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A set of practical improvements and software provide more accurate and less biased metagenomic amplicon sequencing at lower sequencing effort. We describe improvements for sequencing 16S ribosomal RNA (rRNA) amplicons, a cornerstone technique in metagenomics. Through unique tagging of template molecules before PCR, amplicon sequences can be mapped to their original templates to correct amplification bias and sequencing error with software we provide. PCR clamps block amplification of contaminating sequences from a eukaryotic host, thereby substantially enriching microbial sequences without introducing bias.

Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant’s genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome is evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments. Laboratory-based studies of the effect of plant genotype on plant microbiome composition often do not consider the influence of environmental heterogeneity. Here, Wagner et al . use a large-scale field experiment to assess the extent of host genetic and environmental factors on the microbiome of Boechera stricta .

Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and the other serving in microbe–microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. This work expands the genome-based understanding of plant–microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering. Comparative genomic analysis of 3,837 bacterial genomes, including new sequences from 484 root-associated isolates, identifies plant-associated gene clusters and plant-mimicking domains.

Sequencing of the Arabidopsis thaliana root microbiome shows that its composition is strongly influenced by location, inside or outside the root, and by soil type. Root dwellers: bacterial communities in the plant root microbiome The association between a land plant and the soil microbes of the root microbiome is important for the plant's well-being. A deeper understanding of these microbial communities will offer opportunities to control plant growth and susceptibility to pathogens, particularly in sustainable agricultural regimes. Two groups, working separately but developing best-practice protocols in parallel, have characterized the root microbiota of the model plant Arabidopis thaliana . Working on two continents and with five different soil types, they reach similar general conclusions. The bacterial communities in each root compartment — the rhizosphere immediately surrounding the root and the endophytic compartment within the root — are most strongly influenced by soil type, and to a lesser degree by host genotype. In natural soils, Arabidopsis plants are preferentially colonized by Actinobacteria, Proteobacteria, Bacteroidetes and Chloroflexi species. And — an important point for future work — Arabidopsis root selectivity for soil bacteria under controlled environmental conditions mimics that of plants grown in a natural environment. Land plants associate with a root microbiota distinct from the complex microbial community present in surrounding soil. The microbiota colonizing the rhizosphere (immediately surrounding the root) and the endophytic compartment (within the root) contribute to plant growth, productivity, carbon sequestration and phytoremediation 1 , 2 , 3 . Colonization of the root occurs despite a sophisticated plant immune system 4 , 5 , suggesting finely tuned discrimination of mutualists and commensals from pathogens. Genetic principles governing the derivation of host-specific endophyte communities from soil communities are poorly understood. Here we report the pyrosequencing of the bacterial 16S ribosomal RNA gene of more than 600 Arabidopsis thaliana plants to test the hypotheses that the root rhizosphere and endophytic compartment microbiota of plants grown under controlled conditions in natural soils are sufficiently dependent on the host to remain consistent across different soil types and developmental stages, and sufficiently dependent on host genotype to vary between inbred Arabidopsis accessions. We describe different bacterial communities in two geochemically distinct bulk soils and in rhizosphere and endophytic compartments prepared from roots grown in these soils. The communities in each compartment are strongly influenced by soil type. Endophytic compartments from both soils feature overlapping, low-complexity communities that are markedly enriched in Actinobacteria and specific families from other phyla, notably Proteobacteria. Some bacteria vary quantitatively between plants of different developmental stage and genotype. Our rigorous definition of an endophytic compartment microbiome should facilitate controlled dissection of plant–microbe interactions derived from complex soil communities.

Immune systems distinguish \"self\" from \"nonself\" to maintain homeostasis and must differentially gate access to allow colonization by potentially beneficial, nonpathogenic microbes. Plant roots grow within extremely diverse soil microbial communities but assemble a taxonomically limited root-associated microbiome. We grew isogenic Arabidopsis thaliana mutants with altered immune systems in a wild soil and also in recolonization experiments with a synthetic bacterial community. We established that biosynthesis of, and signaling dependent on, the foliar defense phytohormone salicylic acid is required to assemble a normal root microbiome. Salicylic acid modulates colonization of the root by specific bacterial families. Thus, plant immune signaling drives selection from the available microbial communities to sculpt the root microbiome.

