Life/Citable Version

Biologists use the term life to refer to the processes comprising the activity of living, to the entities that embody those processes, and to the interrelations and interactions among them, that together, form complex adaptive self-reproducing systems. The question “what is life?” then turns on just what, precisely, characterizes those 'processes of living'. In answering that, biologists hope to find answers to many other questions in biology, including perhaps, some not yet even asked (see Biology and Systems biology). The meaning of the terms 'life' and 'living' in a number of different contexts unfolds in the course of the article.

A few books representing some of the many topics in the study of living things. The left-hand book and the small small book on top of the stack What is Life? by Erwin Schrodinger (1944-2000) Cambridge University Press. ISBN 0-521-42708-8 http://dieoff.org/page150.htm Link to Chapter 6 “Order, Disorder and Entropy”. Schrodinger stresses open thermodynamic systems as the key to living processes, and predicts a hereditary molecule like a coded periodic crystal. The black book near the top right stack is Schneider ED, Sagan D (2005) Into the Cool: Energy Flow, Thermodynamics, and Life. Chicago: The University of Chicago Press. ISBN 0-226-73937-6 http://www.intothecool.com/ Links to chapter excerpts and reviews. See article citations.

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Linguistics and the Definition of Life

Ernst Mayr, a 20th century giant among evolutionary biologists, in his last decade as a centenarian, wrote a book called This is Biology: The Science of the Living World. In the opening chapter, What Is the Meaning of “Life” , he declares that understanding 'life' is one of the major objectives of biology. However, he suggests that we should fuss less about defining 'life', and concentrate more on defining the process of 'living':

"The problem here is that 'life' suggests some 'thing' — a substance or force — and for centuries philosophers and biologists have tried to identify this 'vital force', to no avail. In reality, the noun 'life' is merely a reification of the process of living. It does not exist as an independent entity. One can deal with the process of living scientifically, something one cannot do with the abstraction 'life'. One can describe, and even try to define, what living is and what a living organism is, and one can try to make a demarcation between living and nonliving. Indeed, one can even try to explain how living as a process can be the product of molecules that themselves are not living."

Evolutionary biologist Ernst Mayr (1904-2005) in 1994. See encomium: Meyer A (2005) On the importance of being Ernst Mayr. PLoS Biol 3(5): e152 An Open Access Journal

Scientist Eric Schneider and science writer Dorian Sagan echo Mayr:

...the word is a grammatical misnomer: life is a noun, but the phenomenon to which it refers is a process. And it is vitalistic: when we say life, we think we know what we are talking about when often we have simply applied a label that allows us to categorize, rather than examine closely, the phenomenon about which we are speaking.

Why this concern about the word? Some words have distinct meanings not definable in terms of other words, and those essential words semioticians call ‘semantic primes’. Ultimately, all definitions converge on about 70 so-called 'semantic primes', universal among languages. Children learn the meaning of prime words by how the society in which they live use them in every day language. Every other word can be defined using some combination of semantic primes. The verb ‘live’ is a semantic prime, the noun ‘life’ is not.

Using semantic primes, 'Life' is defined as 'that which lives', where lives is understood by speakers and listeners from their experience with the language-speakers in their environment. The word "death" also comes from the semantic prime of 'that which lives'. Things which live 'die' and speakers generate the word 'death' to refer to 'that which died'.

Semantically, the question, then, is not 'what is life?', but 'what characterizes things that live?' Biologists act on the latter question, even as they ask it in terms of the former. The biologist, logician and historian J.H. Woodger suggested that the word 'life' can be eliminated from the scientific vocabulary, because it is "an indefinable abstraction and we can get along perfectly well with 'living organism', which is an entity that can be speculatively demonstrated.” Carol Cleland, philosopher and member of NASA’s Astrobiology Institute, adds that scientists are not really interested in what the word 'life' happens to mean in our language. "What we really need to focus on is coming up with an adequately general theory of living systems, as opposed to a definition of 'life'." Perhaps this resonates with the remark of biologist Antonio Lazcano: "Life is like music; you can describe it but not define it".

Differing Perspectives on What Constitutes a Living System

What characterizes living things? As well as sharing a common carbon- and water-based chemistry, entities that biologists generally acknowledge as living — bacteria, trees, fish, chimpanzees etc. — all share a common basic building block, the cell. The cell is the smallest system thought capable of independent living. Many organisms live as single cells, some as cooperative colonies of single cells, others as complex multicellular systems, with many different cell types specialized for different functions. Nature has produced an enormous variety of cell types in three vast ‘domains’ of living systems: Archaea, Bacteria, and Eukarya, yet all three domains share the cellular feature of a boundary separating them from their environment by a surrounding membrane (the plasma membrane). Moreover, the cells in all three domains are ‘manufactured’ by pre-existing cells. All extract chemical energy from simple sugar molecules’ chemical bonds, and convert it by chemical reactions into other energy forms that they use for many different purposes, ultimately enabling them to respond to their evolutionary imperatives of self-perpetuation and self-reproduction. They all possess through inheritance a molecular (i.e., DNA) embodied code, using essentially the same DNA ‘genetic code’ that guides the production of the many different proteins that give structure and function to the cells. All replicate their genetic code faithfully or nearly so, and thereby have the capacity to replicate themselves.

From those basic shared characteristics, biologists view the commonalities and uniquenesses of cell types, and living systems in general, from differing perspectives, which together contribute to understanding what constitutes 'living'.

