Metabolic cross-feeding interactions are ubiquitous in natural microbial communities. However, it remains generally unclear whether the production and exchange of metabolites incurs fitness costs to the producing cells and if so, which ecological mechanisms can facilitate a cooperative exchange of metabolites among unrelated individuals. We hypothesized that positive assortment within structured environments can maintain mutualistic cross-feeding. To test this, we engineered Acinetobacter baylyi and Escherichia coli to reciprocally exchange essential amino acids. Interspecific coculture experiments confirmed that non-cooperating types were selectively favoured in spatially unstructured (liquid culture), yet disfavoured in spatially structured environments (agar plates). Both an individual-based model and experiments with engineered genotypes indicated that a segregation of cross-feeders and non-cooperating auxotrophs stabilized cooperative cross-feeding in spatially structured environments. Chemical imaging confirmed that auxotrophs were spatially excluded from cooperative benefits. Together, these results demonstrate that cooperative crossfeeding between different bacterial species is favoured in structured environments such as bacterial biofilms, suggesting this type of interactions might be common in natural bacterial communities.

Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this ‘protein microarray on a smartphone’-concept for on-site testing, e.g., in food safety, environment and health monitoring.

Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.

Microorganisms encounter a diversity of chemical stimuli that trigger individual responses and influence population dynamics. However, microbial behavior under the influence of different incentives and microbial decision-making is poorly understood. Benthic marine diatoms that react to sexual attractants as well as to nutrient gradients face such multiple constraints. Here, we document and model behavioral complexity and context-sensitive responses of these motile unicellular algae to sex pheromones and the nutrient silicate. Throughout the life cycle of the model diatom Seminavis robusta nutrient-starved cells localize sources of silicate by combined chemokinetic and chemotactic motility. However, with an increasing need for sex to restore the initial cell size, a change in behavior favoring the attraction-pheromone-guided search for a mating partner takes place. When sex becomes inevitable to prevent cell death, safeguard mechanisms are abandoned, and cells prioritize the search for mating partners. Such selection processes help to explain biofilm organization and to understand species interactions in complex communities.

As a part of the complement system, factor H regulates phagocytosis and helps differentiate between a body's own and foreign cells. Owing to mimicry efforts, some pathogenic microorganisms such as are able to bind factor H on their cell surfaces and, thus, become similar to host cells. This implies that the decision between self and foreign is not clear-cut, which leads to a classification problem for the immune system. Here, two different alleles determining the binding affinity of factor H are relevant. Those alleles differ in the SNP Y402H; they are known to be associated with susceptibility to certain diseases. Interestingly, the fraction of both alleles differs in ethnic groups. The game-theoretical model proposed in this article explains the coexistence of both alleles by a game and investigates the trade-off between pathogen detection and protection of host cells. Further, we discuss the ethnicity-dependent frequencies of the alleles. Moreover, the model elucidates the mimicry efforts by pathogenic microorganisms.