Host genetics and the environment influence which fungal microbes colonize a plant. A new study in PLOS Biology finds that the relative influence of these factors changes throughout the development of the biofuel crop switchgrass growing in field settings.

When wild plants defend themselves from pathogens, this often comes with a trade-off: the same genes that protect a plant from disease can also reduce its growth and fecundity in the absence of pathogens. One protein implicated in a major growth-defense trade-off is ACCELERATED CELL DEATH 6 (ACD6), an ion channel that modulates salicylic acid (SA) synthesis to potentiate a wide range of defenses. Wild Arabidopsis thaliana populations maintain significant functional variation at the ACD6 locus, with some alleles making the protein hyperactive. In the greenhouse, plants with hyperactive ACD6 alleles are resistant to diverse pathogens, yet they are of smaller stature, their leaves senesce earlier, and they set fewer seeds compared to plants with the standard allele. We hypothesized that ACD6 hyperactivity would not only affect the growth of microbial pathogens but also more generally change leaf microbiome assembly. To test this in an ecologically meaningful context, we compared plants with hyperactive, standard, and defective ACD6 alleles in the same field-collected soil, both outdoors and in naturally lit and climate-controlled indoor conditions, taking advantage of near-isogenic lines as well as a natural accession and a CRISPR-edited derivative. We surveyed visual phenotypes, gene expression, hormone levels, seed production, and the microbiome in each environment. The genetic precision of CRISPR-edited plants allowed us to conclude that ACD6 genotype had no effect on mature field plants in our setting, despite reproducibly dramatic effects on greenhouse plants. We conclude that additional abiotic and/or microbial signals present outdoors—but not in the greenhouse—greatly modulate ACD6 activity. This raises the possibility that the fitness costs of other commonly studied immune system genes may be grossly misjudged without field studies.

The community structure in the plant-associated microbiome depends collectively on host–microbe, microbe–microbe and host–microbe–microbe interactions. The ensemble of interactions between the host and microbial consortia may lead to outcomes that are not easily predicted from pairwise interactions. Plant–microbe–microbe interactions are important to plant health but could depend on both host and microbe strain variation. Here we study interactions between groups of naturally co-existing commensal and pathogenic Pseudomonas strains in the Arabidopsis thaliana phyllosphere. We find that commensal Pseudomonas prompt a host response that leads to selective inhibition of a specific pathogenic lineage, resulting in plant protection. The extent of protection depends on plant genotype, supporting that these effects are host-mediated. Strain-specific effects are also demonstrated by one individual Pseudomonas isolate eluding the plant protection provided by commensals. Our work highlights how within-species genetic differences in both hosts and microbes can affect host–microbe–microbe dynamics. The authors conduct competition experiments with multiple strains of Pseudomonas (some pathogenic and some commensal) in the phylosphere microbiome of Arabidopsis plants, showing that both the host and the commensal strains interact to inhibit the pathogenic strains.

The ratio of microbial population size relative to the amount of host tissue, or ‘microbial load’, is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because existing methods to determine load, such as serial dilution plating, quantitative PCR, and whole metagenome sequencing add substantial cost and/or experimental burden, they are only rarely paired with amplicon sequencing. We introduce host-associated microbe PCR (hamPCR), a robust strategy to both quantify microbial load and describe interkingdom microbial community composition in a single amplicon library. We demonstrate its accuracy across multiple study systems, including nematodes and major crops, and further present a cost-saving technique to reduce host overrepresentation in the library prior to sequencing. Because hamPCR provides an accessible experimental solution to the well-known limitations and statistical challenges of compositional data, it has far-reaching potential in culture-independent microbiology.

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.