Systems

(See main article, Systems biology)

The 'systems perspective' recalls Aristotle's four components of explanation for a complex natural living system:

• the list of organic and inorganic parts (e.g., carbon-containing molecules and inorganic ions; cells; organelles, organs; organisms) — Aristotle’s 'material' explanation;
• how the parts relate to each other to form substructures (e.g., networks), how they interact with each other (e.g., network dynamics), and how the substructures interact in a coordinated dynamic, and hierarchical manner (e.g., inter-network dynamics, multicellular patterns of static and dynamic form) — Aristotle’s 'formal' (form-like) explanation;
• how the parts and substructures became so organized (e.g., energy influx; gene expression; self-organization; competition) — Aristotle’s 'efficient' (effect-producing) explanation; and,
• how the living system as-a-whole functions and behaves and the properties that characterize it (e.g., reproduction; locomotion; cognition) — Aristotle’s 'final' explanation.

The analysis of those components together as a whole forms part of a new academic discipline, 'Systems Biology'. Systems biologists study, among other things, the phenomenon of 'emergence', whereby properties, functions and behaviors of living systems arise although not shared by any of its components, and not predictable from a reductionist characterization of the components in isolation from the system embedding them. All cell and cellular systems exhibit such ‘emergent’ properties, functions and behaviors.

The inability to predict a system's properties from the properties of its components needs some explanation, as such predictions have characterized the reductionist paradigm. There are two related reasons for the constraint on prediction:

• the intrinsic properties, functions and behaviors of a system’s components do not determine those of the whole system. Rather, their 'organizational dynamics' does, where that includes the interrelations of the components and their dynamic, coordinated, hierarchical interactions;
• the system-as-a-whole operates in its own context (its external environment) which affects the properties, functions and behaviors of the system-as-a-whole. That contextual impact in turn affects the organization of the system's components — a 'downward causation'.

Philosopher of science D.M. Walsh puts it this way: "The constituent parts and processes of a living thing are related to the organism as a whole by a kind of 'reciprocal causation'." In other words, the organization of the system's components determine its behavior, but that organization does not arise solely because of the intrinsic properties and behaviors of the components. The system's behavior, as it interacts with its environment, influences the organization of its components, and novel behaviors of the system 'emerge' that are not predictable from the intrinsic properties, functions and behaviors of the components alone. For example, the behavior of a kidney cell depends not only on the intrinsic characteristics of its components, but also on the organ (kidney) which constitutes its environment, because that environment influences the cell’s structure and behavior (e.g., by physical confinement, cell-to-cell signaling, etc.), which in turn influence the organization of the components.

Systems biologists refer to those as 'bottom-up' and 'top-down' effects. The emergent properties, functions and behaviors that result from a combination of bottom-up and top-down effects constitute general characteristics of living systems.

Thermodynamic

Biologists often view living things from the perspective of thermodynamics — the science of interactions among energy (capacity to do work), heat (thermal energy), work (movement through force), entropy (degree of disorder) and information (degree of order). The interactions define what the system can and cannot do in the process of interconverting energy and work. For example, by the First Law of Thermodynamics, when a process converts one form of energy to another, it results in no net loss of energy, and no net gain. Scientists discovered the laws of thermodynamics through experiment, debate, mathematical formulation and refinement. Albert Einstein believed that they stood as an edifice of physical theory that could never topple. Most pertinent for considering living systems, the Second Law of Thermodynamics has several expressions:

Energy (electromagnetic: light and heat) emitted by our sun provides the great bulk of the energy gradient that living systems on earth exploit, either directly or indirectly, to maintain a state far from the equilibrium state of randomness. The photograph shows a handle-shaped cloud of plasma (hot ions) erupting from the Sun. Courtesy NASA/JPL-Caltech. http://photojournal.jpl.nasa.gov/target/Sun?start=10

• Heat flows spontaneously — i.e., without external help — from a region of higher temperature to one of lower temperature, and never flows spontaneously in the reverse direction. That also holds for other forms of energy (e.g. electromagnetic, chemical, etc.) — concentrations of energy disperse to lower energy levels, flowing “into the cool”, so to speak.
• When heat as input to a system causes it to perform work (e.g., in a steam engine), some heat always dissipates as ‘exhaust’, unused and unusable by the system for further work. That also holds for other forms of energy doing work; some of the energy always turns into ‘exhaust’, typically heat. Energy conversion to work in a system can never proceed at 100% efficiency — an empirical fact.
• The degree of order or organization of a system and its surroundings cannot spontaneously increase; it either remains the same or decreases. Scientists have learned how to put a number on the degree of disorder of a system, and they refer to it as entropy. Water vapor, with its molecules distributed nearly randomly, has a higher entropy than liquid water, with its molecules distributed less randomly, and has a much higher entropy than ice, with its molecules distributed in a more organized crystal array. Left to itself, ice tends to spontaneously melt, and liquid water to evaporate. Order tends to disorder, with the Universe as a whole purportedly tending to exhaust itself into an ‘equilibrium’ state of randomness.

Those three expressions of the Second Law restate each other as tenets of classical thermodynamics, reflecting the empirical fact that high energy and order spontaneously flow downhill — down a ‘gradient’ — toward eliminating the gradient, as if nature abhors gradients of energy and order, intent on obeying the Second Law. Upon gradient elimination, all energy and order has dissipated, degraded, all change ceases, and an equilibrium state ensues.

Given the Second Law, how do living entities manage to come into existence, to develop from an ‘embryonic’ state to one of greater order and lesser entropy, and to perpetuate their order and increase in order? How do they thwart the Second Law?

