The Big Picture
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Schrödinger’s picture of living organisms maintaining their structural in-
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tegrity by using up free energy is impressively manifested in real- world biol-
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ogy. The sun sends us free energy, in the form of relatively high- energy
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visible- light photons. These are captured by plants and single- celled organ-
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isms that use photosynthesis to create ATP for themselves, as well as sugars
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and other edible compounds, which in turn store free energy that can be
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used by animals. This free energy is used to maintain order within the or-
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ganism, as well as allowing it to move and think and react, all of the things
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that living beings do that distinguish them from nonliving things. The so-
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lar energy we started with is gradually degraded along the way, turning into
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disordered energy in the form of heat. That energy is ultimately radiated
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back to the universe as relatively low- energy infrared photons. Long live the
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second law of thermodynamics.
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The basic ingredients in this story are familiar from the Core Theory:
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photons, electrons, and atomic nuclei. As far away as our everyday lives
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seem from the details of modern physics, understanding how we eat and
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breathe and live brings us face-to-face with the underlying particles and
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forces beneath it all.
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Spontaneous Organization
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Flemish chemist Jan Baptist van Helmont, working in the seventeenth
century, was one of the first scientists to understand that there were
gases other than air, and was even responsible for coining the term
“gas.” But he will always be best remembered for his recipes for creating
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living creatures. According to van Helmont, the way to create mice from
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nonliving materials is to place a soiled shirt inside an open vessel, along
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with some grains of wheat. After approximately twenty- one days, he wrote,
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the wheat will have been transformed into mice. If for some reason you
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wanted to make scorpions rather than mice, he recommended scratching a
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hole in a brick, filling the hole with basil, covering with another brick, and
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leaving them out in sunlight.
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If only it were that easy. I like to think that, if van Helmont had followed
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proper Bayesian reasoning, he would have been able to come up with plau-
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sible alternative hypotheses to explain the appearance of mice in his vessel
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with the soiled shirt. Once we move beyond vitalism, and understand that
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“life” is a label we attach to certain kinds of processes rather than a substance
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that inhabits matter and starts pushing it around, we begin to appreciate
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what an enormously complex and interconnected process it is. It’s one thing
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to see how living organisms can harness free energy to maintain themselves
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and move around. It’s quite another thing to understand how life ever got
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started. As of this writing we have more questions than answers.
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For a while there, it seemed like understanding the origin of life, or
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abiogenesis, wouldn’t be that difficult. Charles Darwin didn’t say that much
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about the problem in Origin of Species, but he briefly speculated that a
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“warm little pond” could have witnessed the formation of proteins, which
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might then “undergo still more complex changes.” Darwin didn’t know
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much about chemistry or molecular biology, but in a famous experiment in
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1952, Stanley Miller and Harold Urey took a flask full of some simple gases—
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hydrogen (H ), water (H O), ammonia (NH ), and methane (CH )— and
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zapped it with sparks. The idea was that these compounds may have been
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present in the atmosphere of the ancient Earth, and the sparks would simu-
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late the effects of lightning. With a fairly simple setup, and after running for
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just a week without any special tinkering, Miller and Urey found that their
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experiment had produced a number of different amino acids, organic com-
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pounds that play a crucial role in the chemistry of life.
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Today we don’t think that Miller and Urey were correctly modeling
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conditions on the early Earth. Their experiment nevertheless demonstrated
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a crucial biochemical fact: it’s not that hard to make amino acids. To make
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life, the next step would be to assemble proteins, which do the heavy lifting
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in terms of biological function— they move things around inside the body,
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catalyze useful reactions, and help cells communicate with one another.
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That turns out to be not so easy.
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While it is encouraging that the initial amino- acid step seems relatively
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straightforward, by now it has become clear that scientists are going to have to
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be a lot more clever if we are to understand how the steps proceeded after that.
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The study of the origin of life brings together biology, geology, chemis-
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try, atmospheric science, planetary science, mathematics, information the-
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ory, and physics. There are multiple promising ideas, not always compatible
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with one another. We can sketch out plausible ways life might have origi-
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nally arisen, and how that process fits into the rest of the
big picture.
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Let’s focus on three features that seem to be ubiquitous in life as we know it:
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1. Compartmentalization. Cells, the building blocks of living
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organisms, are bounded by membranes that separate their
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inner structure from the outside world.
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2. Metabolism. Living creatures take in free energy, and use it
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to maintain their form as well as performing actions.
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3. Replication with variation. Living beings create more of
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themselves, passing along information about their struc-
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ture. Small variations in that information enable Darwin-
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ian natural selection.
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There are certainly more aspects to life than this, but if we can account for
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these we will have made major progress in understanding how life got its start.
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Of these features, compartmentalization turns out to be relatively easy
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to understand. Inorganic materials, in appropriate environments, readily
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create membranes and differentiate themselves. When a system is far from
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equilibrium, these spontaneously formed structures can help harness free
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energy, in particular to enable metabolism and replication. The devil, need-
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less to say, is in the details.
