Microbial pathogens represent an increasing threat to human health. Although many infections can be successfully treated and cleared, drug resistance is a widespread problem. The existence of subpopulations of 'tolerant' cells (where a fraction of the population is able to grow above the population resistance level) may increase the rate of treatment failure; yet, existing methods to measure subpopulation effects are cumbersome. Here we describe diskImageR, a computational pipeline that analyses photographs of disk diffusion assays to determine the degree of drug susceptibility [the radius of inhibition, (RAD)], and two aspects of subpopulation growth [the fraction of growth (FoG) within the zone of inhibition, (ZOI), and the rate of change in growth from no drug to inhibitory drug concentrations, (SLOPE)]. diskImageR was used to examine the response of the human fungal pathogen Candida albicans to the antifungal drug fluconazole across different strain backgrounds and growth conditions. Disk diffusion assays performed under Clinical and Laboratory Standards Institute (CLSI) conditions led to more susceptibility and less tolerance than assays performed using rich medium conditions. We also used diskImageR to quantify the effects of three drugs in combination with fluconazole, finding that all three combinations affected tolerance, with the effect of one drug (doxycycline) being very strain dependent. The three drugs had different effects on susceptibility, with doxycycline generally having no effect, chloroquine generally increasing susceptibility and pyrvinium pamoate generally reducing susceptibility. The ability to simultaneously quantitate different aspects of microbial drug responses will facilitate the study of mechanisms of subpopulation responses in the presence of antimicrobial drugs.

The immune system is essential to body defense and maintenance. Specific antibodies to foreign invaders function in body defense, and it has been suggested that autoantibodies binding to self molecules are important in body maintenance. Recently, the autoantibody repertoires in the bloods of healthy mothers and their newborns were studied using an antigen microarray containing hundreds of self molecules. It was found that the mothers expressed diverse repertoires for both IgG and IgM autoantibodies. Each newborn shares with its mother a similar repertoire of IgG antibodies, which cross the placental but its IgM repertoire is more similar to those of other newborns. Here, we took a system-level approach and analyzed the correlations between autoantibody reactivities of the previous data and extended the study to new data from newborns at birth and a week later, and from healthy young women. For the young women, we found modular organization of both IgG and IgM isotypes into antigen cliquessubgroups of highly correlated antigen reactivities. In contrast, the newborns were found to share a universal congenital IgM profile with no modular organization. Moreover, the IgG autoantibodies of the newborns manifested buds of the mothers' antigen cliques, but they were noticeably less structured. These findings suggest that the natural autoantibody repertoire of humans shows relatively little organization at birth, but, by young adulthood, it becomes sorted out into a modular organization of subgroups (cliques) of correlated antigens. These features revealed by antigen microarrays can be used to define personal states of autoantibody organizational motifs.immune development ͉ immune holography ͉ immune network ͉ network cliques

Many eukaryotic cells are able to crawl on surfaces and guide their motility based on environmental cues. These cues are interpreted by signaling systems which couple to cell mechanics; indeed membrane protrusions in crawling cells are often accompanied by activated membrane patches, which are localized areas of increased concentration of one or more signaling components. To determine how these patches are related to cell motion, we examine the spatial localization of RasGTP in chemotaxing Dictyostelium discoideum cells under conditions where the vertical extent of the cell was restricted. Quantitative analyses of the data reveal a high degree of spatial correlation between patches of activated Ras and membrane protrusions. Based on these findings, we formulate a model for amoeboid cell motion that consists of two coupled modules. The first module utilizes a recently developed two-component reaction diffusion model that generates transient and localized areas of elevated concentration of one of the components along the membrane. The activated patches determine the location of membrane protrusions (and overall cell motion) that are computed in the second module, which also takes into account the cortical tension and the availability of protrusion resources. We show that our model is able to produce realistic amoeboid-like motion and that our numerical results are consistent with experimentally observed pseudopod dynamics. Specifically, we show that the commonly observed splitting of pseudopods can result directly from the dynamics of the signaling patches.