Periodic Reporting for period 1 - NatureSToll (Nature Self-medication: Poisoning the microbes a Toll for wildlife)
Periodo di rendicontazione: 2022-04-01 al 2024-03-31
Global pharmaceutical consumption is rising with growing and ageing human population and more intensive food production. Recent studies have revealed pharmaceutical residues in aquatic ecosystems and organisms. Among pharmaceuticals, antibiotics, which are natural, synthetic or semi-synthetic compounds, able to kill and inhibit growth or metabolic activity of microorganism, are one of the most widely used categories. Environmental concentrations of antibiotics are often low, but their continuous discharge in the environment, exposes aquatic organisms during their entire life cycle. There is currently little data on the non-therapeutic effects of antibiotics. The microbiota represents the trillions of microorganisms inhabiting a host. Gut microbiota contributes to the development of an immune response, to metabolic processes and it influences the host behaviour. Gut microbiota is very plastic and recent insights have suggested that most diseases could be linked in some way to an alteration of the gut microbiota (i.e. a dysbiosis). However, no studies so far have investigated the impact of antibiotic residues on wildlife’s gut microbiota composition and its effect on disease occurrence. Top predators of aquatic ecosystems such as mustelids are exposed to high levels of pollutants and are considered as keystone sentinel species for the study of pollutant effects on wildlife. Mustelids are also a reservoir species to zoonotic disease, as they are exposed to diverse types of viruses that can be passed from and to domestic animals and humans. The aims of this research action are to 1) determine the ‘natural’ variation of gut microbiota composition according to biological factors, 2) investigate a threshold effect level for which pharmaceuticals could lead to health effects, 3) test if the individuals with high concentrations of pharmaceuticals are more likely to develop infectious diseases. I investigated these questions in the American mink Neovison vison.
Some instrument failure and methodological issues have significantly delayed the project and most results were only obtained within the four months prior the action end.
Listed below, are the preliminary results for each analyses performed.
Microbiomes: At the genus level, the gut microbiota composition was dominated by Clostridium> Romboutsia> Proteus> Ezakiella> Bacteroides> Paeniclostridium> Peptoniphilus> Vagococcus> Peptostreptococcus> Enterococcus> Tissierella> Anaerococcus. We characterised the health status of the minks by quantifying the following pathogenic bacteria, Enterococcus faecalis, Ralstonia pickettii, Salmonella enterica and Serratia spp. in four organs (kidney, spleen, lung, lymph node). Ralstonia pickettii was the most abundant pathogen and has been detected in the lymph node, kidney and spleen, while in lungs it was the second most abundant bacteria after Metamycoplasma orale. Further analyses will be performed to associate gut microbiota composition to the abundance of pathogens in the four organs analyzed.
Diet: Out of 15 samples (stomach content or feces) we were able to obtain prey DNA for only 7 individuals (we used COI gene metabarcoding) . DNA from the freshwater fish Phoxinus bigerri was detected in three individuals, we also detected DNA of micro-mammals (Crossidura russula, Rattus norvegicus), amphibians (Rana temporaria) and other freshwater fish species (Salmo trutta, Leuciscus burdigalensis, Acanthobrama persidid, Squalius cephalus, Gobio lozanoi).
Pollutants: In the 31 muscle samples, the antibiotic trimetoprime was only detected in three individuals and carbamazepine, a drug to prevent and control seizures, was detected in one individual. Yet in one blood sample used to validate the extraction method for metabolomic analyses, we were able to detect more pharmaceuticals. For instance, we were able to detect three synthetic hormones: altrenogest a synthetic progestin commonly used to synchronize estrus in livestock; norethisterone acetate a progestin which can be used in birth control pills, and methylprednisolone a medication used to reduce inflammation. In addition, we were also able to quantify other environmental pollutants in most whole blood samples such as polycyclic aromatic hydrocarbons and phtalates.
Fecal cortisol: Cortisol concentrations in fecal samples ranged from 3.45 to 168.5 pg/mg dw, in the sub-sample in which these values are available, cortisol concentration will be added as a predictor in the models to explain gut microbiota composition.
Metabolomics: Whole blood samples were extracted with MeOH and MeOH/ACN and metabolomic analyses are undergoing.
Listed below, are the preliminary results for each analyses performed.
Microbiomes: At the genus level, the gut microbiota composition was dominated by Clostridium> Romboutsia> Proteus> Ezakiella> Bacteroides> Paeniclostridium> Peptoniphilus> Vagococcus> Peptostreptococcus> Enterococcus> Tissierella> Anaerococcus. We characterised the health status of the minks by quantifying the following pathogenic bacteria, Enterococcus faecalis, Ralstonia pickettii, Salmonella enterica and Serratia spp. in four organs (kidney, spleen, lung, lymph node). Ralstonia pickettii was the most abundant pathogen and has been detected in the lymph node, kidney and spleen, while in lungs it was the second most abundant bacteria after Metamycoplasma orale. Further analyses will be performed to associate gut microbiota composition to the abundance of pathogens in the four organs analyzed.
Diet: Out of 15 samples (stomach content or feces) we were able to obtain prey DNA for only 7 individuals (we used COI gene metabarcoding) . DNA from the freshwater fish Phoxinus bigerri was detected in three individuals, we also detected DNA of micro-mammals (Crossidura russula, Rattus norvegicus), amphibians (Rana temporaria) and other freshwater fish species (Salmo trutta, Leuciscus burdigalensis, Acanthobrama persidid, Squalius cephalus, Gobio lozanoi).
Pollutants: In the 31 muscle samples, the antibiotic trimetoprime was only detected in three individuals and carbamazepine, a drug to prevent and control seizures, was detected in one individual. Yet in one blood sample used to validate the extraction method for metabolomic analyses, we were able to detect more pharmaceuticals. For instance, we were able to detect three synthetic hormones: altrenogest a synthetic progestin commonly used to synchronize estrus in livestock; norethisterone acetate a progestin which can be used in birth control pills, and methylprednisolone a medication used to reduce inflammation. In addition, we were also able to quantify other environmental pollutants in most whole blood samples such as polycyclic aromatic hydrocarbons and phtalates.
Fecal cortisol: Cortisol concentrations in fecal samples ranged from 3.45 to 168.5 pg/mg dw, in the sub-sample in which these values are available, cortisol concentration will be added as a predictor in the models to explain gut microbiota composition.
Metabolomics: Whole blood samples were extracted with MeOH and MeOH/ACN and metabolomic analyses are undergoing.
When all the results will be available, this will be one of the first projects to investigate the effects of pharmaceuticals on the health of a wild mammal. Some promising results are the detection of numerous xenobiotics in blood using LC-HRMS. More than 50 pharmaceuticals were detected including synthetic hormones, antibiotics, nonsteroidal anti-inflammatory drugs, etc. These results are alarming considering that the American mink is a semi-aquatic mammal with a short lifespan (4-5 years old), this raises concern on the potential health effects of pharmaceutical on aquatic species.