Life/Citable Version

From Citizendium
< Life
Revision as of 11:30, 2 April 2007 by imported>Gareth Leng (→‎Systems)
Jump to navigation Jump to search

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 diverse contexts unfolds in the course of the article.


Views of a Foetus in the Womb (c. 1510 - 1512) is a drawing by Leonardo da Vinci. Detail. Source: http://www.drawingsofleonardo.org/

Thinking clearly about 'life' versus 'living'

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.[1] 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

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."[2]

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' that are universal among languages. Children learn the meaning of prime words by how the society in which they live uses them in everyday language. Every other word can be defined using some combination of semantic primes.[3] The verb ‘live’ is a semantic prime, the noun ‘life’ is not. [4] Using semantic primes, 'Life' is defined as 'that which lives', where lives is understood by speakers and listeners from their own experience of how it is used. 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.”[5] 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'."[6] Perhaps this resonates with the remark of biologist Antonio Lazcano: "Life is like music; you can describe it but not define it".[7]

Living systems as seen from different perspectives — summary

Signs of life. Top: Spermatozoon and oocyte merge to begin a new building block for a living system.. Middle: DNA, the recipe of life. (Courtesy Department of Energy Gallery) Bottom: life encoded in books.

In this article, we will detail several different ways that biologists view living systems. Here we offer a summary by way of preview:

  • living systems import energy, matter, and information from their environment; and export unusable energy and matter (called waste);
  • those abilities enable them to delay (for their lifetime) the dictate of the Second Law of Thermodynamics: that organized systems ultimately degrade to a state of randomness;
  • the flow of energy and matter through living systems enables them to organize and maintain themselves;
  • the basic building blocks of all living systems are cells; the basic (genetic) information that generates the structural components of cells comes as part of their starting materials.
  • cells inherit this information from ‘parent’ cells, raising two as yet unanswered questions: how did cells arise in the first place? and how did they acquire stores of information?;[8]
  • this information, in the form of nucleic acid macromolecules, encodes many different types of proteins that interact with each other to assemble an organization that can import energy, matter, and information and export waste;
  • those activities occur without a 'master controller'; they need only a type of organization that maintains the system far-from-equilibrium, which can yield improbable self-organized structures and activities;
  • the molecular interactions are governed by the universal laws of physics and chemistry;
  • those laws, together with the inherited information, enable a self-organizing system that can work autonomously for survival and reproduction, and enable properties to emerge that could not be anticipated from those of the system's components alone;
  • although living things cannot escape from changing external conditions; they must exhibit robustness in their organization and must have adaptable mechanisms that maintain their stability;
  • robustness and adaptability derive from the properties of a hierarchical network of subnetworks of molecular circuits;
  • living systems must produce enough reproductive variability to allow evolution through natural selection, which guides the ‘living’ world toward perpetuation of the ‘living’ world in both the near and the distant future, a continuation of a 3.5 billion year history of Earth’s ‘living’ world;
  • by evolution, living systems generate increasing varieties of living systems, occupy an extreme spectrum of environments, create their own environments,[9] and permit sufficient complexity to enable them to process information in a way that allows them to ‘experience’ themselves.

The different perspectives by which biologists understand 'living'

Oocyte and spermatozoon merging to begin a new living system.

As well as sharing a common carbon- and water-based chemistry, entities that biologists acknowledge as living — bacteria, trees, fish, chimpanzees etc. — all share a common building block, the cell. The cell is the smallest system thought capable of independent living.[10] Many organisms live as single cells, some as cooperative colonies of cells, and 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 cells in all three domains have many features in common. All cells have a surrounding membrane; a physical boundary that separates them from their environment. [11] All cells are ‘manufactured’ by pre-existing cells. All extract chemical energy from simple sugar molecules, and convert it into other energy forms that they use for many different purposes. They all inherit 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 them structure and function. All replicate their genetic code faithfully or nearly so, and so can replicate themselves.

