Extracellular polymeric substances induced cell-surface interactions facilitate bacteria transport in saturated porous media

Advancing Anti-Biofilm Strategies: Innovations to Combat Biofilm-Related Challenges and Enhance Efficacy

Biofilms are complex communities of microorganisms that can cause significant challenges in various settings, including industrial processes, environmental systems, and human health. The protective nature of biofilms makes them resistant to traditional anti-biofilm strategies, such as chemical agents, mechanical interventions, and surface modifications. To address the limitations of conventional anti-biofilm methods, researchers have explored emerging strategies that encompass the use of natural compounds, nanotechnology-based methods, quorum-sensing inhibition, enzymatic degradation, and antimicrobial photodynamic/sonodynamic therapy. There is an increasing focus on combining multiple anti-biofilm strategies to combat resistance and enhance effectiveness. Researchers are continuously investigating the mechanisms of biofilm formation and developing innovative approaches to overcome the limitations of conventional anti-biofilm methods. These efforts aim to improve the management of biofilms and prevent infections while preserving the environment. This study provides a comprehensive overview of the latest advancements in anti-biofilm strategies. Given the dynamic nature of this field, exploring new approaches is essential to stimulate further research and development initiatives. The effective management of biofilms is crucial for maintaining the health of industrial processes, environmental systems, and human populations.

Bacterial accumulation dynamics in runoff from extreme precipitation

Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 104.5-6.3, 104.5-6.1, 104.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 104.0-6.0, 103.9-5.8, 103.2-4.9 CFU/mL, and viable bacteria = 106.4-8.0, 107.0-8.9, 106.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 109.38-11.31 CFU/m2 and 1011.84-13.25 cells/m2, respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change.

Bacterial surface properties and transport behavior actively respond to an extracellular polymeric substance gradient in saturated porous media

The transport and retention of bacteria in porous media, such as aquifer, are governed by the solid-liquid interface characteristics and bacterial mobility. The secretion of extracellular polymeric substance (EPS) by bacteria modifies their surface property, and thereby has effects on their adhesion to surface. The role of EPS in bacterial mobility within saturated quartz sand media is uncertain, as both promoting and inhibitory effects have been reported, and underlying mechanisms remain unclear. In this study, the effects of EPS on bacterial transport behavior and possible underlying mechanism were investigated at 4 concentrations (0 mg L-1, 50 mg L-1, 200 mg L-1 and 1000 mg L-1) using laboratory simulation experiments in conjunction with Extend Derjaguin-Landau-Verweu-Overbeek (XDLVO) modeling. The results showed that EPS facilitated bacterial mobility at all tested concentrations. It could be partially explained by the increased energy barrier between bacterial cells and quartz sand surface in the presence of EPS. The XDLVO sphere-plate model predicted that EPS induced a higher electrostatic double layer (EDL) repulsive force, Lewis acid-base (AB) and steric stabilization (ST), as well as a lower Lifshitz-van der Waals (LW) attractive force. However, at the highest EPS concentration (1000 mg L-1), the promotion of EPS on bacterial mobility weakened as a result of lower repulsive interactions between cells, which was supported by observed enhanced bacterial aggregation. Consequently, the increased aggregation led to greater bio-colloidal straining and ripening in the sand column, weakening the positive impact of EPS on bacterial transport. These findings suggested that EPS exhibited concentration-dependent effects on bacterial surface properties and transport behavior and revealed non-intuitive dual effects of EPS on those processes.

Micro-interfacial behavior of antibiotic-resistant bacteria and antibiotic resistance genes in the soil environment: A review

Overutilization and misuse of antibiotics in recent decades markedly intensified the rapid proliferation and diffusion of antibiotic resistance genes (ARGs) within the environment, thereby elevating ARGs to the status of a global public health crisis. Recognizing that soil acts as a critical reservoir for ARGs, environmental researchers have made great progress in exploring the sources, distribution, and spread of ARGs in soil. However, the microscopic state and micro-interfacial behavior of ARGs in soil remains inadequately understood. In this study, we reviewed the micro-interfacial behaviors of antibiotic-resistant bacteria (ARB) in soil and porous media, predominantly including migration-deposition, adsorption, and biofilm formation. Meanwhile, adsorption, proliferation, and degradation were identified as the primary micro-interfacial behaviors of ARGs in the soil, with component of soil serving as significant determinant. Our work contributes to the further comprehension of the microstates and processes of ARB and ARGs in the soil environments and offers a theoretical foundation for managing and mitigating the risks associated with ARG contamination.

Starvation Process Would Induce Different Bacterial Mobilities and Attachment Performances in Porous Media without and with Nutrients on Surfaces

The influence and mechanisms of starvation on the bacterial mobile performance in porous media with different nutrition conditions are not well understood. The present study systematically investigated the impacts of starvation on the mobility and attachment of both Gram-negative and Gram-positive strains in porous media without and with nutrients on surfaces in both simulated and real water samples. We found that regardless of strain types and water chemistries, starvation would greatly inhibit bacterial attachment onto bare porous media without nutrients yet could significantly enhance cell attachment onto porous media with nutrients on their surfaces. The mechanisms driving the opposite transport behaviors induced by starvation in porous media without and with nutrients were totally different. We found that the starvation process decreased cell motility and increased repulsive force between bacteria and porous media via decreasing cell sizes and zeta potentials, reducing EPS secretion and cell hydrophobicity, thus increasing transport/inhibiting attachment of bacteria in porous media without nutrients on sand surfaces. In contrast, through strengthening the positive chemotactic response of bacteria to nutrients, the starvation process greatly enhanced bacterial attachment onto porous media with nutrients on sand surfaces. Clearly, via modification of the nutrient conditions in porous media, the mobility/attachment performance of bacteria could be regulated.

