What is Life?:How chemistry becomes biology

by Pross, Addy

  A generation later Jacques Monod, the Nobel biologist, in his classic 1971 monograph Chance and Necessity,10 lucidly reaffirmed the existence of a deep physics–biology divide, a divide only widened by the scientific revolution. The main issue that troubled Monod was life’s teleonomic nature. The very existence of that teleonomic character appeared to violate one of the fundamental principles of modern science—the objectivity of nature. Monod summarized the problem as follows:

  Here therefore, at least in appearance, lies a profound epistemological contradiction. In fact the central problem of biology lies with this very contradiction, which, if it is only apparent, must be resolved; or else proven to be utterly insoluble, if that should indeed turn out to be the case.

  Simply put, how could function and purpose have emerged from an objective universe devoid of function and purpose? So though Aristotelian teleology had been vanquished by the new scientific order, its elimination left a troublesome vacuum. The scientific reality of teleonomy, so evident in every facet of the biological world, was undeniable. No cosmic implications there, just down-to-earth biological empiricism. But what is the source of this teleonomic character? How could purpose of any kind emerge from an objective universe? The conclusion seems inescapable: understanding life will require that we understand teleonomy—the two are necessarily and inexorably linked. But there is a positive aspect to this analysis. If we are able to explain the physical basis of teleonomy, it might provide mechanistic insight into the means by which life itself emerged. We will argue for such a connection in chapters 7and 8.

  In retrospect one might be tempted to say that part of the difficulty that physicists, such as Bohr and Schrödinger, had in addressing the life problem lay with the fact that the problem of what is life and how it emerged is fundamentally a chemical problem. After all, both the processes that govern the function of living systems, as well as the ones that presumably led to the emergence of living systems from inanimate matter, primarily take place at the scientific level of enquiry we call chemistry. But if one might consider that ignorance with regard to the chemical mechanisms of life was the missing element needed to properly address Schrödinger’s question, the dramatic developments within molecular biology over the half-century following Schrödinger’s work proved otherwise. Watson and Crick’s 1953 landmark DNA study11 signalled the beginnings of a true revolution in our understanding of the cell-based machinery, the machinery of life. Major discoveries quickly followed—the mechanisms of DNA replication, protein synthesis, energy transduction, and central metabolic cycles, to name just a few. Truly dramatic advances in our understanding of many of the molecular mechanisms of life took place in rapid succession. Yet, paradoxically, our digging deeper and deeper into the mechanisms of life did not seem to lead us any closer to being able to address Schrödinger’s basic ‘what is life’ question, or the related question—how did life emerge? In fact, in 1974, twenty years after the discovery of DNA, Karl Popper, the iconic philosopher of science, supported the Bohr–Schrödinger view with his assertion that the origin of life problem was ‘an impenetrable barrier to science and a residue to all attempts to reduce biology to chemistry and physics’.12 And the very same Francis Crick of DNA fame, in a 1981 text, Life Itself considered the emergence of life so miraculous an event that he even entertained the possibility of ‘directed panspermia’, the extreme idea that life on earth originated from outer space by the deliberate seeding of the earth by some alien life form!13

  The conclusion is quite striking. In the broadest sense we have made surprisingly little progress regarding the ‘what is life’ question since Charles Darwin. Yes, we now know that all life is cell based, that genetic information is coded in the DNA molecule, that the proteins of life so critical to all of life’s functionality are expressed through a universal code that relates the DNA sequence to particular amino acids, that there is a universal energy storage facility based on the ATP molecule. But that detailed molecular understanding, of enormous significance in its own right, has only served to substantiate Darwin’s original claim—that all life is derived from some early common ancestor, that life is one thing. Darwin, of course, was lacking the plethora of mechanistic details that modern molecular biology has generously bestowed on us, but the belief in the unity of life, the insight that all life is related through physical law, was the essence of his contribution and the basis of the Darwinian revolution. Quite remarkably then, the molecular insights showered upon us by sixty years of extraordinary discoveries in molecular biology do not seem to have brought us any closer to resolving the ‘what is life’ question. Yes, as we have already noted, we can see many, many trees in the forest of life, but the view of the forest itself remains frustratingly obscure.

  Defining life

  Enormous effort has gone into attempts to define life over the years and we will end this section by considering some of the more recent ones. That brief survey will only serve to reaffirm how confused the life topic has become. Literally hundreds of definitions have been proposed over the years and there are few signs that the flow is abating. In Searching for the Definition and Origin of Life,14 Radu Popa lists forty definitions that were proposed in 2002 alone, the last full year before his book was published, suggesting that the process of defining life has within it streaks of autocatalytic character. And therein lies the problem—the plethora of different definitions of life, many incompatible, if not outright contradictory, make it clear there is some inherent difficulty with the ‘definition of life’ endeavour. Stepping back and reflecting on this expanding literature from a distance brings to mind the metaphor of a dog chasing its tail. Let’s consider several recent examples of life definitions arbitrarily chosen from Popa’s list to illustrate the problem first hand.

