Publications

@article{https://doi.org/10.2903/j.efsa.2022.e200407,

title = {Improving the risk assessment of antimicrobial resistance (AMR) along the food/feed chain and from environmental reservoirs using qMRA and probabilistic modelling},

author = {M Niegowska and M Wögerbauer},

url = {https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/j.efsa.2022.e200407},

doi = {https://doi.org/10.2903/j.efsa.2022.e200407},

year  = {2022},

date = {2022-01-01},

journal = {EFSA Journal},

volume = {20},

number = {S1},

pages = {e200407},

abstract = {Abstract Efficient risk assessment of antimicrobial resistance (AMR) in environmental reservoirs, particularly agroecosystems, is critical for predicting threats to animal and human health due to infections unresponsive to antibiotic therapy. However, approaches currently employed for the risk assessment of AMR along the human food chain rarely rely on antibiotic resistance gene (ARG) environmental pathways connected to food production and related quantitative data. The present project aimed at improving the risk assessment related to the spread of AMR along the food/feed chain based on ARG quantification in agroecosystems and interconnected environments. The fellow received training and worked in close cooperation with the team on two ongoing research projects which involved: (i) the monitoring of ARGs in field soils and surface waters to identify and characterise food/feed chain-associated environmental reservoirs of AMR relevant at the national level; (ii) the evaluation of ARG dynamics in relation to agricultural practice within an international project assessing biodiversity as an ecological barrier for the spread of clinically relevant ARGs in the environment. ARG quantification was performed using single/multiplex real-time polymerase chain reaction (PCR) with tailor-made primers/probe sets according to in-house optimised and validated conditions. The assessment was completed by a comprehensive revision of available literature data for risk-ranking of ARGs along with a literature review exploring AMR quantitative knowledge gaps and the role of certain AMR determinants encoded on free extracellular DNA (exDNA) in their environmental spread.},

keywords = {agroecosystem, antibiotic resistance genes, Antimicrobial resistance, ARG, extracellular DNA, risk assessment},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.2903/j.efsa.2022.e200417,

title = {Integration of genomics in surveillance and risk assessment for outbreak investigation},

author = {Vincenzo Pennone and José Francisco Cobo-Díaz and Miguel Prieto-Maradona and Avelino Álvarez-Ordóñez},

url = {https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/j.efsa.2022.e200417},

doi = {https://doi.org/10.2903/j.efsa.2022.e200417},

year  = {2022},

date = {2022-01-01},

journal = {EFSA Journal},

volume = {20},

number = {S1},

pages = {e200417},

abstract = {Abstract Keeping food safe is a challenge that needs continuous surveillance for the sake of consumers’ health. The main issue when a food-borne pathogen outbreak occurs is represented by the identification of the source(s) of contamination. Delivering this information in a timely manner helps to control the problem, with positive outcomes for everyone, especially for the consumers, whose health is in this way preserved, and for the stakeholders involved in food production and distribution, who could face enormous economic losses if recalls or legal issues occur. Whole genome sequencing (WGS) is a tool recently implemented for the characterisation of isolates and the study of outbreaks because of its higher efficiency and faster results, when compared to traditional typing methods. Lower sequencing costs and the development of many bioinformatic tools helped its spread, and much more attention has been given to its use for outbreak investigation. It is important to reach a certain level of standardisation, though, for ensuring result reproducibility and interoperability. Moreover, nowadays it is possible, if not mandatory for Open Science Practices, to share WGS data in publicly available databases, where raw reads, assembled genomes and their corresponding metadata can be easily found and downloaded. The scope of this Fellowship was to provide the Fellow all the training necessary for successfully integrating genomics to surveillance and risk assessment of food-borne pathogens from farm to fork.},

keywords = {Antimicrobial resistance, farm to fork, food safety, outbreak, risk assessment, surveillance, whole genome sequencing},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.2903/j.efsa.2020.e181107,

title = {Identification of risk factors and hotspots of antibiotic resistance along the food chain using next-generation sequencing},

