Continuum and discrete approach in modeling biofilm development and structure: a review

Simulation of head-tail biofilm streamer growth based on immersed boundary method

Biofilms are subjected to various forces in the fluid field, as a result, the biofilm forms a head-tail structure known as a streamer to reduce pressure differential resistance. To characterize biofilm growth in fluid, we establish a head-tail biofilm streamer growth model based on the immersed boundary method using MATLAB software, and simulate streamer growth in various environmental conditions to explore the factors affecting its growth. Firstly, we found that a higher flow velocity makes the streamer grow faster and thereby produce more biomass. Secondly, we explored the effect of the position of nutrient source on the streamer growth, found that when the nutrient source overlaps with the streamer, its length is longer than when the nutrient source and the streamer are mismatched. Further we found that the Young's modulus of the streamer also influences its growth length. Streamers with small Young's modulus were more likely to deform, making them grow longer than the streamers with large Young's modulus. Finally, we determined the relationship between the tail length and the head diameter of the streamer through mechanical analysis, and found that there is an optimal ratio of the tail length to the head diameter which exposes the streamer to the minimum drag in the fluid field.

A Hamilton principle-based model for diffusion-driven biofilm growth

Dense communities of bacteria, also known as biofilms, are ubiquitous in all of our everyday life. They are not only always surrounding us, but are also active inside our bodies, for example in the oral cavity. While some biofilms are beneficial or even necessary for human life, others can be harmful. Therefore, it is highly important to gain an in-depth understanding of biofilms which can be achieved by in vitro or in vivo experiments. Since these experiments are often time-consuming or expensive, in silico models have proven themselves to be a viable tool in assisting the description and analysis of these complicated processes. Current biofilm growth simulations are using mainly two approaches for describing the underlying models. The volumetric approach splits the deformation tensor into a growth and an elastic part. In this approach, the mass never changes, unless some additional constraints are enforced. The density-based approach, on the other hand, uses an evolution equation to update the growing tissue by adding mass. Here, the density stays constant, and no pressure is exerted. The in silico model presented in this work combines the two approaches. Thus, it is possible to capture stresses inside of the biofilm while adding mass. Since this approach is directly derived from Hamilton's principle, it fulfills the first and second law of thermodynamics automatically, which other models need to be checked for separately. In this work, we show the derivation of the model as well as some selected numerical experiments. The numerical experiments show a good phenomenological agreement with what is to be expected from a growing biofilm. The numerical behavior is stable, and we are thus capable of solving complicated boundary value problems. In addition, the model is very reactive to different input parameters, thereby different behavior of various biofilms can be captured without modifying the model.

Mass transfer in heterogeneous biofilms: Key issues in biofilm reactors and AI-driven performance prediction

Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.

The biophysical basis of bacterial colony growth

Bacteria often attach to surfaces and grow densely-packed communities called biofilms. As biofilms grow, they expand across the surface, increasing their surface area and access to nutrients. Thus, the overall growth rate of a biofilm is directly dependent on its "range expansion" rate. One factor that limits the range expansion rate is vertical growth; at the biofilm edge there is a direct trade-off between horizontal and vertical growth-the more a biofilm grows up, the less it can grow out. Thus, the balance of horizontal and vertical growth impacts the range expansion rate and, crucially, the overall biofilm growth rate. However, the biophysical connection between horizontal and vertical growth remains poorly understood, due in large part to difficulty in resolving biofilm shape with sufficient spatial and temporal resolution from small length scales to macroscopic sizes. Here, we experimentally show that the horizontal expansion rate of bacterial colonies is strongly coupled to vertical expansion via the contact angle at the biofilm edge. Using white light interferometry, we measure the three-dimensional surface morphology of growing colonies, and find that small colonies are surprisingly well-described as spherical caps. At later times, nutrient diffusion and uptake prevent the tall colony center from growing exponentially. However, the colony edge always has a region short enough to grow exponentially; the size and shape of this region, characterized by its contact angle, along with cellular doubling time, determines the range expansion rate. We found that the geometry of the exponentially growing biofilm edge is well-described as a spherical-cap-napkin-ring, i.e., a spherical cap with a cylindrical hole in its center (where the biofilm is too tall to grow exponentially). We derive an exact expression for the spherical-cap-napkin-ring-based range expansion rate; further, to first order, the expansion rate only depends on the colony contact angle, the thickness of the exponentially growing region, and the cellular doubling time. We experimentally validate both of these expressions. In line with our theoretical predictions, we find that biofilms with long cellular doubling times and small contact angles do in fact grow faster than biofilms with short cellular doubling times and large contact angles. Accordingly, sensitivity analysis shows that biofilm growth rates are more sensitive to their contact angles than to their cellular growth rates. Finally, we show that a simple biophysical model connecting vertical and horizontal growth dynamics can reproduce the above phenomena, suggesting that the spherical cap and spherical cap napkin ring shapes emerge due to the biophysical consequences of diffusion-limited growth. Thus, to understand the fitness of a growing biofilm, one must account for its shape, not just its cellular doubling time.

A Mathematical Model of Diel Activity and Long Time Survival in Phototrophic Mixed-Species Subaerial Biofilms

Subaerial biofilms (SAB) are intricate microbial communities living on terrestrial surfaces, of interest in a variety of contexts including cultural heritage preservation, microbial ecology, biogeochemical cycling, and biotechnology. Here we propose a mathematical model aimed at better understanding the interplay between cyanobacteria and heterotrophic bacteria, common microbial SAB constituents, and their mutual dependence on local environmental conditions. SABs are modeled as thin mixed biofilm-liquid water layers sitting on stone. A system of ordinary differential equations regulates the dynamics of key SAB components: cyanobacteria, heterotrophs, polysaccharides and decayed biomass, as well as cellular levels of organic carbon, nitrogen and energy. These components are interconnected through a network of energetically dominant metabolic pathways, modeled with limitation terms reflecting the impact of biotic and abiotic factors. Daily cylces of temperature, humidity, and light intensity are considered as input model variables that regulate microbial activity by influencing water availability and metabolic kinetics. Relevant physico-chemical processes, including pH regulation, further contribute to a description of the SAB ecology. Numerical simulations explore the dynamics of SABs in a real-world context, revealing distinct daily activity periods shaped by water activity and light availability, as well as longer time scale survivability conditions. Results also suggest that heterotrophs could play a substantial role in decomposing non-volatile carbon compounds and regulating pH, thus influencing the overall composition and stability of the biofilm.

