Mix and Match

It's easier to reconfigure a complex system to do new things if it is built from simpler, independent modules. But in biology, modules may be useful for more immediate reasons.

Biological systems, ranging from communities to molecular networks, often feature a modular organization, which for one thing makes it easier for a species to evolve in response to changes in the environment. In some cases, this flexibility might have been selected during prior changes. But modularity can also make life easier for a single organism during its lifetime, and be selected for this reason.

In their book The Plausibility of Life, Marc Kirschner and John Gerhart include modularity as one aspect of "facilitated variation." In particular, they say, genetic changes that affect the "weak linkages" between modules can cause major changes in the resulting phenotype. As long as the modules, the "conserved core processes," are not disrupted, the resulting organism is likely to be viable, and possibly an improvement on its predecessors.

In describing facilitated variation, Kirschner and Gerhart defer the question of whether facilitating rapid future evolution alone causes these features to be selected. Perhaps it does, in some circumstances. But in any case, we can regard the presence of features that enable rapid reconfiguration as an observational fact.

Moreover, the practical challenges of development demand the same sort of robust flexibility that encourages rapid evolutionary change. Over the development of a complex organism, various cells are exposed to drastically different local environments. In addition, genetic or other changes pose unpredictable challenges to the molecular and other systems of the cells. Throughout these changes, critical processes, like metabolism and DNA replication, need to keep working reliably.

To survive and reproduce in the face of these variations organisms need a robust and flexible organization. Features that allow such flexibility should be selected, if only because they improve individual fitness. These same features may then increase evolutionary adaptability, whether or not that adaptability is, by itself, evolutionarily favored.

Whether adaptability is selected for its evolutionary potential or only for helping organisms thrive in a chaotic environment, it has a profound effect on subsequent evolution. A flexible organization including modularity and other features allows small genetic alterations to be leveraged into large but nonfatal changes in the developing creature, so the population can rapidly explore possible innovations.

Changing Times

One way to explain the modularity that is seen in biology is that it helps species to evolve quickly as their environment changes.

But the notion that "evolvability" can be selectively favored is tricky intellectual territory, and people can get drawn in to sloppy thinking. Just as group selection must favor more than just "the good of the species," selection for flexibility cannot be grounded in future advantages to the species. To be effective, evolutionary pressure must influence the survival of individuals in the present.

Whether this happens in practice depends on a lot of specific details. Some simulations of the effect of changing environments have not shown any effect. But at a meeting I covered last year for the New York Academy of Sciences, Uri Alon showed one model system that evolves modularity in response to a changing environment.

Alon is well known for describing of "motifs" in networks of molecular interactions. A motif is a regulatory relationship between a few molecules, for example a feed-forward loop, that is seen more frequently in real networks than would be expected by chance. It can be regarded as a building block for the network, but it is not necessarily a module because its action may depend on how it connects with other motifs.

Alon's postdoc Nadav Kashtan simulated a computational system consisting of a set of NAND gates, which perform a primitive logic function. He used an evolutionary algorithm to explore different ways to wire the gates. Wiring configurations that came closest to a chosen overall computation result were rewarded by giving making future generations more likely to resemble them. "The generic thing you see when you evolve something on the computer", Alon said, "is that you get a good solution to the problem, but if you open the box, you see that it's not modular." In general, modules cannot achieve the absolute best performance.

Kashtan then periodically changed the goal, rewarding the system for a different computational output. Over time, the structure of the surviving systems came to have a modular structure. One interesting surprise was that in response to changing goals, the simulated systems evolved much more rapidly than those exposed to a single goal.

But Alon emphasized that this was not a general feature. Instead, the different goals needed to have sub-problems in common. Evolution would then favor the development of dedicated modules to deal with these problems. It is easy to imagine the challenges facing organisms in nature also contain many recurrent tasks, such as the famous "four Fs" of behavior: feeding, fighting, fleeing, and reproducing.

So some biological modularity may reflect the evolutionary response to persistent tasks within a changing environment. But does this explain the wide prevalence of modules? In a future post, I will examine another explanation: that modularity is one of the tools that helps individual organisms adapt to the changing conditions of development and survival during their own lifetimes.

Modules

When people design a complex system, they use a modular approach. But why should biology?

