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Profile of Anthony Trewavas
Molecular Plant Pioneer’s Profile
Profile of Anthony Trewavas When asked to write on my experience in science and give some background, it sounded remarkably easy at first. In fact, it has proved very difficult. Apart from the short introduction below, I decided to write on four topics to which I have made a minor contribution. These are used to illustrate how I often fumbled my way through research and the ideas that I found fascinating. Investigation is never a direct path but a road full of obstacles. I have had several benefits in my scientific life. My surname is unusual (it comes from the southwestern tip of the UK, Cornwall), so I was never confused with anyone else. I graduated in biochemistry, a course full of mathematics, physics, and chemistry, I have never been afraid of equations, unlike many biologists. But my primary benefit has been the influence of others, including a brilliant schoolmaster who enthused me about plants. Another crucial lesson was from a little-known PhD supervisor, Eric Crook. He taught me to ignore what the author of an article thought but instead to look at the data and draw one’s own conclusion. I have as far as possible always done that and occasionally it has caused trouble with people who say that my references are inaccurate because they do not say what I claim. My response: look at the data; draw your own conclusions, not the authors. The third influence, Professor Jack Hanson, will figure later. I have been blessed with some remarkable postdocs and postgrads; many of these needed no more than a nudge in the right direction. Often, they just came in and did their own thing, leaving me to explain to grant-giving authorities why we had not bothered with what was approved. They have been the real pleasure in research; many are now independent creative scientists in their own right. I do regard the present grant-awarding situation, or at least as it was a decade ago, as totally inimical to anything creative. Having one’s grant being hawked around, so everyone knew supposedly what you were doing, is the last way to get people to strike out, follow their nose, and try completely risky things. Scientists need to be trusted and given their head. If they waste money, do not give any more, but no one should have to waste 3 to 4 months every year to try to winkle peanuts out of government research authorities. The grants that are awarded, in my experience, tend to be safe and uncontroversial projects; the opposite of what is needed. I have always been a research gambler: nothing gained without serious risk. I used what grant money I had for things I regarded as priority, not what committees thought. The worst way to get any sensible decision is to ask a committee. Science definitely benefits the communities economically in which it is practiced. In my scheme, some will waste awarded money, but that would be the price paid for the rest, because others freed of constraints will take the necessary risks that cut through limitations in knowledge. Everyone benefits. I wonder if Bill Gates or Steve Jobs ever wrote a grant application.
In my career, I have met, corresponded, and collaborated with many thousands of individual plant scientists. They too have invariably been courteous and helpful and made my life as a scientist an enormous pleasure. They too contributed each in their own way. Ideas are central to science; they brought me into research. But again I have not left out experimental material either. So let battle commence.
BIOLOGY IS A SYSTEM OF SYSTEMS I have always looked for things that give that damascene moment (there is another later), and my first reading into systems was certainly that. In 1972, I had purchased a short book by von Bertalanffy (1971). It completely changed my way of thinking and transcended anything I had read before. But I had been primed. At school, one of my prizes was a small book on steady-state thermodynamics (Denbigh, 1951), which illustrated unusual behavior when chemical reactions were coupled together and away from equilibrium. As an undergraduate, I had read Biochemical Individuality by Williams (1956). This book, surely required reading for any biologist, taught me to mistrust averages. Individuals are not the average and in behavior as in evolution, the individual is king. Any individual organism is a complex system and organisms survive enormous degrees of cell and tissue variation by virtue of that fact. Having read von Bertalanffy, I searched the Edinburgh library for more. Economic, social, and management systems emerged, much of it hypothetical, but it got me in the way of thinking. I also followed the history back as far as possible. When I received an invitation to write for Plant Cell in 2006, I sorted through the pile of articles I had accumulated, then about a meter high, and published some of what I had learnt (Trewavas, 2006). Systems investigations reached mainstream biology in 1990 and are now common in the literature. I had also joined the University of Edinburgh in 1970. The crucial article by Kacser and Burns on the same campus and using systems approaches was published in 1973. It taught me all I needed to know about sensitivity analysis. Finally, Conrad Waddington occupied the genetics Chair at Edinburgh, and his last book (Waddington, 1977), was based entirely on systems understanding. My copy is much thumbed and I have often quoted from it. My first use of systems came in Trewavas (1981) in the arguments about hormones and in Trewavas (1986), I illustrated a complex amino acid biosynthetic pathway as like a simple neural network. Published by the Molecular Plant Shanghai Editorial Office in association with Cell Press, an imprint of Elsevier Inc., on behalf of CSPB and IPPE, SIBS, CAS.
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Molecular Plant A Common Example of Systems Present-day biology uses systems approaches as a tool to investigate cell organization and behavior. I introduce it in a different way and illustrate its properties. The plant science community is a fine example of a dynamic, fully functioning, and self-organizing system. By system is meant a network, a recognized structure constructed from thousands of individual researchers connected in some way to many others by differing forms of communication. The connections are published articles, refereeing grants and articles, meetings, direct communication and collaboration, technique training, email, and sometimes, books and journals. The community acts like an integrated whole. Meetings are like the beehive dance floor: there is direct exchange of ideas and information. Some connections are strong; collaborators and those working on an agreed goal synergize each other. Other connections are weaker and may simply reflect related fields. The system is dynamic in that it sees progress on a variety of fronts and that provides enormous flexibility. The process, called distributed control, is common in self-organizing systems and enables a moderate degree of independence of individual research areas. The system phenotype is plastic; it can extend when needed into different branches as more researchers are drawn into particular exciting issues. Advance takes place at different rates in different areas of knowledge. Furthermore, our system is definitely self-organizing. Researchers to a large extent choose their problems for investigation and become part of the system once the choice is made and research commences. This system has a recognizable structure too; it is composed of hubs and connectors, as first described by Barabasi (2002) for other systems. Hubs have lots of connections; connectors fewer. Small world is another similar, but not identical, descriptor. Hubs are those investigators that receive larger numbers of citations, publish frequently, receive more grant money and invitations, run larger groups, collaborate more, and in meetings acquire larger audiences. Connectors (sometimes termed edges) with fewer connections are composed of those hopefully on the way up. Commonly, these are postgraduates and postdocs who in due course hope to acquire hub status. Other edges are those who chose instead to investigate the essential but more obscure areas of the subject. The numbers of connections to each individual follow a power series. There are few with many connections and many with few. Hubs and connectors between them construct a hierarchy that stabilizes the whole. Negative feedback stabilizes certain areas of research for considerable periods. As scientists retire or go into administration or other career opportunities, their specific research area is replaced by others. There is also feedforward, resulting in amplification. An area in which I worked, cytosolic calcium, is a case in point. Within a decade, it went from one or two researchers to hundreds (Hepler, 2005). The system then stabilizes at a higher level for periods of time as freely available personnel, technical limitations, and easily gained results constrain investigation expansion. Emergent properties are a consequence of connection. They are unique properties, which are not expressed by the individual on 346
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Pioneer’s Profile their own. Synergism between researchers is an obvious example. Common scientific themes that emerge in research are another. Many individuals and published research articles together construct an accepted new understanding, which is used when constructing experimental approaches or writing grant applications. I regard them as similar to Dawkins’s memes; they tend to be stabilized through negative feedback by grant applications, research articles, and reviews. The meme is improved as new results emerge and evolves similarly to Wright’s (1982) adaptive landscape of hills and valleys. The fitter memes move toward successively higher hills. Von Bertalanffy’s contention was that all systems have shared structures and properties. From cells to ecosystems, similar organizational properties emerge as they do in economic and social systems. Power series, feedbacks and feedforwards, connections, emergent properties, and hierarchical structures are all found in the hundred thousand or so different kinds of proteins inside cells. They are also present but less obvious in ecosystems, in which overall the connections are weaker. The individual plant is also self-organizing, with recognizable distributed control and a hierarchically constructed system that shares all the properties described above. The strength of connections between the parts of the system is key to its overall character. These change with time and are the means whereby the system is altered. In our plant research system, they reflect the waxing and waning of either specific research interest or group involvement. Individual plants experience changes in communication, altering the strength of connections between tissues. Is it not time that the system nature of the individual plant was illustrated and actual strength of connections measured? In cells, posttranslational modifications are a primary means for changing the connection strengths. When enough have been changed, the system undergoes a rapid transition to another new relatively stable system. For scientific memes, young radicals with differing ideas replace the old and conservative; time and the grim reaper become the motive force of change.