They don’t. They only appear to do so. Actually, they exploit the Universe’s gradients of energy and order — which run 'downhill' — by their location along those gradients, between the energy input and its dissipation as exhaust. Like a steam engine, they ‘import’ energy and order, convert it, albeit it incompletely, to the work of internal organization, and so reduce their internal entropy, or, equivalently, increase their state or organization. But all along, they emit enough "exhaust" to increase the disorder and entropy of their surroundings, so that the total entropy of the living system and its surroundings increase, in keeping with the Second Law.

Biological cells qualify as non-equilibrium thermodynamic systems because they consume work-enabling energy to live (i.e., to remain in a near steady-state), and because they export unusable (degraded) energy to dissipate the energy gradient they find themselves in &mdash in keeping with the Second Law. As non-equilibrium thermodynamic systems, living things can store energy and perform work both on themselves and their environment. Only after a living thing dies do all parts relate to each other according to strictly spontaneous physical and chemical processes. When alive, a living system always performs its organized functional activities far from the 'equilibrium' state of activity that obtains when no energy (including mass-energy) can be taken in from outside the system. The available outside energy supplies the driving force that keeps the system functioning far-from-equilibrium in a near steady-state. Non-equilibrium thermodynamic systems, including living things, can exhibit unexpectedly complex behaviors when maintained far-from-equilibrium. A remarkable behavior that can result from this disequilibrum is self-organization.

We can, then, view a living system as a state of organizational activity (non-randomness) maintained by importing, storing and transforming energy and matter into the work and structures needed to sustain its organizational activity. They can only do so by producing waste and exporting it, thereby lowering the organizational state of the environment. The living system maintains its organization at the expense of the external environment, leaving the environment more disorganized than the gain in organization of the living system — in keeping with the second law of thermodynamics that the total disorder, or entropy, system plus environment, always increases.

From a thermodynamic perspective, then the following statement could serve as a fundamental characterization of a living system:

• The ability to remain for a time as an organized, functioning system, in which factors that tend to disturb the system’s organization are opposed by built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste (disorder) — operating from an organizationally enabling state far from an ever-approaching equilibrium (the state that we call 'death').

That needs elaboration as we consider other important perspectives on what constitutes a living entity.

Evolutionary

The thermodynamic perspective on what constitutes a living entity might also apply to some non-living entities such as tornadoes or the flames of candles. However, tornadoes and candle flames cannot 'reproduce' themselves, as cells and organisms can. One might then characterize living systems as also having: the capability in principle of reproducing themselves before equilibrium ensues. When a living system reproduces itself, its progeny inherit its properties. However, random events (including 'mutations') can introduce variations in the system's properties. Some variations offer some progeny, or the progeny of some conspecific living systems, less opportunity to reproduce than others, and other progeny better opportunity, sometimes better even than their progenitors, in the unchanged or changed environment. Accordingly, new groups with different properties arise, and they may supplant older groups because of their superior reproductive fitness. Biologists call that process 'evolution by means of natural selection', and regard it as the most important way, though not the only one, whereby living systems evolve over geological time..

Therefore, an important characteristic of living systems is descent with modification: the ability to produce offspring that inherit some of its features, but with some variation due to chance. Evolution by means of natural selection will occur if heritable variations in the offspring result in differential reproductive fitness. The variations occur due to chance variations in the inherited genetic recipe (genotype) for constructing the offspring's organismic traits (phenotype). In all biological systems, DNA or the related molecule, RNA, primarily provides the genetic recipe.

Viruses have few of the characteristics of living systems described above, but they do have a genotype and phenotype, making them subject to natural selection and evolution. Accordingly, descent with modification is not uniquely a characteristic of living systems. Beyond the scope of this article, we find descent with modification in memes and the artificial life of computer software, such as self-modifying computer viruses and programs created through genetic programming. Descent with modification has also been proposed to account for the evolution of the universe.

Enlarging the description of livings things beyond the thermodynamic perspective, we can say that a living systems has:

• The ability to remain for a time as an organized, functioning system, in which factors that tend to disturb the system’s disorganization meet offsetting built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste (disorder) — operating from an organizationally enabling state far from an ever-approaching equilibrium (the state that we call 'death'), and capable in principle of reproducing itself, and of playing a role in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Exobiological

Exobiologists (also known as "astrobiologists") concern themselves with issues relating to the possible existence of extraterrestrial living systems. Dirk Schulze-Makuch and Louis Irwin attempted to distill the essential characteristics of a living system. They stress these characteristics, which resonate with the systems, thermodynamic and evolutionary perspectives discussed above:

• a microenvironment with a boundary between it and its external environment,
• the ability of that microenvironment to transform energy and matter from the environment to maintain a low entropy state (i.e., a highly ordered or 'organizational' state),

• therefore, the ability of that microenvironment to remain in thermodynamic disequilibrium with its environment,

• the ability of that microenvironment to encode and transmit information.

Self-Organization

Living systems organize themselves spontaneously. In cells, self-organization emerges in part from the chemical properties of the proteins encoded in genes. Those proteins make their appearance through a genetic transcription-translation machinery, which represents a self-organized molecular machine emerging in part from the chemical properties of proteins and other molecules. Molecules interact through the formation and breaking of strong covalent bonds, and also through weaker, quasi-stable non-covalent electromagnetic interactions, like hydrogen bonding and van der Waals forces and many others. Those weaker ‘supramolecular’ interactions give physical properties to molecular aggregates, and they underpin many intracellular and intercellular biological processes.

One way to understand self-organization is to view the genetic information (genome) metaphorically as a computer, in which the genome functions as a ‘program’ that constructs critical components of the cell that arrange themselves in a way that accords with their chemical properties. That arrangement, with the tinkering comprising local trial-and-error and evolution’s handiwork, can then carry out ('compute') integrative functions not explicitly encoded in the genome. Cells self-organize by a ‘computational process’.

