User:Gareth Leng/Life/Student Level

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What is life? Biologists use the word 'life' for the processes of living, for the things that carry out those processes, for the entire living world — the biosphere — and the whole history of 'life on earth'. In theory, life might include entities, now unknown, that exist on other planets. Just what qualities must beings possess for scientists to acknowledge them as alive? Could non-living things ever acquire those same qualities? What features separated the first living cells from the inanimate materials that formed them? The answers to such questions form part of the larger answer to that most basic of all questions in Biology: "what is life?" This article focuses on 'living'; on the things that living things do, and on what allows then to do them.

Buzz of Life: One aspect of the interrelations among living entities. Researchers begin to understand the mechanisms governing the complex network interactions between plants and pollinators, such as hummingbirds, shown in this illustration from Ernst Haeckel's Kunstformen der Natur (1904).

Principles of life

Molecules

All known life is built from the same set of organic molecules. Although they contain many elements, organic molecules always have a predominant structure of carbon linked to itself. In living things, organic molecules exist in mixtures of colloidal aqueous solutions that are never completely homogeneous but are bounded by lipid and protein sheets. Each pool can have a different composition with distinct properties of charge, density, viscosity and osmotic pressure; these differences provide the basis for the generation of electric fields, fluid shifts, and transport of molecules. The stuff of life, then, is carbon chains, studded with other atoms, and arranged in lagoons of fat, water, and salts.

Cells

As well as sharing a common carbon- and water-based chemistry, everything that biologists acknowledge as living — bacteria, trees, fish, chimpanzees — shares a common building block, the cell. Many organisms are isolated single cells, others are cooperative colonies of cells, and some are complex multicellular systems that include diverse cell types, each specialized for different functions. Nature has produced an enormous variety of cell types that span 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. That membrane always has special properties that allow protection, excretion, ingestion or communication. Often, these functions are provided by changes in the shape or actual chemical species present on the surface — so pores, receptor molecules and protective walls are often features of the cell surface.

Current evidence indicates that only pre-existing cells can ‘manufacture’ cells. So how did the first cell(s) arise?

Examining what all extant cells have in common may provide insight to the Origin of life. All extract chemical energy from simple oxidation reactions, and convert it into other, chemical forms of energy. All cells inherit information in the form of molecules of DNA, and with minor exceptions the DNA of all cells use the same universal genetic code to produce of a myriad of distinct protein structures. Cells use those proteins to carry out diverse activities, including energy processing and conversion of carbon, nitrogen and phosphorous-containing materials into cellular structures. In the human genome, perhaps as few as 22,000 different protein-coding genes lead to the production of perhaps more than a million distinct protein structures that make up the variety and quantity of protein molecules needed for the structures and functions of a cell.

Nature has produced a huge diversity of single-celled organisms and large, complex animals or plants. The latter can contain vast numbers of cells, each part of a specialized subpopulation (cell types) — in a mammal, the cells that make up bone differ from those that make up muscle, and differ again from those that make up skin, for example. Humans contain approximately 200 different cell types as classified by microscopic anatomy. In multicellular organisms, cells combine to make organs, the functional and structural components of the single larger organism.

So what makes a single celled organism 'alive', and does the answer apply also when we call a large complex multicellular animal or plant 'alive'? What exactly do we mean by 'living'?

Systems view of 'living'

Oocyte and spermatozoon merging to begin a new living system.

From one perspective, a living thing comprises:

• A list of organic and inorganic parts (molecules and ions; cells, organelles, organs and organisms)
• How the parts and structures became dynamically coordinated (e.g., gene expression; self-organization; competition) and
• How the living system as-a-whole functions and behaves, and the properties that characterize it (e.g., reproduction; locomotion; cognition)

The analysis of all of those components together is part of the new discipline of Systems Biology. Systems biologists study, among other things, the phenomenon of 'emergence', whereby properties, functions, and behaviors of living systems arise from the complex interactions of the components the system. Every cellular system exhibits emergent behaviors. Emergent behaviors of living systems include such things as locomotion, sexual display, flocking, and conscious experiencing.

The intrinsic properties of a system’s components themselves do not determine those of the whole system; rather, their 'organizational dynamics' does, and those dynamics include not only the interrelations among the components themselves, but also interactions among the many different organizational units in the system. Secondly, the living system always operates in a context (its external environment), and that always affects the properties of the system-as-a-whole. One cannot simply take a living system apart and predict how it will behave.

