[Fis] NEW YEAR LECTURE (Youri Timsit)

[Loet Leydesdorff]

Dear Gordana:

I highly appreciate your comments. They re to the point.

>For those of us who are not biologists, it would be good to understand 
>the role of those structures in information processing.
>
Structures are structural and systemic. Unlike variation, they are not 
manifest (phenotypical). They are selective. Selection may change the 
balance between filled and unfilled boxes in the data matrix, and thus 
between entropy and redundancy. [H (max) = R + I)]

>Also of relevance might be their temporal behavior, i.e. information 
>transformation and synchronization between processes, including 
>different levels of organization.
>
Would this be the dynamic (temporal) equivalent of structures at each 
moment of time?

>Moreover, one would like to make evolutionary connections between those 
>structures and processes on different scales.
>
>If I understand correctly, those are open questions. Are there any 
>ideas about answers already?
>
The selection mechanisms are probably different. I like this intuition 
from Luhmann (in the discussion with Habermas, 1971):

Rather, what is special about the meaningful or meaning-based processing 
of experience is that it makes possible both the reduction and the 
preservation of complexity; i.e., it provides a form of selection that 
prevents the world from shrinking down to just one particular content of 
consciousness with each act of determining experience. (1990, p. 27)

It seems to me that this other selection mechanism would be intentional 
and therefore future oriented, while traditional selection evolves in 
history. A further selection on historical trajectories can lead to 
evolutionary regimes. Trajectories are history-based; regimes 
expectation-based. The Dubois-formulas for anticipation could be helpful 
for the formalization. Biological selection (upon variation) would then 
be a special case or -- in other words -- a subdynamic (retention).

Best, Loet

PS: Happy New Year for all of you! L.

_______________

Loet Leydesdorff



"The Evolutionary Dynamics of Discusive Knowledge" 
<https://link.springer.com/book/10.1007/978-3-030-59951-5>(Open Access)

Professor emeritus, University of Amsterdam

Amsterdam School of Communication Research (ASCoR)

loet en leydesdorff.net <mailto:loet en leydesdorff.net>; 
http://www.leydesdorff.net/

http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en

ORCID: http://orcid.org/0000-0002-7835-3098;




