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Questions - Information - Navigating by temperature - Creeping flow - Gamete evolution
Here are some of the results of my research, especially the analyses that generated some interesting graphics. I have long been fascinated by the question of good design to conveigh the results of quantitative investigations. A general theme is information—what is it, how do organisms obtain it, and how do they use it.
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Even as a child, I remember the question: what do animals know? Does that ant know were it's nest is, or is it following a trail wherever it goes?
The training in physics taught me to think about the simplest system that had the properties I was interested in studying.
In graduate school looking toward what I would do next, like a lot of other molecular biologists at the time (late 1960s), I took the view that the big mystery of heredity had been solved by DNA. The next big mystery was what are the mechanisms connecting genes to complex organisms, and especially how does the brain work. Molecular genetics had prospered by the use of appropriately simple model systems for study by genetic dissection—primarily bacteria and their viruses. So some molecular biologists naturally asked what is the best model system for studying developmental process and brain function, and a remarkable variety of choices were made:
Julius Adler—chemotaxis of the bacterium E. coli, a single cell with intelligent behavior.
Max Delbruck—the response of the fruiting body of a fungus to light.
Sydney Brenner—a, self-fertilizing roundworm with a tiny, fixed nervous system.
Seymour Benzer—the fruit fly with well-studied genetics and a small brain.
George Streisinger—zebra fish with transparent embryos for studying developmental mechanisms.
François Jacob—mice for studying developmental mechanisms.
Similarly, I followed the information questions. First, with rotifers and then with nematodes. However, I found the genetic dissection approach very time consuming for the understanding gained. Even though the nematode became the only animal in which the complete wiring of the nervous system was described, understanding how it worked was stymied by the small size that made it impossible to stick electrodes into the neurons to see what they were doing. (The whole nematode was smaller than the neurons studied with microelectrodes).
Gradually, my attention shifted from inside the animal to outside. What information was available in the environment? What part of this was obtained? How? What was done with it? Although ecologists had been using some physics (conservation of elements and energy), like biochemists, they had not focused on information.
Frustrated with spending so much time and effort on unfunded grant proposals, I started a book with the working title Information Ecology. In the end, it was published as Sensory Ecology.
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Trying to be logical, I had to think about what information was, in order to determine the scope of the book, as my goal was to be comprehensive with regard to both the kinds of information and the kinds of organism (bacteria to whales and plants). I was surprised to find an absence of sensible definitions of this basic concept. Here is my view:
Inputs and outputs between an individual organism (center), its environment (left), and its population or species (right).
The individual organism exchanges information with two entities—the environment in which it lives and the population or species to which it belongs. From each of these entities, it exchanges two kinds of effects—physical causes and information. The distinguishing feature of information is that it has consequences only if the organism has an appropriate detector and a means of amplification. Consequently, information is easily ignored, while causes are not. Information has value to the recipient only because it is associated with some causal input. Although not logically necessary, usually the distinction between information and causal inputs is clear.
For example, consider a flower and a pollinating animal. The color and scent of the flower provide information because they have no consequences for the pollinator unless it has appropriate sensory systems, and even then their value depends on their association with other features: nectar and pollen, and these provide direct nutritional benefits. In contrast, the color and scent provide no direct benefit and are useful only because of their association with the nectar and pollen.
On the other hand, plants usually produce chemicals that are toxic to animals and discourage eating of the plants. These chemicals are causal, because they directly disrupt physiological functions important to the animal, which would ignore the chemicals if it were possible. A further complication is that some animals adapt to certain plants by evolving systems that detoxify the chemicals produced by that kind of plant. These animals may then seek out this kind of plant, and the chemical that is a toxic causal agent to most animals may become an agent of information to help the specialist herbivore find its appropriate food plant. (This situation occurs in many butterfly/caterpillar species.)
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In the 1980's, my research group at Georgia Tech started trying to identify chemicals that were used by the infective juveniles of root-knot nematodes (Meloidogyne incognita) to find the roots of host plants, such as tomatoes. While investigating this question, we discovered that the nematodes were incredibly sensitive to small temperature differences; they seemed to be able to respond to differences of only 0.001 degree, and such small differences are almost always present in the environment. In addition, when placed in a controlled temperature gradient, they accumulated at a temperature several degrees higher than the temperature to which they had been acclimated for several hours previously. Why did they do this?
Eventually, we explained the behavior by understanding the complex distribution of temperature in soil within a few feet of the surface. Sunlight causes dailey fluctuations of temperature at the surface, and heat is conducted from high to low temperatures, smoothing out any differences. The net result, is that the distribution of temperature looks like a temperature wave propagating down into the soil but losing amplitude as it goes:
Temperature in soil.
The temperatures are represented by red (high), green (average), and blue (low). The image corresponds to a depth of 20 cm or one foot (from the top down), and 4 days occur from left to right.
After measuring the rates at which the nematodes moved and adapted to new temperatures, we constucted a computer model of their behavior in this dynamic temperature environment and traced paths expected for nematodes that started out at different depths:
Nematode paths in soil
The white lines are the paths of nematodes starting out at depths differing by 2 cm (about an inch). Those starting out within the top 15 cm (6 in) move toward a depth of 5-10 cm (2-4 in). It is plausible that this is indeed the depth that they have the best chance of locating the root of a susceptible plant. So we concluded that they have evolved this sophisticated sensory capability and behavior because it makes them more successful in finding a suitable host—otherwise they die because they have no other way to get food.
