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Biology subjects

Arugonda, R.

Publications and source records attributed to Arugonda, R..

2 recordsLinked to original sources

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↗

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↗