2.2 Detecting antimicrobial resistance in the environment
You may have heard the term One Health before. The One Health approach recognises that the health of humans, animals, plants, and the environment are deeply interconnected, and must be addressed together rather than in isolation. Many of the most pressing global health challenges, including food security and emerging infections, arise at the interfaces between these systems.
Another global health challenge is the threat posed by antimicrobial resistance (AMR), when bacteria and other microorganisms evolve the ability to survive treatment with antibiotics and antimicrobial drugs, making infections harder or impossible to treat.
While AMR is often discussed as a clinical or hospital‑based problem, it is in fact a system‑wide issue. Antimicrobials are used not only in human medicine but also in livestock production, aquaculture, plant agriculture, and consumer products. Resistant bacteria and their antimicrobial resistance genes (ARGs) can then move between humans, animals, food, water, soil, and wildlife through direct contact, waste streams, and environmental pollution. ARGs can also be exchanged between bacteria.
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Why do you think metagenomics can be of great help in monitoring AMR in a One Health context?
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Metagenomics allows the detection and characterisation of antimicrobial resistance genes across humans, animals, food, and environmental samples without the need for culturing. This makes it possible to capture the full diversity of ARGs and microbial reservoirs.
Activity 2
Below you will find the abstract of a peer-reviewed research paper on AMR and metagenomics (Kilonzo-Nthenge et al 2024). Read it through and then answer the questions.
Extract
Agricultural practices significantly influence microbial diversity and the distribution of virulence and antimicrobial resistance (AMR) genes, with implications for ecosystem health and food safety.
This study used metagenomic sequencing to analyse 60 samples (30 per state) including water, soil, and manure (10 each) from Alabama (a mix of cattle and poultry sources) and Tennessee (primarily from cattle).
The results highlighted a rich microbial diversity, predominantly comprising Bacteria (67%) and Viruses (33%), with a total of over 1,950 microbial species identified.
The dominant bacterial phyla were Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes, and Bacteroidetes, with the viral communities primarily represented by Phixviricota and Uroviricota. Distinct state-specific microbial profiles were evident, with Alabama demonstrating a higher prevalence of viral populations and unique bacterial phyla compared to Tennessee.
The influence of environmental and agricultural practices was reflected in the microbial compositions: soil samples were notably rich in Actinobacteria, water samples were dominated by Proteobacteria and Cyanobacteria, and manure samples from Alabama showed a predominance of Actinobacteria.
Further analyses, including diversity assessment and enterotype clustering, revealed complex microbial structures. Tennessee showed higher microbial diversity and phylogenetic complexity across most sample types compared to Alabama, with poultry-related samples displaying distinct diversity trends.
Principal Coordinate Analysis (PCoA) highlighted notable state-specific variations, particularly in manure samples. Differential abundance analysis demonstrated elevated levels of Deinococcus and Ligilactobacillus in Alabama, indicating regional effects on microbial distributions. The virulome analysis revealed a significant presence of virulence genes in samples from Alabama.
The community resistome was extensive, encompassing 109 AMR genes across 18 antibiotic classes, with manure samples displaying considerable diversity.
Ecological analysis of the interactions between AMR gene subtypes and microbial taxa revealed a sophisticated network, often facilitated by bacteriophages. These findings underscore the critical role of agricultural practices in shaping microbial diversity and resistance patterns, highlighting the need for targeted AMR mitigation strategies in agricultural ecosystems to protect both public health and environmental integrity.
Question 1
Why did the authors include water, soil, and manure samples in their analysis, rather than focusing on only one sample type?
Answer
Including water, soil, and manure captures different environmental compartments influenced by agriculture, allowing the study to assess how microbes and AMR genes move across interconnected ecosystems.
Question 2
Based on the abstract, calculate the number of soil, manure, and water samples collected in the study across both states. Was the number of samples balanced? Why do you think it is important?
Answer
The study analysed 60 samples in total, consisting of 10 soil, 10 water, and 10 manure samples per state. Since two states were included, this results in 20 samples per type (soil = 20, water = 20, manure = 20). The number of samples was balanced. This is important because it ensures that differences in microbial diversity or AMR patterns reflect real biological or environmental variation, rather than being driven by unequal sampling across environments or regions.
Question 3
Besides bacteria, which other organisms were detected in the samples? Was there any difference in their occurrence between Alabama and Tennessee?
Answer
Viruses were also detected in the samples. Samples from Alabama showed a higher occurrence of viruses compared to samples from Tennessee.
Question 4
The authors use the term resistome in the abstract. Thinking about the metagenome which you encountered in the first section, what do you think resistome means?
Answer
The resistome is the complete collection of all antimicrobial resistance genes present in a microbial community or sample (as the metagenome is the collection of all genetic material in a sample).
Question 5
Why are manure samples particularly important for understanding AMR patterns in this study?
Answer
Manure samples showed the greatest diversity of AMR genes across multiple antibiotic classes, highlighting manure as a key reservoir and potential dissemination point for resistance genes within agricultural systems and into the wider environment.
OpenLearn - The metagenomics revolution: an introduction
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