Peng Guo

Bacterial resistance to antibiotics can lead to long-lasting, hard-to-cure infections that pose significant threats to human health. One key mechanism of antimicrobial resistance (AMR) is to reduce the antibiotic permeation of cellular membranes. For instance, the lack of outer membrane porins (OMPs) can lead to elevated AMR levels. However, knowledge on whether mutations of OMPs can also influence antibiotic susceptibility is limited. This work aims to address this question and identified an A226D mutation in OmpC, a trimeric OMP, in Escherichia coli. Surveillance studies found that this mutation is present in 50 E. coli strains for which whole genomic sequences are available. Measurement of minimum inhibition concentrations (MICs) found that this mutation leads to a 2-fold decrease in MICs for β-lactams ampicillin and piperacillin. Further survival assays confirmed the role this mutation plays in β-lactam susceptibility. With molecular dynamics, we found that the A226D mutation led to increased overall flexibility of the protein, thus facilitating antibiotic uptake, and that binding with piperacillin was weakened, leading to easier antibiotic penetration. This work reports a novel mutation that plays a role in antibiotic susceptibility, along with mechanistic studies, and further confirms the role of OMPs in bacterial tolerance to antibiotics.

Iron is a critical yet limited nutrient for microbial growth. To scavenge iron, most microbes produce siderophores—diverse small molecules with high iron affinities. Different siderophores are specifically recognized and uptaken by corresponding recognizers, enabling targeted interventions and intriguing cheater-producer dynamics. We propose constructing a comprehensive iron interaction network, or "iron-net," across the microbial world. Such a network offers the potential for precise manipulation of the microbiota, with conceivable applications in medicine, agriculture, and industry, as well as advancing microbial ecology and evolution theories. Previously, our successful construction of an iron-net in the Pseudomonas genus demonstrated the feasibility of co-evolution-inspired digital siderophore typing. Enhanced by machine learning techniques and expanding sequencing data, forging such an iron-net calls for multidisciplinary collaborations, and holds significant promise in addressing critical challenges in microbial communities.