Emily Crossette received a $10,000 mini-grant for her project:
Probing microbial diversity and dynamics of land applied manure
Co-advisors: Melissa Duhaime, Lut Raskin, Indika Rajapakse, Krista Wigginton
Introduction
Manure application is an important resource recovery pathways that returns nutrients and organic carbon to soil to improve crop yields and limit the need for carbon-intensive synthesized nutrients. However, biosolids and manure are sources of antimicrobial resistance genes and antimicrobial resistant bacteria [1]–[3] which can present risks through aerosolization of manure-borne bacteria and viruses during spreading [4], water contamination through run-off [5], and food contamination [6] (Figure 1). Land application of manure and municipal biosolids have enriched soil for antimicrobial resistance [7]–[9], another diverse reservoir antimicrobial resistance organisms [10], [11]. The biological treatment processes, such as anaerobic digestion, may provide opportunities for the evolution and cross-bacteria sharing of ARG through horizontal gene transfer [12]–[15]. To ultimately model risk and learn to control antimicrobial resistance gene composition in microbial communities improved quantitative ARG screening tools, cross-sectional studies to probe drivers of microbial ecology of land-applied wastes, and novel mathematical modeling frameworks are needed.
Figure 1: Microbial pollutants released from land application of manure and biosolids have several human exposure routes.
Research Objectives
1. Use a quantitative, high-throughput sequencing approach to characterize the dairy manure resistome.
A high-throughput, quantitative screen of ARGs is a critical step to better predicting the risk of ARG release into the environment from engineered treatment systems. Metagenomic sequencing is a powerful tool to study the genetic potential of microbial communities and is becoming increasingly popular in ARG research. Typically, unassembled or assembled sequence reads are aligned to ARG databases and the number of reads are normalized by total number of reads or reads mapping to 16S databases in order to determine the relative abundance of ARGs [16], [17]. However, relative abundance cannot be used to determine the removal or propagation of ARGs as differences in relative abundance between samples do not imply differences in absolute abundance.
While qPCR provides absolute quantification of gene targets, primer biases and non-specific amplification can prevent accurate quantification [18] and qPCR can only detect targeted genes. These limitations hinder our ability to understand the dynamics of microorganism and gene concentrations between samples and studies. For example, if a wastewater treatment plant is concerned if residual antibiotics are selecting for tetracycline resistance, they would need to quantify over 50 gene targets that confer resistance to tetracycline [19]. A quantitative metagenomic sequencing method will provide a high-throughput tool to evaluate the absolute abundance and fate of a suite of ARGs in environmental reservoirs.
2. Evaluate how anaerobic digestion shapes the lagoon microbiome.
This pilot-scale, cross-sectional study aims to identify the farm or manure management practices that shape the lagoon microbial communities before land application. Understanding the major factors that shape the microbial ecology of land applied manure is critical for designing waste management best practices that mitigate risks associated with antimicrobial resistance. Anaerobic digestion is a biological process employed by some farms to reduce pathogens and generate biogas, and reduce some antimicrobial resistance genes in manure [16], [20], [21]. However, anaerobic digestion is not the final treatment barrier on most farms. After digestion, manure is stored for several months before applied to fields. The microbial ecology and biological processes that shape the ecology in land applied manure during storage is not well-studied.
I hypothesize that the microbial community drives the resistomes in land applied manure. This community is likely driven by a combination of climate, lagoon size, and prior treatment steps including anaerobic digestion. DNA extracted from lagoon samples collected during drawdown events from farms in New York, Maryland, Pennsylvania, and Michigan will be sequenced with internal standard DNA. Dirichlet Mixture models will be used to generate “community” and “Resistome” types which will be correlated with other categorical variables including herd size and use of anaerobic digestion (Figure 2). Results from this objective will better define the variability in microbial composition of land applied manure and will determine if the profiles of antimicrobial resistance genes are shaped by the microbial ecology during lagoon stabilization.
Figure 2: Study design of dairy cross-sectional study to evaluate the role of digestion and storage on microbial community and resistome structure
3. Develop a mathematical framework for modeling horizontal gene transfer
With a mathematical model of the features that drive microbial community robustness and stability, we can exert control on the systems to, for instance, improve efficiency and value of anaerobic digestions products or deliver personalized medicine through human microbiome interventions. The aim of this research is to propose a mathematical framework to describe microbial stability in response to disturbances. I hypothesize that horizontal gene transfer is a feature of microbial communities that contributes to resiliency and robustness. To develop this model, I will build off the work of Juhász et al. [22] to demonstrate through multilinear time invariant systems theory how microbial communities are stabilized in dynamic environments. To build the model, I will first establish a mathematical definition of horizontal gene transfer. Then, using MATLAB, I will simulate microbial communities and test the resiliency of communities when challenged with stresses or dynamic environmental conditions. Ultimately, the goal of this modeling effort is to provide a mathematical basis for horizontal gene transfer that can evaluate when microbial communities are most susceptible to HGT and how to intervene and control horizontal gene transfer.
References
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[21] Y. Ma et al., “Effect of various sludge digestion conditions on sulfonamide, macrolide, and tetracycline resistance genes and class i integrons,” Environ. Sci. Technol., vol. 45, no. 18, pp. 7855–7861, 2011.
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