Multiple Sources of Introduction of North American Arabidopsis thaliana from across Eurasia

Large-scale movement of organisms across their habitable range, or migration, is an important evolutionary process that can shape genetic diversity and influence the adaptive spread of alleles. Although human migrations have been studied in great detail with modern and ancient genomes, recent anthropogenic influence on reducing the biogeographical constraints on the migration of nonnative species has presented opportunities in several study systems to ask the questions about how repeated introductions shape genetic diversity in the introduced range. We present an extensive overview of population structure of North American Arabidopsis thaliana by studying a set of 500 whole-genome sequenced and over 2,800 RAD-seq genotyped individuals in the context of global diversity represented by Afro-Eurasian genomes. We use methods based on haplotype and rare-allele sharing as well as phylogenetic modeling to identify likely sources of introductions of extant N. American A. thaliana from the native range in Africa and Eurasia. We find evidence of admixture among the introduced lineages having increased haplotype diversity and reduced mutational load. We also detect signals of selection in immune-system-related genes that may impart qualitative disease resistance to pathogens of bacterial and oomycete origin. We conclude that multiple introductions to a nonnative range can rapidly enhance the adaptive potential of a colonizing species by increasing haplotypic diversity through admixture. Our results lay the foundation for further investigations into the functional significance of admixture.

Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition

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.

HASTY modulates miRNA biogenesis by linking pri-miRNA transcription and processing

Post-transcriptional gene silencing mediated by microRNAs (miRNAs) modulates numerous developmental and stress response pathways. For the last two decades, HASTY (HST), the ortholog of human EXPORTIN 5, was considered to be a candidate protein that exports plant miRNAs from the nucleus to the cytoplasm. Here, we report that HST functions in the miRNA pathway independent of its cargo-exporting activity in Arabidopsis. We found that Arabidopsis mutants with impaired HST shuttling exhibit normal subcellular distribution of miRNAs. Interestingly, protein-protein interaction and microscopy assays showed that HST directly interacts with the microprocessor core component DCL1 through its N-terminal domain. Moreover, mass spectrometry analysis revealed that HST also interacts independently of its N-terminal domain with the mediator complex subunit MED37. Further experiments revealed that HST could act as a scaffold to facilitate the recruitment of DCL1 to genomic MIRNA loci by stabilizing the DCL1-MED37 complex, which in turn promotes the transcription and proper processing of primary miRNA transcripts (pri-miRNAs). Taken together, these results suggest that HST is likely associated with the formation of the miRNA biogenesis complex at MIRNA genes, promoting the transcription and processing of pri-miRNAs rather than the direct export of processed miRNAs from the nucleus.

Combining whole-genome shotgun sequencing and rRNA gene amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, support the acquisition of nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of the 16S rRNA gene and/or the internal transcribed spacer (ITS) of rRNA genomic loci, which show the relative abundance of the microbes to each other. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S and eukaryotic ITS1 rRNA amplicon data from 176 of these samples. Shotgun data, which unlike the amplicon data capture the ratio of microbe to plant DNA, enable scaling of microbial read abundances to reflect the microbial load on the host. In a more cost-effective hybrid strategy, we show they also allow a similar scaling of amplicon data to overcome compositionality problems. Our wild plants were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. Microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. Critically, considering absolute microbial load led to fundamentally different conclusions about microbiome assembly and the interaction networks among major taxa.

Arabidopsis thaliana and Pseudomonas Pathogens Exhibit Stable Associations over Evolutionary Timescales

Crop disease outbreaks are often associated with clonal expansions of single pathogenic lineages. To determine whether similar boom-and-bust scenarios hold for wild pathosystems, we carried out a multi-year, multi-site survey of Pseudomonas in its natural host Arabidopsis thaliana. The most common Pseudomonas lineage corresponded to a ubiquitous pathogenic clade. Sequencing of 1,524 genomes revealed this lineage to have diversified approximately 300,000 years ago, containing dozens of genetically identifiable pathogenic sublineages. There is differentiation at the level of both gene content and disease phenotype, although the differentiation may not provide fitness advantages to specific sublineages. The coexistence of sublineages indicates that in contrast to crop systems, no single strain has been able to overtake the studied A. thaliana populations in the recent past. Our results suggest that selective pressures acting on a plant pathogen in wild hosts are likely to be much more complex than those in agricultural systems.

