scholarly journals Darwinian properties and their trade-offs in autocatalytic RNA reaction networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sandeep Ameta ◽  
Simon Arsène ◽  
Sophie Foulon ◽  
Baptiste Saudemont ◽  
Bryce E. Clifton ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Network Topology ◽  
Droplet Microfluidics ◽  
Reaction Networks ◽  
Major Goal ◽  
Systems Chemistry ◽  
Trade Offs ◽  
Chemical States ◽  
The Origin Of Life ◽  
Autocatalytic Networks

AbstractDiscovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, differential reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that growth increases with global connectivity. These rules imply trade-offs between reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

scholarly journals Darwinian properties and their trade-offs in autocatalytic RNA reaction networks

2019 ◽  
Author(s):  
Sandeep Ameta ◽  
Simon Arsène ◽  
Sophie Foulon ◽  
Baptiste Saudemont ◽  
Bryce E. Clifton ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Network Topology ◽  
Droplet Microfluidics ◽  
Reaction Networks ◽  
Major Goal ◽  
Systems Chemistry ◽  
Trade Offs ◽  
Chemical States ◽  
The Origin Of Life ◽  
Autocatalytic Networks

Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, differential reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that reproduction increases with global connectivity. These rules imply trade-offs between reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

Seeking to uncover biology's chemical roots

2019 ◽  
Vol 3 (5) ◽  
pp. 435-443 ◽  
Author(s):  
Addy Pross
Keyword(s):  
Environmental Changes ◽  
Biological Systems ◽  
Significant Development ◽  
The Road ◽  
Physical Chemical ◽  
Systems Chemistry ◽  
Biological World ◽  
Inanimate Matter ◽  
The Origin Of Life ◽  
Opening Up

Despite the considerable advances in molecular biology over the past several decades, the nature of the physical–chemical process by which inanimate matter become transformed into simplest life remains elusive. In this review, we describe recent advances in a relatively new area of chemistry, systems chemistry, which attempts to uncover the physical–chemical principles underlying that remarkable transformation. A significant development has been the discovery that within the space of chemical potentiality there exists a largely unexplored kinetic domain which could be termed dynamic kinetic chemistry. Our analysis suggests that all biological systems and associated sub-systems belong to this distinct domain, thereby facilitating the placement of biological systems within a coherent physical/chemical framework. That discovery offers new insights into the origin of life process, as well as opening the door toward the preparation of active materials able to self-heal, adapt to environmental changes, even communicate, mimicking what transpires routinely in the biological world. The road to simplest proto-life appears to be opening up.

scholarly journals Grip on complexity in chemical reaction networks

2017 ◽  
Vol 13 ◽  
pp. 1486-1497 ◽  
Author(s):  
Albert S Y Wong ◽  
Wilhelm T S Huck
Keyword(s):  
Complex Networks ◽  
Chemical Reaction ◽  
Biological Networks ◽  
Chemical Reaction Networks ◽  
Living Systems ◽  
Reaction Networks ◽  
Natural Systems ◽  
Systems Chemistry ◽  
Single Chemical ◽  
And Control

A new discipline of “systems chemistry” is emerging, which aims to capture the complexity observed in natural systems within a synthetic chemical framework. Living systems rely on complex networks of chemical reactions to control the concentration of molecules in space and time. Despite the enormous complexity in biological networks, it is possible to identify network motifs that lead to functional outputs such as bistability or oscillations. To truly understand how living systems function, we need a complete understanding of how chemical reaction networks (CRNs) create function. We propose the development of a bottom-up approach to design and construct CRNs where we can follow the influence of single chemical entities on the properties of the network as a whole. Ultimately, this approach should allow us to not only understand such complex networks but also to guide and control their behavior.

scholarly journals An Effective on-Chip Network Topology for Network on Chip (Noc) Trade-Offs

2016 ◽  
Vol 9 (17) ◽  
Author(s):  
M. Venkateswara Rao ◽  
T. V. Rama Krishna ◽  
S. Raaga Sai Sruthi ◽  
S. Akhila ◽  
Y. Gopi ◽  
...  
Keyword(s):  
Network Topology ◽  
Network On Chip ◽  
Trade Offs ◽  
On Chip

scholarly journals The structure of autocatalytic networks, with application to early biochemistry

