Table of contents

'It is happily no longer axiomatic that a biophysicist is a physiologist who can fix his own amplifier. Fortunately, physicists are still drifting into biology and bringing new ideas. Please dear colleagues, do take the time to learn biochemistry.' Harold Morowitz provides a personal perspective on working at the interface between the physical and biological sciences.

'I didn't really think of this as moving into biology, but rather as exploring another venue in which to do physics.' John Hopfield provides a personal perspective on working on the border between physical and biological sciences.

Despite their cultural differences, physics and biology are destined to interact with each other more in the future. The reason is that modern physics is fundamentally about codification of emergent law, and life is the greatest of all emergent phenomena.

Stan Ulam, the famous mathematician, said once to Hans Frauenfelder: 'Ask not what Physics can do for biology, ask what biology can do for physics'. The interaction between biologists and physicists is a two-way street. Biology reveals the secrets of complex systems, physics provides the physical tools and the theoretical concepts to understand the complexity. The perspective gives a personal view of the path to some of the physical concepts that are relevant for biology and physics (Frauenfelder et al 1999 Rev. Mod. Phys.71 S419–S442). Schrödinger's book (Schrödinger 1944 What is Life? (Cambridge: Cambridge University Press)), loved by physicists and hated by eminent biologists (Dronamraju 1999 Genetics153 1071–6), still shows how a great physicist looked at biology well before the first protein structure was known.

Concepts rooted in physics are becoming increasingly important in biology as we transition to an era in which quantitative descriptions of all processes from molecular to cellular level are needed. In this perspective I discuss two unexpected findings of universal behavior, uncommon in biology, in the self-assembly of proteins and RNA. These findings, which are surprising, reveal that physics ideas applied to biological problems, ranging from folding to gene expression to cellular movement and communication between cells, might lead to discovery of universal principles operating in adoptable living systems.

Biological physics is clearly becoming one of the leading sciences of the 21st century. This field involves the cross-fertilization of ideas and methods from biology and biochemistry on the one hand and the physics of complex and far from equilibrium systems on the other. Here I want to discuss how biological physics is a new area of physics and not simply applications of known physics to biological problems. I will focus in particular on the new advances in theoretical physics that are already flourishing today. They will become central pieces in the creation of this new frontier of science.

I firmly believe that interaction between physics and biology is not only natural, but inevitable. Kamal Shukla provides a personal perspective on working at the interface between the physical and biological sciences.

'Many physicists see the interface with biology as an exciting place to be'. Athene Donald provides a personal perspective on working at the interface between the physical and biological sciences.

My journey into the physics of living systems began with the most fundamental organisms on Earth, bacteria, that three decades ago were perceived as solitary, primitive creatures of limited capabilities. A decade later this notion had faded away and bacteria came to be recognized as the smart beasts they are, engaging in intricate social life through a sophisticated chemical language. Acting jointly, these tiny organisms can sense the environment, process information, solve problems and make decisions so as to thrive in harsh environments. The bacterial power of cooperation manifests in their ability to develop large colonies of astonishing complexity. The number of bacteria in a colony can amount to many billions, yet they exchange 'chemical tweets' that reach each and every one of them so they all know what they're all doing, each cell being both actor and spectator in the bacterial Game of Life. I share my encounters with bacteria, what I learned about the secrets of their social life and wisdom of the crowd, and why and how, starting as a theoretical physicist, I found myself studying social intelligence of bacteria. The story ends with a bacteria guide to cyber-war on cancer.

Good communication, whether it is between quorum-sensing bacteria or the different scientists studying those critters, is the key to a successful interdisciplinary collaboration, Bonnie Bassler and Ned Wingreen provide a personal perspective on working at the interface between the physical and biological sciences.

Unlike a new generation of scientists that are being trained directly to work on the physics of living systems, most of us more senior members of the community had to find our way from other research areas. We all have our own stories as to how we made this transition. Here, I describe how a chance encounter with the eukaryotic microorganism Dictyostelium discoideum led to a decades-long research project and taught me valuable lessons about how physics and biology can be mutually supportive disciplines.

When the author arrived in Berkeley, in the mid 1970s, to study Biophysics he soon felt as if he was engaging himself in a somewhat marginal activity. Biology was then entering another of its cyclical periods of annotation that was to culminate with the human genome project. Two decades later, however, at the end of this process, it had become clear that two main tasks were acquiring a central importance in biological research: a renewed push for a quantitative, precise description of biological systems at the molecular level, and efforts towards an integrated understanding of the operation, control, and coordination of cellular processes. Today, these have become two of the most fertile research areas in Biophysics.

Biology will almost certainly be the predominant science of the twenty-first century but, for it to become successfully so, it will need to embrace some of the quantitative, analytic, predictive culture that has made physics so successful. This includes the search for underlying principles, systemic thinking at all scales, the development of coarse-grained models, and closer ongoing collaboration between theorists and experimentalists. This article presents a personal, slightly provocative, perspective of a theoretical physicist working in close collaboration with biologists at the interface between the physical and biological sciences.

