Hybrid Model of Bacterial Biofilm Growth

Biofilm characterization and dynamic simulation of advanced rope media reactor for the treatment of primary effluent

Biofilm modeling is inherently complex, often requiring multiple assumptions and simplifications. In biofilm modeling, default or literature-based values in biofilm systems are usually used to estimate biofilm parameters, including boundary layer, biofilm density, thickness, attachment, and detachment rates. This study aimed to characterize and model the biofilm of a specific rope-type fixed media system, removing carbon and total inorganic nitrogen, coupled with sensitivity analysis. Among the five model parameters, the sensitivity analysis of this study showed that boundary layer thickness is the most influential parameter for predicting effluent ammonia and nitrate concentrations, and biofilm density is most sensitive with respect to effluent chemical oxygen demand (COD). The least sensitive parameter is the detachment rate. Based on the calculated mean absolute error (MAE) and root mean squared error (RMSE), the calibrated BioCord fixed-film reactor (BFFR) model accurately predicted effluent ammonium and dissolved oxygen (DO) in the continuously aerated bench-scale reactor (R1) and failed to predict well in the intermittently aerated bench-scale reactor (R2). RMSE values calculated for NH3-N and DO in R1 are 0.95 and 0.53 mg/L, respectively. In the BioCord pilot plant's case, ammonium-N predicted by the model fit the measured values well, while it overpredicted DO concentrations. PRACTITIONER POINTS: Fixed biofilm BioCord reactors were studied for primary effluent treatment. A methodology was developed to characterize biofilms. Boundary layer thickness is the most influential parameter for predicting effluent ammonia and nitrate concentrations. Biofilm density is the most sensitive parameter with respect to effluent COD. The calibrated BFFR model can predict effluent ammonium, nitrite, and nitrate-nitrogen.

Contrasting Dynamics of Intracellular and Extracellular Antibiotic Resistance Genes in Response to Nutrient Variations in Aquatic Environments

The propagation of antibiotic resistance in environments, particularly aquatic environments that serve as primary pathways for antibiotic resistance genes (ARGs), poses significant health risks. The impact of nutrients, as key determinants of bacterial growth and metabolism, on the propagation of ARGs, particularly extracellular ARGs (eARGs), remains poorly understood. In this study, we collected microorganisms from the Yangtze River and established a series of microcosms to investigate how variations in nutrient levels and delivery frequency affect the relative abundance of intracellular ARGs (iARGs) and eARGs in bacterial communities. Our results show that the relative abundance of 7 out of 11 representative eARGs in water exceeds that of iARGs, while 8 iARGs dominate in biofilms. Notably, iARGs and eARGs consistently exhibited opposite responses to nutrient variation. When nutrient levels increased, iARGs in the water also increased, with the polluted group (COD = 333.3 mg/L, COD:N:P = 100:3:0.6, m/m) and the eutrophic group (COD = 100 mg/L, COD:N:P = 100:25:5, m/m) showing 1.2 and 3.2 times higher levels than the normal group (COD = 100 mg/L, COD:N:P = 100:10:2, m/m), respectively. In contrast, eARGs decreased by 6.7% and 8.4% in these groups. On the other hand, in biofilms, higher nutrient levels led to an increase in eARGs by 1.5 and 1.7 times, while iARGs decreased by 17.5% and 50.1% in the polluted and eutrophic groups compared to the normal group. Moreover, while increasing the frequency of nutrient delivery (from 1 time/10 d to 20 times/10 d) generally did not favor iARGs in either water or biofilm, it selectively enhanced eARGs in both. To further understand these dynamics, we developed an ARGs-nutrient model by integrating the Lotka-Volterra and Monod equations. The results highlight the complex interplay of bacterial growth, nutrient availability, and mechanisms such as horizontal gene transfer and secretion influencing ARGs' propagation, driving the opposite trend between these two forms of ARGs. This contrasting response between iARGs and eARGs contributes to a dynamic balance that stabilizes bacterial resistance levels amid nutrient fluctuations. This study offers helpful implications regarding the persistence of bacterial resistance in the environment.

Migration of surface-associated microbial communities in spaceflight habitats

Astronauts are spending longer periods locked up in ships or stations for scientific and exploration spatial missions. The International Space Station (ISS) has been inhabited continuously for more than 20 years and the duration of space stays by crews could lengthen with the objectives of human presence on the moon and Mars. If the environment of these space habitats is designed for the comfort of astronauts, it is also conducive to other forms of life such as embarked microorganisms. The latter, most often associated with surfaces in the form of biofilm, have been implicated in significant degradation of the functionality of pieces of equipment in space habitats. The most recent research suggests that microgravity could increase the persistence, resistance and virulence of pathogenic microorganisms detected in these communities, endangering the health of astronauts and potentially jeopardizing long-duration manned missions. In this review, we describe the mechanisms and dynamics of installation and propagation of these microbial communities associated with surfaces (spatial migration), as well as long-term processes of adaptation and evolution in these extreme environments (phenotypic and genetic migration), with special reference to human health. We also discuss the means of control envisaged to allow a lasting cohabitation between these vibrant microscopic passengers and the astronauts.

