Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

Abstract

Microorganisms enhance fitness by prioritizing catabolism of available carbon sources using a process known as carbon catabolite repression (CCR). Planktonically grown Pseudomonas aeruginosa is known to prioritize the consumption of organic acids including lactic acid over catabolism of glucose using a CCR strategy termed “reverse diauxie.” P. aeruginosa is an opportunistic pathogen with well-documented biofilm phenotypes that are distinct from its planktonic phenotypes. Reverse diauxie has been described in planktonic cultures, but it has not been documented explicitly in P. aeruginosa biofilms. Here a combination of exometabolomics and label-free proteomics was used to analyze planktonic and biofilm phenotypes for reverse diauxie. P. aeruginosa biofilm cultures preferentially consumed lactic acid over glucose, and in addition, the cultures catabolized the substrates completely and did not exhibit the acetate secreting “overflow” metabolism that is typical of many model microorganisms. The biofilm phenotype was enabled by changes in protein abundances, including lactate dehydrogenase, fumarate hydratase, GTP cyclohydrolase, L-ornithine N(5)-monooxygenase, and superoxide dismutase. These results are noteworthy because reverse diauxie-mediated catabolism of organic acids necessitates a terminal electron acceptor like O2, which is typically in low supply in biofilms due to diffusion limitation. Label-free proteomics identified dozens of proteins associated with biofilm formation including 16 that have not been previously reported, highlighting both the advantages of the methodology utilized here and the complexity of the proteomic adaptation for P. aeruginosa biofilms. Documenting the reverse diauxic phenotype in P. aeruginosa biofilms is foundational for understanding cellular nutrient and energy fluxes, which ultimately control growth and virulence.

Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy

“…Pseudomonas aeruginosa strain 215 (Pa 215) is a medical isolate from a chronic wound 33 , 34 . Pa 215 was grown in chemically-defined, glucose containing, CSP G medium (materials and methods, supplementary material S1 ).…”

“…P. aeruginosa preference for non-fermentable substrates like succinate makes it a secondary resource specialist that requires terminal electron acceptors like O 2 or nitrate 75 . However, O 2 is often limiting in biofilms where cellular O 2 consumption rates are faster than diffusion rates 34 , 76 . P. aeruginosa possesses effective mechanisms to acquire scarce resources like O 2 70 , 77 – 80 .…”

Pseudomonas aeruginosareverse diauxie is an optimized, resource utilization strategy

“…Pseudomonas aeruginosa strain 215 (Pa 215) is a medical isolate from a chronic wound [36,37]. Pa 215 was grown in chemically-defined, CSP G medium (materials and methods, supplemental material S1).…”

“…P. aeruginosa preference for non-fermentable substrates like succinate makes it a secondary resource specialist that requires terminal electron acceptors like O2 or nitrate [76,77]. However, O2 is often limiting in biofilms where cellular O2 consumption rates are faster than diffusion rates [37,78]. Lactate has remarkable connections to P. aeruginosa substrate preference and medical niches including diabetic wounds.…”

The Role of Proteomics in Bacterial Response to Antibiotics

“…Proteomic analyses have a wide range of applications. Examples include investigating different protein levels in resistant [ 30 ] and drug-tolerant bacterial phenotypes [ 31 ] ( Table 2 ), as well as reports on the bacterial adaptation to different growing conditions and bacterial catabolism [ 32 ], biomarker discovery [ 33 ], and pathogen-host cell interactions [ 34 , 35 ]. In several other studies, different proteome analysis approaches have been employed to study the bacterial response to commonly used antibiotics such as ciprofloxacin [ 36 , 37 , 38 , 39 , 40 ], tobramycin [ 41 , 42 ], colistin [ 43 , 44 , 45 ], polymyxin B [ 46 ], daptomycin [ 47 , 48 ], and silver nanoparticles [ 49 ] ( Table 2 ).…”