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The highly engineered transition to vertebrates: an example of functional information analysis

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In the recent thread “That’s gotta hurt” Bill Cole states:

I think over the next few years 3 other origins (my note: together with OOL), will start to be recognized as equally hard to explain:

  • The origin of eukaryotic cell: difficult to explain the origin of the spliceosome, the nuclear pore complex and chromosome structure.
  • The origin of multicellular life: difficult to explain the origin of the ability to build complex body plans.
  • The origin of man: difficult to explain the origin of language and complex thought.

That thought is perfectly correct. There are, in natural history, a few fundamental transitions which scream design more that anything else. I want to be clear: I stick to my often expressed opinion that each single new complex protein is enough to infer design. But it is equally true that some crucial points in the devlopment of life on earth certainly stand out as major engineering events. So, let’s sum up a few of them:

  1. OOL
  2. The prokaryote – eukaryote transition (IOWs, eukaryogenesis)
  3. The origin of metazoa (multicellular life)
  4. The diversification of the basic phyla and body planes (IOWs, the Cambrian explosion)

Well, saurian-1358308_1280to those 4 examples, I would like to add the diversification of all major clades and subphyla.

Of course, another fundamental transition is the one to homo sapiens, but I will not deal with it here: I fully agree with Bill Cole that it is an amazing event under all points of view, but it is also true that it presents some very specific problems, which make it a little bit different from all the other transitions we have considered above.

I will state now in advance the point that I am trying to make here: each of the transitions described requires tons and tons of new, original, highly specific functional information. Therefore, each of those transitions commands an extremely strong inference to design. I will deal in particular with the transition to the subphylum of vertebrates, for a series of reasons: being vertebrates, we are naturally specially interested in that transition; there are a lot of fully sequenced genomes and proteomes of vertebrate species ;  and a lot is known about vertebrate biology. IOWs, we have a lot of data that can help us in our reasoning. So, I will  try to fix a few basic points which will be the foundation of our analysis:

  • a) The basic phylum is Chordates, which are characterized by the presence of a notochord. Chordates include three different clades: Craniata, Tunicata, Cephalochordata.
  • b) Vertebrates are a subphylum of the phylum Chordates, and in particular of the clade Craniata. They represent the vast majority of Chordates, with  about 64,000 species described. As the name suggests, they are characterized by the presence of a vertebral column, either cartilaginous or bony, which replaces the notochord.
  • c) The phylum Chordate, like other phyla, can be traced at least to the Cambrian explosion (540 million years ago).
  • d) Chordates which are not vertebrates are quite rare today. They include:
    • 1) Craniata: the only craniates which are not vertebrates are in the class Myxini (hagfish), whose classification however remains somewhat controversial. All other craniates are vertebrates.
    • 2) Tunicata (or urochordata): about 3000 species, the best known and studied is Ciona intestinalis.
    • 3) Cephalochordata: about 30 species of Lancelets.
  • e) The phyla most closely related to Chordates are Hemichordates (like the Acorn worm) and Echinoderms (Starfish, Sea urchins, Sea cucumbers).
  • f) Vertebrates can be divided into the following two groups:
    • 1) Fishes: 3 Classes:
      • 1a) Jawless  (lampreys)
      • 1b)  Cartilaginous (sharks, rays, chimaeras)
      • 1c) Bony fish
    • 2) Tetrapods: all the rest (frogs, snakes, birds, mammals)

For the following analysis, I will consider vertebrates versus everything which preceded them (all metazoa, including “pre-chordates” (Hemichordates and Echinoderms) and “early chordates”  (Tunicata and Cephalochordata). So, everything which is new in vertebrates had to appear in the window between early chordates and the first vertebrates: cartilaginous fish and bony fish (I will not refer to lampreys, because the data are rather scarce). So, let’s try to define the temporal window, for what it is possible:

  • Chordates are already present at the Cambrian explosion, 540 my ago.
  • Jawless fish appeared slightly later (about 530 my ago), but they are mostly extinct.
  • The split of jawless fish into cartilaginous fish and bony fish can be traced about at 450 my ago

Therefore, with all the caution that is required, we can say that the information which can be found in both cartilaginous fish and bony fish, but not in non vertebrates (including early chordates), must have been generated in a window of less that 100 my, say between 540 my ago and 450 my ago. Now, my point is very simple: we can safely state that in that window of less than 100 million years a lot of new complex functional information was generated. Really a lot. To begin our reasoning, we can say that vertebrates are characterized by the remarkable development of two major relational systems:

  1. The adaptive immune system, which appears for the first time exactly in vertebrates.
  2. The nervous system, which is obviously well represented in all metazoa, but certainly reaches new important adaptations in vertebrates.

