Scientists have long known what drives the flagellum to spin, but what causes the flagellum to stop spinning — temporarily or permanently — was unknown.

“We think it’s pretty cool that evolving bacteria and human engineers arrived at a similar solution to the same problem,” said IU Bloomington biologist Daniel Kearns, who led the project. “How do you temporarily stop a motor once it gets going?”

The action of the protein they discovered, EpsE, is very similar to that of a car clutch. In cars, the clutch controls whether a car’s engine is connected to the parts that spin its wheels.

-ScienceDaily (June 23, 2008)

Excerpts from The Design Matrix (2007):

We are actually using the knowledge about our own designed artifacts to shed light on biology and how it works. Imagine if there were no computers, tape recorders, and washing machines. Take away human technology, and suddenly, there are no good metaphors left to describe life. - p 52

All of this, of course, makes sense if life really is carbon-based nanotechnology. To understand an alien technology, we would have to use our own technology as a model, and the more similar the technologies, the more easily we could characterize and understand this alien technology. - p 53

If living processes are the products of design, it comes as no surprise that so much of biology is more akin to the study of engineering than to chemistry or physics. Furthermore, it would make sense that as our understanding of the cell advances, that teleological concepts, including the very concept of design, would proliferate in the biological literature. Much of this design terminology stems from the fact that biologists have discovered that cells are filled with miniature machines and that coded information is stored and employed for the synthesis of these machines.- p. 59

Looking at a cell is like looking into the future of our own designs. – p. 204

“Wordle is a toy for generating “word clouds” from text that you provide. The clouds give greater prominence to words that appear more frequently in the source text.”

Here is a Wordle of Chapter 6 from The Design Martrix:

Below the fold is a Wordle of Chapter 2 and then Chapter 7.
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Evidence, evidence, evidence. Lots of people like to use this ill-defined and subjective concept to score points, as it allows people to sit in judgment, pronouncing whether or not some data are “evidence” or whether the evidence is “sufficient.” It’s quite the power-trip to sit in judgment not only of other people, but of Reality. Despite these problems, we cannot ignore the importance of evidence. For example, if we are to convict Jones for the murder of Smith, there had better be evidence to support this contention if we are going to take away Jones’s freedom.

Yet this very example serves to make both points. Yes, evidence is important when making decisions about our natural and social world, but relying solely on the evidence may very well deliver only a superficial, or even false, understanding of the world. We know this simply from the fact that in court rooms around the world, judges and juries have followed the evidence before them to determine guilty people are innocent and innocent people are guilty. This holds true even if we rule out corruption and biases.

Consider some movie where you, the viewer, know that Jones killed Smith, because you watched it happen. Jones, of course, subjectively knows that he killed Smith. The police investigator doesn’t know this, he simply believes that Jones killed Smith because of some clues. The investigator then privately confronts Jones and accuses him of murder. Jones, privately knowing the investigator is correct, simply replies, “There is no evidence and you can’t prove it” and the investigator knows this is true.

Right there, in that scene, we see the difference between evidence and truth. Relying solely on the evidence may very well deliver only a superficial, or even false, understanding of the world.

Embedded within cells are complex signaling mechanisms that transfer information from one part of a cell to another and intercellular mechanisms that transfer information from one part of a multicellular organism to another. Indeed, signal transduction pathways—and the proteins associated with them—appear to serve the functions of information processing and transfer, rather than those of more “traditional” biology (e.g., chemical transformation of metabolic intermediates or the building of cellular structures).

For example, a simple enzyme protein could be viewed as a computational element that takes an input—the concentration of its “substrate,” the molecule with which it interacts—and produces an output: a concentration of the catalyzed reaction product. An enzyme that becomes active only when it binds to two separate regulator molecules will function something like a Boolean AND gate, and so on. Circuits formed from these elements can be as simple as a switch or an oscillator, or as complex as to drive a bacterium’s chemotaxis response. Indeed, the cell even possesses a kind of short-term, “random-access” memory, in the sense that events in its environment have profoundly shaped the concentration and activity of many thousands of molecules in the cell. In short, these protein-based circuits constitute a kind of nervous system for the cell, providing it with much of what it needs to control its behavior.

