Downward causation by information control in micro-organisms

Who's who in Magelona: phylogenetic hypotheses under Magelonidae Cunningham & Ramage, 1888 (Annelida: Polychaeta)

Known as shovel head worms, members of Magelonidae comprise a group of polychaetes readily recognised by the uniquely shaped, dorso-ventrally flattened prostomium and paired ventro-laterally inserted papillated palps. The present study is the first published account of inferences of phylogenetic hypotheses within Magelonidae. Members of 72 species of Magelona and two species of Octomagelona were included, with outgroups including members of one species of Chaetopteridae and four of Spionidae. The phylogenetic inferences were performed to causally account for 176 characters distributed among 79 subjects, and produced 2,417,600 cladograms, each with 404 steps. A formal definition of Magelonidae is provided, represented by a composite phylogenetic hypothesis explaining seven synapomorphies: shovel-shaped prostomium, prostomial ridges, absence of nuchal organs, ventral insertion of palps and their papillation, presence of a burrowing organ, and unique body regionation. Octomagelona is synonymised with Magelona due to the latter being paraphyletic relative to the former. The consequence is that Magelonidae is monotypic, such that Magelona cannot be formally defined as associated with any phylogenetic hypotheses. As such, the latter name is an empirically empty placeholder, but because of the binomial name requirement mandated by the International Code of Zoological Nomenclature, the definition is identical to that of Magelonidae. Several key features for future descriptions are suggested: prostomial dimensions, presence/absence of prostomial horns, morphology of anterior lamellae, presence/absence of specialised chaetae, and lateral abdominal pouches. Additionally, great care must be taken to fully describe and illustrate all thoracic chaetigers in descriptions.

An organisational systems-biology view of viruses explains why they are not alive

Whether or not viruses are alive remains unsettled. Discoveries of giant viruses with translational genes and large genomes have kept the debate active. Here, a fresh approach is introduced, based on the organisational definition of life from within systems biology. It views living as a circular process of self-organisation and self-construction which is 'closed to efficient causation'. How information combines with force to fabricate and organise environmentally obtained materials, given an energy source, is here explained as a physical embodiment of informational constraint. Comparing a general virus replication cycle with Rosen's (M,R)-system shows it to be linear, rather than closed. Some viruses contribute considerable organisational information, but so far none is known to supply all required, nor the material nor energy necessary to complete their replication cycle. As a result, no known virus replication cycle is closed to efficient causation: unlike cellular obligate parasites, viruses do not match the causal structure of an (M,R)-system. Analysis based in identifying a Markov blanket in causal structure proved inconclusive, but using Integrated Information Theory on a Boolean representation, it was possible to show that the causal structure of a virocell is not different from that of the host cell.

The Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation

Evolution exploits the physics of non-neural bioelectricity to implement anatomical homeostasis: a process in which embryonic patterning, remodeling, and regeneration achieve invariant anatomical outcomes despite external interventions. Linear "developmental pathways" are often inadequate explanations for dynamic large-scale pattern regulation, even when they accurately capture relationships between molecular components. Biophysical and computational aspects of collective cell activity toward a target morphology reveal interesting aspects of causation in biology. This is critical not only for unraveling evolutionary and developmental events, but also for the design of effective strategies for biomedical intervention. Bioelectrical controls of growth and form, including stochastic behavior in such circuits, highlight the need for the formulation of nuanced views of pathways, drivers of system-level outcomes, and modularity, borrowing from concepts in related disciplines such as cybernetics, control theory, computational neuroscience, and information theory. This approach has numerous practical implications for basic research and for applications in regenerative medicine and synthetic bioengineering.

How Organisms Gained Causal Independence and How It Might Be Quantified

Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence.

CONCLUSION

organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.

Coarse-graining as a downward causation mechanism

Downward causation is the controversial idea that 'higher' levels of organization can causally influence behaviour at 'lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Top-down models in biology: explanation and control of complex living systems above the molecular level

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering.