For example, the behavior of a human kidney cell depends not only on its cellular physiology, but also on all the properties of the organ (kidney) which constitutes its environment. The kidney's structure and function influence the cell’s structure and behavior (e.g., by physical confinement and by cell-to-cell signaling), which in turn influence the organization of its intracellular components. The kidney in turn responds to its environment, namely the individual body that it lives in, and that body responds to its environment, which includes such factors as the availability of particular food items, fresh water, and ambient temperature and humidity.

The thermodynamics of 'living'

Biologists often view living things from the perspective of thermodynamics — 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). These interactions define what a system can and cannot do when interconverting energy and work. The Second Law of Thermodynamics may be most pertinent to an analysis of living systems:

Energy 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.[1]

• Heat flows spontaneously — i.e., without external help — from a region of higher temperature to one of lower temperature, and never 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", 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.
• Consequences arise from the fact that work can produce organization in a system, but only by exporting disorganizing heat to its surroundings. Experiments reveal the ‘organizational balance’. The degree of order or organization of a system and its surroundings never increases when energy produces work. Scientists have learned how to put a number on the degree of disorder of a system, or system and surrounds, 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. 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, 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 are non-equilibrium thermodynamic systems in that they consume energy to live, and export unusable (degraded) energy to dissipate the energy gradient they find themselves in. 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 would ensue if no energy could be imported: energy from outside 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, and one very remarkable behavior that can result from this disequilibrum is self-organization.

Evolutionary aspects of 'living'

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

Historically, fires and storms both have achieved status as living entities in human imagination. Although some non-living entities, such as tornadoes or the flames of candles, exist, like living things, as non-equilibrium open thermodynamic systems, they lack essential qualities of living things, and those deficiencies remove scientific credence of the 'poetic' view. Tornadoes and candle flames cannot 'reproduce' themselves, as cells and organisms can. Fire may spread and tornadoes may split, but the full system that comprises each phenomenon does not self-replicate. Living systems not only have open access to the environment in terms of energy and entropy exchange, but also have the ability to reproducing. When a living system reproduces itself, its offspring inherit its properties, but with variations introduced by random events (including mutations). Some variations offer some of the offspring less opportunity to reproduce than others, and other offspring better opportunity, sometimes better even than their parents. 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.

Biologists recognize the ability to reproduce with some variation, as an essential characteristic of living systems. They refer to it as descent with modification. Evolution by natural selection will occur if heritable variations produce offspring that differ in their reproductive fitness. The variations occur due to chance variations in the inherited genetic recipe (genotype) for constructing the organismic traits (phenotype). In all living systems, DNA primarily provides the genetic recipe. All living things extant today descended with modification from an ancient ancestral community of microorganisms. To glimpse beyond that horizon, we will need to take heed of the findings of intense current research on early cellular evolution.

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.

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

A living system is able to remain for a time as an organized system, made possible by the influx of energy and matter and a compensatory efflux of waste. A system is also capable of participating in the transgenerational evolution of the species to which it belongs in adapting to changing environments.

Self-organization

In cells, self-organization emerges in part from the chemical properties of the proteins encoded in their genes. Those proteins make their appearance through a genetic transcription-translation machinery, which represents a self-organized molecular machine that itself emerges in part from the chemical properties of proteins and other molecules. One way to understand self-organization is to view the genome as a 'computer program' that guides construction of the components of the cell that then 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.

The patterns of structure and behavior in self-organized systems need no behind-the-scene 'master controller', and no prepared recipes that specify the structure and dynamics of the system. Instead, those patterns emerge from the interactions among the naturally selected components of a system, dictated by their physical properties, and dynamically modified by the emerging organization, which is itself modified by the environment. Thus 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 — becoming a network of many cell-types working cooperatively. That biological systems self-organize has led one prominent biologist to say they are products of a "blind watchmaker".

Self-organization tends to breed greater complexity of self-organization. One important aspect of self-organization in cells rests on the tendency for lipids with polar (water-loving) and non-polar (water-shunning) ends to line up side-by-side to form bilayers in an aqueous solution, each unit of the bilayer with two lipid non-polar ends mutually attracted in the center and the polar ends surrounded by water. Membranes thereby form. Proteins can span the bilayer membrane, or selectively straddle only one or the other side of the membrane and its aqueous surrounding, according to their specific amino-acid sequence and side-groups. Other aspects of self-organization: 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, as in metabolic pathways. Cells communicate with other cells, either in free-living cellular communities or in multicellular organisms, and those communication activities self-organize by virtue of the properties of the cells, selected for fitness by evolutionary mechanisms, and subject to downward effects by the systems' organization and environmental influences on the systems.

