Dataset Information

Fungal and bacterial communities in time

ABSTRACT: Time after time: Temporal variation in the effects of plant species and plant functional groups on soil bacterial and fungal communities

PROVIDER: PRJEB33273 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	ERR3406790_1.fastq.gz	Fastqsanger.gz
	ERR3406790_2.fastq.gz	Fastqsanger.gz
	ERR3406800_1.fastq.gz	Fastqsanger.gz
	ERR3406800_2.fastq.gz	Fastqsanger.gz
	ERR3406810_1.fastq.gz	Fastqsanger.gz

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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:Microbial keratitis is a major cause of blindness worldwide. An excessive host inflammatory response can occur even after adequate antimicrobial treatment. This results in tissue damage with corneal thinning and even perforation, which may require corneal transplantation. In this study we investigated the pathways involved in the pathophysiology of this disease by comparing the human transcriptome profile of tissue from culture-proven bacterial and fungal keratitis (n=7 and n=8 respectively) with normal non-infected cadaveric corneal tissue (C, n=12) using Illumina HT12 v4 microarrays. The causative organisms were Streptococcus pneumoniae (n=6) and Pseudomonas aeruginosa (n=1) for bacterial keratitis (BK). Fungal keratitis (FK) was caused by Fusarium sp. (n=5), Aspergillus sp. (n=2, A. flavus and terreus) and Lasiodiplodia sp. (n=1). Differential expression (DE) analysis revealed 2310 significantly altered probes in the BK v C comparison, and 1813 probes for FK v C. The most highly upregulated gene in both comparisons was MMP9 with fold changes (FC) of 64 (fdr-adjusted p<6 x10-11) for FK v C and 89 for BK v C (fdr-adjusted p<4 x10-11) respectively. Network co-expression analyses revealed the defense response, inflammatory response and extracellular matrix mechanisms to be the main functional pathways involved. Microarray results were validated by performing real-time quantitative PCR (RTqPCR) for 46 DE genes using RNA extracted from the same samples. There was a high correlation between log2 FC values from microarray and RTqPCR. Further studies are needed to evaluate the most highly differentially expressed genes as possible biomarkers of disease progression or therapeutic targets. Case - control study design. Corneal ulcer tissue from 8 bacterial and 9 fungal ulcers was excised at the time of corneal transplantation surgery and immediately preserved in RNALater. Non-infected corneal tissue from 13 cadaver corneas were the control tissue. Transcriptome profile generated using Illumina HT12 v4 beadchips. Differential expression analysis was performed with pairwise comparisons: bacterial ulcers versus controls, fungal ulcers versus controls and bacterial versus fungal ulcers. Microarray results validated with RTqPCR.

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Fungal and bacterial communities in time

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