Hi . Sorry, I didn’t make much progress. I didn’t want to be too destructive. I think we’ll do better when we can talk to one another. Tomorrow will also be pretty bad, because I have a visitor coming. Let’s see what we can do in my morning, not totally sure of my schedule. Red for comments by Michael, Uncomment the line in the file to make them disappear COOL SHORTCUTS: CTL-COMMA BRINGS THE PREVIEW TO THE PLACE YOU ARE. FOR EMACS KEYMAP, SEE END OF DOCUMENT. PROJECT OBJECTIVES I really think that something like this should be included, otherwise it is not clear how what we are doing pertains to their call. I don’t think I did a good job putting it on paper, though. I don’t know, biological systems posses lots of properties, I don’t know if this is the best, or if the readers will understand what we want. Why this one? Biological systems posses the striking ability to propagate information into the future. Information is stored as a spacial structure. Biological systems need to perform two tasks at two time scales: The tasks are - Resist forces of equilibration. (do not die) - Adapt to different forces of equilibration, that change due to changes in the environment (do not get killed by something unexpected) There are roughly two time scales: - Short – lifetime of an organism - Long – evolutionary time scale In the early life the distinction was probably blurred. Bio system perform these tasks at the two timescales by exploiting the environment for energy and materials for: - Maintenance/repair – related to homeostasis/metabolism - Adaptation, sensorimotor/control loop, etc. - Replication - Variability – mutation/selection forces These involve utilizing energy and matter from the environment, transporting it in physical space and removing waste energy and matter. We would like to investigate thermodynamic constraints governing the performance of these tasks. We are interested in the question of how efficiently biological systems, especially those in the early biosphere, exploit resources in their environment for the purpose of performing these tasks. I would like to include somehow the following explanation, because during the conference there was a group of people talking about early life. The Q’s they discussed are like how cell membranes were constructed, what kind of sugars could have been in the backbone of early RNA, what were the possible metabolic pathways, etc. It is a big body of knowledge about which we don’t know much. But you realize that what we will model will be extremely limited. Organisms, even or maybe especially primitive ones rely a lot on 2D structures, 3D structures, molecule shape, folding, separation of domains, diffusion. All these we will not be able to put in. We don’t simulate early life, we just look at the principles of selection in early life. We want to look at very simple living systems to analyze the very basic principles of their operation and emergence, which are obscured by extremely complicated machinery of modern organisms. Besides, the proxi measures that we will be using to assess survival abillities of organisms are probably more relevant in the pre- or early evolutionary stages. I want to postpone explaining our usage of chem network simulations, but then I don’t know how to write the next par. It would be difficult to asses the measure of success of either real, simulated or theoretical organism in performing survival tasks, thus we plan to using proxi measures, such as production of certain types of chemicals (ATP), reproduction, info processing, Homeostatsis/Maintenance... What else was there? Something about cooperation/ecosystems due to Jürgen? Using different proxi measures will lead to defining different efficiencies. We will address the following questions: Which of these efficiencies are most relevant for biological systems, particularly those in the early biosphere? How did these efficiencies evolve with time? Which can be viewed as “fundamental principles of life”? Shall we talk about constraints here (time, robustness,...)? Chemistry provides sufficiently complex dynamics where such questions could be investigated. PROJECT SUMMARY , V3 (BY MICHAEL AND DAVID WITH EXTRA PARAGRAPH) Bio systems posses the striking ability to propagate information into the future. Information is stored as a spacial structure. There are two tasks at two time scales: The tasks are - Resist forces of equilibration. - Adapt to different forces of equilibration, that change due to changes in the environment There are roughly two time scales: - Short – lifetime of an organizm - Long – evolutionary time scale In the early life the destinction was probably blured. Bio system perform this tasks by exploiting the environment for energy and materials for: - Maintenance/repair – related to homeostasis/metabolism - Adaptation, sensorimotor/control loop, etc. - Replication - Variability – mutation/selection forces We would like to investigate thermodinamic constraints governing the performance of these tasks. - We are interested in the question of how efficiently biological systems, especially those in the early biosphere, exploit resources in their environment. - We are also interested in how efficiently biological systems transform resources from their environment into waste products. - In particular, there are many kinds of thermodynamic resources used by biological systems. These include: 1. Environmental free energy (concentration or temperature gradients, chemical energy, electromagnetic energy,...) 