  Life is defined as a material system that can acquire, store, process, and use information to organize its activities.15

  Life is defined as a system of nucleic acid and protein polymerases with a constant supply of monomers, energy and protection.16

  Life is defined as a system capable of 1. self-organization; 2.self-replication; 3. evolution through mutation; 4. metabolism; and 5. concentrative encapsulation.17

  Life is simply a particular state of organized instability.18

  The above definitions, all relatively recent and all insightful in their own way, show almost no overlap. If all of the definitions hadn’t begun with the two words ‘life is…’, we would be excused for believing that these definitions were about totally different concepts. The first, by Freeman Dyson, focuses on information (software); the second, by Victor Kunin, on the nucleic acid and protein infrastructure (hardware) and the energy required to drive the process; the third, by Gustaf Arrhenius, attempts to specify several of the characteristics that living things share; while the fourth, by Remy Hennet, addresses life’s thermodynamic aspect. And had we been willing to list other definitions from the many others on offer, we would have been able to come up with more definitional variety. Life is indeed many things, yet none alone is life.

  Finally let us consider the most common and generally accepted definition of life, the one proposed within the NASA Exobiology Program in 1992, and generally referred to as the NASA definition of life: Life is a self-sustained chemical system capable of undergoing Darwinian evolution. Though attractive in some respects, it also suffers from certain deficiencies. The first might be considered a technical one. The NASA definition could be understood to refer to individual life forms, say, a bacterium, an elephant, or a human. However individual life forms cannot undergo evolution; they can only reproduce and die. It is only populations of living things that are able to undergo Darwinian evolution. But even ignoring that technical aspect, the definition remains problematic as it has obvious exceptions. A mule, the offspring from the mating of a horse and a donkey, is sterile, so it clearly cannot reproduce. That of course means that a population of mules cannot undergo Darwinian evolution, even though we all agree that mules are alive. The same go
es for solitary rabbits—unable to reproduce, yet very much alive. This criticism, based on mules and single rabbits, has been expressed quite frequently in recent years and through repetition seems to have lost some of its force. However familiarity should in no way undermine its relevance and validity. The criticism is soundly based and cannot be ignored. Like so many life definitions, it is too easy to cite exceptions. Invariably living things are either excluded from the various definitions or non-living things are improperly included in them.

  So how to proceed? In an insightful article published a decade ago, Carol Cleland, who teaches philosophy at the University of Colorado, and Christopher Chyba, a Princeton University astronomer, changed the very nature of the debate.19 They pointed out that attempting to define life before we understand what life is, is to put the cart before the horse. Seeking the definition of an entity that we do understand is problematic enough. Attempting to define an entity that we are still struggling to understand is futile. Based on the Cleland and Chyba argument, we can now identify the fundamental problem with the NASA definition. The NASA definition does not attempt to tell us what life is, but rather how we might recognize it. Just as water’s physical characteristics might help us determine if some liquid is water or not, the NASA definition may be able to inform us if something is alive by seeing whether it does something that living things typically do (undergo Darwinian evolution). Cleland and Chyba claim that what is needed is not a definition of life, but a comprehensive theory of life. We will describe our attempts in that direction in the final two chapters.

  To sum up, this brief historical survey has illustrated the confusion that the life issue has generated over the centuries right through to the present day, as well as some of the reasons that the long-standing ‘what is life’ riddle has remained unresolved. Until the deep conceptual chasm that continues to separate living and non-living is bridged, until the two sciences—physics and biology—can merge naturally, the nature of life, and hence man’s place in the universe, will continue to remain gnawingly uncertain.

  3

  Understanding ‘Understanding’

  The previous chapter indicated that we are still lacking a theory of life, a theory that will enable us to understand what life is and how it emerged, that despite the recent detailed insights into life’s mechanism, something central is missing in our understanding of the life phenomenon. But what exactly do we mean by the term ‘understand’? When addressing most day-to-day questions, there seems to be no need to explain the term—it is self-evident. But when addressing the life question, the issue turns out to be more complex. What we mean by ‘understanding’ goes to the very heart of the scientific method and beyond, forcing us to at least briefly address basic philosophical questions that have weighed on mankind for over 2,000 years.

  In the scientific world we strive to achieve understanding of phenomena in the world around us through application of the scientific method. The method is well known so we will just address those aspects that will be relevant to our analysis. At the very heart of the scientific method is the process of induction, a way of reasoning whose roots can be traced back to ancient Greek philosophy, but was raised to scientific prominence with its formal description by Francis Bacon, one of the fathers of the modern scientific revolution. This may all sound quite formal, even esoteric. But the essence of the methodology is actually very simple. So simple in fact that even young children intuitively understand it and (unconsciously) apply it quite routinely. Indeed, I would argue that the essence of all scientific endeavour, stripped of its many elaborations, trimmings, and jargon, is nothing more than the successful application of the inductive method. It is the successful application of the inductive method that forms the basis for what we term ‘understanding’.

