Animal disease
Imago / Xinhua 
“There are many antimicrobial-resistant genes we already know about, but how do we go beyond these and unravel new targets to design new drugs?” asked Dr Tania Dottorini from the School of Veterinary Medicine and Science at the University.
UNITED KINGDOM, Nottingham. Scientists from the University of Nottingham have developed software which combines DNA sequencing and machine learning to aid in locating antibiotic-resistant bacteria transmission between humans, animals and the environment.
The study, published in PLOS Computational Biology, was led by Dr Tania Dottorini from the School of Veterinary Medicine and Science at the University and the Future Food Beacon leadership team.
Anthropogenic environments (spaces created by humans), such as areas of intensive livestock farming, are seen as ideal breeding grounds for antimicrobial-resistant bacteria and antimicrobial-resistant genes, which are capable of infecting humans and carrying resistance to drugs used in human medicine. This can have serious implications for how certain illnesses and infections can be treated effectively.
In the study, a team of experts looked at a large scale commercial poultry farm in China and collected 154 samples from animals, carcasses, workers and their households and environments. From the samples, they isolated a specific bacteria called Escherichia coli (E. coli). These bacteria can live quite harmlessly in a person’s gut but can also be pathogenic and carry resistance genes against certain drugs.
By applying machine learning, the team could detect an entire network of genes associated with antimicrobial resistance, shared across animals, farmworkers and the environment around them. Notably, this network included genes known to cause antibiotic resistance and yet unknown genes associated with antibiotic resistance.
Dr Dottorini said: “We cannot say at this stage where the bacteria originated from, we can only say we found it, and it has been shared between animals and humans. As we already know there has been sharing, this is worrying because people can acquire resistance to drugs in two different ways - from direct contact with an animal or indirectly by eating contaminated meat. This could be a particular problem in poultry farming, as it is the most widely used meat in the world.”
The approach could offer new possibilities for developing fast, affordable and effective computational methods to analyse large amounts of complex data from a range of different sources. The computational tools were fast, precise and could be applied to large environments such as multiple livestock farms simultaneously, Dr Dottorini added. This could aid in developing effective drugs targeting currently found antimicrobial-resistant genes.
The research was done in collaboration with Professor Junshi Chen, Professor Fengqin Li and Professor Zixin Peng from China National Center for Food Safety Risk Assessment (CFSA). The research was supported by Professor David Salt, Director of the Future Food Beacon at the University of Nottingham.
Source: University of Nottingham
