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Wastewater Surveillance: A New Front in Fighting Antibiotic Resistance

Analyzing sewage offers insights into public health and antibiotic resistance trends.

Connor L. Brown, Monjura Afrin Rumi, Lauren McDaniel, Ayella Maile-Moskowitz, Justin Sein, Loc Nguyen, Minyoung Choi, Fadi Hindi, James Mullet, Muhit Emon, Nazifa Ahmad Moumi, Matthew F. Blair, Benjamin C. Davis, Jayashmina Rao, Anthony Baffoe-Bonnie, Peter Vikesland, Amy Pruden, Liqing Zhang

― 6 min read


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Table of Contents

Wastewater-based Surveillance (WBS) is an approach that looks at the chemical and biological material found in sewage to gather information about public health, especially regarding Antibiotic Resistance. This method collects samples from wastewater treatment plants (WWTPs) to identify various pathogens and understand how antibiotics are being used in communities. This is particularly useful because traditional clinical testing might miss some of the bigger trends happening at the community level.

What is Antibiotic Resistance?

Antibiotic resistance (AR) occurs when bacteria change in response to the use of medications designed to kill them. This can make infections harder to treat, leading to longer hospital stays, higher medical costs, and an increased risk of death. Think of it like bacteria putting on a superhero cape to dodge the medicine that's trying to take them down.

Why is WBS Important for AR?

WBS can provide a wealth of information about the levels of antibiotic-resistant bacteria in a community without relying solely on clinical data. This method allows for a broader view, capturing a range of health information that might be lost in individual patient testing. It's like getting a group photo instead of just a selfie. By analyzing wastewater, scientists can identify trends over time and spot outbreaks of resistant bacteria before they become widespread.

Challenges in WBS

Though WBS shows promise, it's not without challenges. For one, antibiotic-resistant pathogens (ARPs) are numerous and vary greatly in their characteristics. Some grow better in certain conditions than others, making it tricky to get a clear picture. Additionally, the human microbes in wastewater are just a tiny part of the larger mix of many different kinds of microbes found in sewage. It's like trying to find a few lost socks in a giant laundry basket full of clothes.

The Complexity of Wastewater

Municipal sewage is a messy cocktail of microbes, including those from human waste and other sources, such as rainwater and Biofilms forming in the sewer pipes. The microbiome-essentially the community of microbes-found in wastewater is quite complex and can change depending on the time of year. This seasonal variation can influence the resistance genes present in the water, making it difficult to determine accurate AR levels.

The Role of Antibiotic Use

Interestingly, the correlation between antibiotic use and the development of resistance isn’t straightforward. While it would make sense that increased antibiotic prescriptions would lead to more resistant bacteria, studies show that the relationship is often weak. This could be due to other factors, such as the transportation of resistant microbes into the community from outside sources, rather than just local antibiotic use.

Seasonal Antibiotic Prescribing Patterns

Antibiotic usage can fluctuate, with seasonal patterns often influenced by factors like viral infections that increase during certain times of the year. For example, when a flu season hits, doctors might prescribe more antibiotics for related infections, which can temporarily boost the presence of resistant bacteria in sewage. Researchers have found that certain antibiotics are more frequently prescribed in the winter months, while others peak in the spring and summer.

Examining Wastewater Samples

Research teams collect samples from sewage several times a week over extended periods. They analyze these samples using advanced sequencing techniques to identify the types of bacteria and resistance genes present. The goal is to connect antibiotic prescribing data with the levels of resistance found in sewage.

Findings on Antibiotic Resistance Genes

In the analysis of wastewater samples, researchers found that specific genes linked to antibiotic resistance indeed corresponded to the antibiotic prescriptions issued in the community. However, the timing matters-there seemed to be a lag between increased antibiotic use and the observable rise in resistance genes in sewage.

Understanding Microbial Dynamics

The microbial community present in the sewage is constantly changing, influenced by many factors such as environmental conditions and human activity. This means that the relationship between antibiotic use and resistance can vary widely, not just between different antibiotics, but also due to different bacterial hosts.

The Influence of Different Bacterial Families

When looking at bacteria in sewage, researchers noted a significant distinction between two main families: Enterobacteriaceae and Pseudomonadaceae. The resistance genes associated with Enterobacteriaceae tended to respond more quickly to antibiotic use, whereas those associated with Pseudomonadaceae showed a delayed response. This suggests that some bacteria are more reactive to antibiotic pressure than others.

The Role of Biofilms

Biofilms, which are colonies of bacteria that cling to surfaces, can complicate the dynamics of antibiotic resistance. They can serve as a reservoir, housing resistant bacteria and genes, and releasing them into the wastewater stream. Think of biofilms as a speakeasy for bacteria-hidden from the outside world until conditions are right for them to spread.

