Cells vary widely in size but are, typically, around one-hundredth of a millimetre (10μm) in diameter. Each cell is surrounded by a thin membrane with a complex interior, packed with many millions of molecules. Although the life we see around us appears very diverse (from ants to elephants! See figure 1), it is remarkably similar at the level of molecules; the exploration of life in the range 10μm–0.1nm is thus especially rewarding (the size of an atom is approx. 0.1nm=10⁻¹⁰m). Such small things cannot be observed with the naked eye, so magnification tools are required to visualize them.

Figure 1 Illustration of the dimensions of some life-related systems on a logarithmic scale (powers of 10). The range visible by some of the different methods mentioned in the text is indicated by horizontal arrows. X-rays and NMR can be used to look at human (more ...)

Studies of cell structure, structural cell biology, began when early microscopes, developed around 350 years ago, gave the first glimpse of single cells. Since then, increasingly sophisticated instruments have revealed ever more information about cell structure (Schliwa 2002; figure 2). Visualization of the large molecules (macromolecules) found in cells, structural molecular biology, only began around 60 years ago when atomic resolution models of DNA and proteins were first obtained (protein dimensions are usually more than 1000 times smaller than cells). Like studies of cells, studies of macromolecules have advanced remarkably (figure 2) and high-resolution structures of many thousands of them are now known (Campbell 2002). The protein databank (PDB) is a depository for all the solved structures and a quick browse of the web site gives a sense of their range and beauty, see http://www.rcsb.org/pdb/Welcome.do. Although structural cell biology and structural molecular biology largely evolved as separate disciplines, there is an increasing awareness that they are more and more convergent (Sali et al. 2003; Harrison 2004). Ever better resolution can be achieved in studies of intact cells and ever larger structures and complexes can be seen using molecular methods. A new structural biology is emerging that encompasses both approaches.

Figure 2 An illustration of advances in structural cell biology (a and b) and structural molecular biology (c and d). (a) Drawings of ‘animalcules’ seen by van Leeuwenhoek in a single lens microscope (figure 3 in the reference Leeuwenhoek 1683 (more ...)

Advances in all branches of science depend heavily on the development of new techniques1 and this is particularly true for structural biology. To illustrate the advances made since the time of William Croone (1633–1684), I will briefly trace the evolution and development of visualization methods. To understand life, we need to know the structure and mechanism of cellular machinery that drives key cellular processes such as cell division, protein synthesis and energy production. To do this, we need to use a range of techniques that give temporal as well as spatial information about the molecules in the crowded environment that exists in and around a cell. The complexity of this problem is clearly illustrated by artistic impressions of the crowded molecular interior of a cell (Goodsell 2005; http://www.scripps.edu/mb/goodsell/illustration/patterson/; Berman et al. 2000). This is a static two-dimensional view; in reality, the components are in a constant state of flux, being manufactured, broken down and moving in three dimensions.

As someone trained in physical sciences, much of my emphasis here will be placed on contributions that have passed from physics into the biological sciences, but many other disciplines, including genetics, chemistry and medicine have, of course, also made seminal contributions to our current level of understanding. To indicate what the current level of understanding is, I will expand a little on one area of personal research interest, cell movement on a surface, a fascinating example of the dynamism of the living state.

To set the scene, here are a few quotations from previous eloquent descriptions of the essentials of the living cell:

Early investigators of cells, including the great Louis Pasteur (1822–1895), were ‘vitalists’, who believed that living organisms have a non-physical inner essence which makes them alive. Although some might still argue that life cannot be completely understood by the usual approaches of molecular biology, which involves separation and dissection of the component parts, there is overwhelming evidence to suggest that life is explicable in terms of the laws of physics and chemistry. As Albert Lehninger (1917–1986) pointed out in early editions of his well-known biochemistry text book

The latter half of the twentieth century saw remarkable developments in ideas about biology at the molecular level. Some of these are: monomers (nucleotides, amino acids and sugars), which are strung together to make polymers (DNA, proteins and polysaccharides); a gene (DNA) provides the template for RNA (a close-chemical relative of DNA), which, in turn, specifies the linear sequence of amino acids in a protein; this sequence defines the protein three-dimensional structure that consists of helical and sheet-like substructures; proteins form the main structural and functional components of cells; proteins interact with numerous molecular partners.