Muperch-62855_640ch can be said about the adaptive immune system, and that will probably be the object of a future OP. For the moment, however, I will discuss some aspects linked to the development of the nervous system. The only point that is important here is that the nervous system of vertebrates undergoes many important modifications, especially a process of encephalization.  My interest is mainly in the developmental controls that are involved in the realization of the new body plans and structures linked to those processes. Of course, we don’t understand how those regulations are achieved. But today we know much about some molecules, especially regulatory proteins, which have an important role in the embryonal development of the vertebrate nervous system, and in particular in the development and migration of neurons, which is obviously the foundation for the achievement of the final structure and function of the nervous system. So, I will link here a recent paper which deals with some important knowledge about the process of neuron migration. I invite all those interested to read it carefully: Sticky situations: recent advances in control of cell adhesion during neuronal migration by David J. Solecki Here is the abstract:

The migration of neurons along glial fibers from a germinal zone (GZ) to their final laminar positions is essential for morphogenesis of the developing brain, aberrations in this process are linked to profound neurodevelopmental and cognitive disorders. During this critical morphogenic movement, neurons must navigate complex migration paths, propelling their cell bodies through the dense cellular environment of the developing nervous system to their final destinations. It is not understood how neurons can successfully migrate along their glial guides through the myriad processes and cell bodies of neighboring neurons. Although much progress has been made in understanding the substrates (14), guidance mechanisms (57), cytoskeletal elements (810), and post-translational modifications (1113) required for neuronal migration, we have yet to elucidate how neurons regulate their cellular interactions and adhesive specificity to follow the appropriate migratory pathways. Here I will examine recent developments in our understanding of the mechanisms controlling neuronal cell adhesion and how these mechanisms interact with crucial neurodevelopmental events, such as GZ exit, migration pathway selection, multipolar-to-radial transition, and final lamination.

In brief, the author reviews what is known about the process of neuronal cell adhesion and migration. Starting from that paper and some other material, I have chosen a group of six regulatory proteins which seem to have an important role in the above process. They are rather long and complex proteins, particularly good for an information analysis. Here is the list. I give first the name of the protein, and then the length and accession number in Uniprot for the human protein:

  • Astrotactin 1,     1302 AAs,     O14525
  • Astrotactin 2,    1339 AAs,     O75129
  • BRNP1 (BMP/retinoic acid-inducible neural-specific protein 1),     761 AAs,     O60477
  • Cadherin 2 (CADH2),      906 AAs,    P19022
  • Integrin alpha-V,    1048 AAs,      P06756
  • Neural cell adhesion molecule 1 (NCAM1),   858 AAs,  P13591

This is a  very interesting bunch of molecules:

  • Astrotactin 1 and 2 are two partially related perforin-like proteins. ASTN-1 is a membrane protein which is directly responsible for the formation of neuron–glial fibre contacts. ASTN2 is not a neuron-glial adhesion molecule, but it functions in cerebellar granule neuron (CGN)-glial junction formation by forming a complex with ASTN1 to regulate ASTN1 cell surface recruitment. More about these very interesting proteins can be found in the following paper:

Structure of astrotactin-2: a conserved vertebrate-specific and perforin-like membrane protein involved in neuronal development by Tao Ni, Karl Harlos, and Robert Gilbert

  • BRNP1 is another  protein which functions in neural cell migration and guidance
  • Cadherin 2, or N-cadherin, is active in many neuronal funtions and in other tissues, and seems to have a crucial role in glial-guided migration of neurons
  • Integrin alpha-V, or Vitronectin receptor, is one of the 18 alpha subunits of integrins in mammals. Integrins are transmembrane receptors that are the bridges for cell-cell and cell-extracellular matrix (ECM) interactions.
  • NCAM1 is a cell adhesion molecule involved in neuron-neuron adhesion, neurite fasciculation, outgrowth of neurites

Now, why have I chosen these six proteins, and what do they have in common? They have two important things in common:

  • They are all big regulatory proteins, and they are all involved in a similar regulatory network which controls endocytosis, cell adhesion and cell migration in neurons, and therefore is in part responsible for the correct development of the vertebrate nervous system
  • All those six proteins present a very big informarion jump between pre-vertebrate organisms and the first vertebrates

The evolutionary history of those six protein is summarized in the following graph, realized as usual by computing the best homology bit score with the human protein in different groups of organisms.

