Webinar part 1 — Precision microbiome engineering as an alternative to antibiotics to prevent bacterial infections in agricultural settings

The human health effects of antibiotic resistance are a growing international crisis. In 2019 an estimated 4.95 million human deaths were associated with antibiotic resistance, and it is estimated that by 2050 there will be 10 million deaths a year due to antibiotic resistance infections. Although antibiotic stewardship in human medicine is an important part of addressing this crisis, 70–80% of all antimicrobials that are produced internationally are used in agriculture to increase growth, provide prophylaxis and treat bacterial infections in livestock. While banning antibiotics in agriculture may seem like a good idea, an immediate ban would result in a 5–8% decrease in productivity on swine farms, an increased mortality of 1.3% for broilers before market weight is achieved and a 95% increase in the rates of mastitis on dairy farms. This decrease in productivity would cause issues in terms of food security.

The Ronholm laboratory aims to address this problem by characterizing the microbiota of livestock, identifying antagonistic interactions that occur naturally between bacterial pathogens and members of the endogenous microbiota, obtain isolates and then engineering designer and disease resistant microbiotas to replace the functional need for antibiotics on farms. Ongoing work in the Ronholm laboratory focuses on investigating how the composition of the microbiota in several livestock models affects susceptibility to several bacterial pathogens and identifying specific endogenous bacteria that can antagonize relevant bacterial pathogens. The lab is currently exploring Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae infections in the mammary gland of dairy cattle (mastitis).

By using a network analysis of 16S sequencing data that compared the microbiota of healthy and cows with mastitis and follow-up shotgun metagenomics, we have shown that, if the udders of dairy cattle that are colonized with Aerococcus urinaeequi or Staphylococcus xylosus, the animals have a significantly lower chance of contracting a mastitis infections caused by S. aureus. After obtaining isolates, we were able to show that A. urinaeequi can inhibit S. aureus growth in co-culture. In the future, it may be possible to harness the power of the microbiota to lower the need for antibiotic use in production agriculture.  

Webinar part 2 — Monitoring antibiotic resistance in human populations is necessary for evidence-based prevention and effective response to control outbreaks.

Although patients carrying emerging extremely resistant bacteria (eXDR) and their contacts can be tracked, the resulting epidemiological data are often incomplete. With new technology, new tools could eliminate the need for tracing while providing enhanced surveillance. Such wastewater-based epidemiology has been shown to be effective for surveillance during the COVID-19 pandemic. For 18 weeks, we analyzed wastewater from three hospital buildings. Two of these buildings (HOM and DIG) house patients with a high rate of eXDR. Wastewater from a third building (LN) houses patents with no added risk of eXDR infection and was used to establish a baseline. Three eXDR-associated genes (bla_OXA-48, bla_NDM, vanA) were monitored. We also monitored the bla_CTX-M gene, which encodes a widespread extended-spectrum betalactamase as an “endemicity standard”. After extraction of total DNA from the wastewater samples, bla_CTX-M, bla_OXA-48, bla_NDM and vanA genes were quantified by qPCR and ddPCR relatively to 16S rRNA genes. In addition, carbapenemase-producing enterobacteria (CPE) and vancomycin-resistant enterococci (VRE) were cultured on CHROMagar mSuperCARBA and CHROMagar VRE selective media, respectively, and identified by MALDI-TOF-MS. To compare the bacterial species cultured from the wastewater and those isolated from the patients during the study, clinical and biological data of the patients were collected. Our results showed that the quantity of genes detected from wastewater varied between genes, buildings and over time, confirming the potential value of this approach as a monitoring tool. The baseline quantification data from the LN building revealed consistent levels over time, which could allow the determination of target/alert thresholds. Levels from the LN building were significantly different than the levels from the HOM and DIG buildings. The bla_OXA-48 signal was generally the same or greater than the bla_CTX-M signal for all three buildings. As bla_OXA-48 is considered as emerging and bla_CTX-M as endemic in France, our results suggest that either the level of OXA-48 CPE currently in circulation in France is underestimated or that a dynamic reservoir of OXA-48 CPE can be harbored in wastewater. Both vanA and bla_NDM exhibited the expected epidemic dynamics. For all three genes, the correlation between the signal and the presence of a known carrier patient was weak due to the low number of known carrier patients over the monitored period. In particular, CPE of the genus Citrobacter were more prevalent in wastewater than was expected for the number of known in patients in the hospital, supporting the role of wastewater as a reserve. This study demonstrates the feasibility of monitoring the epidemiology of antibiotic resistance based on wastewater from a hospital.