Biology subjects

Bonde, N.

Publications and source records attributed to Bonde, N..

3 recordsLinked to original sources

bioRxiv2026

Polystyrene Microplastics Accelerate Antibiotic Resistance Evolution and Exacerbate Pathogenicity in Acinetobacter Baumannii

Microplastics are pervasive environmental contaminants and are increasingly detected in contexts relevant to human health, yet their effects on antimicrobial resistance, host-pathogen interactions, and infection outcomes remain poorly understood. Here, we show that exposure to polystyrene microplastics alters both antibiotic resistance evolution and pathogenic behavior in Acinetobacter baumannii, a leading cause of multidrug-resistant hospital-acquired infections. Using experimental evolution under antibiotic selection, we demonstrate that microplastic exposure accelerates resistance emergence across multiple antibiotic classes. Although microplastic exposure did not uniformly enhance biofilm formation, it modestly impaired macrophage-mediated bacterial clearance, suggesting broader effects on bacterial adaptation and host interaction. In vivo, microplastic-associated infection resulted in more severe disease, characterized by increased lung tissue damage and reduced survival in a murine model of A. baumannii pneumonia. Together, these findings identify microplastics as ecological modifiers of bacterial adaptation, linking widespread plastic pollution to enhanced antimicrobial resistance and worsened infectious disease outcomes.

microbiology↗

bioRxiv2026

DISRUPTION OF A DNA REPAIR PROTEIN PROMOTES ANTIBIOTIC RESISTANCE IN ACINETOBACTER BAUMANNII

Acinetobacter baumannii is a high priority Gram negative opportunistic pathogen known for its high rates of multidrug resistance (MDR). Minocycline (MIN), a tetracycline class antibiotic, is one of the most effective antibiotics for treating A. baumannii infections in patients. Unfortunately, MIN resistance is spreading internationally and has begun to emerge in the United States. While efflux pumps are correlated with MIN resistant A. baumannii, clinical data suggests alternative mechanisms of MIN resistance. To explore the genetic basis for MIN resistance in A. baumannii we employed a machine learning model to predict genetic resistance correlates from clinical isolates. Mutations in ruvB, a DNA repair protein, were strongly correlated with MIN resistant clinical strains of A. baumannii .Consistent with the prediction, tn26 insertion in ruvB in A. baumannii strain AB5075, and deletion of ruvB in strain ATCC 19606, increased MIN minimum inhibitory concentrations to a level that exceeds the MIN resistance breakpoint. RuvB complexes with RuvA and RuvC to resolve Holliday junctions during recombination. However, only ruvB mutants showed the resistance phenotype; neither ruvA nor ruvC mutants were MIN resistant, suggesting loss of the activity of the complex was not the basis for resistance. We observed ruvB mutants produced increased biomass during planktonic growth relative to the other two ruv mutants. Upon examination, the ruvB::tn26 mutant had a 451% increase in biomass and 360% thicker biofilms relative to wildtype. We determined the disruption of ruvB lead to thicker biofilms and enriched in extracellular DNA (eDNA), and DNase I treatment collapsed the enhanced biofilm phenotype and markedly reduced tetracycline class MICs. FLAG-RuvA accumulated within the biofilm matrix in the absence of RuvB, supporting a model in which RuvA contributes to stabilization of eDNA-rich structures. In a murine pneumonia model, ruvB disruption did not significantly alter survival or pulmonary burden in untreated infection but reduced bacterial dissemination and increased minocycline resistance. Together, these findings reveal an unexpected connection between Holliday junction processing, eDNA-rich biofilm architecture, and antibiotic resistance in A. baumannii.

microbiology↗

bioRxiv2026

A Clinically Silent Resistance Phenotype That Promotes Acinetobacter baumannii Survival During Colistin Therapy

Acinetobacter baumannii is a major cause of multidrug-resistant nosocomial infections, particularly ventilator-associated pneumonia, for which therapeutic options are increasingly limited. Colistin, a polymyxin antibiotic, is a drug of last resort for A. baumannii, boasting high susceptibility rates. Yet, despite relatively low rates of breakpoint-defined colistin resistance, clinical outcomes are highly variable, and the bacterial strategies that enable survival during colistin therapy remain poorly understood. Here, we integrate supervised machine-learning-guided genomic prioritization with functional, physiological, and in vivo analyses to interrogate the genetic basis of colistin response in A. baumannii. Machine-learning analysis of clinical isolates identified candidate loci associated with colistin survival, many of which did not alter minimum inhibitory concentration (MIC) when disrupted. Instead, growth-dynamic assays uncovered a subset of mutants capable of maintaining fitness upon inhibitory colistin exposure despite classification as susceptible via standardized antibiotic susceptibility testing. We define this phenotype as clinically silent resistance (CSR), a genetically encoded, MIC-independent survival state. Using a murine pneumonia model, we further demonstrate that CSR mutants thrive during colistin therapy in vivo. Together, these findings reveal a hidden layer of colistin survival that is not captured by standard susceptibility testing and highlight fundamental limitations of breakpoint-centric paradigms for predicting treatment outcomes in A. baumannii.

microbiology↗