The Encyclopedia of Life

Although I am a champion of applying physics to biomedicine, physics has little impact on some parts of biology. For instance, much of zoology and botany consist of the identification and naming of different species: taxonomy. Not too much physics there.

A giant in the field of taxonomy is the Sweedish scientist Carl Linnaeus (1707-1778). Linnaeus developed the modern binomial nomenclature to name organisms. Two names are given (often in Latin), genus then species, both italicized with the genus capitalized and the species not. For example, the readers of this blog are Homo sapiens: genus = Homo and species = sapiens. My dog Suki is a member of Canis lupus. Her case is complicated, since the domestic dog is a subspecies of the wolf, Canis lupus familiaris, but because dogs and wolves can interbreed they are considered the same species and to keep things simple (a physicist’s goal, if not a biologist’s) I will just use Canis lupus. Hodgkin and Huxley performed their experiments on the giant axon from the squid, whose binomial name is Loligo forbesi (as reported in Hodgkin and Huxley, J. Physiol., Volume 104, Pages 176–195, 1945; in their later papers they just mention the genus Loligo, and I am not sure what species they used--they might have used several). My daughter Katherine studied yeast when an undergraduate biology major at Vanderbilt University, and the most common yeast species used by biologists is Saccharomyces cerevisiae. The nematode Caenorhabditis elegans is widely used as a model organism when studying the nervous system. You will often see its name shortened to C. elegans (such abbreviations are common in the Linnaean system). Another popular model system is the egg of the frog species Xenopus laevis. The mouse, Mus musculus, is the most common mammal used in biomedical research. I’m not enough of a biologist to know how viruses, such as the tobacco mosaic virus, fit into the binomial nomenclature.

Out of curiosity, I wondered what binomial names Russ hobbie and I mentioned in the 4th edition of Intermediate Physics for Medicine and Biology. It is surprisingly difficult to say. I can’t just search my electronic version of the book, because what keyword would I search for? I skimmed through the text and found these four; there may be others. (Brownie points to any reader who can find one I missed and report it in the comments section of this blog.)

• Escherichia coli (E. coli): the most famous model system in all of biology. The name of this bacteria species appears on page 2 of IPMB, and in Fig. 1.1. Also it appears on pages 29 and 71 (in homework problems), on page 85 in Table 4.2, and on pages 96 and 109. 
• Aquaspirillum magnetotacticum: a type of magnetotactic bacteria, shown in Fig. 8.25 on page 217 of IPMB. Apparently this organism has been reclassified as Magnetospirillum magnetotacticum.
• Chara corallina: I had forgotten about this one until I stumbled upon it as I browsed through the book. In IPMB, it appears on page 225, in the title of a journal article among the list of references for Chapter 8. It’s a type of green algae that produces a biomagnetic signal.
• Drosophila melanogaster was mentioned last month in this blog. It appears on page 239 of IPMB, when discussing potassium channels.

If you want to learn more about any of these species, I suggest going to the fabulous website EOL.org. The site states

The Encyclopedia of Life (EOL) began in 2007 with the bold idea to provide “a webpage for every species.” EOL brings together trusted information from resources across the world such as museums, learned societies, expert scientists, and others into one massive database and a single, easy-to-use online portal at EOL.org.

While the idea to create an online species database had existed prior to 2007, Dr. Edward O. Wilson's 2007 TED Prize speech was the catalyst for the EOL you see today. The site went live in February 2008 to international media attention. …

Today, the Encyclopedia of Life is expanding to become a global community of collaborators and contributors serving the general public, enthusiastic amateurs, educators, students and professional scientists from around the world.

Principles of Musical Acoustics

Principles of Musical Acoustics,
by William Hartmann.

In the 4th edition of Intermediate Physics for Medicine and Biology, Russ Hobbie and I added a new chapter (Chapter 13) about Sound and Ultrasound. This allows us to discuss acoustics and hearing; an interesting mix of physics and physiology. But one aspect of sound we don’t analyze is music. Yet, there is much physics in music. In a previous blog post, I talked about Oliver Sacks’ book Musicophilia, a fascinating story about the neurophysiology of music. Unfortunately, there wasn’t a lot of physics in that work.

Last year, William Hartmann of Michigan State University (where my daughter Kathy is now a graduate student) published a book that provides the missing physics: Principles of Musical Acoustics. The Preface begins

Musical acoustics is a scientific discipline that attempts to put the entire range of human musical activity under the microscope of science. Because science seeks understanding, the goal of musical acoustics is nothing less than to understand how music “works,” physically and psychologically. Accordingly, musical acoustics is multidisciplinary. At a minimum it requires input from physics, physiology, psychology, and several engineering technologies involved in the creation and reproduction of musical sound.