Much of the remarkable success of modern cellular and molecular biology methods is due to ‘empirical reductionism’ where, for practical reasons, components of biological systems are isolated, purified, dissected and manipulated to extract information about their structure and properties. It is always important, however, to think about how these isolated components work in the context of the intact living cell. One alternative to the reductionist approach would be to assemble some form of primitive ‘artificial life’ in a test tube. Intensive efforts to do this are underway, but the construction of a minimum life form, apparently requiring around 300 genes, still seems a very long way off (Deamer 2005), not least owing to the difficulty in making catalysts that reproduce themselves. There is also the view that

Life is dominated by natural selection. Evolutionary forces are clearly apparent in cellular structures. Biological systems utilize components that have been found, by chance, to be effective and robust. The ribosome, the machine that synthesizes proteins using an RNA template, has been retained in very similar form by all kinds of life. Mitochondria, the energy-providing compartments in many cells, are thought to have arisen from what were once separate free-living organisms. Structural molecular biology has also shown that a limited number of protein structural folds or domains are used repeatedly in various ways. Certain structures were apparently found to make effective and versatile scaffolds and then these were retained and exchanged between organisms (this will be discussed further under ‘cell migration’; figures 3 and 4).

Figure 3 (a) A representation of a cell showing some intracellular organelles such as mitochondria (blue-green) and the nucleus (pink); (b) a side view of the same cell showing some of the actin cytoskeleton (green) and focal adhesions (brown) that form a bridge (more ...)

Figure 4 The structures of some of the modular protein units identified in figure 3e. The symbols generally correspond to those used in the SMART module database (http://smart.embl-heidelberg.de/). The structures were drawn using the graphics program Rastop ( (more ...)

This lecture emphasizes biophysical studies at the level of the single cell. It is worth pointing out, however, that higher levels of organization, as observed in multi-cellular organisms like animals, emerge from the blueprint provided by a single cell. Familiar characteristics exhibited by animals, including structure, response to stimuli, and reproduction, are all programmed by a single cell. Even sophisticated higher level properties, such as consciousness, arise from the ways in which our neuronal cells are connected together.

Man has long been interested in the structure (anatomy) of living organisms. Early pioneers, largely based in Padua, were Andreas Vesalius (1514–1564), who wrote one of the first textbooks on anatomy, Hieronymus Fabricius (1537–1619), who was Galileo's physician, and William Harvey (1578–1657), who discovered the circulation of blood. Dissection of tissue structure to the level of individual cells eluded these pioneers because the available tools were rudimentary. Our understanding of living systems began to improve when a contemporary of Croone2, Antonie van Leeuwenhoek (1623–1723), used a single lens microscope that he had ground himself to observe pond water and a variety of other liquids; he noted

Improvements continued to be made in optical microscopes by enhancing the contrast between different cellular substructures (Zernike 1953), but in the early twentieth century the ability to view cells remained limited. Albert Claude (1899–1983) summarized the situation in his Nobel lecture of 1974:

This situation was changed by the introduction of the electron microscope. Electrons are particles but act like waves with a wavelength which is inversely proportional to their velocity. Lenses for electrons can be made by bending the electron path with applied magnetic or electric fields. Based on this principle, the first electron microscopes were constructed in the 1930s (Ruska 1986). These have a theoretical resolving power much better than 1nm but, in practice, this level cannot be readily achieved for biological samples. By developing methods to ‘fix’ cells, with chemicals such as glutaraldehyde, and to stain them, with metals like osmium and uranium, Keith Porter, Albert Claude, George Palade and others were able to discover many cellular substructures and compartments using the electron microscope (Palade 1975).

Like all methods, the electron microscope has limitations. These include severe sample damage caused by the electron beam in evacuated sample chambers and low contrast between different parts of the sample. There have been a number of important recent technical advances in electron microscopy (EM) that have had a significant impact on studies of cell structure (see also molecules discussed below). These techniques include rapid freezing of an aqueous sample, avoidance of metal stains and sophisticated computer programs that can analyse and average noisy images. The background variation, or ‘noise’, arises because very low electron irradiation doses have to be used to avoid destroying the sample. Another advance came from the application of ‘tomography’ methods, which were first used to look at the structure of viruses in the 1960s (Crowther et al. 1970). A series of images of an object are taken at different angles to the electron beam. A three-dimensional image can then be reconstructed from these angle-dependent images. By combining these approaches—frozen hydrated samples, low doses, tomography and data analysis—detailed images of the structure of cells have now been obtained (Nickell et al. 2006). This technology allows many structural features of a cell, including ribosomes, actin filaments and membrane structures, to be visualized at a resolution of around 2nm (Baumeister 2004), although most of the other molecules in the cell are still invisible and/or unrecognizable (figure 2b).

