Imagine you are taking a water sample from the nearby pond where ducks swim. Likely, this water contains genes that make bacteria impervious to the strongest antibiotics. The first UK study tracking antimicrobial resistance and influenza viruses in water bodies revealed concerning findings. Scientists from Bangor University examined water bodies in England and Wales throughout 2023–24 that are popular with people and birds, particularly migratory ones. Their aim is to discover resistant and non-invasive methods for monitoring threats that can pass from animals to humans.
The problem of antibiotic resistance and zoonotic diseases is a growing worldwide danger to the health of people and animals. Standard surveillance relies on analyzing sick or deceased animals, which demands many resources and is often belated. The team decided to get ahead of events by taking environmental water samples instead of capturing animals. They collected weekly samples at 19 sites—both inland and coastal—for 10 weeks, with collection lasting longer at four points.
For analysis, high-throughput quantitative PCR (HT-qPCR) was employed to find 74 antibiotic resistance genes (AMR), mobile genetic elements, and bacterial markers. Influenza viruses were sought using RT-qPCR, while also attempting to define their subtypes.
High-throughput quantitative PCR (HT-qPCR) is an advanced laboratory diagnostic technique that allows for simultaneously and accurately searching for and “counting” the presence of dozens or even hundreds of specific genetic material fragments (DNA or RNA) in a single specimen. Picture having a glass of murky pond water that might contain gene remnants from thousands of different microorganisms. HT-qPCR is like a very fast and clever scanner that checks this water not for one specific gene (like only colistin resistance), but for an entire “bouquet” of 74 different antibiotic resistance genes, viral genes, and other markers at once. Moreover, it doesn’t just say “present/absent” but estimates the quantity of found copies, which helps in grasping the scope of the phenomenon. This very technology enabled the large-scale environmental monitoring described in the paper.
To grasp the origin of microbial contamination, scientists utilized molecular markers:
CrAssphage—a bacteriophage specific to the human gut, so its genes serve as a marker for human feces.
Catellicoccus marimammalium—a bacterium inhabiting the guts of many wild birds (gulls, pigeons) and marine mammals, an ideal marker for “avian” pollution near the coast.
The analysis showed that avian markers were more frequently encountered in the water than human ones.
Antibiotic resistance genes were ubiquitous. The most common was the aadA7 gene, which renders bacteria insensitive to aminoglycosides. Increased amounts of multi-resistance genes were found in two locations, possibly due to wildlife rather than humans.
Unexpected was the high presence—in 92% of samples—of the mcr1 gene, which confers resistance to colistin, a last-resort antibiotic, states study author Dr. Kata Farkas.
The frequent detection of Shigella spp. bacterial DNA, despite the absence of other common bacteria like E. coli, was also surprising. This might suggest the limits of the method’s sensitivity.
Influenza A virus was found in 3.4% of samples, but its subtypes (like H5N1) could not be determined, likely due to low concentration. “Influenza virus RNA was detected even where outbreaks were not recorded, which might hint at sewage contamination,” Farkas notes.
The research confirmed that monitoring eDNA/RNA in the environment is a potent tool for early threat detection. It operates on the principles of the “One Health” concept, integrating ecological, veterinary, and medical surveillance. The method is cheaper and more scalable than traditional animal testing. It also allows for more precise identification of the source of fecal contamination—whether birds or humans—which current regulated monitoring cannot do.
Next steps involve broadening and extending observations to capture seasonal and regional trends. More sensitive techniques are needed to define influenza virus subtypes in low-concentration samples. The ultimate goal is to integrate environmental monitoring into national surveillance systems to better prepare for future disease outbreaks.
The real value of this work lies in its preventive and integrative nature. It proposes shifting epidemic surveillance from a “firefighting” mode (where we analyze already sick animals or people) to a constant “horizon scanning” mode. Instead of waiting for reports from veterinarians or doctors, we can regularly take water samples at key points—urban ponds, migratory bird gathering spots, sewage—and search for alarming genetic signals.
This is like an early warning system. We could detect the emergence of a dangerous resistance gene (like mcr-1) or a new influenza strain not when it has already caused an outbreak at a poultry farm or entered the human population, but when it is just beginning to circulate in the environment. This will provide precious time for preparation: stepping up lab checks, alerting medical and veterinary services, and analyzing transmission pathways. Furthermore, the method allows for precise determination of the contamination source—birds, humans, or livestock—which is critically important for adopting correct measures. In the long term, this could form the basis for creating a “weather forecast” for biological threats.
The main methodological concern lies in interpreting the DNA finding. Detecting an antibiotic resistance gene (like mcr-1) or a pathogen DNA fragment (Shigella spp.) in water using PCR does not equate to finding a live, active, and infectious bacterium or virus. It is more of a genetic trace. We do not know if these genes reside in dead bacteria, in freely floating DNA fragments, or indeed in living and potentially hazardous microorganisms. Thus, the study excellently captures “genetic noise” and signals a potential hazard, but cannot directly answer the question of immediate health danger for people who, for instance, drink this water. To connect genetic signals with a real threat, supplementary research is necessary, involving culturing microorganisms from the same samples and assessing their virulence. For now, we have a strong alarm signal, but without a precise understanding of how close the “fire” is.
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