Pseudomonas aeruginosa Biofilm Lifecycle: Involvement of Mechanical Constraints and Timeline of Matrix Production

Pseudomonas aeruginosa is an opportunistic pathogen causing acute and chronic infections, especially in immunocompromised patients. Its remarkable adaptability and resistance to various antimicrobial treatments make it difficult to eradicate. Its persistence is enabled by its ability to form a biofilm. Biofilm is a community of sessile micro-organisms in a self-produced extracellular matrix, which forms a scaffold facilitating cohesion, cell attachment, and micro- and macro-colony formation. This lifestyle provides protection against environmental stresses, the immune system, and antimicrobial treatments, and confers the capacity for colonization and long-term persistence, often characterizing chronic infections. In this review, we retrace the events of the life cycle of P. aeruginosa biofilm, from surface perception/contact to cell spreading. We focus on the importance of extracellular appendages, mechanical constraints, and the kinetics of matrix component production in each step of the biofilm life cycle.

Modelling Plasmid-Mediated Horizontal Gene Transfer in Biofilms

In this study, we present a mathematical model for plasmid spread in a growing biofilm, formulated as a nonlocal system of partial differential equations in a 1-D free boundary domain. Plasmids are mobile genetic elements able to transfer to different phylotypes, posing a global health problem when they carry antibiotic resistance factors. We model gene transfer regulation influenced by nearby potential receptors to account for recipient-sensing. We also introduce a promotion function to account for trace metal effects on conjugation, based on literature data. The model qualitatively matches experimental results, showing that contaminants like toxic metals and antibiotics promote plasmid persistence by favoring plasmid carriers and stimulating conjugation. Even at higher contaminant concentrations inhibiting conjugation, plasmid spread persists by strongly inhibiting plasmid-free cells. The model also replicates higher plasmid density in biofilm's most active regions.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Modelling biofilm development: The importance of considering the link between EPS distribution, detachment mechanisms and physical properties

In industry, treatments against biofilms need to be optimized and, in the wastewater treatment field, biofilm composition needs to be controlled. Therefore, describing the biochemical and physical structures of biofilms is now required to better understand the influence of operating parameters and treatment on biofilms. The present study aims to investigate how growth conditions influence EPS composition, biofilm physical properties and volume detachment using a 1D biofilm model. Two types of EPS are considered in the present model, proteins and polysaccharides. The main hypotheses are that: (i) the production of polysaccharides occurs mainly under strong nutrient limitation(s) while the production of proteins is coupled to both the substrate uptake rate and the lysis process; (ii) the local biofilm porosity depends on the local biofilm composition. Both volume and surface detachment occur in biofilms and volume detachment extent depends on the biofilm local cohesion and thus on the local composition of biofilms for a given shear stress. The model is based on experimental trends and aims to represent these observations on the basis of biochemical and physical processes. Four case studies covering a wide range of contrasting growth conditions such as different COD/N ratios, applied SOLR and shear stresses are investigated. The model predicts how the biochemical and physical biofilm structures change as a result of contrasting growth conditions. More precisely simulation results are in good agreement with the main experimental observations reported in the literature, such as: (i) a strong nitrogen limitation of growth induces an important accumulation of polysaccharides leading to a more porous and homogenous biofilm, (ii) a high applied surface organic loading load allows to obtain a high biofilm thickness, (iii) a strong shear stress applied during the biofilm growth leads to a reduction of the biofilm thickness and to a consolidation of the biofilm structure. Overall, this model represents a relevant decision tool for the selection of appropriate enzymatic treatments in the context of negative biofilm control. From our results, it appears that protease based treatments should be more appropriate for biofilms developed under low COD/N ratios (about 20 gCOD/gN) whereas both glucosidases and proteases based treatments should be more appropriate for biofilms developed under high COD/N ratio (about 70 gCOD/gN). In addition, the model could be useful for other applications such as resource recovery in biofilms or granules, and help to better understand biological membrane fouling.

Residual cells and nutrient availability guide wound healing in bacterial biofilms

Biofilms are multicellular heterogeneous bacterial communities characterized by social-like division of labor, and remarkable robustness with respect to external stresses. Increasingly often an analogy between biofilms and arguably more complex eukaryotic tissues is being drawn. One illustrative example of where this analogy can be practically useful is the process of wound healing. While it has been extensively studied in eukaryotic tissues, the mechanism of wound healing in biofilms is virtually unexplored. Combining experiments in Bacillus subtilis bacteria, a model organism for biofilm formation, and a lattice-based theoretical model of biofilm growth, we studied how biofilms recover after macroscopic damage. We suggest that nutrient gradients and the abundance of proliferating cells are key factors augmenting wound closure. Accordingly, in the model, cell quiescence, nutrient fluxes, and biomass represented by cells and self-secreted extracellular matrix are necessary to qualitatively recapitulate the experimental results for damage repair. One of the surprising experimental findings is that residual cells, persisting in a damaged area after removal of a part of the biofilm, prominently affect the healing process. Taken together, our results outline the important roles of nutrient gradients and residual cells on biomass regrowth on macroscopic scales of the whole biofilm. The proposed combined experiment-simulation framework opens the way to further investigate the possible relation between wound healing, cell signaling and cell phenotype alternation in the local microenvironment of the wound.

Evolutionary Epidemiology Consequences of Trait-Dependent Control of Heterogeneous Parasites

AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

Interfacial morphodynamics of proliferating microbial communities

In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.

Pharmacodynamic Model of the Dynamic Response of Pseudomonas aeruginosa Biofilms to Antibacterial Treatments

Accurate pharmacokinetic-pharmacodynamic (PK-PD) models of biofilm treatment could be used to guide formulation and administration strategies to better control bacterial lung infections. To this end, we developed a detailed pharmacodynamic model of P. aeruginosa treatment with the front-line antibiotics, tobramycin and colistin, and validated it on a detailed dataset of killing dynamics. A compartmental model structure was developed in which the key features are the diffusion of the drug through a boundary layer to the bacteria, concentration-dependent interactions with bacteria, and the passage of the bacteria through successive transit states before death. The number of transit states employed was greater for tobramycin, which is a ribosomal inhibitor, than for colistin, which disrupts bacterial membranes. For both drugs, the experimentally observed delay in the killing of bacteria following drug exposure was consistent with the sum of the diffusion time and the time for passage through the transit states. For each drug, the PD model with a single set of parameters described data across a ten-fold range of concentrations and for both continuous and transient exposure protocols, as well as for combined drug treatments. The ability to predict drug response over a range of administration protocols allows this PD model to be integrated with PK descriptions to describe in vivo antibiotic response dynamics and to predict drug delivery strategies for the improved control of bacterial lung infections.

