Biofilm infections can consist of bacterial aggregates that are an order of magnitude larger than neutrophils, phagocytic immune cells that densely surround aggregates but do not enter them. Because a neutrophil is too small to engulf the entire aggregate, it must be able to detach and engulf a few bacteria at a time if it is to use phagocytosis to clear the infection. Current research techniques do not provide a method for determining how the success of phagocytosis, here defined as the complete engulfment of a piece of foreign material, depends on the mechanical properties of a larger object from which the piece must be removed before being engulfed. This article presents a step toward such a method. By varying polymer concentration or cross-linking density, the elastic moduli of centimeter-sized gels are varied over the range that was previously measured for Pseudomonas aeruginosa biofilms grown from clinical bacterial isolates. Human neutrophils are isolated from blood freshly drawn from healthy adult volunteers, exposed to gel containing embedded beads for 1 h, and removed from the gel. The percentage of collected neutrophils that contain beads that had previously been within the gels is used to measure successful phagocytic engulfment. Both increased polymer concentration in agarose gels and increased cross-linking density in alginate gels are associated with a decreased success of phagocytic engulfment. Upon plotting the percentage of neutrophils showing successful engulfment as a function of the elastic modulus of the gel to which they were applied, it is found that data from both alginate and agarose gels collapse onto the same curve. This suggests that gel mechanics may be impacting the success of phagocytosis and demonstrates that this experiment is a step toward realizing methods for measuring how the mechanics of a large target, or a large structure in which smaller targets are embedded, impact the success of phagocytic engulfment.

Phagocytic immune cells can clear pathogens from the body by engulfing them. Bacterial biofilms are communities of bacteria that are bound together in a matrix that gives biofilms viscoelastic mechanical properties that do not exist for free-swimming bacteria. Since a neutrophil is too small to engulf an entire biofilm, it must be able to detach and engulf a few bacteria at a time if it is to use phagocytosis to clear the infection. We recently found a negative correlation between the target elasticity and phagocytic success. That earlier work used time-consuming, manual analysis of micrographs of neutrophils and fluorescent beads. Here, we introduce and validate flow cytometry as a fast and high-throughput technique that increases the number of neutrophils analyzed per experiment by two orders of magnitude, while also reducing the time required to do so from hours to minutes. We also introduce the use of polyacrylamide gels in our assay for engulfment success. The tunability of polyacrylamide gels expands the mechanical parameter space we can study, and we find that high toughness and yield strain, even with low elasticity, also impact the phagocytic success as well as the timescale thereof. For stiff gels with low-yield strain, and consequent low toughness, phagocytic success is nearly four times greater when neutrophils are incubated with gels for 6 h than after only 1 h of incubation. In contrast, for soft gels with high-yield strain and consequent high toughness, successful engulfment is much less time-sensitive, increasing by less than a factor of two from 1 to 6 h incubation.

Many animals can orient using the earth’s magnetic field. In a recent study, we performed three distinct behavioral assays providing evidence that the nematode Caenorhabditis elegans orients to earth-strength magnetic fields (Vidal-Gadea et al., 2015). A new study by Landler et al. suggests that C. elegans does not orient to magnetic fields (Landler et al., 2018). They also raise conceptual issues that cast doubt on our study. Here, we explain how they appear to have missed positive results in part by omitting controls and running assays longer than prescribed, so that worms switched their preferred migratory direction within single tests. We also highlight differences in experimental methods and interpretations that may explain our different results and conclusions. Together, these findings provide guidance on how to achieve robust magnetotaxis and reinforce our original finding that C. elegans is a suitable model system to study magnetoreception.

Biofilms are communities of sessile microbes that are bound to each other by a matrix made of biopolymers and proteins. Spatial structure is present in biofilms on many lengthscales. These range from the nanometer scale of molecular motifs to the hundred-micron scale of multicellular aggregates. Spatial structure is a physical property that impacts the biology of biofilms in many ways. The molecular structure of matrix components controls their interaction with each other (thereby impacting biofilm mechanics) and with diffusing molecules such as antibiotics and immune factors (thereby impacting antibiotic tolerance and evasion of the immune system). The size and structure of multicellular aggregates, combined with microbial consumption of growth substrate, give rise to differentiated microenvironments with different patterns of metabolism and gene expression. Spatial association of more than one species can benefit one or both species, while distances between species can both determine and result from the transport of diffusible factors between species. Thus, a widespread theme in the biological importance of spatial structure in biofilms is the effect of structure on transport. We survey what is known about this and other effects of spatial structure in biofilms, from molecules up to multispecies ecosystems. We conclude with an overview of what experimental approaches have been developed to control spatial structure in biofilms and how these and other experiments can be complemented with computational work.

We present a new strategy for analyzing imaging time-of-flight SIMS data sets affected by detector saturation. Rather than attempt to correct the measured data to remove saturation, we incorporate the detector behavior into the statistical basis of the analysis. This is performed within the framework of maximum a posteriori reconstruction. The proposed approach has several advantages over previous techniques. No approximations are involved other than the assumed model of the detector. The method performs well even when applied to highly saturated and/or single-scan data sets. It is statistically rigorous, correctly treating the underlying statistical distribution of the data. It is also compatible with Bayesian methods for incorporating prior knowledge about sample properties. An efficient iterative scheme for solving the proposed equations is presented for the case of the bilinear model commonly used in analyses of SIMS data. The correctness of the approach and its efficacy are demonstrated on synthetic data sets. The method is found to perform better than a widely-used data-correction method used in combination with alternating-least-squares Multivariate Curve Resolution analysis.