Project description:The rate, timing, and mode of species dispersal is recognized as a key driver of the structure and function of communities of macroorganisms, and may be one ecological process that determines the diversity of microbiomes. Many previous studies have quantified the modes and mechanisms of bacterial motility using monocultures of a few model bacterial species. But most microbes live in multispecies microbial communities, where direct interactions between microbes may inhibit or facilitate dispersal through a number of physical (e.g., hydrodynamic) and biological (e.g., chemotaxis) mechanisms, which remain largely unexplored. Using cheese rinds as a model microbiome, we demonstrate that physical networks created by filamentous fungi can impact the extent of small-scale bacterial dispersal and can shape the composition of microbiomes. From the cheese rind of Saint Nectaire, we serendipitously observed the bacterium Serratia proteamaculans actively spreads on networks formed by the fungus Mucor. By experimentally recreating these pairwise interactions in the lab, we show that Serratia spreads on actively growing and previously established fungal networks. The extent of symbiotic dispersal is dependent on the fungal network: diffuse and fast-growing Mucor networks provide the greatest dispersal facilitation of the Serratia species, while dense and slow-growing Penicillium networks provide limited dispersal facilitation. Fungal-mediated dispersal occurs in closely related Serratia species isolated from other environments, suggesting that this bacterial-fungal interaction is widespread in nature. Both RNA-seq and transposon mutagenesis point to specific molecular mechanisms that play key roles in this bacterial-fungal interaction, including chitin utilization and flagellin biosynthesis. By manipulating the presence and type of fungal networks in multispecies communities, we provide the first evidence that fungal networks shape the composition of bacterial communities, with Mucor networks shifting experimental bacterial communities to complete dominance by motile Proteobacteria. Collectively, our work demonstrates that these strong biophysical interactions between bacterial and fungi can have community-level consequences and may be operating in many other microbiomes.

Project description:A functional biodiversity microarray (EcoChip) prototype has been developed to facilitate the analysis of fungal communities in environmental samples with broad functional and phylogenetic coverage and to enable the incorporation of nucleic acid sequence data as they become available from large-scale (next generation) sequencing projects. A dual probe set (DPS) was designed to detect a) functional enzyme transcripts at conserved protein sites and b) phylogenetic barcoding transcripts at ITS regions present in precursor rRNA. Deviating from the concept of GeoChip-type microarrays, the presented EcoChip microarray phylogenetic information was obtained using a dedicated set of barcoding microarray probes, whereas functional gene expression was analyzed by conserved domain-specific probes. By unlinking these two target groups, the shortage of broad sequence information of functional enzyme-coding genes in environmental communities became less important. The novel EcoChip microarray could be successfully applied to identify specific degradation activities in environmental samples at considerably high phylogenetic resolution. Reproducible and unbiased microarray signals could be obtained with chemically labeled total RNA preparations, thus avoiding the use of enzymatic labeling steps. ITS precursor rRNA was detected for the first time in a microarray experiment, which confirms the applicability of the EcoChip concept to selectively quantify the transcriptionally active part of fungal communities at high phylogenetic resolution. In addition, the chosen microarray platform facilitates the conducting of experiments with high sample throughput in almost any molecular biology laboratory. In this study, two independent RNA samples from a pine forest soil were labelled and hybridised to a custom-made EcoChip microarray consisting of about 9000 probes targeting expressed fungals genes and about 5000 probes targeting the precursor-rRNA of different fungal lineages

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