X-rays, like electrons, can have wavelengths short enough to give less than nanometre resolution, but the construction of X-ray lenses is a formidable problem. Some progress is, however, being made with longer wavelength ‘soft’ X-rays and interesting images of cells are beginning to be produced (Attwood 2006).

Light microscopy has also undergone a remarkable renaissance in the last 20 years. Certain ‘fluorescent’ molecules absorb light at one wavelength and re-emit it at a different, longer wavelength. Beautiful images of fluorescent macromolecules in their cellular location are becoming familiar, as are ‘movies’ of living cells, obtained using time lapse photography (Dunn & Jones 2004). These developments have been enabled by improved fluorescent molecules (Zhang et al. 2002) and new microscope technology. One example of a fluorescent molecule that is having a major impact is green fluorescent protein (GFP) (Tsien 2003). This occurs naturally in some jellyfish and the fluorescent centre is produced by the protein itself; GFP can be attached specifically to molecules inside cells and visualized in living cells.

An example of an important technological improvement in light microscopes was the development of confocal methods. The idea of reducing unwanted light scattering from the specimen by scanning a small spot of light and observing the fluorescent emission was demonstrated in the 1950s by Marvin Minsky, but was not developed commercially for many years (Amos & White 2003). Further developments include total internal reflection fluorescence microscopy, where only a thin layer of a specimen near a surface is observed; a light beam reflected from a surface induces a thin layer of light (approx. 100nm thick) on the opposite side of the reflecting surface and this can be used to excite fluorescent molecules selectively (Schneckenburger 2005). In a modification of the confocal microscope, two light beams can be made to interfere with each other, so that they generate exceptionally small scanning spots (Garini et al. 2005); this approach has taken the resolution of microscopes to better than 100nm, well beyond the theoretical ‘limit’ calculated by Abbé.

With each technical development, our view of cell structure has been extended (Schliwa 2002). We now have a bewildering amount of information about the complexity and structure of cells and their contents. It should be recognized that much of the technology that we use to observe cells—fixation, staining and even GFP—perturbs what is observed. This is, of course, a well-known philosophical as well as practical problem in science, but there is much reason to be optimistic: the history of cell-structure studies clearly illustrates how science advances in cycles of technical development, increased knowledge and improved models.

Biological macromolecules, such as proteins and nucleic acids, are constructed from atoms and bonds with dimensions of around 0.1nm. To understand how macromolecules operate, we need to know how the atoms come together to form their precise and intricate shapes, thus forming structural scaffolds, catalysts and a variety of elaborate machines. Although EM has the capacity to give at least 0.1nm resolution, it is severely limited by practical difficulties and alternative techniques were, fortunately, also developed. There are now three main experimental methods that can give atomic resolution structural information—X-ray crystallography, electron crystallography and nuclear magnetic resonance (NMR).

The serendipitous discovery of X-rays by Wilhelm Röngten (1845–1923) in 1895, followed by the structure determination of crystalline common salt in 1913 by Lawrence Bragg (1890–1971), led to the discipline of X-ray crystallography. Small crystals of macromolecules are irradiated with a beam of X-rays (wavelength around 0.1nm) to produce a diffraction pattern, which is then interpreted in terms of a three-dimensional atomic model. This method has been spectacularly successful in recent years, although the first steps, by the pioneers like Max Perutz (1914–2002) and John Kendrew (1917–1997) were painstakingly slow (Rossmann 1994). A major early stumbling block was to recover essential phase information about the waves making the diffraction pattern (figure 2c). Several ways of solving this ‘phase problem’ have now been devised, including one where naturally occurring sulphur in a protein is substituted by another element, selenium. X-ray crystallography and its lesser used cousin, neutron crystallography, have now been used to solve more than 33000 macromolecular structures: see http://www.rcsb.org/pdb/Welcome.do. Protein structures used to take decades to solve, but now new structures can often be derived in a few days; the hard part is usually to obtain crystals of pure protein.

More recently, two other techniques have been shown to be capable of giving atomic resolution information about biological macromolecules. One of these is electron crystallography, where electron microscope images of thin two-dimensional crystals, collected at different angles to the electron beam (tomography), are combined with electron diffraction information to give a three-dimensional structure. This approach was used to give the first model of the structure of a protein from a salt-loving bacterium (Henderson & Unwin 1975); it was shown to have seven membrane-spanning helices. The number of structures obtained by this method is still relatively small, but there are some important examples of its use, especially with membrane proteins (Gonen et al. 2005).

