Analysis of wastewater has the potential to alert authorities to thousands of health threats at once, from antimicrobial resistance to cholera, according to new research from several European universities.
Led by the National Food Institute DTU, researchers from 11 European universities, institutions and knowledge organizations developed a new method for analyzing data from wastewater monitoring. The method can help determine whether disease-causing bacteria, viruses, and antimicrobial resistance originate in humans, animals, industry, or the environment. Potentially, thousands of threats can be detected simultaneously, including antimicrobial resistance and cholera bacteria, which could help prevent outbreaks from escalating into epidemics. The research was published in the prestigious scientific journal Nature Communications.
The researchers analyzed samples collected over three years from seven wastewater treatment plants in five major European cities: Bologna, Budapest, Copenhagen, Rome and Rotterdam.
Untreated wastewater is increasingly becoming a vital source for the anonymous surveillance of health and disease in large urban populations. However, extracting valuable data from it is not straightforward, as wastewater contains both known and unknown bacteria from various sources, such as humans, plants, animals, rainwater, dishwashing, etc.”
Patrick Munk, corresponding author of the research paper, Assistant Professor from the National Food Institute DTU
In addition, the content of wastewater can vary due to seasonal temperature changes.
Researchers are beginning to overcome these challenges using a new computer program.
“Our research shows significant potential in metagenomics-based wastewater monitoring. Although this method is more accurate than PCR testing, which proved highly effective during the COVID-19 pandemic, PCR tests only one threat the Metagenomics-based wastewater monitoring can assess thousands of threats at once.In addition, the value of each individual sample increases as more samples are collected over time, as historical data is amplified. the value of the new analyses,” says Professor Frank Aarestrup, who leads the Genetic Epidemiology Research Group at the DTU National Food Institute and co-author of the paper.
A monitoring system could be envisioned that combines metagenomics-based wastewater surveillance with PCR testing for specific threats that authorities deem likely to arise.
The study is particularly important because an EU directive requires all major European cities to start monitoring antimicrobial resistance in wastewater. In Denmark, the Statens Serum Institut is leading a large European collaboration to implement this wastewater monitoring.
The software organizes huge data sets into mysterious groups
Over a period of three years, from January 2019 to November 2021, 278 sewage samples were taken from the inlet of the seven sewage plants and sent to the DTU. The researchers then analyzed billions of DNA sequences from the samples, assembling them into genomes from thousands of bacterial species, 1,334 of which were previously unknown.
Data were analyzed using software developed by the Italian project partner at the University of Bologna. This program identifies species that behave similarly over time and groups them together.
“In the analyses, we could see that the bacteria in the wastewater clustered into very distinct clusters. We began to wonder why and how the clusters formed. At first, we thought the clusters might represent microbes cooperating with each other, but that was a dead end. Then, we investigated whether some of the clusters might be made up of bacteria from human faeces, and that’s when we hit the mark,” says Patrick Munk.
Other groups turned out to be bacteria from the environment, and one group present in treatment plants all over the country probably comes from biofilms growing in the pipes leading to the facilities.
Once the researchers identified some of the groups using the analysis software, the task became easier.
“The principle is very simple – some bacteria always come from humans, and the bacteria sequenced in the analysis probably also come from humans. In this way, we can identify groups of species that follow each other over time. time,” he says. Patrick Munk.
The new method significantly improves the success rate
Researchers have analyzed metagenomes in the past but not as efficiently as with the new method.
“In this new study, we identified 1,334 previously unknown bacterial species in wastewater. Typically, when we analyzed a metagenome consisting of 100 million small pieces of DNA, we could only identify the origin of about 10% of the DNA. However, in this new study, we’ve increased it to almost 70% of the DNA assigned to the species from which we recovered a genome,” says Patrick Munk.
The ability to detect new bacteria is essential, as these bacteria may carry previously unknown antimicrobial resistance genes, and this method could potentially reveal new sources of antimicrobial resistance.
This is an observational study where the researchers worked with data based on the bacteria present in the untreated sewage samples, but did not themselves adjust for any variables that may affect the frequency of specific bacteria. This introduces some uncertainty, and although many bacteria associated with humans cluster, this is not always the case. The next step is to create a synthetic data set where researchers know which bacterial species are present and actively change the conditions to observe the effects.
“We don’t have a final success rate for this method yet, but it’s clear that we’re on to something important. We need to further optimize the method to improve its accuracy,” says Patrick Munk.
DATA:
What is the metagenome?
All living organisms have genetic material (genome) consisting of DNA. Sewage and other samples contain many different types of microbes, including bacteria and viruses. When you extract the mixed DNA from these species, you don’t just have a genome, but a metagenome. If the genome of any species is like a puzzle, then the metagenome is like a whole bunch of mixed puzzles. Metagenomics can answer questions about which organisms were present and how common they were, making them a valuable tool for tracking disease-causing bacteria and the genes that make them resistant to antibiotics. Millions of DNA fragments are read from each sample, and many samples can be analyzed by a supercomputer.
Cholera in Copenhagen
Hidden inside the pipes leading to the Avedøre wastewater treatment plant are some bacteria that researchers didn’t expect to find: cholera bacteria. Although the amounts were very small, it was a big surprise for the researchers as they investigated the bacteria in wastewater treatment plants in five major European cities, including the three major plants in Copenhagen: Avedøre Wastewater Treatment Plant, Lynetten Wastewater Treatment Plant and Damhusåen. Wastewater Treatment Plant.
One can imagine that the bacteria was brought to the area of Avedøre’s facility by a person from a part of the world where cholera still infects people. This person had the bacteria in his body and offered feces to the sewage system, after which the bacteria settled in the pipes near the treatment plant and began to reproduce there. The researchers observed that the bacteria remained close to the facility week after week, but could not be found further upstream. Therefore, they suggest that the bacteria are not constantly coming from people who are currently sick but are in the biofilm of the pipes. No cases of cholera have been recorded in Denmark for 150 years and the bacteria has not spread in the environment. However, warmer temperatures could affect the geographic spread of cholera and other potentially dangerous germs.
The new study method can trace where certain bacteria come from, and although the DNA of the bacteria in the three Copenhagen plants is almost identical, there are still small differences that give each plant its own unique signature.
The presence of cholera bacteria near the Avedøre facility is described in a separate scientific article, also derived from this research, published in the journal Microbial Ecology.