>
>
>All the best,
>
>Gordana
>
>
>
>http://gordana.se/
>
>
>
>From: Fis <fis-bounces en listas.unizar.es> on behalf of "Pedro C. 
>Marijuán" <pedroc.marijuan en gmail.com>
>Date: Monday, 10 January 2022 at 18:58
>To: "fis en listas.unizar.es" <fis en listas.unizar.es>
>Subject: Re: [Fis] NEW YEAR LECTURE (Youri Timsit)
>
>
>
>Dear Youri and colleagues,
>
>
>
>Many thanks for your contribution, which we appreciate as it comes from 
>one of the leading groups in ribosome research.
>
>I assume that for some fis parties this kind of cutting edge research 
>may be outside their scope, but it contains a trove of informational 
>problems.
>
>And it may deserve an attention effort.
>
>
>
>To understand better what I mean, and the full implications of Youri's 
>research, let me recommend his recent paper:
>
>Timsit, Y. & Grégoire, S.-P. Towards the Idea of Molecular Brains. 
>International Journal of Molecular Sciences22, 11868 (2021).
>
>It is in an open source journal, can be easily downloaded at: 
>https://www.mdpi.com/1422-0067/22/21/11868 
><https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.mdpi.com%2F1422-0067%2F22%2F21%2F11868&data=04%7C01%7Cgordana.dodig-crnkovic%40mdh.se%7Cade07b6d925d4d3ff52308d9d4628520%7Ca1795b64dabd4758b988b309292316cf%7C0%7C0%7C637774343002525736%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=WBtQ1o7933ReviLgj2bCYJ1TNGjj6NbrkKl6%2B0z3yCo%3D&reserved=0>
>
>
>
>To summarize: we find an amazing protein network in the ribosome,
>
>We find an amazing signaling network in eukaryotic cells (and in many 
>prokaryotes too),
>
>and we find neuronal networks in primitive nervous systems and also 
>(far more developed) in central nervous systems.
>
>These are the main parts of that article (by the way, it contains one 
>of the most cogent compilations of cellular signaling systems--highly 
>recommended only for that).
>
>
>
>So, we have three modalities of information processing networks at 
>increasing levels of complexity.
>
>The three of them are closely related to "function" of a larger entity, 
>they are "anticipative", and probably can be partially capture by 
>notions of the "Bayesian Brain".
>
>
>
>I have argued several times about the link between signaling systems 
>and the life cycle as the biological underpinnings of "meaning".
>
>This is an excellent occasion to realize the full extension of the 
>molecular partners involved.
>
>
>
>Best wishes to all,
>
>--Pedro
>
>
>
>El 08/01/2022 a las 20:49, Pedro C. Marijuan escribió:
>
>>Asunto:
>>
>>  NEW YEAR LECTURE
>>
>>Fecha:
>>
>>Thu, 06 Jan 2022 15:09:26 +0100
>>
>>De:
>>
>>Youri Timsit <youri.timsit en mio.osupytheas.fr> 
>><mailto:youri.timsit en mio.osupytheas.fr>
>>
>>Para:
>>
>>Pedro C. Marijuán <pedroc.marijuan en gmail.com> 
>><mailto:pedroc.marijuan en gmail.com>
>>
>>
>>
>>
>>
>>Happy New Year to all!
>>
>>
>>
>>
>>First of all I would like to warmly thank Pedro Marijuán for having 
>>offered me to contribute to this New Year lecture. It is a great 
>>pleasure to exchange ideas in a context where “informational 
>>choreography” 1 allows for imaginary encounters between Isadora Duncan 
>>and José Ortega y Gasset, to explore new ways of thinking about “what 
>>is life”. The topic of this new year lecture is “molecular brains”, a 
>>theme that has recently been developed on the basis of recent work on 
>>the ribosome 2,  D. Bray's seminal paper published in 1995 3 and the 
>>recent papers about consciousness in non-neural organisms 4
>>
>>
>>
>>Are “molecular brains” a “vision of the mind” or a real property of 
>>matter and universe, born from the first forms of life? And as a 
>>corollary, did LUCA have a brain (molecular) and was he “intelligent”? 
>>And to go even further, is having systems capable of developing 
>>complex behaviours and cognitive faculties a fundamental property of 
>>living beings across scales? I hope that future works will shed light 
>>on these questions, but in the meantime, I present here briefly, the 
>>elements that led to the conclusion that systems equivalent of “neural 
>>networks” on a molecular scale could exist in the ribosome and that 
>>these systems most probably existed before the radiation of the three 
>>kingdoms.
>>
>>
>>
>>The ribosome is indeed considered as window towards the earliest forms 
>>of life that predate the three kingdoms. While in astrophysics looking 
>>far away gives the opportunity to glimpse the fossil radiation of the 
>>universe, looking into the heart of the ribosome may tell us of what 
>>the first forms of life might have looked like. The ribosome evolved 
>>by accretion around a core that predates the radiation of the three 
>>kingdoms and were probably present in LUCA 5–9. The ribosomes are thus 
>>considered as a relic of ancient translation systems that co-evolved 
>>with the genetic code have evolved by the accretion of rRNA and 
>>ribosomal (r)-proteins around a universal core 8,10–14. They then 
>>followed distinct evolutionary pathways to form the bacterial, 
>>archaeal and eukaryotic ribosomes whose overall structures are well 
>>conserved within kingdoms 15–18. The complexity of ribosome 
>>assemblies, structures, efficiencies and translation fidelity 
>>concomitantly increased in course of the evolution.
>>
>>