The hidden simplicity of biology

Life is so remarkable, and so unlike any other physical system, that it is tempting to attribute special factors to it. Physics is founded on the assumption that universal laws and principles underlie all natural phenomena, but is it far from clear that there are 'laws of life' with serious descriptive or predictive power analogous to the laws of physics. Nor is there (yet) a 'theoretical biology' in the same sense as theoretical physics. Part of the obstacle in developing a universal theory of biological organization concerns the daunting complexity of living organisms. However, many attempts have been made to glimpse simplicity lurking within this complexity, and to capture this simplicity mathematically. In this paper we review a promising new line of inquiry to bring coherence and order to the realm of biology by focusing on 'information' as a unifying concept.

Sequence Data, Phylogenetic Inference, and Implications of Downward Causation

Framing systematics as a field consistent with scientific inquiry entails that inferences of phylogenetic hypotheses have the goal of producing accounts of past causal events that explain differentially shared characters among organisms. Linking observations of characters to inferences occurs by way of why-questions implied by data matrices. Because of their form, why-questions require the use of common-cause theories. Such theories in phylogenetic inferences include natural selection and genetic drift. Selection or drift can explain 'morphological' characters but selection cannot be causally applied to sequences since fitness differences cannot be directly associated with individual nucleotides or amino acids. The relation of selection to sequence data is by way of downward or top-down causation from those phenotypes upon which selection occurs. The application of phylogenetic inference to explain sequence data is thus restricted to instances where drift is the relevant theory; those nucleotides or amino acids that can be explained via downward causation are precluded from inclusion in the data matrix. The restrictions on the inclusion of sequence data in phylogenetic inferences equally apply to species hypotheses, precluding the more restrictive approach known as DNA barcoding. Not being able to discern drift and selection as relevant causal mechanisms can severely constrain the inclusion and explanations of sequence data. Implications of such exclusion are discussed in relation to the requirement of total evidence.

RNA self-assembly and RNA nanotechnology

CONSPECTUS: Nanotechnology's central goal involves the direct control of matter at the molecular nanometer scale to build nanofactories, nanomachines, and other devices for potential applications including electronics, alternative fuels, and medicine. In this regard, the nascent use of nucleic acids as a material to coordinate the precise arrangements of specific molecules marked an important milestone in the relatively recent history of nanotechnology. While DNA served as the pioneer building material in nucleic acid nanotechnology, RNA continues to emerge as viable alternative material with its own distinct advantages for nanoconstruction. Several complementary assembly strategies have been used to build a diverse set of RNA nanostructures having unique structural attributes and the ability to self-assemble in a highly programmable and controlled manner. Of the different strategies, the architectonics approach uniquely endeavors to understand integrated structural RNA architectures through the arrangement of their characteristic structural building blocks. Viewed through this lens, it becomes apparent that nature routinely uses thermodynamically stable, recurrent modular motifs from natural RNA molecules to generate unique and more complex programmable structures. With the design principles found in natural structures, a number of synthetic RNAs have been constructed. The synthetic nanostructures constructed to date have provided, in addition to affording essential insights into RNA design, important platforms to characterize and validate the structural self-folding and assembly properties of RNA modules or building blocks. Furthermore, RNA nanoparticles have shown great promise for applications in nanomedicine and RNA-based therapeutics. Nevertheless, the synthetic RNA architectures achieved thus far consist largely of static, rigid particles that are still far from matching the structural and functional complexity of natural responsive structural elements such as the ribosome, large ribozymes, and riboswitches. Thus, the next step in synthetic RNA design will involve new ways to implement these same types of dynamic and responsive architectures into nanostructures functioning as real nanomachines in and outside the cell. RNA nanotechnology will likely garner broader utility and influence with a greater focus on the interplay between thermodynamic and kinetic influences on RNA self-assembly and using natural RNAs as guiding principles.

