Performing Department
(N/A)
Non Technical Summary
Understanding microbiome structure in agrifood systems is critical in harnessing this vital ecosystem to promote crop growth and climate resilience while mitigating plant and zoonotic pathogens and diseases. Ubiquitous applications of nanomaterials (NMs) raise concerns about their impacts on microbiome structure and pathogen persistence in soil and irrigation water. In this proposal, we will attempt to address this critical knowledge gap using a state-of-the-art multi omics and machine learning (ML) platform. Twenty types of monodisperse NMs will be synthesized and characterized. We will investigate how NMs alter microbiome structure in soil and water by Nanopore 16s and 18s rRNA sequencing. Additional studies will focus on the NMs causing the most significant changes in pathogen persistence. Mechanism of NMs-induced pathogen evolution and adaption will be revealed using multi-omics and ML, involving Nanopore whole genome sequencing (WGS), whole transcriptome sequencing (WTS), and metabolomics. All experiments will include climate simulation to examine whether climate change aggravates NMs' risks and implications in agrifood systems. The outcome and significance of the study are multifaceted. Revealing detrimental effects would demand responsible innovation in agrifood nanotechnology, which may require better practices, policies, or end-of-life treatment and risk mitigation. Beneficial evidence, however, would validate nanotechnology as the promising leverage to harness the microbiome for food safety and security with climate resilience.
Animal Health Component
40%
Research Effort Categories
Basic
40%
Applied
40%
Developmental
20%
Goals / Objectives
The proposal will address the following priorities in the program of Nanotechnology for Agricultural and Food Systems (A1511): 1) Environmental, health, and safety assessments of engineered nanoparticles used in food and agricultural systems, including detection and quantification of engineered nanoparticles, characterization of hazards, exposure levels, transport, and the fate of the engineered nanoparticles or nanomaterials in foods, crops, soils (and soil biota), water, and livestock (including aquaculture species), or to agricultural and allied industry workers. This may also include animal feed formulations and processes that utilize novel nanomaterials or develop new nanostructured materials or nanoparticles that are bio-persistent in digestive pathways. 2) Discovery and characterization of nanoscale phenomena, processes, and structures relevant and important to agriculture and food. Although agrifood nanomaterials' (NMs) cytotoxicity and pathophysiology on eukaryotic cells, especially mammalian cells, are generally well characterized and studied, very little is known about NMs' impact on prokaryotic evolution and adaptation and microbiome composition, especially in agrifood environments. Addressing this knowledge gap has profound implications for food security and food safety. In this proposal, we will attempt to address this critical knowledge gap using a state-of-the-art multi-omics and machine learning platform. There are three main goals and objectives: 1) Synthesis and characterizations of monodisperse NMs used in agrifood systems. 2) Impacts of NMs on microbiome structure in agrifood environments. 3) Multi-omics study on the mechanism of pathogen evolution and adaptation to NMs.
Project Methods
Obj. 1. Synthesis and characterizations of monodisperse NMs used in agrifood systems.The study will select at least 3 NMs for each of the four category that are commonly used or found in agrifood environments. The project team will consult the advisory board on the NMs selection based on the number of applications and popularity in the agrifood industry, commercial availability, project duration and budget. The proposal will investigate how these selected NMs impact microbiome structure and pathogen persistence (evolution and adaptation) in agrifood environments. This objective aims to prepare and evaluate discrete and well-defined nanoparticles with a polydispersity index (PdI) less than 0.1 (>90% monodisperse), except for soft polymeric NMs. All synthesized nanomaterials will be characterized with Critical Nanoscale Design Parameters (CNDPs) as in (a) size and PdI, (b) morphology, area fraction, and aspect ratio, (c) surface properties, valency, and composition (Tomalia, 2009). The environmental significance of each CNDP will be further analyzed using machine learning (ML) described in Obj. 2 and 3.Obj. 2. Impacts of NMs on microbiome structure in agrifood environments.Climate change and temperature simulations will be performed in climate-controlled facilities at Gainesville, Live Oak, or Lake Alfred, FL. Simulation experiments will focus on elevated temperature and CO2, as early evidence suggests both factors significantly alter the structure of the rhizosphere microbiome. The compositions of soil microbiota will be profiled using 16s rRNA sequencing, and the water microbiome will be characterized with 16s and 18s rRNA to include algae. The microbiome profile will be correlated to NMs characteristics and soil properties mentioned in Obj 1 and 2.1, using ML. The proposal will focus on the interaction between NMs and microbiome in soil and irrigation water, which are important matrices of NMs persistence and transmission as part of the NMs' life cycle.Obj. 3. Multi-omics study on the mechanism of pathogen evolution and adaptation to NMs.There are urgent demands to understand how foodborne pathogens persist in our agrifood system, including the role of NMs. The mechanisms appear complex and demand a holistic approach to investigating NMs' role. Therefore, this objective will study how NMs and climate change affect pathogen evolution using whole genome sequencing (WGS), whole transcriptome sequencing (WTS), and metabolomics to study pathogen horizontal gene transfer (HGT) and phenotypical plasticity in soil and irrigation water. ML will be performed to address the questions specific to this objective. i) Persistence. Role of NMs on pathogen transformation frequency, HGT, and polymorphisms in soil and irrigation water. NMs with detrimental effects will be identified as high risk. Equal efforts will be attempted to identify potential NMs that reduce pathogen persistence by mitigating selection pressure and slowing down evolution. ii) Climate Ramification. Whether NMs aggregate pathogen survival and virulence in the climate simulation.