Structure-Thermodynamic Relationship of a Polysaccharide Gel (Alginate) as a Function of Water Content and Counterion Type (Na vs Ca)

Biofilms are the predominant mode of microbial life on Earth, and so a deep understanding of microbial communities─and their impacts on environmental processes─requires a firm understanding of biofilm properties. Because of the importance of biofilms to their microbial inhabitants, microbes have evolved different ways of engineering and reconfiguring the matrix of extracellular polymeric substances (EPS) that constitute the main non-living component of biofilms. This ability makes it difficult to distinguish between the biotic and abiotic origins of biofilm properties. An important route toward establishing this distinction has been the study of simplified models of the EPS matrix. This study builds on such efforts by using atomistic simulations to predict the nanoscale (≤10 nm scale) structure of a model EPS matrix and the sensitivity of this structure to interpolymer interactions and water content. To accomplish this, we use replica exchange molecular dynamics (REMD) simulations to generate all-atom configurations of ten 3.4 kDa alginate polymers at a range of water contents and Ca-Na ratios. Simulated systems are solvated with explicitly modeled water molecules, which allows us to capture the discrete structure of the hydrating water and to examine the thermodynamic stability of water in the gels as they are progressively dehydrated. Our primary findings are that (i) the structure of the hydrogels is highly sensitive to the identity of the charge-compensating cations, (ii) the thermodynamics of water within the gels (specific enthalpy and free energy) are, surprisingly, only weakly sensitive to cation identity, and (iii) predictions of the differential enthalpy and free energy of hydration include a short-ranged enthalpic term that promotes hydration and a longer-ranged (presumably entropic) term that promotes dehydration, where short and long ranges refer to distances shorter or longer than ∼0.6 nm between alginate strands.

A transient biological fouling model for constant flux microfiltration

Microfiltration is a widely used engineering technology for fresh water production and water treatment. The major concern in many applications is the formation of a biological fouling layer leading to increased hydraulic resistance and flux decline during membrane operations. The growth of bacteria constituting such a biological layer implicates the formation of a multispecies biofilm and the consequent increase of operational costs for reactor management and cleaning procedures. To predict the biofouling evolution, a mono-dimensional continuous free boundary model describing biofilm dynamics and EPS production in different operational phases of microfiltration systems has been well studied. The biofouling growth is governed by a system of hyperbolic PDEs. Substrate dynamics are modeled through parabolic equations accounting for diffusive and advective fluxes generated during the filtration process. The free boundary evolution depends on both microbial growth and detachment processes. What is not addressed is the interplay between biofilm dynamics, filtration, and water recovery. In this study, filtration and biofilm growth modeling principles have been coupled for the definition of an original mathematical model able to reproduce biofouling evolution in membrane systems. The model has been solved numerically to simulate biologically relevant conditions, and to investigate the hydraulic behavior of the membrane. It has been calibrated and validated using lab-scale data. Numerical results accurately predicted the pressure drop occurring in the microfiltration system. A calibrated model can give information for optimization protocols as well as fouling prevention strategies.

Mathematical modelling of an intermittent anoxic/aerobic MBBR: Estimation of nitrification rates and energy savings

This study aimed at modelling the performance of a novel MBBR configuration, named A/O-MBBR, comprised of a pre-anoxic reactor, with an HRT of 4.5 h, coupled with an intermittent anoxic/aerobic MBBR (HRT = 6.8 h). The lab-scale system was fed with municipal wastewater with an average influent Total Ammonia Nitrogen (TAN) and total COD (TCOD) concentrations of 46 mg of TAN-N L^-1 and 310 mg TCOD L^-1. During the whole experimental period, TAN removal efficiency was always higher than 96%; denitrification was also very effective, achieving nitrate and nitrite concentrations in the effluent both lower than 5 mg NO_x-N L^-1 on average. Moreover, TCOD average removal efficiency was equal to 85%. Modelling was performed to investigate the nitrification efficacy enhancement; to this aim, a biofilm model was developed, adopting the equations for mixed-culture biofilms and the Activated Model Sludge n°1 (ASM1) for the biological processes rates. The model allowed to determine the maximum uptake rate for autotrophic growth (μ_A was 2.5 d^-1) and the semisaturation constant (K_OA was 0.2 mg O₂ L^-1), suggesting that the nitrification process was 3-fold faster than average and very effective at low oxygen concentrations. The model estimated that about 85% of TAN was removed by the biofilm and only the remaining part by suspended biomass in the bulk liquid. Finally, it was assessed that the A/O-MBBR configuration allowed for a 45-60% savings of the energy requirement compared to a Benchmark WWTP layout.

Morphological instability and roughening of growing 3D bacterial colonies

The morphogenesis of two-dimensional bacterial colonies has been well studied. However, little is known about the colony morphologies of bacteria growing in three dimensions, despite the prevalence of three-dimensional environments (e.g., soil, inside hosts) as natural bacterial habitats. Using experiments on bacteria in granular hydrogel matrices, we find that dense multicellular colonies growing in three dimensions undergo a common morphological instability and roughen, adopting a characteristic broccoli-like morphology when they exceed a critical size. Analysis of a continuum “active fluid” model of the expanding colony reveals that this behavior originates from an interplay of competition for nutrients with growth-driven colony expansion, both of which vary spatially. These results shed light on the fundamental biophysical principles underlying growth in three dimensions.

How do growing bacterial colonies get their shapes? While colony morphogenesis is well studied in two dimensions, many bacteria grow as large colonies in three-dimensional (3D) environments, such as gels and tissues in the body or subsurface soils and sediments. Here, we describe the morphodynamics of large colonies of bacteria growing in three dimensions. Using experiments in transparent 3D granular hydrogel matrices, we show that dense colonies of four different species of bacteria generically become morphologically unstable and roughen as they consume nutrients and grow beyond a critical size—eventually adopting a characteristic branched, broccoli-like morphology independent of variations in the cell type and environmental conditions. This behavior reflects a key difference between two-dimensional (2D) and 3D colonies; while a 2D colony may access the nutrients needed for growth from the third dimension, a 3D colony inevitably becomes nutrient limited in its interior, driving a transition to unstable growth at its surface. We elucidate the onset of the instability using linear stability analysis and numerical simulations of a continuum model that treats the colony as an “active fluid” whose dynamics are driven by nutrient-dependent cellular growth. We find that when all dimensions of the colony substantially exceed the nutrient penetration length, nutrient-limited growth drives a 3D morphological instability that recapitulates essential features of the experimental observations. Our work thus provides a framework to predict and control the organization of growing colonies—as well as other forms of growing active matter, such as tumors and engineered living materials—in 3D environments.

