The cell is a complex dynamic system in which macromolecules such as DNA and the various proteins interact within a free energy flux provided by nutrients. Its phenotypes can be represented by quasi-stable attractors embedded in a multi-dimensional state space whose dimensions are defined by the activities of the cell’s constituent proteins.

This is the basis for the dynamical model of the cell.

The current molecular genetic or machine model of the cell, on the other hand, is predicated on the work of Gregor Mendel and Charles Darwin. Mendel framed the laws of inheritance on the basis of his experimental work on pea plants. The first law states that inheritance is a discrete and not a blending process: crossing purple and white flowered varieties produces some offspring with white and some with purple flowers, but generally not intermediately colored offspring. Mendel concluded that whatever was inherited had a material or particulate nature; it could be segregated.

According to the machine cell model, those particles are genes or sequences of nucleobases in the genomic DNA. They constitute Mendel’s units of inheritance. Gene sequences are transcribed, via messenger RNA, to proteins, which are folded linear strings of amino acids called peptides. The interactions between proteins are responsible for phenotypic traits. This assumption relies on two general principles affirmed by Francis Crick in 1958, namely the sequence hypothesis and the central dogma. The sequence hypothesis asserts that the sequence of bases in the genomic DNA determines the sequence of amino acids in the peptide and the three-dimensional structure of the folded peptide. The central dogma states that the sequence hypothesis represents a flow of information from DNA to the proteins and rules out a flow in reverse.

In 1961, the American biologist Christian Anfinsen demonstrated that when the enzyme ribonuclease was denatured, it lost its activity, but regained it on re-naturing. Anfinsen concluded from the kinetics of re-naturation that the amino acid sequence of the peptide determined how the peptide folded. He did not cite Crick’s 1958 paper or the sequence hypothesis, although he had apparently read the first and confirmed the second.

The central dogma and the sequence hypothesis proved to be wonderful heuristic tools with which to conduct bench work in molecular biology.

The machine model recognizes cells to be highly regulated entities; genes are responsible for that regulation through gene regulatory networks (GRNs). Gene sequences provide all the information needed to build and regulate the cell.

Both a naturalist and an experimentalist, Darwin observed that breeding populations exhibit natural variations. Limited resources mean a struggle for existence. Individuals become better and better adapted to their environments. This process is responsible for both small adaptive improvements and dramatic changes. Darwin insisted evolution was, in both cases, gradual, and predicted that intermediate forms between species should be found both in the fossil record and in existing populations. Today, these ideas are part of the modern evolutionary synthesis, a term coined by Julian Huxley in 1942. Like the central dogma, it has been subject to controversy, despite its early designation as the set of principles under which all of biology is conducted.

The modern synthesis, we now understand, does not explain trans-generational epigenetic inheritance, consciousness, and niche construction. It is possible that the concept of the gene and the claim that evolution depends on genetic diversity may both need to be modified or replaced.

This essay is a step towards describing biology as a science founded on the laws of physics. It is a step in the right direction.

Paradigmatic Instability

The human genome was sequenced in 2001. Francis Collins, leader of the International Human Genome Sequencing Consortium and current Director of the US National Institutes of Health, claimed in 1999 that knowing the sequence would lead

to previously unimaginable insights, and from there to the common good [including] a new understanding of genetic contributions to human disease and the development of rational strategies for minimizing or preventing disease phenotypes altogether.

These benefits have not materialized. Only for rare conditions has DNA sequence been related to disease. Where common diseases are concerned, the failure to account for the genetic variation of complex traits in terms of abnormal alleles is widely acknowledged. This is the problem of missing heritability.

Then there is the phenomenon of genomic instability induced by ionizing radiation. The default assumption of radiobiology is that if a cell with damage to its DNA survives cell division, damage will be stably replicated in all subsequent generations. A 1992 experiment showed that, in some cases, cells that survive radiation exposure become unstable and acquire damage spontaneously in subsequent generations.