Biologists study the commonalities and uniquenesses of cell types, and living systems in general, from many 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:[12]

  • 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 structures (e.g., networks), how they interact with each other (e.g., network dynamics), and how the structures 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 structures 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 all of those components together forms part of a new discipline, 'Systems Biology'. Systems biologists study, among other things, the phenomenon of 'emergence', whereby properties, functions and behaviors of living systems can arise even when they are not shared by any of its components, and are not predictable from a reductionist characterization of the components in isolation from the system. All cellular systems exhibit such ‘emergent’ properties. Why we are unable to predict a system's properties from the properties of its components needs explanation, as such predictions have characterized the reductionist paradigm that dominated the Scientific method in the 20th century. There are two related reasons. First, the intrinsic properties of a system’s components do not determine those of the whole system. Rather, their 'organizational dynamics' does, and this includes the interrelations of the components and their dynamic interactions. Second, the system operates in a context (its environment), and this affects the properties of the system-as-a-whole. That contextual impact in turn affects the organization of the components — a 'downward causation'. [13]

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'." [14] In other words, the organization of the components determine the behavior of the system, but that organization does not arise solely because of the intrinsic properties of the components. How the system behaves as it interacts with its environment, influences how its components are organized, and novel behaviors of the system 'emerge' that are not predictable from the intrinsic properties 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 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 [15] — the science of interactions among energy (the capacity to do work), heat (thermal energy), work (movement through force), entropy (degree of disorder) and information (degree of order). [16] The interactions define what the system can and cannot do when 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. [17] Scientists discovered the laws of thermodynamics through experiment, debate, mathematical formulation and refinement, and Albert Einstein believed that they stood as an edifice of physical theory that could never topple. Most pertinent for considering living systems, by the Second Law of Thermodynamics:

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. [3]
  • 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, including electromagnetic and chemical energy — concentrations of energy disperse to lower energy levels, flowing “into the cool”,[2] 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.
  • The degree of order or organization of a system and its surroundings cannot increase spontaneously. 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 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 tending to exhaust itself into an ‘equilibrium’ state of randomness.

Those three expressions of the Second Law reflect the fact that energy and order spontaneously flow downhill — down a ‘gradient’ — toward eliminating the gradient, as if nature abhors gradients of energy and order. [2] Upon gradient elimination, all energy and order has dissipated, all change ceases, and an equilibrium state ensues. Given this, 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 seem to do so. Actually, they exploit the Universe’s gradients of energy and order — which run 'downhill'. Like a steam engine, they ‘import’ energy and order, convert it, albeit incompletely, to the work of internal organization, and so reduce their internal entropy. 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 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 — in keeping with the Second Law. 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 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 can be taken in from outside the system. The outside energy supplies the driving force that keeps the system far from equilibrium. 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. [18]

We can, then, view a living system as a state of organizational activity maintained by importing, storing and transforming energy and matter into the work and structures needed to sustain that state. They can only do so by producing waste and exporting it, and this lowers 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. Thus, from a thermodynamic perspective:

A living system has the ability to remain for a time in a near steady-state as an organized system. It is enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state.

Evolutionary

Last Paragraph of Charles Darwin’s Origin of Species (1859) It is interesting to contemplate an entangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth, and to reflect that these elaborately constructed forms, so different from each other, and dependent on each other in so complex a manner, have all been produced by laws acting around us. These laws, taken in the largest sense, being Growth with Reproduction; Inheritance which is almost implied by reproduction; Variability from the indirect and direct action of the external conditions of life, and from use and disuse; a Ratio of Increase so high as to lead to a Struggle for Life, and as a consequence to Natural Selection, entailing Divergence of Character and the Extinction of less-improved forms. Thus, from the war of nature, from famine and death, the most exalted object which we are capable of conceiving, namely, the production of the higher animals, directly follows. There is grandeur in this view of life, with its several powers, having been originally breathed into a few forms or into one; and that, whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved. Full-Text Here


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, but with variations introduced by random events (including 'mutations'). Some variations offer some progeny [19] less opportunity to reproduce than others, and other progeny better opportunity, sometimes better even than their progenitors. Accordingly, new groups with different properties arise, that may supplant older groups because of their greater reproductive fitness. Biologists call this 'evolution by natural selection', and regard it as the most important way whereby living systems evolve over geological time.[20].