2020 ◽  
Vol 17 (171) ◽  
pp. 20200488
Author(s):  
Mike Steel ◽  
Joana C. Xavier ◽  
Daniel H. Huson
Keyword(s):  
Mathematical Model ◽  
Living Systems ◽  
Bacterial Metabolism ◽  
The Core ◽  
System Building ◽  
Formal Framework ◽  
The Origin Of Life ◽  
Key Features ◽  
Autocatalytic Networks ◽  
New Algorithms

Metabolism across all known living systems combines two key features. First, all of the molecules that are required are either available in the environment or can be built up from available resources via other reactions within the system. Second, the reactions proceed in a fast and synchronized fashion via catalysts that are also produced within the system. Building on early work by Stuart Kauffman, a precise mathematical model for describing such self-sustaining autocatalytic systems (RAF theory) has been developed to explore the origins and organization of living systems within a general formal framework. In this paper, we develop this theory further by establishing new relationships between classes of RAFs and related classes of networks, and developing new algorithms to investigate and visualize RAF structures in detail. We illustrate our results by showing how it reveals further details into the structure of archaeal and bacterial metabolism near the origin of life, and provide techniques to study and visualize the core aspects of primitive biochemistry.

scholarly journals Catalytic processing in ruthenium-based polyoxometalate coacervate protocells

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pierangelo Gobbo ◽  
Liangfei Tian ◽  
B. V. V. S Pavan Kumar ◽  
Samuel Turvey ◽  
Mattia Cattelan ◽  
...  
Keyword(s):  
Horseradish Peroxidase ◽  
Functional Activity ◽  
Soft Matter ◽  
Collective Behaviour ◽  
Reaction Networks ◽  
Systems Chemistry ◽  
Chemical Signalling ◽  
Catalytic Processing ◽  
New Type ◽  
Important Milestone

AbstractThe development of programmable microscale materials with cell-like functions, dynamics and collective behaviour is an important milestone in systems chemistry, soft matter bioengineering and synthetic protobiology. Here, polymer/nucleotide coacervate micro-droplets are reconfigured into membrane-bounded polyoxometalate coacervate vesicles (PCVs) in the presence of a bio-inspired Ru-based polyoxometalate catalyst to produce synzyme protocells (Ru4PCVs) with catalase-like activity. We exploit the synthetic protocells for the implementation of multi-compartmentalized cell-like models capable of collective synzyme-mediated buoyancy, parallel catalytic processing in individual horseradish peroxidase-containing Ru4PCVs, and chemical signalling in distributed or encapsulated multi-catalytic protocell communities. Our results highlight a new type of catalytic micro-compartment with multi-functional activity and provide a step towards the development of protocell reaction networks.

scholarly journals Universal motifs and the diversity of autocatalytic systems

2020 ◽  
Vol 117 (41) ◽  
pp. 25230-25236 ◽  
Author(s):  
Alex Blokhuis ◽  
David Lacoste ◽  
Philippe Nghe
Keyword(s):  
Kinetic Analysis ◽  
Chemical Evolution ◽  
Systematic Study ◽  
Reaction Networks ◽  
Unified Approach ◽  
Unified Framework ◽  
Basic Principles ◽  
The Origin Of Life ◽  
Catalytic Cycles

Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks. This allows for a classification of minimal autocatalytic motifs called cores. While all known autocatalytic systems indeed contain minimal motifs, the classification also reveals hitherto unidentified motifs. We further examine conditions for kinetic viability of such networks, which depends on the autocatalytic motifs they contain and is notably increased by internal catalytic cycles. Finally, we show how this framework extends the range of conceivable autocatalytic systems, by applying our stoichiometric and kinetic analysis to autocatalysis emerging from coupled compartments. The unified approach to autocatalysis presented in this work lays a foundation toward the building of a systems-level theory of chemical evolution.

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