>>
>>The molecular brain’s story started with an attempt to understand the 
>>surprising electrostatic properties of the bL20 ribosomal protein 
>>(r-protein), a protein essential for the assembly of the large subunit 
>>of the bacterial ribosome 19. This r-protein had a kind of subversive 
>>and unique behaviour in deciding to crystallize in both a folded and 
>>an unfolded form within the same crystal 20. In trying to better 
>>understand its properties, we compared it to the other r-proteins 
>>located in the first high-resolution ribosome structures that had just 
>>been published 21... and that's when something strange was noticed: we 
>>realized that uL13 and uL3, two r-proteins of the large subunit, were 
>>touching each other by a tenuous interaction between their two 
>>extensions, long filaments that weave between the phosphate groups of 
>>the rRNA. At that time, these famous r-protein extensions were a real 
>>enigma. It was thought that they could play a role in ribosome 
>>assembly by neutralising RNA phosphates with their positively charged 
>>amino acids 22. But gradually it became apparent that all extensions 
>>of r-proteins systematically wove a gigantic network based on tiny 
>>interactions between them. In general, when proteins interact with 
>>partners, they form large interfaces (> 2000 Å2) sufficient to 
>>stabilise their interactions. In this case, the vast majority of the 
>>interfaces did not exceed 200 Å2, which is all the more surprising 
>>given that they were extremely conserved phylogenetically 23.
>>
>>
>>
>>Strikingly, it was found that the r-protein network also interacted 
>>with or “innervate” the ribosome functional centres such as tRNA 
>>sites, the Peptidyl Transfer Centre (PTC), and the peptide tunnel 
>>23,24. Due to its functional analogy with a sensor-motor network, the 
>>r-protein network has been compared to a neural network, at the 
>>molecular level. Thus, it has been concluded that these tiny but 
>>highly conserved interfaces have been selected during evolution to 
>>play a specific role in inter-protein communication and they possess 
>>interacting residues to ensure information transfer from a protein to 
>>another. Thus, these tiny “molecular synapses" display a “necessary 
>>minimum” for allosteric transmission: a few conserved aromatic/charged 
>>amino acid motifs (fig. 1). Moreover, it is possible that these 
>>minimalist “molecular synapses” reveal much more general principles in 
>>molecular communication. Indeed, these tiny interfaces, which appear 
>>in their simplest expression in the ribosome thanks to the spatial 
>>constraints of ribosomal RNA (rRNA), could be ubiquitous in 
>>macromolecular complexes, but drowned out by a 'structural' background 
>>involving other amino acids for their stabilisation.
>>
>>
>>
>>
>>Figure 1. Molecular synapses and wires in the bacterial large subunit 
>>r-protein network. The tiny interfaces (the molecular synapses) 
>>between r-proteins are represented by surfaces
>>
>>
>>
>>Data from the literature support our “vision of mind” that r-protein 
>>networks could contribute in both the ribosomal assembly and in the 
>>“sensorimotor control” during protein synthesis. Many experimental 
>>studies have indeed shown indeed that ribosome functional sites 
>>continually exchange and integrate information during the various 
>>steps of translation. As the numerous studies of the Dinman group have 
>>shown: “an extensive network of information flow through the ribosome” 
>>during protein biosynthesis 25–32. For example, several studies have 
>>also demonstrated long-range signalling between the decoding centre 
>>that monitors the correct geometry of the codon-anticodon and other 
>>distant sites such as the Sarcin Ricin Loop (SRL) or the E-tRNA site 
>>15,33. R-proteins of the ribosomal tunnel also play an active role in 
>>the regulation of protein synthesis and co-translational folding 
>>34,35. Ribosomes also perceive each other through quality sensor of 
>>collided ribosomes in eukaryotes 36. In addition, the ribosomes 
>>synchronize many complex movements during the translation cycles 
>>37–39. The recent discoveries of “ribosome heterogeneity” 40 also 
>>significantly expands the complexity of the possible ribosome’s 
>>network topologies 41 and  open new perspective on “network 
>>plasticity” that could also play a role its behavioural richness.
>>
>>A recent interdisciplinary study with my mathematician colleagues 
>>Daniel Bennequin and Grégoire Segeant-Perthuis has shown how r-protein 
>>networks have evolved toward a growing complexity through the 
>>coevolution of the r-protein extensions and the increasing number of 
>>connexions 42. This study revealed that network expansion is produced 
>>by the collective (co)-evolution of r-proteins leading to an 
>>asymmetrical evolution of the two subunits. Furthermore, graph theory 
>>showed that the network evolution did not occur at random: each new 
>>occurring extensions and connections gradually relates functional 
>>modules and places the functional centres in central positions of the 
>>network. The strong selective pressure that is also expressed at the 
>>amino acid acquisition links the network architectures and the 
