Chapter 9 – Emerging Biophysics Techniques  397

Systems biophysics approaches have an enormous potential to bridge the genotype to

phenotype gap. Namely, we now have a very good understanding of the composition, type,

and number of genes from sequencing approaches in an organism (see Chapter 7) and also

separately have several approaches that can act as a metric for the phenotype, or behavior, of

a component of a biological process. However, traditionally it has not been easy to correlate

the two in general biological processes that have a high degree of complexity. The key issue

here is with the high number of interactions between different components of different bio­

logical systems.

However, a systems biophysics approach offers the potential to add significant insight here.

Systems biophysics on cells incorporates experimental cellular measurements using a range

of biophysics tools, with the mathematical modeling of systems biology. A useful modern

example is that of chemotaxis, which can operate at the level of populations of several cells,

such as in the movement of small multicellular organisms, and at the level of single cells, such

as the movement of bacteria.

Chemotaxis is a form of signal transduction, which involves the initial detection of external

chemicals by specific cell membrane receptor molecules and complexes of molecules, but

which ultimately span several length and time scales. It is a remarkable process that enables

whole cells to move ultimately toward a source of food or away from noxious substances.

It involves the detection of external chemoattractants and chemorepellents, respectively,

that act as ligands to bind either directly to receptors on the cell membrane or to adapter

molecules, which then in turn bind to the receptor (which we discussed in the context of an

Ising model previously in Chapter 8). Typically, binding results in a conformational change

of the receptor that is transformed via several coupled chemical reaction cascades inside the

cell, which, by a variety of other complex mechanisms, feed into the motility control system

of that cell and result in concerted, directional cellular movement.

In prokaryotes such as bacteria, it is the means by which cells can swim toward abun­

dant food supplies, while in eukaryotes, this process is critical in many systems that rely on

concerted, coordinated responses at the level of many cells. Good examples of chemotaxis

include the immune response, patterning of cells in neuron development, and the morpho­

genesis of complex tissues during different stages of early development in an organism.

Cells from the fungus Dictyostelium discoideum display a strong chemotaxis response to

cyclic adenosine monophosphate (cAMP), which is mediated through a cell surface receptor

complex and G protein–​linked signaling pathway. Using fluorescently labeled Cy3-​cAMP in

combination with single-​molecule TIRF imaging and single particle tracking on live cells,

researchers were able to both monitor the dynamic localization of ligand-​bound receptor

clusters and measure the kinetics of ligand binding in the presence of a chemoattractant con­

centration gradient (Figure 9.1a).

In eukaryotic cells, such as in those of the multicellular organism Dictyostelium, the detec­

tion of the direction of a concentration gradient of an external chemical is made by a complex

mechanism that essentially compares the rate of binding of ligand by receptors on one side to

those on the other. That is, it utilizes the physical length scale of the cell to generate probes in

different regions of the concentration gradient such that on the side of the higher concentra­

tion there will be a small but significant and measurable increase in the rate of ligand binding

compared to the opposite side of the cell. This is in effect spatial sampling of the concentra­

tion gradient. Prokaryotic cells such as bacteria do not use such a mechanism because their

physical length scale of ~10⁻⁶ m results in far too small a difference in ligand binding rates

either side of the cell above the level of stochastic noise, at least for the relatively small con­

centration gradients in external ligand that the cell may need to detect. Instead, the cellular

strategy evolved is one of temporal sampling of the concentration gradient.

Bacterial sensing and reaction to their environment has been well studied using biophys­

ical tools, in particular fluorescence microscopy in living, functional cells at a single-​

molecule level. Their ability to swim up a concentration gradient of a chemical attractant is

well known, so these cells can clearly detect their surroundings and act appropriately. These

systems are excellent models for general sensory networks in far more complex organisms—​

one of the great advantages of using bacteria is that their comparative low complexity allows

experiments to be far more controlled and their results far more definitive in terms of