Simulation-Based Exploration of Quorum Sensing Triggered Resistance of Biofilms to Antibiotics

The emerging challenge of Enterococcus faecalis endocarditis after transcatheter aortic valve implantation: time for innovative treatment approaches

SUMMARYInfective endocarditis (IE) is a life-threatening infection that has nearly doubled in prevalence over the last two decades due to the increase in implantable cardiac devices. Transcatheter aortic valve implantation (TAVI) is currently one of the most common cardiac procedures. TAVI usage continues to exponentially rise, inevitability increasing TAVI-IE. Patients with TAVI are frequently nonsurgical candidates, and TAVI-IE 1-year mortality rates can be as high as 74% without valve or bacterial biofilm removal. Enterococcus faecalis, a historically less common IE pathogen, is the primary cause of TAVI-IE. Treatment options are limited due to enterococcal intrinsic resistance and biofilm formation. Novel approaches are warranted to tackle current therapeutic gaps. We describe the existing challenges in treating TAVI-IE and how available treatment discovery approaches can be combined with an in silico "Living Heart" model to create solutions for the future.

Combatting biofilm-mediated infections in clinical settings by targeting quorum sensing

Biofilm-associated infections constitute a significant challenge in managing infectious diseases due to their high resistance to antibiotics and host immune responses. Biofilms are responsible for various infections, including urinary tract infections, cystic fibrosis, dental plaque, bone infections, and chronic wounds. Quorum sensing (QS) is a process of cell-to-cell communication that bacteria use to coordinate gene expression in response to cell density, which is crucial for biofilm formation and maintenance.. Its disruption has been proposed as a potential strategy to prevent or treat biofilm-associated infections leading to improved treatment outcomes for infectious diseases. This review article aims to provide a comprehensive overview of the literature on QS-mediated disruption of biofilms for treating infectious diseases. It will discuss the mechanisms of QS disruption and the various approaches that have been developed to disrupt QS in reference to multiple clinical pathogens. In particular, numerous studies have demonstrated the efficacy of QS disruption in reducing biofilm formation in various pathogens, including Pseudomonas aeruginosa and Staphylococcus aureus. Finally, the review will discuss the challenges and future directions for developing QS disruption as a clinical therapy for biofilm-associated infections. This includes the development of effective delivery systems and the identification of suitable targets for QS disruption. Overall, the literature suggests that QS disruption is a promising alternative to traditional antibiotic treatment for biofilm-associated infections and warrants further investigation.

Exploring Aeration Strategies for Enhanced Simultaneous Nitrification and Denitrification in Membrane Aerated Bioreactors: A Computational Approach

In this study we employ computational methods to investigate the influence of aeration strategies on simultaneous nitrification-denitrification processes. Specifically, we explore the impact of periodic and intermittent aeration on denitrification rates, which typically lag behind nitrification rates under identical environmental conditions. A two-dimensional deterministic multi-scale model is employed to elucidate the fundamental processes governing the behavior of membrane aerated biofilm reactors (MABRs). We aim to identify key factors that promote denitrification under varying aeration strategies. Our findings indicate that the concentration of oxygen during the off phase and the duration of the off interval play crucial roles in controlling denitrification. Complete discontinuation of oxygen is not advisable, as it inhibits the formation of anaerobic heterotrophic bacteria, thereby impeding denitrification. Extending the length of the off interval, however, enhances denitrification. Furthermore, we demonstrate that the initial inoculation of the substratum (membrane in this study) influences substrate degradation under periodic aeration, with implications for both nitrification and denitrification. Comparison between continuous and periodic/intermittent aeration scenarios reveals that the latter can extend the operational cycle of MABRs. This extension is attributed to relatively low biofilm growth rates associated with non-continuous aeration strategies. Consequently, our study provides a comprehensive understanding of the intricate interplay between aeration strategies and simultaneous nitrification-denitrification in MABRs. The insights presented herein can contribute significantly to the optimization of MABR performance in wastewater treatment applications.

