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"Man, being the servant and
interpreter of Nature, can do and understand so much and so much only as he has
observed in fact or in thought of the course of nature. Beyond this he neither
knows anything nor can do anything,"
Francis Bacon
Prologue – our best friends and
worst enemiesEons before we came into existence, bacteria inhabited the then-hostile planet Earth. Being the first form of life here, they had to devise ways to counter the spontaneous course of increasing entropy and convert high-entropy, inorganic substances into low-entropy, organic molecules. Acting jointly, these tiny organisms also paved the way for other forms of life by changing harsh physical and chemical conditions on the earth surface and its atmosphere into the life-sustaining environment we now have. With their impressive engineering skills, bacteria enriched the atmosphere with oxygen and loaded the water and soil with nutrients, thus enabling higher organisms to develop and flourish [1-5].
Four billion years have passed, and the existence of higher organisms, including us, still depends on the unique bacterial know-how that converts between inanimate and living matter . This makes bacteria our best friends on Earth, indispensable friends we simply cannot do without. With all our scientific knowledge and technological advances, the ways in which these Maxwell demons act against the second law of thermodynamics are still a mystery.
But, as we know, the same best friends are also our worst enemies. In our rush to free the human race from deadly bacterial diseases we created a major health problem worldwide: bacteria are becoming increasingly resistant to antibiotics. Unaware of bacteria's cooperative behavior and social intelligence, which allow them to learn from experience to solve new problems and then share their newly acquired skills, we set out to fight them with heavy use of antibiotics. As a result, we are witnessing the resurgence of strains of disease-causing bacteria, believed to have been vanquished long ago, only now they come armed with multiple drug resistance and we can't invent new drugs fast enough. To reverse this course of events and outsmart the bacteria we need to develop novel strategies. For this to happen, we must first understand that bacteria are not the simple, solitary creatures of limited capabilities they were long believed to be.
The idea that bacteria act as unsophisticated, solitary creatures stems from years of laboratory experiments in which they were grown in Petri dishes under benign conditions. However, under the harsh conditions in the wild, these versatile organisms work as teams and benefit from the power of cooperation. By acting jointly, they can live on any available source of energy and thermodynamic imbalances the environment offers, from deep inside the Earth’s crust to nuclear reactors, and from freezing icebergs to sulfuric hot springs. We now begin to realize that these most fundamental of all organisms are smart, cooperative beasts that use advanced communication and lead complex social lives in colonies whose populations exceed the number of people on earth [4,6-17]. To face changing environmental hazards, the bacteria resort to a wide range of cooperation strategies they keep in store. One aspect of these strategies has to do with spatial organization of the colony, with the bacteria forming different complex patterns as needed to function more efficiently. The most recent findings shown here indicate that, in the presence of antibiotics, bacteria purposefully modify their colonial organization in ways which optimize bacterial survival It seems that bacteria have some sort of collective memory by which they keep track of how they handled their previous encounters with antibiotic. They know how to collectively glean information from the environment, "talk" with each other, distribute tasks, generate collective memory, and turn their colony into a massive "brain" that can process information, learn from past experience and might even create new genes to better cope with new challenges [18,19].
IntroductionIn this article we reexamine Schrödinger’s reflections [20] on the fundamental requirements for life in view of our new observations about bacterial self-organization and complex patterning, and the emerging new understanding of gene-network dynamics. Focusing on the energy, matter and thermodynamic imbalances provided by the environment, Schrödinger proposed his consumption of negative entropy requirement for life. We take the criteria further and propose that, besides feeding on “negative entropy”, organisms also need to consume latent information embedded in the complexity of their environment [5]. By latent information we refer to the non-arbitrary, spatio-temporal patterns of regularities and variations that characterize the environmental dynamics.
Accordingly, we propose that Schrödinger’s criterion of “consumption of negative entropy” is not sufficient and “consumption of latent information” is an additional fundamental requirement of life. In other words, all organisms, including bacteria, are able to sense the environment and perform internal information processing using natural bioinformatics capabilities. We outline how intracellular self-organization together with genome plasticity and membrane dynamics might, in principle, provide the intracellular bioinformatics mechanisms needed for these fundamental functions.
