Life: one possible abiogenesis narrative (with the help of Monod)

I spent my whole professional life researching healthcare technologies, but I never studied current theories of abiogenesis, the natural process by which life arises from non-living matter, such as simple organic compounds. 

But while reading “Chance and Necessity: Essay on the Natural Philosophy of Modern Biology” by Jacques Monod, I became curious.  I read some stuff, bridged it with some personal narrative.

To be clear, we do not know how life appeared, and what follows is a mere narrative, with a limited scientific basis.

Let us imagine that a unicellular organism appears, but as a random event.  It can duplicate every day and dies after seven days.  After only 100 days, the population of organisms will be 10^30, which is roughly what the Earth's ecosphere can sustain.  But of course, this assumes that there is no selection pressure, e.g., that all organisms die of old age.  If we introduce a death rate of 50%, the population will never develop.  But as soon as the death rate goes below 50%, the population growth explodes.  With a death rate of just under 40%, we reach the ecosystem limit within one year.

My point is that once the first living organism appears (some authors call it LUCA, the Last Universal Common Ancestor), life is inevitable.  But what is life?  This is a particularly difficult question.  Probably a decent tentative answer is that LUCA had a boundary (e.g., a membrane) that separated it from the rest of the environment; a metabolism, which would enable it to capture and convert energy in the environment, to sustain all its functions, and to keep its internal entropy low; and to replicate into another organism with low loss of its information content.

I picture life as the eternal fight between order and chaos, where chaos is the thermodynamic inevitability of entropic death, and order is the persistence of this self-replicating stuff that fights the good fight to prevent chaos from changing itself.  And funny enough, life wins when it fails, mutations occur, and more resilient forms of life are pruned through natural selection.  So, in a way, the best friends of life are death and chaos.

Several abiogenesis hypotheses propose that life emerged on Earth more than 3.5 billion years ago from prebiotic chemistry: a set of chemical processes occurring before the existence of living organisms. In some scenarios, these reactions occurred in environments such as shallow ponds, hydrothermal systems, mineral surfaces, volcanic regions, or other chemically active settings, where simple molecules were exposed to energy sources, including sunlight, geothermal heat, electrical discharges, and chemical gradients.

Among the many elements available on the early Earth, a small group became especially central to life: carbon, hydrogen, nitrogen, oxygen, phosphorus, and sulphur, often abbreviated as CHNOPS. These elements form the backbone of most biological molecules. Other elements and ions, including calcium, magnesium, iron, nickel, zinc, and manganese, also became important in biological chemistry, especially as structural components or catalytic cofactors.

Experiments have shown that several key classes of biological molecules, or their precursors, can form under plausible prebiotic conditions. These include amino acids, sugars, lipid-like molecules, nucleobases, and nucleotide-related compounds. However, the transition from these simple compounds to self-sustaining, evolving chemical systems remains one of the most difficult questions in origin-of-life research.

One influential hypothesis is the RNA World. According to this idea, an early stage of life-like chemistry was dominated by RNA or RNA-like polymers. RNA is a polymer made of nucleotides. Each nucleotide contains a ribose sugar, a phosphate group, and one of four nitrogenous bases: adenine, uracil, cytosine, or guanine. RNA is especially interesting because it can both store information and catalyse chemical reactions. At some stage, RNA-like molecules may have become sufficiently abundant and stable for some folded forms to catalyse reactions, possibly including those that helped generate more RNA-like material.

At the same time, simple lipid-like molecules could have spontaneously assembled into vesicles: small membrane-bound compartments. If RNA-like molecules became trapped inside such vesicles, these structures would have resembled early protocells. These primitive compartments would not yet have been true modern cells, but they could have created local chemical environments in which useful molecules were retained, concentrated, and exposed to selection.

Over time, RNA molecules and short chains of amino acids may have begun to interact. These short amino-acid chains, called peptides, could have stabilised RNA structures and improved their catalytic efficiency. This stage is sometimes described as an RNA–peptide world. In such a system, molecular structures that were more stable, more efficient, or more easily replicated would have become more common. In this sense, a primitive form of natural selection could have acted before the existence of fully modern cells.

Eventually, longer peptides and then proteins appeared. Proteins are chemically more versatile than RNA and have become the dominant biological catalysts. Their emergence would have allowed increasingly reliable replication, more complex metabolism, and more efficient control of chemical reactions. The ancestors of ribosomes probably evolved gradually within this RNA–peptide context. Modern ribosomes still preserve a central catalytic role for RNA: the formation of peptide bonds is carried out by ribosomal RNA, not by protein. This strongly suggests that today’s translation machinery retains traces of an ancient RNA-based past.

DNA probably appeared later. Deoxyribonucleotides are structurally similar to ribonucleotides, but they contain deoxyribose instead of ribose, and DNA uses thymine instead of uracil. DNA is more chemically stable than RNA and is better suited to long-term information storage. Once protein enzymes had evolved, the conversion of ribonucleotides into deoxyribonucleotides could have enabled the emergence of DNA genomes. From that point onward, biological information could be stored more reliably in DNA, transcribed into RNA, and translated into proteins.