As Oxford professor Denis Noble reminds us, the Nobel Prize-winning molecular biologist Sidney Brenner expressed the metaphor this way:

• ...biological systems can be viewed as special computing devices. This view emerges from considerations of how information is stored in and retrieved from the genes. Genes can only specify the properties of the proteins they code for, and any integrative properties of the system must be 'computed' by their interactions. This provides a framework for analysis by simulation and sets practical bounds on what can be achieved by reductionist models.”

The patterns of structure and behavior in self-organized systems need no behind-the-scene master, and no prepared recipes that explicitly specify the organizational structure and dynamics of the system. Instead, they emerge from the interactions among the components, dictated by their physical properties, dynamically modified by the emerging organization itself modified by the environment in which it is embedded. The single-celled zygote self-organizes into a multicellular living system as the genetically encoded proteins interact, responding to changing influences from the changing environment generated by growing multicellularity — self-organizing into a network of many cell-types working cooperatively. Self-organized systems ultimately are products of a 'blind watchmaker': natural selection favors self-organized networks that contribute to the reproductive fitness of the system, as they coordinate with the other self-organized networks in the system.

Self-organization tends to breed greater degrees of self-organization — and thus more complexity. Genes express not only proteins that organize themselves into a functional unit, but also proteins that organize themselves to regulate that functional unit, as in transcription regulatory circuits. Protein networks interact in a self-organizing way to produce networks of networks with complex levels of coordination. Cells communicate with other cells, either in free-living cellular communities or in multicellular organisms &dmash communicative activities that self-organize in virtue of the properties, functions and behaviors of the cells, selected for fitness by evolutionary mechanisms, and responsive to downward regulation by environmental influences on the whole system.

Further elaborating the descriptions of living systems beyond the thermodynamic and evolutionary perspectives, we can say that a living system has:

• The ability to remain for a time as a self-organized, functioning system, in which factors tending to disorganize the system meet offsetting, built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste, always operating from an organizationally enabling far-from-equilibrium state, and capable in principle of reproducing itself, and of playing a role in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Autonomous Agents

Stuart Kauffman uses the concept of 'autonomous agents' to explain living systems. He gives the hypothetical example of an enzyme that catalyzes the binding of two smaller sub-component molecules into a copy of itself — self-replication by 'auto-catalysis'. It requires energy to produce the enzyme, and this comes from a neighboring molecule, by breaking an energy-rich bond between the energy-rich molecule's subunits. Thus the neighbor molecule serves as a 'motor' to produce excess enzyme. The self-replication stops after using all duplicates of the motor, so to sustain self-replication, external energy — perhaps from light impinging on the system — must drive the repair of the broken chemical bond, re-establishing an ample supply of that energy-supplying molecule, thereby re-energizing the motor. A new cycle of 'auto-catalytic self-replication' can then begin, given an ample influx of both external energyenery and 'food'(sub-components of the 'auto-catalytic' enzyme). As an essential feature, interactions among the components of a system have effects (technically 'allosteric' effects) that help 'organize' and 'coordinate' its processes, allowing the autonomous self-replication to proceed.

Kauffman conceives, then, of a self-replicating autocatalytic molecule in a network of molecules that has cycles of self-replication driven by external energy and materials. The network has a self-replication process as a subsystem, and a ‘motor’, namely, the breakup of an energy-rich molecule, supplying energy that 'drives' the auto-catalysis self-replication, and its re-energizing repair by transduction of the outside energy source. Kauffman calls such a network a 'molecular autonomous agent' because, given a source of external energy (e.g. photons) and ample materials (the molecules needed to assemble the autocatalytic enzyme), the network perpetuates its existence autonomously, i.e., not controlled by outside forces even though dependent on outside energy and materials. The 'agent' is the system doing work autonomously; in this case, the work of auto-catalytic self-replication. That's what 'agents' do — they do work.

In this example, the agent acts in its own behalf — continuing its existence by ‘eating’ outside materials and energy. Work gets done because the system remains far-from-equilibrium, owing towith an influx of energy and materials. Energy flows through the system, doing work, and dissipating the energy gradient, but temporarily constraining the rate of dissipation by storing energy in its internal organization. The system can only do work while those far-from-equilibrium conditions persist. At equilibrium, no work gets done because no energy flows through the system. Thus the agent continues 'to live' (survive and self-replicate) only while that far-from-equilibrium state exists, and it can be starved to 'death' by removing the matter and energy flowing through the system. Kauffman argues, from his example, that cells, and indeed all living systems, qualify as autonomous agents, constructed on a foundation of molecular autonomous agents.

Autonomous agents also interest scientists in the fields of artificial intelligence and artificial life. One careful description of autonomous agents from some members of that group adds further insight to Kauffman's view of living systems:

An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to effect what it senses in the future. It has the properties of reactivity (timely response to environmental changes; autonomy (controls its own actions); goal-orientation (pursues its own agenda); continuous processing. Some autonomous agents may also have the properties of communicability (with other agents); adaptability (based on previous experience); unscripted flexibility.

For Kauffman, the property of pursuing its own agenda includes acting as a naturally selected system contributing to its own survival and self-reproduction: "...an autonomous agent is something that can both reproduce itself and do at least one thermodynamic work cycle. It turns out that this is true of all free-living cells, excepting weird special cases. They all do work cycles, just like the bacterium spinning its flagellum as it swims up the glucose gradient. The cells in your body are busy doing work cycles all the time." Only one escape from work &mdash death.

