The term antibiotic resistance (AMR) can be used to describe bacteria that are not susceptible to one or more antibiotics. Such bacteria are sometimes referred to as “super bugs.” Resistance can occur as a result of bacteria’s natural defenses or can increase temporarily as a result of antibiotic usage. The concern, as it relates to beef production, is that antibiotics used in the production of beef (such as tylosin or chlortetracycline) could increase the risk of AMR infection in humans through the meat supply. While there is growing concern regarding the incidence and dissemination of AMR, there is no evidence demonstrating a direct link between livestock practices and increased public health risk. 

There are many ways to study AMR genes in a bacterial community. The most traditional scientific approach is to grow specific organisms, such as E. coli, in a laboratory setting and observe whether the organism grows in the presence of various concentrations of antibiotics. Another approach to understanding AMR genes is to perform quantitative PCR using specific primers for the gene of interest. While both of these approaches have been successfully used by scientists for many years, a newer approach known as “shotgun metagenomics” allows for the study of all AMR genes within a community across all organisms without specific primers. Shotgun metagenomics allows for the survey of all genes within a bacterial environment and allows for a more complete picture of all resistance genes present. With that in mind, we chose this particular approach.

To better understand AMR at different stages of beef production, we sampled one group of cattle, the meat derived from these cattle and nearby environments (all within 50 miles of each other). We sampled feces from the feedlot, trimmings from the processing plant, soil that composted beef feces had been applied to, sludge from a nearby human wastewater facility and soil that treated human wastewater had been applied to. After collecting these samples, we extracted DNA and performed a targeted shotgun metagenomic analysis that was specifically aimed at AMR genes. 

Antibiotic resistance genes were identified in all production segments (from feedlot through slaughter) and in the surrounding environments. On average, a very low number of different genes (27) were identified on the meat in contrast to the more than 400 found in beef feces and more than 600 found in human wastewater. It is not unusual to find resistance genes in all of these environments as AMR genes are naturally occurring. Nonetheless, the number of different AMR genes found on meat was much lower than all other stages of production. Of the resistance genes identified, different stages of production had different dominant genes. Instead of looking at the genes at an individual level, we grouped them into different classes of antibiotics representing similarities across gene structure and function.

The AMR genes found in soil from land following the application of composted beef feces and human wastewater were extremely similar in AMR gene makeup (both composted samples were very different than the un-composted feces and human wastewater). This suggested that the native soil present at these sites is the main contributor to what resistance genes are present, more so than the introduction of compost. Tetracycline, a class of resistance typically found in feedlots, was the main class of resistance found in cattle feces. The World Health Organization (WHO) considers tetracycline to be a highly important antimicrobial, being part of the second tier of medically important antibiotics. The meat resistome was composed of beta-lactams and elfamycin. A portion of these classes fall into the critically important antimicrobials, meaning they are the WHO’s highest level of concern. 

We also used a tool that that enabled us to look at patterns in the data to determine whether the resistance genes on meat were from other sources we had collected, such as feces or soil. This tool compares the AMR gene composition found in various environments and determines the probability the genes originated from one of the sampled sources. Of the samples collected, only 6 percent of the resistance genes present on meat were attributed to fecal contamination. Conversely, soil treated with composted feces from both the feedlot and human wastewater made up around a third of the contamination. More than half of the source contamination was not captured in this current dataset, meaning we are not sure where half of the genes residing on beef trimmings originated.

While this survey provides an introductory characterization of which AMR genes are present through a beef production system, there are still questions that remain. One example: If fecal contamination is not the main driver of resistance genes found on meat, what is? More thorough sampling could be conducted closer to the end product (such as holding pens and workers’ shoes in the plant) to gain a better understanding of what contributes to the presence of these genes. Additionally, while these data allow for a more comprehensive characterization of AMR status in beef production, as well as on the trims itself, they are not allowing us to quantify the risk associated with consuming meat. While we know AMR genes can be found on meat products, these data give no indication on whether the presence is actually a public health risk.

Finally, while antimicrobial usage in livestock is often being positioned as a contributor to human AMR bacterial infection, vast data show this is not the only possible avenue that those genes can be introduced to humans. Other concerns include natural occurrence of AMR genes in the environment, overuse of antibiotics in human health care, and other reservoirs such as wild and domestic animals. As we continue to understand where human AMR bacterial infections originate, we need to create a comprehensive program supported by all of the food supply chain stakeholders to alleviate AMR prevalence in the food supply. NP