Trend: Does cell biology need physicists?

Charles W. Wolgemuth, University of Connecticut Health Center, Department of Cell Biology and Center for Cell Analysis and Modeling, Farmington, CT 06030-3505, USA
Published January 10, 2011  |  Physics 4, 4 (2011)  |  DOI: 10.1103/Physics.4.4
+Enlarge image Figure 1
Credit: Carin Cain

Figure 1 The complexity of cellular biology. (a) A subset of the chemical reactions that drive eukaryotic cell crawling. In brief, cells sense the environment through membrane bound proteins. Activation of these receptors leads to activation of a number of other proteins that promote the polymerization of actin. The biochemical reactions that govern the dynamics of actin are included. These chemical reactions produce cell motility. (b)–(d) Time series of a cancer cell (HT1080 fibrosarcoma cell) moving through a collagen I matrix. There are two hour intervals between each frame. (Images courtesy of D. Wirtz, Johns Hopkins University.)

+Enlarge image Figure 2
Credit: Carin Cain

Figure 2 Some examples where physics has shed light on biology. (a) Physics-based simulations of the walking of myosin VI predicted that the molecule would produce both hand-over-hand and inchworm type movements [8], which was later confirmed with single molecule experiments [57]. (Image courtesy of S. X. Sun, Johns Hopkins University.) (b) A crawling cell is driven primarily by the dynamics of its actin cytoskeleton, a network of filaments that polymerize at the leading edge of the cell. Force balance on the crawling cell comes from membrane forces (tension and bending), a polymerization forces, and contractile forces generated inside the cell by myosin motors and other unknown mechanisms. Here we depict a fish keratocyte, which crawls at a roughly constant speed V, while maintaining a steady cell shape. The cell body is shown in gray. (c) Stochastic simulations of microtubules determined some of the constraints for the accurate and efficient capturing of chromosomes during the formation of the mitotic spindle. (Image courtesy of A. Mogilner, University of California, Davis.)

+Enlarge image Figure 3
Credit: Carin Cain

Figure 3 How physicists may be most useful for cell biology. (a) The cloud of electrons around a water molecule leads to a complex interaction potential between two water molecules (based on Ref. [58]). When we consider the bulk flow of a fluid around a ball, though, these complex interactions lead to a single bulk viscosity, which can be used to accurately calculate the fluid flows about the ball and the resistive force exerted on the ball. (b) In a similar fashion, it is possible to consider the stresses that are created inside a cell due to the dynamics of actin, without worrying about the complex reactions that create this dynamics (as depicted in Fig. 1). Combining this average dipole stress of a single cell and the adhesive interactions between neighboring cells can accurately describe the collective behavior of cells during wound healing. The bottom left panel shows the cellular flows that accompany wound healing (originally published in Ref. [56] and reprinted with permission from P. Silberzan) and a simulation from Lee and Wolgemuth (unpublished data).

Introduction

Cells are the fundamental units of life. At a basic level, a cell’s primary functions are to grow, replicate, and divide. Survival, at least for a sufficient length of time, is also extremely important in order to achieve these other functions. However, as humans, we want more. We don’t only want our cells to provide us with a sufficient length of life that we can reproduce; we would also like to guarantee ourselves a long and healthy existence. These desires, though, are all too often thwarted by disease. Though diseases can be caused by a number of different factors, such as molecular toxins, acquired or inherited genetic defects, viruses, and bacteria, which all act at different scales (molecular, cellular, and even multicellular), in most cases, disease represents a cellular level process; i.e., most diseases are, at their heart, a disruption of cellular function, which then ultimately produces organ or organism disability or failure.

Since humans would prefer to live a disease-free existence, it is not surprising that biological and health-related research is highly respected or that the National Institutes of Health have deeper pockets than the National Science Foundation. In addition, recent technological advances have allowed us to look at molecules and cells in much more detail. We are now able to resolve and quantify, at subcellular and even molecular levels, the spatiotemporal dynamics of molecules and processes inside cells. Therefore molecular and cellular biology have become more amenable to a research paradigm that melds experimental and theoretical investigations, and, more specifically, research that is geared toward an accurate description of how things move in space and time. It is, therefore, not surprising that physicists would be attracted to cell biological research.

But the past has shown that cell biologists are extremely capable of making great progress without much need for physicists (other than needing physicists and engineers to develop many of the technologies that they use). Do the new data and new technological capabilities require a physicist’s viewpoint to analyze the mechanisms of the cell? Is physics of use to cell biology?