PLANT HORMONES AND GROWTH In 1964, I moved to the new University of East Anglia and continued research from my PhD thesis on auxin effects on protein synthesis, the frontier at the time. The Holy Grail was the belief that auxin would selectively alter transcription. It was not difficult to demonstrate changes in RNA and apparent specific changes in proteins that I found, as did others. But there was a difficulty in interpretation. If cellular proteins had different turnover rates, a generalized increase in protein synthesis would see apparently very specific changes, led by those with high turnover. There was no literature in growing plant cells on actual protein and RNA turnover rates and, apart from cell death, no indication of any turnover. The problem required unambiguous measurement of separate rates of protein synthesis and degradation. It was suspected at the time that 90%–95% of the amino acid in a plant cell was in a large metabolically inactive pool, possibly but not certainly in the vacuole. The likely precursor pool for protein synthesis was small and potentially rapid in turnover and thus completely swamped in whole tissue analysis. It took 3 years to develop unambiguous methods for discriminating these pools and to obtain genuine rates of synthesis and
Pioneer’s Profile degradation for both proteins and in turn nucleic acids. Both had overall average turnover rates of about 3 days. The importance of compartmentalization was what I learnt, a lesson not applicable just to protein synthesis. In the decade from 1970 onward, research on plant hormones concentrated largely on accurate chemical quantitation from whole tissue extraction. Most hormones had been identified by the simple procedure of adding hormone to tissues and getting an effect. Thus, the supposition that endogenous changes in hormone content would control development and measurement would reveal this to be the case. But my own research experience told me that cells were compartmentalized and the problems experienced with protein turnover were just as likely with hormones. Simple whole tissue extraction could fatally compromise the real meaning of results; the estimates would make sense only if they were in the same compartment as potential receptors, although no receptors were known at the time. There was certainly evidence at the time from using radioactive auxin in transport experiments that at least half ended up in inactive, untransportable pools. Furthermore, I had learnt of the importance of sensitivity (emphasized by Kacser and Burns, 1973). Sensitivity is a systems property dependent in part on everything else. Its measurement required tiny changes in amount to see whether a corresponding tiny change in response occurred. It was the ultimate arbiter of meaning in changes of concentration. In 1981, I published a critical but invited assessment of current plant hormone research (Trewavas, 1981). It was not difficult to point out that many such hormone content measurements did not correlate with the change in the rate of the process that they were supposed to control and that endogenous sensitivity was the one measurement that might make more sense. The effect of publication of the article was most certainly controversial. Warring camps seemed to develop for and against the article, and my promotion was actually blocked by one of the opponents. I received over 620 reprint requests in just a few weeks and I only had 100 reprints; there was no email at that time. These days, mutation of hormone synthesis can be used to drastically change concentration. Kacser and Burns (1973) had emphasized in their estimates of metabolic sensitivity that only tiny incremental changes in amount should be used. That needs to be noted. I did find some results (coleoptiles with auxin, leaf development with gibberellin) in which endogenous sensitivity in intact tissues could be estimated. These suggested that changing hormone content was not a particularly sensitive control, something that still needs further investigation. One problem much discussed at the time was that doseresponse curves, measuring tissue or cell response to added exogenous hormone, were rather wide (3–4 orders of magnitude for a 10%–90% expression of response). For cells in a single tissue (e.g. guard cells), noise in the protein synthesizing machinery may be responsible (Trewavas, 2012). But for groups of plants or plant tissues, it may in addition reflect an ecological requirement. Individual plants should vary enormously in their capability to respond, because of the uncertain environment into which the seed is cast and that the individual must put up with. This is a clear case of bet hedging. But its specific origin remains uncertain.
Molecular Plant Hormones Act to Synchronize or Coerce Heterogenous Cells into Development One spin-off of the 1981 article was numerous invitations to write elsewhere. In Trewavas (1982), I added an extended appendix on the cereal aleurone and gibberellin. A system little used now, but then the subject of hundreds of articles. The classic view was that during germination, the growing embryo synthesized gibberellin, which diffused to the viable aleurone cells surrounding the endosperm. The synthesis and secretion of amylases were induced. On diffusing into the endosperm, sugars and amino acids were released, provisioning the growing embryo. There was a huge amount of conflicting and contradictory evidence for and against this classic view, and those interested can read it all; little has changed. Aleurone cells do have to acquire sensitivity or responsiveness to gibberellin, and this could take up to 24 hours after imbibition. When cereal seeds were treated with exogenous gibberellin concentrations, however, overall amylase production was not increased, but its appearance occurred earlier; synthesis was accelerated but the duration of synthesis shortened. Exogenous gibberellin was acting to synchronize amylase production, although authors failed to recognize it. At that time, the classic synchronizing system was the cultured cell cycle (Smith and Martin, 1973). Resting cells were in G0, but there was a certain probability that they could cross a threshold and enter a deterministic G1 phase and replicate. Cells were thus in an all-or-none situation: either they replicated or they did not. Although G1 lengths could be variable, the rates of cell division reflected the probabilities with which individual cells crossed that threshold and thresholds were statistically distributed. Adding factors to increase cell replication rates simply brought less sensitive cells into replication earlier. The nature of the threshold was suggested to result from controlling proteins of very low copy number, in which large variations in synthesis potentially due to noise were to be expected, but no doubt, it is more complex. The realization that gibberellin synchronized amylase production led me to search for additional hormone synchronizing systems in the plant literature. I identified a number and published the observations in various articles. These were fruit ripening and abscission in response to ethylene; the after-ripening response of Avena fatua seed to gibberellin (after-ripening is simply achieved by acid; auxin storing dry seed for a year); stomatal aperture and abscisic and adventitious root formation. Later on, Kent Bradford (Davis, California) sent me a publication indicating that he had independently observed similar synchronizing behavior in the kinetics of tomato seed germination and gibberellin. We then published a joint significant article (Bradford and Trewavas, 1994). One of my former students, Simon Gilroy, demonstrated beautifully the all-or-none response of amylase secretion using aleurone protoplasts. Each cell produces only a predetermined number of amylase molecules. More amylase, more cells synthesizing. Added exogenous gibberellin simply brings forward less sensitive cells into production; the period of development is thus shortened. I suspect that all plant hormone effects on development follow this pattern, with a threshold passed only on a probability scale. The threshold once passed enables the cells to become sensitive Molecular Plant 8, 345–351, March 2015 ª The Author 2015.
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Molecular Plant to hormone. If hormone is already present, as it commonly is, then entry by individual cells into developmental change will initially be sporadic. The probability of transition has its most interesting consequences in cell extension. In both stems and roots, there are zones of cell division in the extreme tip, followed by a defined zone of extension known to be auxin sensitive; here extension growth rate rapidly increases to a peak and then decreases. Extracted auxin concentrations do not mimic this variation. As cells leave the division zone, there will be a probability of transition to become auxin sensitive and to construct the cell apparatus for cell extension. Once constructed, the elongation program will be maximally expressed because it is all or none. The actual rate of elongation in any part will be determined by how many cells have made the transition, and the decline by how many cells have completed their elongation. Extension rates are initially small, because only a few cells have made the transition and become auxin sensitive; their extension growth is constrained by others as yet unchanged. When elongation rates are much higher, it is because many more cells have made the transition to the elongation program. Exogenous auxin added at this time will bring forward more cells into the elongation phase and accelerate growth rate. But correspondingly, it will accelerate the rate of decline too. Both the 1981 and 1982 articles contained figures that show this clearly. A zone of transition probability will precede elongation itself. Some authors have pointed to the rather special features of these cells (Ishikawa and Evans, 1993; Baluska and Mancuso, 2013).