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. [21] Evolution by 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. [22]

Combining the thermodynamic and evolutionary perspectives, we can say that:

A living system has the ability to remain for a time in a near steady-state as an organized system. It is enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state. Finally, it is capable of participating in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Exobiological

Exobiologists (also known as "astrobiologists") consider 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 in their book Life in the Universe.[23]. 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. [24] 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 by forming and breaking strong covalent bonds, and also through weaker, quasi-stable non-covalent electromagnetic interactions, like hydrogen bonding and van der Waals forces. Those interactions give aggregates of molecules the physical properties that underpin many biological processes. [24] [25] [26] [27]

One way to understand self-organization is to view the genetic information (the genome) as a 'computer' in which the genome functions as a ‘program’ that constructs components of the cell that arrange themselves according to their chemical properties. That arrangement, with the tinkering comprising local trial-and-error and evolution’s handiwork, can then carry out ('compute') integrative functions that are not explicitly encoded in the genome. [28] As Oxford professor Denis Noble[28] reminds us, the Nobel Prize-winning molecular biologist Sidney Brenner[29] 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.” [30]

The patterns of structure and behavior in self-organized systems need no behind-the-scene master, and no prepared recipes that specify the structure and dynamics of the system. Instead, these emerge from the interactions among the components, dictated by their physical properties, dynamically modified by the emerging organization, which is itself modified by the environment. 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'.[31]

Self-organization tends to breed greater self-organization — and hence more complexity. Genes express not only proteins that organize themselves into a functional unit, but also proteins that organize themselves to regulate that 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 — communication activities that self-organize by 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 in a near steady-state as a self-organized system. It is enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state. Finally, it is capable of participating 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.[32] [33] 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'. The energy to produce the enzyme 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 energy 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 self-replication to proceed.[32]

Kauffman conceives, then, of an 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 self-replication, and its re-energizing repair by transduction of external energy. Kauffman calls such a network a 'molecular autonomous agent' because, given external energy (e.g. photons) and ample materials (the molecules needed to assemble the autocatalytic enzyme), the network perpetuates its existence; the network is autonomous because it is not controlled by outside forces even though it depends 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 survives by ‘eating’ outside materials and energy. Work gets done because the system remains far-from-equilibrium: 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 agent continues 'to live' (survive and self-replicate) only while that far-from-equilibrium state exists, and it can be starved to 'death' by stopping the matter and energy from flowing through the system. Kauffman argues, from his example, that cells, and indeed all living systems, qualify as autonomous agents, constructed from molecular autonomous agents.[32]

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." [34]

For Kauffman, the property of pursuing its own agenda includes contributing to its own survival and 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." [35] There is only one escape from work, and that is death.

If the descriptions of living systems from thermodynamic, evolutionary, self-organizational and autonomous agent perspectives are considered, we can say that:

A living system has the ability to remain for a time in a near steady-state as a self-organized system. It works autonomously in its own behalf to offset responses to perturbations, and to reproduce itself, enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state. Finally, it is capable of participating 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: Qi Y, Ge H Modularity and dynamics of cellular networks. PLoS Comp Biol 2(12):e174

The science of networks[36] provides another useful perspective on living things. Networks ‘re-present’ a 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 signalling pathways, to intraspecies networks, to ecosystems. 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. [36] [37]

According to Alon, "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."[38] Alon notes that cellular networks are like many human engineered networks in that they show 'modularity', 'robustness', and 'motifs':