Understanding how the immune system works is a grand challenge in science with myriad direct implications for improving human health. The immune system protects us from infectious pathogens and cancer, and maintains a harmonious steady state with essential microbiota in our gut. Vaccination, the medical procedure that has saved more lives than any other, involves manipulating the immune system. Unfortunately, the immune system can also go awry to cause autoimmune diseases. Immune responses are the product of stochastic collective dynamic processes involving many interacting components. These processes span multiple scales of length and time. Thus, statistical mechanics has much to contribute to immunology, and the oeuvre of biological physics will be further enriched if the number of physical scientists interested in immunology continues to increase. I describe how I got interested in immunology and provide a glimpse of my experiences working on immunology using approaches from statistical mechanics and collaborating closely with immunologists.

Political correctness urges us to state how wonderful it is to work with biologists and how, just as the lion will someday lie down with the lamb, so will interdisciplinary work, where biologists and physicists are mixed together in light, airy buildings designed to force socialization, give rise to wonderful new science. But it has been said that the only drive in human nature stronger than the sex drive is the drive to censor and suppress, and so I claim that it is OK for physicists and biologists to maintain a wary distance from each other, so that neither one censors or suppresses the wild ideas of the other.

The fundamentals of neuronal membrane excitability are globally described using the Hodgkin-Huxley (HH) model. The HH model, however, does not account for a number of biophysical phenomena associated with action potentials or propagating nerve impulses. Physical mechanisms underlying these processes, such as reversible heat transfer and axonal swelling, have been compartmentalized and separately investigated to reveal neuronal activity is not solely influenced by electrical or biochemical factors. Instead, mechanical forces and thermodynamics also govern neuronal excitability and signaling. To advance our understanding of neuronal function and dysfunction, compartmentalized analyses of electrical, chemical, and mechanical processes need to be revaluated and integrated into more comprehensive theories. The present perspective is intended to provide a broad overview of biophysical forces that can influence neural function, but which have been traditionally underappreciated in neuroscience. Further, several examples where mechanical forces have been shown to exert their actions on nervous system development, signaling, and plasticity are highlighted to underscore their importance in sculpting neural function. By considering the collective actions of biophysical forces influencing neuronal activity, our working models can be expanded and new paradigms can be applied to the investigation and characterization of brain function and dysfunction.

The inositol trisphosphate receptor (IPR) is a crucial ion channel that regulates the Ca²⁺ influx from the endoplasmic reticulum (ER) to the cytoplasm. A thorough study of the IPR channel contributes to a better understanding of calcium oscillations and waves. It has long been observed that the IPR channel is a typical biological system which performs adaptation. However, recent advances on the physical essence of adaptation show that adaptation systems with a negative feedback mechanism, such as the IPR channel, must break detailed balance and always operate out of equilibrium with energy dissipation. Almost all previous IPR models are equilibrium models assuming detailed balance and thus violate the dissipative nature of adaptation. In this article, we constructed a nonequilibrium allosteric model of single IPR channels based on the patch-clamp experimental data obtained from the IPR in the outer membranes of isolated nuclei of the Xenopus oocyte. It turns out that our model reproduces the patch-clamp experimental data reasonably well and produces both the correct steady-state and dynamic properties of the channel. Particularly, our model successfully describes the complicated bimodal [Ca²⁺] dependence of the mean open duration at high [IP₃], a steady-state behavior which fails to be correctly described in previous IPR models. Finally, we used the patch-clamp experimental data to validate that the IPR channel indeed breaks detailed balance and thus is a nonequilibrium system which consumes energy.

Eukaryotic chemotaxis is usually mediated by intracellular signals that tend to localize at the front or back of the cell. Such intracellular polarities frequently require no extracellular guidance cues, indicating that spontaneous polarization occurs in the signal network. Spontaneous polarization activity is considered relevant to the persistent motions in random cell migrations and chemotaxis. In this study, we propose a theoretical model that connects spontaneous intracellular polarity and motile ability in a chemoattractant solution. We demonstrate that the intracellular polarity can enhance the accuracy of chemotaxis. Chemotactic accuracy should also depend on chemoattractant concentration through the concentration-dependent correlation time in the polarity direction. Both the polarity correlation time and the chemotactic accuracy depend on the degree of responsiveness to the chemical gradient. We show that optimally accurate chemotaxis occurs at an intermediate responsiveness of intracellular polarity. Experimentally, we find that the persistence time of randomly migrating Dictyostelium cells depends on the chemoattractant concentration, as predicted by our theory. At the optimum responsiveness, this ameboid cell can enhance its chemotactic accuracy tenfold.

