Unraveling the Role of Vegetables in Spreading Antimicrobial-Resistant Bacteria: A Need for Quantitative Risk...

In recent years, vegetables gain consumer attraction due to their reputation of being healthy in combination with low energy density. However, since fresh produce is often eaten raw, it may also be a source for foodborne illness. The presence of antibiotic-resistant bacteria might pose a particular risk to the consumer. Therefore, this review aims to present the current state of knowledge concerning the exposure of humans to antibiotic-resistant bacteria via food of plant origin for quantitative risk assessment purposes. The review provides a critical overview of available information on hazard identification and characterization, exposure assessment, and risk prevention with special respect to potential sources of contamination and infection chains. Several comprehensive studies are accessible regarding major antimicrobial-resistant foodborne pathogens (e.g., Salmonella spp., Listeria spp., Bacillus cereus, Campylobacter spp., Escherichia coli) and other bacteria (e.g., further Enterobacteriaceae, Pseudomonas spp., Gram-positive cocci). These studies revealed vegetables to be a potential-although rare-vector for extended-spectrum beta-lactamase-producing Enterobacteriaceae, mcr1-positive E. coli, colistin- and carbapenem-resistant Pseudomonas aeruginosa, linezolid-resistant enterococci and staphylococci, and vancomycin-resistant enterococci. Even if this provides first clues for assessing the risk related to vegetable-borne antimicrobial-resistant bacteria, the literature research reveals important knowledge gaps affecting almost every part of risk assessment and management. Especially, the need for (comparable) quantitative data as well as data on possible contamination sources other than irrigation water, organic fertilizer, and soil becomes obvious. Most crucially, dose-response studies would be needed to convert a theoretical "risk" (e.g., related to antimicrobial-resistant commensals and opportunistic pathogens) into a quantitative risk estimate.