In regard to intra-cellular processes, Schrödinger postulated that new physics is needed to explain the conversion of the genetically stored information into a functioning cell. At present, his ontogenetic dilemma is generally perceived as solved and his original postulate is attributed to the lack of knowledge –in his time, the pre-DNA era of molecular biology. So it is widely accepted that there is no need for some unknown laws of physics to explain cellular ontogenetic development. We take a different view and in Schrödinger’s footsteps we suggest that, despite the new discoveries about gene-networks dynamics and plasticity (e.g. alternative splicing, RNA editing, small RNA, etc), we still lack a satisfactory framework of explanation for living systems - some principles of self-organization in open systems are missing for understanding how to assemble the cell’s component into an information-based functioning “machine” or a cognitive system.
We continue with a concise description of the notion of thermodynamic machines and compare them to biotic machines. We explain the special role of ATP as the energy currency [21-25] – feeding energy in a specific manner, according to stored information, into specific micro-level degrees of freedom. Next, we present the idea that biotic machines are information-driven and should be viewed as analogous to complex man-made cybernetic systems composed of information-processing systems and of thermodynamic machines. The latter are composed of engines (that provides work) and pumps (that can reduce the entropy). Both are regulated by the information processing systems. Moreover, the biotic machine can also generate new information, assign contextual meaning to gathered information and change its structure according to the task it has to perform. This is why I propose that they should be viewed as cybernetic machines.
Schrödinger’s
Negative Entropy
In 1943,
a decade before the discovery of DNA’s structure, Erwin Schrödinger, one of the
founders of quantum mechanics, ventured into a novel speculation about the
fundamental character of life processes. In a series of lectures, which were
soon published as "What is
Life?" – The Physical Aspects of Living Cells (1945) [20], Schrödinger
postulated that to answer fundamental questions related to “What is Life?”
demanded a new research approach. He
began with a modest apology:
A
scientist is supposed to have a complete and thorough knowledge, at first hand,
of some subjects and, therefore, is
usually expected not to write on any topic of which he is not a life master.
This is regarded as a matter of noblesse
oblige. For the present purpose I beg to renounce the noblesse, if any, and to be the freed of the ensuing obligation.
…some of us should venture to embark on a synthesis of facts and theories,
albeit with second-hand and incomplete knowledge of some of them -and at the
risk of making fools of ourselves. So much for my apology. (Schrödinger 1945, p. vii)
Schrodinger
continued and argued that, despite the vast accumulation of detailed knowledge
about the biochemistry and genetics of cellular processes, the physical
principles that enable them are still a mystery. It seemed to Schrödinger that
some fundamental principle(s) was missing:
Today,
thanks to the ingenious work of biologists, mainly of geneticists, during the
last 30 or 40 years, enough is known about the actual material structure of
organisms and about their functioning to state that, and to tell precisely why
present-day physics and chemistry could not possibly account for what happens
in space and time within a living organism. (ibid. p. 2)
Schrödinger
did warn that seeking such principles “is a rather subtle line of thought,
open to misconception in more than one respect” (ibid. p.69), but went on
to pose the following questions:
What
is the characteristic feature of life? When is a piece of matter said to be
alive? When it goes on 'doing something', moving, exchanging material with its
environment, and so forth, and that for a much longer period than we would
expect of an inanimate piece of matter to 'keep going' under similar
circumstances. (ibid. p. 70)
To explain
how the organism maintains vitality and avoids equilibrium, Schrödinger
formulated the basis of life from the point of view of statistical physics. He
proposed that, to maintain life, it is not sufficient for organisms just to
feed on energy, like man-made machines do. Instead, he argued, internal
metabolism required that organisms must absorb low-entropy energy and exude
high-entropy waste products:
Every process, event, happening –
call it what you will; in a word, everything that is going on in Nature means
an increase of the entropy of the part of the world where it is going on. Thus a living organism continually increases
its entropy – or, as you may say, produces positive entropy – and thus tends to
approach the dangerous state of maximum entropy, which is death. It can only keep aloof from it, i.e., alive,
by continually drawing from its environment negative entropy...(ibid. p. 72)
Photosynthesizing
organisms and chloroplasts satisfy the requirements for feeding on negative entropy
and thus provided Schrödinger with the conceptual apparatus with which he might
explore the unique thermodynamic machinery of metabolism. After all, from the perspective of physics,
the consumption of photons can be viewed as a general principle of living on
imbalances. In this case, the imbalance employed by biotic machines is more
transparent than, for instance, that existing between the sun (the source of
the photons) and the colder earth.
