While biofilms are ubiquitous in nature, the mechanism by which they form is still poorly understood. This study investigated the process by which bacteria deposit and, shortly after, attach irreversibly to surfaces by reorienting to create a stronger interaction, which leads to biofilm formation. A model for attachment of Pseudomonas aeruginosa was developed using a quartz crystal microbalance with dissipation monitoring (QCM-D) technology, along with a fluorescent microscope and camera to monitor kinetics of adherence of the cells over time. In this model, the interaction differs depending on the force that dominates between the viscous, inertial, and elastic loads. P. aeruginosa, grown to the midexponential growth phase (hydrophilic) and stationary phase (hydrophobic) and two different surfaces, silica (SiO2) and polyvinylidene fluoride (PVDF), which are hydrophilic and hydrophobic, respectively, were used to test the model. The bacteria deposited on both of the sensor surfaces, though on the silica surface the cells reached a steady state where there was no net increase in deposition of bacteria, while the quantity of cells depositing on the PVDF surface continued to increase until the end of the experiments. The change in frequency and dissipation per cell were both positive for each overtone (n), except when the cells and surface are both hydrophilic. In the model three factors, specifically, viscous, inertial, and elastic loads, contribute to the change in frequency and dissipation at each overtone when a cell deposits on a sensor. On the basis of the model, hydrophobic cells were shown to form an elastic connection to either surface, with an increase of elasticity at higher overtones. At lower overtones, hydrophilic cells depositing on the hydrophobic surface were shown to also be elastic, but as the overtone increases the connection between the cells and sensor becomes more viscoelastic. In the case of hydrophilic cells interacting with the hydrophilic surface, the connection is viscous at each overtone measured. It could be inferred that the transformation of the viscoelasticity of the cell–surface connection is due to changes in the orientation of the cells to the surface, which allow the bacteria to attach irreversibly and begin biofilm formation.

In this study we investigate how growth stage and depositional environment affect variability of cell properties and transport behavior of eight porcine E. coli isolates. We compared the surface properties for cells harvested during exponential and stationary growth phase and their transport behavior through columns packed with either uncoated or Fe-coated quartz sand. We then investigated correlations between measured cell properties and fitted bacterial attachment efficiencies. For both growth stages we found that bacterial attachment efficiencies in the uncoated quartz sand varied among the eight different isolates by over an order of magnitude whereas attachment efficiencies in the Fe-coated sands varied by a factor of less than two. With the exception of one isolate, growth condition had minimal impact on attachment efficiencies to the uncoated sands. A strong and statistically significant inverse relationship was observed between bacterial attachment efficiencies in the uncoated quartz sand columns and log-transformed zeta potential, whereas a mild yet statistically significant relationship between bacterial attachment efficiencies in the Fe-coated sands and cell width was observed. For the experimental conditions used in our study, we found that variability in E. coli transport was more dependent on the depositional environment than on growth conditions.

Genetic and environmental factors are well-studied influences on phenotype; however, time is a variable that is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional oscillation in a yeast continuous culture system with ~2 and ~4 h periods. We mapped the global patterns of transcriptional oscillations into a 3D map to represent different cellular phenotypes of redox cycles. This map shows the dynamic nature of gene expression in that transcripts are ordered and coupled to each other through time and concentration space. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. When oscillation period lengthened, the peak to trough ratio of transcripts increased and the fraction of cells in the unbudded (G0/G1) phase of the cell division cycle increased. Decreasing the glucose level in the culture media was one way to increase the redox cycle, possibly from changes in metabolic flux. The period may be responding to lower glucose levels by increasing the fraction of cells in G1 and reducing S-phase gating so that cells can spend more time in catabolic processes. Our results support that gene transcripts are coordinated with metabolic functions and the cell division cycle.