Exploring the Function of Quorum Sensing Regulated Biofilms in Biological Wastewater Treatment: A Review

Quorum sensing (QS), a type of bacterial cell–cell communication, produces autoinducers which help in biofilm formation in response to cell population density. In this review, biofilm formation, the role of QS in biofilm formation and development with reference to biological wastewater treatment are discussed. Autoinducers, for example, acyl-homoserine lactones (AHLs), auto-inducing oligo-peptides (AIPs) and autoinducer 2, present in both Gram-negative and Gram-positive bacteria, with their mechanism, are also explained. Over the years, wastewater treatment (WWT) by QS-regulated biofilms and their optimization for WWT have gained much attention. This article gives a comprehensive review of QS regulation methods, QS enrichment methods and QS inhibition methods in biological waste treatment systems. Typical QS enrichment methods comprise adding QS molecules, adding QS accelerants and cultivating QS bacteria, while typical QS inhibition methods consist of additions of quorum quenching (QQ) bacteria, QS-degrading enzymes, QS-degrading oxidants, and QS inhibitors. Potential applications of QS regulated biofilms for WWT have also been summarized. At last, the knowledge gaps present in current researches are analyzed, and future study requirements are proposed.

Exploring the role of microbial biofilm for industrial effluents treatment

Biofilm formation on biotic or abiotic surfaces is caused by microbial cells of a single or heterogeneous species. Biofilm protects microbes from stressful environmental conditions, toxic action of chemicals, and antimicrobial substances. Quorum sensing (QS) is the generation of autoinducers (AIs) by bacteria in a biofilm to communicate with one other. QS is responsible for the growth of biofilm, synthesis of exopolysaccharides (EPS), and bioremediation of environmental pollutants. EPS is used for wastewater treatment due to its three-dimensional matrix which is composed of proteins, polysaccharides, humic-like substances, and nucleic acids. Autoinducers mediate significantly the degradation of environmental pollutants. Acyl-homoserine lactone (AHL) producing bacteria as well as quorum quenching enzyme or bacteria can effectively improve the performance of wastewater treatment. Biofilms-based reactors due to their economic and ecofriendly nature are used for the treatment of industrial wastewaters. Electrodes coated with electro-active biofilm (EAB) which are obtained from sewage sludge, activated sludge, or industrial and domestic effluents are getting popularity in bioremediation. Microbial fuel cells are involved in wastewater treatment and production of energy from wastewater. Synthetic biological systems such as genome editing by CRISPR-Cas can be used for the advanced bioremediation process through modification of metabolic pathways in quorum sensing within microbial communities. This narrative review discusses the impacts of QS regulatory approaches on biofilm formation, extracellular polymeric substance synthesis, and role of microbial community in bioremediation of pollutants from industrial effluents.

Validated In Silico Model for Biofilm Formation in Escherichia coli

Using Escherichia coli as the representative biofilm former, we report here the development of an in silico model built by simulating events that transform a free-living bacterial entity into self-encased multicellular biofilms. Published literature on ∼300 genes associated with pathways involved in biofilm formation was curated, static maps were created, and suitably interconnected with their respective metabolites using ordinary differential equations. Precise interplay of genetic networks that regulate the transitory switching of bacterial growth pattern in response to environmental changes and the resultant multicomponent synthesis of the extracellular matrix were appropriately represented. Subsequently, the in silico model was analyzed by simulating time-dependent changes in the concentration of components by using the R and python environment. The model was validated by simulating and verifying the impact of key gene knockouts (KOs) and systematic knockdowns on biofilm formation, thus ensuring the outcomes were comparable with the reported literature. Similarly, specific gene KOs in laboratory and pathogenic E. coli were constructed and assessed. MiaA, YdeO, and YgiV were found to be crucial in biofilm development. Furthermore, qRT-PCR confirmed the elevation of expression in biofilm-forming clinical isolates. Findings reported in this study offer opportunities for identifying biofilm inhibitors with applications in multiple industries. The application of this model can be extended to the health care sector specifically to develop novel adjunct therapies that prevent biofilms in medical implants and reduce emergence of biofilm-associated resistant polymicrobial-chronic infections. The in silico framework reported here is open source and accessible for further enhancements.

Thin-film lubrication model for biofilm expansion under strong adhesion

Understanding microbial biofilm growth is important to public health because biofilms are a leading cause of persistent clinical infections. In this paper, we develop a thin-film model for microbial biofilm growth on a solid substratum to which it adheres strongly. We model biofilms as two-phase viscous fluid mixtures of living cells and extracellular fluid. The model explicitly tracks the movement, depletion, and uptake of nutrients and incorporates cell proliferation via a nutrient-dependent source term. Notably, our thin-film reduction is two dimensional and includes the vertical dependence of cell volume fraction. Numerical solutions show that this vertical dependence is weak for biologically feasible parameters, reinforcing results from previous models in which this dependence was neglected. We exploit this weak dependence by writing and solving a simplified one-dimensional model that is computationally more efficient than the full model. We use both the one- and two-dimensional models to predict how model parameters affect expansion speed and biofilm thickness. This analysis reveals that expansion speed depends on cell proliferation, nutrient availability, cell-cell adhesion on the upper surface, and slip on the biofilm-substratum interface. Our numerical solutions provide a means to qualitatively distinguish between the extensional flow and lubrication regimes, and quantitative predictions that can be tested in future experiments.