Additional insights can be gained from the notion that both computational processes and biological pathways can be viewed as processes that affect the state of a system according to well-defined (though possibly probabilistic) rules. Thus, it is possible to describe regulatory, metabolic, and signaling pathways, as well as multicellular processes such as immune responses, as systems of interacting computations operating in parallel. In particular, languages such as Petrinets, Statecharts, and the Pi-calculus, originally developed for the specification and study of systems of interacting computations, can be used to represent such systems. Such representations enable researchers to simulate their behavior, and to support qualitative and quantitative reasoning on the properties of these systems.

- From
Catalyzing Inquiry at the Interface of Computing and Biology, pp. 207-208

Jacques Monod shared a Nobel Prize for his work on the lac operon. . This work played a crucial role in the development of molecular biology and ultimately led to the birth of evo-devo. In 1971, Monod wrote a classic book entitled, Chance and Necessity. It begins as follows:

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Let’s look more closely at the building blocks of DNA – the nucleotides.

Notice that it is more complex than an amino acid, where three complex chemical groups are covalently linked together. And unlike amino acids, nucleotides are not recovered in Miller-Urey type experiments. In fact, Robert Shapiro, professor emeritus of chemistry and senior research scientist at New York University, notes:

And no sample of a nucleotide, the building block of RNA or DNA, has ever been discovered in a natural source apart from Earth life. Or even take off the phosphate, one of the three parts, and no nucleoside has ever been put together. Nature has no inclination whatsoever to build nucleosides or nucleotides that we can detect, and the pharmaceutical industry has discovered this.

What is also remarkable about nucleotides is that it is possible to connect the sugar, phosphate group, and nitrogenous base together to form different structures.

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We’ve seen that the logic of protein structure entails the covalent linkage of a pattern of noncovalent interactions. This is how we encode a three-dimensional reality in one-dimensional terms. And all of this was made possible by the fact that amino acids are linked together in a way where their side chains were not involved in the linkage and thus served more like appendages.

But we have also seen this very logic is at play when it comes to the formation of a chain of nucleotides. As with the side chains of amino acids, the nitrogenous bases can interact with each other through noncovalent forces causing the nucleotide chain to fold into a three-dimensional structure. This is what happens with a lot of RNA and explains its ability to function as a catalyst. But let’s turn to DNA.

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We’ve seen that a protein is formed by covalently linking amino acids, yet in a fashion where the diverse side chains do not participate in this binding. This frees them to function elsewhere. So what do the side-chains do? In short, they interact with each other. Through electrostatic interactions, they fold most proteins into a compact, globular shape and it is the shape that is at the very heart of protein function (if you disrupt the shape, you disrupt the function).

What I’d like to do now is impress upon you the very brilliance of this design, as it goes a very long way in explaining why proteins have been so useful for evolution.

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To make a protein, we simply covalently link individual amino acids together via a peptide bond. The figure below shows the formation of a peptide bond.

I’d like to draw your attention to two things. First, note that the carboxyl group of one amino acid reacts with the amino group of the second amino acid to form the peptide bond (highlighted in the orange box). This creates a dipeptide with differing ends. At the N-terminal end, there is a free amino group and the C-terminal end has a free carboxyl group. This simply means we can attached a third amino acid to the C-terminal end of the dipeptide with the very same reaction. And if we can add a third, we can add a fourth. Etc. Thus, the structure of the amino acid is perfectly poised to create a growing chain whose length would be determined by factors other than amino acid structure. We can thus begin to catch a glimpse of one reason why proteins are so versatile, as the relative ease of construction is coupled to an ability to vary the length.

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