How
would we express in terms of the statistical theory the marvelous faculty of a
living organism, by which it delays the decay into thermodynamic equilibrium
(death)? We said before: 'It feeds upon negative entropy', attracting, as it
was a stream of negative entropy upon itself, to compensate the entropy increase
it produces by living and thus to maintain itself on a stationary and fairly
low entropy level…. Indeed, in the case of higher animals we know the kind of
orderliness they feed upon well enough, viz. the extremely well-ordered
state of matter in more or less complicated organic compounds, which serve them
as foodstuffs. After utilizing it they return it in a very much degraded form -
not entirely degraded, however, for plants can still make use of it.
(ibid. pp. 74-5)
Bacteria
use a variety of available sources of energy and entropy imbalances encountered
in their different environments, from deep inside the earth crust to nuclear
reactors and from freezing icebergs to sulfuric hot springs [26-33]. Using
thermodynamic imbalances, bacteria are capable of converting myriad substances,
from tar to metals, into life sustaining organic molecules. More complex
organisms depend on this unique capacity of bacteria (and of the symbiotic
chloroplast). And, as Schrödinger noted, with all of our scientific knowledge
and technological advances, we cannot design man-made machines to mimic the
ways in which bacteria solve this fundamental requirement for life.
Thermodynamic vs. Biotic Machines
Both biotic and man-made machines use imbalances for their operation, yet there are some essential differences [5,19]. Following Schrödinger, we begin from his perspective of equilibrium statistical physics and show that, even on this simplified level, additional requirements are called for to explain bacterial abilities.
The second law of equilibrium
thermodynamics evolved from a practical quest to improve the efficiency of
steam engines. These engines use the temperature imbalances between the high
temperature (Th) of burning coal and the lower temperature (Tc)
of the environment. Simply phrased,
according to the second law, even an ideal engine cannot convert the entire
amount of heat (energy) dQh from the burning coal
into useful work, as some amount of heat dQc has to be transferred
in the process to the colder environment. Therefore, an ideal machine is
limited in its ability to generate the amount of work dW with
ideal (theoretical) efficiency Є≡dW/dQh,. This result is
derived from the requirement of energy conservation,
dW= dQh
- dQc
and the requirement that the
machine’s internal entropy change dS = 0, where
dS =dQh/
Th - dQc/
Tc .
Other thermodynamic machines operate as active pumps and use energy to operate against temperature imbalances. For example, air conditioners use energy to transfer heat from a cold room into the warmer exterior. Ionic pumps on cell membranes are examples of thermodynamic machines that use energy to transfer ions against concentration gradients.
From the perspective of a thermodynamic machine, each bacterium is a hybridization of two kinds of machines: one uses imbalances in the environment to extract energy, and the other uses this energy to act against the natural course of entropy increase, e.g. for the synthesis of organic substances. Note that the first machine type is equivalent to an engine, while the second functions as a pump that reduces its own entropy. In this fashion, each of the machines performs an open cycle in contrast to the ideal thermodynamic engine that operates on closed cycles, i.e. the system returns to its initial state. In other words, on each cycle the machines can return to a state that is close but not equal to the initial state. As a result, the internal state of the cell, an open system in itself, continuously changes in time.
At present, we are missing a physical theory to describe such situation and can only use equilibrium and close to equilibrium thermodynamics for approximate description over finite intervals of time. And even so, we need an additional assumption about the use of the internal supply of “negative entropy” that is provided by ATP, as we explain further below.
The coordination of the two machines is regulated by utilizing the contextual information stored in the system and the relevant information extracted from the environment during the execution of the cycles. This means that a third – information processing – machine is coupled to the other two machines. Namely, a biotic machine is analogous to hybridization of three man-made machines – a thermodynamic engine, a pump and an information processing system. Note that the pump represents the internal cellular metabolism of synthesis of the organic materials that is similar to a reduction of entropy.
ATP-nano-machinesAs we describe below, to increase the efficiency, the biotic machines can maintain a non-equilibrium (evolving) state where both their internal structure and composition are regulated by internally stored information. In addition, biotic machines have a membrane, which enables them to generate from the external environment internal large imbalances that may be regulated and used when needed. Moreover, the exchange of energy, matter, and information across the membrane is actively regulated according to the internal state and stored information of the biotic machine and the surrounding conditions.
Photosynthesizing bacteria invented an additional operating principle: Low-entropy energy is first stored in transferable packets of usable “currency” – ATP molecules [21-25]. Namely, the photon energy is stored in nano-size coins for ready use. From engineering perspective, these coins are used when and where needed for efficient operation, e.g., they are “injected” directly into molecular engines for movement and into enzymes for reaction. In other words, they are not randomly consumed but are used in a regulated manner.