2. Negentropy In their exploiting those resources biological systems create some irreversible entropy as a waste product, i.e., dissipate some work. (Note though that some of the heat that is produced may be used by the organism itself to warm itself up.) - In addition there are other resources that biological systems transform into waste products that are not thermodynamic. In particular, biological systems take in chemicals from their environment, and produce other chemicals that must be excreted. Which of these efficiencies are most relevant for biological systems, particularly those in the early biosphere? Which can be viewed as “fundamental principles of life”? How did these efficiencies evolve with time? Note as well that biological systems are information-processing systems, e.g., processing information from their environment for homeostasis, performing reproduction (amplification). These processes can also be analyzed in terms of their (in)efficiencies. In particular, they take in some information, and transform it into other information. How important are these efficiencies, and how do they relate to the others discussed above? To address this issue and test our theoretical work, we plan to use Peter’s artificial chemistry as an approximation of the chemical reaction networks in cells (mainly the metabolic network). The system should be augmented to deal with - Spatial structures/compartmentalization - Polymerization, RNA, ... - Ribozymes (?) - Populations, food webs This will require a higher-level simulation that runs on top of the chemical network. We will measure the efficiencies of the systems in performing various tasks: - ATP production as main bottleneck in free energy use - Replication/Amplification - Homeostatsis/Maintenance (not clear how to measure it) - Ecosystems — coordination of production and exploitation of chemicals among the various organisms - Closed loop control — responding to the environment in an appropriate manner. We will use and extend modern non-equilibrium statistical physics to analyze the thermodynamics of the system performing these tasks, e.g., the minimal amount of environmental free energy they require, and how much work they waste (dissipate) when exploiting that free energy. All these studies can be performed under additional constraints such as - time constraints - robustness (resistance to undesired environment perturbations) - ability to remove unnecessary byproducts - (un-)specific inputs (omnivore vs. “monovore”) - ability adapt to fluctuations in the environment (information processing) We will study the various types of efficiency by performing random mutations of a given chemical network, to determine how well it performs compared to alternative networks. This will allow us both to model evolution, and to quantify how well a given network performs, compared to its nearest neighbors in network space. By studying how the thermodynamic performance of cells relate to other kinds of efficiency we hope to get a better understanding of what it is that biological cells optimize and how it relates to evolution. PROJECT OBJECTIVE We want to further develop the artificial chemistry toolbox created by one of the partners and utilize it to study conceptual questions about the origin of life and fundamental properties of living systems at different scales, from individual chemical reactions to networks of interacting artificial cells or rudimentary organisms. This artificial chemistry can simulate covalent bonds forming molecules and thereby investigate metabolic processes. Importantly, it admits an energy function. On this basis, we shall investigate thermodynamic aspects of living systems and find out to what extent thermodynamic efficiency contributes to fitness and is realized in chemical agents that interact and compete with others for resources. This is particularly important for active or dynamic kinetic stability which involves turning free energy from the environment into information. Stability/persistence is maintenance of structure against the forces of equilibration. Active stability or dynamic kinetic stability involves turning free energy from the environment into information. The efficiency of this process, and the evolution of such an efficiency is important in the emergence of life-like structures. In particular, it is interesting to investigate, whether efficiency is a driving force in the evolution of stability, that is: in the selection for stability is efficiency being selected for. Another question: Is replication more energetically efficient then simple amplification? Stochastic thermodynamics as a thermodynamics of information seems to provide an appropriate language and tools. On the temporal and spacial scales available to us for observations, chemistry is the only domain of sufficiently complex dynamics. Therefore it seems sensible to apply and test the theory using chemical networks. DESCRIPTION OF PROJECT

