2D and 3D Micropatterning of Mussel-Inspired Functional Materials by Direct Laser Writing.

This work addresses the critical need for multifunctional materials and substrate-independent high-precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel-inspired materials (MIMs) is combined with state-of-the-art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub-micron to micron resolution and extensive post-functionalization capabilities. This study includes polydopamine (PDA), mussel-inspired linear, and dendritic polyglycerols (MI-lPG and MI-dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single-stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.

A fluorescently labelled quaternary ammonium compound (NBD-DDA) to study resistance mechanisms in bacteria.

Quaternary ammonium compounds (QACs) are widely used as active agents in disinfectants, antiseptics, and preservatives. Despite being in use since the 1940s, there remain multiple open questions regarding their detailed mode-of-action and the mechanisms, including phenotypic heterogeneity, that can make bacteria less susceptible to QACs. To facilitate studies on resistance mechanisms towards QACs, we synthesized a fluorescent quaternary ammonium compound, namely N-dodecyl-N,N-dimethyl-[2-[(4-nitro-2,1,3-benzoxadiazol-7-yl)amino]ethyl]azanium-iodide (NBD-DDA). NBD-DDA is readily detected by flow cytometry and fluorescence microscopy with standard GFP/FITC-settings, making it suitable for molecular and single-cell studies. As a proof-of-concept, NBD-DDA was then used to investigate resistance mechanisms which can be heterogeneous among individual bacterial cells. Our results reveal that the antimicrobial activity of NBD-DDA against Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa is comparable to that of benzalkonium chloride (BAC), a widely used QAC, and benzyl-dimethyl-dodecylammonium chloride (BAC12), a mono-constituent BAC with alkyl-chain length of 12 and high structural similarity to NBD-DDA. Characteristic time-kill kinetics and increased tolerance of a BAC tolerant E. coli strain against NBD-DDA suggest that the mode of action of NBD-DDA is similar to that of BAC. As revealed by confocal laser scanning microscopy (CLSM), NBD-DDA is preferentially localized to the cell envelope of E. coli, which is a primary target of BAC and other QACs. Leveraging these findings and NBD-DDA's fluorescent properties, we show that reduced cellular accumulation is responsible for the evolved BAC tolerance in the BAC tolerant E. coli strain and that NBD-DDA is subject to efflux mediated by TolC. Overall, NBD-DDA's antimicrobial activity, its fluorescent properties, and its ease of detection render it a powerful tool to study resistance mechanisms of QACs in bacteria and highlight its potential to gain detailed insights into its mode-of-action.

Persistence against benzalkonium chloride promotes rapid evolution of tolerance during periodic disinfection.

Biocides used as disinfectants are important to prevent the transmission of pathogens, especially during the current antibiotic resistance crisis. This crisis is exacerbated by phenotypically tolerant persister subpopulations that can survive transient antibiotic treatment and facilitate resistance evolution. Here, we show that E. coli displays persistence against a widely used disinfectant, benzalkonium chloride (BAC). Periodic, persister-mediated failure of disinfection rapidly selects for BAC tolerance, which is associated with reduced cell surface charge and mutations in the lpxM locus, encoding an enzyme for lipid A biosynthesis. Moreover, the fitness cost incurred by BAC tolerance turns into a fitness benefit in the presence of antibiotics, suggesting a selective advantage of BAC-tolerant mutants in antibiotic environments. Our findings highlight the links between persistence to disinfectants and resistance evolution to antimicrobials.

Biphasic Cell-Size and Growth-Rate Homeostasis by Single Bacillus subtilis Cells.

The growth rate of single bacterial cells is continuously disturbed by random fluctuations in biosynthesis rates and by deterministic cell-cycle events, such as division, genome duplication, and septum formation. It is not understood whether, and how, bacteria reject these growth-rate disturbances. Here, we quantified growth and constitutive protein expression dynamics of single Bacillus subtilis cells as a function of cell-cycle progression. We found that, even though growth at the population level is exponential, close inspection of the cell cycle of thousands of single Bacillus subtilis cells reveals systematic deviations from exponential growth. Newborn cells display varying growth rates that depend on their size. When they divide, growth-rate variation has decreased, and growth rates have become birth size independent. Thus, cells indeed compensate for growth-rate disturbances and achieve growth-rate homeostasis. Protein synthesis and growth of single cells displayed correlated, biphasic dynamics from cell birth to division. During a first phase of variable duration, the absolute rates were approximately constant and cells behaved as sizers. In the second phase, rates increased, and growth behavior exhibited characteristics of a timer strategy. These findings demonstrate that, just like size homeostasis, growth-rate homeostasis is an inherent property of single cells that is achieved by cell-cycle-dependent rate adjustments of biosynthesis and growth.

Prevalent Synergy and Antagonism Among Antibiotics and Biocides in Pseudomonas aeruginosa.

Antimicrobials can exert specific physiological effects when used in combination that are different from those when applied alone. While combination effects have been extensively mapped for antibiotic-antibiotic combinations, the combination effects of antibiotics with antimicrobials used as biocides or antiseptics have not been systematically investigated. Here, we investigated the effects of combinations of antibiotics (meropenem, gentamicin, and ciprofloxacin) and substances used as biocides or antiseptics [octenidine, benzalkonium chloride, cetrimonium bromide, chlorhexidine, Povidone-iodine, silver nitrate (AgNO3), and Ag-nanoparticles] on the planktonic growth rate of Pseudomonas aeruginosa. Combination effects were investigated in growth experiments in microtiter plates at different concentrations and the Bliss interaction scores were calculated. Among the 21 screened combinations, we find prevalent combination effects with synergy occurring six times and antagonism occurring 10 times. The effects are specific to the antibiotic-biocide combination with meropenem showing a tendency for antagonism with biocides (6 of 7), while gentamicin has a tendency for synergy (5 of 7). In conclusion, antibiotics and biocides or antiseptics exert physiological combination effects on the pathogen P. aeruginosa. These effects have consequences for the efficacy of both types of substances and potentially for the selection of antimicrobial resistant strains in clinical applications with combined exposure (e.g., wound care and coated biomaterials).

Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli.

The inherent stochasticity of molecular reactions prevents us from predicting the exact state of single-cells in a population. However, when a population grows at steady-state, the probability to observe a cell with particular combinations of properties is fixed. Here we validate and exploit existing theory on the statistics of single-cell growth in order to predict the probability of phenotypic characteristics such as cell-cycle times, volumes, accuracy of division and cell-age distributions, using real-time imaging data for Bacillus subtilis and Escherichia coli. Our results show that single-cell growth-statistics can accurately be predicted from a few basic measurements. These equations relate different phenotypic characteristics, and can therefore be used in consistency tests of experimental single-cell growth data and prediction of single-cell statistics. We also exploit these statistical relations in the development of a fast stochastic-simulation algorithm of single-cell growth and protein expression. This algorithm greatly reduces computational burden, by recovering the statistics of growing cell-populations from the simulation of only one of its lineages. Our approach is validated by comparison of simulations and experimental data. This work illustrates a methodology for the prediction, analysis and tests of consistency of single-cell growth and protein expression data from a few basic statistical principles.

Effects of growth rate and promoter activity on single-cell protein expression.

Protein expression in a single cell depends on its global physiological state. Moreover, genetically-identical cells exhibit variability (noise) in protein expression, arising from the stochastic nature of biochemical processes, cell growth and division. While it is well understood how cellular growth rate influences mean protein expression, little is known about the relationship between growth rate and noise in protein expression. Here we quantify this relationship in Bacillus subtilis by a novel combination of experiments and theory. We measure the effects of promoter activity and growth rate on the expression of a fluorescent protein in single cells. We disentangle the observed protein expression noise into protein-specific and systemic contributions, using theory and variance decomposition. We find that noise in protein expression depends solely on mean expression levels, regardless of whether expression is set by promoter activity or growth rate, and that noise increases linearly with growth rate. Our results can aid studies of (synthetic) gene circuits of single cells and their condition dependence.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments.

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation.

Metabolism at evolutionary optimal States.

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

TRANSPARENT TESTA 13 is a tonoplast P3A -ATPase required for vacuolar deposition of proanthocyanidins in Arabidopsis thaliana seeds.

Intracellular pH homeostasis is essential for all living cells. In plants, pH is usually maintained by three structurally distinct and differentially localized types of proton pump: P-type H(+) -ATPases in the plasma membrane, and multimeric vacuolar-type H(+) -ATPases (V-ATPases) and vacuolar H(+) -pyrophosphatases (H(+) -PPases) in endomembranes. Here, we show that reduced accumulation of proanthocyanidins (PAs) and hence the diminished brown seed coloration found in the Arabidopsis thaliana mutant transparent testa 13 (tt13) is caused by disruption of the gene encoding the P3A -ATPase AHA10. Identification of the gene encoded by the tt13 locus completes the molecular characterization of the classical set of transparent testa mutants. Cells of the tt13 seed coat endothelium do not contain PA-filled central vacuoles as observed in the wild-type. tt13 phenocopies tt12, a mutant that is defective in vacuolar import of the PA precursor epicatechin. Our data show that vacuolar loading with PA precursors depends on TT13. Consistent with the tt13 phenotype, but in contrast to other isoforms of P-type H(+) -ATPases, TT13 localizes to the tonoplast. PA accumulation in tt13 is partially restored by expression of the tonoplast localized H(+) -PPase VHP1. Our findings indicate that the P3A -ATPase TT13 functions as a proton pump in the tonoplast of seed coat endothelium cells, and generates the driving force for TT12-mediated transport of PA precursors to the vacuole.

Update on transparent testa mutants from Arabidopsis thaliana: characterisation of new alleles from an isogenic collection.

MAIN CONCLUSION: We present a comprehensive overview on flavonoid-related phenotypes of A. thaliana tt and tds mutants, provide tools for their characterisation, increase the number of available alleles and demonstrate that tds3 is allelic to tt12 and tds5 to aha10. Flavonoid biosynthesis is one of the best-studied secondary metabolite pathways in plants. In the model system Arabidopsis thaliana it leads to the synthesis of three phenolic compound classes: flavonol glycosides, anthocyanins and proanthocyanidins (PAs). PAs appear brown in their oxidised polymeric forms, and most A. thaliana mutants impaired in flavonoid accumulation were identified through screens for lack of this seed coat pigmentation. These mutants are referred to as transparent testa (tt) or tannin-deficient seed (tds). More than 20 mutants of these types have been published, probably representing most of the genes relevant for PA accumulation in A. thaliana. However, data about the genes involved in PA deposition or oxidation are still rather scarce. Also, for some of the known mutants it is unclear if they represent additional loci or if they are allelic to known genes. For the present study, we have performed a systematic phenotypic characterisation of almost all available tt and tds mutants and built a collection of mutants in the genetic background of the accession Columbia to minimise effects arising from ecotype variation. We have identified a novel tt6 allele from a forward genetic screen and demonstrated that tds3 is allelic to tt12 and tds5 to aha10.