Bacterial Spermosphere Inoculants Alter N. benthamiana-Plant Physiology and Host Bacterial Microbiome.

In this study, we investigated the interplay between the spermosphere inoculum, host plant physiology, and endophytic compartment (EC) microbial community. Using 16S ribosomal RNA gene sequencing of root, stem, and leaf endophytic compartment communities, we established a baseline microbiome for Nicotiana sp. Phenotypic differences were observed due to the addition of some bacterial inoculants, correlated with endogenous auxin loads using transgenic plants expressing the auxin reporter pB-GFP::P87. When applied as spermosphere inoculants, select bacteria were found to create reproducible variation within the root EC microbiome and, more systematically, the host plant physiology. Our findings support the assertion that the spermosphere of plants is a zone that can influence the EC microbiome when applied in a greenhouse setting.

Spatial metatranscriptomics resolves host-bacteria-fungi interactomes.

The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host-microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host-microbiome interplay.

Contrasting patterns of microbial dominance in the Arabidopsis thaliana phyllosphere.

Sphingomonas is one of the most abundant bacterial genera in the phyllosphere of wild Arabidopsis thaliana, but relative to Pseudomonas, the ecology of Sphingomonas and its interaction with plants is poorly described. We analyzed the genomic features of over 400 Sphingomonas isolates collected from local A. thaliana populations, which revealed much higher intergenomic diversity than for the considerably more uniform Pseudomonas isolates found in the same host populations. Variation in Sphingomonas plasmid complements and additional genomic features suggest high adaptability of this genus, and the widespread presence of protein secretion systems hints at frequent biotic interactions. While some of the isolates showed plant-protective phenotypes in lab tests, this was a rare trait. To begin to understand the extent of strain sharing across alternate hosts, we employed amplicon sequencing and a bulk-culturing metagenomics approach on both A. thaliana and neighboring plants. Our data reveal that both Sphingomonas and Pseudomonas thrive on other diverse plant hosts, but that Sphingomonas is a poor competitor in dying or dead leaves.

The changing influence of host genetics on the leaf fungal microbiome throughout plant development.

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.

Commensal Pseudomonas strains facilitate protective response against pathogens in the host plant.

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.

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.

Blue Native Polyacrylamide Gel Electrophoresis (BN-PAGE) for the Analysis of Protein Oligomers in Plants.

Protein-protein interactions, including oligomerization, are involved in regulation of many cellular processes. Unfortunately, many proteins are expressed at a very low level in vivo, making it challenging to observe oligomerization by size-exclusion chromatography, also known as gel filtration. In this protocol, we present detailed steps to perform blue native polyacrylamide gel electrophoresis (BN-PAGE), a method to study protein oligomers in plants. The article describes protein sample preparation from transgenic Arabidopsis thaliana and running a BN-PAGE gel followed by direct western blotting or, alternatively, two-dimensional sodium dodecyl sulfide-polyacrylamide gel electrophoresis (2D SDS-PAGE). This protocol will be helpful for new researchers conducting related experiments to analyze stable protein interactions including homo- or hetero-oligomerization in plants. © 2020 The Authors.

Minimal effects of reduced teaching hours on undergraduate medical student learning outcomes and course evaluations.

Introduction: Various pressures exist for curricular change, including economic forces, burgeoning knowledge, broadening learning outcomes, and improving quality and outcomes of learning experiences. In an Australian 5-year undergraduate medical course, staff were asked to reduce teaching hours by 20% to alleviate perceived overcrowded preclinical curriculum, achieve operating efficiencies and liberate time for students' self-directed learning.Methods: A case study design with mixed methods was used to evaluate outcomes.Results: Teaching hours were reduced by 198 hours (14%) overall, lectures by 153 hours (19%) and other learning activities by 45 hours (7%). Summative assessment scores did not change significantly after the reductions: 0.4% increase, 1.5% decrease and 1.7% increase in Years 1, 2 and 3, respectively. The percentage of students successfully completing their academic year did not change significantly: 94.4% before and 93.3% after the reductions. Student evaluations from eVALUate surveys changed little, except workload was perceived to be more reasonable.Conclusions: Teaching hours, particularly lectures, can be moderately reduced with little impact on student learning outcomes or satisfaction with an undergraduate medical course.

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 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.

A psychometric evaluation of the anatomy learning experiences questionnaire and correlations with learning outcomes.

The Anatomy Learning Experiences Questionnaire (ALEQ) was designed by Smith and Mathias to explore students' perceptions and experiences of learning anatomy. In this study, the psychometric properties of a slightly altered 34-item ALEQ (ALEQ-34) were evaluated, and correlations with learning outcomes investigated, by surveying first- and second-year undergraduate medical students; 181 usable responses were obtained (75% response rate). Psychometric analysis demonstrated overall good reliability (Cronbach's alpha of 0.85). Exploratory factor analysis yielded a 27-item, three-factor solution (ALEQ-27, Cronbach's alpha of 0.86), described as: (Factor 1) (Reversed) challenges in learning anatomy, (Factor 2) Applications and importance of anatomy, and (Factor 3) Learning in the dissection laboratory. Second-year students had somewhat greater challenges and less positive attitudes in learning anatomy than first-year students. Females reported slightly greater challenges and less confidence in learning anatomy than males. Total scores on summative gross anatomy examination questions correlated with ALEQ-27, Pearson's r = 0.222 and 0.271, in years 1 and 2, respectively, and with Factor 1, r = 0.479 and 0.317 (all statistically significant). Factor 1 also had similar correlations across different question types (multiple choice; short answer or essay; cadaveric; and anatomical models, bones, or radiological images). In a retrospective analysis, Factor 1 predicted poor end-of-semester anatomy examination results in year 1 with a sensitivity of 88% and positive predictive value of 33%. Further development of ALEQ-27 may enable deeper understanding of students' learning of anatomy, and its ten-item Factor 1 may be a useful screening tool to identify at-risk students. Anat Sci Educ 10: 514-527. © 2017 American Association of Anatomists.

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.

Online dissection audio-visual resources for human anatomy: Undergraduate medical students' usage and learning outcomes.

In an attempt to improve undergraduate medical student preparation for and learning from dissection sessions, dissection audio-visual resources (DAVR) were developed. Data from e-learning management systems indicated DAVR were accessed by 28% ± 10 (mean ± SD for nine DAVR across three years) of students prior to the corresponding dissection sessions, representing at most 58% ± 20 of assigned dissectors. Approximately 50% of students accessed all available DAVR by the end of semester, while 10% accessed none. Ninety percent of survey respondents (response rate 58%) generally agreed that DAVR improved their preparation for and learning from dissection when used. Of several learning resources, only DAVR usage had a significant positive correlation (P = 0.002) with feeling prepared for dissection. Results on cadaveric anatomy practical examination questions in year 2 (Y2) and year 3 (Y3) cohorts were 3.9% (P < 0.001, effect size d = -0.32) and 0.3% lower, respectively, with DAVR available compared to previous years. However, there were positive correlations between students' cadaveric anatomy question scores with the number and total time of DAVR viewed (Y2, r = 0.171, 0.090, P = 0.002, n.s., respectively; and Y3, r = 0.257, 0.253, both P < 0.001). Students accessing all DAVR scored 7.2% and 11.8% higher than those accessing none (Y2, P = 0.015, d = 0.48; and Y3, P = 0.005, d = 0.77, respectively). Further development and promotion of DAVR are needed to improve engagement and learning outcomes of more students. Anat Sci Educ 9: 545-554. © 2016 American Association of Anatomists.

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.

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.