Contemplating libraries in biology. Not that kind. Not that one either.

What is a library? If you ask a biologist (especially a molecular biologist) this question, they are likely to ask for clarification. In their work, they are likely to make regular use of two very different kinds of libraries.

The first is the kind that we've had for millenia: a collection of books, journals, and media that is ordered and curated by people. These are the OG libraries, with 'book' at the very root of the word. They're rapidly evolving in our digital world, but I think they are still essentially what they've always been. Your friend the molecular biologist may not regularly go to a separate room or building to find materials, but they will use the library often.

The second is an extension of the OG concept of a library, but is still called a 'library' by your friend. It contains information, perhaps in vast amounts, but is not ordered or curated. Crucially, it is a specific collection of a particular type of information: genetic information. And while it's neither ordered nor curated, it is physical, and is designed to be searched. The contents of the library might be DNA sequences (genes or even just chunks of some interesting genome) or protein sequences. Unlike your favorite public library, this one doesn't come with a search feature: you have to do that yourself. The process of searching a library is called screening. Your molecular biologist friend can go to the institutional library to read about these kinds of libraries, and find techniques on how to screen one, then perhaps go to a colleague or a vendor to obtain a library. Or she will obtain tools to make one herself.

In my previous post, I talked of an even more radical extension of the concept of a library: a collection of all the versions of any kind of text (a book, a genome, a set of proteins).

The library of possible proteins is beyond vast. Does this cause us to view evolution as harder than it is?

Bates Hall at the Boston Public Library

One of the most effective metaphors for evolutionary change is the image of an exploration of a space, perhaps a map that shows "fitness peaks" or, better, a library of possibilities. The philosopher Daniel Dennett, writing in Darwin's Dangerous Idea, suggested The Library of Mendel as a way of thinking about the total set of possible gene sequences. He was adapting an idea famously employed in a short story by Jorge Luis Borges called "The Library of Babel," which consists of the total set of possible books of a particular length. (This "library" exists on a website designed for creators and researchers.)

Contemplating a space of possibilities—whether that space consists of books written in English (26 letters), or "books" written in the language of DNA (four letters), or "books" written in the language of protein (20 letters)—is both fun and dizzying. The dizziness is induced (for me, at least) by the vastness of these libraries (Babel or Mendel, doesn't matter). How vast? Here is how Dennett describes the Library of Babel's size (italics are his):

No actual astronomical quantity (such as the number of elementary particles in the universe, or the amount of time since the Big Bang, measured in nanoseconds) is even visible against the backdrop of these huge-but-finite numbers. If a readable volume in the Library were as easy to find as a particular drop in the ocean, we'd be in business!

—Darwin's Dangerous Idea, p. 109

Dennett then uses Vast to indicate "Very-much-more-than-astronomically" large and Vanishingly small to indicate the likelihood of something like discovering a "volume with so much as a grammatical sentence in it" in the Library. In other words, we lack words to adequately describe the size of the Library and the improbability of randomly discovering anything coherent inside it.

Mapping fitness: ribozymes, landscapes, and Seattle

A few months ago, we were looking at the concept of a fitness landscape and how new technologies are creating opportunities for biologists to look in detail at relationships between genetics and fitness. The first post discussed the concepts of a fitness landscapes and adaptive walks, with some focus on the limitations of the metaphor. The second post summarized some recent work on bacterial fitness and mutation rates, with the concept of a fitness landscape as a theme, and the third post reviewed another recent paper, one that described techniques for studying fitness landscapes in detail by linking protein function (which can be screened and/or selected) and genetic information. Here we'll look at yet another approach to the problem, in which the subject of the analysis is not an organism (as in the first paper) or a protein (as in the second paper) but an RNA molecule.

Mapping fitness: protein display, fitness, and Seattle

A couple of months ago we started looking at the concept of fitness landscapes and at some new papers that have significantly expanded our knowledge of the maps of these hypothetical spaces. Recall that a fitness landscape, basically speaking, is a representation of the relative fitness of a biological entity, mapped with respect to some measure of genetic change or diversity. The entity in question could be a protein or an organism or a population, mapped onto specific genetic sequences (a DNA or protein sequence) or onto genetic makeup of whole organisms. The purpose of the map is to depict the effects of genetic variation on fitness.

Suppose we want to examine the fitness landscape represented by the structure of a single protein. Our map would show the fitness of the protein (its function, measured somehow) and how fitness is affected by variations in the structure of the protein (its sequence, varied somehow). It's hard enough to explain or read such a map. Even more daunting is the task of creating a detailed map of such a widely-varying space. Two particular sets of challenges come to mind.

Mapping fitness: bacteria, mutations, and Seattle

Thinking about fitness landscapes can stimulate detailed discussion and consideration of the meanings and limitations of such metaphors, and my introductory comments at The Panda's Thumb did just that. Most notably, Joe Felsenstein pointed us to the various ways these depictions can be employed, and urged everyone to use caution in interpreting them. All too true, but the goal here is modest: I want to discuss the interesting questions that arise when considering the relationship between genotypes and phenotypes, i.e., how a particular genetic makeup influences fitness, whether the genetic makeup in question is simple or complex, and however fitness is conceived. These questions can take further discussion in all sorts of directions, but there are two that I have in mind in this series. First, I want to point to increasing capacity of scientists in their ability to examine these relationships experimentally. Second, I want to highlight the failure of design creationists to address or even to understand such matters.

Mapping fitness: landscapes, topographic maps, and Seattle

The concept of a "fitness landscape" is a fundamental idea in evolutionary biology, first introduced and established during the so-called "evolutionary synthesis" in the early 20^th century. It was the great Sewall Wright who pictured adaptation as a "walk" through a landscape (pictured below), where the walking is done by variants (of an organism or a molecule) and the landscape is a theoretical representation of the relative fitness of the variants. (J.B.S. Haldane did similar work around the same time, but Wright's paper is much better known perhaps because it's more accessible to non-experts. See Carneiro and Hartl in PNAS earlier this year for more.)

It's a simple concept, and a helpful one, though sometimes subject to over-interpretation. And it helps to frame some of the big questions in evolutionary genetics. One of those big questions is this one, stated somewhat simplistically: how do the variants navigate to fitness peaks, if there are fitness valleys that separate the peaks? (The ideas is that fitness is higher on the peaks, and so a population would be unlikely to descend from a local peak into a valley.) In other words, given a particular fitness landscape, what are the evolutionary trajectories by which variation can explore that landscape?