Saturday, 27 October 2012

51. Biological Symbiosis and Evolution

Ironically the popular evolutionist’s view that organisms evolve by the accumulation of random mutation best describes the evolutionary process in bacteria. All of the larger, more familiar organisms originated by symbiont integration that led to permanent associations (Margulis and Sagan 2002).

Biological symbiosis means a prolonged living arrangement or physical association among members of two or more different species. Levels of partner integration in symbiosis may vary in intimacy; and integration may be behavioural, metabolic, of gene products, or 'genic'.

An example of symbiosis in action are the microbes that live in a special stomach of the cow, providing the enzymes for the digestion of cellulose. The cow, in turn, provides shelter and nutrition to the microbes. We say that the microbes are the 'symbionts' of the cow.

Biological cells are either prokaryotes or eukaryotes (cf. Part 43). Examples of prokaryotes are: E. coli; blue-green algae or cyanobacteria; and archaebacteria.

Eukaryotes can be divided into four kingdoms:

  • Protoctists (algae; amoebas; ciliates; slime moulds).
  • Fungi (moulds; yeasts; mushrooms).
  • Plants (mosses; ferns; flowering plants).
  • Animals (molluscs; arthropods; fish; mammals). 

The genealogical relationship of all living organisms has three main branches: bacteria, archaea, and eucarya. However, some authors distinguish just two branches, namely bacteria and eucarya, and subdivide bacteria into eubacteria and archaebacteria. The eubacteria and the archaea or archaebacteria are prokaryotes. The eucarya are eukaryotes.

Lynn Margulis is a major proponent of the idea that parasitism and symbiosis were major driving forces in the evolution of cellular complexity. She has been hammering home the point that the main components of eukaryotic cells have descended from independent living creatures which ‘attacked’ the cells from outside. In due course, the attackers and the host evolved a relationship of mutual dependence and benefit. In stages, the erstwhile invading organisms became first chronic parasites, then symbiotic partners, and finally an indispensable part of the host.

The mitochondria are symbionts in both plant and animal cells, as are chloroplasts in plant cells. The evidence for this is that the molecular structures of mitochondria and chloroplasts are indeed very close to certain bacteria.

The emergence of a new life form from such symbiosis is called 'symbiogenesis'.

Margulis marshalled evidence to argue that most of the big steps in cellular evolution were caused by parasites. And that nucleic acids were the oldest and the most successful cellular parasites.

Thus the classical viewpoint that speciation occurs, i.e. new species arise, only as a result of the cumulative effect of mutations etc., has been strongly contested by Margulis. According to Margulis and Sagan (2002), ‘No evidence in the vast literature of heredity change shows unambiguous evidence that random mutation itself, even with geographical isolation of populations, leads to speciation. Then how do new species come into being? How do cauliflowers descend from tiny, Mediterranean cabbagelike plants, or pigs from wild boars?’ Their answer is that species arise largely by the acquisition of entire genomes through symbiogenesis.

Margulis’s stance raised debate. Ernst Mayr wrote an appreciative foreword to the 2002 book by Margulis & Sagan. But the foreword also said this: ‘Speciation – the multiplication of species – and symbiogenesis are two independent, superimposed processes. There is no indication that any of the 10,000 species of birds or the 4,500 species of mammals originated by symbiogenesis.’ Contrast this with the statement of Rachel Nowak (2005): ‘Symbiosis has popped up so frequently during evolution that it is safe to say that it’s the rule, not the exception.’

In biology, studies of evolution are about tracking the changes of life through time. In particular, they are about tracking the origin of species. But what exactly is a species?

The morphological definition. Creatures belonging to a species look alike (dogs look like dogs).

The biological definition. Creatures belong to a species if they can mate and produce fertile offspring. This was introduced by zoologists, and also by botanists.

The phylogenetic definition. Groups of organisms considered to be all descended from the same ancestors are said to belong to the same species.

Margulis & Sagan (2002) rejected the biological and the phylogenetic definition, and suggested something which can accommodate only the morphological definition:

The symbiogenetic definition. 'If organism A belongs to the same species as organism B, then both are composed of the same set of integrated genomes, both qualitatively and quantitatively. All organisms that can be assigned to a unique species are products of symbiogenesis'.

Life originated with bacteria. Bacteria do not speciate. The idea of a species does not apply to them. Bacteria can pass genes back and forth. There is no fixed genome to define the species of any bacteria. Bacteria are prokaryotes.

The first eukaryote emerged by the symbiogenesis of two prokaryotes. The concept of a species can apply only to eukaryotes. It follows that the origin of species occurred long after the origin of life in the form of bacteria. Therefore, the species of all the larger organisms (protoctists, fungi, animals, plants) originated symbiogenetically in the beginning. Nucleated organisms emerged on Earth some 1.2 billion years ago.

Symbiosis can occur only if the arrangement is beneficial to all the partners involved. In a later post, when I shall give you a historical narrative of the various 'energy regimes' in the evolution of our ecosphere, I shall explain what benefits accrued to the partners when the eukaryotic cell evolved from its partner organisms.