Neuron_migration

Very briefly, all the six human molecules have low homology with pre-vertebrates, while they already show a very high homology  in cartilaginous fishes. The most striking example is probably Astrotactin 2, which presents the biggest jump from cephalochordata (329 bits) to cartilaginous fishes (1860 bits), for a great total of 1531 bits of jump! The range of individual jumps in the group is 745 – 1531 bits, with a mean jump of 1046 bits per molecule and a total jump of 6275 bits for all six molecules. The jump has always been computed as the difference between the best bit score in cartilaginous fishes and the best bitscore in all pre-vertebrate metazoa. We can also observe that the first three proteins have really low homology with everything up to tunicates, but show a definite increase in Cephalochordata, which precedes the big jump in cartilaginous fishes, while the other three molecules have a rather constant behaviour in all pre-vertebrate metazoa, with a few hundred bits of homology, before “jumping” up in sharks. One could ask: is that a common behaviour of all proteins? The answer is no. Look at the following graph, which shows the same evolutionary history for two other proteins, both of them very big regulatory proteins, both of them implied in the same processes as the previous six.

Neuron_migration2

Here, the behaviour is completely different. While there is a slight increase of homology in time, with a few smaller “jumps”, there is nothing comparable to the thousand bit jumps in the first six molecules. IOWs, these two molecules already show a very high level of homology to the human form in pre-vertebrates, and change only relatively little in vertebrates. We can say, therefore, that most of the functional information in these two proteins was already present before the transition to vertebrates.

So, to sum up:

  • a) The six proteins analyzed here all exhibit a huge informational jump between pre-vertebrates and vertebrates. The total functional informational novelty for just this small group of proteins is more than 6000 bits, with a mean of more than 1000 bits per protein.
  • b) These proteins are probably crucial agents in a much more complex regulation network implied in neuron adhesion, endocytosis, migration, and in the end in the vast developmental process which makes individual neurons migrate to their specific individual locations in the vertebrate body plan.
  • c) The above process is certainly much more complex than the six proteins we have considered, and implies other proteins and obviously many non coding elements. Our six proteins, therefore, can be considered as a tiny sample of the general complexity of the process, and of the informational novelty implied in the process itself.
  • d) Moreover, the process regulating neuron migration is certainly strictly integrated, with so many agents working in a coordinated way. Therefore, there is obviously a strong element of irreducible complexity implied in the whole informational novelty of the vertebrate process, an element that we can only barely envisage, because we still understand too little.
  • e) The neuron regulation process, of course, is only a part of the informational novelty implied in vertebrates, a small sample of a much more complex reality. For example, there is a lot of similar novelty implied in the workings of the immune system, of the cytokine signaling system, and so on.
  • f) The jump described here is really a jump: there is no trace of intermediate forms which can explain that jump in all existing pre-vertebrates. Of course, neo darwinists can always dream of lost intermediates in extinct species. This is a free world.
  • g) Are these 6000+ bits of functional information really functional? Yes, they are. Why? because they have been conserved for more than 400 million years. Remember, the transition we have considered happens between the first chordates and cartilaginous fish, and it can be traced to that range of time. And those 6000+ bits are bits of homology between cartilaginous fish and humans.
  • h) How much is 6000 bits of functional information? It is really a lot! Remember, Dembski’s Universal Probability Bound, taking in consideration the whole reasonable probabilistic resource of our whole universe from the Big Bang to now, is just 500 bits. 6000 bits correspond to a search space of 2^6000, IOWs about 10^2000, a number so big that we cannot even begin to visualize it. It’s good to remind ourselves, from time to time, that we are dealing with exponential values.
  • i) How great is the probability that 6000 bits of functional information can be generated in a window time of less than 100 million years, by some unguided process of RV + NS in six objects connected in an irreducibly complex system, even if RV were really helped by some NS in intermediates of which there is no trace? The answer is simple: practically non existent.
  • j) Therefore, the tiny sample of six proteins that we have considered here, which is only a small part of a much bigger scenario, points with extreme strength to a definite design inference:

The transition to vertebrates was a highly engineered process. The necessary functional information was added by design.