Seasonal Trends in Bacterial Populations

Research showed that the population of certain bacteria in sewage is not static. It changes with the seasons, affecting the prevalence of resistant strains. By examining how these populations shift, researchers can gain insights into how well specific antibiotics are working and what resistance might be on the rise.

Linking Antibiotic Use and Resistance

By meticulously analyzing the correspondence between antibiotic prescriptions and resistance genes in sewage, researchers found noteworthy associations. For example, certain antibiotics showed a strong correlation with specific resistance genes, reinforcing the idea that community antibiotic use does impact what happens in the local sewage system.

Implications for Public Health

Understanding the dynamics of antibiotic resistance in sewage can have significant implications for public health. By tracking these trends, healthcare officials can better anticipate outbreaks and develop strategies to combat resistance before it becomes a larger issue. WBS can serve as an early warning system, giving communities a chance to address these threats head-on.

Future Directions for Research

While there is much to learn from wastewater surveillance regarding antibiotic resistance, more research is needed. Future studies will aim to understand the complexities of microbial interactions in sewage, the stability of antibiotics in different environments, and more about how resistance develops. As technology improves, so too will the precision of our analyses.

Conclusion

Wastewater-based surveillance provides a unique window into the health of communities and the rising threat of antibiotic resistance. Though challenges remain, the insights gained can guide efforts to tackle resistance effectively. With continued research and the right strategies, we can turn the tide against antibiotic resistance, ensuring that antibiotics remain effective tools in the fight against infections. And who knows, maybe one day we’ll figure out how to get those pesky bacteria to give up their superhero capes for good.

Original Source

Title: Metagenomics disentangles epidemiological and microbial ecological associations between community antibiotic use and antibiotic resistance indicators measured in sewage

Abstract: Wastewater-based surveillance (WBS) is proving to be a valuable source of information regarding pathogens circulating in the community, but complex microbial ecological processes that underlie antibiotic resistance (AR) complicate the prospect of extending WBS for AR monitoring. The epidemiological significance of observed relative abundances of antibiotic resistance genes (ARGs) in sewage is unclear, in part due to multiple sources and in-sewer processes that shape the ARG signal at the entry to the wastewater treatment plant (WWTP). Differentiating between human-derived signals of resistance and those associated with downstream physical and ecological processes could help amplify public health value of WBS of AR by removing noise. In particular, autochthonous sewage microbiota--microbes stably associated with sewage collection networks independent of human/fecal input--could influence profiles of antibiotic resistance via seasonality, temperature, or other factors that alter human community-level AR signals at a given time point. Here we address this fundamental challenge by differentiating distinct associations between sewage-borne antibiotic resistant bacteria and outpatient antibiotic use in the community served by the sewershed. This was made possible using a unique dataset of outpatient antibiotic prescription rates encompassing the majority of antibiotic use over a 5-year period. Leveraging a yearlong 2x weekly sampling of a conventional WWTP with deep metagenomic sequencing (average 29 Gbp/sample) and extensive bioinformatics analysis, we identify striking associations between sewage-borne ARGs and antibiotic usage depending on the putative bacterial host and the presumed environmental stability of the antibiotic. It was found that a subset of ARGs, predominantly associated with Enterobacteriaceae, displayed a direct correlation with antibiotic usage, while ARGs predominantly associated with Pseudomonadaceae displayed a lagged relationship with antibiotic usage (between 1-3 months). Nested statistical modeling was applied to model the relationship between Pseudomonas metagenome assembled genomes and lagged sulfamethoxazole/trimethoprim use while jointly considering sewage characteristics and seasonality. This effort demonstrates the utility of WBS for understanding epidemiological dimensions of AR and provides a framework for accomplishing this purpose by considering microbial ecological factors that contribute to the corresponding signals in sewage.

Authors: Connor L. Brown, Monjura Afrin Rumi, Lauren McDaniel, Ayella Maile-Moskowitz, Justin Sein, Loc Nguyen, Minyoung Choi, Fadi Hindi, James Mullet, Muhit Emon, Nazifa Ahmad Moumi, Matthew F. Blair, Benjamin C. Davis, Jayashmina Rao, Anthony Baffoe-Bonnie, Peter Vikesland, Amy Pruden, Liqing Zhang

Last Update: Dec 12, 2024

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2024.12.11.24318846

Source PDF: https://www.medrxiv.org/content/10.1101/2024.12.11.24318846.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to medrxiv for use of its open access interoperability.

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