The other method that can give atomic resolution structural information is NMR, a technique first demonstrated independently in 1946 by Felix Bloch (1905–1983) and Ed Purcell (1912–1997). This method observes nuclei that have magnetic dipoles. These ‘resonate’ in the radiofrequency range (10–1000MHz) when they are placed in a strong magnetic field. The resonance frequency is exquisitely sensitive to the electrons around the nuclear dipole, so that individual resonances can be resolved and assigned to particular atoms in a macromolecule. Proteins are made from strings of amino acids. There are only 20 amino acids so that even a small protein will contain several amino acids of one type in its sequence. An NMR spectrum of a small protein will usually be able to resolve all the different nuclear resonances from different groups and to assign them to specific positions in the amino acid sequence. Assignment is done by identifying the amino acids' neighbours in the known protein sequence (just as the three ‘e's in the word ‘sequence’ are made unique when neighbouring letters are considered). Thousands of specific short-range interactions (approx. 0.3nm) between nuclear dipoles can be detected in a protein. This information, combined with ‘molecular dynamics simulations’ (see next paragraph), allows the structure of macromolecules to be calculated3 (Wüthrich 2003). An advantage of the method, which has now solved over 5600 structures, is that the protein is simply dissolved in water; crystals are not required and there is no ‘phase problem’. There is, however, a practical size limit because the resonances can no longer be resolved and assigned when the macromolecules become very large. The method works best for determining the structure and dynamics of relatively small macromolecules of about 200 amino acids in length (approx. 22kDa); this limit can, however, be extended to over 50kDa by extensive and expensive isotope labelling (e.g. substituting ¹²C by ¹³C, ¹⁴N by ¹⁵N and many ¹H by ²H; Kay 2005).

The above three methods, crystallography, EM and NMR, depend heavily on computational methods to derive, refine and visualize models of the macromolecule or complex being studied. Computer modelling is also very useful for giving insight into the structure of proteins with a close relative of the known structure. Modelling can also be used to explore ways in which two molecules might dock together, an approach much used by the pharmaceutical industry in their quest for new drugs. Simulations of molecular motions in a computer, by allowing atoms to move under the influence of various energetic restraints, can give considerable insight into possible macromolecular structures and how the various parts can move with respect to each other. Such simulations are usually carried out by considering a ‘box’ containing the molecule(s) of interest plus solvent water. The possible trajectories of the atoms in the box are calculated, one very short step (10⁻¹⁵s) at a time, using laws of physics that were first described by Isaac Newton (1643–1727). An example of this approach is the exploration of how proteins can fold from an extended chain to a well-defined structure (Vendruscolo & Dobson 2005). These ‘molecular dynamics’ simulations are also very important in refining structures derived from experimental information. A difficulty is that the time-scales that can be simulated, even using very powerful computers, are relatively short (approx. 10ns) compared with the time-scales of most molecular interactions in the cell. This limitation has been relaxed to some extent recently by the realization that larger time-step sizes can often be used if suitable approximations are made (Bahar & Rader 2005).

There have been exceptional technical developments and improvements in structure-determination methods over the last 30 years. The improvements in computers are familiar to us all, but X-ray sources, NMR spectrometers, microscopes and data collection procedures are all orders of magnitude better than they were; for example, the signal-to-noise ratio obtained in a single scan NMR spectrum is now several orders of magnitude better than it was 40 years ago—a result of higher field strengths, better electronics and better data collection methods. We also must not forget that molecular biology methods have improved dramatically; almost any specified protein can now be produced by expressing its gene in host cells, often in simple bacteria, and the sequences of most important proteins are now known owing to genome-sequencing projects.

These various improvements have led to an extraordinary growth in structural information in the last 25 years. Representative examples of most classes of existing protein structures are already known. Even systems thought to be particularly intractable, such as proteins embedded in membranes, are yielding to sustained efforts (see http://blanco.biomol.uci.edu/membrane_proteins_xtal.html). The key structural features of several of the essential, multi-component molecular machines in cells have also been solved. Examples include muscle action (Geeves & Holmes 2005), the transcription of DNA into RNA (Armache et al. 2005) and the synthesis of proteins from an RNA template on the ribosome (Moore & Steitz 2005; figure 2d). In many cases, the models for these complex machines have been obtained using combinations of all the molecular structural tools mentioned above—crystallography, EM, NMR and molecular modelling. This astonishing success certainly does not mean that structural molecular biology is reaching an end. While structures of complexes like the ribosome, which are relatively stable and resistant to the rigours of isolation and purification, have now been solved, it is clear that many of the networks of protein–protein interactions which make essential complexes are transient. It will, therefore, be much harder to build up a picture of how these dynamic systems operate.