  • Modules comprise subnetworks with a specific function that connect with other modules often only at one input node and one output node. Modularity facilitates cellular adaptation to a changing environment, as, to produce an adaptation, evolution need tinker with a few modules rather than with the whole system. Evolution can exapt[39] existing modules for novel functions that contribute to survival.
  • Robustness offers continued functionality of a network in the face of environmental perturbations that affect the components. Robustness also restricts the range of network types that researchers have to consider, because only certain types enable robustness.
  • Network motifs offer economy of network design, as the same circuit can have many different uses in cellular regulation, as in the case of autoregulatory circuits and feedforward loops. Nature selects motifs in part for their ability to make networks robust, so systems use motifs that work well over and over again in many different networks. [40] 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. [41] Networks, like those in cells and those in neural networks in the brain,[42] employ motifs as basic building blocks, like multicellular organisms employ cells as basic building blocks. Other characteristics of motifs as well offer biologists a level of simplicity of biological functionality for their efforts to model the dynamics of organized hierarchies of networks. [40]

The view of the cell as an overlay of mathematically-definable dynamic networks can reveal how a living system can exist as an improbable, intricate, self-orchestrated dance of molecules. [43] 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 in a near steady-state as a self-organized system of hierarchical robust modular networks. It works autonomously in its own behalf to offset responses to perturbations, and to reproduce itself, enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state. Finally, it is capable of participating 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[44] 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 this 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: 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.

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 indicate 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: Qi Y, Ge H Modularity and dynamics of cellular networks. PLoS Comp Biol 2:e174 doi:10.1371/journal.pcbi.0020174


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. 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[45] 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 have information content in that they are unlikely (non-random) arrangements of parts, non-random collections of interactions of parts, non-random collections of functional activities.

The thermodynamic and autonomous agent perspectives discussed cells as intermediates in a gradient of higher to lower forms of usable energy. The flow of energy through the cell feeds it, enabling it to work to gain form, or order, and to gain functionalities, raising its information content. [46] 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[47] and materials in its environment, fueling and supplying the machinery that builds and sustains information-rich organization; it can generate new information inside itself, as in embryonic development; and it can transmit information within and outside itself, as in transcription regulation and exporting pheromones. From its parent, it inherits information that establishes its developmental potential and scripts its realization, — including information that enables it to reproduce itself.

Combined with other perspectives, viewing living systems as information banks, as inheritors, receivers, generators and transmitters of information, and as reproducers of inherited information, enables one to see living systems and their interactions with other living 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'. [48] 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.

We might now consider another, closely related, perspective, a ‘cognitive’ perspective. [49] Given that networks resist common perturbations (‘robustness’, ‘homeostasis’), one might think of them as containing a ‘representation’ of their environment and of how it might vary. As networks self-organize through interactions between proteins, any network ‘representation’ of its environment must derive from the genetic information that determines those proteins. The genetic information comprises a molecular code, and the process that transforms that information into proteins describes an algorithm &mdash the transcription-translation algorithm. As these algorithms evolved through natural selection, one can view evolution as selecting for ‘cognitive’ functionality in the genome &mdash the ability to ‘represent’ the cell’s environment, and more generally, to remember and anticipate.

Further elaborating 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 faculty to remain for a time in a near steady-state as a self-organized system of hierarchical robust modular networks. It works autonomously in its own behalf to offset responses to perturbations, and to reproduce itself, enabled by the influx of energy and matter and by a more than compensatory efflux of waste (disorder), thereby exploiting an organizationally enabling far-from-equilibrium state. Finally, it is capable of participating in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Synthesis of perspectives on what constitutes a living system

The activity of living, for a cell-based system, depends on the ability to maintain a near steady-state of organized functioning far from the state of randomness. The system achieves this in part because of its location in the path of a downhill gradient of flowing energy. It exploits that gradient through its abilities to import some of the energy flowing past it, and to export unusable energy and material, thus increasing its own order at the expense of a more than counterbalancing disorder of its surroundings.