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.

Complete genome analysis reveals environmental adaptability of sulfur-oxidizing bacterium Thioclava nitratireducens M1-LQ-LJL-11 and symbiotic relationship with deep-sea hydrothermal vent Chrysomallon squamiferum

One sulfur-oxidizing bacterium Thioclava sp. M1-LQ-LJL-11 was isolated from the gill of Chrysomallon squamiferum collected from 2700 m deep hydrothermal named Longqi on the southwest Indian Ocean ridge. In order to understand its survival mechanism in hydrothermal extreme environment and symbiotic relationship with its host, the complete genome of strain M1-LQ-LJL-11 was sequenced and analyzed. A total of 6117 Mb of valid data was obtained, including 4096 coding genes, 61 non coding genes, including 9 rRNAs (among them, there are 3 in 23S rRNA, 3 in 5S rRNA, and 3 in 16S rRNA.), 52 tRNAs and 35 genomic islands. Strain M1-LQ-LJL-11 contains one chromosome and two plasmids. In the genome annotation information of the strain, we found 28 genes including cys sox, sor, sqr, tst related to sulfur metabolism and 17 metal resistance genes. Interestingly, a pair of quorum sensing system which probably regulating biofilm formation located in chromosome was found. These genes are critical for self-adaptation against severe environment as well as host survival. This study provides a basis understanding for the adaptive strategies of deep-sea hydrothermal bacteria and symbiotic relationship with its host in extreme environments through gene level.

Multidrug-Resistant Biofilms (MDR): Main Mechanisms of Tolerance and Resistance in the Food Supply Chain

Biofilms are mono- or multispecies microbial communities enclosed in an extracellular matrix (EPS). They have high potential for dissemination and are difficult to remove. In addition, biofilms formed by multidrug-resistant strains (MDRs) are even more aggravated if we consider antimicrobial resistance (AMR) as an important public health issue. Quorum sensing (QS) and horizontal gene transfer (HGT) are mechanisms that significantly contribute to the recalcitrance (resistance and tolerance) of biofilms, making them more robust and resistant to conventional sanitation methods. These mechanisms coordinate different strategies involved in AMR, such as activation of a quiescent state of the cells, moderate increase in the expression of the efflux pump, decrease in the membrane potential, antimicrobial inactivation, and modification of the antimicrobial target and the architecture of the EPS matrix itself. There are few studies investigating the impact of the use of inhibitors on the mechanisms of recalcitrance and its impact on the microbiome. Therefore, more studies to elucidate the effect and applications of these methods in the food production chain and the possible combination with antimicrobials to establish new strategies to control MDR biofilms are needed.

Crumbling the Castle: Targeting DNABII Proteins for Collapsing Bacterial Biofilms as a Therapeutic Approach to Treat Disease and Combat Antimicrobial Resistance

Antimicrobial resistance (AMR) is a concerning global threat that, if not addressed, could lead to increases in morbidity and mortality, coupled with societal and financial burdens. The emergence of AMR bacteria can be attributed, in part, to the decreased development of new antibiotics, increased misuse and overuse of existing antibiotics, and inadequate treatment options for biofilms formed during bacterial infections. Biofilms are complex microbiomes enshrouded in a self-produced extracellular polymeric substance (EPS) that is a primary defense mechanism of the resident microorganisms against antimicrobial agents and the host immune system. In addition to the physical protective EPS barrier, biofilm-resident bacteria exhibit tolerance mechanisms enabling persistence and the establishment of recurrent infections. As current antibiotics and therapeutics are becoming less effective in combating AMR, new innovative technologies are needed to address the growing AMR threat. This perspective article highlights such a product, CMTX-101, a humanized monoclonal antibody that targets a universal component of bacterial biofilms, leading to pathogen-agnostic rapid biofilm collapse and engaging three modes of action-the sensitization of bacteria to antibiotics, host immune enablement, and the suppression of site-specific tissue inflammation. CMTX-101 is a new tool used to enhance the effectiveness of existing, relatively inexpensive first-line antibiotics to fight infections while promoting antimicrobial stewardship.