Genomic instability was first observed in 1976 by the Swedish geneticist K. G. Lüning. He exposed male mice (F0) to 239Pu and scored their offspring (F1) for intra-uterine death, caused by a dominant lethal mutation. Surviving male offspring, however, also produced intra-uterine death in their offspring (F2). A dominant lethal mutation had skipped a generation.

More recently, irradiated round worms (Caenorhabditis elegans) were shown after several generations to exhibit significant differences in gene expression when compared to non-irradiated controls. The gene expression in the irradiated population was more heterogeneous, indicative of stochastic diversification of phenotype, the same result seen in genomically-unstable human cells.

Genomic instability has been observed for several phenotypic endpoints and is inducible by several environmental agents in addition to radiation. It is a real biological phenomenon, not an experimental artifact.

Darwin recognized that neither the fossil record nor the evidence from extant organisms supported a gradual view of evolution. Many distinguished biologists, including Thomas Huxley, William Bateson, Hugo de Vries, Richard Goldschmidt, and Stephen Jay Gould, have questioned gradualism. More recently, Denis Noble has questioned the modern synthesis of evolution. There is important experimental evidence that is inconsistent with the principles underpinning the machine model of the cell.

A new approach is required.

Thermodynamics

Twenty years before Darwin published On the Origin of Species, Edward Blyth made an important point:

[A]mong animals which procure their food by means of their agility, strength, or delicacy of sense, the one best organized must always obtain the greatest quantity; and must, therefore, become physically the strongest, and be thus enabled, by routing its opponents, to transmit its superior qualities to a greater number of offspring.

Food is free energy that metabolic processes convert to work and entropy. Free energy utilization is governed by the second law of thermodynamics. By 1900, when biologists were first aware of the implications of the work of both Darwin and Mendel, Ludwig Boltzmann had already formulated the molecular interpretation of entropy. Since then, it has been commonplace to understand the second law of thermodynamics as suggesting that increasing entropy inevitably implies increasing disorder.

Evolution demonstrates the reverse. Organisms evolve to become more ordered and complex, rather than less. Erwin Schrödinger thus suggested that life feeds on negative entropy by exporting entropy to its environment. In extending this idea, Roger Penrose argued that high-energy solar photons are a form of low-entropy energy. Life degrades them into low-energy, high-entropy photons that are radiated back to space at night. But empirical evidence shows that the more mature an ecosystem, the lower its black body temperature.

The physicist Arto Annila, focusing on energy carriers, rather than energy itself, has considered systems open to energy exchanges with their surroundings and with chemically-interacting components. In energy-rich surroundings, as free energy is consumed and entropy increases, the system evolves towards diversity via its chemical reactions, occupying higher and higher energy levels. Increasingly complex chemical compounds are formed as the kinetics of the chemical reactions move the system to more probable states.

Increasing entropy does not inevitably lead to increasing disorder. In 1900, Henri Bénard demonstrated what is now called Rayleigh–Bénard convection, a clear empirical demonstration of increased entropy appearing as order in the form of structured Bénard cells. Increased entropy and disorder need not be synonymous. Evolution and the second law are compatible.

Nature has long been known to follow Pierre Louis Maupertuis’s principle of least action. In the context of energy consumption, this means that disequilibria in free energy will be leveled as efficiently as local conditions allow. In evolutionary terms, any improvement to an organism’s metabolic efficiency will be advantageous, and if transmitted to the next generation will lead to the evolution of increasingly more efficient organisms.

Efficiency of energy transduction then is the basis for natural selection, not genetic diversity.

What would be the cellular phenotype of a complex system? The question requires an answer in terms of dynamical system theory, a discipline deployed to describe the long-term behavior of such systems in mathematical terms. In dynamical system theory, an attractor is a stationary state of a system toward which those states that are within a basin of attraction converge. Although this makes an attractor stable under small perturbations, larger perturbations can push the system to a variant attractor. There is no continuum of stable states between attractors. Transitions are true saltations: jumps or switches.

Gradualism is not an option.

