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Hanley, L.

Publications and source records attributed to Hanley, L..

2 recordsLinked to original sources

Spatially resolved analysis of Pseudomonas aeruginosa biofilm proteomes measured by laser ablation sample transfer

Heterogeneity in the distribution of nutrients and O2 gradients during biofilm growth gives rise to changes in phenotype. There has been long term interest in identifying spatial differences during biofilm development including clues that identify chemical heterogeneity. Laser ablation sample transfer (LAST) allows site-specific sampling combined with label free proteomics to distinguish radially and axially resolved proteomes for Pseudomonas aeruginosa biofilms. Specifically, differential protein abundances on oxic vs. anoxic regions of a biofilm was observed by combining LAST with bottom up proteomics. This study reveals active metabolism in the anoxic region of the biofilm with respect to the oxic region in P. aeruginosa, an aerobe by nature. Protein abundance data related to cellular acclimations to chemical gradients include identification of glucose catabolizing proteins, high abundance of proteins from arginine and polyamine metabolism, and proteins that could also support virulence and environmental stress mediation on the anoxic region. Finally, this methodology requires only a few mm2 of biofilm area to identify hundreds of proteins.

microbiology

Pseudomonas aeruginosa reverse diauxie is an optimized, resource utilization strategy

Pseudomonas aeruginosa is a globally-distributed bacterium often found in medical infections. The opportunistic pathogen uses a different, carbon catabolite repression (CCR) strategy than many, model microorganisms. It does not utilize a classic diauxie phenotype, nor does it follow common systems biology assumptions including preferential consumption of glucose with an overflow metabolism. Despite these contradictions, P. aeruginosa is competitive in many, disparate environments underscoring knowledge gaps in microbial ecology and systems biology. Physiological, omics, and in silico analyses were used to quantify the P. aeruginosa CCR strategy known as reverse diauxie. An ecological basis of reverse diauxie was identified using a genome-scale, metabolic model interrogated with in vitro omics data. Reverse diauxie preference for lower energy, nonfermentable carbon sources, such as acetate or succinate over glucose, was predicted using a multidimensional strategy which minimized resource investment into central metabolism while completely oxidizing substrates. Application of a common, in silico optimization criterion, which maximizes growth rate, did not predict the reverse diauxie phenotypes. This study quantifies P. aeruginosa metabolic strategies foundational to its wide distribution and virulence.

systems biology