 

Comments
gpuccio
OMagain: For all proteins which exhibit a total functional information (or an informational transition) higher than an appropriate threshold (150 bits are good, for me), and for which there is no trace of a detailed naturally selectable pathway that can lower the probabilistic barriers (that is easy: there is no such trace at all for any complex protein) pre Rumracket This is hilarious. Gpuccio is making a designer of the gaps-argument. Where we lack a sufficiently detailed phylogeny, that’s where the designer acted.
The TSZ guys are bringing designer of the gaps arguments out. The use of straw-man arguments appears to signal the end of a viable challenge to your arguments at this point. The fact that the genome is a sequence appears to be a very difficult problem for Neo-darwinism and modern evolutionary theory including universal common descent.bill cole
July 31, 2016
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What a pity. The comments at TSZ have gone completely wild. No more arguments, no more reason. I will just answer this brief question from Allan Miller, who remains after all one of the most "normal" people there: "Good grief! ID of organismal proteins – how non-conjectural is that? Or is gpuccio of the “ID is not a science” school?" ID explains facts, and is motivated by facts. Functional information in proteins is a fact. My OP here is about facts. I copy here my question at #215. About a fact: "Astrotactin 2 is a 1339 AAs protein. 889 of them are identical in sharks and humans.The positives are 1048. I would really appreciate if our friends at TSZ could comment about this very simple fact." On the other hand, missing intermediates, imaginary pathways, connections in proteins space, are all conjectures without a trace of support from facts, and against any rationale. So yes, ID is not conjectural, and neo darwinism is. And no, I am not of the “ID is not a science” school. ID is science. Completely empirical science.gpuccio
July 31, 2016
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Mung: Evolutionary times, I suppose. :)gpuccio
July 31, 2016
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Therefore, the experiment tells absolutely nothing about neo darwinist evolution. When will you people admit it? My guess is at about the same time they admit a program designed to find a target phrase has nothing to do with neo darwinist evolution.Mung
July 31, 2016
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And you neo darwinists fall for it! So much for skepticism. Hanging out at a blog called "The Skeptical Zone" doesn't make one a skeptic.Mung
July 31, 2016
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Allan Miller:
So the peptide space is grudgingly accepted to be rich in ‘function’ – defined as showing up in some assay for that function – but poor in ‘naturally selectable function’? How has that been determined? You can’t just look at the space and declare it so. It renders all the ooga-booga probability calculations (and all effort spent addressing them) a waste of time, since selection is entirely context dependent. There is no information regarding it anywhere in protein space.
If you read my OP about functional information: https://uncommondescent.com/intelligent-design/functional-information-defined/ you will see that "function" is a very generic concept, unless it is linked to precise definitions and context. In ID, for example, function in itself is of no importance. What is important is only the quantity of information connected to some defined function. Complex functional information points to design, not function in itself. In neo darwinisms, the only function that counts is naturally selectable function. So, it is the burden of neo darwinists to show that naturally selectable functions exist with some relevant frequency in random libraries. That's what Keefe and Szostak's paper is supposed to do. It's not what it does. It simply uses a very generic concept of function, and then gives the illusion that the results can apply to naturally selectable function. And you neo darwinists fall for it! So much for skepticism. So your position becomes that NS of new complex functions arising from RV cannot be detected, but can exist, like the missing intermediates, and like all the myths of neo darwinism. Have you ever thought that science should be based on facts, and not only on conjectures (and rather unreasonable conjectures, for that!)gpuccio
July 31, 2016
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Rumrackest adds: "But as I wrote already earlier, we can forget about Keefe and Szostak if it makes Gpuccio feel better, and start talking about other similar types of experiments, such as Hayashi et al 2006, where the selection criterion was the capacity of a bacteriophage to infect a bacterium, using a randomized ~140 amino acid protein subdomain. So the reproductive success here was that of a bacteriophage. That’s textbook natural selection. What’s Gpuccio’s excuse going to be now?" No excuse. I am a great fan of the Ayashi paper, as everybody who reads my posts should know. It is one of the few experiments which deal really with NS. The result show clearly that, while some low level rescue of function (in a system where the function is already present and organized, but has been partially knocked out) is possible, but that the rugged nature of the functional landscape makes it practically impossible to reach the wildtype, or any comparable functionality: indeed, none of the selected sequences has any sequence homology with the wildtype. (So much for connected spaces!) And the authors compute that an initial library of 10^70 would be necessary to reach the wildtype. You see, even if you darwinists seem not to understand it, the rugged landscape is the death of any possible connected space.gpuccio
July 31, 2016