In the case of a cell, the system is defined by the interactions among proteins, which can be represented by a state space in varying dimensions. A typical human cell is able to express a few thousand active proteins. Its state space would thus have a few thousand dimensions, each corresponding to the activity of one protein. Active proteins are governed by rules of engagement that determine their involvement in the attractor.

The attractor is formally defined by relations in predicate (or first order) logic in terms of the activities of the participating gene products, the proteins p k . Whether or not a given protein is engaged in the attractor depends on rules specifying its maximum and minimum activities. These encompass the range, r, of activities, m, required at any given time t. For two proteins p 1 and p 2 if the activity of p 1 lies within its specified range at time t 1 , then the activity of p 2 will lie within its specified range at t 2 , on the condition that t 2 > t 1 . If the condition set by a given rule cannot be met, the attractor collapses and a variant attractor may be adopted.

Notice that:

The gene products, or proteins, are governed by the attractor.

The attractor evolves irreversibly in time; the system ages.

The attractor is a non-holonomic entity; its present state is contingent on its history.

For any gene product there are typically several rules of engagement. A gene product can be engaged with several other gene products. A perturbation of any one gene product thus has the potential to perturb all those with which it is engaged. If perturbations lead to the adoption of a variant attractor, the transition can induce a substantial phenotypic jump, several traits gained or lost simultaneously.

This has important implications for evolution.

The Unit of Inheritance

Attractors can be regarded as ordered, non-holonomic profiles of active proteins evolving according to the rules of engagement. Out of these profiles emerge the regulation and phenotype of the cell. If, on cell division, this profile is shared between the two resultant cells, they will both inherit the attractor. Mendel’s unit of inheritance is a process in protein chemistry that takes place in the cytoplasm and not the nucleus of the cell. Attractor states are discrete and can be segregated. They conform to Mendel’s analysis of inheritance.

Some years ago, the mathematical biologist Robert Rosen concluded that living systems are complex systems that are closed to efficient causes. They are systems capable of self-regulation. Machines, on the other hand, are systems open to efficient causes. Such systems can be reduced to their component parts and reassembled. Complex systems that yield emergent properties cannot. Only the dynamic cell model satisfies Rosen’s conditions for living systems.

The gene is not what regulates the cell, it is not responsible for the organism’s phenotype, and it is not Mendel’s unit of inheritance.

What role, then, does it play?

DNA is essential to the functioning of the cell. A great many resources are devoted to maintaining its integrity. DNA serves as an inert database to enable the cell to provide its progeny with necessary peptides. These are the starting materials that when folded and activated become the cell’s work horses.

Although the peptides are intermediates between messenger RNA (mRNA) and the protein, Crick paid them scant attention. Anfinsen confirmed Crick’s sequence hypothesis, but the folding process in his experiments was far too slow to be the mechanism operating in the cell. What Anfinsen did show is that the proteins acquire information when the peptide folds. The folding process consumes free energy. The information measures the entropy of the process and it is not necessarily related to the information in the DNA.

Genes play practically no role in the properties of the cellular phenotype.

John Ellis has long urged protein chemists to conduct their experiments under conditions closer to those prevailing in the cell. This is, of course, what the great Hans Krebs argued as early as 1962. Anfinsen’s experiments could not have been representative of what was taking place in the cell. Little progress in elucidating the structure of proteins in the cellular environment has been made.

Genomic Instability

In 1984, Barbara McClintock noted

There are “shocks” that the genome must face repeatedly, and for which it is prepared to respond with a programmed manner. Examples are the “heat shock” responses in eukaryotic organisms and the “SOS” responses in bacteria. … But there are also responses of genomes to unanticipated challenges that are not so precisely programmed. The genome is unprepared for these shocks. Nevertheless they are sensed, and the genome responds in a discernable but initially unforeseen manner.