THE ROAD TO CALCIUM How I ended up working on cytosolic calcium is a tale of total accident, uncertainty, luck, and serendipity. I went to the University of Edinburgh in 1970. Within weeks the Head of Department (HOD) called me together with John Ingle (working on DNA) and Chris Leaver (working on RNA). After short talks from both of these, the HOD turned to me and said ‘‘I am not having competition in this department; go and find a project on proteins.’’ Photolabile, azido crosslinking groups had very recently been described, so I outlined synthesizing and using azido auxins to pick up receptors. The HOD was keen at first, then came back several hours later and said no: no reasons were given, but it was lucky for me. When I went to Urbana in 1980, azido auxins and a number of others had been synthesized there, and Alan Jones (recent President of the American Society of Plant Biologists) had been using them. But instead of the hoped for one or two proteins, they turned out to be rather promiscuous labeling agents. I had unknowingly avoided what might have been a waste of many years. Part of my PhD had raised the issue of protein phosphorylation. My supervisor had heard a lecture that outlined the relationship between cyclic AMP, protein kinase, adrenalin, and phosphorylase in liver cells: Earl Sutherland’s enormous breakthrough. So it was suggested I try the effects of auxin on phosphorylase, and I naively agreed. One year later, with completely negative data, I realized that there was a world of difference between plants that had buckets of carbohydrate swilling around them and organisms that did not. Thinking first would have been helpful. 348
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Pioneer’s Profile But in looking at the literature in 1970, there was an astonishing nothing on protein phosphorylation in plant cells, so this was chosen. The aim was to use this direction as a route to answer questions about plant cyclic AMP. Polyribosomes were first chosen for investigation, because they could be easily purified on sucrose gradients; cell fractionation was still primitive then. Within a year, I had identified a single phosphorylated ribosomal protein attached to the small subunit with phosphorylation on serine; within another year, an attached protein kinase. Frustratingly, the activity of this kinase was unaffected by everything that was thrown at it, including cyclic nucleotides and calcium. To rub salt in the wound, I received a letter in 1973 from Ira Wool (Chicago), who had found a phosphorylated protein in the small ribosomal subunit of animal cells of identical molecular weight. His attached protein kinase was cyclic AMP dependent. Cyclic AMP has been the black sheep of the plant signaling family; surprising, because many other signaling molecules found in animal cells are used in plants (Assmann, 1995). Skepticism about cyclic AMP in plant cells was certainly rampant in the early 1970s. Well-performed assays of extracts from whole plants placed it below detectable levels. However, the article published with Rui Mahlo in 2001 (Moutinho et al., 2001) established beyond reasonable doubt that it was both synthesized in pollen tubes and functioned in growth polarity. Cyclic nucleotide gated channels, which have been clearly identified in plant cells, probably mediate pollen tube growth effects. The failure of Ca2+ to have any effect on this protein kinase (I found it slightly inhibitory) did not bother me at the time, since like cAMP, I had come to believe that this was another mechanism found only in animal cells. I had done crude cell fractionations and found protein kinase activity everywhere but no response to cAMP or Ca2+. So the search was continued for other significant changes in nuclear protein phosphorylation (and thus hopefully protein kinase control). About 50–80 such proteins in plant cells were detected using 2D gels, and some specific changes were found to be associated with plant cell division, particularly in histone H1. At that time in 1980, I had considered and rejected attempting to purify protein kinase, but which substrates could be used? Most kinases will phosphorylate casein or histones. That was a lucky choice again. With 1000 protein kinases in plant cells, this would probably have been another dead end. But the change came when I went to Urbana, Illinois to do some work with Larry Vanderhoef (later President of Davis, California), who disappeared within a few weeks to promotion elsewhere. Instead, I spent some of the time talking and writing an article on plant growth with Jack Hanson. He urged me to look again at how I had estimated protein kinase activity, because he had observed very rapid effects of Ca2+ on root growth and thought protein kinase control would be a good explanation. Furthermore, a calmodulin-like molecule had been identified in plant cells a year before. I went back through the literature, rereading furiously. It was very humbling; I had thought foolishly that double-distilled water would be free of calcium. It most certainly was not; use of EGTA was the critical key to set known Ca2+ free concentrations, an obvious damascene moment. Back at the bench and using crude
Pioneer’s Profile membrane preparations again, a 5- to 6-fold increase in phosphorylation was easily detected and maximal at 1 mM free Ca2+; in fact, this kind of kinase activity seemed to be in all cell fractions. Hepler (2005) described in excellent detail the slow and hesitant appreciation of the use of cytosolic calcium in plant cells, which accurately describes my own fumbling at the topic. The meeting I organized in Edinburgh 1985 on molecular and cellular aspects of calcium in plant development was a watershed (Trewavas, 1985). Numerous discussion periods highlighted in particular the necessity for both unambiguous measurements and imaging of cytosolic Ca2+ in plant cells. I decided there and then never to look at a dead cell again and to accept that challenge. If we needed to measure the concentration of any molecule or manipulate its concentration, a suitable probe would have to be constructed for imaging in live cells. In addition, caged compounds could be introduced and released by photolysis. Caged hormones and caged EGTA were both later used, with significant outcomes (Shacklock et al., 1992; Allan et al., 1994). The notion that Ca2+ distributions inside cells could be imaged was extraordinary but absolutely essential to understanding. The plant cell cytoplasm is highly differentiated, and Ca2+ is not a mobile ion in the cytoplasm. Imaging where and when Ca2+ is elevated could provide superlative information on where the cytoplasm is activated and the source that gives rise to elevation. Roger Tsien (later Nobel Prize winner) had in the mid-1980s designed suitable dyes for fluorescence ratio imaging and described equipment he had constructed for the purpose. These days, the equipment can be bought off the shelf, but it took us (Simon Gilroy, Mark Fricker, and I) from 1987 onwards, 3 years, and three grants to construct our own, with a very steep learning curve. Once constructed, imaging of cytosolic Ca2+ was used for guard cells, red light-responding protoplasts, and pollen tubes; it revealed how local cytoplasmic Ca2+ signaling controls whole cell behavior and that the vacuole in particular was one source of Ca2+ responsible for elevating cytoplasmic levels (Gilroy et al., 1990; Shacklock et al., 1992; Malho and Trewavas, 1996). The growing pollen tube continued to be a source of fascination and was continued later by Maasaki Watahiki, many of whose excellent studies remain unpublished. Maasaki showed using highly focused flash photolysis that a tip located Ca2+ sensitive protein kinase moves with extraordinary speed to the flanks and must recycle back. A further pollen tube protein kinase was also located attached to cell wall containing vesicles, which appeared to be in vast excess and which fluctuated in position at enormous rates. What I did want, however, was a simple method for measuring whole plant cytosolic Ca2+, and this came with the use of the Ca2+ sensitive luminescent protein, aequorin. In the jellyfish, from which aequorin is obtained, it is found together with GFP. But aequorin is composed of an apoprotein and the luminophore, coelenterazine. The protein could be expressed by transformation, but all that could be done with the luminophore was to incubate the tissue in it and hope aequorin would form. In 1990, it seemed an enormous gamble, and I had a second fallback project available, but work it did, due solely to Marc Knight, who got the technique up and running (Knight et al., 1991). The exquisite touch sensitivity of plants exemplified by immediate
Molecular Plant cytosolic Ca2+ transients lasting 10–20 seconds dropped out immediately. We used this aequorin method to report on the effects of blue and red light, tropic bending, circadian processes, wind, osmotic pressure, cold and heat shock, and fungal invasion. The luminescence was imaged too, showing transmission of Ca2+ waves across tissues, and targeted to some cell compartments, indicating separate organelle (nucleus and chloroplast) control. The technique is very simple and has been used by hundreds of laboratories. Cytosolic Ca2+ is now an established, ubiquitous, second messenger in plant cells.
PLANT BEHAVIOR AND INTELLIGENCE The final piece in this article is most certainly controversial again and best introduced with two quotations. From plant biologist Barbara McClintock in her Nobel Prize acceptance speech: ‘‘A goal for the future would be to determine the extent of knowledge the cell has of itself and it uses that knowledge in a thoughtful manner when challenged.’’ The response to challenge is behavior, and thoughtful responses are clearly intelligent. The commonest descriptor of intelligence among those who have studied the subject is that it involves problem solving, and a capacity for problem solving best indicates the variability in this quality between individuals. In 1937, Went (the discoverer of auxin) and Thimann published the first book on phytohormones, now regarded as the Bible of auxin effects. On page 151, ‘‘However in tropistic movements, plants appear to exhibit a sort of intelligence; their movement is of subsequent advantage to them.’’ Advantage directly implicates fitness, the ultimate evolutionary criterion and experienced only by wild, not laboratory-grown, plants. Fitness is a life cycle assessment, and seed number represents a simple proxy. Throughout their life cycle, wild plants experience environmental situations in which decisions about costs and benefits have to be made. Usually, these concern the distribution of limited resources, but there are also environmental impacts to be dealt with. Many of these do not come in nicely packaged quantities but are often chaotic in appearance. Decisions involve an assessment that incorporates past experience (the potential reason for the decision in the first place) and the future (the consequence of taking one course of action rather than another). Assessment is the same as McClintock’s ‘‘thoughtful’’ manner, which I consider intelligent too (Trewavas, 2014). Because of predation, animals evolved separate sensory and motor systems and joined the two with a fast transmission connection, the nervous system. With increasing complexity, the nervous system began to act as an assessment, learning, and memory system, where it resides today. Because plants lack a defined nervous system, assessment involves the whole organism, requiring complex and interactive communication. Plants do use electrical controls, most recently indicated in the development of herbivore resistance, but it is clearly less elaborated. Plant hormones, proteins, peptides, RNAs large and small, and other molecules combine together in whole plant communication to provide for assessment in ways simply not understood but essential to fitness. To me, assessment is obviously a complex system property, involving communication throughout the plant, and is surely a challenging frontier for those prepared to take it on. It is why I have argued for plant intelligence. Molecular Plant 8, 345–351, March 2015 ª The Author 2015.