The elephants in the room: genetics, proteomics, and systems biology

It is hard to overestimate the role that genetics has played in biology over the last 30 years. Molecular and cellular biology, to a very large extent, are about proteins and their interactions. The ability to perturb a specific protein inside a cell and then observe the consequences has led to an amazing number of advances in our understanding of the roles of certain proteins in cellular function. It would almost seem that if we could just compile a list of all the proteins inside the cell (a field called proteomics) and determine their reactions and reaction rates, we would understand how a cell works. With high-throughput methods, we are now able to quickly measure DNA transcripts and protein levels and correlate these with observed cell characteristics (“phenotypes”) [1]. We have amassed a lot of data, and the more we put together, the more complex and harder to interpret the data becomes.

For a cell with a fairly small genome, such as the yeast Saccharomyces cerevisiae, which can produce between 104 and 105 proteins, the number of possible protein interactions is 105107 [1]. Even if we consider a single cellular function (for instance, the ability of a eukaryotic cell to move along a substrate) the chemical reaction network that describes this behavior appears incomprehensible (Fig. 1). The hope of systems biology is to use a higher level approach to understand these systems, to analyze the reaction networks at a more functional level and provide a framework for assembling models of biological pathways from systematic measurements [2]. Absent from this discussion is any mention of the physics involved in cellular processes. It is possible that the physics that cells must deal with is slave to the reactions; i.e., the protein levels and kinetics of the biochemical reactions determine the behavior of the system, and any physical processes that a cell must accomplish are purely consequences of the biochemistry. Or, could it be that cellular biology cannot be fully understood without physics?

Some examples of successful physical biology

The successes of genetics and biochemistry in describing cellular function have overshadowed an important point: Cells are not isolated bags of proteins. The inside of a cell has structure, and this structure is not static. In addition, cells must live in and interact with the environment, which is often unpredictable and not always favorable. In order to grow, move, and survive, cells must be able to produce force. That is, physics matters, at least at some level.

Potential pitfalls for physicists in biology

Fifteen years ago, around the time that I began working in biophysics, there were very few collaborations between physicists and cell biologists, especially if the physicists were theorists. Theory was, and still is to a good degree, a word that should be avoided in the presence of biologists. Those of us who use math and computers to try to understand how cells work tend to call ourselves modelers instead of theorists. My suspicion is that many of the first physicists and mathematicians who tried to develop models for how biology works attempted to be too abstract or too general. As physicists we like to try to find universal laws, and though there are undoubtedly general principles at play in cell biology, it is likely that there are no real universal rules. Evolution need not find only one way to do something but more often probably finds many. Rather than search out generalities, we will serve biology better if we deal with specifics. As Aharon Katchalsky, who is largely credited with bringing nonequilibrium thermodynamics to biology, purportedly said, “It is easier to make a theory of everything than a theory of something.”

In recent years, physicists have done a much better job at addressing specific problems in biology. However, there still remains a divide between the two communities. Indeed, good physical biology that comes out of the physics community often goes unnoticed or is under appreciated. The burden falls on us to properly convey our work so as to be accessible to biologists. We need to make conscious efforts at communication and dissemination of our results. Two useful approaches toward this end are to publish in broader audience journals that reach both communities, and for papers that contain theoretical analyses to provide a qualitative description of the modeling in the main text, while leaving the more mathematical details for the appendices or supplemental material (for further discussion of this topic, see Ref. [55]). It is also of prime importance to maintain and to forge new connections between physicists and biologists.

There is one other concern that I harbor; I worry about the misconceived equating of successful computer simulations and understanding. Over the past 30 years, the computational power that one has at one’s fingertips has increased by orders of magnitude. We are now able to simulate hundreds of coupled ODEs describing large biochemical networks. We can solve these in two and three dimensions with arbitrary transport mechanisms. We can also reproduce in silico the stochastic dynamics of thousands of interacting proteins. We get closer and closer to having the ability to simulate, molecule by molecule, a reasonable fraction of a cell. But then I reflect on the modest advances that these investigations have made in our understanding of how cells work. It seems that Turing may have moved us farther forward with his analytic analysis of reaction-diffusion systems than we have moved since. It would almost seem that there is little or no correlation between computer power and true scientific advancement.