James Shapiro, a student of McClintock, has also argued the case for the cell being able to modify its genome, at all scales, from point mutations to major chromosomal rearrangements and whole genome duplications. Suppose that as a result of cellular stress a specific protein cannot function within its required range. The attractor collapses and the system makes an arbitrary transition to a variant attractor. Because of the high dimensionality of the system, this phenotypic transition is irreversible. Once displaced from its initial attractor, the new phenotype is more prone to attractor collapse and, thus, further phenotypic transitions.

Genomic instability is irreversible. In germ cells, it can be transmitted to future generations; in somatic cells, it is capable of inducing the same effects as mutations. The cell regulates itself, often by acting on its own DNA. This regulation represents a violation of the central dogma. Circular causality is an essential feature of a living organism and is one of the features that distinguish what is alive from what is not.

The cellular phenotype is an emergent property of the cell. Emergence has proved a controversial concept, but simple chemical reactions provide examples. A mixture of nitrogen and hydrogen molecules at room temperature is clearly different from the product of the energy-induced reaction that forms ammonia.

In the same way, the consequences of introducing or modifying genes may not be predictable or reversible given the highly interactive nature of the proteins engaged in the attractor and the non-holonomic nature of the cell phenotype.

The Key to Life

Proteins and protein chemistry are, therefore, central to the functioning of organisms. Proteins are a multifunctional class of compounds of nearly unlimited variety; their properties can be modulated by the environment. Their chemistry takes place largely in the cytoplasm. In the machine cell model, chemical regulation is provided through a gene regulatory network.

There are several empirical problems with this paradigm. The cytoplasm of eukaryotic cells houses numerous partially-folded proteins that are fully functional when induced to fold. In 1890, the German chemist Emil Fischer introduced the lock-and-key concept to explain the specificity of enzymes. This was adapted to the machine model of the cell, an enzyme uniquely recognizing a DNA binding site and triggering the transcription of a specific gene sequence.

Very little is known about the structure of proteins in the crowded environment of the cytoplasm. Two processes must be involved: self-organization and computation.

Self-organization occurs when the entropy generated by free energy dissipation appears as order rather than disorder. How a system behaves in this respect depends on context. Consider the flocking of birds. Here, a large numbers of birds behave in an orchestrated way. Flocking can be described from the outside by the specific rules of engagement followed by each individual. It is doubtful that any of the birds are calculating their position by an appeal to external rules of engagement. In all probability, adopting a specific position relative to other birds is the most energy-efficient way to fly. The birds are slip streaming.

Either these rules, or the non-linear dynamics of the system, create order out of potential disorder. Similarly, one can interpret the protein interaction maps that have been constructed from cell lysates as systems in which proteins behave according to a set of rules.

Some proteins catalyze reactions, but many, as Dennis Bray has observed, govern the transfer and processing of information.

Because of their high degree of interconnection, systems of interacting proteins act as neural networks trained by evolution to respond appropriately to patterns of extracellular stimuli.

Even primitive microbes exhibit purposeful behavior, such as quorum sensing, chemotaxis, and phototaxis. Consider the slime mould Physarum polycephalum grown under warm, humid conditions. The tips show a marked reduction in growth when the temperature is lowered and the humidity reduced. Having reduced their growth under these conditions, the plasmodia continued to reduce their growth in their absence. Other experiments with the mould strongly suggest the ability to trade off risk for benefit. Even more remarkable are the army ants, Eciton, which can form living bridges over obstacles that hinder foraging ants. These bridges reduce the number of army ants available for foraging, but under experimental conditions, army ants have been observed to move their bridges in order to optimize foraging.

František Baluška cites other examples of neurobiological phenomena across the microbial world and in plants that can only be attributed to information processing. He makes the case that consciousness and cognition are undeniable and essential features of life. And, whatever else they may be, attractors are also computational units of the cell.

Dynamical versus Machine Models

Is there an empirical test to discriminate unequivocally between the dynamic and machine cell models? The answer is probably not. However, so far it has not proved possible to explain genomic instability in terms of molecular genetics; inheritance of genomic instability is non-Mendelian. This is a strong argument against the machine cell model.