>>r-protein phylogeny thus suggesting that the networks have gradually 
>>evolved to sophisticated allosteric pathways. The congruence between 
>>independent evolutionary traits indicates that the network 
>>architectures evolved to relate and optimize the information spread 
>>between functional modules (fig. 2). In summary, graph theory, without 
>>knowing the function of the ribosome, can blindly detect the central 
>>functional centres of the ribosome. Conversely, ribosomes have learned 
>>graph theory during evolution, by placing the PTC and important 
>>functional centres at nodes corresponding to the maximum centrality of 
>>the network.
>>
>>
>>
>>
>>
>>
>>
>>Figure 2. r-protein and functional centres  networks in the large 
>>subunit of the eukaryotic ribosome. The r-proteins and their 
>>extensions are represented according to their evolutionary status. 
>>Universal (common to bacteria, archaea and eukarya): red; Archaea: 
>>cyan; Eukarya: yellow. Lines between two circles symbolize an 
>>interaction between two globular domains. The colours of the lines 
>>follow the code for the evolutionary status described above, except 
>>for eukarya specific connection that are represented with black lines, 
>>for clarity. “N” or “C” indicate if the seg or mix are N-terminal or 
>>C-terminal extensions. NC indicates proteins without a globular domain 
>>(uS14, eL29, eS30, eL37 and eL39). Functional sites (PTC, Tunnel, 
>>tRNAs and mRNA) are represented in light blue. The names of bacterial 
>>proteins which, by convergence, occupy a position similar to that of 
>>Eukaryotic or Archaeal r-proteins, are shown in blue below the 
>>circles.
>>
>>
>>
>>Moreover, a network archaeology study has also revealed the existence 
>>of a universal network, that consists of 49 strictly conserved 
>>connections that was probably present before the radiation of the 
>>bacteria and archaea 43. This primordial network is much more 
>>developed in the small ribosomal subunit suggesting that the large 
>>subunit network complexity developed in later evolutionary stages. 
>>These findings therefore suggest that LUCA already possessed such type 
>>of molecular networks, with long wires and tiny interfaces. 
>>Interestingly, these networks also mix the i-systems of rRNA and 
>>aromatic amino acids of proteins for forming conserved structural 
>>motifs probably involved in a still unknown mechanism of signal 
>>transduction (probably involving electron or charge transfer). It is 
>>therefore possible that this ancestral mode of communication has then 
>>not only evolved in modern ribosomes but in other macromolecular 
>>systems for information transfer and processing. These results 
>>therefore suggest that the ribosome opens a window on the first 
>>information processing networks, which appeared at the origin of life. 
>>They probably diverged towards other cell systems that have been 
>>compared to brains such as the multiple nano-brains. These works 
>>provide the molecular basis to decipher how non-neural unicellular 
>>organisms may display complex behaviours such as associative learning 
>>and decision-making1,2,44.
>>
>>
>>
>>Waiting for your comments and opinions,
>>
>>Best regards to all!
>>
>>Youri
>>
>>
>>
>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>Coexistence of two protein folding states in the crystal structure of 
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>>
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>>
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>>
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>>
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>>Ribosome Facts, Hypotheses and Perspectives. Int J Mol Sci20, (2019).
>>
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>>
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>>
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>>
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>>
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>>
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>>
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>>2203–2216 (2016).
>>
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>>
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>>
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>>
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>>hub for protein quality control. Mol. Cell49, 411–421 (2013).
>>
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>>of Collided Ribosomes. Mol Cell72, 469-481.e7 (2018).
>>
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>>
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>>ribosomal RNAs. Nucleic Acids Res43, 4640–4649 (2015).
>>
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>>
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>>Life. Mol. Cell71, 364–374 (2018).
>>
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>>
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>>
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>>
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>>throughout Biological Systems. Front Psychol7, 902 (2016).
>>
>>
>>
>>
>>
>>-----------------------------------------------------------
>>
>>
>>
>>
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