(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Introduction
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Glossary
Recent Additions
Search
Submit

VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

A. A Further Report of Common Principles

Salman, Hanna, et al. Universal Protein Fluctuations in Populations of Microorganisms. Physics Review Letters. 108/238105, 2012. Similar to Nacher and Ochiai above, University of Pittsburgh biophysicists detect a common explicate recurrence amongst life’s metabolisms of nature’s ubiquitous lineaments and vitality.

The copy number of any protein fluctuates among cells in a population; characterizing and understanding these fluctuations is a fundamental problem in biophysics. We show here that protein distributions measured under a broad range of biological realizations collapse to a single non-gaussian curve under scaling by the first two moments. Moreover, in all experiments the variance is found to depend quadratically on the mean, showing that a single degree of freedom determines the entire distribution. Our results imply that protein fluctuations do not reflect any specific molecular or cellular mechanism, and suggest that some buffering process masks these details and induces universality. (Abstract)

Sarpeshkar, Rahul. Analog Synthetic Biology. Philosophical Transactions of the Royal Society. Online March, 2014. Nature is not purely digital. While molecules are discrete and digital, all molecular interactions that lead to computation, e.g., association, transformation and dissociation chemical reactions, have a probabilistic analog nature to them. (2) A MIT bioelectrical engineer makes a strong claim that life does not evolve as isolate entities only, rather it is graced by equally real communicative interrelations. Thus a complementarity of analog and digital phase aspects would better distinguish organisms. It is also averred that Digital computation is a subset of analog computation, which we might note is akin to our own brains, especially a woman’s bicameral mind. Such insights and syntheses are then said to provide a better guide for palliative synthetic biology enhancements.

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog–digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets.

We present schematics for efficiently representing analog DNA–protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations. (Abstract)

Schack, Carolann, et al. Modularity is the Mother of Invention: A Review of Polymorphism in Bryozoans. Biological Reviews. Online November, 2018. Victoria University of Wellington, New Zealand biologists post a 35 page study of how pervasive nature’s evolutionary and biological employ of semi-autonomous modular units within larger assemblies such as bodies and brains actually is. Some two decades after their initial view by Gunter Wagner and others, this efficient structural composition, famously noted by Herbert Simon (search) in the 1960s, can now be well affirmed across the Metazoan lineages.

Modularity is a fundamental concept in biology. Most taxa within the colonial invertebrate phylum Bryozoa have achieved division of labour through the development of specialized modules (polymorphs), and this group is well exemplifies this phenomenon. We provide a comprehensive description of the diversity, morphology and function of these polymorphs and the significance of modularity to the evolutionary success of the phylum, which has >21000 described fossil and living species. Modular diversity likely arose from heterogeneous microenvironmental conditions, and repeated module clusters are an emergent property of zooid plasticity. (Abstract excerpt)

Scheffer, Marten. Critical Transitions in Nature and Society. Princeton: Princeton University Press, 2009. Because research results are now sufficiently established and wide ranging, a Wageningen University (Netherlands) theoretical ecologist can accomplish a book length compilation of how life’s evolution, natural ecosystems, and human civilizations have each and all come to be poised in a dynamical self-organized state. An initial Part explains such Emergent Patterns in Complex Systems, which are then shown to universally apply, via Case Studies, from lakes, climate, the Cambrian burst of species, oceans to cities in unsustainable crisis. A running implication is that the whole biotic Earth ought to be seen as residing in a critical state between order and chaos, which now quite demands our mitigating analysis and attention. See also an article from a team lead by Scheffer "Early-Warning Signals for Critical Transitions," Nature (461/53, 2009).

Scheffer, Marten, et al. Early-Warning Signals for Critical Transitions. Nature. 461/53, 2009. A ten man team across the EU and USA find that when complex dynamical systems from climates and fisheries to asthma attacks and financial failures approach a “tipping point” bifurcation, certain constant signs become evident. These are: slower recovery from perturbations, increased autocorrelation (repeated patterns), and increased variance magnitude. Such phenomena are then seen to appear everywhere “…regardless of differences in the details of each system,” which would suggest an independent mathematical existence. See also Scheffer’s new book Critical Transitions in Nature and Society.

Schlosser, Gerhard and Gunter Wagner, eds. Modularity in Development and Evolution. Chicago: University of Chicago Press, 2003. This comprehensive work on the constant employ of modular components and processes is reviewed more in Part V: A Quickening Evolution.

Modularity pervades every level of biological organization. From proteins to populations, larger biological units are built of smaller, quasi-autonomous parts. (Craig Nelson 17) The modular architecture of metazoan body plans is generated by a similarly modular genetic regulatory hierarchy. (CN 30)

Schuster, Peter. Nonlinear Dynamics from Physics to Biology. Complexity. 12/4, 2007. The Austrian editor-in-chief of this journal perceives the self-organization paradigm to now reach a broad acceptance across the scientific disciplines and rightly apply to human intention. This article was prompted by the 2006 conference of the European Complex Systems Society, check their website for more such info.