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Rumracket tries again: (we can criticize these guys as much as we like, but they are really obstinate!). "ATP binding is a naturally selectable function. Countless critical regulatory elements and core metabolic enzymes have ATP binding pockets necessary for their current function. If tomorrow all the ATP binding capacity of Gpuccio’s cells disappeared, he’d die in less than a minute (and if he doesn’t have children already, his reproductive success would go to zero)." It is tiresome to explain neo darwinism to neo darwinists, but OK: The problem is simply: is the weak ATP binding in the protein which was present in the original library naturally selectable? IOWs (please, put your full attention on it, maybe you will understand): if such a sequence arose by chance in some living being, did it give some reproductive advantage, which allowed for its selection and fixation? If the answer is no, then the sequence is not naturally selectable. As I have said, there is no trace of demonstration the either the original sequence or the final engineered protein can confer some reproductive advantage in a living system. Are you aware of any evidence that I am not aware of?gpuccio
July 31, 2016
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Rumracket at TSZ reaches new peaks of his favourite quality: "A human being being within a few meters of the test tube isn’t going to make ATP binding suddenly appear where it would not be if the human stepped further away. Gpuccio’s excuse couldn’t be any more ridiculous even if he tried." Obviously, the fact that the human being has set up columns which can bind proteins with ATP affinity, and performs mutational PCR followed by further column selection, is not relevant. The important thing is that the human being is within a few meters of the test tube. This is magic, after all. And of course nature is completely able to do the same. As OMagain has demonstrated many times, we can believe anything, if we try hard.gpuccio
July 31, 2016
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OMagain, lacking other "arguments", becomes if possible even more trivial: "gpuccio, you obviously have the time to comment on my posts rather than the more specific more technical rebuttals others have made. Why is that?" Maybe I am fascinated by your personality. By the way, which "more technical rebuttals"? Does my answer to Allan Miller at #257 count? I will answer for the moment your very technical question: "For example, are all functional proteins designed?" OK. I tend to believe that they are, but what I believe is of no importance. The correct question is: for what functional proteins can we reasonably infer design? And I have given the answer many times: For all proteins which exhibit a total functional information (or an informational transition) higher than an appropriate threshold (150 bits are good, for me), and for which there is no trace of a detailed naturally selectable pathway that can lower the probabilistic barriers (that is easy: there is no such trace at all for any complex protein).gpuccio
July 31, 2016
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Allan Miller at TSZ:
Yes, gpuccio, rounds of intelligent selection are only possible in a peptide space that is connected – where weak function can be tuned by [some kind of] selection to improve. Why is this possible in an experimental setup, yet not in nature? It’s not as if the people are picking the sequences most likely to improve. They are simply assaying for the chosen function, then subsetting the peptide library on that basis, mutating and repeating.
In this case, the only connection is between an existing affinity and a refined affinity, IOWs, a tweaking if the same function in the same functional island. That tells us absolutely nothing about "connections" between different, isolated functional islands, like protein superfamilies. I am sure that you understand that. You ask: "Why is this possible in an experimental setup, yet not in nature?" It's simple. Because here you have a function which can only be selected by us because we recognize it, and we set up the lab to select for that desired function. That's called intelligent selection, and is a form of design. In "nature", nothing like that could happen: the weak binding to ATP that was present in the original library cannot give any reproductive advantage, and therefore is not naturally selectable. Indeed, as I have said many times, not even the engineered protein is naturally selectable. Therefore, the experiment tells absolutely nothing about neo darwinist evolution. When will you people admit it? Never, I suppose.gpuccio
July 31, 2016
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gpuccio: Regardless of our opinions on the subject, we should admit that their "half full cup" optimistic view of how much is currently understood is encouraging:
[...] the genetic mechanisms of their phenotypic transition are poorly understood [...]
How much is "poorly" - 75%, 50%, 25%, 5%, 1%, 0.1%? :) That's why we've got to do more research in biology. Emphasis mine.Dionisio
July 31, 2016
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Dionisio: This is very interesting. I think Berlinski would love it! :) Hundreds of Genes Experienced Convergent Shifts in Selective Pressure in Marine Mammals.