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The appearance of cell membranes and other kinds of compartments is
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one example of the more general phenomenon of self- organization. That’s
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what we call it when a large system, consisting of many smaller subsystems,
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falls into orderly patterns of configuration or behavior, even though the
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subsystems all behave independently, and with no special goal in mind. The
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idea of self- organization has been fruitfully applied to phenomena as dispa-
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rate as the growth of computer networks, the appearance of stripes and
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spots on animal hides, the spread of cities, and the sudden formation of
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traffic jams. A classic example is swarming: in flocks of birds or schools of
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fish, each animal responds only to what its nearest neighbors are doing, but
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the result is an impressive display of what looks for all the world like highly
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choreographed behavior.
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Self- organization is everywhere. Let’s consider one particular example,
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to get a general flavor for the idea, before moving on to the specifics of cel-
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lular membranes. Someday, after all, we might want to understand the na-
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ture and origin of spontaneously formed membranes in biospheres other
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than the one here on Earth.
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In 1971, American economist Thomas Schelling proposed a simple
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model of segregation. One form would be racial segregation within cities,
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but the basic idea would work for a variety of differences, from linguistic
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communities to boys and girls choosing seats in an elementary school class-
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room. Schelling asked us to imagine a square grid with two different kinds
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of symbols, X’s and O’s, as well as a few empty spaces. Suppose that the X’s 252
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and O’s aren’t completely intolerant of each other, but they get a little un-
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comfortable if they feel surrounded by symbols of the opposite type. If a
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symbol is unhappy— if an X has too many O neighbors, for example— it
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will get up and move to a randomly selected empty space. That happens
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over and over again, until everybody is happy.
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Spontaneous segregation in the Schelling model. Initial condition on the left, final condi-17
tion on the right.
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You wouldn’t be surprised to see significant segregation if the symbols
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were very intolerant— if they were unhappy even having one or two neigh-
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bors of the other type, for example. Schelling showed that even a little bit of
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preference was enough to induce large- scale segregation. In the figure we’ve
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shown an example with 500 symbols, half X’s and half O’s, randomly distrib-24
uted on a grid with a few empty spaces. Imagine that a given symbol is un-
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happy if 70 percent or more of its neighbors are of the opposite type. That’s
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relatively tolerant; an O is fine with having as many as five X’s among eight 27
neighbors, and becomes unhappy only when there are six or more. In the
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initial configuration, only 17 percent of the symbols start out as unhappy.
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But that’s enough. Once we let the unhappy symbols pull up stakes and
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move to empty spots on the grid, and let that process continue until everyone
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is happy, what we’re left with is the arrangement on the right. Large swaths of
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segregated neighborhoods, separated by clearly demarcated boundaries.
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This large- scale order emerged purely as the result of localized, individ-
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ual decisions, not as the handiwork of some malicious central planner. And
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self- organization, not externally imposed or goal- driven. We could imagine
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individual molecules behaving the same way, and indeed they sometimes do.
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Oil and water separate from each other, and we’ll see that lipid molecules
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have definite preferences that help account for the origin of membranes in
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cellular life. Schelling shared the 2005 Nobel Prize in Economics with Rob-
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ert Aumann, primarily for his work in game theory and conflict behavior.
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One important point about Schelling’s theory is that the way we model
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the evolution of the system is not reversible. The dynamics are not “Laplac-
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ian”; information is not
conserved. It is therefore not a model of the real
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world at its most fundamental level. But it can be a perfectly good emergent
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description of coarse- grained dynamics, as long as the system as a whole is
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far from equilibrium. The process of an X or O noticing that it’s unhappy 13
and moving to a randomly chosen empty space is one that necessarily in-
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creases the entropy of the universe in the process. Information is lost, since
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many initial configurations could lead to the same final one. Entropy in-
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creases, but the way it increases is by creating an impermanent structure
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with a high degree of order and complexity.
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The alacrity with which simple dynamic systems exhibit self- organization
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makes it a little easier to believe that something like a cellular membrane
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could spontaneously assemble under the right conditions. But real biologi-
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cal membranes aren’t made out of boys and girls who don’t want to sit next
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to each other in class; they’re made of lipids.
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A lipid is a particular type of organic molecule, one that has ambivalent
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feelings toward water. To chemists, organic simply means “based mostly on
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carbon atoms, often involving hydrogen and perhaps a few other elements,”
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regardless of whether a compound has anything to do with living creatures.
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It’s a very different notion of “organic” than you will find in your local up-
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scale supermarket. The connection with biology arises because so much of
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biochemistry is based on carbon, which can easily form arbitrarily complex
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molecular chains.
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Lipids have a “head” that is hydrophilic (attracted to water) on one end, 34
and a “tail” that is hydrophobic (repelled by water) on the other. It’s this split 35S
personality, attracting water from one side and repelling it from the other,
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that helps these lipids form into membranes.
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Imagine putting a concentration of such lipids into water. The hydro-
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philic end is happy, but the hydrophobic end doesn’t know what to do with
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itself— there’s water everywhere. “Happy” is not meant to be taken literally;
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as with the X’s and O’s, an unhappy molecule is just one that will move to 04
a different configuration until some condition is satisfied. For a lipid, one