Investigations

Tracking Coastal Antibiotic-Resistance: A Sampling Approach from Italy
Arrone River, Italy
Case Studies Italy

If we’re to understand what causes coastal pathogens to thrive, we need to use sampling methods we can trust. Surface water sampling is an essential part of the study of waterborne pathogens, but it’s all-too easy to get misleading results from this complex and delicate procedure.

Stefania Marcheggiani and a team of researchers from Istituto Superiore di Sanità (ISS) have developed a new sampling method to study antibiotic-resistant pathogens in the Arrone River in central Italy. This is based on plastic polymers commonly found as waste in aquatic ecosystems

The Arrone River flows for 35 km from Lake Bracciano (a potable water reservoir) to the Tyrrhenian Sea. Its agricultural setting puts it at risk from run-off pollution, and there are two wastewater treatment plants on the river. The Arrone is also suffering from water scarcity, which affects pathogen concentration. With this combination of factors, it’s the ideal test site for the ISS team to evaluate surface water sampling methods.

Research highlights

  1. Accurate surface water sampling is essential if we’re to establish what’s in the water and what the potential risks to human and animal health might be.
  2. With features including a potable water reservoir, wastewater treatment plants, and an agricultural landscape, the Arrone River is the perfect place for research.
  3. The ISS team developed an Artificial Plastic Substrates (APSs) sampling tool, based on common plastic contaminants such as plastic polymers.

Why is this so important?

Antimicrobial resistance (AMR) represents a crucial prevention challenge within the One Health approach. Common human infections, once easily treatable with antibiotics, are becoming dangerous again.

How did this problem arise? Bacteria can rapidly develop resistance upon exposure to drugs like antibiotics. Antibiotics shouldn’t be used to prevent or treat viral infections, as they are ineffective against viruses unless bacterial infections are also present. Excessive and/or inappropriate use of antibiotics in human and veterinary medicine as well as in agriculture, favoured the emergence and spread of drug-resistant bacterial strains.

Antibiotics can enter aquatic ecosystems through wastewater, manure and agricultural run-off. To mitigate this risk, a better understanding of the environment’s role in antibiotic-resistant pathogens is needed. In addition to identifying aquatic “hotspots,” researchers developed risk models related to climate change (including rising water temperatures), increased salinity and water scarcity.

Because these pathogens are often present at low numbers in aquatic ecosystems, they are difficult to detect accurately, especially since most sampling procedures require large volumes of water. The primary challenge of the ISS study was to develop a sampling tool capable of detecting pathogens and their antibiotic resistance genes (ARGs) in transitional waters without compromising water volume.

How did we do the research?

The ISS team developed an Artificial Plastic Substrates (APSs) sampling tool based on plastic polymers commonly found as plastic contamination in surface water, such as Polystyrene (PS), Polyethene Terephthalate (PET) and Polyvinyl Chloride (PVC). The size and shape of each plastic polymer were standardised to ensure the bacteria were exposed to the same area for colonisation.

The sampling tool has two main parts: one is mobile for bacterial sampling, and the other is anchored at the sampling points. The team chose three river sites popular with recreational users and bathers.

During the monthly sampling campaign of the 2023 bathing season, APS samples were collected at each sampling site alongside raw water (RW) samples. The team also measured conductivity, salinity, temperature and pH with a probe.

The APSs were left in position for a month at a time, submerged at a depth of around 50 cm. When the month was up, the APSs were transported to the lab where the samples were analysed.

Results

Results and new publications coming soon.

Share this research