Multiscale Modelling of De Novo Anaerobic Granulation

A multiscale mathematical model is presented to describe de novo granulation, and the evolution of multispecies granular biofilms, in a continuously fed bioreactor. The granule is modelled as a spherical free boundary domain with radial symmetry. The equation governing the free boundary is derived from global mass balance considerations and takes into account the growth of sessile biomass as well as exchange fluxes with the bulk liquid. Starting from a vanishing initial value, the expansion of the free boundary is initiated by the attachment process, which depends on the microbial species concentrations within the bulk liquid and their specific attachment velocity. Nonlinear hyperbolic PDEs model the growth of the sessile microbial species, while quasi-linear parabolic PDEs govern the dynamics of substrates and invading species within the granular biofilm. Nonlinear ODEs govern the evolution of soluble substrates and planktonic biomass within the bulk liquid. The model is applied to an anaerobic, granular-based bioreactor system, and solved numerically to test its qualitative behaviour and explore the main aspects of de novo anaerobic granulation: ecology, biomass distribution, relative abundance, dimensional evolution of the granules and soluble substrates, and planktonic biomass dynamics within the bioreactor. The numerical results confirm that the model accurately describes the ecology and the concentrically layered structure of anaerobic granules observed experimentally, and that it can predict the effects on the process of significant factors, such as influent wastewater composition; granulation properties of planktonic biomass; biomass density; detachment intensity; and number of granules.

Development and Quantitation of Pseudomonas aeruginosa Biofilms after in vitro Cultivation in Flow-reactors

Characterization of biofilm formation and metabolic activities is critical to investigating biofilm interactions with environmental factors and illustrating biofilm regulatory mechanisms. An appropriate in vitro model that mimics biofilm in vivo habitats therefore demands accurate quantitation and investigation of biofilm-associated activities. Current methodologies commonly involve static biofilm setups (such as biofilm assays in microplates, bead biofilms, or biofilms on glass-slides) and fluidic flow biofilm systems (such as drip-flow biofilm reactors, 3-channel biofilm reactors, or tubing biofilm reactors). Continuous flow systems take into consideration the contribution of hydrodynamic shear forces, nutrient supply, and physical transport of dispersed cells, which define the habitat for biofilm development in most natural and engineered systems. This protocol describes the assembly of 3 flow-system setups to cultivate Pseudomonas aeruginosa PAO1 and Shewanella oneidensis MR-1 model biofilms, including the respective quantitation and observation approaches. The standardized flow systems promise productive and reproducible biofilm experimental results, which can be further modified according to specific research projects.

Biofilm viscoelasticity and nutrient source location control biofilm growth rate, migration rate, and morphology in shear flow

We present a numerical model to simulate the growth and deformation of a viscoelastic biofilm in shear flow under different nutrient conditions. The mechanical interaction between the biofilm and the fluid is computed using the Immersed Boundary Method with viscoelastic parameters determined a priori from measurements reported in the literature. Biofilm growth occurs at the biofilm-fluid interface by a stochastic rule that depends on the local nutrient concentration. We compare the growth, migration, and morphology of viscoelastic biofilms with a common relaxation time of 18 min over the range of elastic moduli 10-1000 Pa in different nearby nutrient source configurations. Simulations with shear flow and an upstream or a downstream nutrient source indicate that soft biofilms grow more if nutrients are downstream and stiff biofilms grow more if nutrients are upstream. Also, soft biofilms migrate faster than stiff biofilms toward a downstream nutrient source, and although stiff biofilms migrate toward an upstream nutrient source, soft biofilms do not. Simulations without nutrients show that on the time scale of several hours, soft biofilms develop irregular structures at the biofilm-fluid interface, but stiff biofilms deform little. Our results agree with the biophysical principle that biofilms can adapt to their mechanical and chemical environment by modulating their viscoelastic properties. We also compare the behavior of a purely elastic biofilm to a viscoelastic biofilm with the same elastic modulus of 50 Pa. We find that the elastic biofilm underestimates growth rates and downstream migration rates if the nutrient source is downstream, and it overestimates growth rates and upstream migration rates if the nutrient source is upstream. Future modeling can use our comparison to identify errors that can occur by simulating biofilms as purely elastic structures.

Four species of bacteria deterministically assemble to form a stable biofilm in a millifluidic channel

Multispecies microbial adherent communities are widespread in nature and organisms, although the principles of their assembly and development remain unclear. Here, we test the possibility of establishing a simplified but relevant model of multispecies biofilm in a non-invasive laboratory setup for the real-time monitoring of community development. We demonstrate that the four chosen species (Bacillus thuringiensis, Pseudomonas fluorescens, Kocuria varians, and Rhodocyclus sp.) form a dynamic community that deterministically reaches its equilibrium after ~30 h of growth. We reveal the emergence of complexity in this simplified community as reported by an increase in spatial heterogeneity and non-monotonic developmental kinetics. Importantly, we find interspecies interactions consisting of competition for resources-particularly oxygen-and both direct and indirect physical interactions. The simplified experimental model opens new avenues to the study of adherent bacterial communities and their behavior in the context of rapid global change.

Lattice Boltzmann Method in Modeling Biofilm Formation, Growth and Detachment

Biofilms are a complex and heterogeneous aggregation of multiple populations of microorganisms linked together by their excretion of extracellular polymer substances (EPS). Biofilms can cause many serious problems, such as chronic infections, food contamination and equipment corrosion, although they can be useful for constructive purposes, such as in wastewater treatment, heavy metal removal from hazardous waste sites, biofuel production, power generation through microbial fuel cells and microbially enhanced oil recovery; however, biofilm formation and growth are complex due to interactions among physicochemical and biological processes under operational and environmental conditions. Advanced numerical modeling techniques using the lattice Boltzmann method (LBM) are enabling the prediction of biofilm formation and growth and microbial community structures. This study is the first attempt to perform a general review on major contributions to LBM-based biofilm models, ranging from pioneering efforts to more recent progress. We present our understanding of the modeling of biofilm formation, growth and detachment using LBM-based models and present the fundamental aspects of various LBM-based biofilm models. We describe how the LBM couples with cellular automata (CA) and individual-based model (IbM) approaches and discuss their applications in assessing the spatiotemporal distribution of biofilms and their associated parameters and evaluating bioconversion efficiency. Finally, we discuss the main features and drawbacks of LBM-based biofilm models from ecological and biotechnological perspectives and identify current knowledge gaps and future research priorities.

