Functional Rhizosphere Microbiomes And Effects On Plant-Host Growth, Development, And Abiotic Stress Tolerance

FUNCTIONAL RHIZOSPHERE MICROBIOMES AND EFFECTS ON PLANTHOST GROWTH, DEVELOPMENT, AND ABIOTIC STRESS TOLERANCE Kevin Wayne Panke-Buisse, Ph. D. Cornell University, February, 2016 The rhizosphere microbiome is the community of microorganisms on and surrounding plant roots. This community is important for both above and below ground ecosystem functioning as well as plant growth and development. The depth and complexity of microbe-microbe and plant-microbe interactions within the rhizosphere remain largely uncharacterized. In this dissertation, I explore the rhizosphere system from three directions. First, I propose multiple levels of selection upon extracellular enzyme production and soil organic matter depolymerization as a conceptual framework for explaining the evolution of cooperative rhizospheres. Second, I demonstrate the ability to apply ecosystem-level selection to rhizosphere microcosms to assemble functional microbiomes capable of altering plant flowering phenology and biomass partitioning. I also test the ability of the assembled flowering microbiomes, and sub-communities cultivated from them, to reproduce their function in novel and familiar plant hosts. Flowering microbiomes were able to reproduce their function in several novel Arabidopsis thaliana genotypes and Brassica rapa, a family-level relative. Cultivated sub-communities displayed variability in their effects on host plant growth and development depending on the composition of the cultivation media. Two of the four cultivation media reproduced the flowering effects of the early-flowering whole microbiome from which they were cultivated. These two sub-communities also increased plant biomass in contrast to the decrease in plant biomass associated with the whole microbiome. Third, I investigate the rhizosphere microbiome of 116 closely-related tall fescue varieties under drought stress to assess the role of the rhizosphere microbiome in genotype-specific variations in abiotic stress tolerance. Differences in drought tolerance were primarily associated with shifts in microbial extracellular enzyme production and fungal endophyte infection rates over differences in bacterial community composition. This work adds to the growing understanding of the complex network of interactions within the rhizosphere and presents ecosystem selection and cultivation as a means of enhancing and characterizing microbiomemediated effects on plant growth and development. Furthermore, the parallel investigation of rhizosphere microbiome function between plant genotypes and the response of the microbiome to selective pressure begins to uncover the potential of microbial components in traditional plant breeding programs

Bacterial community composition of vermicompost-treated tomato rhizospheres.

Vermicompost application has been shown to promote plant growth, alter the rhizosphere microbiome, and suppress plant pathogens. These beneficial properties are often attributed to the activity of vermicompost-associated microorganisms. However, little is known about the microbial shifts that occur in the rhizosphere after vermicompost application. To better understand the impact of vermicompost treatments on the assembly of rhizosphere bacterial communities, 16S rDNA communities of vermicompost and rhizospheres of each peat- and soil-grown tomatoes were profiled after conventional fertigation, irrigation without additional nutrients, and addition of three different vermicompost-extracts. The full dataset consisted of 412 identified genera, of which 317 remained following stringent quality filtration. Tomato rhizosphere microbiome responses to treatments were complex and unique between peat and soil growth substrates. Direct colonization of vermicompost-origin taxa into rhizospheres was limited, with genera Photobacterium and Luteimonas colonizing peat rhizospheres, genera Truepera, Phenylobacterium, and Lysinibacillus colonizing soil rhizospheres, and genus Pelagibius appearing in both soil and peat rhizospheres. Further patterns of differential abundance and presence/absence between treatments highlight vermicompost-mediated effects on rhizosphere microbiome assembly as an interplay of rhizosphere medium, direct colonization of vermicompost-origin taxa and vermicompost-induced shifts in the rhizosphere microbial community. This exploratory analysis is intended to provide an initial look at 16S community composition of vermicompost and the effects of vermicompost treatment on the rhizosphere microbiome assembly to highlight interactions of potential merit for subsequent investigations

Increasing Dairy Sustainability with Integrated Crop–Livestock Farming

Dairy farms are predominantly carbon sources, due to high livestock emissions from enteric fermentation and manure. Integrated crop–livestock systems (ICLSs) have the potential to offset these greenhouse gas (GHG) emissions, as recycling products within the farm boundaries is prioritized. Here, we quantify seasonal and annual greenhouse gas budgets of an ICLS dairy farm in Wisconsin USA using satellite remote sensing to estimate vegetation net primary productivity (NPP) and Intergovernmental Panel on Climate Change (IPCC) guidelines to calculate farm emissions. Remotely sensed annual vegetation NPP correlated well with farm harvest NPP (R2 = 0.9). As a whole, the farm was a large carbon sink, owing to natural vegetation carbon sinks and harvest products staying within the farm boundaries. Dairy cows accounted for 80% of all emissions as their feed intake dominated farm feed supply. Manure emissions (15%) were low because manure spreading was frequent throughout the year. In combination with soil conservation practices, ICLS farming provides a sustainable means of producing nutritionally valuable food while contributing to sequestration of atmospheric CO2. Here, we introduce a simple and cost-efficient way to quantify whole-farm GHG budgets, which can be used by farmers to understand their carbon footprint, and therefore may encourage management strategies to improve agricultural sustainability

Root Fungal Endophytes and Microbial Extracellular Enzyme Activities Show Patterned Responses in Tall Fescues under Drought Conditions

