diskImageR: quantification of resistance and tolerance to antimicrobial drugs using disk diffusion assays.

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 motility-proliferation-metabolism interplay during metastatic invasion.

Metastasis is the major cause for cancer patients' death, and despite all the recent advances in cancer research it is still mostly incurable. Understanding the mechanisms that are involved in the migration of the cells in a complex environment is a key step towards successful anti-metastatic treatment. Using experimental data-based modeling, we focus on the fundamentals of metastatic invasion: motility, invasion, proliferation and metabolism, and study how they may be combined to maximize the cancer's ability to metastasize. The modeled cells' performance is measured by the number of cells that succeed in migration in a maze, which mimics the extracellular environment. We show that co-existence of different cell clones in the tumor, as often found in experiments, optimizes the invasive ability in a frequently-changing environment. We study the role of metabolism and stimulation by growth factors, and show that metabolism plays a crucial role in the metastatic process and should therefore be targeted for successful treatment.

Tumor invasion optimization by mesenchymal-amoeboid heterogeneity.

Metastasizing tumor cells migrate through the surrounding tissue and extracellular matrix toward the blood vessels, in order to colonize distant organs. They typically move in a dense environment, filled with other cells. In this work we study cooperative effects between neighboring cells of different types, migrating in a maze-like environment with directional cue. Using a computerized model, we measure the percentage of cells that arrive to the defined target, for different mesenchymal/amoeboid ratios. Wall degradation of mesenchymal cells, as well as motility of both types of cells, are coupled to metabolic energy-like resource level. We find that indirect cooperation emerges in mid-level energy, as mesenchymal cells create paths that are used by amoeboids. Therefore, we expect to see a small population of mesenchymals kept in a mostly-amoeboid population. We also study different forms of direct interaction between the cells, and show that energy-dependent interaction strength is optimal for the migration of both mesenchymals and amoeboids. The obtained characteristics of cellular cluster size are in agreement with experimental results. We therefore predict that hybrid states, e.g. epithelial-mesenchymal, should be utilized as a stress-response mechanism.

Propagating waves of directionality and coordination orchestrate collective cell migration.

The ability of cells to coordinately migrate in groups is crucial to enable them to travel long distances during embryonic development, wound healing and tumorigenesis, but the fundamental mechanisms underlying intercellular coordination during collective cell migration remain elusive despite considerable research efforts. A novel analytical framework is introduced here to explicitly detect and quantify cell clusters that move coordinately in a monolayer. The analysis combines and associates vast amount of spatiotemporal data across multiple experiments into transparent quantitative measures to report the emergence of new modes of organized behavior during collective migration of tumor and epithelial cells in wound healing assays. First, we discovered the emergence of a wave of coordinated migration propagating backward from the wound front, which reflects formation of clusters of coordinately migrating cells that are generated further away from the wound edge and disintegrate close to the advancing front. This wave emerges in both normal and tumor cells, and is amplified by Met activation with hepatocyte growth factor/scatter factor. Second, Met activation was found to induce coinciding waves of cellular acceleration and stretching, which in turn trigger the emergence of a backward propagating wave of directional migration with about an hour phase lag. Assessments of the relations between the waves revealed that amplified coordinated migration is associated with the emergence of directional migration. Taken together, our data and simplified modeling-based assessments suggest that increased velocity leads to enhanced coordination: higher motility arises due to acceleration and stretching that seems to increase directionality by temporarily diminishing the velocity components orthogonal to the direction defined by the monolayer geometry. Spatial and temporal accumulation of directionality thus defines coordination. The findings offer new insight and suggest a basic cellular mechanism for long-term cell guidance and intercellular communication during collective cell migration.

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

"Self-assisted" amoeboid navigation in complex environments.

BACKGROUND: Living cells of many types need to move in response to external stimuli in order to accomplish their functional tasks; these tasks range from wound healing to immune response to fertilization. While the directional motion is typically dictated by an external signal, the actual motility is also restricted by physical constraints, such as the presence of other cells and the extracellular matrix. The ability to successfully navigate in the presence of obstacles is not only essential for organisms, but might prove relevant in the study of autonomous robotic motion. METHODOLOGY/PRINCIPAL FINDINGS: We study a computational model of amoeboid chemotactic navigation under differing conditions, from motion in an obstacle-free environment to navigation between obstacles and finally to moving in a maze. We use the maze as a simple stand-in for a motion task with severe constraints, as might be expected in dense extracellular matrix. Whereas agents using simple chemotaxis can successfully navigate around small obstacles, the presence of large barriers can often lead to agent trapping. We further show that employing a simple memory mechanism, namely secretion of a repulsive chemical by the agent, helps the agent escape from such trapping. CONCLUSIONS/SIGNIFICANCE: Our main conclusion is that cells employing simple chemotactic strategies will often be unable to navigate through maze-like geometries, but a simple chemical marker mechanism (which we refer to as "self-assistance") significantly improves success rates. This realization provides important insights into mechanisms that might be employed by real cells migrating in complex environments as well as clues for the design of robotic navigation strategies. The results can be extended to more complicated multi-cellular systems and can be used in the study of mammalian cell migration and cancer metastasis.