Pan-Genome Analysis of Vibrio cholerae and Vibrio metschnikovii Strains Isolated From Migratory Birds at Dali Nouer Lake in Chifeng, China

Migratory birds are recently recognized as Vibrio disease vectors, but may be widespread transporters of Vibrio strains. We isolated Vibrio cholerae (V. cholerae) and Vibrio metschnikovii (V. metschnikovii) strains from migratory bird epidemic samples from 2017 to 2018 and isolated V. metschnikovii from migratory bird feces in 2019 from bird samples taken from the Inner Mongolia autonomous region of China. To investigate the evolution of these two Vibrio species, we sequenced the genomes of 40 V. cholerae strains and 34 V. metschnikovii strains isolated from the bird samples and compared these genomes with reference strain genomes. The pan-genome of all V. cholerae and V. metschnikovii genomes was large, with strains exhibiting considerable individual differences. A total of 2,130 and 1,352 core genes were identified in the V. cholerae and V. metschnikovii genomes, respectively, while dispensable genes accounted for 16,180 and 9,178 of all genes for the two strains, respectively. All V. cholerae strains isolated from the migratory birds that encoded T6SS and hlyA were non-O1/O139 serotypes without the ability to produce CTX. These strains also lacked the ability to produce the TCP fimbriae nor the extracellular matrix protein RbmA and could not metabolize trimetlylamine oxide (TMAO). Thus, these characteristics render them unlikely to be pandemic-inducing strains. However, a V. metschnikovii isolate encoding the complete T6SS system was isolated for the first time. These data provide new molecular insights into the diversity of V. cholerae and V. metschnikovii isolates recovered from migratory birds.

Modeling of Symbiotic Bacterial Biofilm Growth with an Example of the Streptococcus-Veillonella sp. System

We present a multi-dimensional continuum mathematical model for modeling the growth of a symbiotic biofilm system. We take a dual-species namely, the Streptococcus-Veillonella sp. biofilm system as an example for numerical investigations. The presented model describes both the cooperation and competition between these species of bacteria. The coupled partial differential equations are solved by using an integrative finite element numerical strategy. Numerical examples are carried out for studying the evolution and distribution of the bio-components. The results demonstrate that the presented model is capable of describing the symbiotic behavior of the biofilm system. However, homogenized numerical solutions are observed locally. To study the homogenization behavior of the model, numerical investigations regarding on how random initial biomass distribution influences the homogenization process are carried out. We found that a smaller correlation length of the initial biomass distribution leads to faster homogenization of the solution globally, however, shows more fluctuated biomass profiles along the biofilm thickness direction. More realistic scenarios with bacteria in patches are also investigated numerically in this study.

Surrogate based Global Sensitivity Analysis of ADM1-based Anaerobic Digestion Model

In order to calibrate the model parameters, Sensitivity Analysis routines are mandatory to rank the parameters by their relevance and fix to nominal values the least influential factors. Despite the high number of works based on ADM1, very few are related to sensitivity analysis. In this study Global Sensitivity Analysis (GSA) and Uncertainty Quantification (UQ) for an ADM1-based Anaerobic Digestion Model have been performed. The modified version of ADM-based model selected in this study was presented by Esposito and co-authors in 2013. Unlike the first version of ADM1, focused on sewage sludge degradation, the model of Esposito is focused on organic fraction of municipal solid waste digestion. It his recalled that in many applications the hydrolysis is considered the bottleneck of the overall anaerobic digestion process when the input substrate is constituted of complex organic matter. In Esposito's model a surfaced based kinetic approach for the disintegration of complex organic matter is introduced. This approach allows to better model the disintegration step taking into account the effect of particle size distribution on the digestion process. This model needs thus GSA and UQ to pave the way for further improvements and reach a deep understanding of the main processes and leading input factors. Due to the large number of parameters to be analyzed a first preliminary screening analysis, with the Morris' Method, has been conducted. Since two quantities of interest (QoI) have been considered, the initial screening has been performed twice, obtaining two set of parameters containing the most influential factors in determining the value of each QoI. A surrogate of ADM1 model has been defined making use of the two defined quantities of interest. The output results from the surrogate model have been analyzed with Sobol' indices for the quantitative GSA. Finally, uncertainty quantification has been performed. By adopting kernel smoothing techniques, the Probability Density Functions of each quantity of interest have been defined.

Relevance of Biofilm Models in Periodontal Research: From Static to Dynamic Systems

Microbial biofilm modeling has improved in sophistication and scope, although only a limited number of standardized protocols are available. This review presents an example of a biofilm model, along with its evolution and application in studying periodontal and peri-implant diseases. In 2011, the ETEP (Etiology and Therapy of Periodontal and Peri-Implant Diseases) research group at the University Complutense of Madrid developed an in vitro biofilm static model using representative bacteria from the subgingival microbiota, demonstrating a pattern of bacterial colonization and maturation similar to in vivo subgingival biofilms. When the model and its methodology were standardized, the ETEP research group employed the validated in vitro biofilm model for testing in different applications. The evolution of this model is described in this manuscript, from the mere observation of biofilm growth and maturation on static models on hydroxyapatite or titanium discs, to the evaluation of the impact of dental implant surface composition and micro-structure using the dynamic biofilm model. This evolution was based on reproducing the ideal microenvironmental conditions for bacterial growth within a bioreactor and reaching the target surfaces using the fluid dynamics mimicking the salivary flow. The development of this relevant biofilm model has become a powerful tool to study the essential processes that regulate the formation and maturation of these important microbial communities, as well as their behavior when exposed to different antimicrobial compounds.

Non-Invasive Measurement, Mathematical Simulation and In Situ Detection of Biofilm Evolution in Porous Media: A Review

The development of biofilms and the related changes in porous media in the subsurface cannot be directly observed and evaluated. The primary reason that the mechanism of biofilm clogging in porous media cannot be clearly demonstrated is due to the opacity and structural complexity of three-dimensional pore space. Interest in exploring methods to overcome this limitation has been increasing. In the first part of this review, we introduce the underlying characteristics of biofilm in porous media. Then, we summarize two approaches, non-invasive measurement methods and mathematical simulation strategies, for studying fluid–biofilm–porous medium interaction with spatiotemporal resolution. We also discuss the advantages and limitations of these approaches. Lastly, we provide a perspective on opportunities for in situ monitoring at the field site.