Plant response to water stress can be modified by the rhizosphere microbial community, but the range of responses across plant genotypes is unclear. We imposed drought conditions on 116 Festuca arundinacea (tall fescue) accessions using a rainout shelter for 46 days, followed by irrigation, to stimulate drought recovery in 24 days. We hypothesized that prolonged water deficit results in a range of phenotypic diversity (i.e., green color index) across tall fescue genotypes that are associated with distinct microbial taxonomic and functional traits impacting plant drought tolerance. Microbial extracellular enzyme activities of chitinase and phenol oxidase (targeting chitin and lignin) increased in rhizospheres of the 20 most drought tolerant genotypes. Lower rates of fungal (dark septate) endophyte root infection were found in roots of the most drought tolerant genotypes. Bacterial 16S rRNA gene and fungal ITS sequencing showed shifts in microbial communities across water deficit conditions prior to drought, during drought, and at drought recovery, but was not patterned by drought tolerance levels of the plant host. The results suggest that taxonomic information from bacterial 16S rRNA gene and fungal ITS sequences provided little indication of microbial composition impacting drought tolerance of the host plant, but instead, microbial extracellular enzyme activities and root fungal infection results revealed patterned responses from drought

Selection on soil microbiomes reveals reproducible impacts on plant function.

Soil microorganisms found in the root zone impact plant growth and development, but the potential to harness these benefits is hampered by the sheer abundance and diversity of the players influencing desirable plant traits. Here, we report a high level of reproducibility of soil microbiomes in altering plant flowering time and soil functions when partnered within and between plant hosts. We used a multi-generation experimental system using Arabidopsis thaliana Col to select for soil microbiomes inducing earlier or later flowering times of their hosts. We then inoculated the selected microbiomes from the tenth generation of plantings into the soils of three additional A. thaliana genotypes (Ler, Be, RLD) and a related crucifer (Brassica rapa). With the exception of Ler, all other plant hosts showed a shift in flowering time corresponding with the inoculation of early-or lateflowering microbiomes. Analysis of the soil microbial community using 16 S rRNA gene sequencing showed distinct microbiota profiles assembling by flowering time treatment. Plant hosts grown with the late-flowering-associated microbiomes showed consequent increases in inflorescence biomass for three A. thaliana genotypes and an increase in total biomass for B. rapa. The increase in biomass was correlated with two-to five-fold enhancement of microbial extracellular enzyme activities associated with nitrogen mineralization in soils. The reproducibility of the flowering phenotype across plant hosts suggests that microbiomes can be selected to modify plant traits and coordinate changes in soil resource pools

Next-generation whole-farm dairy sustainability analysis: The Ruminant Farm Systems Model

We are building a next-generation dairy systems simulation model that has the flexibility to represent the diversity of management practices on U.S. dairies and is adaptable to our continually growing knowledge of dairy systems. Our Ruminant Farm Systems (RuFaS) model combines knowledge of management, soils, crops, animal nutrition and husbandry, and weather to predict farm productivity, nutrient cycling and loss, energy and water use, GHG emissions, and production costs. By predicting both production and environmental impact under diverse management and climate conditions, RuFaS provides a platform to assess whole system impacts of management strategies and new technologies under current and future climate conditions.The Manager is published by Progressive Dairyman, an award-winning magazine that provides compelling features, helpful articles, insightful news analysis, and entertaining commentary about the people, practices and topics related to a dairy lifestyle

Brisket Disease Is Associated with Lower Volatile Fatty Acid Production and Altered Rumen Microbiome in Holstein Heifers

Brisket disease is heritable but is also associated with non-genetic risk factors and effects of the disease on the rumen microbiome are unknown. Ten Holstein heifers were exposed to the plateau environment for three months and divided into two groups according to the index of brisket disease, the mean pulmonary arterial pressure (mPAP): brisket disease group (BD, n = 5, mPAP > 63 mmHg) and healthy heifer group (HH, n = 5, mPAP < 41 mmHg). Rumen fluid was collected for analysis of the concentrations of volatile fatty acids (VFAs). Extracted DNA from rumen contents was analyzed using Illumina MiSeq 16S rRNA sequencing technology. The concentration of total VFA and alpha-diversity metrics were significantly lower in BD group (p < 0.05). Ruminococcus and Treponema were significantly decreased in BD heifers (p < 0.05). Correlation analysis indicated that 10 genera were related to the mPAP (p < 0.05). Genera of Anaerofustis, Campylobacter, and Catonella were negatively correlated with total VFA and acetic acid (R < −0.7, p < 0.05), while genera of Blautia, YRC22, Ruminococcus, and Treponema were positively related to total VFA and acetic acid (R > 0.7; p < 0.05). Our findings may be a useful biomarker in future brisket disease work

Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities

Microbial communities might include distinct lineages of closely related organisms that complicate metagenomic assembly and prevent the generation of complete metagenome-assembled genomes (MAGs). Here we show that deep sequencing using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex microbial communities. Using existing methods, we sequenced the sheep fecal metagenome and identified 428 MAGs with more than 90% completeness, including 44 MAGs in single circular contigs. To resolve closely related strains (lineages), we developed MAGPhase, which separates lineages of related organisms by discriminating variant haplotypes across hundreds of kilobases of genomic sequence. MAGPhase identified 220 lineage-resolved MAGs in our dataset. The ability to resolve closely related microbes in complex microbial communities improves the identification of biosynthetic gene clusters and the precision of assigning mobile genetic elements to host genomes. We identified 1,400 complete and 350 partial biosynthetic gene clusters, most of which are novel, as well as 424 (298) potential host–viral (host–plasmid) associations using Hi-C data