Further elaborating the descriptions of living systems beyond the thermodynamic and evolutionary perspectives, we might say that:

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

Autonomous agents

Views of a Foetus in the Womb (c. 1510 - 1512) is a drawing by Leonardo da Vinci. Detail. Although this near term fetus is a symbol of a new human life, the drawing is of a cadaver specimen. [2]

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. The energy to produce the enzyme comes from a neighboring molecule, by breaking an energy-rich bond, 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.

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. Such a network is 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: as energy flows through the system, the system does its work, and in so doing dissipates the energy gradient, but it temporarily constrains 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 that cells, and indeed all living systems, qualify as autonomous agents, constructed from molecular autonomous agents.

For Kauffman, the property of pursuing its own agenda includes contributing to its own survival and reproduction.

If the descriptions of living systems from thermodynamic, evolutionary, self-organizational and autonomous agent perspectives are considered, we might 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 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 a 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 provides another useful perspective on living things. Networks ‘re-present’ a system as '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 signaling 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; they also construct networks of electronic parts to produce, for example, mobile phones; and networks 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.

Cellular networks,like many human engineered networks, they show 'modularity', 'robustness', and 'motifs':

• Modules are subnetworks with a specific function and which connect with other modules often only at one input node and one output node. Modularity facilitates adaptation to a changing environment, as, to produce an adaptation, evolution need tinker with just a few modules rather than with the whole system. Evolution can sometimes 'exapt' existing modules for new functions that contribute to reproductive fitness. For example, the swim bladder evolved as an adaptation for control of buoyancy but was exapted as a respiratory organ in various groups of fish.
• Robustness describes how a network is able to maintain its functionality despite environmental perturbations that affect the components. Robustness also reduces the range of network types that researchers must consider, because only certain types of networks are robust.
• 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. In several well-studied biological networks, the abundance of network motifs — small subnetworks — correlates with the degree of robustness. Networks, like those in cells and those in neural networks in the brain, use motifs as basic building blocks, like multicellular organisms use cells as basic building blocks. Motifs offer biologists a level of simplicity of biological functionality for their efforts to model the dynamics of organized hierarchies of networks.

The view of the cell as an overlay of mathematically-definable dynamic networks can reveal how a living system can be an improbable, intricate, self-orchestrated dance of molecules. The 'overlay of networks' view 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 might 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 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 a 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 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 or to conserve the environment). Those realities attest that biological systems harbor information, at least as people usually understand the term. 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.

Information processing from DNA to a living system. Genes are made up of DNA, and contain the information used by other cellular components to create proteins. A cell is tightly packed with tens of thousands of proteins and other molecules, often working as multimolecular 'machines' to perform essential cellular activities. Courtesy U.S. Department of Energy. http://DOEgenomestolife.org/pubs/overview.pdf or http://genomicsgtl.energy.gov/pubs/overview_screen.pdf

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 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, and 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. and permit sufficient complexity to enable them to process information in a way that allows them to ‘experience’ themselves.

Synthesis of perspectives on what constitutes Life

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

The building block and working unit of all living systems is the cell. For cells to utilize available external energy or energy-rich matter and achieve order, they must have, from the outset, some informational content. That enables the cell to produce components that can, by molecular interactions, respond to the imported energy and material to organize themselves. That organization 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 to maintain its steady-state despite fluctuations in environmental factors. That principle, too, applies to all living systems. Any 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 that as homeostasis.

The networks that regulate the flow of information through the cell were 'designed' by natural selection and other evolutionary processes. That is, the codes that evolved by natural selection were those which produced molecules that could interact in ways that contribute to self-organization of those networks that enable a cell to sustain and reproduce itself. The collaboration of natural selection and physico-chemical laws perpetuates living systems not only in real-time but also in geological, or ‘evolutionary’, time. From common ancestors — however they may have arisen (see Evolution of cells) — 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 and degradation, and harvesting energy in developing systems organization by a more than counterbalancing dis-organizing of the larger system in which it is embedded.