I have outlined current ways of visualizing cells (μm) and molecules (0.1nm; figure 2). How can we fit all this together to obtain an operational model of the living cell? The methods discussed so far still leave many gaps in our knowledge about the ‘bustling community of molecules’ in the cellular environment. Filling these gaps remains a major technical challenge.

EM of cell structures has already been mentioned and is a tool that can give structural information over a wide range (nanometre to micrometre). Large macromolecular complexes can be studied by EM using ‘single particle’ analysis; the particles are embedded in ice formed by rapid freezing and images are taken using a weak dose of electrons. Many thousands of noisy images are collected, analysed and averaged to obtain a three-dimensional reconstruction of the object. This method still cannot give us atomic resolution images, but resolution better than 1nm is possible (Frank 2006). This method is especially powerful when used in combination with other techniques; for example, high-resolution X-ray structures of components can be fitted into low-resolution EM images of multi-component complexes. This is the one way of finding out about the operation of an assembled cellular machine like a muscle (Geeves & Holmes 2005).

Other techniques that span structural studies of cells and molecules include those that can observe the location and properties of a single molecule at a time. Early success was achieved using ‘patch clamp’ methods, where ions passing though a single membrane-spanning channel were detected electrically (Sakmann 1992). Atomic force microscopy (Binnig & Rohrer 1983), where a sharp probe is scanned in a controlled way over molecules on a surface thus tracing their shape, has become a valuable and flexible tool both for looking at large molecules and studying various interactions (Horber & Miles 2003). Scanning EM can also be powerful in the 100nm range (Wanner et al. 2005). Another way of manipulating single molecules is to use the small, but measurable force that light exerts on an object. In 1970, Arthur Ashkin noticed that he could use laser light to trap small latex beads (Ashkin 1997). This technology, often referred to as ‘optical tweezers’, can manipulate single molecules and measure the forces they exert.

The innumerable interacting networks among cellular components in a cell are sometimes called the ‘interactome’ (Cusick et al. 2005). These interactions are the key to what makes cells ‘alive’. What experimental tools can be used to define them? Cell fractionation and analysis of the contents of the fractions are a first step; an early example was enzyme assays of fractions obtained after ultracentrifugation (Duve 1975). The fractionation approach is now generally called ‘proteomics’ when applied to studies of protein components of the cell. Protein mixtures can be resolved by spreading them out in two dimensions by electrophoresis; separation in one dimension is based on charge, the other on size. Once resolved, the different proteins can be identified by measuring their mass accurately in a mass spectrometer. A recent review classifies the location of thousands of different proteins in different cellular compartments using such methods (Yates et al. 2005). Microscopy can also determine the location of particular molecules if they are tagged with visible labels and there are ambitious projects to tag all the proteins in a genome with GFP (Simpson & Pepperkok 2003).

While a catalogue of components, with their cellular locations, is essential, we also need to know about the dynamic organization of the ‘elaborate network of interlocking assembly lines’. One way forward is to map the various interactions using ‘screening’ methods where a large number of potential targets can be investigated rapidly. One such is the ‘yeast two-hybrid’ screen where an interaction between proteins is detected by switching on a gene that results in a colour reaction. This approach has been used to identify over 4000 protein–protein interactions in the nematode worm, Caenorhabditis elegans (Li et al. 2004). Other promising methods for identifying multiple interactions include protein ‘microarrays’ (Bertone & Snyder 2005) and large-scale affinity purification (Gavin et al. 2006).

Once potential interacting partners have been identified in screens, we need to quantify the interactions using a variety of biophysical tools (Harding & O'Shea 2003; Piehler 2005). Among these is a sensor device (surface plasmon resonance) that monitors changes in mass at a surface when two components interact (Karlsson 2004). Measurements of interactions can also be carried out at the single molecule level using fluorescence microscopy (Kelley et al. 2001). For example, if two suitable fluorescent probes come within approximately 10nm of each other, the fluorescence emitted by one is perturbed by the presence of the other. This ‘fluorescence resonance energy transfer’ can be used to detect interactions between molecules and measure their separation in a living cell (Michalet et al. 2003). Another way to define macromolecular interactions is NMR (Clarkson & Campbell 2003). The advantage here is that when two molecules are added together in solution, induced perturbations in the NMR spectra can be identified and mapped onto the three-dimensional structure to show exactly where the interactions take place.