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Molecular Plant Self-organization is another critical property that characterizes the development of the plant phenotype. There is no overall controller dictating development according to a predetermined plan. The phenotype develops instead as a result of interactions, simple communications, between the constituent parts. The elements of communication then change with time and size. To try to understand plant behavior and intelligence, clues can be obtained from other self-organizing systems in biology. The human brain itself, surprisingly, is one such, but the most useful are social insect colonies, where their behavior is described as swarm intelligence. Colonies function by interactions between the constituent organisms to construct a system. The colony self-organizes, grows by increasing constituents and accumulated resources, and uses negative feedback and feedforward controls; size plays its critical part too. Colony growth is slow and a consequence of numerous activities that take place on a shorter time scale. The colony behaves like a single organism, but its phenotype is plastic, the consequence of distributed control; parts can act locally to specific signals that benefit the whole. Does that all sound familiar? I think there are some remarkable organizational analogies between colonies and plants. The organization and behavior of the colony should help understand the organization of plant behavior! Bee colonies have a central area, in which much information is exchanged, leading to changes in colony behavior; it is known as the dance floor. I think the cambium has an analogous function in growing plants. As a tissue, it is like an internal skin and thus has the potential to transfer information throughout itself. In growing plants, shoots (branches) compete with each other for root resources. The cambium is in a position to assess the relative performance quality of each shoot. Current evidence suggests the cambium controls root resource demarcation by increasing the number of vascular elements to those shoots growing vigorously and by blocking some or all of the vascular elements to those contributing less or nothing. Changing root resource distribution involves both feedback and feedforward, and these critical control elements are also involved in enabling leaves to maintain a relatively constant temperature. It is thus surprising that in tissue bending so much emphasis is placed just on auxin, when the growth kinetics of many individual roots illustrate clear negative feedbacks. The controlled diversion of shoot resources can be expected to underpin the root phenotype. When environmental situations change, those plants that exhibit greater plasticity can learn to successfully adapt their behavior more quickly. In itself, that implies a potential to assess possible future circumstances. Phenotypic responses are commonly slow, like colony growth. The most difficult situation arises when the reason for environmental challenge has disappeared before the new phenotype has appeared. On the other hand, if this environmental change is maintained or is repetitive, this should promote selection of those individuals whose progeny develop the relevant characteristics with greater rapidity, higher probability, or lower cost. Later selection thus ratifies an adaptation that has already been tested through genetic and/or epigenetic means. When faced with environmental change, the behavior will thus either be interpreted as insight or an uncanny ability to predict future events. 350
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Pioneer’s Profile Darwin considered that competition between individuals was fundamental to selection. Competition is a primary challenge that faces all wild plants, and game theory is designed to understand its basis. Competitive plants become part of the system structure of the plant, like all facets of its environment. The ‘‘prisoner’s dilemma’’ is undoubtedly applicable to the interactions between plants and associated microbes, and individual plants have mechanisms to deal with cheating partners (Trewavas, 2014). But clearly, competing against oneself would be disadvantageous. Experimental evidence using a number of species indicates that plant individuals do distinguish between themselves and other alien individuals and thus are capable of forms of self-recognition. The shade avoidance syndrome results from competition between individuals for light. But it is as much about denying light to competitors as counteracting the physical characteristics of shade. Root proliferation in N and P rich patches, although increasing resource uptake, is also designed to deny these resources to competitors by removing them first. Decisions are inherent in game theory and require individuals to learn about the competition and to remember it for considerable periods. In nonneural organisms, learning starts with the perception of a stimulus, and the chemical and physiological trace of the transduction chain represents its memory. The commonest pathways use cytosolic calcium; subsequent changes involve protein phosphorylation, ion flux changes, chromatin alterations, and cytoplasmic restructuring. Phosphorylation changes the strength of connections within the cell network, just as hormones and other communicating molecules change the strength of connections between cells and tissues. In the case of herbivory or disease, memory (commonly called priming) can last years and can be transmitted to subsequent generations. The presence of memory ensures that subsequent stimuli are acted upon more quickly and with greater sensitivity. Many stress stimuli (water shortage, temperatures, excessive touch, soil problems, flooding, and toxic ions among others) elicit an equivalent but shorter kind of priming for future protection. It is not then too much to say that a plant is capable of cognition in the same way that a human being is. The plant gathers diverse information about its surroundings, combines this with information about its internal state, and makes decisions that reconcile its well-being with its environment. These themes are all expanded in a recent book (Trewavas, 2014). Received: January 25, 2015 Revised: January 25, 2015 Accepted: January 25, 2015 Published: January 29, 2015
Anthony Trewavas* Institute of Molecular Plant Science, University of Edinburgh, Mayfield Road, Edinburgh EH9 3 JH, UK *Correspondence: Anthony Trewavas ([email protected]) http://dx.doi.org/10.1016/j.molp.2015.01.020
REFERENCES Allan, A., Fricker, M.D., Ward, J.L., Beale, M.H., and Trewavas, A.J. (1994). Two transduction pathways mediate rapid effects of abscisic acid in Commelina guard cells. Plant Cell 6:1319–1328.
Pioneer’s Profile Assmann, S.M. (1995). Cyclic AMP as a second messenger in higher plants. Plant Physiol. 108:885–889. Baluska, F., and Mancuso, S. (2013). Root apex transition zone as oscillatory zone. Front. Plant Sci. 4:354–377. Barabasi, A.L. (2002). Linked. The New Science of Networks (New York: Perseus Books Group). Bradford, K.J., and Trewavas, A.J. (1994). Sensitivity thresholds and variable time scales in plant hormone action. Plant Physiol. 105:1029–1036. Denbigh, K.G. (1951). The thermodynamics of the steady state (London: Methuen). Gilroy, S., Read, N., and Trewavas, A.J. (1990). Elevation of stomatal cytosol calcium caged probes initiates stomatal closure. Nature 346:769–771. Hepler, P. (2005). Calcium: a central regulator of plant growth and development. Plant Cell 17:2142–2155. Ishikawa, H., and Evans, M.L. (1993). The role of the distal elongation zone in the response of maize roots to auxin and gravity. Plant Physiol. 102:1203–1210. Kacser, H., and Burns, J.A. (1973). The control of flux. Symp. Soc. Exp. Biol. Med. 27:65–104. Knight, M.R., Campbell, A.K., Smith, S.M., and Trewavas, A.J. (1991). Transgenic plant aequorin reports the effects of touch and cold shock and elicitors on cytoplasmic calcium. Nature 352:524–526. Malho, R., and Trewavas, A.J. (1996). Localised apical increases of cytosolic free calcium controls pollen tube orientation. Plant Cell 8:1935–1949. Moutinho, A., Hussey, P.J., Trewavas, A.J., and Malho, R. (2001). cAMP acts as a second messenger in pollen tube growth and reorientation. Proc. Nat. Acad. Sci. USA 98:10481–10486.
Molecular Plant Shacklock, P., Read, N.D., and Trewavas, A.J. (1992). Cytosolic free calcium mediates red light-induced photomorphogenesis. Nature 358:753–755. Smith, J.A., and Martin, L. (1973). Do cells cycle? Proc. Nat. Acad. Sci. USA 70:1263–1267. Trewavas, A.J. (1981). How do plant growth substances work? Plant Cell Environ. 4:203–228. Trewavas, A.J. (1982). Growth substance sensitivity; the limiting factor in plant development. Physiol. Plant. 55:60–72. Trewavas, A.J. (1985). Molecular and Cellular Aspects of Calcium in Plant Development (New York: Plenum Press). Trewavas, A.J. (1986). Understanding the control of plant development and the role of growth substances. Australian J. Plant Physiol. 13:447–457. Trewavas, A.J. (2006). A brief history of systems biology. Plant Cell 18:2420–2430. Trewavas, A.J. (2012). Information, noise and communication: thresholds as controlling elements. In Biocommunication of Plants, G. Witzany and F. Baluska, eds. (Berlin: Springer-Verlag), pp. 11–37. Trewavas, A.J. (2014). Plan Behaviour and Intelligence (Oxford: Oxford University Press). von Bertalanffy, L. (1971). General System Theory (London: Allen Lane). Waddington, C.H. (1977). Tools for Thought (St Albans: Paladin). Williams, R.J. (1956). Biochemical Individuality (New Canaan: Keats Publishing). Wright, S. (1982). Character change, speciation and the higher taxa. Evolution 36:427–443.