Mammal species have made the transition to the marine environment several times, and their lineages represent one of the classical examples of convergent evolution in morphological and physiological traits. Nevertheless, the genetic mechanisms of their phenotypic transition are poorly understood, and investigations into convergence at the molecular level have been inconclusive. While past studies have searched for convergent changes at specific amino acid sites, we propose an alternative strategy to identify those genes that experienced convergent changes in their selective pressures, visible as changes in evolutionary rate specifically in the marine lineages. We present evidence of widespread convergence at the gene level by identifying parallel shifts in evolutionary rate during three independent episodes of mammalian adaptation to the marine environment. Hundreds of genes accelerated their evolutionary rates in all three marine mammal lineages during their transition to aquatic life. These marine-accelerated genes are highly enriched for pathways that control recognized functional adaptations in marine mammals, including muscle physiology, lipid-metabolism, sensory systems, and skin and connective tissue. The accelerations resulted from both adaptive evolution as seen in skin and lung genes, and loss of function as in gustatory and olfactory genes. In regard to sensory systems, this finding provides further evidence that reduced senses of taste and smell are ubiquitous in marine mammals. Our analysis demonstrates the feasibility of identifying genes underlying convergent organism-level characteristics on a genome-wide scale and without prior knowledge of adaptations, and provides a powerful approach for investigating the physiological functions of mammalian genes.
gpuccio
July 31, 2016
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Maybe this was referred here before? Epistasis in protein evolution. Starr TN1, Thornton JW2. Protein Sci. ;25(7):1204-18. doi: 10.1002/pro.2897. How mutational epistasis impairs predictability in protein evolution and design. Miton CM1, Tokuriki N1. Protein Sci. 25(7):1260-72. doi: 10.1002/pro.2876. Evolving Methanococcoides burtonii archaeal Rubisco for improved photosynthesis and plant growth. Wilson RH1, Alonso H1, Whitney SM1. Sci Rep. ;6:22284. doi: 10.1038/srep22284. Selection on different genes with equivalent functions: the convergence story told by Hox genes along the evolution of aquatic mammalian lineages. Nery MF1, Borges B2, Dragalzew AC2, Kohlsdorf T3. BMC Evol Biol. ;16(1):113. doi: 10.1186/s12862-016-0682-4. Hundreds of Genes Experienced Convergent Shifts in Selective Pressure in Marine Mammals. Chikina M1, Robinson JD2, Clark NL1. Mol Biol Evol. pii: msw112. doi: 10.1093/molbev/msw112 Not sure if it relates to the discussed topics, though.Dionisio
July 31, 2016
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OMagain at TSZ demonstrates again that he does not understand my arguments. Good.
gpuccio destroys the core of his own argument and does not seem to notice: I think we can find some sequence with a weak affinity for anything, in a modestly big library [Szostak’s] like that.
The core of my own argument? !!! And that would be? I quote my true argument, with some emphasis added just to help OMagain to understand it! (OK, one can always dream...):
The paper only shows that in a big enough random library of proteins there are a few molecules with some weak binding of ATP. And that it is possible to select those molecule in the lab, by artificial selection, and to use a procedure of rounds of mutation and further selection for ATP binding, and guess what? They obtain a molecule which strongly binds ATP. And which has some folding. And which is absolutely non naturally selectable, exactly like its precursors in the original library! Amazing! So, protein engineering works (up to a point). Who would have suspected such a thing. Important points: 1) Neither the weakly binding proteins, nor the artificially engineered final protein, have been shown to be even vaguely naturally selectable. Indeed, the final protein has been shown to be deleterious, in the right environment. 2) Some folding has been shown for the engineered protein, not for the “natural” sequences in the original library. 3) You can like the paper as you want, but it is a fact that it tells absolutely nothing about the occurrence of naturally selectable protein sequences in random libraries. Least of all quantifies it.
And from post #231:
I think we can find some sequence with a weak affinity for anything, in a modestly big library like that. So, what did they do? Did they just study the sequence which was in the library, and say: Hey, we can find this kind of sequence once in 10^11? No. Why? Because nobody would have cared. That sequence is simply insignificant. So, they did change it. By rounds of intelligent selection. But that means that the final result is not what can be found in a random library. The final result is what intelligent protein engineering (and not natural selection) can derive from a random library. This is the only honest way of putting it.
Maybe I should remind OMagain that, in his theory (neo darwinism), naturally slectable functions are the only functions that count. Any other "function" is insignificant, because it cannot be "seen" by the NS process. IOWs, any function which does not confer any reproductive advantage is not a function, in a neo darwinian context. Is that so difficult to understand? I suppose that one who embraces a scientific theory should at least try to understand it. In the meantime, I would suggest that OMagain (and a few others) read carefully this OP of mine: https://uncommondescent.com/intelligent-design/natural-selection-vs-artificial-selection/ If they want, of course. This is a free world.gpuccio
July 31, 2016
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@249
What is the funny part? Just to know.
We lack neo-Darwinian sense of humor.Dionisio
July 31, 2016
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keiths (an old "friend") makes an unusual statement at TSZ:
Since I typically disagree with gpuccio, it’s good when I occasionally find something to agree with him about. I think his criticism of Flint’s statement is valid.
Thank you Keiths. I hoped that someone at TSZ would be honest enough to admit what is obvious, but I must confess that I was not betting on that. This is appreciated. :)gpuccio