Those principles apply to all living systems: single cells, multicellular organs and organisms, and multi-organism demes and ecosystems.

The building block of all living systems is the cell. For a system to achieve order, cells must have, from the outset, some informational content. This enables the cell to produce components that can respond to the imported energy and material by organizing themselves. That state comprises modular networks of molecular interactions, and networks of interacting networks, self-organized and coordinated functional interactions. The properties of the networks and those of the hierarchy of networks enable the system to perpetuate itself, and allow it to maintain its steady-state despite fluctuations in environmental factors. This principle, too, applies to all living systems. An organism, plant or animal, comprises a network of organs working autonomously, maintaining its steady-state functioning far from equilibrium in response to environmental perturbations — physiologists refer to this as homeostasis.

The networks that regulate the flow of information through the cell were 'designed' by natural selection and other evolutionary processes. The collaboration of natural selection and physico-chemical laws serves to perpetuate living systems not only in real-time but also in geological, or ‘evolutionary’, time. From one common ancestor cell — however that may have emerged from non-living systems — informationally-guided, self-organizing, autonomous network dynamics enabled generation of the diversity of all living systems on the planet, over a period of more than three billion years. Living systems perpetuate living systems, exploiting free energy on its inexorable path to dissipation, constraining that dissipation in developing systems organization by a more than counterbalancing dis-organizing of the larger system in which it is embedded.