For us, modularity is a way to limit complexity. Breaking a big problem into a series or hierarchy of smaller ones makes it more manageable and comprehensible, which is especially important if it is assembled by many people--or one person over an extended time.

The key to a successful module is that its "guts"--the way its parts work together--doesn't depend on how it connects to other stuff. The module can be thought of as a "black box," that just does its job. You don't have to think about it again. For this to work, the connections between modules must be weak, limited to well-defined inputs and outputs that don't directly affect its internal workings.

When it's done right, a module can be easily re-used in new situations. For example, the part of a computer operating system that offers a help menu is tapped by lots of programs without worrying about how it works.

But biology is not designed. Biological systems emerge from an evolutionary process that rewards only survival and reproduction, with no regard for elegance or comprehensibility. Re-usability sounds like a good thing in the long run, but doesn't help an individual survive in the here and now.

Nonetheless, modularity seems to be widespread feature of biological systems. Your gall bladder, for example, is a well-defined blob that receives and releases fluids like blood and bile, but otherwise keeps its own counsel. It can even be removed if necessary. And it does much the same thing in other people and animals.

At a smaller scale, many of the basic components of cells are the same for all eukaryotes. They have the discrete nuclei that define them, and they also have other organelles that perform essential functions, like mitochondria that generate energy. These modules work the same way, whether they happen to appear in a brain cell or a skin cell.

Even at the molecular level, re-usable modules abound. For example, although ribosomes don't have a membrane delimiting them, they consist of very similar bundles of proteins and RNA for all eukaryotic cells, and only modestly different bundles for bacteria. In addition to such complexes, many "pathways," or chains of molecular interactions, recur in many different species.

We have to be careful, of course: simply because we represent complex biological systems as modules doesn't mean they are there. The modules we think we see could simply reflect our limited capacity to understand messy reality. But when researchers have looked at this question carefully, they found that modules really exist in biology, much more than they would in a random system of similar complexity.

But why should evolution favor modular arrangements? And how does a modular structure change the way organisms evolve?

Don't Fear the Hyphen

Hyphens come up a lot in scientific writing. Or at least they should. Unfortunately, small as they are, many people are afraid of them.

One problem is that hyphens get used for some very different purposes, although all of them tend to bind words or fragments together. I'm only going to talk here about making compound words with them.

Another problem is that you don't have to use a hyphen if you don't have to: if the meaning is clear without it (semantics), you're allowed to omit it (punctuation). This makes it very hard to figure out the real punctuation rules, since they don't arise from syntax alone.

Compound words are hard to predict. Sometimes two words are locked together to form one new word, as in German: eyewitness. Sometimes the two words keep their distance even as they form a single, new concept: eye shadow. But some pairs are bound with the medium-strength hyphen: eye-opener. This mostly happens when both words are nouns, so that the first noun is acting as an adjective, making the second more specialized.

There's really no perfect way to know which form is favored, and it varies over time. Novel pairings generally start out separated and become hyphenated when they seem to represent a unique combined identity. When that combined form becomes so familiar that it is easily recognized, the hyphen disappears, (unless the result would be confusing, as in a recent example, "muppethugging," or the less novel "cowriting.") You just have to look in an up-to-date dictionary.

For the single compound words and those that are always hyphenated that's the end of the story. The problem is that the isolated pairs of words sometimes should be hyphenated, too. This hyphenation is not a property of the pair, and it can't be found in the dictionary. It's a real punctuation mark, and depends on the details of the sentence.

The hyphen belongs when the pair is used as an adjective, known as a compound modifier, as in the previous "medium-strength hyphen." But generally the hyphen is omitted when the adjective occurs later on: "The hyphen has a medium strength." But the AP Stylebook (not hyphenated!) says that when that "after a form of to be, the hyphen usually must be retained to avoid confusion: The man is well-known." AP also has a rule that when for an adverb-adjective pair, the hyphen is not used if the adverb is "very" or ends in "-ly."

OK, this is getting confusing, so let's regroup: The important principle is that the hyphen is there to make clear when there is a link that might otherwise be missed. If we talk about a "highly important person," it's clear that it's the importance that's high, not the person. But if we talk about a "little known person," it's not so obvious whether it's the knowledge or the person that's diminutive, because
"little" can be an adjective or an adverb. If it's an adjective, you might have said "little, known person, " but "little-known person" avoids any chance of confusion.