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Profile of Anthony Trewavas When asked to write on my experience in science and give some background, it sounded remarkably easy at first. In fact, it has proved very difficult. Apart from the short introduction below, I decided to write on four topics to which I have made a minor contribution. These are used to illustrate how I often fumbled my way through research and the ideas that I found fascinating. Investigation is never a direct path but a road full of obstacles. I have had several benefits in my scientific life. My surname is unusual (it comes from the southwestern tip of the UK, Cornwall), so I was never confused with anyone else. I graduated in biochemistry, a course full of mathematics, physics, and chemistry, I have never been afraid of equations, unlike many biologists. But my primary benefit has been the influence of others, including a brilliant schoolmaster who enthused me about plants. Another crucial lesson was from a little-known PhD supervisor, Eric Crook. He taught me to ignore what the author of an article thought but instead to look at the data and draw one’s own conclusion. I have as far as possible always done that and occasionally it has caused trouble with people who say that my references are inaccurate because they do not say what I claim. My response: look at the data; draw your own conclusions, not the authors. The third influence, Professor Jack Hanson, will figure later. I have been blessed with some remarkable postdocs and postgrads; many of these needed no more than a nudge in the right direction. Often, they just came in and did their own thing, leaving me to explain to grant-giving authorities why we had not bothered with what was approved. They have been the real pleasure in research; many are now independent creative scientists in their own right. I do regard the present grant-awarding situation, or at least as it was a decade ago, as totally inimical to anything creative. Having one’s grant being hawked around, so everyone knew supposedly what you were doing, is the last way to get people to strike out, follow their nose, and try completely risky things. Scientists need to be trusted and given their head. If they waste money, do not give any more, but no one should have to waste 3 to 4 months every year to try to winkle peanuts out of government research authorities. The grants that are awarded, in my experience, tend to be safe and uncontroversial projects; the opposite of what is needed. I have always been a research gambler: nothing gained without serious risk. I used what grant money I had for things I regarded as priority, not what committees thought. The worst way to get any sensible decision is to ask a committee. Science definitely benefits the communities economically in which it is practiced. In my scheme, some will waste awarded money, but that would be the price paid for the rest, because others freed of constraints will take the necessary risks that cut through limitations in knowledge. Everyone benefits. I wonder if Bill Gates or Steve Jobs ever wrote a grant application.
In my career, I have met, corresponded, and collaborated with many thousands of individual plant scientists. They too have invariably been courteous and helpful and made my life as a scientist an enormous pleasure. They too contributed each in their own way. Ideas are central to science; they brought me into research. But again I have not left out experimental material either. So let battle commence.
BIOLOGY IS A SYSTEM OF SYSTEMS I have always looked for things that give that damascene moment (there is another later), and my first reading into systems was certainly that. In 1972, I had purchased a short book by von Bertalanffy (1971). It completely changed my way of thinking and transcended anything I had read before. But I had been primed. At school, one of my prizes was a small book on steady-state thermodynamics (Denbigh, 1951), which illustrated unusual behavior when chemical reactions were coupled together and away from equilibrium. As an undergraduate, I had read Biochemical Individuality by Williams (1956). This book, surely required reading for any biologist, taught me to mistrust averages. Individuals are not the average and in behavior as in evolution, the individual is king. Any individual organism is a complex system and organisms survive enormous degrees of cell and tissue variation by virtue of that fact. Having read von Bertalanffy, I searched the Edinburgh library for more. Economic, social, and management systems emerged, much of it hypothetical, but it got me in the way of thinking. I also followed the history back as far as possible. When I received an invitation to write for Plant Cell in 2006, I sorted through the pile of articles I had accumulated, then about a meter high, and published some of what I had learnt (Trewavas, 2006). Systems investigations reached mainstream biology in 1990 and are now common in the literature. I had also joined the University of Edinburgh in 1970. The crucial article by Kacser and Burns on the same campus and using systems approaches was published in 1973. It taught me all I needed to know about sensitivity analysis. Finally, Conrad Waddington occupied the genetics Chair at Edinburgh, and his last book (Waddington, 1977), was based entirely on systems understanding. My copy is much thumbed and I have often quoted from it. My first use of systems came in Trewavas (1981) in the arguments about hormones and in Trewavas (1986), I illustrated a complex amino acid biosynthetic pathway as like a simple neural network. Published by the Molecular Plant Shanghai Editorial Office in association with Cell Press, an imprint of Elsevier Inc., on behalf of CSPB and IPPE, SIBS, CAS.
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Molecular Plant A Common Example of Systems Present-day biology uses systems approaches as a tool to investigate cell organization and behavior. I introduce it in a different way and illustrate its properties. The plant science community is a fine example of a dynamic, fully functioning, and self-organizing system. By system is meant a network, a recognized structure constructed from thousands of individual researchers connected in some way to many others by differing forms of communication. The connections are published articles, refereeing grants and articles, meetings, direct communication and collaboration, technique training, email, and sometimes, books and journals. The community acts like an integrated whole. Meetings are like the beehive dance floor: there is direct exchange of ideas and information. Some connections are strong; collaborators and those working on an agreed goal synergize each other. Other connections are weaker and may simply reflect related fields. The system is dynamic in that it sees progress on a variety of fronts and that provides enormous flexibility. The process, called distributed control, is common in self-organizing systems and enables a moderate degree of independence of individual research areas. The system phenotype is plastic; it can extend when needed into different branches as more researchers are drawn into particular exciting issues. Advance takes place at different rates in different areas of knowledge. Furthermore, our system is definitely self-organizing. Researchers to a large extent choose their problems for investigation and become part of the system once the choice is made and research commences. This system has a recognizable structure too; it is composed of hubs and connectors, as first described by Barabasi (2002) for other systems. Hubs have lots of connections; connectors fewer. Small world is another similar, but not identical, descriptor. Hubs are those investigators that receive larger numbers of citations, publish frequently, receive more grant money and invitations, run larger groups, collaborate more, and in meetings acquire larger audiences. Connectors (sometimes termed edges) with fewer connections are composed of those hopefully on the way up. Commonly, these are postgraduates and postdocs who in due course hope to acquire hub status. Other edges are those who chose instead to investigate the essential but more obscure areas of the subject. The numbers of connections to each individual follow a power series. There are few with many connections and many with few. Hubs and connectors between them construct a hierarchy that stabilizes the whole. Negative feedback stabilizes certain areas of research for considerable periods. As scientists retire or go into administration or other career opportunities, their specific research area is replaced by others. There is also feedforward, resulting in amplification. An area in which I worked, cytosolic calcium, is a case in point. Within a decade, it went from one or two researchers to hundreds (Hepler, 2005). The system then stabilizes at a higher level for periods of time as freely available personnel, technical limitations, and easily gained results constrain investigation expansion. Emergent properties are a consequence of connection. They are unique properties, which are not expressed by the individual on 346
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Pioneer’s Profile their own. Synergism between researchers is an obvious example. Common scientific themes that emerge in research are another. Many individuals and published research articles together construct an accepted new understanding, which is used when constructing experimental approaches or writing grant applications. I regard them as similar to Dawkins’s memes; they tend to be stabilized through negative feedback by grant applications, research articles, and reviews. The meme is improved as new results emerge and evolves similarly to Wright’s (1982) adaptive landscape of hills and valleys. The fitter memes move toward successively higher hills. Von Bertalanffy’s contention was that all systems have shared structures and properties. From cells to ecosystems, similar organizational properties emerge as they do in economic and social systems. Power series, feedbacks and feedforwards, connections, emergent properties, and hierarchical structures are all found in the hundred thousand or so different kinds of proteins inside cells. They are also present but less obvious in ecosystems, in which overall the connections are weaker. The individual plant is also self-organizing, with recognizable distributed control and a hierarchically constructed system that shares all the properties described above. The strength of connections between the parts of the system is key to its overall character. These change with time and are the means whereby the system is altered. In our plant research system, they reflect the waxing and waning of either specific research interest or group involvement. Individual plants experience changes in communication, altering the strength of connections between tissues. Is it not time that the system nature of the individual plant was illustrated and actual strength of connections measured? In cells, posttranslational modifications are a primary means for changing the connection strengths. When enough have been changed, the system undergoes a rapid transition to another new relatively stable system. For scientific memes, young radicals with differing ideas replace the old and conservative; time and the grim reaper become the motive force of change.