My favorite chapters in Hartmann’s book are Chapter 13 on Pitch, and Chapter 14 on Localization of Sound. Chapter 13 begins

Pitch is the psychological sensation of the highness or the lowness of a tone. Pitch is the basis of melody in music and of emotion in speech. Without pitch, music would consist only of rhythm and loudness. Without pitch, speech would be monotonic—robotic. As human beings, we have astonishingly keen perception of pitch. The principal physical correlate of the psychological sensation of pitch is the physical property of frequency, and our keen perception of pitch allows us to make fine discriminations along a frequency scale. Between 100 and 10,000 Hz we can discriminate more than 2,000 different frequencies!

That is two thousand different pitches within a factor of one hundred in the range of frequencies (over six octaves), meaning we can perceive pitches that differ in frequency by about 0.23 %.  A semitone in music (for example, the difference between a C and a C-sharp) is about 5.9 %. That's pretty good: twenty-five pitches within one semitone. No wonder we have to hire piano tuners.

Pitch is perceived by “place,” different locations in the cochlea (part of the inner ear) respond to different frequencies, and by “timing,” neurons spike in synchrony with the frequency of the sound. For complex sounds, there is also a “template” theory, in which we learn to associate a collection of frequencies with a particular pitch. The perception of pitch is not a simple process.

There are some interesting differences between pitch perception in hearing and color perception in vision. For instance, on a piano play a middle C (262 Hz) and the next E (330 Hz) a factor of 1.25 higher in frequency. What you hear is not a pure tone, but a mixture of frequencies—a chord (albeit a simple one). But if you mix red light (450 THz) and green light (563 THz, again a factor of 1.25 higher in frequency), what you see is yellow, indistinguishable by eye from a single frequency of about 520 THz. I find it interesting and odd that the eye and ear differ so much in their ability to perceive mixtures of frequencies. I suspect it has something to do with the eye needing to be able to form an image, so it does not have the luxury of allocating different locations on the retina to different frequencies. One the other hand, the cochlea does not form images, so it can distribute the frequency response over space to improve pitch discrimination. I suppose if we wanted to form detailed acoustic images with our ear, we would have to give up music.

Hartmann continues, emphasizing that pitch perception is not just physics.

Attempts to build a purely mechanistic theory for pitch perception, like the place theory or the timing theory, frequently encounter problems that point up the advantages of less mechanistic theories, like the template theory. Often, pitch seems to depend on the listener’s interpretation.

Both Sacks and Hartmann discuss the phenomena of absolute, or perfect, pitch (AP). Hartmann offers this observation, which I find amazing, suggesting that we should be training our first graders in pitch recognition.

Less than 1% of the population has AP, and it does not seem possible for adults to learn AP. By contrast, most people with musical skills have RP [relative pitch], and RP can be learned at any time in life. AP is qualitatively different from RP. Because AP tends to run in families, especially musical families, it used to be thought that AP is an inherited characteristic. Most of the modern research, however, indicates that AP is an acquired characteristic, but that it can only be acquired during a brief critical interval in one’s life—a phenomenon known as “imprinting.” Ages 5–6 seem to be the most important.

My sister (who has perfect pitch) and I both started piano lessons in early grade school. I guess she took those lessons more seriously than I did.

In Chapter 14 Hartmann addresses another issue: localization of sound. It is complex, and depends on differences in timing and loudness between the two ears.

The ability to localize the source of a sound is important to the survival of human beings and other animals. Although we regard sound localization as a common, natural ability, it is actually rather complicated. It involves a number of different physical, psychological, and physiological, processes. The processes are different depending on where the sound happens to be with respect to the your head. We begin with sound localization in the horizontal plane.”

Interestingly, localization of sound gets more difficult when echos are present, which has implications for the design of concert halls. He writes

A potential problem occurs when sounds are heard in a room, where the walls and other surfaces in the room lead to reflections. Because each reflection from a surface acts like a new source of sound, the problem of locating a sound in a room has been compared to finding a candle in a dark room where all the walls are entirely covered with mirrors. Sounds come in from all directions and it’s not immediately evident which direction is the direction of the original source.

The way that the human brain copes with the problem of reflections is to perform a localization calculation that gives different weight to localization cues that arrive at different times. Great weight is placed on the information in the onset of the sound. This information arrives directly from the source before the reflections have a chance to get to the listener. The direct sound leads to localization cues such as ILD [interaural level difference], ITD [interaural time difference], and spectral cues that accurately indicate the source position. The brain gives much less weight to the localization cues that arrive later. It has learned that they give unreliable information about the source location. This weighting of localization cues, in favor of the earliest cues, is called the precedence effect.

The enjoyment of music is a truly complicated event, involving much physics and physiology. The Principles of Musical Acoustics is a great place to start learning about it.