July 31, 2016
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Allan Miller at TSZ: "Random peptides have, incidentally, been shown to successfully replace knockouts for multiple functions in vivo, with absolutely no connection between the algorithm used to subset peptide space and the peptide replaced. But I guess, unless one releases them into the wild and gets a brand new pathogenic strain out of it, it’s inconclusive on the ‘selectable’ question!" I am well aware of those experiments. However, apart from the question that you correctly mention of selectability in the wild, there are a couple of other problems with those scenarios: 1) Function is only partially retrieved. Like in Ayashi's rugged landscape experiment. 2) The mechanism for that partial retrieval of function, as far as I am aware, is not elucidated. One problem with function retrieval experiments is that they rely on some functions which persists, although impaired. Moreover, function retrieval can be due to indirect events, implying other existing functions. Ayashi's experiment, IMO, is the only one where function retrieval has been directly connected to the RV in substituted sequences. And it is also the one that gives the best insight of the function landscape. As I have said, Deep mutational scanning techniques will help us understand things better. I am very confident! :)gpuccio
July 31, 2016
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OMagain at TSZ: "Hahaha! This is funny. I’m quite sure gpuccio will not appreciate how funny that is. ‘Deleterious in the right environment’ indeed." Why is it funny? I am referring to a paper where they tried to introduce the protein in a bacterial system, and it proved to be deleterious. It's the only experimental living system where it was tested, as far as I am aware. What is the funny part? Just to know.gpuccio
July 31, 2016
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Sorry for the off topic digression @247. Should move it out to another thread: https://uncommondescent.com/intelligent-design/mystery-at-the-heart-of-life/#comment-614196Dionisio
July 31, 2016
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#240, #241 & #244 follow-up 1. tRNA regulation:
1.1 Are the tRNA genes expressed straightforwardly as per the central dogma, i.e. without any post-transcriptional or post-translational modifications? 1.2 Are their expressions triggered by some kind of signaling pathways associated with specific spatiotemporal conditions?
2. aminoacyl tRNA synthetase (aaRS) regulation:
2.1 Are the aaRS genes expressed straightforwardly as per the central dogma, i.e. without any post-transcriptional or post-translational modifications? 2.2 Are their expressions triggered by some kind of signaling pathways associated with specific spatiotemporal conditions?
3. Is there any known spatiotemporal/quantitative relation between the above processes (1) and (2)?Dionisio
July 31, 2016
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Flint, at TSZ, reiterates the errors about the deck of cards arguments (always in the dice form):
This always seems to confuse some people. If the dice are fair, then ANY sequence of 10 rolls is going to be highly improbable, and all will be equally improbable. I think people tend to find ordered sequences (according to some ordering scheme in their minds) as being somehow inherently less likely. For example, they might consider a lottery number selection of 1-2-3-4-5-6 as being less likely than a more “random-looking” sequence. What would be suspicious is if the same sequence were rolled twice.
Emphasis mine. And I ask: Flint, why would that be suspicious? According to your reasoning, the first occurrence has the same probability as any other sequence. Correct. Well, but after the sequence has occurred, what is its probability of occurring a second time? The answer is simple: exactly the same. So, what is the probability of having the same sequence occurring twice in a row? Exactly the same as the probability of having any couple of sequences occur (the product of the individual probabilities). This is absolutely correct: any couple of sequences (with repetition) has the same probability to occur. So, why do you find that scenario "suspicious"? Is it because people tend to find recurring sequences (according to some scheme in their minds) as being somehow inherently less likely? No, the answer is more simple. It's because people, correctly, compute probabilities for specified sets of results. A set of ordered results is small and highly unlikely. A set of non specific, disordered results is highly likely. The same sequence twice in a row is simply a form of order. Like the ordered sequence of the cards. Like all gas molecules in half the space. Like function. Small specified sets are extremely unlikely in a big search space. Which is exactly the concept of ID. I hope that, if your anti-ID dogma allows it, you can recognize your error.gpuccio
July 31, 2016
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Dioniso: Us - them: 245 -255. Life is cruel! :)gpuccio
July 31, 2016
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Dionisio: We also have to consider that a tRNA gene is about 70 - 90 nucleotides, for a total maximum search space of 180 bits: big, but not huge. As a general rule, the lower the search space, the higher the target space/search space ratio will be, in average. In language, for example, it's easy to verify that the search space grows much more rapidly than the target space. See here: https://uncommondescent.com/intelligent-design/an-attempt-at-computing-dfsci-for-english-language/gpuccio
July 31, 2016