Activated membrane patches guide chemotactic cell motility.

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.

Transient localized patterns in noise-driven reaction-diffusion systems.

Noise can induce excitable systems to make time-limited transitions between quiescent and active states. Here we investigate the possibility that these transitions occur locally in a spatially extended medium, leading to the occurrence of spatiotemporal patches of activation. We show that this can in fact occur in a parameter range such that there exist (in general unstable) localized solutions of the governing deterministic reaction-diffusion equations. Our work is motivated by a recent biological example showing transiently excited cell membrane regions.

Organization of the autoantibody repertoire in healthy newborns and adults revealed by system level informatics of antigen microarray data.

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 cliques-subgroups 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.

Determining the scale of the Bicoid morphogen gradient.

Bicoid is a morphogen that sets up the anterior-posterior axis in early Drosophila embryos. Although the form of the Bicoid profile is consistent with a simple diffusion/degradation model, the observed length scale is much larger than should be expected based on the measured diffusion rate. Here, we study two possible mechanisms that could, in principle, affect this gradient and, hence, address this disagreement. First, we show that including trapping and release of Bicoid by the nuclei during cleavage cycles does not alter the morphogen length scale. More crucially, the inclusion of advective transport due to cytoplasmic streaming can have a large effect. Specifically, we build a simple model based on the (limited) experimental data and show that such a flow can lead to a Bicoid profile that is consistent with various experimental features. Specifically, the observed length scale is obtained, a steady profile is established, and improved scaling between embryos of different lengths is demonstrated.

Correlated phenotypic transitions to competence in bacterial colonies.

Genetic competence is a phenotypic state of a bacterial cell in which it is capable of importing DNA, presumably to improve survival under stress. Motivated by several colony-level known responses, we present a model for the influence of quorum sensing on the transition to competence of B. Subtilis. Coupling to the external signal creates an effective inhibitory mechanism, which results in anticorrelation between the cycles of adjacent cells. We show that this is consistent with recent experimental measurements and propose measurement methods to verify the role of quorum-sensing signals.

Perturbation analysis for competing reactions with initially separated components.

We study a competitive reaction-diffusion system with initially separated components. In this system, two similar species on one side of the system compete to react with the species on the other side. The competition is due to significant differences in the microscopic reaction constants and the initial densities of the two competing species. In the short-time limit, each of the competitive reactions is considered as perturbation with respect to the diffusion, the latter is essential for the effective mixing of the reactants. We identify the small parameters required for the perturbation analysis of the competitive scheme. The resulting perturbative expressions provide the rich spatiotemporal reaction front patterns, which were experimentally observed for Cr3+ + Xylenol Orange (XO) --> products, where the aggregated and nonaggregated forms of Cr3+ in aqueous solution compete to react with the XO.

Reaction-diffusion front width anomalies in disordered media.

We study the front characteristics of the A + B --> C reaction-diffusion system with initially separated reactants in disordered media, exemplified by two-dimensional (2D) percolation. We investigate the front characteristics as a function of the disorder degree in this system, in particular close to criticality. We show that the front width exponent is larger than the mean-field (MF) exponent of 1/6, and at criticality it approaches 1/4, which is the one-dimensional (1D) exponent. We show that previous predictions in the literature for the 2D percolation cluster at criticality are wrong. The results are discussed in the context of other systems with attenuated transport where the front width exponent is smaller than the MF exponent. We also study the short-time behavior of the front width exponent, and discuss the validity of the scaling relations between the relevant exponents.

Interface roughening dynamics: temporal width fluctuations and the correlation length.

In this work we study experimentally and numerically the temporal width fluctuations obtained in kinetic roughening of single interfaces. This fluctuative behavior, which results from competing mechanisms in the interface growth process, is shown to contain information on the growth process of the specific interface. We define a measure of the temporal interface width fluctuations in order to extract the correlation length of the interface from the fluctuating data. We study numerically the quenched Kardar-Parisi-Zhang (QKPZ) equation for single interfaces in order to assess the role of the different mechanisms, such as normal growth and surface tension, on the fluctuations. We analyze experimental data of mercury droplets spreading on various metal films (silver and gold) in various thicknesses, as well as data of water spreading on paper (imbibition), in order to demonstrate the validity of our method in a wide range of growing interfaces.

Roughness and growth in a continuous fluid invasion model.

We have studied interface characteristics in a continuous fluid invasion model, first introduced by Phys. Rev. Lett. 60, 2042 (1988)]. In this model, the interface grows as a response to an applied quasistatic pressure, which induces various types of instabilities. We suggest a variant of the model, which differs from the original model by the order of instabilities treatment. This order represents the relative importance of the physical mechanisms involved in the system. This variant predicts the existence of a third, intermediate regime, in the behavior of the roughness exponent as a function of the wetting properties of the system. The gradual increase of the roughness exponent in this third regime can explain the scattered experimental data for the roughness exponent in the literature. The growth exponent in this model was found to be around zero, due to the initial rough interface.