PLANT HORMONES AND GROWTH In 1964, I moved to the new University of East Anglia and continued research from my PhD thesis on auxin effects on protein synthesis, the frontier at the time. The Holy Grail was the belief that auxin would selectively alter transcription. It was not difficult to demonstrate changes in RNA and apparent specific changes in proteins that I found, as did others. But there was a difficulty in interpretation. If cellular proteins had different turnover rates, a generalized increase in protein synthesis would see apparently very specific changes, led by those with high turnover. There was no literature in growing plant cells on actual protein and RNA turnover rates and, apart from cell death, no indication of any turnover. The problem required unambiguous measurement of separate rates of protein synthesis and degradation. It was suspected at the time that 90%–95% of the amino acid in a plant cell was in a large metabolically inactive pool, possibly but not certainly in the vacuole. The likely precursor pool for protein synthesis was small and potentially rapid in turnover and thus completely swamped in whole tissue analysis. It took 3 years to develop unambiguous methods for discriminating these pools and to obtain genuine rates of synthesis and
Pioneer’s Profile degradation for both proteins and in turn nucleic acids. Both had overall average turnover rates of about 3 days. The importance of compartmentalization was what I learnt, a lesson not applicable just to protein synthesis. In the decade from 1970 onward, research on plant hormones concentrated largely on accurate chemical quantitation from whole tissue extraction. Most hormones had been identified by the simple procedure of adding hormone to tissues and getting an effect. Thus, the supposition that endogenous changes in hormone content would control development and measurement would reveal this to be the case. But my own research experience told me that cells were compartmentalized and the problems experienced with protein turnover were just as likely with hormones. Simple whole tissue extraction could fatally compromise the real meaning of results; the estimates would make sense only if they were in the same compartment as potential receptors, although no receptors were known at the time. There was certainly evidence at the time from using radioactive auxin in transport experiments that at least half ended up in inactive, untransportable pools. Furthermore, I had learnt of the importance of sensitivity (emphasized by Kacser and Burns, 1973). Sensitivity is a systems property dependent in part on everything else. Its measurement required tiny changes in amount to see whether a corresponding tiny change in response occurred. It was the ultimate arbiter of meaning in changes of concentration. In 1981, I published a critical but invited assessment of current plant hormone research (Trewavas, 1981). It was not difficult to point out that many such hormone content measurements did not correlate with the change in the rate of the process that they were supposed to control and that endogenous sensitivity was the one measurement that might make more sense. The effect of publication of the article was most certainly controversial. Warring camps seemed to develop for and against the article, and my promotion was actually blocked by one of the opponents. I received over 620 reprint requests in just a few weeks and I only had 100 reprints; there was no email at that time. These days, mutation of hormone synthesis can be used to drastically change concentration. Kacser and Burns (1973) had emphasized in their estimates of metabolic sensitivity that only tiny incremental changes in amount should be used. That needs to be noted. I did find some results (coleoptiles with auxin, leaf development with gibberellin) in which endogenous sensitivity in intact tissues could be estimated. These suggested that changing hormone content was not a particularly sensitive control, something that still needs further investigation. One problem much discussed at the time was that doseresponse curves, measuring tissue or cell response to added exogenous hormone, were rather wide (3–4 orders of magnitude for a 10%–90% expression of response). For cells in a single tissue (e.g. guard cells), noise in the protein synthesizing machinery may be responsible (Trewavas, 2012). But for groups of plants or plant tissues, it may in addition reflect an ecological requirement. Individual plants should vary enormously in their capability to respond, because of the uncertain environment into which the seed is cast and that the individual must put up with. This is a clear case of bet hedging. But its specific origin remains uncertain.
Molecular Plant Hormones Act to Synchronize or Coerce Heterogenous Cells into Development One spin-off of the 1981 article was numerous invitations to write elsewhere. In Trewavas (1982), I added an extended appendix on the cereal aleurone and gibberellin. A system little used now, but then the subject of hundreds of articles. The classic view was that during germination, the growing embryo synthesized gibberellin, which diffused to the viable aleurone cells surrounding the endosperm. The synthesis and secretion of amylases were induced. On diffusing into the endosperm, sugars and amino acids were released, provisioning the growing embryo. There was a huge amount of conflicting and contradictory evidence for and against this classic view, and those interested can read it all; little has changed. Aleurone cells do have to acquire sensitivity or responsiveness to gibberellin, and this could take up to 24 hours after imbibition. When cereal seeds were treated with exogenous gibberellin concentrations, however, overall amylase production was not increased, but its appearance occurred earlier; synthesis was accelerated but the duration of synthesis shortened. Exogenous gibberellin was acting to synchronize amylase production, although authors failed to recognize it. At that time, the classic synchronizing system was the cultured cell cycle (Smith and Martin, 1973). Resting cells were in G0, but there was a certain probability that they could cross a threshold and enter a deterministic G1 phase and replicate. Cells were thus in an all-or-none situation: either they replicated or they did not. Although G1 lengths could be variable, the rates of cell division reflected the probabilities with which individual cells crossed that threshold and thresholds were statistically distributed. Adding factors to increase cell replication rates simply brought less sensitive cells into replication earlier. The nature of the threshold was suggested to result from controlling proteins of very low copy number, in which large variations in synthesis potentially due to noise were to be expected, but no doubt, it is more complex. The realization that gibberellin synchronized amylase production led me to search for additional hormone synchronizing systems in the plant literature. I identified a number and published the observations in various articles. These were fruit ripening and abscission in response to ethylene; the after-ripening response of Avena fatua seed to gibberellin (after-ripening is simply achieved by acid; auxin storing dry seed for a year); stomatal aperture and abscisic and adventitious root formation. Later on, Kent Bradford (Davis, California) sent me a publication indicating that he had independently observed similar synchronizing behavior in the kinetics of tomato seed germination and gibberellin. We then published a joint significant article (Bradford and Trewavas, 1994). One of my former students, Simon Gilroy, demonstrated beautifully the all-or-none response of amylase secretion using aleurone protoplasts. Each cell produces only a predetermined number of amylase molecules. More amylase, more cells synthesizing. Added exogenous gibberellin simply brings forward less sensitive cells into production; the period of development is thus shortened. I suspect that all plant hormone effects on development follow this pattern, with a threshold passed only on a probability scale. The threshold once passed enables the cells to become sensitive Molecular Plant 8, 345–351, March 2015 ª The Author 2015.
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Molecular Plant to hormone. If hormone is already present, as it commonly is, then entry by individual cells into developmental change will initially be sporadic. The probability of transition has its most interesting consequences in cell extension. In both stems and roots, there are zones of cell division in the extreme tip, followed by a defined zone of extension known to be auxin sensitive; here extension growth rate rapidly increases to a peak and then decreases. Extracted auxin concentrations do not mimic this variation. As cells leave the division zone, there will be a probability of transition to become auxin sensitive and to construct the cell apparatus for cell extension. Once constructed, the elongation program will be maximally expressed because it is all or none. The actual rate of elongation in any part will be determined by how many cells have made the transition, and the decline by how many cells have completed their elongation. Extension rates are initially small, because only a few cells have made the transition and become auxin sensitive; their extension growth is constrained by others as yet unchanged. When elongation rates are much higher, it is because many more cells have made the transition to the elongation program. Exogenous auxin added at this time will bring forward more cells into the elongation phase and accelerate growth rate. But correspondingly, it will accelerate the rate of decline too. Both the 1981 and 1982 articles contained figures that show this clearly. A zone of transition probability will precede elongation itself. Some authors have pointed to the rather special features of these cells (Ishikawa and Evans, 1993; Baluska and Mancuso, 2013).