Genomic features of bacterial adaptation to plants

Plants intimately associate with diverse bacteria. Plant-associated (PA) bacteria have ostensibly evolved genes enabling adaptation to the plant environment. 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 3837 bacterial genomes to identify thousands of PA gene clusters. Genomes of PA bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant associated genomes. We experimentally validated candidates from two sets of PA genes, one involved in plant colonization, the other serving in microbe-microbe competition between PA bacteria. We also identified 64 PA protein domains that potentially mimic plant domains; some are shared with PA fungi and oomycetes. This work expands the genome-based understanding of plant-microbe interactions and provides leads for efficient and sustainable agriculture through microbiome engineering.

Learning Microbial Interaction Networks from Metagenomic Count Data

Many microbes associate with higher eukaryotes and impact their vitality. To engineer microbiomes for host benefit, we must understand the rules of community assembly and maintenance that, in large part, demand an understanding of the direct interactions among community members. Toward this end, we have developed a Poisson-multivariate normal hierarchical model to learn direct interactions from the count-based output of standard metagenomics sequencing experiments. Our model controls for confounding predictors at the Poisson layer and captures direct taxon-taxon interactions at the multivariate normal layer using an ℓ1 penalized precision matrix. We show in a synthetic experiment that our method handily outperforms state-of-the-art methods such as SparCC and the graphical lasso (glasso). In a real in planta perturbation experiment of a nine-member bacterial community, we show our model, but not SparCC or glasso, correctly resolves a direct interaction structure among three community members that associates with Arabidopsis thaliana roots. We conclude that our method provides a structured, accurate, and distributionally reasonable way of modeling correlated count-based random variables and capturing direct interactions among them.

Methods for Genotyping-by-Sequencing

A major goal for biologists is to understand the connection between genes and phenotypic traits, and genetic mapping in experimental populations remains a powerful approach for discovering the causal genes underlying phenotypes. For genetic mapping, the process of genotyping was previously a major rate-limiting step. Modern sequencing technology has greatly improved the resolution and speed of genetic mapping by reducing the time, labor, and cost per genotyping marker. In addition, the ability to perform genotyping-by-sequencing (GBS) has facilitated large-scale population genetic analyses by providing a simpler way to survey segregating genetic variation in natural populations. Here we present two protocols for GBS, using the Illumina platform, that can be applied to a wide range of genotyping projects in different species. The first protocol is for genotyping a subset of marker positions genome-wide using restriction digestion, and the second is for preparing inexpensive paired-end whole-genome libraries. We discuss the suitability of each approach for different genotyping applications and provide notes for adapting these protocols for use with a liquid-handling robot.

Host genotype and age shape the leaf and root microbiomes of a wild perennial plant

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.

PLANT MICROBIOME. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa

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.

ProDeGe: a computational protocol for fully automated decontamination of genomes

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.

MT-Toolbox: improved amplicon sequencing using molecule tags

Background

Short oligonucleotides can be used as markers to tag and track DNA sequences. For example, barcoding techniques (i.e. Multiplex Identifiers or Indexing) use short oligonucleotides to distinguish between reads from different DNA samples pooled for high-throughput sequencing. A similar technique called molecule tagging uses the same principles but is applied to individual DNA template molecules. Each template molecule is tagged with a unique oligonucleotide prior to polymerase chain reaction. The resulting amplicon sequences can be traced back to their original templates by their oligonucleotide tag. Consensus building from sequences sharing the same tag enables inference of original template molecules thereby reducing effects of sequencing error and polymerase chain reaction bias. Several independent groups have developed similar protocols for molecule tagging; however, user-friendly software for build consensus sequences from molecule tagged reads is not readily available or is highly specific for a particular protocol.