Regulatory Effect of Irresistin-16 on Competitive Dual-Species Biofilms Composed of Streptococcus mutans and Streptococcus sanguinis

Based on the ecological plaque hypothesis, suppressing opportunistic pathogens within biofilms, rather than killing microbes indiscriminately, could be a biofilm control strategy for managing dental caries. The present study aimed to evaluate the effects of irresistin-16 (IRS-16) on competitive dual-species biofilms, which consisted of the conditional cariogenic agent Streptococcus mutans (S. mutans) and oral commensal bacteria Streptococcus sanguinis (S. sanguinis). Bacterial growth and biofilm formation were monitored using growth curve and crystal violet staining, respectively. The microbial proportion was determined using fluorescence in situ hybridization. A 2, 5-diphenyltetrazolium bromide assay was used to measure the metabolic activity of biofilms. Bacterial/extracellular polysaccharide (EPS) dyeing, together with water-insoluble EPS measurements, were used to estimate EPS synthesis. A lactic acid assay was performed to detect lactic acid generation in biofilms. The cytotoxicity of IRS-16 was evaluated in mouse fibroblast L929 cells using a live/dead cell viability assay and cell counting kit-8 assay. Our results showed that IRS-16 exhibited selective anti-biofilm activity, leading to a remarkable survival disadvantage of S. mutans within competitive dual-species biofilms. In addition, the metabolic activity, EPS synthesis, and acid generation of dual-species biofilms were significantly reduced by IRS-16. Moreover, IRS-16 showed minimal cytotoxicity against mouse fibroblast L929 cells. In conclusion, IRS-16 exhibited remarkable regulatory effects on dual-species biofilms composed of S. mutans and S. sanguinis with low cytotoxicity, suggesting that it may have potential for use in caries management through ecological biofilm control.

The role of antibiotics and heavy metals on the development, promotion, and dissemination of antimicrobial resistance in drinking water biofilms

Antimicrobial resistance (AMR), as well as the development of biofilms in drinking water distribution systems (DWDSs), have become an increasing concern for public health and management. As bulk water travels from source to tap, it may accumulate contaminants of emerging concern (CECs) such as antibiotics and heavy metals. When these CECs and other selective pressures, such as disinfection, pipe material, temperature, pH, and nutrient availability interact with planktonic cells and, consequently, DWDS biofilms, AMR is promoted. The purpose of this review is to highlight the mechanisms by which AMR develops and is disseminated within DWDS biofilms. First, this review will lay a foundation by describing how DWDS biofilms form, as well as their basic intrinsic and acquired resistance mechanisms. Next, the selective pressures that further induce AMR in DWDS biofilms will be elaborated. Then, the pressures by which antibiotic and heavy metal CECs accumulate in DWDS biofilms, their individual resistance mechanisms, and co-selection are described and discussed. Finally, the known human health risks and current management strategies to mitigate AMR in DWDSs will be presented. Overall, this review provides critical connections between several biotic and abiotic factors that influence and induce AMR in DWDS biofilms. Implications are made regarding the importance of monitoring and managing the development, promotion, and dissemination of AMR in DWDS biofilms.

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.