Long before the appearance of modern organisms, protocells therefore may have evolved into increasingly complex cellular systems containing genetic polymers, catalytic RNAs, proteins, primitive metabolic networks, and membrane-based energy-conservation mechanisms. ATP eventually became the main energy currency of cells, although the exact timing and nature of early ATP-producing systems, including ATP synthase, remain debated.

After a long period of early evolution, one lineage, or population of related lineages, gave rise to the Last Universal Common Ancestor, or LUCA. LUCA was not the first living organism. It was already a relatively advanced cellular system, with DNA, RNA, proteins, ribosomes, a genetic code, and complex metabolism. It is called “last universal” because all known organisms alive today — bacteria, archaea, and eukaryotes — descend from it. Life as we know it did not begin with LUCA. Rather, LUCA marks the deepest common root we can infer from living organisms today. The origin of life lies further back, in the long and still partly mysterious transition from prebiotic chemistry to evolving protocells.

Maxwell’s demon and the cost of control

In my research on how the central nervous system controls human movement, I stepped into the Uncontrolled Manifold hypothesis proposed by John Scholz and Gregor Schöner, and later popularised by Mark Latash.  I always explained this hypothesis to my students and coworkers by positing that controlling a quantity would entail a metabolic cost, and thus the parsimonious view of evolution led humans to keep control only of quantities that directly affect the motor goal. Control only what is necessary.

But I never had a true theoretical basis for this.  Recently, while reading “Chance and Necessity: Essay on the Natural Philosophy of Modern Biology” by Jacques Monod, I found something that could help. It is related to the so-called Maxwell’s demon.

Maxwell imagined a tiny being that could open and close a small door between two gas-filled containers. It lets only fast molecules pass one way, and only slow molecules pass the other way. This seems to create a temperature difference without doing work, decreasing entropy and apparently violating the second law of thermodynamics.

The modern resolution is this: the demon must measure the molecules’ speeds and use that information to decide when to open the door. The measurement itself can, in principle, be performed with very little cost, but the demon has finite memory. Sooner or later, it must erase the information it has collected in order to continue operating.

Here comes a long train of concepts that I cannot detail, as they are too complex.  In What is Life, Schrodinger proposes that living organisms produce negentropy, e.g. consume energy to keep their internal entropy low, at the cost of increasing the entropy of their environment. In 2009, Mahulikar & Herwig redefined thermodynamic negentropy as the specific entropy deficit of the dynamically ordered sub-system relative to its surroundings.

Shannon proposed that a Gaussian distribution has the highest entropy among all distributions with the same mean and variance (makes sense: if an event is totally random, it is normally distributed). He uses negentropy as the measure of distance, for a given distribution, from the normal one. 

In 1929, Leó Szilárd suggested that the apparent paradox of Maxwell’s demon experiment could be solved if one accepted that the demon's information about the molecule's velocity cost the same amount of entropy that was missing.  More specifically, the so-called Szilárd engine considers Maxwell's set-up, but with only a single gas particle in a box. If the demon knows which half of the box the particle is in (equivalent to a single bit of information), it can close a shutter between the two halves of the box, close a piston unopposed into the empty half of the box, and then extract kBTln2 joules of useful work if the shutter is opened again. The particle can then be left to expand isothermally back to its original equilibrium volume. In just the right circumstances, therefore, the possession of a single bit of Shannon information really does correspond to a reduction in the entropy of the physical system. The global entropy is not decreased, but information-to-free-energy conversion is possible.

In 1953, Léon Brillouin derived a general equation stating that changing the value of an information bit requires at least kBTln2 energy. This is the same energy that Leó Szilárd's engine produces in the idealised case. In his book, he further explored this problem, concluding that any cause of this bit-value change (measurement, a decision about a yes/no question, erasure, display, etc.) will require the same amount of energy.

In fact, one can generalise: any information that has a physical representation must somehow be embedded in the statistical mechanical degrees of freedom of a physical system. Thus, Rolf Landauer argued in 1961, if one were to imagine starting with those degrees of freedom in a thermalised state, there would be a real reduction in thermodynamic entropy if they were then reset to a known state. This can only be achieved under information-preserving microscopically deterministic dynamics if the uncertainty is somehow dumped somewhere else – i.e. if the entropy of the environment (or the non-information-bearing degrees of freedom) is increased by at least an equivalent amount, as required by the Second Law, by gaining an appropriate quantity of heat: specifically, kBTln2 of heat for every 1 bit of randomness erased.

On the other hand, Landauer argued, there is no thermodynamic objection to a logically reversible operation potentially being achieved in a physically reversible way in the system. It is only logically irreversible operations – for example, the erasing of a bit to a known state, or the merging of two computation paths – which must be accompanied by a corresponding entropy increase. When information is physical, all processing of its representations, i.e., generation, encoding, transmission, decoding, and interpretation, are natural processes in which entropy increases through the consumption of free energy.

Applied to the Maxwell's demon/Szilard engine scenario, this suggests that it might be possible to "read" the state of the particle into a computing apparatus with no entropy cost, but only if the apparatus has already been SET into a known state, rather than being in a thermalised state of uncertainty. To SET (or RESET) the apparatus into this state will cost all the entropy that can be saved by knowing the state of Szilard's particle.

I think all this provides the theoretical background to my postulate that control costs metabolic energy.