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This project aims to study the microbial structure and potential functions of bacterial and fungal microbiomes in leaves, stems, roots, rhizospheres, and bulk soils of energy crops (oilcane) grown in greenhouses.
Support from this award enabled us to expand critical genomic and epigenomic resources available for the study and engineering of duckweeds, and to complete design-build-test-learn cycles that culminated in the engineering of high oil duckweeds. We shared our findings with the public and scientific community in a series of peer-reviewed publications highlighted within. We successfully reengineered metabolism, dramatically increasing oil content by diverting a substantial portion of accumulated carbon from starch. This sets the stage for the use of fast growing aquatic duckweeds as robust, highly productive sources of biodiesel, with the capacity to outperform soybean oil crops.
Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development. Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data. We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.
Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.
Plants can influence soil microbes through resource acquisition and interference competition, with consequences for ecosystem function such as nitrification. However, how plants alter soil conditions to influence nitrifiers and nitrification rates remains poorly understood, especially in the subsoil. Here, coupling the 15N isotopic pool dilution technique, high throughput sequencing and in situ soil O2 monitoring, we investigated how a deep-rooted perennial grass, miscanthus, versus an adjacent shallow-rooted turfgrass reference shapes nitrifier assembly and function along 1 m soil profiles. In topsoil, the suppression of ammonia (NH3) oxidizing archaea (AOA) and gross nitrification rates in miscanthus relative to the reference likely resulted from nitrifiers being outcompeted by plant roots and heterotrophic bacteria for ammonium (NH4+). The stronger tripartite competition under miscanthus may have been caused in part by the lower soil organic matter (SOM) content, which supported lower gross nitrogen (N) mineralization, the major soil process that produces NH4+. In contrast, below 10 cm soil depth, significantly greater gross nitrification rates were observed in miscanthus compared to the reference. This was likely driven by the significantly lower oxygen (O2) in miscanthus than reference subsoil, which selected against aerobic heterotrophic bacteria but in favor of AOA. Overall, we found that plants can regulate AOA community structure and function through different mechanisms in topsoil and subsoil, with suppression of nitrification in topsoil and enhancement of nitrification in subsoil.
Endophytes are potential partners for improving the resource use efficiency of bioenergy feedstock systems such as short rotation coppiced Populus. Endophytes isolated from members of the Salicaceae family have broad host compatibility and can improve water use efficiency (WUE) through decreases in stomatal conductance. However, the literature is inconsistent with regards to the environmental conditions and temporal patterns of these benefits. This study investigates how endophyte mediated changes in Populus trichocarpa (Torr. and Gray) ‘Nisqually-1’ stomatal conductance and WUE shift with time and scale in response to water-deficit stress. Leaf gas exchange and above-ground productivity were used to evaluate the carbon and water balances of glasshouse grown plants in response to endophyte inoculation and water-deficit. Differences in stomatal conductance between control and inoculated plants were more pronounced (39.7 % decrease, Welch’s two-sample t(14.34 dfadj) = -2.358, p-value = 0.033) under water-deficit conditions in the late morning during a period of higher light intensity. The decrease in stomatal conductance accompanied a substantial increase in intrinsic WUE (iWUE) for water-deficit inoculated plants. However, increases in iWUE did not result in improvements in aboveground productivity or shoot biomass WUE (WUEsb) for water-deficit inoculated plants. This decoupling between iWUE and aboveground productivity may be an indicator of assimilate allocation to microbial metabolism as an additional carbon sink or a shift in carbon allocation towards belowground biomass. Future work should take a whole-plant approach that accounts for diurnal patterns in incident irradiance to evaluate the impact of endophyte inoculation on host WUE and stress tolerance.
ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.