Orientation to stimuli

As with all organisms, an ability to orient with respect to stimuli greatly increases the competitive ability of the microbial species. It allows them to increase their feeding and photosynthetic rate, and remain in chemically favorable environments as well as avoid potentially damaging situations. As previously mentioned, however, microorganisms are too small to be able to perceive chemical gradients over the length of their bodies and too simple to develop complex eyes. Hence, they have been forced to develop other means of orienting to stimuli based on a short term "memory" that allows them to detect changes in stimuli intensity [103]. The degree to which they have succeeded in doing this is remarkable and is an example of how complex and interesting the world of such seemingly simple organisms can be. However, as the topic is generally well described (see Refs. [104,105] as well as the comprehensive introductions in Refs. [106,107]), I restrict myself to a brief overview here.

Bacteria are so small and swim at such low velocities that swimming in a straight path is made impossible by Brownian motions. Instead they swim in what has been named the "random walk," which involves alternating "runs" and "tumbles." In the run, the bacterium swims in an almost straight path with the flagella rotating in a bundle. In tumbles, the flagella change the direction of the rotation, for example, from counterclockwise to clockwise, and the individual flagella separate, which causes the bacterium to stop and change direction randomly (e.g., [108]). Though runs and tumbles always occur, the presence of attractant or repellents can change the frequency with which they occur (e.g., Refs. [103,109]). When swimming up a concentration gradient of a positive attractant or down a gradient of a negative repellant, the tumbles become less frequent and the runs consequently become longer. When swimming in the opposite direction, tumbles become more frequent. This occurs through a direct reaction of the bacterium to the attractants or repellents via chemoreceptors in the membrane [110]. This type of locomotion appears to be advantageous only for bacteria longer than about 0.6 ^m. Orientation to stimuli in bacteria smaller than this would be too inefficient, which explains why no motile bacteria shorter than 0.8 ^m have been found [111].

The orientation process of bacteria is random because it swims in a random direction after it tumbles. The changes in tumbling frequency, however, results in a higher probability that the net movement of the bacteria will be toward an attractant rather than away from it, or vice versa for repellents (Figure 13.11). This is surprisingly effective, and the bacterial concentrations around nutrient patches may be orders of magnitude higher than ambient bacterial concentrations [61-63,85,112]. In this way, bacteria may form dense clusters at optimal conditions with respect to parameters such as oxygen tension or nutrient concentrations. The chemotactic behavior of bacteria may as much as double the turnover rate of organic carbon in aquatic ecosystems.

For protozoa, this results in an environment of alternating feasts and famines, with patches of high bacterial concentrations dispersed among large areas of low concentrations. This makes it important for protozoa to be capable of chemotactic orientation to such patches so as to utilize the available food resources. In addition,

FIGURE 13.11 Orientation by random walk of a bacterium toward an attractant. As the bacterium swims up the concentration gradient, the frequency of tumbles decreases, resulting in longer "runs," whereas when it swims down the concentration gradient, the frequency increases. This results in an overall movement toward the attractant.

FIGURE 13.11 Orientation by random walk of a bacterium toward an attractant. As the bacterium swims up the concentration gradient, the frequency of tumbles decreases, resulting in longer "runs," whereas when it swims down the concentration gradient, the frequency increases. This results in an overall movement toward the attractant.

FIGURE 13.12 Swimming in a helix, in this case for the flagellate Pteridomonas. The swimming path of the organism and hence the helix is defined by the velocity vector (V) and the rotational vector (w). is a sum of a component (mj) parallel to the velocity vector and a component (w2) perpendicular to the velocity vector. The axis of the helix will be parallel to w.

protozoa may be phototactic, especially those that contain chloroplasts. Though some protozoa make use of the random-walk methods of orienting to stimuli [106], most protozoa are capable of a somewhat more precise orientation.

Most protozoa swim in a helical path (Figure 13.12). As pointed out by Jennings [113], this may be a way of swimming in a straight line, much in the manner of the spinning of a bullet, because the asymmetry of the organisms would otherwise tend to make them swim in circles. The helical swimming path also allows for an ingenious way of orienting to light or chemical stimuli. The helical movement of the protozoa can be resolved in a translational component and two rotational components, one parallel to and one perpendicular to the direction of motion (Figure 13.12). Theoretically this allows the organism to orient to stimuli if the relative velocities of these components are functions of the stimulus intensity [63,114-116].