The finding of a genome-wide oscillation in transcription that gates cells into S phase and coordinates mitochondrial and metabolic functions has altered our understanding of how the cell cycle is timed and how stable cellular phenotypes are maintained. Here we present the evidence and arguments in support of the idea that everything oscillates, and the rationale for viewing the cell as an attractor from which deterministic noise can be tuned by appropriate coupling among the many feedback loops, or regulons, that make up the transcriptional-respiratory attractor cycle. The existence of this attractor also explains many of the dynamic macroscopic properties of the cell cycle and appears to be the timekeeping oscillator in both cell cycles and circadian rhythms. The path taken by this primordial oscillator in the course of differentiation or drug response may involve period-doubling behavior. Evidence for a relatively high-frequency timekeeping oscillator in yeast and mammalian cells comes from expression array analysis, and GC/MS in the case of yeast, and primarily from macroscopic measures of phase response to perturbation in the case of mammalian cells. Low-amplitude, genome-wide oscillations, a ubiquitous but often unrecognized attribute of phenotype, may be a source of seemingly intractable biological noise in microarray and proteomic studies. These oscillations in transcript and protein levels and the repeated cycles of synthesis and degradation they require, represent a high energy cost to the cell which must, from an evolutionary point of view, be recovered as essential information. We suggest that the information contained in this genome-wide oscillation is the dynamic code that organizes a stable phenotype from an otherwise passive genome.

Pathogenic bacteria are generally studied as a single strain under ideal growing conditions, although these conditions are not the norm in the environments in which pathogens typically proliferate. In this investigation, a representative microbial community along with Escherichia coli O157:H7, a model pathogen, was studied in three environments in which such a pathogen could be found: a human colon, a septic tank, and groundwater. Each of these systems was built in the lab in order to retain the physical/ chemical and microbial complexity of the environments while maintaining control of the feed into the models. The microbial community in the colon was found to have a high percentage of bacteriodetes and firmicutes, while the septic tank and groundwater systems were composed mostly of proteobacteria. The introduction of E. coli O157:H7 into the simulated systems elicited a shift in the structures and phenotypic cell characteristics of the microbial communities. The fate and transport of the microbial community with E. coli O157:H7 were found to be significantly different from those of E. coli O157:H7 studied as a single isolate, suggesting that the behavior of the organism in the environment was different from that previously conceived. The findings in this study clearly suggest that to gain insight into the fate of pathogens, cells should be grown and analyzed under conditions simulating those of the environment in which the pathogens are present.

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Sharpshooter leafhoppers (Hemiptera: Cicadellidae: Cicadellinae) are important vectors of the plant pathogenic bacterium Xylella fastidiosa Wells et al. (Xanthomonadales: Xanthomonadaceae). This pathogen causes economically significant diseases in olive, citrus, and grapes on multiple continents. Bacterial acquisition and inoculation mechanisms are linked to X. fastidiosa biofilm formation and fluid dynamics in the functional foregut of sharpshooters, which together result in egestion (expulsion) of fluids likely carrying bacteria. One key X. fastidiosa vector is the blue–green sharpshooter, Graphocephala atropunctata (Signoret, 1854). Herein, a 3D model of the blue–green sharpshooter functional foregut is derived from a meta-analysis of published microscopy images. The model is used to illustrate preexisting and newly defined anatomical terminology that is relevant for investigating fluid dynamics in the functional foregut of sharpshooters. The vivid 3D illustrations herein and supplementary interactive 3D figures are suitable resources for multidisciplinary researchers who may be unfamiliar with insect anatomy. The 3D model can also be used in future fluid dynamic simulations to better understand acquisition, retention, and inoculation of X. fastidiosa. Improved understanding of these processes could lead to new targets for preventing diseases caused by X. fastidiosa.

The aim of this investigation is to determine the effect that growth solution has on the cell surface properties and transport behavior of eleven Escherichia coli isolates through saturated porous media. The two growth solutions used were a standard laboratory growth medium (LB) and a dairy manure extract solution. In general, cells grown in manure extract were more hydrophobic, had a more negative zeta potential, had lower amounts of surface macromolecules, and had lower attachment efficiencies than isolates grown in LB. An inverse relationship between the natural log of zeta potential and the attachment efficiency of the isolates for the cells grown in LB media was the only statistically significant correlation observed between transport behavior and cell characteristics of the isolates. This study shows the need to consider growth conditions when studying bacteria to better mimic the environmental stresses that bacteria undergo in the natural environment. This approach could lead to a better understanding of the behavior of manure-derived bacteria in aquatic and terrestrial environments.