A few blogs ago I asked, "Where, in fact, do 'the good ones' really come from?" By "good ones" I meant useful genome changes in evolution. This question stimulated some debate about whether it was possible to distinguish good changes from bad changes before they occur.
In the abstract, this may seem an overwhelmingly difficult problem. But if we think a bit about the highly organized state of the genome and non-random natural genetic engineering, biasing changes toward "good ones" becomes more conceivable.
I have already discussed purposeful, targeted changes in the immune system. The immune system illustrates how efficiently cells can target DNA restructuring by recognizing specific sequences and coupling DNA changes to transcription (copying DNA sequence into RNA).
Some evolutionists object that a somatic process like antibody synthesis provides no model for germline changes in evolution. So let's examine natural genetic engineering events in microbial cells. We'll look at mobile genetic elements targeted in ways that increase their evolutionary potential.
Mobile genetic elements come in many forms. Some operate purely as DNA. Others make an RNA copy and reverse transcribe it back into DNA as it inserts at a new location. Elements that move, or transpose, to multiple new locations are called "transposons" or "retrotransposons" (if they use an RNA intermediate).
Other mobile elements only insert in particular locations by a process called "site-specific" recombination. In bacterial evolution, this process is used in specialized structures called "integrons" that capture casettes containing protein coding sequences for antibiotic resistance, pathogenicity, and other functions.
What all mobile elements share are proteins that aid them to cut and splice DNA chains so that they can construct novel sequences, much as human genetic engineers do in their test tubes. These proteins have various names, such as "recombinase," "transposase," and "integrase." It is the specificity of the cutting reactions involving these proteins that determines where a mobile element moves in the genome.
One fascinating case of highly biased integration is the bacterial transposon Tn7. Tn7 has two specialized proteins to target its transposition. The TnsD protein directs Tn7 to insert into a special "attTn7" site in the chromosomes of many bacterial species where it does not disrupt any host functions and so causes no deleterious effects.
Another, more interesting protein, TnsE, directs Tn7 to insert into replicating DNA molecules. The reason this is important is that transmissible plasmids replicate their DNA as they transfer from one cell to another. TnsE targeting to plasmids in transit to new cells thus enhances the spread of Tn7 and the resistances it carries to many different kinds of bacteria.
Tn7 carries its antibiotic resistance determinants in an integron. Integrons and their recombinase proteins are likewise specialized to participate in plasmid spreading through bacterial populations. Plasmids enter new cells as single-stranded DNA. We learned just in 2005 that integron site-specific recombinases are special in operating on single-stranded DNA, not double-stranded molecules like previously studied recombinases. Moreover, integron recombinase synthesis is triggered by the entrance of single-stranded DNA into a cell. So integron activity is intimately linked in more than one way to plasmid transfer.
Among eukaryotic microbes, retrotransposons show targeting that strongly biases them against disrupting the densely packed coding sequences in their genomes. The integrase proteins of retrotransposons in budding yeast Saccharomyces cerevisiaea, fission yeast Schizosaccharomyces pombe, and the slime mold Dictyostelium discoideum all bind to transcription factors (proteins involved in controlling transcription) so that they insert upstream of the functional DNA coding sequence. In this way, they can change regulation of the transcribed sequence without damaging the protein coding capacity of the cell.
The interactions involve a variety of transcription factors. In Saccharomyces, for example, the Ty1 and Ty3 retrotransposons target sites upstream of RNA polymerase III transcripts (95 to 98 percent of all inserts). The Ty1 integrase binds to TFIIIB subunit Bdp1p, and Ty3 integrase binds to the TFIIIB and TFIIIC factors.
The TRE-5A element of Dictyostileum discoideum belongs to a different class of retrotransposons from Ty3 and uses a different reverse transcription and integration mechanism. Nonetheless, its integration protein also interacts with TFIIIB and TFIIIC transcription factors and shows a similar preference for inserting upstream of RNA polymerase III start sites.
Two more Saccharomyces retrotransposons (Ty2 and Ty4) show the same target preferences as Ty1 and Ty4, but the protein affinities of their integrases are unknown. In contrast, the integrase of the Ty5 retrotransposon binds the Sir4 chromatin silencing protein and targets Ty5 insertions to epigenetically silenced regions of the genome, where they have minimal impact.
In Schizosaccharomyces pombe, theTf1 integrase binds to a transcriptional activator, Atf1p, and targets insertions upstream of RNA polymerase II transcription start sites. The Tfi insertions are not uniform for all RNA polymerase II start sites; they favor those activated by stress responses. The researchers who found this specificity hypothesized, "This targeting of stress response genes coupled with the ability of Tf1 to regulate the expression of adjacent genes suggests Tf1 may improve the survival of S. pombe when cells are exposed to environmental stress."
In a future blog, we'll leave the realm of microbes and discuss mobile elements in the germlines of insects and vertebrates, where the story is much the same. The DNA mobility machinery interacts with transcription factors or other proteins to target many mobile elements to sites where they do no damage.
For now we have two answers and a mystery:
I can envision a conscious organism evaluating the environment, organizing tentative adaptations, retaining those that prove effective, and keeping its genome relatively up to date. I can’t imagine a genome reorganizing itself, and I can‘t imagine the individual cells doing any reorganizing. I ask you these questions, Dr. Shapiro, because of all the evolutionary biologist I know of, I respect you the most.