Microalgal extracellular polymeric substances (EPS) and their roles in cultivation, biomass harvesting, and bioproducts extraction

Microalgae extracellular polymeric substances (EPS) are complex high-molecular-weight polymers and the physicochemical properties of EPS strongly affect the core features of microalgae cultivation and resource utilization. Revealing the key roles of EPS in microalgae life-cycle processes in an interesting and novelty topic to achieve energy-efficient practical application of microalgae. This review found that EPS showed positive effect in non-gas uptake, extracellular electron transfer, toxicity resistance and heterotrophic symbiosis, but negative impact in gas transfer and light utilization during microalgae cultivation. For biomass harvesting, EPS favored biomass flocculation and large-size cell self-flocculation, but unfavored small size microalgae self-flocculation, membrane filtration, charge neutralization and biomass dewatering. During bioproducts extraction, EPS exhibited positive impact in extractant uptake, but the opposite effect in cellular membrane permeability and cell rupture. Future research on microalgal EPS were also identified, which offer suggestions for comprehensive understanding of microalgal EPS roles in various scenarios.

A review of chemical signaling pathways in the quorum sensing circuit of Pseudomonas aeruginosa

Pseudomonas aeruginosa, an increasingly common competitive and biofilm organism in healthcare infection with sophisticated, interlinked and hierarchic quorum systems (Las, Rhl, PQS, and IQS), creates the greatest threats to the medical industry and has rendered prevailing chemotherapy medications ineffective. The rise of multidrug resistance has evolved into a concerning and potentially fatal occurrence for human life. P. aeruginosa biofilm development is assisted by exopolysaccharides, extracellular DNA, proteins, macromolecules, cellular signaling and interaction. Quorum sensing is a communication process between cells that involves autonomous inducers and regulators. Quorum-induced infectious agent biofilms and the synthesis of virulence factors have increased disease transmission, medication resistance, infection episodes, hospitalizations and mortality. Hence, quorum sensing may be a potential therapeutical target for bacterial illness, and developing quorum inhibitors as an anti-virulent tool could be a promising treatment strategy for existing antibiotics. Quorum quenching is a prevalent technique for treating infections caused by microbes because it diminishes microbial pathogenesis and increases microbe biofilm sensitivity to antibiotics, making it a potential candidate for drug development. This paper examines P. aeruginosa quorum sensing, the hierarchy of quorum sensing mechanism, quorum sensing inhibition and quorum sensing inhibitory agents as a drug development strategy to supplement traditional antibiotic strategies.

Assessment of kinetic and statistical models for predicting breakthrough curves of bio-colloid transport through saturated porous media

The microbial contamination of groundwater and its prevention is a widespread concern in developing countries. The present study simulated the transportation and interception of bio-colloid, Escherichia coli in porous media experimentally using packed columns to address certain aspects of underexplored sorption potential and validated using several kinetic models. The breakthrough curves obtained through experiments are observed to be in good agreement with its prediction using kinetic models namely Thomas, Yoon-Nelson and Modified Dose-Response. The overall comparisons of R2 among all the three models suggest that the MDR model fits more perfectly to experimental results. The combined effect of independent factors (column depth, particle size and alumina content) on response factors (maximum relative concentration and time required to achieve peak concentration) was investigated by using Box-Behnken Design under Response Surface Methodology (RSM) to check statistical significancy of independent factors. The R2 values for both response factors are observed to be 0.94 and 0.99, indicating a very high correlation between predicted and actual values. The results obtained in the present study also confirms that the travel distance and particle size are the statistically significant parameters that efficiently impact on sorption of Escherichia coli during their transport whereas the alumina content also affects the sorption but is observed to be a statistically non-significant.

Predicting bacterial transport through saturated porous media using an automated machine learning model

Escherichia coli, as an indicator of fecal contamination, can move from manure-amended soil to groundwater under rainfall or irrigation events. Predicting its vertical transport in the subsurface is essential for the development of engineering solutions to reduce the risk of microbiological contamination. In this study, we collected 377 datasets from 61 published papers addressing E. coli transport through saturated porous media and trained six types of machine learning algorithms to predict bacterial transport. Eight variables, including bacterial concentration, porous medium type, median grain size, ionic strength, pore water velocity, column length, saturated hydraulic conductivity, and organic matter content were used as input variables while the first-order attachment coefficient and spatial removal rate were set as target variables. The eight input variables have low correlations with the target variables, namely, they cannot predict target variables independently. However, using the predictive models, input variables can effectively predict the target variables. For scenarios with higher bacterial retention, such as smaller median grain size, the predictive models showed better performance. Among six types of machine learning algorithms, Gradient Boosting Machine and Extreme Gradient Boosting outperformed other algorithms. In most predictive models, pore water velocity, ionic strength, median grain size, and column length showed higher importance than other input variables. This study provided a valuable tool to evaluate the transport risk of E.coli in the subsurface under saturated water flow conditions. It also proved the feasibility of data-driven methods that could be used for predicting other contaminants' transport in the environment.