Visions of the future

Though I do not know in which directions biophysics will head, my current impression is that physicists will have the most success by trying to provide a simpler view of the astounding complexity that we see in cellular biology. In the end, the massive interconnected biochemical networks have developed to achieve a countable number of functions, and on top of this, some of the complexity is redundant, a means for self-preservation in the face of mutation and a harsh environment. It therefore may be useful to focus our attention at the level of the functions rather than at the level of the proteins. Reductionism is not always useful. Physicists have done very well with determining what details are important and which aren’t.

There are at least two means by which this can be done. The first is to examine a high-level behavior and extrapolate general principles. Take, for example, the classic story of Newton, whereby the law of gravity was intuited by the falling of an apple. Whether the story is true or not, Newton was able to determine general laws for understanding macroscopic behavior (as long as the macroscopic object is not moving too fast). The details of quantum mechanics and the intermolecular forces between atoms do not really matter for describing the flight of the baseball on its route from the pitcher’s hand to the awaiting bat; the interaction between the ball and the air matter much more. And now consider this mass of air that surrounds the traveling ball [Fig. 3 (a)]. Once again, the details of the molecular interactions, or even the identities of the molecular constituents of the air, do not matter so much. Between statistical mechanics and fluid mechanics, we can gain a much better description of the bulk behavior of the air than we could if we considered the air at a more fundamental level. Indeed, at the level of a fluid, the molecular details average together into a much smaller set of bulk material parameters, such as the viscosity or the coefficient of thermal expansion. It is these bulk parameters that determine the course of the flying baseball.

As an example, Pilhwa Lee and I have recently been working on a model to describe the physics that is involved in wound healing. When an organism is wounded, epithelial cells crawl to fill in the wounded area. An experimental method for exploring this process is to grow a monolayer of epithelial cells on a substrate and then to “wound” the layer using a scalpel or some other object to scrape away a region of cells. Pascal Silberzan and co-workers have shown that the motion of the cells during wound healing is not trivial and involves long-range order and complex cellular flows [56]. Based on these observations and an analogy between crawling cells and the collective swimming of bacteria, we proposed a model that captures many features that are observed in wound healing assays. We suggest that two dominant physical attributes are responsible for most of the processes involved in wound healing: (i) the dipole nature of the stress distribution of a crawling cell and (ii) cell-cell adhesions. This model absorbs all of the complex biochemistry and actin dynamics inside a cell into two parameters that describe the stress that a cell exerts on its surroundings, and cell-cell adhesion dynamics can be shown to lead to visco-elastic couplings between cells [Fig. 3 (b)]. Therefore, where many groups have focused extensively on the complex biochemical interactions inside the cell, at a functional level (i.e., healing of a wound), many of the molecular details may only act to regulate a few bulk physical parameters.

However, for biology, and especially medicine, it will not suffice to just develop nonreductionist theories of cellular function; it will also be necessary to compute the effective parameters of the theories in terms of the actual molecular level interactions. (Yet another task for which physicists are well suited.) The current paradigm of disease treatment is molecule based. We develop drugs that interact with or replace the proteins that our bodies are or aren’t making. We seek out poisons that specifically target cancer cells. Alzheimer’s patients are treated with molecules that prevent the breakdown of acetylcholine, a chemical implicated in learning and memory. And, some diseases, such as cystic fibrosis, can even be treated by replacing defective genes in an individual with a functional copy of the gene. In addition, biological research is strongly tied to the genetic approach. A specific protein is knocked out, up-regulated, or down-regulated and the resulting phenotype is determined. To be truly successful, we must provide an understanding of biology that spans the gorge from biochemistry and genetics to cellular function, and do it in such a way that our models and experiments are not only informative about physics, but directly impact biology.

Cell biology is awaiting these descriptions. And it may be that physicists are the most able to draw these connections between the protein level description of cellular biology that currently dominates and a more intuitive, yet still quantitative, description of the behavior of cells and their responses to their environments.

Acknowledgments

The author would like to thank S. X. Sun, G. Huber, and I. Moraru for useful discussions.

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About the Author: Charles W. Wolgemuth


Charles W. Wolgemuth

Charles Wolgemuth received his Ph.D. from the University of Arizona in 2000. After a brief stint at the University of California, Berkeley, working with George Oster, he took a faculty position in the Department of Cell Biology and the Richard D. Berlin Center for Cell Analysis and Modeling at the University of Connecticut Health Center, where he has been since. He is currently the Director for the Cell Analysis and Modeling graduate program and an Editorial Board Member for the Biophysical Journal. His research investigates the mechanisms that cells use to move, grow, and to create and maintain their shapes.



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