  Inductive reasoning involves the reaching of general conclusions from a set of empirically obtained facts—what one might simplistically term pattern recognition. Consider a very simple example: the falling of apples. Indeed without exception, all apples do fall, so one can reasonably formulate a general rule of nature: ‘apples fall’. However, even the less observant amongst us will have noticed that it is not just apples that fall, but that all material objects display that same falling characteristic. Accordingly, the limited ‘apples fall’ rule can be further extended to an ‘all objects fall’ rule, though the behaviour of certain objects, such as hot-air balloons, requires the pattern to be elaborated further to account for these apparent exceptions.

  Needless to say the phenomenon of falling objects is so obvious that even a small child grasps its essence very quickly and in doing so has applied the inductive method at a fundamental level. When a child drops some object and it falls to the ground, it doesn’t take too long before the child ‘understands’ that the singular event of the falling object manifests the general ‘objects fall’ rule. So even young children, with no knowledge of induction or the scientific method, intuitively apply the principles of induction to better understand and adapt to the world around them. Thomas Macaulay, a British poet and historian, pointed this out already over 150 years ago with hiscomment:

  The inductive method has been practised ever since the beginning of the world by every human being. It is constantly practised by the most ignorant clown, by the most thoughtless schoolboy, by the very child at the breast. That method leads the clown to the conclusion that if he sows barley he shall not reap wheat. By that method the schoolboy learns that a cloudy day is the best for catching trout. The very infant, we imagine, is led by induction to expect milk from his mother or nurse, and none from his father.20

  In fact all cognitive beings, human and non-humans alike, apply the method routinely, whether consciously or subconsciously, in a process that has been deeply engrained in us all by evolution. Yes, your pet dog, despite his lack of familiarity with Bacon’s treatise, or epistemology in general, also routinely applies the inductive method. Just watch his reaction when you begin to open a can of his favourite dog food. Based on the pattern he has learnt to recognize over time, he fully understands that he is about to get fed. It is that evolutionarily acquired ability to gather empirical information and to recognize patterns within that gathered information which provides cognitive beings with the ability to respond to the external world in a beneficial manner (from the point of view of the cognitive being). Both your dog, a 2-year-old child, and the scientist in the lab are applying the same inductive methodology, the difference only being in the level of sophistication of the patterns that are recognized.

  As mentioned above, small children recognize the ‘objects fall’ rule. But it took the genius of an Isaac Newton to recognize a much broader pattern, one which links the behaviour of falling apples to the orbits of celestial bodies, such as the moon and the earth—a law of gravity that describes the interaction of physical bodies in precise mathematical terms. So when we say we understand why apples fall and why the moon rotates around the earth, it is because both these specific events exemplify a more general pattern, one that governs the behaviour of all physical bodies. But what that means, however, is that there is no absolute and deep understanding as to why apples fall. Gravity is just the name of the general pattern to which the falling apple event belongs.

  Ultimately all scientific explanations are inductive—they involve no more than the recognition of patterns and the association of the specific within the general. Broadly speaking the wider the generalization, i.e., the greater the number of empirical observations that are embraced by the generalization, the greater its predictive power and the more significant the generalization. Simplistically, that’s what modern physics is all about—seeking ever-general laws that underlie the workings of the universe, extending the pattern. So that is what Einstein’s special and general theories of relativity do—they extend and generalize the more limited Newtonian pattern. With his theory of relativity Einstein was able to place Newton’s gravitational force in a more general context, and in that sense it constituted an advance on t
he Newtonian description.

  According to Einstein, gravity is just the natural movement of objects through curved four-dimensional spacetime, thereby providing a more general basis for understanding a wide range of physical phenomena, including the behaviour of falling apples. And, of course, physicists are still at it, attempting to further generalize, with sophisticated formulations such as string theory and M-theory, constantly working toward the so-called final theory—the theory of everything, the ultimate pattern. Of course whether an ultimate pattern is achievable is another question, one that belongs within the realms of philosophy, not just science—a wonderful question in its own right, but one that goes well beyond the scope of this discussion.

  The role of mathematics in generating patterns is crucially important. The ability to express the pattern quantitatively through the language of mathematics greatly enhances the predictive power of the generalization and therefore its utility. Richard Feynman, the Nobel physicist, once compared the accuracy of quantum theories to the ability to measure the width of North America to an accuracy of one hair’s breadth. Now that’s a pattern we should take note of! Such predictive capabilities ensure that mathematics plays a central role in pattern formulation, though this is not to dismiss the value and utility of qualitative patterns. Let us not forget the revolutionary impact of Darwin’s ideas of natural selection and common descent, ideas that were entirely qualitative in their formulation yet continue to profoundly impact on man’s view of himself to this very day. To quote the aphorism attributed to Albert Einstein: Not everything that counts can be counted, and not everything that can be counted, counts.