Malignant tissue exhibits both genomic instability and mutations. The same is true of cells in atherosclerotic tissue. Disease endpoints provide few clues about their origins. On the other hand, a number of hereditary conditions associated with radiation exposure can definitely be attributed to mutations. Radiation would appear capable of damaging cells by inducing both genomic instability and mutations.

In 1974, Richard Lewontin pointed to a paradox that has been inherent in experimental genetics since Mendel’s time: in terms of traits, what is interesting is not measurable, and what is measurable is not interesting. Genetics is based on measurements of well-defined traits, like flower color, but geneticists have tended to ignore more complex traits, such as those emerging from several interacting proteins.

Is the success of molecular genetics based on an unwarranted generalization of a series of special cases?

Genomic instability is induced by radiation much more effectively than mutations, and at much lower doses. An enzyme is not an ordinary chemical, Rosen correctly observed. Much of the structure of a protein forms a scaffold, which holds a few critical amino acids in a specific formation. Most amino acid substitutions in the scaffold are unlikely to affect the protein’s activity. The cell is refractory to mutations.

Suppose that a gene codes for a specific peptide; the peptide then folds to a protein governing a particular trait. A mutation rendering the protein inactive, the mutation and the trait find themselves associated, but not necessarily causally. Consider again Mendel’s pea plants. In the purple-flowered variety, a transcription factor switches on the expression of anthrocyanin. A single base substitution that renders the transcription factor inactive produces the white-flowered variety. All that can be said is that that protein no longer has the information necessary to induce the color.

Diseases such as cancer, schizophrenia, and type II diabetes are usually regarded as due either to environmental causes or faulty genes. If they are heritable, the assumption is that they are genetic. Since 2001, with the completion of the sequencing of the human genome, it has been possible to test the latter hypothesis.

It has comprehensively failed.

Even before 2001, identical twin studies showed that common cancers have a minimal genetic component. More recently, the results of a very large study of schizophrenia patients demonstrated that, at best, less than four per cent of the disease risk is genetic. Kenneth Kendler, reviewing thirty years of research, has concluded that “efforts to ground a categorical biomedical model of schizophrenia in Mendelian genetics have failed.”

If the cell is treated as a complex system with a quasi-stable phenotype, it is clear that genomic instability and not genetic change underpins most environmentally induced disease. Treating it as genetic will not help to develop the “rational strategies for minimizing or preventing disease phenotypes altogether” that Francis Collins predicted.

The Origin of Life

There are two theories about the origin of life: replication-first or metabolism-first. The replication-first hypothesis, which invokes an RNA world, is the more widely accepted. RNA has, like DNA, the capacity to store sequence information, but it can also exhibit catalytic activity, thus behaving like a protein. The metabolism-first is often dismissed because proteins are necessary for transcription from DNA and DNA is necessary for the existence of proteins. For this reason, the origin of life is often regarded as a chicken and egg problem.

Through the chemical polymerization of small molecules, just possibly, proto-life evolved in oily droplets suspended in the oceans. I suggest the protein-only proto-life preceded life as we now know it. Due to stress on droplet membranes, droplets could divide but not replicate.

The adult tardigrade, a small animal whose somatic cells do not divide after hatching, so rendering its DNA inactive, has extraordinary resistance to environmental stress, including ionizing radiation, and for practical purposes can be regarded as a protein-only multicellular organism.

Protein-only proto-life is viable.

At a later stage, amino acid sequences might have been read back into RNA and then DNA. A plausible mechanism for reverse translation has been proposed. Reverse transcriptase is able to convert mRNA to DNA. Reverse translation and reverse transcription are legitimate cellular processes.

Building on the work of Mendel and Darwin, Ronald Fisher published The Genetical Theory of Natural Selection in 1930. Fisher’s first law of natural selection was that the rate of increase of fitness of any organism is proportional to its genetic variance. This law, operating on Mendel’s particulate units of inheritance, is the foundation of the modern evolutionary synthesis. Speciation occurs when breeding populations adapt to environmental change over many generations, or new mutations arise, introducing new variation.