There is no reason to believe that symbiogenesis is the only way in which new species can arise. It is a characteristic of complex systems that, often, small changes can have unexpectedly large consequences, including the emergence of new species. Effects of mutations can gradually build up to a stage wherein a sudden bifurcation occurs in phase space (cf. Part 30), and a new species arises. Speciation may well be an emergent phenomenon often. This contention of mine is in disagreement with the statement of Margulis & Sagan (2002) that 'intraspecific variation never seems to lead, by itself, to new species'.

Saturday, 20 October 2012

50. Darwinism and Neo-Darwinism

The main postulate in Darwin's theory of evolution was that a species evolves because natural selection acts on small inheritable variations in the members of the species (cf. Part 31).

But it was argued by his opponents that, since a species is also characterized by interbreeding, such small variations should get averaged away. Darwin had no answer to counter this because the actual mechanism of inheritance was not known at that time.

The answer in fact had been provided in 1865 (i.e. during the lifetime of Darwin, but apparently unknown to him) by the work of Gregor Mendel, the founder of the subject of genetics. We now know that the 'genotype' or the genome of an organism is its genetic blueprint, and is present in the nucleus of every cell of the organism. The 'phenotype', on the other hand, is the end-product (the organism) which emerges through execution of the instructions carried by the genotype. It is the phenotype that is subjected to the battle for survival and natural selection, but it is the genotype which carries the accumulated evolutionary benefits to succeeding generations. The phenotypes compete, and the fittest among them have a higher chance of exchanging genes among themselves.

Mendel’s laws of genetics were rediscovered independently by quite a few workers. One of them was the Dutch botanist Hugo de Vries, who not only rediscovered Mendel’s laws for the inheritance of 'dominant' (or expressed)
and 'recessive' (or suppressed) characteristics, but also discovered genetic mutations. These were sudden (unexplained) changes of form which were inherited by the offspring.

The present, post-Darwinian, picture is that the inherited characteristics of the progeny are carried by genes. In sexually reproducing organisms, each parent provides one complete set of genes to the offspring. Genes are portions of molecules of DNA, and their specificity is governed by the sequences in which their four bases (adenine (A), thymine (T), guanine (G), and cytosine (C)) are arranged. The double-helix structure of DNA, together with the restriction on the pairing of bases comprising the DNA molecule to only A-T and G-C, provides a mechanism for the exact replication of DNA molecules. And the DNA sequences on genes determine the sequence of amino acids in the specific proteins created by the live organism.

Genes programme embryos to develop into adults with certain characteristics, and these characteristics are not entirely identical among the individuals in the population. Genes of individuals with characteristics that enable them to reproduce successfully tend to survive in the gene pool, at the expense of genes that tend to fail. This feature of natural selection at the gene level has consequences which become manifest at the organism or phenotype level. Cumulative natural selection is NOT a random process.

If like begets like (through inheritance of characteristics), by what mechanism do slight differences arise in the gene pool of successive generations so that the species evolves towards evolutionary novelty? One mechanism is that of mutations. Mutations, brought about by radiation or by chemicals in the environment, or by any other agents causing replication errors, change the sequence of the four bases in the DNA molecules comprising the genes. Most mutations are deleterious and get weeded out by natural-selection processes, but those which happen to be beneficial to the population have a selection advantage and get further propagated in the population.

If all living beings have the same or only a few ancestors, how have the various species arisen? The Darwinistic answer lies in isolation and branching, aided by evolution. Migrations of populations also play a role in the evolutionary development of species. If there are barriers to interbreeding, geographical or otherwise, single populations can branch and evolve into distinct species over long enough periods of time. Each such branching event is a 'speciation': A population accidentally separates into two, and they evolve independently. When separate evolution has reached a stage that no interbreeding is possible even when there is no longer any geographical or other barrier, a new species is said to have originated.

The term neo-Darwinism essentially connotes a modification of the original ideas of Darwin in the light of later knowledge about the mechanism of transmittal of genetic information from one generation to the next. Margulis and Sagan (2002), who disagreed with this neo-Darwinistic view of the origin of species (I shall describe their work in the next post), summed up neo-Darwinism as follows:

‘All organisms derive from common ancestors by natural selection. Random mutations (heritable changes) appear in the genes, the DNA of organisms, and the best “mutants” (individuals bearing the mutations) in competition with the others, are naturally selected to survive and persist. The unsuited offspring die – they tend to be called “unfit” – with fitness, a technical term, referring to the relative numbers of offspring left by an individual to the next generation. The most fit, by definition, produce the largest number of offspring. The mutant variations then leave more offspring, and populations evolve; that is, they change through time. When the number of changes in the offspring accumulates to recognizable proportions, in geographically isolated populations, new species gradually emerge. When sufficient numbers of changes in offspring populations accumulate, higher (more inclusive) taxa gradually appear. Over geological periods of time new species and higher taxa (genera, families, orders, classes, phyla, and so on) are easily distinguished from their ancestors.’