Bacterial Decision Making

Medical and biological physics sometimes appear on the cover of Physics Today. For instance, this month (February, 2014) the cover shows E coli. The caption for the cover picture states

Escherichia coli bacteria have served for decades as the “hydrogen atom” of cellular decision making. In that branch of biology, researchers strive to understand the origin of cellular individuality and how a cell decides whether or not to express a particular gene in its DNA. For some of the physics involved, turn to the article by Jané Kondev on page 31.

The article begins with a description of Jacques Monod’s work with the lac operon: a stretch of DNA that regulates the lac genes responsible for lactose digestion. (This story is told in detail in Horace Freeland Judson’s masterpiece The Eighth Day of Creation.) Kondev writes

The key question I’ll address in this article is, What is the molecular basis by which a cell decides to switch a gene on? Although all the cells in figure 1b are genetically identical and experience the same environment, only one appears to be making the protein. As we’ll see, that cellular individuality is a direct consequence of molecular noise that accompanies cellular decision making. The sources of the noise and its biological consequences are currently a hot topic of research. And statistical physics is proving to be an indispensable tool for producing mathematical models capable of explaining data from experiments that look at decisions made by individual cells.

The caption of Fig. 1b reads

In the presence of a lactose surrogate, individual cells can switch from a state in which they are unable to digest lactose to a state in which they are able to consume the secondary sugar. Yellow indicates the amount of a fluorescently labeled protein, lactose permease, which is one of the enzymes needed by the cell to digest lactose.

The article then draws on several physics concepts that Russ Hobbie and I discuss in the 4th edition of Intermediate Physics for Medicine and Biology: the Boltzmann factor, the Gibbs free energy, the Poisson probability distribution, and feedback. The last of these concepts is crucial.

Thanks to that positive feedback, E. coli cells exist in two different steady states—one in which there are many permeases in the cell (the yellow cell in figure 1b), the other in which the number of permeases is low (the dark cells in 1b). Stochastic fluctuations in the expression of the lac genes—fluctuations, for instance, between an on and an off state of the promoter—can flip the switch and turn a lactose noneater to a lactose eater.

The article concludes

Physics-based models are leading to more stringent tests of the molecular mechanisms responsible for gene expression than those provided by the qualitative model presented in biology textbooks. They also pave the way for the design of so-called synthetic genetic circuits, in which the proteins produced by the expression of one gene affect the expression of another. Such circuits hold the promise of bacterial cells capable of producing useful chemicals or combating diseased human cells, including cancerous cells. Whether this foray of physics into biology will lead to fundamentally new biological insights about gene expression remains to be seen.

Kondev’s review offers us one more example of the importance of physics in biology and medicine. And for those of you who think E. coli bacteria is not an appropriate topic for a Valentine’s Day blog post, I say bah humbug.

Distances and Sizes

One of the additions that Russ Hobbie and I made to the 4th edition of Intermediate Physics for Medicine and Biology is an initial section in Chapter 1 about Distances and Sizes.

In biology and medicine, we study objects that span a wide range of sizes: from giant redwood trees to individual molecules. Therefore, we begin with a brief discussion of length scales.

The Machinery of Life,
by David Goodsell.

We then present two illustrations. Figure 1.1 shows objects from a few microns to a few hundred microns in size, including a paramecium, an alveolus, a cardiac cell, red blood cells, and E. coli. Figure 1.2 contains objects from a few to a few hundred nanometers, including HIV, hemoglobin, a cell membrane, DNA, and glucose. Many interesting and important biological structures were left out of these figures.

I admit that our figures are not nearly as well drawn as, say, David Goodsell’s artwork in The Machinery of Life. But, I enjoy creating such drawings, even if I am artistically challenged. So, below are two new illustrations, patterned after Figs. 1.1 and 1.2. Think of them as supplementary figures for readers of this blog.

FIGURE 1.1½. Objects ranging in size from 1 mm down to 1 μm.
(a) Human hair, (b) human egg, or ovum, (c) sperm,
(d) large myelinated nerve axon, (e) skeletal muscle fiber,
(f) capillary, (g) yeast, and (h) mitochondria.

FIGURE 1.2½. Objects ranging in size from 1 μm down to 1 nm.
(a) Ribosomes, (b) nucleosomes, (c) tobacco mosaic virus,
(d) antibodies, and (e) ATP.

Powers of Ten.

When you combine these figures with those in IPMB, you get a nice overview of the important biological objects at these spatial scales. Two things you do not get are a sense of their dynamic behavior (e.g., Brownian motion) at the microscopic scale, and an appreciation for the atomic nature of all objects (you could not detect single atoms in Fig. 1.2½, but they lurk just below the surface; ATP consists of just 47 atoms).

If you like this sort of thing, you will love browsing through The Machinery of Life or Powers of Ten.