Further elaborating the descriptions of living systems beyond from the thermodynamic, evolutionary and self-organizational perspectives, we can say that a living system has:

• The ability to remain for a time as a self-organized system, functioning autonomously to work in its own behalf for self-maintenance and reproduction, where factors tending to disorganize the system meet offsetting, built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste, always exploiting its situation far from equilibrium, and capable of playing a role in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Networks

The modular organization of a cellular network. Yeast Transcriptional Regulatory Modules. Nodes represent modules, and boxes around the modules represent module groups. Directed edges represent regulatory relationship. The functional categories of the modules are color-coded. (Reproduced from Bar-Joseph Z et al. (2003) Computational discovery of gene modules and regulatory networks. Nat Biotechnol 21:1337–42.) From: Modularity and Dynamics of Cellular Networks Qi Y, Ge H PLoS Computational Biology Vol. 2, No. 12, e174 doi:10.1371/journal.pcbi.0020174

The science of networks provides another, highly useful perspective on the nature of living things. Networks ‘re-present’ a functioning system as a collection of ‘nodes’ and ‘interactions’ among the nodes (also referred to as ‘edges’ or ‘arrows’ or ‘links’). For example, in a spoken sentence, words and phrases make up the nodes, and the interconnections of syntax (subject-to-predicate, preposition-to-object of preposition, etc.) make up the links. Intracellular molecular networks represent specific functions in the cell; molecules make up the nodes, and their interactions with other nodes make up the edges or arrows. Some networks accept inputs of one kind and return outputs of a different kind.

One 'finds' networks everywhere in biology, from intracellular molecular networks, to intraspecies networks, to ecosystem networks. Humans deliberately construct social networks, of individuals working (more or less) to a common purpose, such as the U.S. Congress; of electronic parts to produce, for example, mobile phones; of sentences and paragraphs to express messages, including this very article. Researchers view the World Wide Web as a network, and study its characteristics and dynamics. Referring to cells, Alon says: "The cell can be viewed as an overlay of at least three types of networks, which describes protein-protein, protein-DNA, and protein-metabolite interactions."

Alon notes that cellular networks resemble many types of human engineered networks, in that they show what network analysts call 'modularity', 'robustness', and 'motifs'.

• Modules comprise subnetworks that perform a specific function and that connect with other modules often only at one input node and one output node. Modularity facilitates cellular adaptation to a changing environment, inasmuch as, to produce an adaptation, evolution need tinker with just a single or a few modules rather than with the whole system. Evolution can exapt existing modules for novel functions that contribute to survival.
• Robustness offers continued functionality of a network in the face of typical deviations in the state of the components due to environmental perturbations. Robustness restricts the range of network types researchers have to consider because only certain types enable robustness.
• Network motifs offer economy of design, as the same circuit design can have widespread applicability in cellular regulation, as in the case of autoregulatory circuits and feedforward loops. Networks, like those in cells and those in neural networks in the brain, employ motifs as basic building blocks, like multicellular organisms employ cells as basic building blocks. In several well-studied biological networks, the abundance of network motifs — small subnetworks — correlates with the degree of robustness to small perturbations acting on the network.

The view of the cell as an overlay of mathematically-definable dynamic networks, especially when analyzed in detail in relation to known cellular activities, can reveal how a living system can exist as an improbable, intricate self-orchestrated dance of molecules. It also suggests how the concept of self-organized networks can extend to all higher levels of living systems.

Further elaborating the descriptions of living systems beyond the thermodynamic, evolutionary, self-organizational and autonomous agent perspectives, we can say that a living system has:

• The ability to remain for a time as a self-organized system of networks of modular robust networks, functioning autonomously to work in its own behalf for self-maintenance and self-reproduction, where factors tending to disorganize the system meet offsetting, built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste, always exploiting its organizationally enabling far from equilibrium state, and capable of playing a role in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Information Processing

Bioscientists study biological systems for many different reasons, hence biology has many subdisciplines (see Biology and List of biology topics). But in every subdiscipline, bioscientists study biological systems for the proximate reason of gaining information about the system to satisfy their however-motivated curiosity, and to apply that information to human agendas (e.g., to prevent disease, to conserve the environment). Those realities attest that biological systems harbor information, at least as people usually understand 'information'. To appreciate how viewing biological systems from an 'information' perspective can contribute to understanding living systems, the following questions need answers:

• what do we mean by information?
• how does information apply to biological systems?
• how does information emerge in biological systems?
• how do the answers to those questions add to explaining living systems?

The word 'information' comes from the verb 'to inform', originally meaning to put form in something, to give it form. The seal in-forms the wax, and the wax now contains in-formation. A random collection of particles or other entities has no form, nothing has given it form, and it contains no in-formation. The more randomness in the structure of the collection, the fewer improbable arrangements or interactions it has among its parts, inasmuch as the second law of thermodynamics teaches us that the universe, and any other 'isolated' system, tends to randomness as its most probable state. A drinking glass falls onto the sidewalk, it falls apart into a random collection of bits of glass. Notice it doesn’t regroup into the drinking glass — you could watch it for a lifetime. Our experience shows us that the drinking glass is more improbable than the glass in smithereens.