As emphasized by Stuart Kauffman, evolution of biological complexity is determined by two factors: natural selection, and self-organization. Self-organization creates order in any complex system. Darwinian natural selection acts on this existing order and hones it further.

The phrase 'selfish gene' was introduced by Richard Dawkins: 'The most inspiring way of teaching evolution is to say that it's all about the genes. It's the genes that, for their own good, are manipulating the bodies they ride about in. The individual organism is a survival machine for its genes.'

Saturday, 13 October 2012

49. Kauffman's Work on Genetic Regulatory Networks

A genetic regulatory network (GRN) in a cell is a set of DNA segments that interact with one another and govern the rates at which the genes in the network are transcribed into mRNA. As discussed in Part 48, GRNs in single-celled organisms like E. coli respond to external stimuli to do what is good for the organism. In multicellular organisms the GRNs play other roles also, like cell differentiation (there are some 285 different types of cells in the human body).

A variety of models have been developed for understanding the GRNs. I shall focus on a model based on random Boolean networks (RBNs), on which pioneering work was done by Stuart Kauffman.

In Kauffman's RBN model a gene (represented as a node of the network) was modelled as a binary device (like an electric bulb which is either 'on' or 'off'), the whole network having N such nodes. Each gene or node was modelled as receiving K inputs (KN) from randomly chosen ‘controlling’ genes or nodes, and also receiving one random ‘update’ function for its K inputs. The update function prescribed the state of the gene in the next time step, given its state in the current time step, and was chosen according to some probability-distribution function. By varying N and K for these RBNs, the behaviour of a variety of such finite sequential switching 'automata' could be investigated. At any time step, each gene or node had a value 1 or 0, and the network was a collection of these 1s and 0s, representing the ‘state’ of the network. This pattern of 1s and 0s served as the input, determining the pattern for the next time step of the gene.

The RBN has 2N possible states; i.e. it has a finite number of states. This finiteness, coupled with the fact that the modelled dynamics is deterministic, implies that, as the RBN proceeds through a sequence of states, it must eventually return to a pattern it had at some earlier time step, and from then on it must repeat the same pattern-sequence periodically. That is, it must be trapped in a re-entrant cycle of states, or an attractor in phase space. Each such state cycle or attractor represents a distinct temporal mode of behaviour of the net, and was equated by Kauffman with a distinct cell type (kidney, liver, etc.). Cell types differ only in the pattern of gene activity; they all carry the same genome.

Kauffman focussed his attention on ‘critical’ RBNs. These lie at the edge of chaos, i.e. at the boundary between frozen networks and chaotic networks. Frozen networks have very short attractors or cycle lengths. And chaotic networks have large-sized attractors that may include a substantial portion of the phase space. To quote Kauffman:

Let’s talk about networks as a model of the genetic regulatory system. My claim is that sparsely connected networks in the ordered regime, but not too far from the edge (of chaos) do a pretty good job of fitting lots of features about real embryonic development, and real cell types, and real cell differentiation. And insofar as that’s true, then it is a good guess that a billion years of evolution has in fact tuned real cell types to be near the edge of chaos. So that’s very powerful evidence that there must be something good about the edge of chaos. So let’s say the phase transition is the place to be for complex computation. Then the second assertion is something like ‘Mutation and selection will get you there.’
Thus Jacob & Monod’s cell types, distinguished from one another by the distinct and stable network patterns of gene activity, were interpreted by Kauffman as represented by different attractors in phase space. For K = 1 and for K = N the length of the attractor cycles is very large. But for K = 2, i.e. when there are two inputs per gene, the lengths of the cycles are very small, roughly scaling as ~√N for critical networks. For example, for N = 1000, i.e. for 21000 possible states of the network, the modelled genome was found to cycle typically among just 30 time steps, a remarkable result indeed.

Kauffman's work demonstrated that highly ordered dynamical behaviour is typical even for randomly constructed genetic networks getting just a few inputs per component. This implied that homeostasis in living complex systems is a direct consequence of the high molecular specificity among the macromolecules involved. Similarly, cell differentiation reflects the capacity of complex adaptive systems to behave in several distinct, highly localized ways.

Kauffman’s work established that complex genetic networks could come into being by spontaneous self-organization, without the need for slow evolution by trial and error. After all, the whole thing had to be there together, and not partially, to function at all.

Kauffman also tackled the question of how extremely large molecules like RNA and DNA came into existence in the first place. In any case, even DNA requires the availability of certain protein molecules for its genetic role. Therefore, there must have been a mechanism which resulted in the spontaneous creation of protein molecules without the intervention of DNA or RNA.In other words, there must have been a non-random origin of life. There must have been another way, independent of the need to involve DNA molecules, for self-reproducing molecular systems to have got started. Kauffman carried Melvin Calvin’s (1969) idea of autocatalytic reactions much further to explain how this could happen. In Kauffman’s model, life originated before the advent of RNA or DNA. And his network model could incorporate features like reproduction, as also competition and cooperation for survival and evolution (including 'coevolution').

More on this in future posts.