The other organism that has been found to be guided by very shallow temperature gradients is the slime mold Dictostelium discoideum. This interesting organism has been much studied because it forms organized communities. It feeds as single-cell amoeba-like organisms, but when well-fed but sensing that food is running out, it aggregates into a mass of cells, commonly referred to as a "slug" (although it is not an animal). For a few hours, the slug migrates through its environment and then reorganizes to form a "fruiting body" with a stalk that can release spores into air and away from the surface, where they can disperse into the environment to start a new generation at another location. It was discovered that the slugs are guided by very small temperature gradients, although (unlike the nematodes) they move away from a temperature several degrees below the temperature to which they have been adapted over several hours:
Slime mold paths in soil
The white lines are the paths of slime mold "slugs" starting out at depths differing by 3 cm (about an inch). Those starting out within the top 20 cm (8 in) move toward the surface. This makes sense, as the slugs are most successful if they move to a location where they can release spores that have a good chance of being carried to a new location by wind, water, or passing animals.
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Engineers studying the movement of boats through water, or water through pipes or channels have found it indispensible to consider the Reynolds number of the flow. This dimensionless number is determined by the density and viscosity of the fluid, the speed of the flow, and some length representing the size of the solid surfaces confining the flow. In flows were the Reynolds number is far above one, the flow is dominated by the mass or inertia of the fluid, while at low Reynolds numbers the flow is dominated by the viscosity of the fluid (which measures its frictional resistance to moving).
Examples of Reynolds numbers
Shown above are examples of a molecule, virus, and nano-particle in thermal motion at room temperature in water; gravitational sedimentation of a raindrop, and clay, silt and sand particles in water; self-propelled bacteria, sperm, fly, fish, bird, automobile, and airplane; bullet and inkjet projectiles; solder flow; and continental drift with the high viscosity of the earth's mantel. In most familiar situations, inertia is important (Re >> 1), but at microscale it is usually not (Re << 1).
As seen in the figure, most familiar things operate at high Reynolds numbers, where flows tend to be chaotic and unpredictable. In contrast, single cells such as bacteria or sperm swim at low Reynolds numbers, where flows are smooth and predictable.
Coefficient of drag
As seen above, the simple Stokes' law accurately predicts the force observed on a sphere moving through a fluid at low Reynolds numbers but the drag (force) deviates dramatically from this model in a complicated fashion at high Reynolds numbers.
The simple flows at low Reynolds numbers are often called creeping flows. These flows are often important, as the motion of molecules, microorganisms, and nano particles is usually one of low Reynolds number. However, the physics of such flows differs in striking ways from that of the turbulent world that is familiar at human size scale. For example, flows are reversible, so mixing by stirring can be undone. And moving bodies carry a relatively large halo of surrounding fluid with them, so the shape of the body has relatively little impact on resistance to movement; no matter what the shape of the body, the resistance to translation in two different directions is always less than 2-fold. And even more surprisingly, it is cylindrical shapes rather than flat plates that have the largest differences in resistance to motion in different directions: consequently, microorganisms swim by means of cylindrical appendages rather than the flat paddles (think fins and wings) used at our size scale.
In the natural world, creeping flows occur in such diverse areas as geological flows of magma, hydraulic flows through porous substrates, meteorological movements of cloud droplets, thermal movements of molecules through liquids, biological flows of blood through capillaries and the swimming of microorganisms such as bacteria or sperm. In technology, creeping flows occur in lubrication, soldering, flow through porous filters, microfluidics, micro-robots, and some molecular properties of matter.
Much of my research of the 1990s exploited the predictability of flows at micro scale to make rigorous calculations of the behavioral abilities of various micro-organisms. My book Living at Micro Scale introduces the basic science of creeping flow and other physical relationships important at micro scale such as Brownian motion and diffusion. These physical relationships are then applied to microorganisms to gain a fundamental understanding of many of their observed features and behaviors.
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Male and female are defined by the type of gametes produced by the body. Males produce many small gametes specialized for transport by swimming (sperm), wind or insect (pollen), while females produce fewer large, immobile eggs. Biologists recognized years ago that sexual reproduction does not require sperm and eggs. Many species of algae and fungi reproduce by fusing gametes that look identical; sometimes there are even more than two mating types, with the rule that you can mate with anyone of a different type. But in all the large organisms familiar to us, reproduction requires the fusion of a large gamete with a small gamete, specialized for transport (swimming, wind, insect, etc.). Why?
A lunch-time conversation with my colleague Terry Snell inspired me to think that small organisms and cells might be too small to use pheromones to attract mates effectively. This led me to do some simple calculations and computer modeling of the process of getting two small animals or gametes together. The results are summarized in the following plot:
Encounter rates between gametes of various sizes.
The black and white lines trace the predicted evolution of gametes starting with nearly-equal (but various) sizes and selected for more likely encounters with the other type. This analysis predicts that the process leads to the evolution of two disticnct types of gametes—eggs and sperm. So here we have a fundamental explanation of why males and females exist—they helped the gametes of our ancestors find one another. Remember, you are the unique result of a particular sperm finding a particular egg, in each generation, going back a billion years—with millions of unique sperm-egg encounters in your heritage.
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Last revised 25 June 2013.
E-mail me: SeekingIllumination@hotmail.com