A novel computational simulation approach to study biofilm significance in a packed-bed biooxidation reactor

Fe (II) biooxidation has recently gained significant interest. It plays a key role in a number of environmental and industrial processes such as bioleaching, acid mine drainage treatment, desulphurization of sour gases, and coal desulphurization. In this work, a three-dimensional CFD model for gas-liquid flow in a lab-scale packed-bed biooxidation reactor is used. The reactor is randomly packed with spherical particles, and the particles are covered with Leptospirillum ferrooxidans biofilm for Fe (II) biooxidation. A modified Jodrey-Tory algorithm is used to generate random packing with actual porosity of 0.42, and biofilm layer with constant thickness is considered over the particles. A simplified Eulerian-Eulerian model is used to obtain detailed flow field. The concentration profile in the reactor and the conversion of Fe (II) from the present simulations are obtained and validated using experimental data reported in the literature. The results of the study indicate that about three-quarters of the conversion occurs in the upper half of the reactor and Fe (II) concentration on the biofilm surface at the lower quarter of the reactor does not exceed 5 mM (The inlet concentration is 89.6 mM). The findings reveal that rate-limiting phenomena may vary in different parts of the reactor. The results obtained through the simulations represent advantages for the design and optimization of packed-bed biofilm reactors.

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.

Microbial carbon metabolic functions of biofilms on plastic debris influenced by the substrate types and environmental factors

As an artificial type of microbial carrier, plastic debris has been widely detected in freshwater habitats, and the potential impacts of the plastisphere (biofilms colonized on plastics) in aquatic ecosystems have drawn increasing attention. Distinct community compositions and structures of biofilms in plastic and natural substrates have been recorded in freshwater environments. However, the microbial metabolic functioning of the plastisphere was underestimated, especially in freshwater environments. In this study, the effects of substrate types on the carbon metabolic functions of biofilms were studied by in situ cultivation of biofilms on plastics (polyvinyl chloride, PVC and polyethylene, PE) and natural substrate (cobblestone) for 44 days in two rivers (the Niushoushan River and the Qinhuai River) and two lakes (Donghu Lake and Xuanwu Lake). Biofilms on plastics showed higher biomasses than those on natural substrates in all ecosystems. Variations in the micro-structure and compactness of biofilms developed under different substrates were observed from scanning electron microscope and confocal laser scanning microscope image analyses. The carbon metabolic activities of the biofilms evaluated by BIOLOG EcoPlate were different between plastics (PVC and PE) and natural substrate (cobblestone) in the four freshwater ecosystems. In the Niushoushan River, PE-associated biofilms had different capacity in using carbon sources from cobblestone-associated biofilms as illustrated by the Shannon-Wiener diversity index and Shannon evenness index. Additionally, the metabolic functional diversity profiles of biofilms on PVC were significantly different from those on cobblestone in the other three aquatic ecosystems. Moreover, results from variation partitioning analysis suggested that the impact of environmental factors (contribution: 21%) on microbial carbon metabolic functions was much greater than that of substrate types (contribution: 6%). These findings illustrated distinct microbial functions of biofilms inhabited on plastics, and environmental factors play a decisive role in the differentiation and specificity of carbon metabolism of the plastisphere. This study offers new insights that plastics serving as artificial microbial niches have the ability to affect the microbial-mediated carbon cycling process in aquatic ecosystems.

Microbial biofilm ecology, in silico study of quorum sensing receptor-ligand interactions and biofilm mediated bioremediation

Biofilms are structured microbial communities of single or multiple populations in which microbial cells adhere to a surface and get embedded in extracellular polymeric substances (EPS). This review attempts to explain biofilm architecture, development phases, and forces that drive bacteria to promote biofilm mode of growth. Bacterial chemical communication, also known as Quorum sensing (QS), which involves the production, detection, and response to small molecules called autoinducers, is highlighted. The review also provides a brief outline of interspecies and intraspecies cell-cell communication. Additionally, we have performed docking studies using Discovery Studio 4.0, which has enabled our understanding of the prominent interactions between autoinducers and their receptors in different bacterial species while also scoring their interaction energies. Receptors, such as LuxN (Phosphoreceiver domain and RecA domain), LuxP, and LuxR, interacted with their ligands (AI-1, AI-2, and AHL) with a CDocker interaction energy of - 31.6083 kcal/mole; - 34.5821 kcal/mole, - 48.2226 kcal/mole and - 41.5885 kcal/mole, respectively. Since biofilms are ideal for the remediation of contaminants due to their high microbial biomass and their potential to immobilize pollutants, this article also provides an overview of biofilm-mediated bioremediation.

Engineering and modeling of multicellular morphologies and patterns

Synthetic multicellular (MC) systems have the capacity to increase our understanding of biofilms and higher organisms, and to serve as engineering platforms for developing complex products in the areas of medicine, biosynthesis and smart materials. Here we provide an interdisciplinary perspective and review on emerging approaches to engineer and model MC systems. We lay out definitions for key terms in the field and identify toolboxes of standardized parts which can be combined into various MC algorithms to achieve specific outcomes. Many essential parts and algorithms have been demonstrated in some form. As key next milestones for the field, we foresee the improvement of these parts and their adaptation to more biological systems, the demonstration of more complex algorithms, the advancement of quantitative modeling approaches and compilers to support rational MC engineering, and implementation of MC engineering for practical applications.

Investigation of architecture development and phosphate distribution in Chlorella biofilm by complementary microscopy techniques

Microalgae biofilms may play an important role in the mitigation and prevention of eutrophication caused by domestic, agricultural and industrial wastewater effluents. Despite their potential, the biofilm development and role in nutrient removal are not well understood. Its clarification requires comprehensive studies of the complex three-dimensional architecture of the biofilm. In this study, we established a multimodal imaging approach to provide key information regarding architecture development and nutrient distribution in the biofilm of two green algae organisms: Chlorella pyrenoidosa and Chlorella vulgaris. Helium ion microscopy (HIM), scanning electron microscopy coupled with energy dispersive X-ray analysis (SEM-EDX) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) were employed for i) elucidation of spatial arrangement, ii) elemental mapping and iii) 3D chemical imaging of the biofilm. The fine structure of the algal biofilm was resolved by HIM, the evidence of the accumulation of phosphate in hot spots was provided by SEM-EDX and the localization of phosphate oxides granules throughout the whole sample was clarified by ToF-SIMS. The reported results shed light on the phosphorus distribution during Chlorella's biofilm formation and highlight the potential of such correlative approach to solve fundamental question in algal biotechnology research.