Schematic depicting a portion of the information content and interrelations in a cell. An Overview of Biological Network Analyses Based on “Omic” Data (DOI: 10.1371/journal.pcbi.0020174.g001). “Recent high-throughput technologies have produced massive amounts of gene expression, macromolecular interaction, or other type of “omic” data. Using a computational modeling approach, the architecture of cellular networks can be learned from these “omic” data, and topological or functional units (motifs and modules) can be identified from these networks. Comparisons of cellular networks across different species may reveal how network structures evolve. In particular, the evolutionary conservation of motifs and modules can be an indication of their biological importance. A dynamic view of cellular networks describes active network components and interactions under various conditions and time points. Network motifs and modules can also be time-dependent or condition-specific.” From: Modularity and Dynamics of Cellular Networks Qi Y, Ge H PLoS Computational Biology Vol. 2, No. 12, e174 doi:10.1371/journal.pcbi.0020174

The more improbable the arrangements, the more in-formation a collection of parts has received and therefore contains. An observer will conclude that something has happened to 'form' the parts into a more improbable state — an in-formation has occurred, and that the collection of parts contains that in-formation. By that reasoning, biological systems contain in-formation: something has happened to 'form' the parts into an improbable state.

An ordered desktop soon becomes disordered. The ordered desktop has message value, or 'information', in that something must have happened to give it form. The more unlikely the arrangement of the parts, the more information it contains. Biological systems thus have information content, in that they are unlikely (non-random) arrangement of parts, non-random collections of interactions of parts, non-random collections of functional activities.

The thermodynamic and autonomous agent perspectives on living systems discussed the notion of cells as intermediates in a gradient of higher to lower forms of usable energy, including mass-energy. The flow of energy and materials through the living system feeds it, enabling it to do work on itself. That work enables it to give itself form, or order, and to give itself functionalities, raising its information content. The cell can do work on its environment also.

Thus a living system emerges as an information processing system. It can:

• receive information from energy and materials in its environment, fueling and supplying the machinery that builds and sustains information-rich organization;
• generate new information inside itself, as in embryonic development;
• transmit information within and outside itself, as in transcription regulation and exporting pheromones.

From its parent, it inherits (genetic) information that establishes its developmental potential and scripts its realization, including controlling what parts of the inherited information-base transmit their piece of information within or outside, depending on cell-type and environmental conditions — and including information that enables it to reproduce itself.

Combined with other perspectives, viewing living systems as information banks, as inheritors of information, as receivers, generators and transmitters of information, and as reproducers of inherited information, enables one to see living systems and their interactions with other livings systems as a vast, complex, naturally-selected, self-sustaining, evolving communication network. Recently (on the timescale of evolving living systems) that evolving communication network emerged as the human brain, capable of communicating with itself and other humans using networks of 'symbols'. That led to the emergence of cultural evolution, a whole new domain of self-reproducing entities ('culturgens', 'memes') and descent with modification. That led to the emergence of another vast communication network: books, wikis, and other technologies of information generation and exchange.

Further elaborating the descriptions of living systems beyond the thermodynamic, evolutionary, self-organizational, autonomous agent, and network perspectives, we can say that a living system has:

• The informational content and information-processing ability to remain for a time as a self-organized system of networks of modular robust networks, functioning autonomously to work in its own behalf for self-maintenance and reproduction, where factors tending to disorganize the system meet offsetting, built-in self-correcting mechanisms fueled by external energy and matter, and facilitated by production and exportation of waste, always exploiting its organizationally enabling far from equilibrium state, and capable of playing a role in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

A Synthesis of Perspectives

In regard to the question of what constitutes a living system, what do the perspectives discussed above, together, offer in answer? The last paragraph of the preceding section would seem to encapsulate the answer. In breakdown, the several perspectives seem to involve a few basic concepts:

• living systems can import work-enabling energy, matter, and information directly or indirectly from the environment that embeds them;

• they also can export to their environment unusable and information-poor energy and matter;

• those two abilities — how the get accomplished &mdash enable them to delay (for an individual’s lifetime and for the living world’s evolutionary lifetime) the ultimate dictate of the second law of thermodynamics, that energized organized systems ultimately degrade to the disorganized state of the equilibrium of randomness;

• the flow of energy and energy-rich matter through them enables them to self-organize and self-maintain their fully-functioning living system, given the basic information that generates their structural components;

• that information comes as part of the starting materials in the basic building blocks of all living systems, namely cells;

• cells inherit information from ‘parent’ cells — unique to living systems — raising two new questions: how did cells arise in the first place? and how did they acquire information banks?;

• that information, in the form of nucleic acid macromolecules, encode many different types of macromolecules that interact by strong and weak molecular encounters among themselves and with their encoding macromolecules, thereby self-assembling an organization that sustains its ability to import energy, matter, and information directly or indirectly from the local environment;

• that self-organizing activity occurs without a 'master controller' (other than physicochemical laws), needing only a type of organization that supports the system far-from-equilibrium, that can yield improbable self-organized structures and activities;

• the physicochemical laws include:

• laws that allow local energy importation and the accumulation of order, organization and information by entities caught in their downhill flow so long as they export a surfeit of disorder to their environment;
• laws that enable molecular interactions;
• laws that enable selection and adaptation;

• those laws and inherited information enable operation of a self-organizing system that can work autonomously in its own behalf for survival and reproduction;

• although autonomous, living things cannot escape from changing external conditions that threaten their perpetuation; they must exhibit robustness in their organized network dynamics and must have built-in adaptable mechanisms that maintain their stability;

• they must also produce enough reproductive variability-producing infidelity to allow natural selection for reproductive fitness, which operates to guide the ‘living’ world toward perpetuation of the ‘living’ world both in the near future and in the distant future, a continuation of a 3.5 billion year history of Earth’s ‘living’ world;

• by being subject to natural selection and other dimensions of evolution, living systems generate increasing varieties of living systems, occupy an extreme spectrum of environments, create their own environments (‘niche construction’), including the Earth’s biosphere, and permit emergence of degrees of complexity capable of sufficient information processing to allow them to ‘experience’ themselves as living systems experiencing themselves.