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Hi . Sorry, I didn’t make much progress. I didn’t want to be too destructive. I think we’ll do better when we can talk to one another. Tomorrow will also be pretty bad, because I have a visitor coming. Let’s see what we can do in my morning, not totally sure of my schedule. Red for comments by Michael, Uncomment the line in the file to make them disappear Cool shortcuts: ctl-comma brings the preview to the place you are. For emacs keymap, see end of document. Project objectives I really think that something like this should be included, otherwise it is not clear how what we are doing pertains to their call. I don’t think I did a good job putting it on paper, though. I don’t know, biological systems posses lots of properties, I don’t know if this is the best, or if the readers will understand what we want. Why this one? Biological systems posses the striking ability to propagate information into the future. Information is stored as a spacial structure. Biological systems need to perform two tasks at two time scales: The tasks are

Resist forces of equilibration. (do not die)
Adapt to different forces of equilibration, that change due to changes in the environment (do not get killed by something unexpected)

There are roughly two time scales:

Short – lifetime of an organism
Long – evolutionary time scale

In the early life the distinction was probably blurred. Bio system perform these tasks at the two timescales by exploiting the environment for energy and materials for:

Maintenance/repair – related to homeostasis/metabolism
Adaptation, sensorimotor/control loop, etc.
Replication
Variability – mutation/selection forces

These involve utilizing energy and matter from the environment, transporting it in physical space and removing waste energy and matter. We would like to investigate thermodynamic constraints governing the performance of these tasks. We are interested in the question of how efficiently biological systems, especially those in the early biosphere, exploit resources in their environment for the purpose of performing these tasks. I would like to include somehow the following explanation, because during the conference there was a group of people talking about early life. The Q’s they discussed are like how cell membranes were constructed, what kind of sugars could have been in the backbone of early RNA, what were the possible metabolic pathways, etc. It is a big body of knowledge about which we don’t know much. But you realize that what we will model will be extremely limited. Organisms, even or maybe especially primitive ones rely a lot on 2D structures, 3D structures, molecule shape, folding, separation of domains, diffusion. All these we will not be able to put in. We don’t simulate early life, we just look at the principles of selection in early life. We want to look at very simple living systems to analyze the very basic principles of their operation and emergence, which are obscured by extremely complicated machinery of modern organisms. Besides, the proxi measures that we will be using to assess survival abillities of organisms are probably more relevant in the pre- or early evolutionary stages. I want to postpone explaining our usage of chem network simulations, but then I don’t know how to write the next par. It would be difficult to asses the measure of success of either real, simulated or theoretical organism in performing survival tasks, thus we plan to using proxi measures, such as production of certain types of chemicals (ATP), reproduction, info processing, Homeostatsis/Maintenance... What else was there? Something about cooperation/ecosystems due to Jürgen? Using different proxi measures will lead to defining different efficiencies. We will address the following questions: Which of these efficiencies are most relevant for biological systems, particularly those in the early biosphere? How did these efficiencies evolve with time? Which can be viewed as “fundamental principles of life”? Shall we talk about constraints here (time, robustness,...)? Chemistry provides sufficiently complex dynamics where such questions could be investigated. Project Summary , V3 (by Michael and David with extra paragraph) Bio systems posses the striking ability to propagate information into the future. Information is stored as a spacial structure. There are two tasks at two time scales: The tasks are

Resist forces of equilibration.
Adapt to different forces of equilibration, that change due to changes in the environment

There are roughly two time scales:

Short – lifetime of an organizm
Long – evolutionary time scale

In the early life the destinction was probably blured. Bio system perform this tasks by exploiting the environment for energy and materials for:

Maintenance/repair – related to homeostasis/metabolism
Adaptation, sensorimotor/control loop, etc.
Replication
Variability – mutation/selection forces

We would like to investigate thermodinamic constraints governing the performance of these tasks.

