Performing Department
(N/A)
Non Technical Summary
Global agriculture sectors are competing for finite P reserves, as it is an essential nutrient for plant growth. Based on current metrics, inexpensive rock phosphate is expected to be depleted within 50-100 years. Focus on P resource management and recovery is critical for all crop production areas, including soil-based, hydroponic, and aquaponic systems. In the soilless AP system, nitrogen transformation and utilization have been the focus of nutrient research. There is a stark lack of information on other essential nutrients in AP, like P, particularly regarding plant-available forms. This knowledge gap limits the sustainability, productivity, and capacity for crop diversification in AP systems. The aim of this proposal is to understand how P recovery/availability, microbial composition of the plant rhizosphere, and regulation of microbial P-enzymes are affected by environmental conditions. We will characterize how these parameters change throughout the plant lifecycle and can be optimized to improve productivity and plant quality in AP systems. By understanding the interactions among the host, environment, and the microbiome, AP practitioners will have a better understanding of nutrient management leading to enhanced system design, improved potential for crop diversification, and possible increased profitability. Results from this research are applicable to home practitioners and multimillion-dollar AP facilities alike. Microbial associations within the plant rhizosphere remain a black box in AP. Given their irreplaceable role in function of the system, it is surprising that investigation into the significant microbial communities that govern AP systems is just beginning. Current research on the taxonomic profile of microorganisms in AP has focused on biofiltration and solids filtration components of the system. There is some, albeit limited, research on the microbial composition in different components of AP systems. Few studies have examined the community composition of the plant rhizosphere. This research utilized 16S rRNA sequencing to identify the quantity and proportion of taxa; however, this technology is limited due to the low taxonomic resolution and bias for assignment of sequences for the variable region chosen for the analysis. In addition, 16S rRNA sequencing only describes what organisms are present and do not infer function of the community. We propose to use a multi-pronged approach to characterize the composition and function of the plant rhizosphere microbiome of AP systems through metagenomics and metatranscriptomics technology, respectively. To our knowledge, this is the first research in AP to employ this approach to determine environmental drivers that influence plant rhizosphere microbiota composition and function. This research will lay the foundation for future microbiome research in AP and open pathways for continued research in the field. Funding of AP research not only provides advances in scientific understanding of these systems but also can potentially provide key insights into microbe-plant interaction in soil-based agriculture. A major focus of soil systems is how microbiota are recruited to the rhizosphere by the plant. These mechanisms are mainly theoretical because results are difficult to dissect due to the physical and chemical complexity of the soil structure. This complexity can hinder sequence-based approaches to microbial community formation, genetic influence on nutrient cycling , and capacity to engineer the plant rhizosphere through plant-promoting organisms. Conversely, AP systems are highly controlled and have little variation in parameters such as temperature, pH, hydraulic loading rate, and nutrient application. The matrix surrounding the plant rhizosphere is markedly less complex in AP than in soil. These systems provide a mechanism to conduct cross-disciplinary research on the plant rhizosphere that can be applied to multiple agriculture production systems. The use of metagenomic data to guide isolation can provide future research opportunities on engineering the plant rhizosphere.
Animal Health Component
20%
Research Effort Categories
Basic
30%
Applied
20%
Developmental
50%
Goals / Objectives
The overall goal of this proposal is to implement low-cost sequencing and -omics technologies to provide key insights into community structure and function of the plant rhizosphere in aquaponics (AP) systems. The specific objectives of this research are to:1) Identify the main environmental drivers of microbial community composition in AP systems.2) Determine if the proportions of rhizosphere microbiota responsible for P-transformation change during the plant lifecycle;3) Determine the effect of environmental manipulation (pH and temperature) on rhizosphere microbiota in vitro;4) Evaluate if optimized environmental parameters correlate to microbial populations that improve P solubilization in-situ;
Project Methods
Obj 1)Water and plant roots samples will be collected from 15 aquaponic (AP) systems nationally. The taxonomic microbial composition and functional gene profile of the plant rhizosphere will be characterized using MGA and MT analysis. Distance-based redundancy analysis (Db-Rda) will be used to identify the main environmental contributors to community composition. A survey will be conducted for participating farms that will collect production data including inputs, production information, and water quality history. A full water nutrient analysis will be conducted for each sample. A hybrid sequencing approach (Nanopore Long reads and Illumina short reads) will be used to characterize microbial communities. RNASeq libraries will be prepared for each individual sample using the NEBNext Ultra II Directional RNA Library Prep kit. Data will be represented in ordination plots using the function ENVFIT (Vegan). Distance-based redundancy analysis will be conducted using the ADONIS function (Vegan) to determine main environmental drivers for abundance and diversity of taxa.Obj 2) Four replicated AP systems will be used, each consisting of one 415-L fish tank, one 190-L clarifier, one 115-L mineralization tank, two 454-L hydroponic troughs, and a sump. Systems are deep-water culture design using floating rafts (2.7-m2 of raft space per system). Nile tilapia will be stocked into systems to achieve a final tank harvest density of 6 kg, corresponding to a feed input rate of 