From physics perspective, the ATP molecules act as nano-machines that feed low-entropy quanta of energy directly into micro-level degrees of freedom of the system. And they do it with a non-arbitrary spatio-temporal distribution. Thus, the process of energy consumption in the living cells is essentially different from what happens in man-made machines in which ordered energy (say, mechanical work) is dissipated homogenously into the microscopic degrees of freedom, giving rise to spontaneous entropy production. Hence, I suggest that an individual bacterium should not be compared to a single man-made machine but to a whole factory composed of many man-made machines and information processing systems that regulate the operation and exchange of energy and materials between the machines. The factory is regulated according to a common “currency” for assessment of the “value” of the raw materials, the “cost” of the manufacturing processes and the value of the manufactured products. The operation is regulated also according to assessment of the state of resources and of the market.
The
Maxwell Demons of Nature
The complementary part of the above picture is that, from physics perspective, bacterial membranes act as Maxwell demons since, using the ATP coins, they exchange energy and matter with the environment in a way that enables them to lower the internal entropy. For that to happen and to fulfill energy and material needs, bacteria developed sophisticated mechanisms to detect and assess (using internal information processing) the various available sources at their location [34,35].
For example, E. coli bacteria have different sets of genes for digesting different sugars [34]. The biological problem is how to activate (express) the right set of genes to digest only the preferred sugar glucose (a better source of carbon) when it is present in the medium. So when the cell is not seeking to digest other sugars, say lactose, a specific gene continuously produces a repressor of the lac gene whose product is required for lactose digestion. Under normal conditions, the lac gene is OFF; the presence of lactose turns the repressor gene off, but this is not sufficient to turn the lac gene on. Other specific genes produce CAP (catabolic activator protein), which is an activator of the lac genes. The glucose enzymes act as repressors for these genes, so in the presence of glucose the expression of the CAP genes is disabled. Hence, the lac genes are expressed only if lactose is present and glucose is not.
From the perspective of physics and information theory, in addition to stored genetic information, an efficient operation of such computation-based consumption requires that the ATP coins be injected in a regulated manner according to the execution of the process. We suggested that ATP provides a “sensory system” for the genome, or in another parlance, the “contextual information” required for function. .
The lac case illustrates what we mean by internal information processing and justifies the notion of intra-cellular cybernetics. A similar "tasting" mechanism is used in other cases of bacterial taxis. For example, photosynthesizing bacteria "taste" light and assess its level to perform photo-taxis towards higher intensity.
Self-Organization:
From Micro (bacterium) to Macro (colony)
An individual bacterium is limited in its ability to sense the environment. After all, it is only about one micron in size; it replicates about every 30 minutes and performs random walk at a rate of about one micron per second. We now understand that these versatile organisms learned to work as a team and benefit from the power of cooperation. Under natural growth conditions, certain bacterial species self-organize into hierarchically complex, structured colonies, containing 109-1012 organisms (Figure 1). The colony behaves much like a multi-cellular organism. As such, it can collect information about the environment over long times and extended distances and process it. Then, it performs distributed information processing to asses the situation and self-organize into different patterns as needed to function better in the encountered conditions.
Remarkably, the bacteria utilize pattern-formation mechanisms that we have begun to understand only in last few decades, mostly through the study of the physics and mathematics of self-organization in non-living systems [36]. The bacteria are literally billions of years ahead of us in their harnessing of pattern formation.
Compared to pattern formation in non-living systems [37], bacterial self-organization involves an additional inherent degree of plasticity: the building blocks of the colony are themselves living organisms, each with internal degrees of freedom, internally stored information and internal assessment of external chemical messages [15]. Efficient adaptation of the colony requires self-organization via cooperative behavior of the individual cells. To coordinate such cooperative ventures, bacteria have developed and utilized various methods of biochemical communication [38-47] in which they utilize a variety of mediators, ranging from simple molecules to polymers, peptides, complex proteins, genetic material, and even "cassettes of genetic information" such as plasmids (cassettes of genetic information that is used in genetic engineering) and viruses.
The
Engineering Skills of BacteriaThe idea that bacteria act as unsophisticated, solitary creatures stems from years of laboratory experiments in which they were grown in Petri dishes under benign conditions. They can be challenged to reveal their tricks by exposing them in the lab to adverse growth conditions mimicking those they usually encounter in their natural habitats. For example, the patterns shown in fig. 1 self organize in response to growth on nutrient-poor and hard surfaces. To cope with this situation, they collectively produce a lubricating layer of fluid that allows them to swim on the hard surface. As they swim, the individual bacteria at the front push the layer forward so as to pave the way for the colony to expand. By carefully adjusting the lubricant viscosity, the bacteria stick together and keep the colony dense enough for protection [4].