We are interested in the question of how efficiently biological systems, especially those in the early biosphere, exploit resources in their environment.
We are also interested in how efficiently biological systems transform resources from their environment into waste products.
In particular, there are many kinds of thermodynamic resources used by biological systems. These include:
1. Environmental free energy (concentration or temperature gradients, chemical energy, electromagnetic energy,...)
2. Negentropy
In their exploiting those resources biological systems create some irreversible entropy as a waste product, i.e., dissipate some work. (Note though that some of the heat that is produced may be used by the organism itself to warm itself up.)
In addition there are other resources that biological systems transform into waste products that are not thermodynamic. In particular, biological systems take in chemicals from their environment, and produce other chemicals that must be excreted.

Which of these efficiencies are most relevant for biological systems, particularly those in the early biosphere? Which can be viewed as “fundamental principles of life”? How did these efficiencies evolve with time? Note as well that biological systems are information-processing systems, e.g., processing information from their environment for homeostasis, performing reproduction (amplification). These processes can also be analyzed in terms of their (in)efficiencies. In particular, they take in some information, and transform it into other information. How important are these efficiencies, and how do they relate to the others discussed above? To address this issue and test our theoretical work, we plan to use Peter’s artificial chemistry as an approximation of the chemical reaction networks in cells (mainly the metabolic network). The system should be augmented to deal with

Spatial structures/compartmentalization
Polymerization, RNA, ...
Ribozymes (?)
Populations, food webs

This will require a higher-level simulation that runs on top of the chemical network. We will measure the efficiencies of the systems in performing various tasks:

ATP production as main bottleneck in free energy use
Replication/Amplification
Homeostatsis/Maintenance (not clear how to measure it)
Ecosystems — coordination of production and exploitation of chemicals among the various organisms
Closed loop control — responding to the environment in an appropriate manner.

We will use and extend modern non-equilibrium statistical physics to analyze the thermodynamics of the system performing these tasks, e.g., the minimal amount of environmental free energy they require, and how much work they waste (dissipate) when exploiting that free energy. All these studies can be performed under additional constraints such as

time constraints
robustness (resistance to undesired environment perturbations)
ability to remove unnecessary byproducts
(un-)specific inputs (omnivore vs. “monovore”)
ability adapt to fluctuations in the environment (information processing)

We will study the various types of efficiency by performing random mutations of a given chemical network, to determine how well it performs compared to alternative networks. This will allow us both to model evolution, and to quantify how well a given network performs, compared to its nearest neighbors in network space. By studying how the thermodynamic performance of cells relate to other kinds of efficiency we hope to get a better understanding of what it is that biological cells optimize and how it relates to evolution. Project objective We want to further develop the artificial chemistry toolbox created by one of the partners and utilize it to study conceptual questions about the origin of life and fundamental properties of living systems at different scales, from individual chemical reactions to networks of interacting artificial cells or rudimentary organisms. This artificial chemistry can simulate covalent bonds forming molecules and thereby investigate metabolic processes. Importantly, it admits an energy function. On this basis, we shall investigate thermodynamic aspects of living systems and find out to what extent thermodynamic efficiency contributes to fitness and is realized in chemical agents that interact and compete with others for resources. This is particularly important for active or dynamic kinetic stability which involves turning free energy from the environment into information. Stability/persistence is maintenance of structure against the forces of equilibration. Active stability or dynamic kinetic stability \cite{Pross2009} involves turning free energy from the environment into information. The efficiency of this process, and the evolution of such an efficiency is important in the emergence of life-like structures. In particular, it is interesting to investigate, whether efficiency is a driving force in the evolution of stability, that is: in the selection for stability is efficiency being selected for. Another question: Is replication more energetically efficient then simple amplification? Stochastic thermodynamics \cite{Seifert2012} as a thermodynamics of information \cite{Parrondo2015} seems to provide an appropriate language and tools. On the temporal and spacial scales available to us for observations, chemistry is the only domain of sufficiently complex dynamics. Therefore it seems sensible to apply and test the theory using chemical networks. Description of project

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