Optimal traffic organisation in ants under crowded conditions

Efficient transportation, a hot topic in nonlinear science, is essential for modern societies and the survival of biological species. Biological evolution has generated a rich variety of successful solutions, which have inspired engineers to design optimized artificial systems. Foraging ants, for example, form attractive trails that support the exploitation of initially unknown food sources in almost the minimum possible time. However, can this strategy cope with bottleneck situations, when interactions cause delays that reduce the overall flow? Here, we present an experimental study of ants confronted with two alternative routes. We find that pheromone-based attraction generates one trail at low densities, whereas at a high level of crowding, another trail is established before traffic volume is affected, which guarantees that an optimal rate of food return is maintained. This bifurcation phenomenon is explained by a nonlinear modelling approach. Surprisingly, the underlying mechanism is based on inhibitory interactions. It implies capacity reserves, a limitation of the density-induced speed reduction, and a sufficient pheromone concentration for reliable trail perception. The balancing mechanism between cohesive and dispersive forces appears to be generic in natural, urban and transportation systems.Comment: For related work see http://www.helbing.or

The Populus holobiont: dissecting the effects of plant niches and genotype on the microbiome

Background: Microorganisms serve important functions within numerous eukaryotic host organisms. An understanding of the variation in the plant niche-level microbiome, from rhizosphere soils to plant canopies, is imperative to gain a better understanding of how both the structural and functional processes of microbiomes impact the health of the overall plant holobiome. Using Populus trees as a model ecosystem, we characterized the archaeal/bacterial and fungal microbiome across 30 different tissue-level niches within replicated Populus deltoides and hybrid Populus trichocarpa × deltoides individuals using 16S and ITS2 rRNA gene analyses. Results: Our analyses indicate that archaeal/bacterial and fungal microbiomes varied primarily across broader plant habitat classes (leaves, stems, roots, soils) regardless of plant genotype, except for fungal communities within leaf niches, which were greatly impacted by the host genotype. Differences between tree genotypes are evident in the elevated presence of two potential fungal pathogens, Marssonina brunnea and Septoria sp., on hybrid P. trichocarpa × deltoides trees which may in turn be contributing to divergence in overall microbiome composition. Archaeal/bacterial diversity increased from leaves, to stem, to root, and to soil habitats, whereas fungal diversity was the greatest in stems and soils. Conclusions: This study provides a holistic understanding of microbiome structure within a bioenergy relevant plant host, one of the most complete niche-level analyses of any plant. As such, it constitutes a detailed atlas or map for further hypothesis testing on the significance of individual microbial taxa within specific niches and habitats of Populus and a baseline for comparisons to other plant species

Immunoproteasome dysfunction augments alternative polarization of alveolar macrophages.

The proteasome is a central regulatory hub for intracellular signaling by degrading numerous signaling mediators. Immunoproteasomes are specialized types of proteasomes involved in shaping adaptive immune responses, but their role in innate immune signaling is still elusive. Here, we analyzed immunoproteasome function for polarization of alveolar macrophages, highly specialized tissue macrophages of the alveolar lung surface. Classical activation (M1 polarization) of primary alveolar macrophages by LPS/IFNγ transcriptionally induced all three immunoproteasome subunits, low molecular mass protein 2 (LMP2), LMP7 and multicatalytic endopeptidase complex-like 1, which was accompanied by increased immunoproteasome activity in M1 cells. Deficiency of LMP7 had no effect on the LPS/IFNγ-triggered M1 profile indicating that immunoproteasome function is dispensable for classical alveolar macrophage activation. In contrast, IL-4 triggered alternative (M2) activation of primary alveolar macrophages was accompanied by a transcriptionally independent amplified expression of LMP2 and LMP7 and an increase in immunoproteasome activity. Alveolar macrophages from LMP7 knockout mice disclosed a distorted M2 profile upon IL-4 stimulation as characterized by increased M2 marker gene expression and CCL17 cytokine release. Comparative transcriptome analysis revealed enrichment of IL-4-responsive genes and of genes involved in cellular response to defense, wounding and inflammation in LMP7-deficient alveolar macrophages indicating a distinct M2 inflammation resolving phenotype. Moreover, augmented M2 polarization was accompanied by amplified AKT/STAT6 activation and increased RNA and protein expression of the M2 master transcription factor interferon regulatory factor 4 in LMP7(-/-) alveolar macrophages. IL-13 stimulation of LMP7-deficient macrophages induced a similar M2-skewed profile indicative for augmented signaling via the IL-4 receptor α (IL4Rα). IL4Rα expression was generally elevated only on protein but not RNA level in LMP7(-/-) alveolar macrophages. Importantly, specific catalytic inhibition with an LMP7-specific proteasome inhibitor confirmed augmented IL-4-mediated M2 polarization of alveolar macrophages. Our results thus suggest a novel role of immunoproteasome function for regulating alternative activation of macrophages by limiting IL4Rα expression and signaling

Collective behavior in animal groups: theoretical models and empirical studies

Collective phenomena in animal groups have attracted much attention in the last years, becoming one of the hottest topics in ethology. There are various reasons for this. On the one hand, animal grouping provides a paradigmatic example of self-organization, where collective behavior emerges in absence of centralized control. The mechanism of group formation, where local rules for the individuals lead to a coherent global state, is very general and transcends the detailed nature of its components. In this respect, collective animal behavior is a subject of great interdisciplinary interest. On the other hand, there are several important issues related to the biological function of grouping and its evolutionary success. Research in this field boasts a number of theoretical models, but much less empirical results to compare with. For this reason, even if the general mechanisms through which self-organization is achieved are qualitatively well understood, a quantitative test of the models assumptions is still lacking. New analysis on large groups, which require sophisticated technological procedures, can provide the necessary empirical data