A population of Escherichia coli, subject to a glucose nutrient that limited growth, was regularly sampled over 40,000 cell generations to assess relative fitness. Mutation rates were determined by DNA sequencing. Up to 20,000 generations, mutations increased linearly, at the rate of about two per 1,000 generations. Relative fitness, on the other hand, rose dramatically in the first 1,000 generations to some 80% of the fitness recovered at 20,000 generations. Thereafter it increased linearly at a much reduced rate of 1.5% per 1000 generations. Beyond 20,000 generations, the cells became hypermutable.

This experimental result is not explicable in terms of the modern evolutionary synthesis.

Testing to see how a bacterium responds to previously un-encountered environmental conditions, Akiko Kashiwagi et al. equipped an E. coli bacterium with a plasmid containing two operons enabling the cell to exploit two nutrient sources. Each operon suppressed the other if deployed. Fluorescent assays indicated which operon was active. When confronted by a major environmental change, the cell, the authors assume, has to find and adopt a new signal transduction route using natural selection. In this case, the bacterium was given the solution that natural selection might have found, but no signal transduction route. On switching the bacteria from one nutrient source to the other, metabolic activity initially dropped dramatically, but after an hour or so increased again, signaling that the alternative nutrient was being metabolized. The authors concluded that the bacterium was able to select between attractors each adapted to the appropriate nutrient conditions much more rapidly than conventional theory would predict.

There is no role for natural selection here.

For at least its first two billion years, life consisted of prokaryotes, with a very limited capability to form multicellular structures. These life forms had qualities of the kind generally attributable to neurological activity. Without them, the organisms would have been helpless in a hostile environment. The same must have been true for the preceding proto-life forms.

Simply encoding peptide sequences in DNA would not have been enough to bring about such a profound property. Neurological activity is a product of protein chemistry. It is notable that all life forms can be rendered unconscious by the same anesthetics that work on humans.

Life Without Genes

Mauno Rönkkö has developed a virtual ecosystem based on information-bearing particles. Each particle—whether a speck of the soil, grass, rain, a worm or beetle, or a scent emitted by grass—carries information that enables it to interact with other particles in highly specific time-dependent ways. Running the full sequence of particle interactions animates the organisms in the ecosystem. In principle, cells in multicellular organisms could carry such information in their phenotypes. That information specifies associations with other cells, and from it emerges the organism’s form. Diversity in biological form can, therefore, be seen as a result of variation in cellular phenotype, derived from protein chemistry.

The evolution of function, according to the modern evolutionary synthesis, has been controversial. Richard Dawkins has argued that no matter how improbable a trait, there are gradual changes leading up to it. In the dynamical model, gradualism is not a constraint. Genomic instability is a process in which the cell can experiment with diverse traits already inherent in its peptides, and which can be modified by spontaneous mutation as well as by the cellular phenotype.

Natural selection is based on the ability of an organism to extract free energy from its environment. An acquired ability to detect light or sound will preferentially be passed to future generations if these properties increase how efficiently energy is extracted. Thus, a genomically-unstable organism can improve an imperfect function by seeking variant protein chemistry within its own state space. The Kashiwagi experiment and the long term culture of E. coli provide evidence that this is so.

Since the publication of On the Origin of Species, many distinguished biologists have proposed mechanisms for non-gradual evolution. Gould and Niles Eldredge have proposed that evolution is characterized by long periods of equilibrium punctuated by relatively short periods of rapid phenotypic change. Gould was influenced by the discovery of a diverse range of fossil forms in the Burgess Shale in Canada, formed some 505 million years ago in the Cambrian period. Some of the basic forms that exist today, such as bilateralia, are present in those fossils; what is more, the Burgess Shale preserved the fossils of soft-bodied organisms as well.

Punctuations in the fossil record might represent periods of genomic instability initiated by stress on an organism poorly adapted to a changing environment. The organism might have lost a nutrient source, the environment may have changed for the worse, or a new predator may have appeared. Genomic instability in the punctuation phase of an organism’s evolution could thus be the basis of speciation.