author = {I. Bergšpica and G. Kaprou and E. A. Alexa and M. Prieto-Maradona and A. Alvarez-Ordóñez},

url = {https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/j.efsa.2020.e181107},

doi = {https://doi.org/10.2903/j.efsa.2020.e181107},

year  = {2020},

date = {2020-01-01},

journal = {EFSA Journal},

volume = {18},

number = {S1},

pages = {e181107},

abstract = {Abstract Bacterial antimicrobial resistance (AMR) is considered to be very alarming following an upward trend and thus posing a primary threat to public health. AMR has tremendous adverse effects on humans, farm animals, healthcare, the environment, agriculture and, thus, on national economies. Several tools have been proposed and adopted by numerous countries after comprehending the need for antimicrobial stewardship and for a rational use of antibiotics. These tools include diagnostics for infections or AMR detection, for measuring and monitoring antibiotic consumption (e.g. surveillance tools) and for guiding medical doctors and veterinarians in selecting suitable antibiotics. In addition, it has been known that the food chain represents a leading vector for the transmission of pathogens to humans via various routes (direct or indirect). Considerable efforts have been made and are still in progress both at international and national levels in order to control and mitigate the spread of pathogens and thus ensure food safety. During the last decades, a new concern has risen regarding the food chain playing a potential major role in the transmission of resistant bacteria as well as resistance genes from the animal kingdom to humans. Several recent studies highlight the role of food processing environments as potential AMR hotspots contributing to this spread phenomenon. Next-generation sequencing (NGS) technologies are becoming broadly used in the AMR field, since they allow the surveillance of resistant microorganisms, AMR determinants and mobile genetic elements. Moreover, NGS is capable of providing information on the mechanisms driving and spreading AMR throughout the food chain. In the current work programme, the aim was to acquire knowledge and skills to track AMR genes and mobile genetic elements in the food chain through NGS methodologies in order to implement a quantitative risk assessment and identify hotspots and routes of transmission of AMR along the food chain.},

keywords = {Antimicrobial resistance, food chain, next-generation sequencing, risk assessment},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.2903/j.efsa.2018.e160811,

title = {Risk assessment of antimicrobial resistance along the food chain through culture-independent methodologies},

author = {E Likotrafiti and EA Oniciuc and M Prieto and JA Santos and S López and A Alvarez-Ordóñez},

url = {https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/j.efsa.2018.e160811},

doi = {https://doi.org/10.2903/j.efsa.2018.e160811},

year  = {2018},

date = {2018-01-01},

journal = {EFSA Journal},

volume = {16},

number = {S1},

pages = {e160811},

abstract = {Abstract Antimicrobial resistance (AMR) represents a major challenge for Public Health and the scientific community, and requires immediate and drastic solutions. Acquired resistance to certain antimicrobials is already widespread to such an extent that their efficacy in the treatment of certain life-threatening infections is already compromised. To date, the emergence and spread of AMR has been attributed to the use, misuse or indiscriminate use of antibiotics as therapeutic drugs in human, animal and plant health, or as growth promoters in veterinary husbandry. In addition, there is growing concern over the possibility of AMR transmission via the food chain. Food processing environments could act as potential hotspots for AMR acquisition and spread. Indeed, biocide use and exposure to food-related stresses and food processing technologies could presumably act as selection pressures for increased microbial resistance against clinically relevant antibiotics. Global AMR surveillance is critical for providing the necessary information to form global strategies and to monitor the effectiveness of public health interventions as well as to detect new trends and emerging threats. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterisation of the strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence and spread of AMR genes. Whole genome sequencing (WGS) of bacterial pathogens is a powerful tool that can be used for epidemiological surveillance, outbreak detection and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on the occurrence of AMR genes. Both approaches can be used to provide the information necessary for the implementation of quantitative risk assessment of AMR transmission routes along the food chain.},

keywords = {Antimicrobial resistance, food-borne pathogens, metagenomics, risk assessment, surveillance, whole genome sequencing},

pubstate = {published},

tppubtype = {article}

}