Unraveling spatiotemporal variability of arbuscular mycorrhizal fungi in a temperate grassland plot

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldmann, K., Boeddinghaus, R. S., Klemmer, S., Regan, K. M., Heintz-Buschart, A., Fischer, M., Prati, D., Piepho, H., Berner, D., Marhan, S., Kandeler, E., Buscot, F., & Wubet, T. Unraveling spatiotemporal variability of arbuscular mycorrhizal fungi in a temperate grassland plot. Environmental Microbiology, 22(3),(2020): 873-888, doi:10.1111/1462-2920.14653.Soils provide a heterogeneous environment varying in space and time; consequently, the biodiversity of soil microorganisms also differs spatially and temporally. For soil microbes tightly associated with plant roots, such as arbuscular mycorrhizal fungi (AMF), the diversity of plant partners and seasonal variability in trophic exchanges between the symbionts introduce additional heterogeneity. To clarify the impact of such heterogeneity, we investigated spatiotemporal variation in AMF diversity on a plot scale (10 × 10 m) in a grassland managed at low intensity in southwest Germany. AMF diversity was determined using 18S rDNA pyrosequencing analysis of 360 soil samples taken at six time points within a year. We observed high AMF alpha‐ and beta‐diversity across the plot and at all investigated time points. Relationships were detected between spatiotemporal variation in AMF OTU richness and plant species richness, root biomass, minimal changes in soil texture and pH. The plot was characterized by high AMF turnover rates with a positive spatiotemporal relationship for AMF beta‐diversity. However, environmental variables explained only ≈20% of the variation in AMF communities. This indicates that the observed spatiotemporal richness and community variability of AMF was largely independent of the abiotic environment, but related to plant properties and the cooccurring microbiome.We thank the managers of the three Exploratories, Kirsten Reichel‐Jung, Swen Renner, Katrin Hartwich, Sonja Gockel, Kerstin Wiesner, and Martin Gorke for their work in maintaining the plot and project infrastructure; Christiane Fischer and Simone Pfeiffer for giving support through the central office, Michael Owonibi and Andreas Ostrowski for managing the central data base, and Eduard Linsenmair, Dominik Hessenmöller, Jens Nieschulze, Ernst‐Detlef Schulze, Wolfgang W. Weisser and the late Elisabeth Kalko for their role in setting up the Biodiversity Exploratories project. The work has been funded by the DFG Priority Program 1374 ‘Infrastructure‐Biodiversity‐Exploratories’ (BU 941/22‐1, BU 941/22‐3, KA 1590/8‐2, KA 1590/8‐3). Field work permits were issued by the responsible state environmental office of Baden‐Württemberg (according to § 72 BbgNatSchG). Likewise, we kindly thank Beatrix Schnabel, Melanie Günther and Sigrid Härtling for 454 sequencing in Halle. AHB gratefully acknowledges the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig funded by the German Research Foundation (FZT 118). Authors declare no conflict of interests

Small RNA profiling of low biomass samples: identification and removal of contaminants

Background Sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. DNA contamination has been previously reported, yet contamination with RNA is usually considered to be very unlikely due to its inherent instability. Small RNAs (sRNAs) identified in tissues and bodily fluids, such as blood plasma, have implications for physiology and pathology, and therefore the potential to act as disease biomarkers. Thus, the possibility for RNA contaminants demands careful evaluation. Results Herein, we report on the presence of small RNA (sRNA) contaminants in widely used microRNA extraction kits and propose an approach for their depletion. We sequenced sRNAs extracted from human plasma samples and detected important levels of non-human (exogenous) sequences whose source could be traced to the microRNA extraction columns through a careful qPCR-based analysis of several laboratory reagents. Furthermore, we also detected the presence of artefactual sequences related to these contaminants in a range of published datasets, thereby arguing in particular for a re-evaluation of reports suggesting the presence of exogenous RNAs of microbial and dietary origin in blood plasma. To avoid artefacts in future experiments, we also devise several protocols for the removal of contaminant RNAs, define minimal amounts of starting material for artefact-free analyses, and confirm the reduction of contaminant levels for identification of bona fide sequences using ‘ultra-clean’ extraction kits. Conclusion This is the first report on the presence of RNA molecules as contaminants in RNA extraction kits. The described protocols should be applied in the future to avoid confounding sRNA studies. Keywords: RNA sequencing; Artefact removal; Exogenous RNA in human blood plasma; Contaminant RNA; Spin column

The archives are half-empty : an assessment of the availability of microbial community sequencing data

As DNA sequencing has become more popular, the public genetic repositories where sequences are archived have experienced explosive growth. These repositories now hold invaluable collections of sequences, e.g., for microbial ecology, but whether these data are reusable has not been evaluated. We assessed the availability and state of 16S rRNA gene amplicon sequences archived in public genetic repositories (SRA, EBI, and DDJ). We screened 26,927 publications in 17 microbiology journals, identifying 2015 16S rRNA gene sequencing studies. Of these, 7.2% had not made their data public at the time of analysis. Among a subset of 635 studies sequencing the same gene region, 40.3% contained data which was not available or not reusable, and an additional 25.5% contained faults in data formatting or data labeling, creating obstacles for data reuse. Our study reveals gaps in data availability, identifies major contributors to data loss, and offers suggestions for improving data archiving practices

Sample preservation and storage significantly impact taxonomic and functional profiles in metaproteomics studies of the human gut microbiome

With the technological advances of the last decade, it is now feasible to analyze microbiome samples, such as human stool specimens, using multi-omic techniques. Given the inherent sample complexity, there exists a need for sample methods which preserve as much information as possible about the biological system at the time of sampling. Here, we analyzed human stool samples preserved and stored using different methods, applying metagenomics as well as metaproteomics. Our results demonstrate that sample preservation and storage have a significant effect on the taxonomic composition of identified proteins. The overall identification rates, as well as the proportion of proteins from were much higher when samples were flash frozen. Preservation in RNAlater overall led to fewer protein identifications and a considerable increase in the share of , as well as . Additionally, a decrease in the share of metabolism-related proteins and an increase of the relative amount of proteins involved in the processing of genetic information was observed for RNAlater-stored samples. This suggests that great care should be taken in choosing methods for the preservation and storage of microbiome samples, as well as in comparing the results of analyses using different sampling and storage methods. Flash freezing and subsequent storage at -80 °C should be chosen wherever possible