My emphasis, so far, has been on physical methods, but it has also been suggested that

A theme of this lecture is the drive towards visualization of the workings of a living cell. We live in an age where the genome sequences and structural properties of most of the component parts are known, yet the complexity of dynamic cellular networks is bewildering. It is therefore timely to try to employ mathematical methods to help, using an approach often now called ‘systems biology’ (Aderem 2005). Among the goals would be the explanations for how properties, not apparent in the individual parts, can ‘emerge’ from a complex assembly. Mathematics can help here by using sets of equations to describe a network of interacting components. The predictive and explanatory power of such models can, however, only be as good as the quantitative information (about rate constants and concentrations of the interacting components) that they rely on. Close cooperation between modellers and experimentalists should encourage the acquisition of critical quantitative data and enable the validation of models as they are constructed. In a recent example from this laboratory, it was possible to use a combination of equations and experiments to deduce how a single bacterial cell can develop into two different cell types—a spore and a mother cell—in response to stress (Iber et al. 2006); this example illustrated how mathematical modelling can guide experiments and give fresh insight into the functioning of whole systems.

To illustrate how the complex molecular interactions in a living cell can be unravelled, I will briefly discuss cell migration. All the molecular and cellular tools mentioned above have been brought to bear on this topic. Cell motility is a recognizable property of a living system and van Leeuwenhoek quickly realized that the tiny moving objects he saw in his microscope were alive. The ability of a cell to move is a necessary feature of many essential processes in life and disease, including the development of an embryo, the repair of tissue and the spread of cancer. Key questions we need to answer are: ‘how do cells move?’ and ‘how do they respond to stimuli?’ Much progress has already been achieved and a large amount of information on this topic is already available in the literature (Bray 2001; Ridley et al. 2003; Webb et al. 2005) and Websites (http://www.cellmigration.org/index.shtml). I will concentrate here on eukaryotic cells that can crawl on surfaces, such as fibroblasts (skin cells) and neutrophils (a type of white blood cell).

Figure 3 contains a simplified illustration of a cell moving on a surface. Neutrophils migrate from the blood stream to infected tissues to hunt out and destroy unwanted invaders when they ‘smell’ danger. The danger signal may be a peptide derived from bacteria; this is detected by a cell surface protein receptor, which then transmits a signal to the cell interior, resulting in cell movement in a particular direction. The chief forward propulsion force comes from the directed addition of globular actin monomers to a growing actin filament (F-actin). This actin assembly process is driven by hydrolysis of adenosine triphosphate, the main fuel of life. Another key feature of cell propulsion in crawling cells is the formation of contacts, called focal adhesions, between the extracellular molecules, the extracellular matrix and the actin filaments. These provide the ‘grip’ that allows the cell to drag itself forward. The cells extend a thin (approx. 200nm thick) leaflet of cytoplasm, called a lamellipodium, at the front of the cell, where new focal adhesions are formed. At the same time, focal adhesions at the rear of the cell dissolve and the actin filaments retract. Without an external signal, the cells stop moving and go into a quiescent state. A few highlights and key features of the molecular processes involved in cell migration, particularly focal adhesion formation, follow.

Figure 5 An illustration of two of the conformational states available to integrins. These correspond to an ‘off’ state on the left and an ‘on’ state, also shown in figure 3e. The large movements mainly arise from a rearrangement (more ...)

The history of single cell investigation, begun over 300 years ago, has shown that the more we examine cells and their constituents the more remarkable they seem. Innumerable carefully balanced processes—self-assembly and disassembly, phosphorylation and dephosphorylation, synthesis and breakdown—are continually in play and the balance is adjusted by small changes in environment and energy flow. Our main challenge is to discover how all these components work together in a concerted way.

Grateful thanks are given to: many essential colleagues who have mentored and worked with me over the years; several friends, notably Mark Howarth, who gave valuable comments on this manuscript; various agencies, including the Wellcome Trust, BBSRC, Medical Research Council and the National Institutes of Health Cell Migration Consortium, who have provided funds and the Royal Society who gave me the unexpected and undeserved honour to present this lecture.