With those mutually resonating principles, we can unpack definitions of ‘life’ typically stated in terms of entities capable of metabolism, reproduction and evolution.

References

Published Collections of Definitions of 'Life' or 'Living Systems'

• Popa R. (2004) Chronology of Definitions and Interpretations of Life. In: Popa R, ed. Between Necessity and Probability: Searching for the Definition and Origin of Life. Berlin: Springer-Verlag 2004: pp. 197-205

• Quotes and source-citations from 1885 to 2002 CE

• Barbieri M. (2003) Appendix: Definitions of Life. In: The Organic Codes: An Introduction to Semantic Biology. Cambridge, UK: Cambridge University Press ISBN 0521824141

• Quotes from 1802 to 2002

Further Reading Not Cited in Text

Books and Book Chapters

• Schrodinger E. (1944-2000) What is Life? Cambridge University Press (Canto). ISBN 0-521-42708-8 Chapter 6: Order, Disorder and Entropy

• Prediction of hereditary molecule like a coded periodic crystal. Watson claims inspiration. Stresses open thermodynamic systems key to life.

• Kaneko K. (2006) Life: An Introduction to Complex Systems Biology. Springer, Berlin. ISBN 3-540-32666-9
• Dill KA, Bromberg S, Stigter D. (2003) Molecular Driving Forces: Statistical Thermodynamics in Chemistry and Biology. Garland Science, New York. ISBN 0-8153-2051-5
• Strogatz SH (2003) Sync: The Emerging Science of Spontaneous Order. Theia, New York. ISBN 0-7868-6844-9
• Buchanan M (2002) Nexus: Small Worlds and the Groundbreaking Science of Networks. W.W. Norton, New York. ISBN 0-393-04153-0
• Hoagland M, Dodson B, Hauck J. (2001) Exploring the Way Life Works: The Science of Biology. Jones and Bartlett Publishers, Inc., Mississauga, Ontario. ISBN 0-7637-1688-X

• Wonderful especially for young people. An illustrated text.

• Solé R, Goodwin B. (2000) Signs of Life: How Complexity Pervades Biology. Basic Books, Perseus Books Group, New York. ISBN 0-465-01928-5
• Loewenstein WR. (2000) The Touchstone of life: Molecular Information, Cell Communication, and the Foundations of Life. Oxford University Press, Oxford. ISBN 0-19-514057-5 Book Review and Chapter One
• Hoagland M, Dodson B. (1998) The Way Life Works: The Science Lovers Illustrated Guide to How Life Grows, Develops, Reproduces, and Gets Along. Three Rivers Press, New York. ISBN 0-8129-2888-1

• Wonderful especially for young people. An illustrated text.

• Mayr E. (1997) This is Biology: The Science of the Living World. Belknap Press of Harvard University Press, Cambridge, Mass. ISBN 067488468X
• Margulis L, Sagan D. (1995) What is Life? Simon & Schuster. ISBN 0-684-81087-5

Articles

• Epstein IR, Pojman JA, Steinbock O. (2006) Introduction: Self-organization in nonequilibrium chemical systems. Chaos 16:037101 PMID 17014235
• Hazen R. (2006) The Big Questions: What is Life? New Scientist Issue 2578, 17 November 2006, page 46-51
• Marenduzzo D, Micheletti C, Cook PR. (2006) Entropy-driven genome organization. Biophys J 90:3712-3721 PMID 16500976
• Morowitz H, Smith E (2006) Energy flow and the organization of life. Link to PDF
• Scheffer M, van Nes EH. (2006) Self-organized similarity, the evolutionary emergence of groups of similar species. Proc Natl Acad Sci U S A 103:6230-6235 PMID 16585519
• Walsh DM. (2006) Organisms as natural purposes: The contemporary evolutionary perspective. Studies in History and Philosophy of Science. Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 37:771-791 Link to Article
• Park K, Lai YC, Ye N. (2005) Self-organized scale-free networks. Phys Rev E Stat Nonlin Soft Matter Phys 72:026131 PMID 16196668
• Troisi A, Wong V, Ratner MA. (2005) An agent-based approach for modeling molecular self-organization. Proc Natl Acad Sci U S A 102:255-260 PMID 15625108
• Pace NR. (2001) Special Feature: The universal nature of biochemistry. PNAS 98:805-8
  
• Dronamraju KR. (1999) Erwin Schrodinger and the Origins of Molecular Biology. Genetics 153:1071-1076 PMID 10545442 Link to Journal

Interviews and Commentaries

• Kauffman S. The Adjacent Possible: A Talk with Stuart Kauffman

See also in Citizendium

• Origin of life
• Evolution of cells
• Systems biology
• Biology

External links not cited above

• "In the Beginning..." (The Economist)

• From the preface: "How life on Earth got going is still mysterious, but not for want of ideas."

• Stanford Encyclopedia of Philosophy entry

• Excerpt from Conclusion: "“Living organisms are autopoietic systems: self-constructing, self-maintaining, energy-transducing autocatalytic entities” in which information needed to construct the next generation of organisms is stabilized in nucleic acids that replicate within the context of whole cells and work with other developmental resources during the life-cycles of organisms, but they are also “systems capable of evolving by variation and natural selection: self-reproducing entities, whose forms and functions are adapted to their environment and reflect the composition and history of an ecosystem” (Harold 2001, 232)."

• Life under extreme conditions.

