Anthropogenic nitrogen enrichment enhances soil carbon accumulation by impacting saprotrophs rather than ectomycorrhizal fungal activity.

There is evidence that anthropogenic nitrogen (N) deposition enhances carbon (C) sequestration in boreal forest soils. However, it is unclear how free-living saprotrophs (bacteria and fungi, SAP) and ectomycorrhizal (EM) fungi responses to N addition impact soil C dynamics. Our aim was to investigate how SAP and EM communities are impacted by N enrichment and to estimate whether these changes influence decay of litter and humus. We conducted a long-term experiment in northern Sweden, maintained since 2004, consisting of ambient, low N additions (0, 3, 6, and 12 kg N ha-1  year-1 ) simulating current N deposition rates in the boreal region, as well as a high N addition (50 kg N ha-1  year-1 ). Our data showed that long-term N enrichment impeded mass loss of litter, but not of humus, and only in response to the highest N addition treatment. Furthermore, our data showed that EM fungi reduced the mass of N and P in both substrates during the incubation period compared to when only SAP organisms were present. Low N additions had no effect on microbial community structure, while the high N addition decreased fungal and bacterial biomasses and altered EM fungi and SAP community composition. Actinomycetes were the only bacterial SAP to show increased biomass in response to the highest N addition. These results provide a mechanistic understanding of how anthropogenic N enrichment can influence soil C accumulation rates and suggest that current N deposition rates in the boreal region (≤12 kg N ha-1  year-1 ) are likely to have a minor impact on the soil microbial community and the decomposition of humus and litter.

HCK and ABAA: A Newly Designed Pipeline to Improve Fungi Metabarcoding Analysis.

INTRODUCTION: The fungi ITS sequence length dissimilarity, non-specific amplicons, including chimaera formed during Polymerase Chain Reaction (PCR), added to sequencing errors, create bias during similarity clustering and abundance estimation in the downstream analysis. To overcome these challenges, we present a novel approach, Hierarchical Clustering with Kraken (HCK), to classify ITS1 amplicons and Abundance-Base Alternative Approach (ABAA) pipeline to detect and filter non-specific amplicons in fungi metabarcoding sequencing datasets. MATERIALS AND METHODS: We compared the performances of both pipelines against QIIME, KRAKEN, and DADA2 using publicly available fungi ITS mock community datasets and using BLASTn as a reference. We calculated the Precision, Recall, F-score using the True-Positive, False-positive, and False-negative estimation. Alpha diversity (Chao1 and Shannon metrics) was also used to evaluate the diversity estimation of our method. RESULTS: The analysis shows that ABAA reduced the number of false-positive with all metabarcoding methods tested, and HCK increases precision and recall. HCK, coupled with ABAA, improves the F-score and bring alpha diversity metric value close to that of the BLASTn alpha diversity values when compared to QIIME, KRAKEN, and DADA2. CONCLUSION: The developed HCK-ABAA approach allows better identification of the fungi community structures while avoiding use of a reference database for non-specific amplicons filtration. It results in a more robust and stable methodology over time. The software can be downloaded on the following link: https://bitbucket.org/GottySG36/hck/src/master/.

Contribution of Ultra Deep Sequencing in the Clinical Diagnosis of a New Fungal Pathogen Species: Basidiobolus meristosporus.

Some cases of fungal infection remained undiagnosed, especially when the pathogens are uncommon, require specific conditions for in vitro growth, or when several microbial species are present in the specimen. Ultra-Deep Sequencing (UDS) could be considered as a precise tool in the identification of involved pathogens in order to upgrade patient treatment. In this study, we report the implementation of UDS technology in medical laboratory during the follow-up of an atypical fungal infection case. Thanks to UDS technology, we document the first case of gastro-intestinal basidiobolomycosis (GIB) due to Basidiobolus meristosporus. The diagnosis was suspected after histopathological examination but conventional microbiological methods failed to supply proof. The final diagnosis was made by means of an original approach based on UDS. DNA was extracted from the embedded colon biopsy obtained after hemicolectomy, and a fragment encompassing the internal transcribed spacer (ITS) rDNA region was PCR-amplified. An Amplicon library was then prepared using Genome Sequencer Junior Titanium Kits (Roche/454 Life Sciences) and the library was pyrosequenced on a GS Junior (Roche/454 Life Sciences). Using this method, 2,247 sequences with more than 100 bases were generated and used for UDS analysis. B. meristosporus represented 80% of the sequences, with an average homology of 98.8%. A phylogenetic tree with Basidiobolus reference sequences confirmed the presence of B. meristosporus (bootstrap value of 99%). Conclusion : UDS-based diagnostic approaches are ready to integrate conventional diagnostic testing to improve documentation of infectious disease and the therapeutic management of patients.

Characterization of Bacterial and Fungal Community Dynamics by High-Throughput Sequencing (HTS) Metabarcoding during Flax Dew-Retting.

Flax dew-retting is a key step in the industrial extraction of fibers from flax stems and is dependent upon the production of a battery of hydrolytic enzymes produced by micro-organisms during this process. To explore the diversity and dynamics of bacterial and fungal communities involved in this process we applied a high-throughput sequencing (HTS) DNA metabarcoding approach (16S rRNA/ITS region, Illumina Miseq) on plant and soil samples obtained over a period of 7 weeks in July and August 2014. Twenty-three bacterial and six fungal phyla were identified in soil samples and 11 bacterial and four fungal phyla in plant samples. Dominant phyla were Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes (bacteria) and Ascomycota, Basidiomycota, and Zygomycota (fungi) all of which have been previously associated with flax dew-retting except for Bacteroidetes and Basidiomycota that were identified for the first time. Rare phyla also identified for the first time in this process included Acidobacteria, CKC4, Chlorobi, Fibrobacteres, Gemmatimonadetes, Nitrospirae and TM6 (bacteria), and Chytridiomycota (fungi). No differences in microbial communities and colonization dynamics were observed between early and standard flax harvests. In contrast, the common agricultural practice of swath turning affects both bacterial and fungal community membership and structure in straw samples and may contribute to a more uniform retting. Prediction of community function using PICRUSt indicated the presence of a large collection of potential bacterial enzymes capable of hydrolyzing backbones and side-chains of cell wall polysaccharides. Assignment of functional guild (functional group) using FUNGuild software highlighted a change from parasitic to saprophytic trophic modes in fungi during retting. This work provides the first exhaustive description of the microbial communities involved in flax dew-retting and will provide a valuable benchmark in future studies aiming to evaluate the effects of other parameters (e.g., year-to year and site variability etc.) on this complex process.