50-year history and perspective on biomechanics of swimming microorganisms: Part II. Collective behaviours

The paired review papers in Parts I and II describe the 50-year history of research on the biomechanics of swimming microorganisms and its prospects in the next 50 years. Parts I and II are divided not by the period covered, but by the content of the research: Part I explains the behaviours of individual microorganisms, and Part II explains collective behaviour. In the 1990s, the description of microbial suspensions as a continuum progressed, and macroscopic flow structures such as bioconvection were analysed. The continuum model was later extended to analyse various phenomena such as flow induced trapping of microorganisms and accumulation of cells at interfaces. In the 2000s, the collective behaviour of swimming microorganisms came into the limelight, and physicists as well as biomechanics researchers carried out many studies probing microorganism collectivity. In particular, research on the turbulence-like flow structure of dense bacterial suspensions has led to dramatic developments in the field of microbial biomechanics. Efforts to bridge the cellular scale to the macroscopic scale by extracting macroscopic physical quantities from the microstructure of cell suspensions are also underway. This Part II reviews these collective behaviours of swimming microorganisms and discusses future prospects of the field.

Agent-Based Modeling of Microbial Communities

Microbial communities are complex living systems that populate the planet with diverse functions and are increasingly harnessed for practical human needs. To deepen the fundamental understanding of their organization and functioning as well as to facilitate their engineering for applications, mathematical modeling has played an increasingly important role. Agent-based models represent a class of powerful quantitative frameworks for investigating microbial communities because of their individualistic nature in describing cells, mechanistic characterization of molecular and cellular processes, and intrinsic ability to produce emergent system properties. This review presents a comprehensive overview of recent advances in agent-based modeling of microbial communities. It surveys the state-of-the-art algorithms employed to simulate intracellular biomolecular events, single-cell behaviors, intercellular interactions, and interactions between cells and their environments that collectively serve as the driving forces of community behaviors. It also highlights three lines of applications of agent-based modeling, namely, the elucidation of microbial range expansion and colony ecology, the design of synthetic gene circuits and microbial populations for desired behaviors, and the characterization of biofilm formation and dispersal. The review concludes with a discussion of existing challenges, including the computational cost of the modeling, and potential mitigation strategies.

Antibiotic susceptibility test under a linear concentration gradient using travelling surface acoustic waves

An efficient and accurate antibiotic susceptibility test (AST) is indispensable for measuring the antimicrobial resistance of pathogenic bacteria. A minimal inhibitory concentration (MIC) can be obtained without performing repeated dilutions of the antibiotic by forming a linear antibiotic concentration gradient in a microfluidic channel. We demonstrated a device designed to use travelling surface acoustic waves (TSAWs) to enable a rapid formation of an antibiotic gradient in a few seconds. The TSAWs produced by a focused interdigital transducer deposited on the surface of a piezoelectric (LiNbO₃) substrate generated an acoustic streaming flow inside a microfluidic channel, which mixed confluent streams of antibiotics in a controlled fashion. The growth of bacteria exposed to the antibiotic gradient was determined by measuring the MIC, which was used as an indicator of the effectiveness of the AST. The concentration gradient produced using our device was linear, a feature that enhanced the reliability of measurements throughout the microchannel. Two ASTs, namely Pseudomonas aeruginosa against gentamicin and levofloxacin were chosen for the case of slowly proliferating bacteria, and one AST, namely Escherichia coli against gentamicin, were chosen for the rapidly proliferating case. Appropriate antibiotic doses for Pseudomonas aeruginosa and Escherichia coli were each obtained in an efficient manner.

Mechanics of biofilms formed of bacteria with fimbriae appendages

Gram-negative bacteria, as well as some Gram-positive bacteria, possess hair-like appendages known as fimbriae, which play an important role in adhesion of the bacteria to surfaces or to other bacteria. Unlike the sex pili or flagellum, the fimbriae are quite numerous, with of order 1000 fimbriae appendages per bacterial cell. In this paper, a recently developed hybrid model for bacterial biofilms is used to examine the role of fimbriae tension force on the mechanics of bacterial biofilms. Each bacterial cell is represented in this model by a spherocylindrical particle, which interact with each other through collision, adhesion, lubrication force, and fimbrial force. The bacterial cells absorb water and nutrients and produce extracellular polymeric substance (EPS). The flow of water and EPS, and nutrient diffusion within these substances, is computed using a continuum model that accounts for important effects such as osmotic pressure gradient, drag force on the bacterial cells, and viscous shear. The fimbrial force is modeled using an outer spherocylinder capsule around each cell, which can transmit tensile forces to neighboring cells with which the fimbriae capsule collides. We find that the biofilm structure during the growth process is dominated by a balance between outward drag force on the cells due to the EPS flow away from the bacterial colony and the inward tensile fimbrial force acting on chains of cells connected by adhesive fimbriae appendages. The fimbrial force also introduces a large rotational motion of the cells and disrupts cell alignment caused by viscous torque imposed by the EPS flow. The current paper characterizes the competing effects of EPS drag and fimbrial force using a series of computations with different values of the ratio of EPS to bacterial cell production rate and different numbers of fimbriae per cell.