FIGURE 13.13 Orientation of a protozoa swimming in a helix toward an attractant. If the angle between Vw and is a function of the solute concentration, the axis of the helix will bend toward the source of the concentration gradient as long as the organism is not swimming directly toward or away from the source.

If, for instance, the angle between the translational and the rotational vectors increases as the organism moves down the gradient, the path of the organism will be bent toward the source of the attractant (Figure 13.13).

Numerous experimental studies have confirmed that this does indeed seem to be the main method by which most protozoa orient to stimuli (e.g., Refs. [106,117,118]). It is not clear however how the protozoa physically change the parameters of the helix. Numerous studies have been done on the reaction of whole organisms as well as on isolated and reactivated demembranated flagellar apparatuses in ambient ion concentrations. Hence, it is well known that changes in the intracellular Ca2+ level have marked effects on the beating pattern and frequency of cilia (e.g., Refs. [119,120]), flagella of flagellates (e.g., Refs. [121,122]), and spermatozoa from completely unrelated species (e.g., Refs. [123,124]). There is little doubt that this universal mechanism plays an important role in the chemo- and phototaxis of protozoa.

What is less clear is the step from the simple reversals and frequency changes observed with changing Ca2+ levels to the complex flagellar or ciliary reactions that are responsible for modifying the helical path and how these are achieved. This is only partially understood and only for a few species. Dinoflagellates make use of the transverse flagellum to control their rotational velocity [125]. Paramecium can alter the parameters of the helix by changing the direction and frequency of the three-dimensional movement of the cilia, the control of which seems to involve also H+, Mg2+, and ATP [118]. Pteridomonas seems to be capable of an accurate three-dimensional control of the axis of the planar waveform of the flagellum, resulting in a very precise control of swimming directions, but this is as yet incompletely understood [44]. For most species, the flagellar and ciliary mechanisms by which protozoa change the direction of the axis of the helix is not known. It is important for our understanding of the microbial ecosystems to gain a deeper understanding of how organisms orient physiologically to stimuli and of the factors that may affect this ability to orient.

Protozoa may react not only to light intensities and chemical gradients but also to gravity. In fact, the ecologically important vertical migrations of many organisms in aquatic environments seem driven as much by gravity as by a reaction to light intensities [126-128]. For most of the last century, gravitaxis was believed to be caused largely by a density gradient in the cell so that the lower, heavier end would passively align with the gravity vector [129-132]. It has been shown however that the ciliate Laxodes is capable of switching between positive and negative gravitaxis without any apparent structural changes in the cell [133], requiring more complicated mechanisms for perceiving gravity.

The asymmetrical shape of the organism may play an important role in the gravitational response of ciliates, and even slight changes in shape may have a profound effect on the orientation of the organism [107]. The prevailing theory today, however, is that at least some protozoa are capable of sensing gravity directly by the cytoplasmic contents of the cell exerting a pressure on the lower membrane, thus activating stretch-sensitive calcium-specific ion channels [105]. This hypothesis is supported, among other things, by the fact that changes in density, but not viscosity, of the fluid can reverse the gravitational response of Euglena [134] and that for this organism, inhibitors of stretch-sensitive ion channels inhibit gravitaxis [134,135]. The precise gravitational response of many organisms may in reality be a combination of this mechanism and shape and density distribution.

The extent to which the ability of an organism to orient to stimuli allows it to exploit patchy resources depends on a number of factors, including how long-lived and far away an average resource path is compared to the swimming speed and navigation abilities of the organism. Based on these parameters, Grunbaum [136] recently presented a simple numerical index, the Frost number, with which it is possible to predict roughly the availability of a patchy resource to a consumer using various forms of biased random walks. The Frost number is based on the mobility of individual organisms, yet provides a powerful tool in understanding ecological processes and first approximations of quantifications such as carbon turnover rates. As with many other aspects presented in this review, this shows how much our understanding of ecological processes can be improved by bringing our ecological investigations down to the level of the mechanics of the individual. Failing to do so will leave our understanding of ecological systems much poorer.

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