Schwab, Julian, et al. Concepts in Boolean Network Modeling. Computational and Structural Biotechnology Journal. March, 2020. Ulm University system biochemists contribute some latest verifications of Stuart Kauffman’s first 1969 notice that living nature can be described by these mathematical topologies. The paper reviews their technical features and a few biological applications. In closing it notes that in contrast to a reductive focus, if in addition the presence of these real interconnective dynamics is allowed, then an integral model of life’s evolutionary animation can be achieved. The 140 references from this composite 21st century endeavor (search Villani, et al) well augurs for a 2020 discovery.

Boolean network models are one of the simplest models to study complex dynamic behavior in biological systems. They can be applied to unravel the mechanisms regulating the properties of the system or to identify promising intervention targets. Since its introduction by Stuart Kauffman in 1969 for describing gene regulatory networks, various biologically based networks and tools for their analysis were developed. Here, we summarize and explain the concepts for Boolean network modeling. We also present application examples and guidelines to work with and analyze Boolean network models. (Abstract)

Boolean networks are well-studied discrete models of biological networks such as gene regulatory networks where DNA segments in a cell interact with each other indirectly through their RNA and protein expression products or with other substances in the cell, thereby governing the rates at which genes in the network are transcribed into mRNA. (Google BN)

Sigaki, Higor, et al. History of Art Paintings through the Lens of Entropy and Complexity. Proceedings of the National Academy of Sciences. 115/E8585, 2018. Akin to how Nakamura and Kaneko (above) find nonlinear patterns amongst musical compositions, systems physicists Sigaki and Haroldo Ribeiro, Univerisidade Estadual de Maringa, Brazil and Matjaz Perc, University of Maribor, Slovenia discern the presence of intrinsic recurrent forms across a wide array (over fifty) of artistic schools from Romanticism to Art-Deco.

Art is the ultimate expression of human creativity that is deeply influenced by the philosophy and culture of the corresponding historical epoch. Here, we present a large-scale quantitative analysis of almost 140,000 paintings, spanning nearly a millennium. Based on local spatial patterns in the images of these paintings, we estimate the permutation entropy and the statistical complexity. These measures map the degree of visual order of artworks into a scale of order–disorder and simplicity–complexity. The dynamical behavior of these measures reveals a clear temporal evolution of art, marked by transitions that agree with the main historical periods of art. Our research shows that different artistic styles have a distinct average degree of entropy and complexity, thus allowing a hierarchical organization and clustering of styles. (Abstract excerpt)

Singh Sandhu, Kuljeet, et al. Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks. Cell Reports. Vol. 2/Pg. 1207, 2012. “Chromatin is the combined DNA and proteins that make up the nucleus of a cell.” Various headings are Chromatin Communities Organize Functional Compartmentalization, Transcription-Associated Chromatin Interactions Form a Complex Hierarchical Network, Chromatin Communities are Evolutionarily Constrained. In this new online journal from Cell Press, 17 co-authors from Singapore, India, Australia, Croatia, USA, and Hungary, perceive in self-organizing genomes an innate propensity to form into invariant, communally nested networks. This paper could be paired with “Community Landscapes,” Istvan Kovacs, et al, herein, with Peter Csermely listed on both, because they realize that this lively phenomena is an iconic exemplar of nature’s universal sustainable reciprocity of agency and communion.

Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic (see next) through evolution. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions. (Summary excerpts)

In classical genetics, synteny describes the physical co-localization of genetic loci on the same chromosome within an individual or species. Today, however, biologists usually refer to synteny as the conservation of blocks of order within two sets of chromosomes that are being compared with each other. This concept can also be referred to as shared synteny. (Wikipedia)

Sinha, Saurabh, et al. Behavior-related Gene Regulatory Networks: A New Level of Organization in the Brain. Proceedings of the National Academy of Sciences. 117/23270, 2020. In this significant contribution, fifteen systems biologists from the University of Illinois, SUNY Buffalo, UT Austin (Hans Hofmann), UM Amherst, University of Toronto, and Cornell University trace these basic genetic functions all the way to their cerebral presence and effect. By so doing, a novel dimension can be added to neural operations and cognitive behaviors. In a further take, here is another example of a common interchange of this archetypal formative system.

Neuronal networks are the standard model today to describe brain activity associated with animal behavior. Recent studies now reveal an extensive role for a completely distinct layer of networked activities in the brain — the gene regulatory network (GRN) — that expresses thousands of genes in a behavior-related manner. We examine emerging insights into the relationships between these two types of networks and discuss their interplay in spatial and temporal dimensions across multiple scales of organization. We discuss properties expected of behavior-related GRNs by drawing upon the rich literature on GRNs related to animal development. (Abstract excerpt)

A rich body of genetic and, more recently, genomic studies have revealed that behavior is also associated with the coordinated activities of genes that operate in brain cells. Many studies have found significant, predictable, and specific changes in brain gene expression profiles associated with behavioral responses to particular environmental stimuli. These findings suggest that a second layer of network biology — that of gene regulatory networks — also underlies behavior. (23270)

Smith, Eric and Harold Morowitz. Universality in Intermediary Metabolism. Proceedings of the National Academy of Sciences. 101/13168, 2004. The stoichiometry, energetics, and reaction concentration dependence of the reductive tricarboxylic acid cycle, via its network and autocatalytic properties, is proposed as a primordial metabolic core.

Widespread or universal structures and processes in cellular biochemistry are central to a coherent understanding of life, much as universality in physics has become central to understanding order in condensed-matter systems. (13168)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next  [More Pages]