Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

Background The native crop bacterial microbiota of the rhizosphere is envisioned to be engineered for sustainable agriculture. This requires the identification of keystone rhizosphere Bacteria and an understanding on how these govern crop-specific microbiome assembly from soils. We identified the metabolically active bacterial microbiota (SSU RNA) inhabiting two compartments of the rhizosphere of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rye (Secale cereale), and oilseed rape (Brassica napus L.) at different growth stages. Results Based on metabarcoding analysis the bacterial microbiota was shaped by the two rhizosphere compartments, i.e. close and distant. Thereby implying a different spatial extent of bacterial microbiota acquirement by the cereals species versus oilseed rape. We derived core microbiota of each crop species. Massilia (barley and wheat) and unclassified Chloroflexi of group ‘KD4-96’ (oilseed rape) were identified as keystone Bacteria by combining LEfSe biomarker and network analyses. Subsequently, differential associations between networks of each crop species’ core microbiota revealed host plant-specific interconnections for specific genera, such as the unclassified Tepidisphaeraceae ‘WD2101 soil group’. Conclusions Our results provide keystone rhizosphere Bacteria derived from for crop hosts and revealed that cohort subnetworks and differential associations elucidated host species effect that was not evident from differential abundance of single bacterial genera enriched or unique to a specific plant host. Thus, we underline the importance of co-occurrence patterns within the rhizosphere microbiota that emerge in crop-specific microbiomes, which will be essential to modify native crop microbiomes for future agriculture and to develop effective bio-fertilizers.

Dryland xeric conditions exert a deterministic effect on microbial communities, forcing life into refuge niches. Deposited rocks can form a lithic niche for microorganisms in desert regions. Mineral weathering is a key process in soil formation and the importance of microbial-driven mineral weathering for nutrient extraction is increasingly accepted. Advances in geobiology provide insight into the interactions between microorganisms and minerals that play an important role in weathering processes. In this study, we present the examination of the microbial diversity in dryland rocks from the Tsauchab River banks in Namibia. We paired culture-independent 16S rRNA gene amplicon sequencing with culture-dependent (isolation of bacteria) techniques to assess the community structure and diversity patterns. Bacteria isolated from dryland rocks are typical of xeric environments and are described as being involved in rock weathering processes. For the first time, we extracted extra- and intracellular DNA from rocks to enhance our understanding of potentially rock-weathering microorganisms. We compared the microbial community structure in different rock types (limestone, quartz-rich sandstone and quartz-rich shale) with adjacent soils below the rocks. Our results indicate differences in the living lithic and sublithic microbial communities.

Background: The native crop bacterial microbiota of the rhizosphere is envisioned to be engineered for sustainable agriculture. This requires the identification of keystone rhizosphere Bacteria and an understanding on how these govern crop-specific microbiome assembly from soils. We identified the metabolically active bacterial microbiota (SSU RNA) inhabiting two compartments of the rhizosphere of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rye (Secale cereale), and oilseed rape (Brassica napus L.) at different growth stages. Results: Based on metabarcoding analysis the bacterial microbiota was shaped by the two rhizosphere compartments, i.e. close and distant. Thereby implying a different spatial extend of bacterial microbiota acquirement by the cereals species versus oilseed rape. We derived core microbiota of each crop species. Massilia (barley and wheat) and unclassified Chloroflexi of group ‘KD4-96’ (oilseed rape) were identified as keystone Bacteria by combining LEfSe biomarker and network analyses. Subsequently, differential associations between networks of each crop species’ core microbiota revealed host plant-specific interconnections for specific genera, such as the unclassified Tepidisphaeraceae ‘WD2101 soil group’. Conclusions: Our results provide keystone rhizosphere Bacteria derived from for crop hosts and revealed that cohort subnetworks and differential associations elucidated host species effect that was not evident from differential abundance of single bacterial genera enriched or unique to a specific plant host. Thus, we underline the importance of co-occurrence patterns within the rhizosphere microbiota that emerge in crop-specific microbiomes, which will be essential to modify native crop microbiome for future agriculture and to develop effective bio-fertilizers.

To adapt to climate change, several agricultural strategies are currently being explored, including a shift in land use areas. Regional differences in microbiome composition and associated phytopathogens need to be considered. However, most empirical studies on differences in the crop microbiome focused on soil communities, with insufficient attention to the phyllosphere. In this study, we focused on wheat ears in three regions in northeastern Germany (Magdeburger Börde (MBB), Müncheberger Sander (MSA), Uckermärkisches Hügelland (UKH)) with different yield potentials, soil, and climatic conditions. To gain insight into the fungal community at different sites, we used a metabarcoding approach (ITS-NGS). Further, we examined the diversity and abundance of Fusarium and Alternaria using culture-dependent and culture-independent techniques. For each region, the prevalence of different orders rich in phytopathogenic fungi was determined: Sporidiobolales in MBB, Capnodiales and Pleosporales in MSA, and Hypocreales in UKH were identified as taxonomic biomarkers. Additionally, F. graminearum was found predominantly in UKH, whereas F. poae was more abundant in the other two regions. Environmental filters seem to be strong drivers of these differences, but we also discuss the possible effects of dispersal and interaction filters. Our results can guide shifting cultivation regions to be selected in the future concerning their phytopathogenic infection potential.