Under conditions somewhat more favorable to motion, such as softer substrate, the bacteria engineer radically different classes of colony patterns. In this situation, the branches exhibit macroscopic chirality, always curling in the same direction. Accompanying the colonial structure is a designed genome change: the bacteria are now programmed to become much longer, which helps them to move in a coordinated motion within the branches.
To achieve even greater efficiency, bacteria invented the clever mechanism of chemotactic signaling, in which the individual bacteria send chemical messages to tell their peers in which directions to move. For example, when detecting a rich source of food they call their peers to join the meal by sending attractive chemotactic signals. On the other hand, bacteria that detect regions of low food or harmful chemical imbalances send out a repulsive chemical to signal the others to stay away.
Using these self-engineering strategies, the individual cells collectively manipulate the overall colony organization for the group benefit, as is reflected in the tantalizing colonial patterns shown in Fig.1.
Fig. 1: Patterns of Paenibacillus dendritiformis bacteria form when grown on nutrient-poor, hard substrate. Far from being shapes of mere aesthetic beauty, these colonial structures reflect the self-engineering skills of bacteria. The spreading patterns help the colony access more of the scarce food in the most efficient way under the given conditions. Ordinary branching pattern is shown on the left (a), and the chiral one (with broken left-right symmetry) is shown on the right (b). The top pictures show the colony patterns. Each colony is a few inches in size and has more bacteria than the number of people on Earth. The bottom pictures (c) and (d) show the individual bacteria (the small bars) at the branch tips with x500 magnification for (a) and (b) respectively. |
Clearly, bacteria cannot contain in their genes the
information for creating all the patterns they might need to survive in
unexpected situations. Well, they don't need to; they only need to have coded
genetic information to provide them with the strategic design principles and
the tools for communication, for information processing, and for changing
themselves accordingly. Using these tools, they can design new creative shapes
[4,6,15-17].
Higher ComplexityBacterial engineering creativity is further
manifested when forced to grow on very hard surfaces. The colony is now formed
from new building blocks – the vortices shown in Fig.2. It becomes much like
multi-cellular organisms, with cell differentiation and distributed tasks.
Fig. 2: Patterns of the Paenibacillus vortex are formed during growth on very hard surface. In these colonies (a), foraging vortices of rotating bacteria shoot out to conquer the hard agar, lubricating the way for their followers. The dynamics is fascinating: a vortex (b) grows and moves, producing a trail of bacteria and being pushed forward by the very same bacteria left behind. At some point, the process stalls and this is the signal for the generation of a new vortex behind the original one; the latter leaves home (the trail) as a new entity toward the colonization of new territory. |
Functional
Complexity – Higher complexity for Better AdaptabilityThe ongoing communication-based interplay between the bacteria as individuals and the same bacteria as part of the colony leads to the emergence of the observed colonial patterns. As the individuals increase their adaptability to the group, the colony elevates its durability and adaptability to the environment by increasing its complexity. The essential new lesson learned from bacteria is that colonial higher complexity provides the flexibility required for better adaptability of the colony as a whole to harsh environments. The bacteria cannot store in their genes all the information required to create the colonial patterns. In the new picture, they do not need to since the required information is cooperatively generated as self-organization proceeds.
These remarkable capabilities led to the notion of functional complexity. The idea is that the complexity of the colony organization is not arbitrary but has biological function. I have suggested [4, 15] that, under stress, the bacteria are able to purposefully modify (re-engineer) their colonial shape to better adapt to the encountered stress. In other words, bacteria utilize the high complexity of the colony structure for elevated adaptability. This higher complexity for better adaptability principle is manifested, for example, when the bacteria are exposed to non-lethal levels of antibiotics [4,15-19,48] (Fig. 3).
Recently it has been suggested that bacteria possess (epigenetic) memory, which enables them to keep track of how they handled previous encounters with antibiotics. In fig 3 we demonstrate that indeed bacteria are able to cope better upon second encounter with the same antibiotic as if they learn from past experience.