Results

MT-Toolbox recognizes oligonucleotide tags in amplicons and infers the correct template sequence. On a set of molecule tagged test reads, MT-Toolbox generates sequences having on average 0.00047 errors per base. MT-Toolbox includes a graphical user interface, command line interface, and options for speed and accuracy maximization. It can be run in serial on a standard personal computer or in parallel on a Load Sharing Facility based cluster system. An optional plugin provides features for common 16S metagenome profiling analysis such as chimera filtering, building operational taxonomic units, contaminant removal, and taxonomy assignments.

Conclusions

MT-Toolbox provides an accessible, user-friendly environment for analysis of molecule tagged reads thereby reducing technical errors and polymerase chain reaction bias. These improvements reduce noise and allow for greater precision in single amplicon sequencing experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-284) contains supplementary material, which is available to authorized users.

Natural soil microbes alter flowering phenology and the intensity of selection on flowering time in a wild Arabidopsis relative

Plant phenology is known to depend on many different environmental variables, but soil microbial communities have rarely been acknowledged as possible drivers of flowering time. Here, we tested separately the effects of four naturally occurring soil microbiomes and their constituent soil chemistries on flowering phenology and reproductive fitness of Boechera stricta, a wild relative of Arabidopsis. Flowering time was sensitive to both microbes and the abiotic properties of different soils; varying soil microbiota also altered patterns of selection on flowering time. Thus, soil microbes potentially contribute to phenotypic plasticity of flowering time and to differential selection observed between habitats. We also describe a method to dissect the microbiome into single axes of variation that can help identify candidate organisms whose abundance in soil correlates with flowering time. This approach is broadly applicable to search for microbial community members that alter biological characteristics of interest.

Practical innovations for high-throughput amplicon sequencing

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.

Defining the core Arabidopsis thaliana root microbiome

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. Colonization of the root occurs despite a sophisticated plant immune system, 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.

Defining the core Arabidopsis thaliana root microbiome

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. Colonization of the root occurs despite a sophisticated plant immune system, 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.

The transcriptional regulator AlgR is essential for Pseudomonas aeruginosa pathogenesis

Chronic Pseudomonas aeruginosa lung infection is the major cause of morbidity and mortality in cystic fibrosis (CF) patients. One P. aeruginosa virulence factor unique to CF isolates is overproduction of alginate, phenotypically termed mucoidy. Mucoidy is the result of increased transcription from the algD gene and is activated by the transcriptional regulator AlgR. Mutations in algR result in a nonmucoid phenotype and loss of twitching motility. Additionally, AlgR controls transcription of algC, encoding a dual-function enzyme necessary for both lipopolysaccharide (LPS) and alginate production. Therefore, to determine the effect of algR on P. aeruginosa virulence, an algR mutant was examined for sensitivity to reactive oxygen intermediates, killing by phagocytes, systemic virulence, and the ability to maintain a murine lung infection. We found that P. aeruginosa PAO700 (algR::Gm(r)) was less lethal than PAO1, as tested in an acute septicemia infection mouse model, and was cleared more efficiently in a mouse pneumonia model. Additionally, the algR mutant (PAO700) was more sensitive to hypochlorite. However, PAO700 was more resistant to hydrogen peroxide and killed less readily in an acellular myeloperoxidase assay than PAO1. There was little difference in killing between PAO1 and PAO700 with macrophage-like J774 cells and human polymorhonuclear leukocytes. Two-dimensional gel analysis of P. aeruginosa algR mutant and wild-type protein extracts revealed 47 differentially regulated proteins, suggesting that AlgR plays both a positive role and a negative role in gene expression. Together, these results imply that AlgR is necessary for virulence and regulates genes in addition to the genes associated with alginate and LPS production and pilus function.