The problem is worse when the first word is a noun, because it doesn't really give you any syntax clues about whether it's acting as an adjective or adverb. This issue comes up frequently in science writing. I imagine most people will realize that a "surface area calculation," refers to a calculation of surface area, and not a surface calculation of the area. But sometimes it's hard to know what will be confusing. I prefer to assume as little possible about what my readers are getting, so I would use "surface-area calculation." But many editors correct this (and I generally defer to them).

Unfortunately, there is a compelling to reason to be sparing with hyphens, which is that they can't be nested. This also comes up frequently in science writing, when a compound modifier is constructed from another compound modifier, as in "surface area calculation results." If we used parentheses to tie together related words, this would be rendered "((surface area) calculation) results." But there's no way to indicate priority with hyphens.

The right thing to do is to decide what level of compounding needs to be made explicit, and retain hyphens at all levels up to that, for example "surface-area-calculation results." Sadly, I frequently see something like "surface area-calculation results." That's just wrong, since the hyphen ties together "area" and "calculation" more strongly than "surface" and "area." In this case you'd be better off leaving out all hyphens and hoping for the best.

Of course, as in most cases of confusing writing, the best alternative is "none of the above": recast the sentence so that it doesn't have compound-compound modifiers. "The results of the surface-area calculation" leaves nothing to chance. But it's clunkier.

Innovation

About 540 million years ago, virtually all the basic types of animals appeared in a geographic eyeblink known as the Cambrian explosion.

The late Stephen Jay Gould used this amazing event (if a period of millions of years can be called an event) in his 1989 bestseller Wonderful Life: The Burgess Shale and the Nature of History to debunk two popular myths about evolution. First, evolution is not a steady march toward more and more advanced forms (presumably culminating in us). Second, diversity does not steadily increase. The Cambrian was populated by many types of creature no longer around today, some so exotic as to be worthy of a science fiction film. Rather than growing steadily bushier, the tree of life was later brutally pruned, and we grew from the remaining twigs.

In The Plausibility of Life, Marc Kirschner and John Gerhart highlight another critical facet of this amazing period: since that period of innovation, no more than one new animal type has appeared. The diversity we enjoy today is built from basic parts that were "invented" in the Cambrian explosion.

Rather than get into how and why this happened, for now let's just regard it as an observational fact from the fossil record:

True innovation is rare.

We know this is true in human affairs. Producers of movies and TV shows, for example, often play the odds by re-using and recombining proven concepts. The same goes for technology, where many innovations combine familiar elements in new ways. It's faster, it's cheaper, and it's safer.

For whatever reason, the evolutionary history of life is a series of one-time innovations. After they are adopted, these "core processes" change very little, even though they have eons of time to do so. That doesn't mean that the organisms themselves stay the same--far from it. But they use the core processes in different ways, just as a bat wing is built in the same way as the human hand.

Kirschner and Gerhart discuss several examples of conserved core process, starting with the fundamental chemistry of DNA, RNA, proteins and the genetic code that connects them. Every living thing on earth uses the same chemistry. The appearance of the eukaryotic cell is defined by the presence of the nucleus, but a host of other innovations occurred at the same time. All eukaryotes from amoebae to people share these features even now. The joining of cells into multicellular organisms was also accompanied by innovations that helped the cells stick together and cooperate. Every plant and animal has retained these features largely intact.

Like the animal body plans of the Cambrian explosion, these burst of innovation occurred over relatively short periods, and were permanently added to the toolkit. All of the animals we know, from cockroaches to cockatoos, from squirrels to squids, arose by applying those tools in new ways.

But what is it about the core processes that makes them so resistant to change? What makes them so useful? And are the answers to these questions related?

Monday Morning Quarterbacks

Many news stories simply report the facts; the better ones put the facts in the context and explore their likely impact.

Then there are stories that explain "why."

I have a simple assessment for these explanation stories that saves me a lot of time. This is it:

"What's new?"

More specifically, is there anything about the "explanation" that wasn't known before the event actually happened? If not, click on.

A classic example is election-night analysis. Even before all the votes are counted, pundits materialize to explain what message the voters were trying to send, and which campaign screwed up.