RNA modularity for synthetic biology

RNA molecules are highly modular components that can be used in a variety of contexts for building new metabolic, regulatory and genetic circuits in cells. The majority of synthetic RNA systems to date predominately rely on two-dimensional modularity. However, a better understanding and integration of three-dimensional RNA modularity at structural and functional levels is critical to the development of more complex, functional bio-systems and molecular machines for synthetic biology applications.

Top-down causation: an integrating theme within and across the sciences?

This issue of the journal is focused on ‘top-down (downward) causation'. The words in this title, however, already raise or beg many questions. Causation can be of many kinds. They form our ways of ordering our scientific understanding of the world, all the way from the reductive concept of cause as elementary objects exerting forces on each other, through to the more holistic concept of attractors towards which whole systems move, and to adaptive selection taking place in the context of an ecosystem. As for ‘top’ and ‘down’, in the present scientific context, these are clearly metaphorical, as some of the articles in this issue of the journal make clear. Do we therefore know what we are talking about? The meeting at the Royal Society on which this set of papers is based included philosophers as well as scientists, and some of those (Jeremy Butterfield, Barry Loewer, Alan Love, Samir Okasha and Eric Scerri) have contributed articles to this issue. We would like also to thank those (Claus Kiefer, Peter Menzies, Jerome Feldman and David Papineau) who contributed only to the discussion meeting. Their contributions were also valuable, both at the meeting and by influencing the articles that have been written by others. We include a glossary with this introduction, composed by one of us (O'Connor). The clarification of the use of words and their semantic frames is an important role of philosophy, and this was evident in the discussions at the meeting and is now evident in many of the articles published here. Moreover, philosophical analysis is not limited to the papers by the professional philosophers. The idea of top-down causation is intimately related to concepts of emergence; indeed, it is a key factor in strong theories of emergence.

Top-down causation and emergence: some comments on mechanisms

Both bottom-up and top-down causation occur in the hierarchy of structure and causation. A key feature is multiple realizability of higher level functions, and consequent existence of equivalence classes of lower level variables that correspond to the same higher level state. Five essentially different classes of top-down influence can be identified, and their existence demonstrated by many real-world examples. They are: algorithmic top-down causation; top-down causation via non-adaptive information control, top-down causation via adaptive selection, top-down causation via adaptive information control and intelligent top-down causation (the effect of the human mind on the physical world). Through the mind, abstract entities such as mathematical structures have causal power. The causal slack enabling top-down action to take place lies in the structuring of the system so as to attain higher level functions; in the way the nature of lower level elements is changed by context, and in micro-indeterminism combined with adaptive selection. Understanding top-down causation can have important effects on society. Two cases will be mentioned: medical/healthcare issues, and education-in particular, teaching reading and writing. In both cases, an ongoing battle between bottom-up and top-down approaches has important consequences for society.

Attenuation of loop-receptor interactions with pseudoknot formation

RNA tetraloops can recognize receptors to mediate long-range interactions in stable natural RNAs. In vitro selected GNRA tetraloop/receptor interactions are usually more ‘G/C-rich’ than their ‘A/U-rich’ natural counterparts. They are not as widespread in nature despite comparable biophysical and chemical properties. Moreover, while AA, AC and GU dinucleotide platforms occur in natural GAAA/11 nt receptors, the AA platform is somewhat preferred to the others. The apparent preference for ‘A/U-rich’ GNRA/receptor interactions in nature might stem from an evolutionary adaptation to avoid folding traps at the level of the larger molecular context. To provide evidences in favor of this hypothesis, several riboswitches based on natural and artificial GNRA receptors were investigated in vitro for their ability to prevent inter-molecular GNRA/receptor interactions by trapping the receptor sequence into an alternative intra-molecular pseudoknot. Extent of attenuation determined by native gel-shift assays and co-transcriptional assembly is correlated to the G/C content of the GNRA receptor. Our results shed light on the structural evolution of natural long-range interactions and provide design principles for RNA-based attenuator devices to be used in synthetic biology and RNA nanobiotechnology.