Berthajane Vandegrift
A Few Autistic Questions about Freud Marx and Darwin
This is a reply both to this comment and to your earlier one at 9:57.
What we know is that the biased genetic changes take place inside cells. Cells pick up sensory information and can communicate it to their genome through molecular signaling networks. These networks allow the cells to interpret the sensory information and adjust processes that may involve the genome, such as expressing information encoded there and, in some cases, restructuring the DNA.
We have identified and possess some level of understanding of the molecules involved in sensing, signal transmission, genome expression and DNA restructuring. We do not know exactly how and to what degree the cells are capable of interpreting the information they receive. That is what we need to know in order to address the kinds of questions you ask.
Finding answers will require us to think about cells in a less mechanical way than we do now. As scientists focus more on cell responses, control and regulation, new ideas about how they process information will develop. That is what I see as a major part of the agenda for 21st Century biology. I'm afraid we'll just have to wait for better answers.
I was wondering what kinds of ideas are being proposed with respect to how cells process information. It seems that many scientists still view cellular processes as purely chemical.
What if there is an electromagnetic component to the information processing? I know this would be getting into quantum physics, but perhaps there is a memory component that we can't see which involves magnetic fields (as is proposed to be involved in human memory as well).
Cells give the impression of "thinking". So perhaps there actually exists a "mind" of sorts which is a central, reflective point of cognition. I've often wondered this, but most quote unquote scientists or academically minded people laugh at me when I propose it. I'm in no way suggesting that bacteria have an experience like a human being, but what if there really is instinctual "mind", an immaterial aspect that is reflective of the functionally coordinating whole?
Do you find such an idea unscientific, or interesting? You have mentioned before that you think bacteria might be sentient. I believe life is an inherent feature of the universe, not a contingent and fortuitous one. So that leads me to ask these kinds of questions. But the real scientific question is, how would we go about pointing to and understanding such a thing (a cellular "mind") if it does indeed exist?
There is more to the story than just losing the deleterious changes. The experiments can be done where they would (and are) still detected. I tried to explain some of the molecular mechanisms involved in the biasing towards positive outcomes. How far that biasing can extend remains to be explored.
Computers make decisions based on programs that use the fundamentally bi-state nature of the transistor. They are limited in logic to a two-state system and operations that cannot exceed the power of recursion.
Now consider that any molecule in 4 dimension space-time has an uncountable number of quantum states and that those states can be entangled and in superposition until nature decides to pick one of the possible states at which point the molecule is committed to a particular energy / position, etc. This is a huge increase in power over digital computers.
Second, consider that nature appears to work by the principle of least action, whereby use of resources are minimized. One example is that a stick immersed in a pond of water will appear bent because light "finds" the path that requires the least time to traverse between eye and object.
One calculation that cellular molecules seem to do requires an assessment of the energy landscape in their surroundings. This energy landscape is part of the quantum state of all molecules in the cell. It should not be too surprising that they have evolved to do that rather well.
I think the computer analogy can be quite fruitful in understanding cell informatics if used with care. Cells are full of multimolecular networks, and there are probably many similarities between these and computational circuits executed both in hardware and software.
Certainly cells can do what computers can and then some. Computer science is likely to benefit mightily when we figure where the extra capacity of cells resides. Like most places where two disciplines interact, both will be changed for the better.
I have to differ with you, however, on the least action idea.
We used to think that cells economised on ATP and other energy-rich compounds. Today, we know that they burn prodigious amounts of ATP and use both complexity and redundancy to make sure that cell operations proceed reliably and precisely.
Information and accuracy are the truly valuable commodities in cells. RNA and protein molecules are synthesized and degraded with abandon in the pursuit of reliable control. The lesson of molecular cell biology is that complexity rather than simplicity is the rule so that cells are protected from failure.
One of the benefits of pursuing a quantum computing model is to avoid deterministic outcomes like the principle of least action. At the same time, cells that burn too much ATP without some benefit would not last long in the evolutionary scheme.
Quantum computing appears to have a built-in counterfactual capability that would need to be simulated in a digital computer. Through counterfactual analysis, "what-if" scenarios can be evaluated to determine if buring more energy might have beneficial consequences. It is well known that interactions at the quantum level can violate classical energy barriers (tunneling effect). This capability could keep a complex system from getting trapped in a local energy minimum when there is a better long range solution that would require climbing an energy gradient. Perhaps this is why we don't see the types of decision making that cells do in simple inanimate systems: quantum computing needs complex molecular systems to achieve its full potential.
Berthajane Vandegrift
A Few Autistic Questions about Freud, Marx and Darwin
I don't understand your question. The issue is to find out how adaptations are achieved. You seem to imply that they arise prior to genome change. Most scientists assume that the genome changes are primary events leading to new adaptations. It would help if you could explain more fully what you have in mind.
Berthajane Vandegrift
A Few Autistic Questions about Freud Marx and Darwin
And if there is this natural genetic engineering, why do replica plating experiments are so consistent with specific mutation rates?
I am not denying the role of mobile elements, horizontal gene transfer, epigenetics or even ecosystems sharing metagenomic pools, in evolution. However, they seem to be more an emergent property of "the usual suspects" than evolutionary forces in themselves.
We are not talking about making predictions here but about a cell's capacity to bias change operators in favor of useful outcomes. We'll see more examples in the future.
As for mutation rates, no consistent rate exists under changing conditions. "Specific mutation rates" are imaginary, not experimentally verifiable. They were invented for ease in writing equations but have no reality.