References

Citations and Notes

  1. Mayr E (1997) This is Biology: The Science of the Living World. Cambridge, Mass: Belknap Press of Harvard University Press
  2. Jump up to: 2.0 2.1 2.2 Schneider ED, Sagan D (2005) Into the Cool: Energy Flow, Thermodynamics, and Life. University of Chicago Press. ISBN 0-226-73936-8 Read large excerpts of several chapters here Cite error: Invalid <ref> tag; name "schneider05" defined multiple times with different content
  3. Wierzbicka A (1996) Semantics: Primes and Universals. Oxford England: Oxford University Press ISBN 0198700024
  4. See list of semantic primes at this site: Goddard C, Wierzbicka A (2006) Semantic Primes and Cultural Scripts in Language: Learning and Intercultural Communication
  5. J.H. Woodger (1929) quoted in Barbieri M (2003) The Organic Codes; An Introduction to Semantic Biology. Cambridge: Cambridge University Press. Appendix. DEFINITIONS OF LIFE. (Author notes: From Noam Lahav's Biogenesis, 1999; from Martino Rizzotti's Defining Life, 1996; and from personal communications by David Abel, Pietro Ramellini and Edward Trifonov, with permission)
  6. Read Carol Cleland here
  7. (Lazcano 1994, cited in 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
  8. Note: We can arrive at a more-or-less empirically sound explanation of what constitutes living systems without having a good explanation for how they arose in the first place, because we can study the here-and-now and not the there-and-then.
  9. Odling-Smee FJ, Laland KN, Feldman MW. (2003) Niche Construction; The Neglected Process in Evolution. Princeton: Princeton University Press. ISBN 0691044384
  10. Note: This article will not refer to intracellular systems (e.g., cellular organelles, metabolic pathways, gene transcription circuits) as 'living systems', but rather as 'biological systems', which generically includes 'living systems'. The rationale for that distinction becomes apparent when we learn that 'living systems' emerge from the cooperative effort of those intracellular systems.
  11. ’’’Note’’’: Other boundaries of living systems include bark, shells, cell walls, skin, fur, and structures of the physical environment.
  12. Andrea Falcon (2006) Aristotle on Causality
  13. Note: In relation to downward causation, the environment’s effect can sometimes reach down to the genetic recipe with molecular signals, altering the recipe’s expression and consequently the characteristics of the cells — so-called 'epigenetic' effects. When epigenetic alterations of gene expression occur in the reproductive organs, the system changes can transmit to the next generation. See the following articles and the references cited therein
    Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: The MIT Press
    Gorelick R (2004) Neo-Lamarckian medicine. Med Hypotheses 62:299-303 PMID 14962644
  14. Walsh DM (2006) Organisms as natural purposes: the contemporary evolutionary perspective. Stud Hist Philos Biol Biomed Sci 37: 771-91
  15. Note: thermodynamics: thermo-, heat; -dynamics, movement
  16. Note: A random pattern of parts has no order (it has maximum entropy), and no information. A living system has order in its organized functions, has computationally-rich informational content, and low entropy.
  17. Note: The total energy of the Universe remains constant, but if and when it completely disperses itself, in such ‘degraded’ form it no longer can do work.
  18. Prigogine I, Stengers I (1997) The End of Certainty: Time, Chaos, and the New Laws of Nature. Free Press, New York. ISBN 0684837056
  19. Note: ....or the progeny of some conspecific living systems. Many living systems coexist with like living systems, constituting a 'species', or group of 'conspecifics'.
  20. Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: The MIT Press
  21. Darwin C (1982; originally 1859) The Origin of Species By Means of Natural Selection or the Preservation of Favoured Races in the Struggle for Life. London: Penguin Books ISBN 9780140432053
  22. Smolin L (1997) The Life of the Cosmos. New York: Oxford University Press. ISBN 019510837X
  23. Schulze-Makuch D, Irwin LN, Definition of Life. In Life in the Universe. Berlin: Springer-Verlag 2004: Chapter 2. pp. 8-34 Link to Summary and Full-Text
  24. Jump up to: 24.0 24.1 Lehn JM (2002) Toward self-organization and complex matter. Science 295:2400-3
  25. Reinhoudt DN, Crego-Calama M (2002) Synthesis beyond the molecule. Science 295:2403-7
  26. Percec V et al. (2006) CHEMISTRY: Self-assembly in action. Science 313:2403-7
  27. Note: The qualifier, ‘in part’, in this paragraph reflects the need to invoke not only molecular self-assembly, but also evolutionary mechanisms selecting genes that yield proteins whose chemical properties enable interactions that tend to optimize functional self-organization — in other words, adaption to circumstances. One must also invoke local real-time selective processes that confer stability and appropriate functionality to molecular self-assembly, called homeostasis. Self-organization and adaptation conjoin to yield function.
    Heylighen F (2001) The Science of Self-organization and Adaptivity. In: Kiel LD (ed.) Knowledge Management, Organizational Intelligence and Learning, and Complexity: The Encyclopedia of Life Support Systems (EOLSS) Oxford: Eolss
  28. Jump up to: 28.0 28.1 Noble D (2002) Modeling the heart—from genes to cells to the whole organ. Science 295:1678-82
  29. Sidney Brenner’s Nobel lecture (2002) “Nature’s Gift to Science”
  30. Brenner S (1998) Biological computation. Novartis Found Symp 213:106-11 PMID 9653718
  31. Dawkins R. (1988) The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design. New York: W.W. Norton & Company, Inc. ISBN 0393304485 Excerpt from Amazon.com review: “The title of this 1986 work, Dawkins's second book, refers to the Rev. William Paley's 1802 work, Natural Theology, which argued that, just as finding a watch would lead you to conclude that a watchmaker must exist, the complexity of living organisms proves that a Creator exists. Not so, says Dawkins: "the only watchmaker in nature is the blind forces of physics, albeit deployed in a very special way... it is the blind watchmaker." Physics, of course, includes non-equilibrium thermodynamics.
  32. Jump up to: 32.0 32.1 32.2 Kauffman S (2003) Molecular autonomous agents. Philos Transact A Math Phys Eng Sci. 361:1089-99 PMI: 12816601
  33. Kauffman SA (2000) Investigations. Oxford University Press, Oxford. ISBN 019512104X Publisher’s description and reviews
  34. Franklin S, Graesser A (1996) Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents. Proc Third Int Workshop on Agent Theories, Architectures, and Languages, Springer-Verlag
  35. Kauffman S (2003) The Adjacent Possible
  36. Jump up to: 36.0 36.1 Barabási AL (2002) Linked: The New Science of Networks. Cambridge, Mass: Perseus Pub. ISBN 0-7382-0667-9
  37. Watts DJ. (2007) A twenty-first century science. Nature 2007;445:489 Link to Full-Text
  38. Alon U (2003) Biological networks: the tinkerer as an engineer. Science 301:1866-7 Link to Full-Text PMID 14512615
  39. Note: “Exapt: to adapt [a biological system], by [natural] selection, to a different purpose. Examples: (1) the muscles homologous to the usual vertebrate eye muscles have become exapted to move the tentacles in caecilians [snake-like amphibians]; (2) the swim bladder, originally adapted for control of buoyancy, was exapted as a respiratory organ in various groups of fish." See: [1]
  40. Jump up to: 40.0 40.1 Alon U. (2007) Simplicity in biology. Nature 446:497 Link to Full-Text
  41. Prill RJ et al.2004) Dynamic properties of network motifs contribute to biological network organization. PLoS Biol 3: e343 [2]
  42. Sporns O, Kotter R (2004) Motifs in brain networks. PLoS Biol 2: e369
  43. Alon U (2007) An Introduction to Systems Biology: Design Principles of Biological Circuits. Boca Raton: Chapman and Hall/CRC
  44. Note: proximate. (n.d.). WordNet® 2.1. Closest in degree or order (space or time) especially in a chain of causes and effects. http://dictionary.reference.com/browse/proximate
  45. Note: This article takes the view that cells underlie ‘living systems’, and that cellular subsystems, like transcription networks and metabolic pathways, qualify as ‘biological systems’ but not themselves as ‘living systems’.
  46. Note: That does not explain the origin of the ability to utilize available energy and materials. To explain that requires knowledge of the origin of living systems. See Origin of life
  47. Note: Usable energy, also called ‘free energy’, in virtue of its organized state that flows downhill to dissipated uselessness, has all the attributes of information.
  48. Deacon TW. (1997) The Symbolic Species: The Co-Evolution of Language and the Brain. New York: W.W. Norton & Company, Inc. ISBN 0393038386
  49. Danchin A et al. (2007) The extant core bacterial proteome is an archive of the origin of life Proteomics 7:875–89