THE ROAD TO CALCIUM How I ended up working on cytosolic calcium is a tale of total accident, uncertainty, luck, and serendipity. I went to the University of Edinburgh in 1970. Within weeks the Head of Department (HOD) called me together with John Ingle (working on DNA) and Chris Leaver (working on RNA). After short talks from both of these, the HOD turned to me and said ‘‘I am not having competition in this department; go and find a project on proteins.’’ Photolabile, azido crosslinking groups had very recently been described, so I outlined synthesizing and using azido auxins to pick up receptors. The HOD was keen at first, then came back several hours later and said no: no reasons were given, but it was lucky for me. When I went to Urbana in 1980, azido auxins and a number of others had been synthesized there, and Alan Jones (recent President of the American Society of Plant Biologists) had been using them. But instead of the hoped for one or two proteins, they turned out to be rather promiscuous labeling agents. I had unknowingly avoided what might have been a waste of many years. Part of my PhD had raised the issue of protein phosphorylation. My supervisor had heard a lecture that outlined the relationship between cyclic AMP, protein kinase, adrenalin, and phosphorylase in liver cells: Earl Sutherland’s enormous breakthrough. So it was suggested I try the effects of auxin on phosphorylase, and I naively agreed. One year later, with completely negative data, I realized that there was a world of difference between plants that had buckets of carbohydrate swilling around them and organisms that did not. Thinking first would have been helpful. 348
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Pioneer’s Profile But in looking at the literature in 1970, there was an astonishing nothing on protein phosphorylation in plant cells, so this was chosen. The aim was to use this direction as a route to answer questions about plant cyclic AMP. Polyribosomes were first chosen for investigation, because they could be easily purified on sucrose gradients; cell fractionation was still primitive then. Within a year, I had identified a single phosphorylated ribosomal protein attached to the small subunit with phosphorylation on serine; within another year, an attached protein kinase. Frustratingly, the activity of this kinase was unaffected by everything that was thrown at it, including cyclic nucleotides and calcium. To rub salt in the wound, I received a letter in 1973 from Ira Wool (Chicago), who had found a phosphorylated protein in the small ribosomal subunit of animal cells of identical molecular weight. His attached protein kinase was cyclic AMP dependent. Cyclic AMP has been the black sheep of the plant signaling family; surprising, because many other signaling molecules found in animal cells are used in plants (Assmann, 1995). Skepticism about cyclic AMP in plant cells was certainly rampant in the early 1970s. Well-performed assays of extracts from whole plants placed it below detectable levels. However, the article published with Rui Mahlo in 2001 (Moutinho et al., 2001) established beyond reasonable doubt that it was both synthesized in pollen tubes and functioned in growth polarity. Cyclic nucleotide gated channels, which have been clearly identified in plant cells, probably mediate pollen tube growth effects. The failure of Ca2+ to have any effect on this protein kinase (I found it slightly inhibitory) did not bother me at the time, since like cAMP, I had come to believe that this was another mechanism found only in animal cells. I had done crude cell fractionations and found protein kinase activity everywhere but no response to cAMP or Ca2+. So the search was continued for other significant changes in nuclear protein phosphorylation (and thus hopefully protein kinase control). About 50–80 such proteins in plant cells were detected using 2D gels, and some specific changes were found to be associated with plant cell division, particularly in histone H1. At that time in 1980, I had considered and rejected attempting to purify protein kinase, but which substrates could be used? Most kinases will phosphorylate casein or histones. That was a lucky choice again. With 1000 protein kinases in plant cells, this would probably have been another dead end. But the change came when I went to Urbana, Illinois to do some work with Larry Vanderhoef (later President of Davis, California), who disappeared within a few weeks to promotion elsewhere. Instead, I spent some of the time talking and writing an article on plant growth with Jack Hanson. He urged me to look again at how I had estimated protein kinase activity, because he had observed very rapid effects of Ca2+ on root growth and thought protein kinase control would be a good explanation. Furthermore, a calmodulin-like molecule had been identified in plant cells a year before. I went back through the literature, rereading furiously. It was very humbling; I had thought foolishly that double-distilled water would be free of calcium. It most certainly was not; use of EGTA was the critical key to set known Ca2+ free concentrations, an obvious damascene moment. Back at the bench and using crude
Pioneer’s Profile membrane preparations again, a 5- to 6-fold increase in phosphorylation was easily detected and maximal at 1 mM free Ca2+; in fact, this kind of kinase activity seemed to be in all cell fractions. Hepler (2005) described in excellent detail the slow and hesitant appreciation of the use of cytosolic calcium in plant cells, which accurately describes my own fumbling at the topic. The meeting I organized in Edinburgh 1985 on molecular and cellular aspects of calcium in plant development was a watershed (Trewavas, 1985). Numerous discussion periods highlighted in particular the necessity for both unambiguous measurements and imaging of cytosolic Ca2+ in plant cells. I decided there and then never to look at a dead cell again and to accept that challenge. If we needed to measure the concentration of any molecule or manipulate its concentration, a suitable probe would have to be constructed for imaging in live cells. In addition, caged compounds could be introduced and released by photolysis. Caged hormones and caged EGTA were both later used, with significant outcomes (Shacklock et al., 1992; Allan et al., 1994). The notion that Ca2+ distributions inside cells could be imaged was extraordinary but absolutely essential to understanding. The plant cell cytoplasm is highly differentiated, and Ca2+ is not a mobile ion in the cytoplasm. Imaging where and when Ca2+ is elevated could provide superlative information on where the cytoplasm is activated and the source that gives rise to elevation. Roger Tsien (later Nobel Prize winner) had in the mid-1980s designed suitable dyes for fluorescence ratio imaging and described equipment he had constructed for the purpose. These days, the equipment can be bought off the shelf, but it took us (Simon Gilroy, Mark Fricker, and I) from 1987 onwards, 3 years, and three grants to construct our own, with a very steep learning curve. Once constructed, imaging of cytosolic Ca2+ was used for guard cells, red light-responding protoplasts, and pollen tubes; it revealed how local cytoplasmic Ca2+ signaling controls whole cell behavior and that the vacuole in particular was one source of Ca2+ responsible for elevating cytoplasmic levels (Gilroy et al., 1990; Shacklock et al., 1992; Malho and Trewavas, 1996). The growing pollen tube continued to be a source of fascination and was continued later by Maasaki Watahiki, many of whose excellent studies remain unpublished. Maasaki showed using highly focused flash photolysis that a tip located Ca2+ sensitive protein kinase moves with extraordinary speed to the flanks and must recycle back. A further pollen tube protein kinase was also located attached to cell wall containing vesicles, which appeared to be in vast excess and which fluctuated in position at enormous rates. What I did want, however, was a simple method for measuring whole plant cytosolic Ca2+, and this came with the use of the Ca2+ sensitive luminescent protein, aequorin. In the jellyfish, from which aequorin is obtained, it is found together with GFP. But aequorin is composed of an apoprotein and the luminophore, coelenterazine. The protein could be expressed by transformation, but all that could be done with the luminophore was to incubate the tissue in it and hope aequorin would form. In 1990, it seemed an enormous gamble, and I had a second fallback project available, but work it did, due solely to Marc Knight, who got the technique up and running (Knight et al., 1991). The exquisite touch sensitivity of plants exemplified by immediate
Molecular Plant cytosolic Ca2+ transients lasting 10–20 seconds dropped out immediately. We used this aequorin method to report on the effects of blue and red light, tropic bending, circadian processes, wind, osmotic pressure, cold and heat shock, and fungal invasion. The luminescence was imaged too, showing transmission of Ca2+ waves across tissues, and targeted to some cell compartments, indicating separate organelle (nucleus and chloroplast) control. The technique is very simple and has been used by hundreds of laboratories. Cytosolic Ca2+ is now an established, ubiquitous, second messenger in plant cells.
PLANT BEHAVIOR AND INTELLIGENCE The final piece in this article is most certainly controversial again and best introduced with two quotations. From plant biologist Barbara McClintock in her Nobel Prize acceptance speech: ‘‘A goal for the future would be to determine the extent of knowledge the cell has of itself and it uses that knowledge in a thoughtful manner when challenged.’’ The response to challenge is behavior, and thoughtful responses are clearly intelligent. The commonest descriptor of intelligence among those who have studied the subject is that it involves problem solving, and a capacity for problem solving best indicates the variability in this quality between individuals. In 1937, Went (the discoverer of auxin) and Thimann published the first book on phytohormones, now regarded as the Bible of auxin effects. On page 151, ‘‘However in tropistic movements, plants appear to exhibit a sort of intelligence; their movement is of subsequent advantage to them.’’ Advantage directly implicates fitness, the ultimate evolutionary criterion and experienced only by wild, not laboratory-grown, plants. Fitness is a life cycle assessment, and seed number represents a simple proxy. Throughout their life cycle, wild plants experience environmental situations in which decisions about costs and benefits have to be made. Usually, these concern the distribution of limited resources, but there are also environmental impacts to be dealt with. Many of these do not come in nicely packaged quantities but are often chaotic in appearance. Decisions involve an assessment that incorporates past experience (the potential reason for the decision in the first place) and the future (the consequence of taking one course of action rather than another). Assessment is the same as McClintock’s ‘‘thoughtful’’ manner, which I consider intelligent too (Trewavas, 2014). Because of predation, animals evolved separate sensory and motor systems and joined the two with a fast transmission connection, the nervous system. With increasing complexity, the nervous system began to act as an assessment, learning, and memory system, where it resides today. Because plants lack a defined nervous system, assessment involves the whole organism, requiring complex and interactive communication. Plants do use electrical controls, most recently indicated in the development of herbivore resistance, but it is clearly less elaborated. Plant hormones, proteins, peptides, RNAs large and small, and other molecules combine together in whole plant communication to provide for assessment in ways simply not understood but essential to fitness. To me, assessment is obviously a complex system property, involving communication throughout the plant, and is surely a challenging frontier for those prepared to take it on. It is why I have argued for plant intelligence. Molecular Plant 8, 345–351, March 2015 ª The Author 2015.