210 g of 32% protein feed day-1. Thirty-two bell pepper plants will be stocked in each system (16 per trough). Bell peppers were selected as they grow well in aquaponic systems, have high yield varieties, require moderate amounts of P, and are desired by consumers. Seedlings will be germinated in rockwool cubes in a recirculating system using aquaponic system water. Water quality parameters will be monitored. Temperature, dissolved oxygen, pH, and electrical conductivity will be monitored daily. Total ammonia nitrogen (TAN), nitrite (NO2-N), nitrate (NO3-N), alkalinity, total iron, total phosphorus, and orthophosphate will be monitored twice weekly. Four plants will be randomly harvested from each system at four life stages seedling (1-day post-transplant [PT]), vegetative (25 days PT), flowering (40 days PT), and first harvest (70 days PT).Water samples will be collected pre-transplant and at each sampling period. Root and water samples (both from system and directly from plant rhizosphere) will be collected during sampling. At sampling for transplant, seedling, and vegetative stages, plants will be cut above the cube (leaving roots intact and undisturbed). Shoot weight, number of leaves, chlorophyll content, and leaf surface area will be recorded. Dry weight of leaves will be recorded and analyzed for macro- and micro-nutrient composition. Root samples will be collected aseptically, placed in a sterile bag, and stored for genomic analysis. Additionally, number of flowers/fruits and total fruit weight will be recorded for the mature stages. Upon completion of the study, fish will be harvested and evaluated for total tank weight gain (g), average daily gain (g), specific growth rate (g day-1), and feed conversion ratio. Plants will be documented photographically during development to obtain canopy area. This information can be used to compare bacterial communities, nutrient availability, and water quality parameters. Fish skin and gut samples will be preserved for future analysis of their microbiomes. The influence of fish on plant rhizosphere microbiome assembly can be analyzed and may provide future funding opportunities in Animal Microbiomes.Obj 3) Change in phytase and phosphatase activity will be evaluated from biofilms in-vitro using aquaponic water. Biofilm formation will be determined using the CBR method (four used). Three reactors will be used as treatment (change in condition, pH, or temperature) and one bioreactor will be used as the control (standard conditions for AP). CBR reservoir tanks containing peptone-amended aquaponic source water will be circulated through each bioreactor to allow adequate biofilm formation on each coupon. Addition of peptone to aquaponic water will be used for enrichment of bacterial organisms to maintain suitable growth parameters while biofilms are established. After 72 hours, amended AP water will be replaced with unamended source water. Water parameters will be adjusted and CBRs will run under continuous flow condition. Environmental parameters (pH and temperature) will be run as separate experiments, followed by a trial implementing a combination of pH and temperature. Each experiment will last for six days with sampling on day 0, 2, 4, and 6. Experiments will be repeated to compare variation between runs. One-way ANOVA will be used to determine variation of P-solubilizing bacteria between treatments (P<0.05). DNA and RNA will be extracted from the biofilm using DNeasy PowerBiofilm Kit and RNeasy PowerBiofilm Kit (Qiagen), respectively. Genes responsible for organic P transformation will be quantified using MT, following procedures from Obj 2, and will be compared to publicly available datasets to determine levels of overlap with P-cycling and regulation. The expression of microbial derived phosphatase and phytase will be quantified using MT. Procedures will follow those outlined in Obj 1 and 2.Obj 4) Replicated AP systems and stocking procedures will be the same as described in Obj 2. Three systems will serve as controls and will be operated under standard AP conditions (pH 6.8-7.0; temp 25°C). Three systems will be operated according to optimized pH and temperature identified in Obj 3. Tilapia and bell pepper plants, 16 plants per trough (32 per system), will be used. Four plants from each system will serve as representative samples. Plant height for each representative plant will be monitored weekly. Water quality parameters will be monitored throughout the growing period. Temperature, dissolved oxygen, pH, and electrical conductivity will be monitored daily. Total ammonia nitrogen (TAN), nitrite (NO2-N), nitrate (NO3-N), alkalinity, total iron, total phosphorus, and orthophosphate will be monitored twice weekly. Water samples will be collected from the plant rhizosphere weekly and sent for full nutrient analysis.At harvest (~ 60 days), water samples will be collected from the plant rhizosphere and submitted for full nutrient analysis. Fish and plant phenotypic data will be collected, stored, and processed as in Obj 2.Statistical analysis - A two-sample t-test will be used to compare means of fish and plant data between the two treatments. Within treatment differences will be enumerated using repeated measures ANOVA. Statistical analysis will be conducted using SPSS 26.0. Genomic Analysis - A MGS and MT approach as described above in Obj 2 will be implemented to investigate how the putatively optimal conditions for P cycling affect microbial taxa abundance, as well as the abundance and expression of genes involved in microbial metabolic pathways related to P cycling. For this, after general gene abundance/expression analysis, statistical analysis will be focused comparing gene expression levels between the two experimental conditions of genes involved in metabolic pathways related to P solubilization. Genes will be identified using their KEGG Orthology (KO) terms.Taxonomical and functional data will then be imported to DeSeq Bioconductor using the Project Narrative R. Data will be normalized to library size. Differentially expressed transcripts and significantly shifted taxa abundances will be obtained using DeSeq assuming a binomial distribution model.Significant differences in gene expression or taxa abundance will be granted if p < 0.05 and if multiple testing correction of FDR < 5%.Microbial characterization - Isolation and characterization of P-solubilizing microorganisms will follow procedures in Obj 2 and 3.