A computational study of combination HIFU-chemotherapy as a potential means of overcoming cancer drug resistance

The application of local hyperthermia, particularly in conjunction with other treatment strategies (like chemotherapy and radiotherapy) has been known to be a useful means of enhancing tumor treatment outcomes. However, to our knowledge, there has been no mathematical model designed to capture the impact of the combination of hyperthermia and chemotherapies on tumor growth and control. In this study, we propose a nonlinear Partial Differential Equation (PDE) model which describes the tumor response to chemotherapy, and use the model to study the effects of hyperthermia on the response of prototypical tumor to the generic chemotherapeutic agent. Ultrasound energy is delivered to the tumor through High Intensity Focused Ultrasound (HIFU), as a noninvasive technique to elevate the tumor temperature in a controlled manner. The proposed tumor growth model is coupled with the nonlinear density dependent Westervelt and Penne's bio-heat equations, used to calculate the net delivered energy and temperature of the tumor and its surrounding normal tissue. The tumor is assumed to be composed of two species: drug-sensitive and drug-resistant. The central assumption underlying our model is that the drug-resistant species is converted to a drug-sensitive type when the tumor temperature is elevated above a certain threshold temperature. The "in silico" results obtained, confirm that hyperthermia can result in less aggressive tumor development and emphasize the importance of designing an optimized thermal dose strategy. Furthermore, our results suggest that increasing the length of the on/off cycle of the transducer is an efficient approach to treatment scheduling in the sense of optimizing tumor eradication.

A study of nitric oxide dynamics in a growing biofilm using a density dependent reaction-diffusion model

One of a number of critical roles played by NO· as a chemical weapon (generated by the immune system) is to neutralize pathogens. However, the virulence of pathogens depends on the production activity of reductants to detoxify NO·. Broad reactivity of NO· makes it complicated to predict the fate of NO· inside bacteria and its effects on the treatment of any infection. Here, we present a mathematical model of biofilm response to NO·, as a stressor. The model is comprised of a PDE system of highly nonlinear reaction-diffusion equations that we study in computer simulations to determine the positive and negative effects of key parameters on bacterial defenses against NO·. From the reported results, we conjecture that the oscillatory behavior of NO· under a microaerobic regime is a temporal phenomenon and does not give rise to a spatial pattern. It is also shown computationally that decreasing the initial size of the biofilm colony negatively impacts the functionality of reducing agents that deactivate NO·. Whereas nutrient deprivation results in the development of biofilms with heterogeneous structure, its effect on the activity of NO· reductants depends on the oxygen availability, biofilm size, and the amount of NO·.

Simulation Based Exploration of Bacterial Cross Talk Between Spatially Separated Colonies in a Multispecies Biofilm Community

We present a simple mesoscopic model for bacterial cross-talk between growing biofilm colonies. The simulation setup mimics a novel microfludic biofilm growth reactor which allows a 2D description. The model is a stiff quasilinear system of diffusion-reaction equations with simultaneously a super-diffusion singularity and a degeneracy (as in the porous medium equation) that leads to the formation of sharp interfaces with finite speed of propagation and gradient blow up. We use a finite volume method with arithmetic flux averaging, and a time adaptive stiff time integrator. We find that signal and nutrient transport between colonies can greatly control and limit biofilm response to induction signals, leading to spatially heterogeneous biofilm behavior.

Bayesian inversion for a biofilm model including quorum sensing

We propose a mathematical model based on a system of partial differential equations (PDEs) for biofilms. This model describes the time evolution of growth and degradation of biofilms which depend on environmental factors. The proposed model also includes quorum sensing (QS) and describes the cooperation among bacteria when they need to resist against external factors such as antibiotics. The applications include biofilms on teeth and medical implants, in drinking water, cooling water towers, food processing, oil recovery, paper manufacturing, and on ship hulls. We state existence and uniqueness of solutions of the proposed model and implement the mathematical model to discuss numerical simulations of biofilm growth and cooperation. We also determine the unknown parameters of the presented biofilm model by solving the corresponding inverse problem. To this end, we propose Bayesian inversion techniques and the delayed-rejection adaptive-Metropolis (DRAM) algorithm for the simultaneous extraction of multiple parameters from the measurements. These quantities cannot be determined directly from the experiments or from the computational model. Furthermore, we evaluate the presented model by comparing the simulations using the estimated parameter values with the measurement data. The results illustrate a very good agreement between the simulations and the measurements.