Hybrid Model of Bacterial Biofilm Growth

Bacterial biofilms play a critical role in environmental processes, water treatment, human health, and food processing. They exhibit highly complex dynamics due to the interactions between the bacteria and the extracellular polymeric substance (EPS), water, and nutrients and minerals that make up the biofilm. We present a hybrid computational model in which the dynamics of discrete bacterial cells are simulated within a multiphase continuum, consisting of EPS and water as separate interacting phases, through which nutrients and minerals diffuse. Bacterial cells in our model consume water and nutrients in order to grow, divide, and produce EPS. Consequently, EPS flows outward from the bacterial colony, while water flows inward. The model predicts bacterial colony formation as a treelike structure. The distribution of bacterial growth and EPS production is found to be sensitive to the pore spacing between bacteria and the consumption of nutrients within the bacterial colony. Forces that are sometimes neglected in biofilm simulations, such as lubrication force between nearby bacterial cells and osmotic (swelling) pressure force resulting from gradients in EPS concentration, are observed to have an important effect on biofilm growth via their influence on bacteria pore spacing and associated water/nutrient percolation into the bacterial colony.

Computational and Experimental Investigation of Biofilm Disruption Dynamics Induced by High-Velocity Gas Jet Impingement

Knowledge of mechanisms promoting disruption though mechanical forces is essential in optimizing biofilm control strategies which rely on fluid shear. Our results provide insight into how biofilm disruption dynamics is governed by applied forces and fluid properties, revealing a mechanism for ripple formation and fluid-biofilm mixing. These findings have important implications for the rational design of new biofilm cleaning strategies with fluid jets, such as determining optimal parameters (e.g., jet velocity and position) to remove the biofilm from a certain zone (e.g., in dental hygiene or debridement of surgical site infections) or using antimicrobial agents which could increase the interfacial area available for exchange, as well as causing internal mixing within the biofilm matrix, thus disrupting the localized microenvironment which is associated with antimicrobial tolerance. The developed model also has potential application in predicting drag and pressure drop caused by biofilms on bioreactor, pipeline, and ship hull surfaces.

Experimental data showed that high-speed microsprays can effectively disrupt biofilms on their support substratum, producing a variety of dynamic reactions such as elongation, displacement, ripple formation, and fluidization. However, the mechanics underlying the impact of high-speed turbulent flows on biofilm structure is complex under such extreme conditions, since direct measurements of viscosity at these high shear rates are not possible using dynamic testing instruments. Here, we used computational fluid dynamics simulations to assess the complex fluid interactions of ripple patterning produced by high-speed turbulent air jets impacting perpendicular to the surface of Streptococcus mutans biofilms, a dental pathogen causing caries, captured by high-speed imaging. The numerical model involved a two-phase flow of air over a non-Newtonian biofilm, whose viscosity as a function of shear rate was estimated using the Herschel-Bulkley model. The simulation suggested that inertial, shear, and interfacial tension forces governed biofilm disruption by the air jet. Additionally, the high shear rates generated by the jet impacts coupled with shear-thinning biofilm property resulted in rapid liquefaction (within milliseconds) of the biofilm, followed by surface instability and traveling waves from the impact site. Our findings suggest that rapid shear thinning under very high shear flows causes the biofilm to behave like a fluid and elasticity can be neglected. A parametric sensitivity study confirmed that both applied force intensity (i.e., high jet nozzle air velocity) and biofilm properties (i.e., low viscosity and low air-biofilm surface tension and thickness) intensify biofilm disruption by generating large interfacial instabilities.

A thin-film extensional flow model for biofilm expansion by sliding motility

In the presence of glycoproteins, bacterial and yeast biofilms are hypothesized to expand by sliding motility. This involves a sheet of cells spreading as a unit, facilitated by cell proliferation and weak adhesion to the substratum. In this paper, we derive an extensional flow model for biofilm expansion by sliding motility to test this hypothesis. We model the biofilm as a two-phase (living cells and an extracellular matrix) viscous fluid mixture, and model nutrient depletion and uptake from the substratum. Applying the thin-film approximation simplifies the model, and reduces it to one-dimensional axisymmetric form. Comparison with Saccharomyces cerevisiae mat formation experiments reveals good agreement between experimental expansion speed and numerical solutions to the model withO ( 1 ) parameters estimated from experiments. This confirms that sliding motility is a possible mechanism for yeast biofilm expansion. Having established the biological relevance of the model, we then demonstrate how the model parameters affect expansion speed, enabling us to predict biofilm expansion for different experimental conditions. Finally, we show that our model can explain the ridge formation observed in some biofilms. This is especially true if surface tension is low, as hypothesized for sliding motility.

Modeling Heavy Metal Sorption and Interaction in a Multispecies Biofilm

A mathematical model able to simulate the physical, chemical and biological interactions prevailing in multispecies biofilms in the presence of a toxic heavy metal is presented. The free boundary value problem related to biofilm growth and evolution is governed by a nonlinear ordinary differential equation. The problem requires the integration of a system of nonlinear hyperbolic partial differential equations describing the biofilm components evolution, and a systems of semilinear parabolic partial differential equations accounting for substrates diffusion and reaction within the biofilm. In addition, a semilinear parabolic partial differential equation is introduced to describe heavy metal diffusion and sorption. The biosoption process modeling is completed by the definition and integration of other two systems of nonlinear hyperbolic partial differential equations describing the free and occupied binding sites evolution, respectively. Numerical simulations of the heterotrophic-autotrophic interaction occurring in biofilm reactors devoted to wastewater treatment are presented. The high biosorption ability of bacteria living in a mature biofilm is highlighted, as well as the toxicity effect of heavy metals on autotrophic bacteria, whose growth directly affects the nitrification performance of bioreactors.

Repeated-Batch Fermentation of Cheese Whey for Semi-Continuous Lactic Acid Production Using Mixed Cultures at Uncontrolled pH

The paper investigates mixed-culture lactate (LA) fermentation of cheese whey (CW) in order to verify the possibility of using waste materials as feedstock to produce a product with high economic potential. The fermentation performance of two reactors operating in repeated-batch mode under uncontrolled pH conditions and various hydraulic retention time and feeding conditions was evaluated in terms of LA production. Five experimental phases were conducted. The hydraulic retention time (HRT) was varied from 1 to 4 days to verify its effect on the process performance. The best results, corresponding to the maximum LA concentration (20.1 g LA/L) and the maximum LA yield (0.37 g chemical oxygen demand (COD)(LA)/g COD(CW)), were reached by feeding the reactors with cheese whey alone and setting the HRT to 2 days. The maximum productivity of lactic acid (10.6 g LA/L/day) was observed when the HRT was decreased to 1 day.