Competition between independently arising beneficial mutations is enhanced in spatial populations due to the linear rather than exponential growth of clones. Recent theoretical studies have pointed out that the resulting fitness dynamics is analogous to a surface growth process, where new layers nucleate and spread stochastically, leading to the build up of scale-invariant roughness. This scenario differs qualitatively from the standard view of adaptation in that the speed of adaptation becomes independent of population size while the fitness variance does not. Here we exploit recent progress in the understanding of surface growth processes to obtain precise predictions for the universal, non-Gaussian shape of the fitness distribution for one-dimensional habitats, which are verified by simulations. When the mutations are deleterious rather than beneficial the problem becomes a spatial version of Mullerʼs ratchet. In contrast to the case of well-mixed populations, the rate of fitness decline remains finite even in the limit of an infinite habitat, provided the ratio ${{U}_{d}}/{{s}^{2}}$ between the deleterious mutation rate and the square of the (negative) selection coefficient is sufficiently large. Using, again, an analogy to surface growth models we show that the transition between the stationary and the moving state of the ratchet is governed by directed percolation.

The mechanical properties within the cell are regulated by the organization of the actin cytoskeleton, which is linked to the extracellular environment through focal adhesion proteins that transmit force. Chemical and mechanical stimuli alter the organization of cytoskeletal actin, which results in changes in cell shape, adhesion, and differentiation. By combining particle-tracking microrheology and traction force cytometry, we can monitor the mechanical properties of the actin meshwork and determine how changes in the intracellular network contribute to force generation. In this study, we investigated the effects of chemical (differentiation factors) and mechanical (substrate rigidity) stimuli important in mesenchymal stem cell (MSC) differentiation on the intracellular mechanics and traction stress generation. We found the presence of adipogenic factors resulted in stiffening of the actin meshwork regardless of substrate rigidity. In contrast, these factors increased traction stresses on hard substrates, which was associated with increased expression of contractility genes. Furthermore, MSCs cultured on hard substrates expressed both adipogenic and osteogenic markers indicative of mixed differentiation. On hard substrates, heterogeneity in the local elastic modulus-traction stress correlation was also increased in response to adipogenic factors, indicating that these mechanical properties may be reflective of differences in the level of MSC differentiation. These results suggest intracellular rheology and traction stress generation are spatially regulated and contribute insight into how single cell mechanical forces contribute to MSC differentiation.

The twin-arginine translocation (Tat) system transports folded proteins of various sizes across both bacterial and plant thylakoid membranes. The membrane-associated TatA protein is an essential component of the Tat translocon, and a broad distribution of different sized TatA-clusters is observed in bacterial membranes. We assume that the size dynamics of TatA clusters are affected by substrate binding, unbinding, and translocation to associated TatBC clusters, where clusters with bound translocation substrates favour growth and those without associated substrates favour shrinkage. With a stochastic model of substrate binding and cluster dynamics, we numerically determine the TatA cluster size distribution. We include a proportion of targeted but non-translocatable (NT) substrates, with the simplifying hypothesis that the substrate translocatability does not directly affect cluster dynamical rate constants or substrate binding or unbinding rates. This amounts to a translocation model without specific quality control. Nevertheless, NT substrates will remain associated with TatA clusters until unbound and so will affect cluster sizes and translocation rates. We find that the number of larger TatA clusters depends on the NT fraction f. The translocation rate can be optimized by tuning the rate of spontaneous substrate unbinding, ${{\Gamma }_{U}}$. We present an analytically solvable three-state model of substrate translocation without cluster size dynamics that follows our computed translocation rates, and that is consistent with in vitro Tat-translocation data in the presence of NT substrates.

In cells and in in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework in which to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the balance between supply (concentration of motor proteins in the flow chamber) and demand (total number of polymerized tubulin heterodimers). We present analytical results for the density profiles of bound motors and the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir. We then propose experiments for validating our models and discuss how the 'supply–demand' effects can regulate motor traffic also in in vivo conditions.

Cell clustering and scattering play important roles in cancer progression and tissue engineering. While the extracellular matrix (ECM) is known to control cell clustering, much of the quantitative work has focused on the analysis of clustering between cells with strong cell–cell junctions. Much less is known about how the ECM regulates cells with weak cell–cell contact. Clustering characteristics were quantified in rat adenocarcinoma cells, which form clusters on physically adsorbed collagen substrates, but not on covalently attached collagen substrates. Covalently attaching collagen inhibited desorption of collagen from the surface. While changes in proliferation rate could not explain differences seen in the clustering, changes in cell motility could. Cells plated under conditions that resulted in more clustering had a lower persistence time and slower migration rate than those under conditions that resulted in less clustering. Understanding how the ECM regulates clustering will not only impact the fundamental understanding of cancer progression, but also will guide the design of tissue engineered constructs that allow for the clustering or dissemination of cells throughout the construct.