To the Editor, The conventional understanding of antimicrobial resistance (AMR), centered on individual bacterial mutations, is insufficient to explain the rapid global spread of resistance. We propose the “Resistance Transfer Network” (RTN) hypothesis, a framework that models AMR as a networked phenomenon. In this model, resistance determinants are not static traits but mobile assets actively exchanged through a dynamic network of bacteria, fungi, and bacteriophages, which act as hubs and vectors for dissemination. The architecture of these networks is built upon well-established microbial interactions. For instance, symbiotic relationships, such as those between bacteria and their insect hosts, demonstrate how microorganisms can form tightly integrated functional units (Douglas, 2015). Within an RTN, these interactions are repurposed for survival under antibiotic pressure. Biofilms, which are complex communities of bacteria and fungi, serve as the physical infrastructure—the “nodes” and “hubs”—of this network, creating a protected environment where genetic exchange is optimized.1 Bacteriophages are the primary “vectors” in this network, functioning as high-speed data carriers that transfer antibiotic resistance genes (ARGs) between different bacterial nodes. Their ability to infect multiple hosts makes them exceptionally efficient at disseminating resistance across species boundaries, far faster than vertical inheritance would allow.2 The RTN hypothesis posits that this phage-mediated transfer is not random but is a regulated process, potentially influenced by signals from the microbial community. A novel aspect of the RTN model is the role of fungi as “stabilizing hubs.” Fungi can act as reservoirs for ARGs and phages, protecting them from environmental degradation. Their physical structure within biofilms facilitates close contact between bacteria and phages, effectively creating “transfer hotspots” that accelerate the dissemination of resistance. This transforms the fungus from a passive bystander into an active and critical component of the resistance infrastructure.3 Furthermore, the RTN framework suggests that metabolic byproducts and signaling molecules function as the “network protocols” that regulate gene flow. Quorum sensing signals, for example, could modulate phage activity or bacterial competence for transformation, ensuring that ARGs are shared most efficiently when the community is under threat. This coordinated, network-level response allows the microbial community to adapt as a cohesive whole Figure 1.Figure 1: Conceptual model of the Resistance Transfer Network (RTN) illustrating the role of bacteria, bacteriophages, and fungal hubs in the dissemination of antibiotic resistance genes (ARGs) within polymicrobial biofilm communitiesViewing AMR through the lens of Resistance Transfer Networks opens up new therapeutic strategies focused on network disruption. Instead of targeting the pathogen alone, interventions could be designed to disable the network’s infrastructure. This might involve disrupting the biofilm matrix, inhibiting phage-mediated gene transfer, or targeting the fungal hubs that stabilize the network. By destabilizing these critical network components, it may be possible to isolate pathogens and restore their susceptibility to existing antibiotics, a concept supported by studies on polymicrobial interactions.4 The RTN hypothesis reframes AMR as a problem of connectivity, urging a shift towards therapies that dismantle the networks enabling microbial survival. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
Falah Hasan Obayes Al-Khikani (Thu,) studied this question.