Cytoplasmic Flow and Mixing Due to Deformation of Motile Cells.

The cytoplasm of a living cell is a dynamic environment through which intracellular components must move and mix. In motile, rapidly deforming cells such as human neutrophils, bulk cytoplasmic flow couples cell deformation to the transport and dispersion of cytoplasmic particles. Using particle-tracking measurements in live neutrophil-like cells, we demonstrate that fluid flow associated with the cell deformation contributes to the motion of small acidic organelles, dominating over diffusion on timescales above a few seconds. We then use a general physical model of particle dispersion in a deforming fluid domain to show that transport of organelle-sized particles between the cell periphery and the bulk can be enhanced by dynamic deformation comparable to that observed in neutrophils. Our results implicate an important mechanism contributing to organelle transport in these motile cells: cytoplasmic flow driven by cell shape deformation

Listeria monocytogenes cell-to-cell spread in epithelia is heterogeneous and dominated by rare pioneer bacteria.

Listeria monocytogenes hijacks host actin to promote its intracellular motility and intercellular spread. While L. monocytogenes virulence hinges on cell-to-cell spread, little is known about the dynamics of bacterial spread in epithelia at a population level. Here, we use live microscopy and statistical modeling to demonstrate that L. monocytogenes cell-to-cell spread proceeds anisotropically in an epithelial monolayer in culture. We show that boundaries of infection foci are irregular and dominated by rare pioneer bacteria that spread farther than the rest. We extend our quantitative model for bacterial spread to show that heterogeneous spreading behavior can improve the chances of creating a persistent L. monocytogenes infection in an actively extruding epithelium. Thus, our results indicate that L. monocytogenes cell-to-cell spread is heterogeneous, and that rare pioneer bacteria determine the frontier of infection foci and may promote bacterial infection persistence in dynamic epithelia. Editorial note:This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter)

A First Exposure to Statistical Mechanics for Life Scientists

Statistical mechanics is one of the most powerful and elegant tools in the quantitative sciences. One key virtue of statistical mechanics is that it is designed to examine large systems with many interacting degrees of freedom, providing a clue that it might have some bearing on the analysis of the molecules of living matter. As a result of data on biological systems becoming increasingly quantitative, there is a concomitant demand that the models set forth to describe biological systems be themselves quantitative. We describe how statistical mechanics is part of the quantitative toolkit that is needed to respond to such data. The power of statistical mechanics is not limited to traditional physical and chemical problems and there are a host of interesting ways in which these ideas can be applied in biology. This article reports on our efforts to teach statistical mechanics to life science students and provides a framework for others interested in bringing these tools to a nontraditional audience in the life sciences.Comment: 27 pages, 16 figures. Submitted to American Journal of Physic

Listeria monocytogenes Invades the Epithelial Junctions at Sites of Cell Extrusion

Listeria monocytogenes causes invasive disease by crossing the intestinal epithelial barrier. This process depends on the interaction between the bacterial surface protein Internalin A and the host protein E-cadherin, located below the epithelial tight junctions at the lateral cell-to-cell contacts. We used polarized MDCK cells as a model epithelium to determine how L. monocytogenes breaches the tight junctions to gain access to this basolateral receptor protein. We determined that L. monocytogenes does not actively disrupt the tight junctions, but finds E-cadherin at a morphologically distinct subset of intercellular junctions. We identified these sites as naturally occurring regions where single senescent cells are expelled and detached from the epithelium by extrusion. The surrounding cells reorganize to form a multicellular junction that maintains epithelial continuity. We found that E-cadherin is transiently exposed to the lumenal surface at multicellular junctions during and after cell extrusion, and that L. monocytogenes takes advantage of junctional remodeling to adhere to and subsequently invade the epithelium. In intact epithelial monolayers, an anti-E-cadherin antibody specifically decorates multicellular junctions and blocks L. monocytogenes adhesion. Furthermore, an L. monocytogenes mutant in the Internalin A gene is completely deficient in attachment to the epithelial apical surface and is unable to invade. We hypothesized that L. monocytogenes utilizes analogous extrusion sites for epithelial invasion in vivo. By infecting rabbit ileal loops, we found that the junctions at the cell extrusion zone of villus tips are the specific target for L. monocytogenes adhesion and invasion. Thus, L. monocytogenes exploits the dynamic nature of epithelial renewal and junctional remodeling to breach the intestinal barrier

A First Exposure to Statistical Mechanics for Life Scientists: Applications to Binding

Statistical mechanics is one of the most powerful and elegant tools in the quantitative sciences. One key virtue of statistical mechanics is that it is designed to examine large systems with many interacting degrees of freedom, providing a clue that it might have some bearing on the analysis of the molecules of living matter. As a result of data on biological systems becoming increasingly quantitative, there is a concomitant demand that the models set forth to describe biological systems be themselves quantitative. We describe how statistical mechanics is part of the quantitative toolkit that is needed to respond to such data. The power of statistical mechanics is not limited to traditional physical and chemical problems and there are a host of interesting ways in which these ideas can be applied in biology. This article reports on our efforts to teach statistical mechanics to life science students with special reference to binding problems in biology and provides a framework for others interested in bringing these tools to a nontraditional audience in the life sciences. 1 1 Does Statistical Mechanics Matter in Biology

Fundamental limits on the rate of bacterial growth

Recent years have seen an experimental deluge interrogating the relationship between bacterial growth rate, cell size, and protein content, quantifying the abundance of proteins across growth conditions with unprecedented resolution. However, we still lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we seek to quantitatively understand this relationship across a collection of Escherichia coli proteomic data covering ≈ 4000 proteins and 36 growth rates. We estimate the basic requirements for steady-state growth by considering key processes in nutrient transport, cell envelope biogenesis, energy generation, and the central dogma. From these estimates, ribosome biogenesis emerges as a primary determinant of growth rate. We expand on this assessment by exploring a model of proteomic regulation as a function of the nutrient supply, revealing a mechanism that ties cell size and growth rate to ribosomal content

Fundamental limits on the rate of bacterial growth

Recent years have seen an experimental deluge interrogating the relationship between bacterial growth rate, cell size, and protein content, quantifying the abundance of proteins across growth conditions with unprecedented resolution. However, we still lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we seek to quantitatively understand this relationship across a collection of Escherichia coli proteomic data covering ≈ 4000 proteins and 36 growth rates. We estimate the basic requirements for steady-state growth by considering key processes in nutrient transport, cell envelope biogenesis, energy generation, and the central dogma. From these estimates, ribosome biogenesis emerges as a primary determinant of growth rate. We expand on this assessment by exploring a model of proteomic regulation as a function of the nutrient supply, revealing a mechanism that ties cell size and growth rate to ribosomal content