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Molecular Plant Self-organization is another critical property that characterizes the development of the plant phenotype. There is no overall controller dictating development according to a predetermined plan. The phenotype develops instead as a result of interactions, simple communications, between the constituent parts. The elements of communication then change with time and size. To try to understand plant behavior and intelligence, clues can be obtained from other self-organizing systems in biology. The human brain itself, surprisingly, is one such, but the most useful are social insect colonies, where their behavior is described as swarm intelligence. Colonies function by interactions between the constituent organisms to construct a system. The colony self-organizes, grows by increasing constituents and accumulated resources, and uses negative feedback and feedforward controls; size plays its critical part too. Colony growth is slow and a consequence of numerous activities that take place on a shorter time scale. The colony behaves like a single organism, but its phenotype is plastic, the consequence of distributed control; parts can act locally to specific signals that benefit the whole. Does that all sound familiar? I think there are some remarkable organizational analogies between colonies and plants. The organization and behavior of the colony should help understand the organization of plant behavior! Bee colonies have a central area, in which much information is exchanged, leading to changes in colony behavior; it is known as the dance floor. I think the cambium has an analogous function in growing plants. As a tissue, it is like an internal skin and thus has the potential to transfer information throughout itself. In growing plants, shoots (branches) compete with each other for root resources. The cambium is in a position to assess the relative performance quality of each shoot. Current evidence suggests the cambium controls root resource demarcation by increasing the number of vascular elements to those shoots growing vigorously and by blocking some or all of the vascular elements to those contributing less or nothing. Changing root resource distribution involves both feedback and feedforward, and these critical control elements are also involved in enabling leaves to maintain a relatively constant temperature. It is thus surprising that in tissue bending so much emphasis is placed just on auxin, when the growth kinetics of many individual roots illustrate clear negative feedbacks. The controlled diversion of shoot resources can be expected to underpin the root phenotype. When environmental situations change, those plants that exhibit greater plasticity can learn to successfully adapt their behavior more quickly. In itself, that implies a potential to assess possible future circumstances. Phenotypic responses are commonly slow, like colony growth. The most difficult situation arises when the reason for environmental challenge has disappeared before the new phenotype has appeared. On the other hand, if this environmental change is maintained or is repetitive, this should promote selection of those individuals whose progeny develop the relevant characteristics with greater rapidity, higher probability, or lower cost. Later selection thus ratifies an adaptation that has already been tested through genetic and/or epigenetic means. When faced with environmental change, the behavior will thus either be interpreted as insight or an uncanny ability to predict future events. 350
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Pioneer’s Profile Darwin considered that competition between individuals was fundamental to selection. Competition is a primary challenge that faces all wild plants, and game theory is designed to understand its basis. Competitive plants become part of the system structure of the plant, like all facets of its environment. The ‘‘prisoner’s dilemma’’ is undoubtedly applicable to the interactions between plants and associated microbes, and individual plants have mechanisms to deal with cheating partners (Trewavas, 2014). But clearly, competing against oneself would be disadvantageous. Experimental evidence using a number of species indicates that plant individuals do distinguish between themselves and other alien individuals and thus are capable of forms of self-recognition. The shade avoidance syndrome results from competition between individuals for light. But it is as much about denying light to competitors as counteracting the physical characteristics of shade. Root proliferation in N and P rich patches, although increasing resource uptake, is also designed to deny these resources to competitors by removing them first. Decisions are inherent in game theory and require individuals to learn about the competition and to remember it for considerable periods. In nonneural organisms, learning starts with the perception of a stimulus, and the chemical and physiological trace of the transduction chain represents its memory. The commonest pathways use cytosolic calcium; subsequent changes involve protein phosphorylation, ion flux changes, chromatin alterations, and cytoplasmic restructuring. Phosphorylation changes the strength of connections within the cell network, just as hormones and other communicating molecules change the strength of connections between cells and tissues. In the case of herbivory or disease, memory (commonly called priming) can last years and can be transmitted to subsequent generations. The presence of memory ensures that subsequent stimuli are acted upon more quickly and with greater sensitivity. Many stress stimuli (water shortage, temperatures, excessive touch, soil problems, flooding, and toxic ions among others) elicit an equivalent but shorter kind of priming for future protection. It is not then too much to say that a plant is capable of cognition in the same way that a human being is. The plant gathers diverse information about its surroundings, combines this with information about its internal state, and makes decisions that reconcile its well-being with its environment. These themes are all expanded in a recent book (Trewavas, 2014). Received: January 25, 2015 Revised: January 25, 2015 Accepted: January 25, 2015 Published: January 29, 2015
Anthony Trewavas* Institute of Molecular Plant Science, University of Edinburgh, Mayfield Road, Edinburgh EH9 3 JH, UK *Correspondence: Anthony Trewavas ([email protected]) http://dx.doi.org/10.1016/j.molp.2015.01.020
REFERENCES Allan, A., Fricker, M.D., Ward, J.L., Beale, M.H., and Trewavas, A.J. (1994). Two transduction pathways mediate rapid effects of abscisic acid in Commelina guard cells. Plant Cell 6:1319–1328.
Pioneer’s Profile Assmann, S.M. (1995). Cyclic AMP as a second messenger in higher plants. Plant Physiol. 108:885–889. Baluska, F., and Mancuso, S. (2013). Root apex transition zone as oscillatory zone. Front. Plant Sci. 4:354–377. Barabasi, A.L. (2002). Linked. The New Science of Networks (New York: Perseus Books Group). Bradford, K.J., and Trewavas, A.J. (1994). Sensitivity thresholds and variable time scales in plant hormone action. Plant Physiol. 105:1029–1036. Denbigh, K.G. (1951). The thermodynamics of the steady state (London: Methuen). Gilroy, S., Read, N., and Trewavas, A.J. (1990). Elevation of stomatal cytosol calcium caged probes initiates stomatal closure. Nature 346:769–771. Hepler, P. (2005). Calcium: a central regulator of plant growth and development. Plant Cell 17:2142–2155. Ishikawa, H., and Evans, M.L. (1993). The role of the distal elongation zone in the response of maize roots to auxin and gravity. Plant Physiol. 102:1203–1210. Kacser, H., and Burns, J.A. (1973). The control of flux. Symp. Soc. Exp. Biol. Med. 27:65–104. Knight, M.R., Campbell, A.K., Smith, S.M., and Trewavas, A.J. (1991). Transgenic plant aequorin reports the effects of touch and cold shock and elicitors on cytoplasmic calcium. Nature 352:524–526. Malho, R., and Trewavas, A.J. (1996). Localised apical increases of cytosolic free calcium controls pollen tube orientation. Plant Cell 8:1935–1949. Moutinho, A., Hussey, P.J., Trewavas, A.J., and Malho, R. (2001). cAMP acts as a second messenger in pollen tube growth and reorientation. Proc. Nat. Acad. Sci. USA 98:10481–10486.
Molecular Plant Shacklock, P., Read, N.D., and Trewavas, A.J. (1992). Cytosolic free calcium mediates red light-induced photomorphogenesis. Nature 358:753–755. Smith, J.A., and Martin, L. (1973). Do cells cycle? Proc. Nat. Acad. Sci. USA 70:1263–1267. Trewavas, A.J. (1981). How do plant growth substances work? Plant Cell Environ. 4:203–228. Trewavas, A.J. (1982). Growth substance sensitivity; the limiting factor in plant development. Physiol. Plant. 55:60–72. Trewavas, A.J. (1985). Molecular and Cellular Aspects of Calcium in Plant Development (New York: Plenum Press). Trewavas, A.J. (1986). Understanding the control of plant development and the role of growth substances. Australian J. Plant Physiol. 13:447–457. Trewavas, A.J. (2006). A brief history of systems biology. Plant Cell 18:2420–2430. Trewavas, A.J. (2012). Information, noise and communication: thresholds as controlling elements. In Biocommunication of Plants, G. Witzany and F. Baluska, eds. (Berlin: Springer-Verlag), pp. 11–37. Trewavas, A.J. (2014). Plan Behaviour and Intelligence (Oxford: Oxford University Press). von Bertalanffy, L. (1971). General System Theory (London: Allen Lane). Waddington, C.H. (1977). Tools for Thought (St Albans: Paladin). Williams, R.J. (1956). Biochemical Individuality (New Canaan: Keats Publishing). Wright, S. (1982). Character change, speciation and the higher taxa. Evolution 36:427–443.
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