Appendix A

Specific Characteristics Shared by All Living Things and Not Explicitly Stated in Article

Living things share some very specific features not always explicitly stated above. For example,

• in addition to the principle of parsimony, much evidence supports the proposition that all extant living things descended from a common ancestor; little evidence argues against that proposition;
• only preexisting cells can "manufacture" new cells;
• only preexisting multicellular organisms can 'manufacture" new multicellular organisms;
• a membrane encloses every cell, protecting each from dissolution into its external environment;

• the cell membrane contains molecular systems that enables the cell to import usable matter and energy and to export unusable matter and energy, and others that enable it to send and receive signals to and from other cells;

• all cells and multicellular systems eventually die.

Appendix B

Selected Definitions of Life Offered by 19th and 20th Century Thinkers

Marcello Bárbieri, Professor of Morphology and Embryology at the University of Ferrara, Italy, collected an extensive list of definitions of “Life” from scientists and philosophers of the 19th and 20th centuries. Those selected below resonate with the systems and thermodynamic perspectives of living systems:

• "The broadest and most complete definition of life will be "the continuous adjustment of internal to external relations". — Hebert Spencer (1884)

• "It is the particular manner of composition of the materials and processes, their spatial and temporal organisation which constitute what we call life." — A. Putter (1923)

• "A living organism is a system organised in a hierarchic order of many different parts, in which a great number of processes are so disposed that by means of their mutual relations, within wide limits with constant change of the materials and energies constituting the system, and also in spite of disturbances conditioned by external influences, the system ts generated or remains in the state characteristic of it, or these processes lead to the production of similar systems." — Ludwig von Bertalanffy (1933)

• "Life seems to be an orderly and lawful behaviour of matter, not based exclusively on its tendency to go from order to disorder, but based partly on existing order that is kept up." — Erwin Schrodinger (1944)

• "Life is made of three basic elements: matter, energy and information. Any element in life that is not matter and energy can be reduced to information." — P.Fong (1973)

• "A living system is an open system that is self-replicating, self-regulating, and feeds on energy from the environment." — R. Sattler (1986)

Appendix C

Textbook mentionables

From the several different perspectives on what constitutes a living system, discussed in this article, one can derive the list of features that biology textbooks often ascribe to living systems:

1. Organization: A temporary organization of interrelated, coordinated, dynamically interacting hierarchy of molecular components within cells, of cellular components within organs and organisms, of organisms within species, and of species within ecosystems—each importing energy and matter, and using it to build, grow and sustain its structural organization for performing the functional activities needed to maintain that organization for reproducing itself.
2. Metabolism: Conversion of imported energy into any or all of the various forms of energy (e.g., chemical, electrical, mechanical, thermal), needed to utilize imported matter for maintaining functional organization.
3. Growth: At certain stages of its life-cycle, cells, organs, and organisms maintain a higher rate of synthesis (anabolism) than breakdown (catabolism) of structure and increase in organizational complexity. Growth occurs largely according to a "plan" for survival and reproduction. Species tend to grow in numbers of individuals as resources and other factors permit.
4. Reproduction: The ability to reproduce itself, for example, the division of one cell to form two new cells. Usually the term is applied to the production of a new individual (either asexual reproduction, from a single parent organism, or sexual reproduction from at least two differing parent organisms), although strictly speaking it also describes the production of new cells in the process of growth.
5. Gain of New Inheritable Traits.: Inheritable diversity, whether adaptive, neutral or disadvantageous, is a common feature of living things, and the starting point for natural selection. (See also:)
6. Adaptation: At the species level, the ability to gain traits through evolutionary processes that improve the members of the species chance for reproductive success; at the individual organism level, the ability to change (e.g., through learning) in ways that improve the individual's chances for reproductive success.
7. Response to stimuli: A response can take many forms, from the contraction of a unicellular organism when touched, to complex reactions involving all the senses of higher animals. A response is often expressed by motion, for example, the leaves of a plant turning toward the sun, an animal chasing its prey, or neuronal action potentials traveling down nerve fibres during thought.
8. Homeostasis: Regulation of the internal environment to maintain a near-constant state in response to perturbations; for example, sweating to cool off.

Exceptions

Not all entities that otherwise qualify as living reproduce themselves, although they exist as reproduced living things. Biologists call such living things 'sterile'. Examples include programmed sterility (e.g., worker ants, mules); acquired sterility (due to acquired injury (disease) to the reproductive process; access sterility (lack of reproductive fitness); voluntary sterility (e.g., human couples). Obviously living things with the capacity to reproduce may die before reaching the reproductive stage in their life-cycle. Conversely, non-reproducing individuals may still effect reproduction of copies of their genes by facilitating the reproduction of kin, who share many genes (see kin selection).

Viruses would not qualify strictly as living things, but manage to 'reproduce' in living systems.

One might ask whether a spermatozoon qualifies as a living entity. From the thermodynamic perspective, one might answer affirmatively, as it keeps itself ‘living’ by doing cellular work. It has a compartmentalized internal organization functioning to keep it far-from-equilibrium. In that respect it resembles a motile bacterium. A spermatozoon reproduces, but in a different way than a motile bacterium: it does it through its parent’s progeny, which the spermatozoon plays an essential role in generating. It doesn’t have to hijack a cell’s machinery to reproduce; it cooperates with another cell (an ovum) to generate cells with machinery to reproduce it. Moreover, in reproducing that way, it subjects itself to meiotic crossover variation, just as its parent’s progeny does, contributing to the variation needed by natural selection to perpetuate the process of living on an earth with ever-changing environments.