Development has traditionally been explained as the expression of specific genes that have acquired positional information. The origin of this information is not completely clear, but may be related to gradients of certain chemical morphogens. Morphogen concentrations in the cell switch the differentiation processes on or off, and ultimately give rise to the many different cell types.

In the dynamical cell model, development is regulated by cellular phenotypes. Alan Turing outlined the mathematical basis for development through self-organization in terms of a reaction–diffusion model. In Turing’s model, cells release ligands, or morphogens, that bind to receptors on other cells, in order to enhance or repress their own release. Testing this model has proved difficult. Little is known of the morphogens involved. But it has been verified in an artificial cell system comprised of emulsion droplets that represent cells.

Consider now the ecosystem. All organisms evolve in the context of an ecosystem and each influences the other. Evolution is not a passive process. In the words of Annila, “everything depends on everything else,” and outcomes are therefore non-linear.

Evolution is often seen as a struggle for survival among species. Darwin’s third chapter in the Origin is, after all, entitled “Struggle for Existence.” But if a stable ecosystem is an attractor state, as I would propose, predation cannot be on the only guarantor of its stability. A steady state between competitive and cooperative behavior is inescapable. Cooperation in nature is sometimes called symbiosis. African acacias, for example, are able to produce tannin. Tannin is toxic to mammals such as kudus and giraffes. Overgrazed acacia trees release ethylene, a plant hormone that stimulates trees downwind to produce protective tannin.

The South African bird, the honeyguide, seems to cooperate with other species by showing them the location of bee colonies. Once the nest is broken open and the honey retrieved, the honeyguide can feed on the exposed beeswax. Beeswax is a potent free energy source, but honeyguides are almost unique in being able to metabolize it.

According to Claire Spottiswoode, the honeyguide is also a highly virulent brood parasite. Honeyguide chicks are reared by a species that neither cooperates with partners nor consumes beeswax. Spottiswoode questions whether the chicks’ extreme violence best serves their interests. Perhaps the cooperative behavior that makes beeswax available in the ecosystem was a relatively late evolutionary development. The ability to utilize beeswax may have been an even later development. Not every trait necessarily has an explanation in terms of evolutionary theory or the struggle for existence.

But there is another interesting issue here: how do honeyguide chicks know how to behave in partnership? How do they know that beeswax is good to eat? They apparently are not taught by their parents, who abandon them as soon as the egg is laid.

It is a puzzle to Spottiswoode as well.

Conclusion

The concept of the gene as the material element embodied in chromosomes that causes the cellular phenotype, regulates the cell, and constitutes Mendel’s units of inheritance dates back to the mid-1920s, and research led by Thomas Hunt Morgan. At the same time, Hermann Muller showed that X-rays could mutate fruit fly genes:

It has been found quite conclusively that treatment of the sperm with relatively heavy doses of X-rays induces the occurrence of true “gene mutations” in a high proportion of the treated germ cells.

According to Jan Sapp, by the end of the 1920s, Muller and Morgan together had ensured the institutional dominance of genetics based on the governance of the cell by genes residing in the nucleus. Fisher published his theory of natural selection in 1930. At the same time, Bénard had demonstrated directly that increasing entropy could appear as order in an open system, and Alexander Oparin had published his proposal for a metabolism-first origin of life.

When the structure of DNA was unraveled and information in the form of a base sequence code revealed, it was but a short and apparently irresistible step to the conclusion that genes were DNA base sequences. The sequencing of the human genome has revealed the failure of the strategy launched nearly 100 years ago by Morgan and Muller; the majority of common heritable physical diseases cannot be accounted for in terms of genetic variance.

The sequence hypothesis and the central dogma, were, as Crick admitted in 1970, brash hypotheses. The uncritical acceptance of these principles has been detrimental to biology. The infatuation with DNA has obscured the fact that there are deep, unexplored issues in protein chemistry: they need the attention of curious and innovative minds.