the most studied unicellular organisms. In a way, this bacterium can be seen as a sort of industrial plant.
The production system of this bacterium is aimed at only one product: it seeks to reproduce itself, that is, to produce another factory. And like any good business manager, he wants to get maximum output at minimum cost. The cost in this case is measured by the amount of energy and other resources that the bacterium needs to spend to produce the various components of its body, and the energy required to assemble them and create a new, independent bacterium. The yield is measured during the time required for the production of a new bacterium. The combination between these two factors (time and resources) is the efficiency rate of the "plant".
Dr. Zvi Telusti and research student Arbel Tadmor from the Department of Physics of Complex Systems at the Weizmann Institute of Science developed a mathematical model that describes the bacterium's production system and examines its effectiveness. The model, recently described in an article published by the scientists in the online journal PloS Computational Biology, manages to describe this complex micro-plant using five remarkably simple mathematical equations. The first examines the process in which the bacterium produces ribosomes, the intracellular organelles through which the cell produces proteins (unlike most human factories, the bacterial factory produces its own machines and devices). Naturally, the second equation describes how these ribosomes produce the other proteins that make up the cell.
The third equation focuses on the production process of the enzyme by means of which the cell translates the genetic information contained in the DNA, and thereby produces single-stranded messenger RNA molecules, which carry the genetic information from the cell nucleus to the ribosome. In a certain sense, this enzyme (called RNA polymerase) can be seen as a kind of "production manager" that uses the production plan stored in DNA to manage the production of proteins in the necessary quantities and at the desired rate. Some of the RNA that the polymerase produces is used to build the ribosomes, so the production manager is himself, in fact, a kind of machine. The fourth and fifth equations describe how the bacterium wisely divides the ribosomes (the "machines") and the polymerases (the "production managers") between the different tasks of protein production, ribosome production, and polymerase production. These five simple equations make it possible to calculate and predict the bacteria's reproduction rate - the "bottom line" by which its effectiveness is measured.
The model was tested against experiments in which the reproduction rate of Escherichia coli bacteria was measured, and then the changes that occurred in the reproduction rate were observed as a result of a series of genetic changes made in these bacteria (the change was expressed in the addition or deletion of various genes responsible for or playing a central role in the production of some central component in the bacterial cell. For example, the gene responsible for the main part of the ribosome structure). As a result of the genetic changes, the bacteria changed their "production strategy", with the aim of achieving the best possible production performance in the given situation imposed on them. The model was able to accurately predict the reactions of the bacteria.
For example, the bacterium can "decide" how many ribosomes to produce. Apparently, one should aim for as many ribosomes as possible, because the more ribosomes there are, the more proteins he will be able to produce in less time. But the production of the ribosome and its maintenance cost quite a bit in terms of energy. The model found that the optimal number of genes encoding the production of the ribosome is seven, as is true in nature. Furthermore, in those that contained nine copies of the ribosome gene, or only five copies for example, the culture efficiency was measured to be lower compared to bacteria with seven copies. In other words, evolution "plans" the plant to be the most efficient under the given conditions.
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Nature is frugal
Aye, this 'garlic' was almost deadly :)
Surely these equations will find use when nanorobots assemble themselves.
Hugin:
enough.
How many times can the same argument be repeated.
I bring data and reasons and you bring baseless statements and say there is no proof.
Let me talk to people who understand my words and stop your attempts to drag me into idle arguments.
You learned from me that you need to define what you are talking about and now you demand a definition for every word, so please - start! Define the word "define" and use only the words you defined earlier!
Again entering into the same uncertain semantic debate.?
Evolution = development / in a slow and gradual process
Why are there no admissions that 'nature' by itself and all its organs do not have a 'thinking type' or planning/intuitive/internal brain types?
If we are natural thinkers there is no reason why primary levels don't 'think'.
Michael: We have not yet defined 'animal thoughts' as a type./It has not yet been proven that there is no 'will' of nature.
There is a big difference between artificial machines that are attributed with personification and between various natural elements that are closer to our natures.
point:
This is a form of speech that makes expression very easy, so it is difficult to avoid it. We personify evolution just as we often personify the computer or the car. In our speech we attribute a will to everyone, even though it is clear to us that they do not have a will.
In order to avoid chronic and harmful reluctance of the text, it is better in my opinion to continue using this form of speech and only occasionally comment - as you did here - that this form of speech is actually just a shorthand used to describe a behavior that is outwardly similar, and with a low resolution on the timeline, to that of willing beings and that the reality High resolution is different.
To demand otherwise is a bit like demanding to describe the behavior of the macroscopic world in terms of quantum theory (not exactly but I hope you get my point).
Another comment I have - a comment that I bring up from time to time but I don't bother to emphasize in every phrase - for exactly the same reason - is that evolution is actually a theorem in statistics - a theorem that the conditions it sets for its existence do not include a requirement for life but only for replication with errors and competition for resources. Therefore, evolution can also be seen in computerized environments, both in memes and in technology (implementation of memes).
Bacteria do not have a nucleus
interesting.
Regarding the term evolution, you should stop and use this term to describe some active factor.
Evolution is not something that plans or acts or is responsible for any thing that exists in nature.
Evolution is a word that came to describe natural processes that we see in nature. These processes are the results of the laws of physics-chemistry-biology only.
To say (and even in quotation marks, in the language of the question, or by analogy) that evolution plans for the efficiency of the manufacturing plant to increase, is just like saying that the mountain plans for the rain that falls on it to fall down the mountain. That is, without any explanatory, non-literal, non-topical, and non-scientific meaning. And in the end it misleads and confuses the public who don't understand that much about these matters anyway.