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Mung at #237: Just for a comparison: The correct probabilities in the case of "gas molecules in a container" scenario: 1) Probability of a state with all the molecules in the right half of the molecule, and void in the left half: practically zero. Miracle or design. 2) Probability of a state with all the molecules in the left half of the molecule, and void in the right half: practically zero. Miracle or design. 3) Probability of a state with all the molecules distributed non specifically and without any recognizable order in all the volume of the container: practically 1. What always happens.gpuccio
July 31, 2016
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Mung at #237: The correct probabilities in the deck of cards scenario: 1) Probability of a new occurrence of a sequence which we has just occurred: 1:8*10^67. Miracle or design. 2) Probability of the occurrence of the perfectly ordered sequence, independently defined: 1:8*10^67. Miracle or design. 3) Probability of the occurrence of some non specific, non ordered sequence: almost 1. What always happens.gpuccio
July 31, 2016
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Dionisio: Well, this is about a tRNA gene, so the scenario is a little different. However, the results seem quite similar, according to the abstract:
Fitness landscapes describe the genotype-fitness relationship and represent major determinants of evolutionary trajectories. However, the vast genotype space, coupled with the difficulty of measuring fitness, has hindered the empirical determination of fitness landscapes. Combining precise gene replacement and next-generation sequencing, we quantify Darwinian fitness under a high-temperature challenge for over 65,000 yeast strains each carrying a unique variant of the single-copy Embedded Image gene at its native genomic location. Approximately 1% of single point mutations in the gene are beneficial, while 42% are deleterious. Almost half of all mutation pairs exhibit significant epistasis, which has a strong negative bias except when the mutations occur at Watson-Crick paired sites. Fitness is broadly correlated with the predicted fraction of correctly folded tRNA molecules, revealing a biophysical basis of the fitness landscape.
gpuccio
July 31, 2016
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gpuccio: Have you seen this paper?
The fitness landscape of a tRNA gene Chuan Li, Wenfeng Qian, Calum J. Maclean, and Jianzhi Zhang Science. 352(6287): 837–840. doi: 10.1126/science.aae0568
Not sure if it relates to the discussed topics, though.Dionisio
July 30, 2016
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bill: "Thank you for this very interesting paper. I think it supports my hypothesis that the more ways a specific protein functions i.e. binding to small molecules other proteins etc the more critical its sequence is. When we get to nuclear proteins that may interact with dozens of other proteins most mutations will be problematic." Absolutely! And that becomes even more true for complex long regulatory proteins, like the six I have considered in my OP. And it is not necessary to have "1/total possible sequences=probability of finding the required function by random search", which is probably never true for any protein: it's enough to have a huge functional information, as measured, for example, by the conservation based methodology I have used in the OP. And the longer the protein, the more the search space becomes so huge that any functional target space, however big, can be considered as trivial in comparison (that is exactly the reason why we never get ordered states in gas molecules). And finally, let's remember that my conservation based method can only underestimate functional information, because it cannot see all the functional information in a sequence that is taxonomically restricted, or even species specific: see for example my considerations about Prickle protein here: https://uncommondescent.com/intelligent-design/information-jumps-again-some-more-facts-and-thoughts-about-prickle-1-and-taxonomically-restricted-genes/ and the interesting conclusion of the authors of the quoted paper:
By comparing the evolutionary conservation of RRM residues with their ability to function in the context of the yeast Pab1 protein, we could implicate some residues in yeast-specific functions.
(emphasis mine) IOWs, the results of their metrics, based on direct measure of function in the lab, compared with the results of a conservation based metrics (like the one I have used in the OP) can help detect that important part of functional information which is species specific. That is certainly a relevant part of the total functional information, especially in regulatory molecules, like TFs, which act multi-combinatorially, as you very correctly say. IOWs, my estimate of 1531 bits of specific functional information in astrotactin 2 based on its specific conservation in vertebrates is certainly a big underestimate! There is certainly a part of functional information, specific for example to fish, or to snakes, or to birds, or to mammals, that my methodology cannot see! But 1531 bits are common to all vertebrates, and that part my conservation based methodology sees all too well. :)gpuccio
July 30, 2016
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gpuccio
“Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein” http://www.ncbi.nlm.nih.gov/pm.....MC3851721/ Just a couple of quotes (the paper is rather complex, and really rich of facts):
Thank you for this very interesting paper. I think it supports my hypothesis that the more ways a specific protein functions i.e. binding to small molecules other proteins etc the more critical its sequence is. When we get to nuclear proteins that may interact with dozens of other proteins most mutations will be problematic. This is where we approach the equation that 1/total possible sequences=probability of finding the required function by random search.bill cole
July 30, 2016
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