Published collections of definitions of 'Life' or 'Living Systems'

  • 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

Books
  • 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 &mdash Watson claims inspiration $mdash 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 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.)
  • 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, page 46-51
  • Marenduzzo D et al. (2006) Entropy-driven genome organization. Biophys J 90:3712-3721 PMID 16500976
  • Morowitz H, Smith E (2006) Energy flow and the organization of life
  • Scheffer M, van Nes EH (2006) Self-organized similarity, the evolutionary emergence of groups of similar species. Proc Natl Acad Sci USA 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 USA 102:255-260 PMID 15625108
  • Pace NR. (2001) Special Feature: The universal nature of biochemistry. Proc Natl Acad Sci USA 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

See also in Citizendium

External links not cited above

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

Appendix A

Certain characteristics shared by all living things — not explicitly stated in text of 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.[1] 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.
  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 increase 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:[2])
  6. Adaptation: At the species level, the ability to gain traits through evolutionary processes[2] 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; at the cellular level, the ability maintain a near steady-state in response to perturbations and to change functionality in response to changes in environmental conditions;
  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.

  1. Bárbieri M. (2003) The Organic Codes; An Introduction to Semantic Biology. Cambridge: Cambridge University Press.
  2. Jump up to: 2.0 2.1 Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: The MIT Press