Fig. 3: Learning from experience The observations show the response of the P. vortex bacteria to non lethal levels of Septrin. In (a) we show the normal growth pattern in the absence of antibiotic. The effect of first exposure of the bacteria to the antibiotic is shown in (b) and the response in a second encountered is shown in (c). In response to the antibiotic stress, the bacteria intensify chemotactic attraction to form larger vortices. This clever strategy protects the bacteria, since the antibiotic is diluted in larger vortices by the lubricating fluid excreted by the bacteria. At the same time the bacteria also enhance their repulsive chemotactic signaling to push the vortices faster away from the encountered antibiotic. The “higher complexity for better adaptability” is manifested in the fact that the growth pattern in (b) has lower complexity in comparison to that in (a). Learning from experience (c) is manifested by the fact that upon second encounter with the antibiotic the colony expands faster and the pattern has higher complexity. |
The above are just a few examples how, using communication, bacteria can lead rich social life for the group benefit [14]. They maintain the colony integrity by sharing information exchanged via chemical messages. They can develop collective memory, use and generate common knowledge and learn from experience to improve themselves. The ensuing communications are nothing less than a dialog, which gives the colony means for purposeful alteration of structure and decision-making. Should this be called bacterial intelligence [15]?
Epilogue – How we can outsmart the bacteriaThe use of the term “bacterial intelligence” reflects the emergence of a new paradigm in which these features are perceived as the fundamental (primitive) functional elements of cognitive functions that any living system must possess [15]. The new paradigm, if correct, implies that the combined intra-cellular gel and the genome should have certain cybernetic (computational and self-alteration) capabilities that are required to sustain the elements of bacterial cognitive functions [4,5,15-19,49]. Overlooking the special group capabilities of bacteria, we made a colossal mistake – the hasty use of antibiotics for people and especially in agriculture [16]. Now we understand that by doing so we led to a surprising evolutionary phenomenon in the microbial world [18]. New strains of more sophisticated bacteria are rapidly appearing. These new strains have multiple drug resistance and, moreover, can learn to develop resistance to new drugs at an alarming rate. In effect, what we did is to boost bacterial intelligence by forcing them to cooperate and challenging them with increasingly harder problems to solve (advanced drugs to cope with). Only by understanding the foundations of bacterial intelligence will we be able to outsmart them and protect our health. For example, we should not wait for resistant strains to appear following the use of antibiotics and then try to develop new antibiotic drugs to replace the old ones; it may be too late! Instead, we should use the old war strategy of cutting the enemy communication lines, or even confuse it by sending wrong messages. Doing so, we will render the bacteria more vulnerable to the antibiotic drugs, which will allow us to use lower doses. At the same time, in the absence of communication, the bacteria will not be able to process information to redevelop new resistant strains. A simple and direct way to interfere with communication could be by blocking the receivers (membrane receptors) they use for reading the incoming chemical messages. Or we can block the transmitters (membrane channels) used by the bacteria for broadcasting the chemical messages. Having dealt with the destructive aspects of bacteria, we can now consider how to exploit their constructive capabilities. As an example, let us take Geobacter, microbes that like iron, and dislike oxygen. They also have the interesting ability to transfer electrons into metal, that is, to produce electricity while processing waste. These bacteria have even been shown to be able to generate electricity by decomposing body waste. Obviously, building bacterial power plants that can convert wastes to usable materials and at the same time produce electric power is almost like a dream come true. However, letting the bacteria do the magic at a pace that suites their needs is far too slow for ours. We cannot force the bacteria to work harder, but we can use their own intelligence in order to trick them into doing so. Suppose we'd like the bacteria to produce some particular enzymes at a higher rate (e.g. needed to decompose pop, process sugar into alcohol or any other need) or some human hormones (e.g. insulin) or any other useful material. We can prepare a plasmid that includes both the genes for production of the material we’d like the bacteria to make for us and genes for resistance to a specific antibiotic. Now, if we expose the bacteria to this antibiotic they will make many copies of the plasmid to protect themselves from the antibiotic and as a byproduct they will also make the substance we want. This illustrates how we can use bacterial skills to work for us once we understand the essence of bacterial intelligence. AcknowledgmentsThis manuscript is based on several conceptual papers (see references below) published with H. Levine, Y. Shapira and F. Tauber. It is supported in part by the Tauber Fund through the Foundations of Cognition Initiative.
Supplementary
reading material
Additional
relevant publications, pictures of bacterial colonies and video clips of
bacterial movements can be found at my Home page http://star.tau.ac.il/~eshel/
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[] Some plants
and algae use chloroplasts for photosynthesis. It is now understood that
chloroplasts like mitochondria (the organelles in eukaryotic cells that provide
energy) are former symbiotic bacteria.
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