Unfortunately, most of what they say was just as true the day before. Sure, they now have more precise results, and maybe a geographic breakdown and some exit polls. But most of the commentators' facts were already known to everyone. Somehow the surrounding story seems more profound once it aligns with actual events--and once the arguments for the other side have been conveniently forgotten.

Stories about stocks can also be amusing, or pathetic. It's hard to find any report on a market move that doesn't attribute it to concern about Chinese exports, or some such. When the market is truly uncooperative, analysts resort to saying that it "shrugged off" some really dire economic news. Sorry, guys. If you knew how the market would react, you'd be rich.

Unfortunately, the challenge of explanation applies to the real economy as well. I'm a regular reader of Paul Krugman, who warned a year ago that the stimulus package would likely not generate enough jobs. Sure enough, we now have an unemployment rate that once would have been thought unacceptable. So was Krugman right? Or were the conservatives who said the stimulus just wouldn't work?

The sad fact is we hardly know any better now than we did a year ago. We know what happened, of course. But we still don't know what would have happened if we had done something different. Evaluating such past hypothetical situations requires the same kind of modeling, and relies on the same ideological assumptions, as predictions do. Unsurprisingly, the experts mostly see the past the same way they saw the future.

The same problem may apply to climate change. I don't usually think of the existence of global warming as a political question (as opposed the policy response). In a hundred years, after all, liberals and conservatives will both suffer the same heat and drought and see the same sea level rise, or not. But even then, they probably won't agree on what we did, or didn't do, to get them there. We don't have a duplicate world to do control experiments on.

As Yogi Berra is quoted, "Predictions are hard, especially about the future." Sadly, they are almost as hard about the past.

The Plausibility of Life

When creationists, or, as they would have it, advocates of "intelligent design," talk about the "weaknesses" of evolutionary theory, knowledgeable people generally roll their eyes and ignore them. This is appropriate, as these advocates only raise the questions in a disingenuous attempt to promote a religious agenda, under the pretense of open-mindedness and "teaching the controversy." In truth, there is no controversy in the scientific community about the dominant role of natural selection (evolution, the theory) in shaping the observed billions of years of change (evolution, the fact) of life on this planet.

But this response obscures the fact that very interesting issues in evolution remain poorly understood.

I'm not referring to the direct exchange of genetic material between single-cell organisms, although that does call into question the tree-like structure of relationships between these simple species. But at the level of complex, multi-cellular creatures like ourselves, this "horizontal gene transfer" is unimportant compared the "vertical" transfer from parents to offspring. The tree metaphor is still intact.

But even for complex creatures-- especially for complex creatures--there are important open questions about how evolution works in detail. The insightful (and cheap!) 2006 book, The Plausibility of Life, by Marc Kirschner and John Gerhart, began to frame some answers to these questions.

The fundamental ingredients of evolution by natural selection were laid out by Darwin: heritable natural variations lead some individuals to be more likely to survive and thus to pass on these variations.

We now know in great detail how cells use some genes in the DNA as a blueprint for proteins, and how these proteins and other parts of the DNA in turn regulate when various genes are active. And we know, as Darwin could only imagine, how that DNA is copied and mixed between generations, only occasionally developing mutations at single positions or in larger chunks. We understand heritable variation.

We also understand the arithmetic of natural selection, which confirms Darwin's intuition: a mutation that improves the chances that its host will survive to be reproduced will spread through a population, while a deleterious mutation will die out (although evolution is indifferent to most mutations). This all takes many generations, but the history of life on earth is long.

But there is something missing, what Kirschner and Gerhart call the third leg of the stool: how does the variability at the DNA level translate into variability at the level of the organism? Selection must occur at this higher level, the level of phenotype, but can only be passed on at the level of the genotype. How do we close this loop?

It would be easy if a creature's fitness were some average of the fitness of each of the three billion bases in the DNA, but it's not that simple. For example, if two proteins work together as a critical team, a mutation in one can kill the organism, even if they could be an even better team if they both mutated in a coordinated way.

This sounds disturbingly reminiscent of the neo-creationist argument that life is so "irreducibly complex" that there must have been a creator--er, designer. But Kirschner and Gerhart don't believe that for a second. What they argue instead is that organisms are constructed so that genetic change can dramatically alter phenotype without sacrificing key functions--in a process they call facilitated variation.

In future posts I will discuss clues that this construction--I'm avoiding the word "design"-- is present in organisms today, and some of the principles it follows.