Recovery of soil unicellular eukaryotes: an efficiency and activity analysis on the single cell level

Soil filtration-sedimentation improves shelled protist recovery in eukaryotic eDNA surveys

A large part of the soil protist diversity is missed in metabarcoding studies based on 0.25 g of soil environmental DNA (eDNA) and universal primers due to ca. 80% co-amplification of non-target plants, animals and fungi. To overcome this problem, enrichment of the substrate used for eDNA extraction is an easily implemented option but its effect has not yet been tested. In this study, we evaluated the effect of a 150 μm mesh size filtration and sedimentation method to improve the recovery of protist eDNA, while reducing the co-extraction of plant, animal and fungal eDNA, using a set of contrasted forest and alpine soils from La Réunion, Japan, Spain and Switzerland. Total eukaryotic diversity was estimated by V4 18S rRNA metabarcoding and classical amplicon sequence variant calling. A 2- to 3-fold enrichment in shelled protists (Euglyphida, Arcellinida and Chrysophyceae) was observed at the sample level with the proposed method, with, at the same time, a 2-fold depletion of Fungi and a 3-fold depletion of Embryophyceae. Protist alpha diversity was slightly lower in filtered samples due to reduced coverage in Variosea and Sarcomonadea, but significant differences were observed in only one region. Beta diversity varied mostly between regions and habitats, which explained the same proportion of variance in bulk soil and filtered samples. The increased resolution in soil protist diversity estimates provided by the filtration-sedimentation method is a strong argument in favour of including it in the standard protocol for soil protist eDNA metabarcoding studies.

Structural and Dynamic Analysis of Leaf-Associated Fungal Community of Walnut Leaves Infected by Leaf Spot Disease Based Illumina High-Throughput Sequencing Technology

Leaf-associated microbiota is vital in plant-environment interactions and is the basis for micro-ecological regulation. However, there are no studies on the direct differences in microbial community composition between disease-susceptible and healthy walnut leaves. This study collected five samples of healthy and infected leaves (all leaves with abnormal spots were considered diseased leaves) from May to October 2018. Differences in fungal diversity (Chao1 index, Shannon index, and Simpson index) and community structure were observed by sequencing and analyzing diseased and healthy leaf microbial communities by Illumina HiSeq sequencing technology. The main fungal phyla of walnut leaf-associated were Ascomycota, Basidiomycota, and Glomeromycota. Diversity indices (Shannon and Chao1 index values) of healthy leaves differed significantly in the late stages of disease onset. The results showed that the fungal species that differed considerably between the healthy and infected groups differed, and the fungal species that differed significantly between the healthy and infected groups changed with the development of the leaf disease. Critical control time points were determined by analyzing the population dynamics of pathogenic fungi. Leaf-associated microorganisms are abundant and diverse, and fungal identification and diversity studies are helpful for developing more appropriate walnut management strategies.

When FLOW-FISH met FACS: Combining multiparametric, dynamic approaches for microbial single-cell research in the total environment

In environmental microbiology, the ability to assess, in a high-throughput way, single-cells within microbial communities is key to understand their heterogeneity. Fluorescence in situ hybridization (FISH) uses fluorescently labeled oligonucleotide probes to detect, identify, and quantify single cells of specific taxonomic groups. The combination of Flow Cytometry (FLOW) with FISH (FLOW-FISH) enables high-throughput quantification of complex whole cell populations, which when associated with fluorescence-activated cell sorting (FACS) enables sorting of target microorganisms. These sorted cells may be investigated in many ways, for instance opening new avenues for cytomics at a single-cell scale. In this review, an overview of FISH and FLOW methodologies is provided, addressing conventional methods, signal amplification approaches, common fluorophores for cell physiology parameters evaluation, and model variation techniques as well. The coupling of FLOW-FISH-FACS is explored in the context of different downstream applications of sorted cells. Current and emerging applications in environmental microbiology to outline the interactions and processes of complex microbial communities within soil, water, animal microbiota, polymicrobial biofilms, and food samples, are described.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

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.

MetaEuk-sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics

BACKGROUND

Metagenomics is revolutionizing the study of microorganisms and their involvement in biological, biomedical, and geochemical processes, allowing us to investigate by direct sequencing a tremendous diversity of organisms without the need for prior cultivation. Unicellular eukaryotes play essential roles in most microbial communities as chief predators, decomposers, phototrophs, bacterial hosts, symbionts, and parasites to plants and animals. Investigating their roles is therefore of great interest to ecology, biotechnology, human health, and evolution. However, the generally lower sequencing coverage, their more complex gene and genome architectures, and a lack of eukaryote-specific experimental and computational procedures have kept them on the sidelines of metagenomics.

RESULTS

MetaEuk is a toolkit for high-throughput, reference-based discovery, and annotation of protein-coding genes in eukaryotic metagenomic contigs. It performs fast searches with 6-frame-translated fragments covering all possible exons and optimally combines matches into multi-exon proteins. We used a benchmark of seven diverse, annotated genomes to show that MetaEuk is highly sensitive even under conditions of low sequence similarity to the reference database. To demonstrate MetaEuk's power to discover novel eukaryotic proteins in large-scale metagenomic data, we assembled contigs from 912 samples of the Tara Oceans project. MetaEuk predicted >12,000,000 protein-coding genes in 8 days on ten 16-core servers. Most of the discovered proteins are highly diverged from known proteins and originate from very sparsely sampled eukaryotic supergroups.

CONCLUSION

The open-source (GPLv3) MetaEuk software (https://github.com/soedinglab/metaeuk) enables large-scale eukaryotic metagenomics through reference-based, sensitive taxonomic and functional annotation. Video abstract.

A convenient, rapid and efficient method for establishing transgenic lines of Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop that offers a considerable amount of biomass for global vegetable oil production. The establishment of an efficient genetic transformation system with a convenient transgenic-positive screening method is of great importance for gene functional analysis and molecular breeding. However, to our knowledge, there are few of the aforementioned systems available for efficient application in B. napus.

RESULTS

Based on the well-established genetic transformation system in B. napus, five vectors carrying the red fluorescence protein encoding gene from Discosoma sp. (DsRed) were constructed and integrated into rapeseed via Agrobacterium-mediated hypocotyl transformation. An average of 59.1% tissues were marked with red fluorescence by the visual screening method in tissue culture medium, 96.1% of which, on average, were amplified with the objective genes from eight different rapeseed varieties. In addition, the final transgenic-positive efficiency of the rooted plantlets reached up to 90.7% from red fluorescence marked tissues, which was much higher than that in previous reports. Additionally, visual screening could be applicable to seedlings via integration of DsRed, including seed coats, roots, hypocotyls and cotyledons during seed germination. These results indicate that the highly efficient genetic transformation system combined with the transgenic-positive visual screening method helps to conveniently and efficiently obtain transgenic-positive rapeseed plantlets.

CONCLUSION

A rapid, convenient and highly efficient method was developed to obtain transgenic plants, which can help to obtain the largest proportion of transgene-positive regenerated plantlets, thereby avoiding a long period of plant regeneration. The results of this study will benefit gene functional studies especially in high-throughput molecular biology research.