Mathematical Modeling of Biofilm Structures Using COMSTAT Data

Mathematical modeling holds great potential for quantitatively describing biofilm growth in presence or absence of chemical agents used to limit or promote biofilm growth. In this paper, we describe a general mathematical/statistical framework that allows for the characterization of complex data in terms of few parameters and the capability to (i) compare different experiments and exposures to different agents, (ii) test different hypotheses regarding biofilm growth and interaction with different agents, and (iii) simulate arbitrary administrations of agents. The mathematical framework is divided to submodels characterizing biofilm, including new models characterizing live biofilm growth and dead cell accumulation; the interaction with agents inhibiting or stimulating growth; the kinetics of the agents. The statistical framework can take into account measurement and interexperiment variation. We demonstrate the application of (some of) the models using confocal microscopy data obtained using the computer program COMSTAT

Determination of Tobramycin in M₉ Medium by LC-MS/MS: Signal Enhancement by Trichloroacetic Acid

It is well known that ion-pairing reagents cause ion suppression in LC-MS/MS methods. Here, we report that trichloroacetic acid increases the MS signal of tobramycin. To support studies of an in vitro pharmacokinetic/pharmacodynamic simulator for bacterial biofilms, an LC-MS/MS method for determination of tobramycin in M9 media was developed. Aliquots of 25 μL M9 media samples were mixed with the internal standard (IS) tobramycin-d5 (5 µg/mL, 25 µL) and 200 µL 2.5% trichloroacetic acid. The mixture (5 µL) was directly injected onto a PFP column (2.0 × 50 mm, 3 µm) eluted with water containing 20 mM ammonium formate and 0.14% trifluoroacetic acid and acetonitrile containing 0.1% trifluoroacetic acid in a gradient mode. ESI+ and MRM with ion m/z 468 → 324 for tobramycin and m/z 473 → 327 for the IS were used for quantification. The calibration curve concentration range was 50–25000 ng/mL. Matrix effect from M9 media was not significant when compared with injection solvents, but signal enhancement by trichloroacetic acid was significant (∼3 fold). The method is simple, fast, and reliable. Using the method, the in vitro PK/PD model was tested with one bolus dose of tobramycin

Draft Genome Sequence of Acinetobacter johnsonii C6, an Environmental Isolate Engaging in Interspecific Metabolic Interactions

ABSTRACT Acinetobacter johnsonii C6 originates from creosote-polluted groundwater and performs ecological and evolutionary interactions with Pseudomonas putida in biofilms. The draft genome of A. johnsonii C6 is 3.7 Mbp and was shaped by mobile genetic elements. It reveals genes facilitating the biodegradation of aromatic hydrocarbons and resistance to antimicrobials and metals. </jats:p

Development of Spatial Distribution Patterns by Biofilm Cells

Confined spatial patterns of microbial distribution are prevalent in nature, such as in microbial mats, soil communities, and water stream biofilms. The symbiotic two-species consortium of Pseudomonas putida and Acinetobacter sp. strain C6, originally isolated from a creosote-polluted aquifer, has evolved a distinct spatial organization in the laboratory that is characterized by an increased fitness and productivity. In this consortium, P. putida is reliant on microcolonies formed by Acinetobacter sp. C6, to which it attaches. Here we describe the processes that lead to the microcolony pattern by Acinetobacter sp. C6. Ecological spatial pattern analyses revealed that the microcolonies were not entirely randomly distributed and instead were arranged in a uniform pattern. Detailed time-lapse confocal microscopy at the single-cell level demonstrated that the spatial pattern was the result of an intriguing self-organization: small multicellular clusters moved along the surface to fuse with one another to form microcolonies. This active distribution capability was dependent on environmental factors (carbon source and oxygen) and historical contingency (formation of phenotypic variants). The findings of this study are discussed in the context of species distribution patterns observed in macroecology, and we summarize observations about the processes involved in coadaptation between P. putida and Acinetobacter sp. C6. Our results contribute to an understanding of spatial species distribution patterns as they are observed in nature, as well as the ecology of engineered communities that have the potential for enhanced and sustainable bioprocessing capacity

Mutations causing low level antibiotic resistance ensure bacterial survival in antibiotic-treated hosts

In 474 genome sequenced Pseudomonas aeruginosa isolates from 34 cystic fibrosis (CF) patients, 40% of these harbor mutations in the mexZ gene encoding a negative regulator of the MexXY-OprM efflux pump associated with aminoglycoside and fluoroquinolone resistance. Surprisingly, resistance to aminoglycosides and fluoroquinolones of mexZ mutants was far below the breakpoint of clinical resistance. However, the fitness increase of the mutant bacteria in presence of the relevant antibiotics, as demonstrated in competition experiments between mutant and ancestor bacteria, showed that 1) very small phenotypic changes cause significant fitness increase with severe adaptive consequences, and 2) standardized phenotypic tests fail to detect such low-level variations. The frequent appearance of P. aeruginosa mexZ mutants in CF patients is directly connected to the intense use of the target antibiotics, and low-level antibiotic resistance, if left unnoticed, can result in accumulation of additional genetic changes leading to high-level resistance

Evolutionary highways to persistent bacterial infection

The pathogen Pseudomonas aeruginosa undergoes complex trait adaptation within cystic fibrosis patients. Here, Bartell, Sommer, and colleagues use statistical modeling of longitudinal isolates to characterize the joint genetic and phenotypic evolutionary trajectories of P. aeruginosa within hosts